consider_distance_to_river.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [],
   "source": [
    "%load_ext watermark\n",
    "import datetime as dt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "\n",
    "\n",
    "import IPython\n",
    "from PIL import Image as PILImage\n",
    "from IPython.display import Markdown as md\n",
    "from IPython.display import display\n",
    "from myst_nb import glue\n",
    "\n",
    "# code descriptions\n",
    "dfCodes = pd.read_csv(\"resources/codes_with_group_names_2015.csv\")\n",
    "\n",
    "# set the index of to codes\n",
    "dfCodes.set_index(\"code\", inplace=True)\n",
    "\n",
    "# code description map\n",
    "code_d_map = dfCodes.description\n",
    "\n",
    "# code material map\n",
    "code_m_map = dfCodes.material\n",
    "\n",
    "pdtype = pd.core.frame.DataFrame\n",
    "pstype = pd.core.series.Series\n",
    "\n",
    "def scaleTheColumn(x):\n",
    "    \n",
    "    xmin = x.min()\n",
    "    xmax = x.max()\n",
    "    xscaled = (x-xmin)/(xmax-xmin)\n",
    "    \n",
    "    return xscaled\n",
    "\n",
    "def rotateText(x):\n",
    "    return 'writing-mode: vertical-lr; transform: rotate(-180deg);  padding:10px; margins:0; vertical-align: baseline;'\n",
    "\n",
    "def cleanSurveyResults(data):\n",
    "    # performs data cleaning operations on the\n",
    "    # default data\n",
    "    \n",
    "    data['loc_date'] = list(zip(data.location, data[\"date\"]))\n",
    "    data['date'] = pd.to_datetime(data[\"date\"])\n",
    "    \n",
    "    # get rid of microplastics\n",
    "    mcr = data[data.groupname == \"micro plastics (< 5mm)\"].code.unique()\n",
    "    \n",
    "    # replace the bad code\n",
    "    data.code = data.code.replace('G207', 'G208')\n",
    "    data = data[~data.code.isin(mcr)]\n",
    "    \n",
    "    # walensee has no landuse values\n",
    "    data = data[data.water_name_slug != 'walensee']   \n",
    "    \n",
    "    return data\n",
    "\n",
    "class SurveyResults:\n",
    "    \"\"\"Creates a dataframe from a valid filename. Assigns the column names and defines a list of\n",
    "    codes and locations that can be used in the CodeData class.\n",
    "    \"\"\"\n",
    "    \n",
    "    file_name = 'resources/checked_sdata_eos_2020_21.csv'\n",
    "    columns_to_keep=[\n",
    "        'loc_date',\n",
    "        'location', \n",
    "        'river_bassin',\n",
    "        'water_name_slug',\n",
    "        'city',\n",
    "        'w_t', \n",
    "        'intersects', \n",
    "        'code', \n",
    "        'pcs_m',\n",
    "        'quantity'\n",
    "    ]\n",
    "        \n",
    "    def __init__(self, data: str = file_name, clean_data: bool = True, columns: list = columns_to_keep, w_t: str = None):\n",
    "        self.dfx = pd.read_csv(data)\n",
    "        self.df_results = None\n",
    "        self.locations = None\n",
    "        self.valid_codes = None\n",
    "        self.clean_data = clean_data\n",
    "        self.columns = columns\n",
    "        self.w_t = w_t\n",
    "        \n",
    "    def validCodes(self):\n",
    "        # creates a list of unique code values for the data set    \n",
    "        conditions = [\n",
    "            isinstance(self.df_results, pdtype),\n",
    "            \"code\" in self.df_results.columns\n",
    "        ]\n",
    "\n",
    "        if all(conditions):\n",
    "\n",
    "            try:\n",
    "                valid_codes = self.df_results.code.unique()\n",
    "            except ValueError:\n",
    "                print(\"There was an error retrieving the unique code names, self.df.code.unique() failed.\")\n",
    "                raise\n",
    "            else:\n",
    "                self.valid_codes = valid_codes\n",
    "                \n",
    "        \n",
    "    def surveyResults(self):\n",
    "        \n",
    "        # if this method has been called already\n",
    "        # return the result\n",
    "        if self.df_results is not None:\n",
    "            return self.df_results\n",
    "        \n",
    "        # for the default data self.clean data must be called        \n",
    "        if self.clean_data is True:\n",
    "            fd = cleanSurveyResults(self.dfx)\n",
    "            \n",
    "        # if the data is clean then if can be used directly\n",
    "        else:\n",
    "            fd = self.dfx\n",
    "        \n",
    "        # filter the data by the variable w_t\n",
    "        if self.w_t is not None:\n",
    "            fd = fd[fd.w_t == self.w_t]            \n",
    "         \n",
    "        # keep only the required columns\n",
    "        if self.columns:\n",
    "            fd = fd[self.columns]\n",
    "        \n",
    "        # assign the survey results to the class attribute\n",
    "        self.df_results = fd\n",
    "        \n",
    "        # define the list of codes in this df\n",
    "        self.validCodes()\n",
    "        \n",
    "        return self.df_results\n",
    "    \n",
    "    def surveyLocations(self):\n",
    "        if self.locations is not None:\n",
    "            return self.locations\n",
    "        if self.df_results is not None:\n",
    "            self.locations = self.dfResults.location.unique()\n",
    "            return self.locations\n",
    "        else:\n",
    "            print(\"There is no survey data loaded\")\n",
    "            return None    \n",
    "\n",
    "# this defines the css rules for the note-book table displays\n",
    "header_row = {'selector': 'th:nth-child(1)', 'props': f'background-color: #FFF;'}\n",
    "even_rows = {\"selector\": 'tr:nth-child(even)', 'props': f'background-color: rgba(139, 69, 19, 0.08);'}\n",
    "odd_rows = {'selector': 'tr:nth-child(odd)', 'props': 'background: #FFF;'}\n",
    "table_font = {'selector': 'tr', 'props': 'font-size: 12px;'}\n",
    "table_css_styles = [even_rows, odd_rows, table_font, header_row]\n",
    "\n",
    "# collecting survey data\n",
    "fdx = SurveyResults()\n",
    "df = fdx.surveyResults()\n",
    "\n",
    "# exclude the data from the walensee area\n",
    "# inlcuding river samples\n",
    "location_no_luse = [\n",
    "    \"linth_route9brucke\",\n",
    "    \"seez_spennwiesenbrucke\",\n",
    "    \"limmat_dietikon_keiserp\",\n",
    "    \"seez\"\n",
    "]\n",
    "\n",
    "city_no_luse = [\"Walenstadt\", \"Weesen\", \"Glarus Nord\", \"Quarten\"]\n",
    "\n",
    "df = df[(~df.city.isin(city_no_luse))]\n",
    "df = df[~df.location.isin(location_no_luse)]\n",
    "\n",
    "# use the same criteria from the project results\n",
    "codes = df[df.quantity > 20].code.unique()\n",
    "\n",
    "# the intersect data\n",
    "ind = pd.read_csv('resources/hex-3000m-cleaned/river-intersect-length.csv')\n",
    "\n",
    "# merge the intersection data with the survey data\n",
    "ints_and_data = df.merge(ind, on=\"location\", how=\"outer\")\n",
    "\n",
    "# define the locations of interest\n",
    "locations = df.location.unique()\n",
    "\n",
    "data = ints_and_data[(ints_and_data.code.isin(codes)) & (ints_and_data.location.isin(locations))].copy()\n",
    "\n",
    "# the number of intersects is from old map data\n",
    "# it can be dropped for\n",
    "data.drop(\"intersects\", inplace=True, axis=1)\n",
    "\n",
    "n_c_names = {\n",
    "    \"KLASSE\": 'class',\n",
    "    \"NAMN\": 'name',\n",
    "    \"BREITE\": 'size',\n",
    "    \"water_name_slug\":\"feature\",\n",
    "}\n",
    "data.rename(columns=n_c_names, inplace=True)\n",
    "data.fillna(0, inplace=True)\n",
    "\n",
    "def collectCorrelation(data, codes, columns):\n",
    "    results = []\n",
    "    for code in codes:\n",
    "        d = data[data.code == code]\n",
    "        dx = d.pcs_m.values\n",
    "        for name in columns:\n",
    "            dy = d[name].values            \n",
    "            c, p = stats.spearmanr(dx, dy)\n",
    "            results.append({\"code\":code, \"variable\":name, \"rho\":c, \"p\":p})\n",
    "    return results\n",
    "\n",
    "def resultsDf(rhovals: pdtype = None, pvals: pdtype = None)-> pdtype:\n",
    "    results_df = []\n",
    "    for i, n in enumerate(pvals.index):\n",
    "        arow_of_ps = pvals.iloc[i]\n",
    "        p_fail = arow_of_ps[ arow_of_ps > 0.05]\n",
    "        arow_of_rhos = rhovals.iloc[i]\n",
    "        \n",
    "        for label in p_fail.index:\n",
    "            arow_of_rhos[label] = 0\n",
    "        results_df.append(arow_of_rhos)\n",
    "    \n",
    "    return results_df\n",
    "\n",
    "def styleBufferResults(buffer_results):\n",
    "    buffer_results.columns.name = None\n",
    "    bfr = buffer_results.style.format(precision=2).set_table_styles(table_css_styles)\n",
    "    bfr = bfr.background_gradient(axis=None, vmin=buffer_results.min().min(), vmax=buffer_results.max().max(), cmap=\"coolwarm\")\n",
    "    bfr = bfr.applymap_index(rotateText, axis=1)\n",
    "    \n",
    "    return bfr\n",
    "\n",
    "def countTheNumberOfCorrelationsPerBuffer(pvals: pdtype = None, rhovals: pdtype = None) -> (pdtype, pstype):\n",
    "    \n",
    "    # the number of times p <= 0.05\n",
    "    number_p_less_than = (pvals <= 0.05).sum()\n",
    "    number_p_less_than.name = \"correlated\"\n",
    "    \n",
    "    # the number of postive correlations\n",
    "    number_pos = (rhovals > 0).sum()\n",
    "    number_pos.name = \"positive\"\n",
    "    \n",
    "    # the number of negative correlations\n",
    "    number_neg = (rhovals < 0).sum()\n",
    "    number_neg.name = \"negative\"\n",
    "\n",
    "    ncorrelated = pd.DataFrame([number_p_less_than, number_pos, number_neg])\n",
    "    ncorrelated[\"total\"] = ncorrelated.sum(axis=1)\n",
    "    totals = ncorrelated.total    \n",
    "    \n",
    "    return ncorrelated, totals\n",
    "\n",
    "# this defines the css rules for the note-book table displays\n",
    "header_row = {'selector': 'th:nth-child(1)', 'props': f'background-color: #FFF; text-align:right'}\n",
    "even_rows = {\"selector\": 'tr:nth-child(even)', 'props': f'background-color: rgba(139, 69, 19, 0.08);'}\n",
    "odd_rows = {'selector': 'tr:nth-child(odd)', 'props': 'background: #FFF;'}\n",
    "table_font = {'selector': 'tr', 'props': 'font-size: 12px;'}\n",
    "table_data = {'selector': 'td', 'props': 'padding: 6px;'}\n",
    "table_css_styles = [even_rows, odd_rows, table_font, header_row]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "(distancetoriver)=\n",
    "# Distance, size and class of rivers\n",
    "\n",
    "In the initial report and in the first section the influence of river inputs was quantitied by the number of river intersects within 1500 m of a survey location. With this method 13 possible correlations were identified, 11 positive and two negative. This method does not take into account the distance to the intersection, the length of the river section within the 1500 m buffer nor does it consider the size or class of the river. Here we consider those previously disregarded variables."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "```{figure} resources/images/stream_length_buffer_land_use.jpeg\n",
    "---\n",
    "name: dist_to_int\n",
    "---\n",
    "` `\n",
    "```\n",
    "{numref}`figure %s: <dist_to_int>` Measuring the distance to the intersection and length of the intersection in the buffer. Location: grand-clos, St. Gingolph - Lac Léman."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Extracting the values from the map layer\n",
    "\n",
    "The map layers that are publicly available have changed since the land-use attributes were originally considered for the project national survey. At that time we did not consider the length or distance. The size and the class of each river was not indicated on the previous map layers either. All that has changed:\n",
    "\n",
    "1. There are fewer rivers and streams in the new map layers\n",
    "2. Each river (section) is labled with the size, class, name and designated as man-made or natural.\n",
    "\n",
    "To extract the required data for the analysis for each location and river the following steps were followed:\n",
    "\n",
    "1. Identify locations of interest\n",
    "2. Construct a buffer around each point\n",
    "3. Mark the intersection of the river with the buffer and the lake\n",
    "4. Calculate the length of the river section that traverses the buffer\n",
    "5. Calculate the straight line distance from the survey location to the point where the river leaves the buffer and enters the lake\n",
    "\n",
    "Most locations have more than one intersection. Which means that the survey result for a code is considered under all the possible conditions for each location. The results from St. Gingolph illustrate this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_5d22e tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_5d22e tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_5d22e tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_5d22e th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_5d22e\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_5d22e_level0_col0\" class=\"col_heading level0 col0\" >loc_date</th>\n",
       "      <th id=\"T_5d22e_level0_col1\" class=\"col_heading level0 col1\" >location</th>\n",
       "      <th id=\"T_5d22e_level0_col2\" class=\"col_heading level0 col2\" >river_bassin</th>\n",
       "      <th id=\"T_5d22e_level0_col3\" class=\"col_heading level0 col3\" >feature</th>\n",
       "      <th id=\"T_5d22e_level0_col4\" class=\"col_heading level0 col4\" >city</th>\n",
       "      <th id=\"T_5d22e_level0_col5\" class=\"col_heading level0 col5\" >w_t</th>\n",
       "      <th id=\"T_5d22e_level0_col6\" class=\"col_heading level0 col6\" >code</th>\n",
       "      <th id=\"T_5d22e_level0_col7\" class=\"col_heading level0 col7\" >pcs_m</th>\n",
       "      <th id=\"T_5d22e_level0_col8\" class=\"col_heading level0 col8\" >quantity</th>\n",
       "      <th id=\"T_5d22e_level0_col9\" class=\"col_heading level0 col9\" >name</th>\n",
       "      <th id=\"T_5d22e_level0_col10\" class=\"col_heading level0 col10\" >size</th>\n",
       "      <th id=\"T_5d22e_level0_col11\" class=\"col_heading level0 col11\" >class</th>\n",
       "      <th id=\"T_5d22e_level0_col12\" class=\"col_heading level0 col12\" >distance</th>\n",
       "      <th id=\"T_5d22e_level0_col13\" class=\"col_heading level0 col13\" >length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_5d22e_level0_row0\" class=\"row_heading level0 row0\" >32125</th>\n",
       "      <td id=\"T_5d22e_row0_col0\" class=\"data row0 col0\" >('grand-clos', '2020-05-07')</td>\n",
       "      <td id=\"T_5d22e_row0_col1\" class=\"data row0 col1\" >grand-clos</td>\n",
       "      <td id=\"T_5d22e_row0_col2\" class=\"data row0 col2\" >rhone</td>\n",
       "      <td id=\"T_5d22e_row0_col3\" class=\"data row0 col3\" >lac-leman</td>\n",
       "      <td id=\"T_5d22e_row0_col4\" class=\"data row0 col4\" >Saint-Gingolph</td>\n",
       "      <td id=\"T_5d22e_row0_col5\" class=\"data row0 col5\" >l</td>\n",
       "      <td id=\"T_5d22e_row0_col6\" class=\"data row0 col6\" >Gfrags</td>\n",
       "      <td id=\"T_5d22e_row0_col7\" class=\"data row0 col7\" >2.56</td>\n",
       "      <td id=\"T_5d22e_row0_col8\" class=\"data row0 col8\" >82.00</td>\n",
       "      <td id=\"T_5d22e_row0_col9\" class=\"data row0 col9\" >Canal Stockalper</td>\n",
       "      <td id=\"T_5d22e_row0_col10\" class=\"data row0 col10\" >18.00</td>\n",
       "      <td id=\"T_5d22e_row0_col11\" class=\"data row0 col11\" >8.00</td>\n",
       "      <td id=\"T_5d22e_row0_col12\" class=\"data row0 col12\" >1114.31</td>\n",
       "      <td id=\"T_5d22e_row0_col13\" class=\"data row0 col13\" >498.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5d22e_level0_row1\" class=\"row_heading level0 row1\" >32126</th>\n",
       "      <td id=\"T_5d22e_row1_col0\" class=\"data row1 col0\" >('grand-clos', '2020-05-07')</td>\n",
       "      <td id=\"T_5d22e_row1_col1\" class=\"data row1 col1\" >grand-clos</td>\n",
       "      <td id=\"T_5d22e_row1_col2\" class=\"data row1 col2\" >rhone</td>\n",
       "      <td id=\"T_5d22e_row1_col3\" class=\"data row1 col3\" >lac-leman</td>\n",
       "      <td id=\"T_5d22e_row1_col4\" class=\"data row1 col4\" >Saint-Gingolph</td>\n",
       "      <td id=\"T_5d22e_row1_col5\" class=\"data row1 col5\" >l</td>\n",
       "      <td id=\"T_5d22e_row1_col6\" class=\"data row1 col6\" >Gfrags</td>\n",
       "      <td id=\"T_5d22e_row1_col7\" class=\"data row1 col7\" >2.56</td>\n",
       "      <td id=\"T_5d22e_row1_col8\" class=\"data row1 col8\" >82.00</td>\n",
       "      <td id=\"T_5d22e_row1_col9\" class=\"data row1 col9\" >Le Rhône</td>\n",
       "      <td id=\"T_5d22e_row1_col10\" class=\"data row1 col10\" >1.00</td>\n",
       "      <td id=\"T_5d22e_row1_col11\" class=\"data row1 col11\" >4.00</td>\n",
       "      <td id=\"T_5d22e_row1_col12\" class=\"data row1 col12\" >1372.53</td>\n",
       "      <td id=\"T_5d22e_row1_col13\" class=\"data row1 col13\" >475.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5d22e_level0_row2\" class=\"row_heading level0 row2\" >32127</th>\n",
       "      <td id=\"T_5d22e_row2_col0\" class=\"data row2 col0\" >('grand-clos', '2020-05-07')</td>\n",
       "      <td id=\"T_5d22e_row2_col1\" class=\"data row2 col1\" >grand-clos</td>\n",
       "      <td id=\"T_5d22e_row2_col2\" class=\"data row2 col2\" >rhone</td>\n",
       "      <td id=\"T_5d22e_row2_col3\" class=\"data row2 col3\" >lac-leman</td>\n",
       "      <td id=\"T_5d22e_row2_col4\" class=\"data row2 col4\" >Saint-Gingolph</td>\n",
       "      <td id=\"T_5d22e_row2_col5\" class=\"data row2 col5\" >l</td>\n",
       "      <td id=\"T_5d22e_row2_col6\" class=\"data row2 col6\" >Gfrags</td>\n",
       "      <td id=\"T_5d22e_row2_col7\" class=\"data row2 col7\" >2.56</td>\n",
       "      <td id=\"T_5d22e_row2_col8\" class=\"data row2 col8\" >82.00</td>\n",
       "      <td id=\"T_5d22e_row2_col9\" class=\"data row2 col9\" >Le Tové</td>\n",
       "      <td id=\"T_5d22e_row2_col10\" class=\"data row2 col10\" >10.00</td>\n",
       "      <td id=\"T_5d22e_row2_col11\" class=\"data row2 col11\" >10.00</td>\n",
       "      <td id=\"T_5d22e_row2_col12\" class=\"data row2 col12\" >632.92</td>\n",
       "      <td id=\"T_5d22e_row2_col13\" class=\"data row2 col13\" >1021.84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc034316790>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dxf = data[(data.location == 'grand-clos') & (data.code == \"Gfrags\")&(data.loc_date == (\"grand-clos\", \"2020-05-07\"))].head()\n",
    "\n",
    "dxf.style.format(precision=2).set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    },
    "tags": []
   },
   "source": [
    "## Testing the impacts of river inputs\n",
    "\n",
    "The method of aggregation leaves a few options for testing the impact of river inputs. Recall that there are river and lake side samples, the sampling conditions are not homogenous and the results differ both in magnitude of pcs/m and the variety of objects found, see [IQAASL -lakes and rivers](https://hammerdirt-analyst.github.io/IQAASL-End-0f-Sampling-2021/lakes_rivers.html) and compare the median pcs/m in the national results.\n",
    "\n",
    "1. River and lake samples can be tested togethor\n",
    "2. River and lake samples can be tested separately\n",
    "3. The distance and length parameters can be aggregated\n",
    "   1. average distance to intersection per location\n",
    "   2. total river network length in each buffer per location   \n",
    "\n",
    "### Lake surveys\n",
    "\n",
    "As illustrated above some locations have mulitple intersection within the 1500 m buffer and some have none. Lake locations that have no intersections within the buffer are given a distance of 0 and length of 0. The class and size are both 20, indicating the smallest class and river size possible (example below). The name of the river intersection is given, in the case that there are no intersections within a 1500 m buffer then name=0. Removing the records with name=0 eliminates all lake records with no intersection data. However, for rivers the intersection name = the name of the feature that was sampled."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_6a8b2 tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_6a8b2 tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_6a8b2 tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_6a8b2 th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_6a8b2\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_6a8b2_level0_col0\" class=\"col_heading level0 col0\" >loc_date</th>\n",
       "      <th id=\"T_6a8b2_level0_col1\" class=\"col_heading level0 col1\" >location</th>\n",
       "      <th id=\"T_6a8b2_level0_col2\" class=\"col_heading level0 col2\" >river_bassin</th>\n",
       "      <th id=\"T_6a8b2_level0_col3\" class=\"col_heading level0 col3\" >feature</th>\n",
       "      <th id=\"T_6a8b2_level0_col4\" class=\"col_heading level0 col4\" >city</th>\n",
       "      <th id=\"T_6a8b2_level0_col5\" class=\"col_heading level0 col5\" >w_t</th>\n",
       "      <th id=\"T_6a8b2_level0_col6\" class=\"col_heading level0 col6\" >code</th>\n",
       "      <th id=\"T_6a8b2_level0_col7\" class=\"col_heading level0 col7\" >pcs_m</th>\n",
       "      <th id=\"T_6a8b2_level0_col8\" class=\"col_heading level0 col8\" >quantity</th>\n",
       "      <th id=\"T_6a8b2_level0_col9\" class=\"col_heading level0 col9\" >name</th>\n",
       "      <th id=\"T_6a8b2_level0_col10\" class=\"col_heading level0 col10\" >size</th>\n",
       "      <th id=\"T_6a8b2_level0_col11\" class=\"col_heading level0 col11\" >class</th>\n",
       "      <th id=\"T_6a8b2_level0_col12\" class=\"col_heading level0 col12\" >distance</th>\n",
       "      <th id=\"T_6a8b2_level0_col13\" class=\"col_heading level0 col13\" >length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_6a8b2_level0_row0\" class=\"row_heading level0 row0\" >108961</th>\n",
       "      <td id=\"T_6a8b2_row0_col0\" class=\"data row0 col0\" >('versoix', '2020-10-13')</td>\n",
       "      <td id=\"T_6a8b2_row0_col1\" class=\"data row0 col1\" >versoix</td>\n",
       "      <td id=\"T_6a8b2_row0_col2\" class=\"data row0 col2\" >rhone</td>\n",
       "      <td id=\"T_6a8b2_row0_col3\" class=\"data row0 col3\" >lac-leman</td>\n",
       "      <td id=\"T_6a8b2_row0_col4\" class=\"data row0 col4\" >Versoix</td>\n",
       "      <td id=\"T_6a8b2_row0_col5\" class=\"data row0 col5\" >l</td>\n",
       "      <td id=\"T_6a8b2_row0_col6\" class=\"data row0 col6\" >Gfrags</td>\n",
       "      <td id=\"T_6a8b2_row0_col7\" class=\"data row0 col7\" >0.68</td>\n",
       "      <td id=\"T_6a8b2_row0_col8\" class=\"data row0 col8\" >35.00</td>\n",
       "      <td id=\"T_6a8b2_row0_col9\" class=\"data row0 col9\" >0</td>\n",
       "      <td id=\"T_6a8b2_row0_col10\" class=\"data row0 col10\" >20.00</td>\n",
       "      <td id=\"T_6a8b2_row0_col11\" class=\"data row0 col11\" >20.00</td>\n",
       "      <td id=\"T_6a8b2_row0_col12\" class=\"data row0 col12\" >0.00</td>\n",
       "      <td id=\"T_6a8b2_row0_col13\" class=\"data row0 col13\" >0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc034316670>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddxf = data[(data.location == 'versoix') & (data.code == \"Gfrags\")&(data.loc_date == (\"versoix\", \"2020-10-13\"))].head()\n",
    "\n",
    "ddxf.style.format(precision=2).set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### River surveys\n",
    "\n",
    "The intersection of one river to another was not considered. Therefore, for river surveys the measured parameter is the length of the river in the buffer that was sampled. The class and size are set to 20 and the distance to intersection is 0. River sample locations, for this analysis, are considered the same as a lake locations with no corresponding intersections."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_e5290 tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_e5290 tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_e5290 tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_e5290 th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_e5290\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_e5290_level0_col0\" class=\"col_heading level0 col0\" >loc_date</th>\n",
       "      <th id=\"T_e5290_level0_col1\" class=\"col_heading level0 col1\" >location</th>\n",
       "      <th id=\"T_e5290_level0_col2\" class=\"col_heading level0 col2\" >river_bassin</th>\n",
       "      <th id=\"T_e5290_level0_col3\" class=\"col_heading level0 col3\" >feature</th>\n",
       "      <th id=\"T_e5290_level0_col4\" class=\"col_heading level0 col4\" >city</th>\n",
       "      <th id=\"T_e5290_level0_col5\" class=\"col_heading level0 col5\" >w_t</th>\n",
       "      <th id=\"T_e5290_level0_col6\" class=\"col_heading level0 col6\" >code</th>\n",
       "      <th id=\"T_e5290_level0_col7\" class=\"col_heading level0 col7\" >pcs_m</th>\n",
       "      <th id=\"T_e5290_level0_col8\" class=\"col_heading level0 col8\" >quantity</th>\n",
       "      <th id=\"T_e5290_level0_col9\" class=\"col_heading level0 col9\" >name</th>\n",
       "      <th id=\"T_e5290_level0_col10\" class=\"col_heading level0 col10\" >size</th>\n",
       "      <th id=\"T_e5290_level0_col11\" class=\"col_heading level0 col11\" >class</th>\n",
       "      <th id=\"T_e5290_level0_col12\" class=\"col_heading level0 col12\" >distance</th>\n",
       "      <th id=\"T_e5290_level0_col13\" class=\"col_heading level0 col13\" >length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_e5290_level0_row0\" class=\"row_heading level0 row0\" >71862</th>\n",
       "      <td id=\"T_e5290_row0_col0\" class=\"data row0 col0\" >('schusspark-strand', '2020-08-08')</td>\n",
       "      <td id=\"T_e5290_row0_col1\" class=\"data row0 col1\" >schusspark-strand</td>\n",
       "      <td id=\"T_e5290_row0_col2\" class=\"data row0 col2\" >aare</td>\n",
       "      <td id=\"T_e5290_row0_col3\" class=\"data row0 col3\" >schuss</td>\n",
       "      <td id=\"T_e5290_row0_col4\" class=\"data row0 col4\" >Biel/Bienne</td>\n",
       "      <td id=\"T_e5290_row0_col5\" class=\"data row0 col5\" >r</td>\n",
       "      <td id=\"T_e5290_row0_col6\" class=\"data row0 col6\" >Gfrags</td>\n",
       "      <td id=\"T_e5290_row0_col7\" class=\"data row0 col7\" >0.06</td>\n",
       "      <td id=\"T_e5290_row0_col8\" class=\"data row0 col8\" >3.00</td>\n",
       "      <td id=\"T_e5290_row0_col9\" class=\"data row0 col9\" >La Suze</td>\n",
       "      <td id=\"T_e5290_row0_col10\" class=\"data row0 col10\" >20.00</td>\n",
       "      <td id=\"T_e5290_row0_col11\" class=\"data row0 col11\" >20.00</td>\n",
       "      <td id=\"T_e5290_row0_col12\" class=\"data row0 col12\" >0.00</td>\n",
       "      <td id=\"T_e5290_row0_col13\" class=\"data row0 col13\" >3248.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc0343167c0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddxf = data[(data.location == 'schusspark-strand') & (data.code == \"Gfrags\")&(data.loc_date == (\"schusspark-strand\", \"2020-08-08\"))]\n",
    "ddxf.style.format(precision=2).set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Description of the survey results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_bf500 tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_bf500 tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_bf500 tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_bf500 th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_bf500\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_bf500_level0_col0\" class=\"col_heading level0 col0\" >total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_bf500_level0_row0\" class=\"row_heading level0 row0\" >n locations</th>\n",
       "      <td id=\"T_bf500_row0_col0\" class=\"data row0 col0\" >128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bf500_level0_row1\" class=\"row_heading level0 row1\" >n samples</th>\n",
       "      <td id=\"T_bf500_row1_col0\" class=\"data row1 col0\" >349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bf500_level0_row2\" class=\"row_heading level0 row2\" >n lake samples</th>\n",
       "      <td id=\"T_bf500_row2_col0\" class=\"data row2 col0\" >300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bf500_level0_row3\" class=\"row_heading level0 row3\" >n river samples</th>\n",
       "      <td id=\"T_bf500_row3_col0\" class=\"data row3 col0\" >49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bf500_level0_row4\" class=\"row_heading level0 row4\" >n identified object types</th>\n",
       "      <td id=\"T_bf500_row4_col0\" class=\"data row4 col0\" >191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bf500_level0_row5\" class=\"row_heading level0 row5\" >n possible object types</th>\n",
       "      <td id=\"T_bf500_row5_col0\" class=\"data row5 col0\" >211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bf500_level0_row6\" class=\"row_heading level0 row6\" >total number of objects</th>\n",
       "      <td id=\"T_bf500_row6_col0\" class=\"data row6 col0\" >46832</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fbfa5b53850>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## The survey results\n",
    "locations = df.location.unique()\n",
    "samples = df.loc_date.unique()\n",
    "lakes = df[df.w_t == \"l\"].drop_duplicates(\"loc_date\").w_t.value_counts().values[0]\n",
    "rivers = df[df.w_t == \"r\"].drop_duplicates(\"loc_date\").w_t.value_counts().values[0]\n",
    "codes_identified = df[df.quantity > 0].code.unique()\n",
    "codes_possible = df.code.unique()\n",
    "total_id = df.quantity.sum()\n",
    "\n",
    "data_summary = {\n",
    "    \"n locations\": len(locations),\n",
    "    \"n samples\": len(samples),\n",
    "    \"n lake samples\": lakes,\n",
    "    \"n river samples\": rivers,\n",
    "    \"n identified object types\": len(codes_identified),\n",
    "    \"n possible object types\": len(codes_possible),\n",
    "    \"total number of objects\": total_id\n",
    "}\n",
    "\n",
    "survey_desc = pd.DataFrame(index = data_summary.keys(), data=data_summary.values(), columns=[\"total\"])\n",
    "survey_desc.style.set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### River and lake samples\n",
    "\n",
    "The survey resutls for both river and lakes are tested for correlation. Each intersection is tested once. Consider the example from St. Gingolph under this model each results is tested against the distance and length of each intersection for each location, this includes the size and the class.\n",
    "\n",
    "__River and lake samples not aggregated__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_86b08 tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_86b08 tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_86b08 tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_86b08 th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_86b08\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >variable</th>\n",
       "      <th id=\"T_86b08_level0_col0\" class=\"col_heading level0 col0\" >class</th>\n",
       "      <th id=\"T_86b08_level0_col1\" class=\"col_heading level0 col1\" >distance</th>\n",
       "      <th id=\"T_86b08_level0_col2\" class=\"col_heading level0 col2\" >length</th>\n",
       "      <th id=\"T_86b08_level0_col3\" class=\"col_heading level0 col3\" >size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row0\" class=\"row_heading level0 row0\" >Food containers single use foamed or plastic</th>\n",
       "      <td id=\"T_86b08_row0_col0\" class=\"data row0 col0\" >-0.14</td>\n",
       "      <td id=\"T_86b08_row0_col1\" class=\"data row0 col1\" >0.19</td>\n",
       "      <td id=\"T_86b08_row0_col2\" class=\"data row0 col2\" >-0.11</td>\n",
       "      <td id=\"T_86b08_row0_col3\" class=\"data row0 col3\" >-0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row1\" class=\"row_heading level0 row1\" >Clothing, towels & rags</th>\n",
       "      <td id=\"T_86b08_row1_col0\" class=\"data row1 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row1_col1\" class=\"data row1 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row1_col2\" class=\"data row1 col2\" >0.09</td>\n",
       "      <td id=\"T_86b08_row1_col3\" class=\"data row1 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row2\" class=\"row_heading level0 row2\" >Paper packaging</th>\n",
       "      <td id=\"T_86b08_row2_col0\" class=\"data row2 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row2_col1\" class=\"data row2 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row2_col2\" class=\"data row2 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row2_col3\" class=\"data row2 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row3\" class=\"row_heading level0 row3\" >Fireworks paper tubes and fragments</th>\n",
       "      <td id=\"T_86b08_row3_col0\" class=\"data row3 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row3_col1\" class=\"data row3 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row3_col2\" class=\"data row3 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row3_col3\" class=\"data row3 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row4\" class=\"row_heading level0 row4\" >Foil wrappers, aluminum foil</th>\n",
       "      <td id=\"T_86b08_row4_col0\" class=\"data row4 col0\" >-0.23</td>\n",
       "      <td id=\"T_86b08_row4_col1\" class=\"data row4 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row4_col2\" class=\"data row4 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row4_col3\" class=\"data row4 col3\" >-0.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row5\" class=\"row_heading level0 row5\" >Metal bottle caps, lids & pull tabs from cans</th>\n",
       "      <td id=\"T_86b08_row5_col0\" class=\"data row5 col0\" >-0.11</td>\n",
       "      <td id=\"T_86b08_row5_col1\" class=\"data row5 col1\" >0.10</td>\n",
       "      <td id=\"T_86b08_row5_col2\" class=\"data row5 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row5_col3\" class=\"data row5 col3\" >-0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row6\" class=\"row_heading level0 row6\" >Glass drink bottles, pieces</th>\n",
       "      <td id=\"T_86b08_row6_col0\" class=\"data row6 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row6_col1\" class=\"data row6 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row6_col2\" class=\"data row6 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row6_col3\" class=\"data row6 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row7\" class=\"row_heading level0 row7\" >Construction material; bricks, pipes, cement</th>\n",
       "      <td id=\"T_86b08_row7_col0\" class=\"data row7 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row7_col1\" class=\"data row7 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row7_col2\" class=\"data row7 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row7_col3\" class=\"data row7 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row8\" class=\"row_heading level0 row8\" >Glass or ceramic fragments > 2.5 cm</th>\n",
       "      <td id=\"T_86b08_row8_col0\" class=\"data row8 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row8_col1\" class=\"data row8 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row8_col2\" class=\"data row8 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row8_col3\" class=\"data row8 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row9\" class=\"row_heading level0 row9\" >Drink lids</th>\n",
       "      <td id=\"T_86b08_row9_col0\" class=\"data row9 col0\" >-0.13</td>\n",
       "      <td id=\"T_86b08_row9_col1\" class=\"data row9 col1\" >0.20</td>\n",
       "      <td id=\"T_86b08_row9_col2\" class=\"data row9 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row9_col3\" class=\"data row9 col3\" >-0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row10\" class=\"row_heading level0 row10\" >Lids for chemicals, detergents (non-food)</th>\n",
       "      <td id=\"T_86b08_row10_col0\" class=\"data row10 col0\" >-0.15</td>\n",
       "      <td id=\"T_86b08_row10_col1\" class=\"data row10 col1\" >0.13</td>\n",
       "      <td id=\"T_86b08_row10_col2\" class=\"data row10 col2\" >-0.10</td>\n",
       "      <td id=\"T_86b08_row10_col3\" class=\"data row10 col3\" >-0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row11\" class=\"row_heading level0 row11\" >Lids unidentified</th>\n",
       "      <td id=\"T_86b08_row11_col0\" class=\"data row11 col0\" >-0.14</td>\n",
       "      <td id=\"T_86b08_row11_col1\" class=\"data row11 col1\" >0.21</td>\n",
       "      <td id=\"T_86b08_row11_col2\" class=\"data row11 col2\" >-0.08</td>\n",
       "      <td id=\"T_86b08_row11_col3\" class=\"data row11 col3\" >-0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row12\" class=\"row_heading level0 row12\" >Lid/cap rings from plastic bottles/containers</th>\n",
       "      <td id=\"T_86b08_row12_col0\" class=\"data row12 col0\" >-0.15</td>\n",
       "      <td id=\"T_86b08_row12_col1\" class=\"data row12 col1\" >0.20</td>\n",
       "      <td id=\"T_86b08_row12_col2\" class=\"data row12 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row12_col3\" class=\"data row12 col3\" >-0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row13\" class=\"row_heading level0 row13\" >Tobacco; plastic packaging, containers</th>\n",
       "      <td id=\"T_86b08_row13_col0\" class=\"data row13 col0\" >-0.19</td>\n",
       "      <td id=\"T_86b08_row13_col1\" class=\"data row13 col1\" >0.22</td>\n",
       "      <td id=\"T_86b08_row13_col2\" class=\"data row13 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row13_col3\" class=\"data row13 col3\" >-0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row14\" class=\"row_heading level0 row14\" >Cigarette filters</th>\n",
       "      <td id=\"T_86b08_row14_col0\" class=\"data row14 col0\" >-0.21</td>\n",
       "      <td id=\"T_86b08_row14_col1\" class=\"data row14 col1\" >0.15</td>\n",
       "      <td id=\"T_86b08_row14_col2\" class=\"data row14 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row14_col3\" class=\"data row14 col3\" >-0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row15\" class=\"row_heading level0 row15\" >Bags; plastic shopping/carrier/grocery and pieces</th>\n",
       "      <td id=\"T_86b08_row15_col0\" class=\"data row15 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row15_col1\" class=\"data row15 col1\" >0.09</td>\n",
       "      <td id=\"T_86b08_row15_col2\" class=\"data row15 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row15_col3\" class=\"data row15 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row16\" class=\"row_heading level0 row16\" >Food wrappers; candy, snacks</th>\n",
       "      <td id=\"T_86b08_row16_col0\" class=\"data row16 col0\" >-0.24</td>\n",
       "      <td id=\"T_86b08_row16_col1\" class=\"data row16 col1\" >0.23</td>\n",
       "      <td id=\"T_86b08_row16_col2\" class=\"data row16 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row16_col3\" class=\"data row16 col3\" >-0.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row17\" class=\"row_heading level0 row17\" >Coverings; plastic packaging, sheeting for protecting large cargo items</th>\n",
       "      <td id=\"T_86b08_row17_col0\" class=\"data row17 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row17_col1\" class=\"data row17 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row17_col2\" class=\"data row17 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row17_col3\" class=\"data row17 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row18\" class=\"row_heading level0 row18\" >Industrial sheeting</th>\n",
       "      <td id=\"T_86b08_row18_col0\" class=\"data row18 col0\" >-0.24</td>\n",
       "      <td id=\"T_86b08_row18_col1\" class=\"data row18 col1\" >0.18</td>\n",
       "      <td id=\"T_86b08_row18_col2\" class=\"data row18 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row18_col3\" class=\"data row18 col3\" >-0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row19\" class=\"row_heading level0 row19\" >Shotgun cartridges</th>\n",
       "      <td id=\"T_86b08_row19_col0\" class=\"data row19 col0\" >-0.11</td>\n",
       "      <td id=\"T_86b08_row19_col1\" class=\"data row19 col1\" >0.15</td>\n",
       "      <td id=\"T_86b08_row19_col2\" class=\"data row19 col2\" >-0.09</td>\n",
       "      <td id=\"T_86b08_row19_col3\" class=\"data row19 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row20\" class=\"row_heading level0 row20\" >Foamed items & pieces (non packaging/insulation) foamed sponge material</th>\n",
       "      <td id=\"T_86b08_row20_col0\" class=\"data row20 col0\" >-0.12</td>\n",
       "      <td id=\"T_86b08_row20_col1\" class=\"data row20 col1\" >0.14</td>\n",
       "      <td id=\"T_86b08_row20_col2\" class=\"data row20 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row20_col3\" class=\"data row20 col3\" >-0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row21\" class=\"row_heading level0 row21\" >Foam packaging/insulation/polyurethane</th>\n",
       "      <td id=\"T_86b08_row21_col0\" class=\"data row21 col0\" >-0.25</td>\n",
       "      <td id=\"T_86b08_row21_col1\" class=\"data row21 col1\" >0.25</td>\n",
       "      <td id=\"T_86b08_row21_col2\" class=\"data row21 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row21_col3\" class=\"data row21 col3\" >-0.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row22\" class=\"row_heading level0 row22\" >Plastic construction waste</th>\n",
       "      <td id=\"T_86b08_row22_col0\" class=\"data row22 col0\" >-0.15</td>\n",
       "      <td id=\"T_86b08_row22_col1\" class=\"data row22 col1\" >0.16</td>\n",
       "      <td id=\"T_86b08_row22_col2\" class=\"data row22 col2\" >-0.08</td>\n",
       "      <td id=\"T_86b08_row22_col3\" class=\"data row22 col3\" >-0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row23\" class=\"row_heading level0 row23\" >Fireworks; rocket caps, exploded parts & packaging</th>\n",
       "      <td id=\"T_86b08_row23_col0\" class=\"data row23 col0\" >-0.12</td>\n",
       "      <td id=\"T_86b08_row23_col1\" class=\"data row23 col1\" >0.10</td>\n",
       "      <td id=\"T_86b08_row23_col2\" class=\"data row23 col2\" >-0.09</td>\n",
       "      <td id=\"T_86b08_row23_col3\" class=\"data row23 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row24\" class=\"row_heading level0 row24\" >Ceramic tile and pieces</th>\n",
       "      <td id=\"T_86b08_row24_col0\" class=\"data row24 col0\" >0.09</td>\n",
       "      <td id=\"T_86b08_row24_col1\" class=\"data row24 col1\" >0.09</td>\n",
       "      <td id=\"T_86b08_row24_col2\" class=\"data row24 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row24_col3\" class=\"data row24 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row25\" class=\"row_heading level0 row25\" >Labels, bar codes</th>\n",
       "      <td id=\"T_86b08_row25_col0\" class=\"data row25 col0\" >-0.15</td>\n",
       "      <td id=\"T_86b08_row25_col1\" class=\"data row25 col1\" >0.12</td>\n",
       "      <td id=\"T_86b08_row25_col2\" class=\"data row25 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row25_col3\" class=\"data row25 col3\" >-0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row26\" class=\"row_heading level0 row26\" >Tissue, toilet paper, napkins, paper towels</th>\n",
       "      <td id=\"T_86b08_row26_col0\" class=\"data row26 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row26_col1\" class=\"data row26 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row26_col2\" class=\"data row26 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row26_col3\" class=\"data row26 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row27\" class=\"row_heading level0 row27\" >Ribbons and bows</th>\n",
       "      <td id=\"T_86b08_row27_col0\" class=\"data row27 col0\" >-0.10</td>\n",
       "      <td id=\"T_86b08_row27_col1\" class=\"data row27 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row27_col2\" class=\"data row27 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row27_col3\" class=\"data row27 col3\" >-0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row28\" class=\"row_heading level0 row28\" >Foamed EVA (flexible plastic) for crafts & watersports</th>\n",
       "      <td id=\"T_86b08_row28_col0\" class=\"data row28 col0\" >-0.14</td>\n",
       "      <td id=\"T_86b08_row28_col1\" class=\"data row28 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row28_col2\" class=\"data row28 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row28_col3\" class=\"data row28 col3\" >-0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row29\" class=\"row_heading level0 row29\" >Packaging films nonfood or unknown</th>\n",
       "      <td id=\"T_86b08_row29_col0\" class=\"data row29 col0\" >-0.16</td>\n",
       "      <td id=\"T_86b08_row29_col1\" class=\"data row29 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row29_col2\" class=\"data row29 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row29_col3\" class=\"data row29 col3\" >-0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row30\" class=\"row_heading level0 row30\" >Pellet mass from injection molding</th>\n",
       "      <td id=\"T_86b08_row30_col0\" class=\"data row30 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row30_col1\" class=\"data row30 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row30_col2\" class=\"data row30 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row30_col3\" class=\"data row30 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row31\" class=\"row_heading level0 row31\" >Cotton bud/swab sticks</th>\n",
       "      <td id=\"T_86b08_row31_col0\" class=\"data row31 col0\" >-0.25</td>\n",
       "      <td id=\"T_86b08_row31_col1\" class=\"data row31 col1\" >0.23</td>\n",
       "      <td id=\"T_86b08_row31_col2\" class=\"data row31 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row31_col3\" class=\"data row31 col3\" >-0.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row32\" class=\"row_heading level0 row32\" >Sanitary pads /panty liners/tampons and applicators</th>\n",
       "      <td id=\"T_86b08_row32_col0\" class=\"data row32 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row32_col1\" class=\"data row32 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row32_col2\" class=\"data row32 col2\" >0.00</td>\n",
       "      <td id=\"T_86b08_row32_col3\" class=\"data row32 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row33\" class=\"row_heading level0 row33\" >Diapers - wipes</th>\n",
       "      <td id=\"T_86b08_row33_col0\" class=\"data row33 col0\" >0.00</td>\n",
       "      <td id=\"T_86b08_row33_col1\" class=\"data row33 col1\" >0.00</td>\n",
       "      <td id=\"T_86b08_row33_col2\" class=\"data row33 col2\" >0.15</td>\n",
       "      <td id=\"T_86b08_row33_col3\" class=\"data row33 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row34\" class=\"row_heading level0 row34\" >Expanded polystyrene</th>\n",
       "      <td id=\"T_86b08_row34_col0\" class=\"data row34 col0\" >-0.23</td>\n",
       "      <td id=\"T_86b08_row34_col1\" class=\"data row34 col1\" >0.22</td>\n",
       "      <td id=\"T_86b08_row34_col2\" class=\"data row34 col2\" >-0.10</td>\n",
       "      <td id=\"T_86b08_row34_col3\" class=\"data row34 col3\" >-0.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_86b08_level0_row35\" class=\"row_heading level0 row35\" >Fragmented plastics</th>\n",
       "      <td id=\"T_86b08_row35_col0\" class=\"data row35 col0\" >-0.26</td>\n",
       "      <td id=\"T_86b08_row35_col1\" class=\"data row35 col1\" >0.20</td>\n",
       "      <td id=\"T_86b08_row35_col2\" class=\"data row35 col2\" >-0.09</td>\n",
       "      <td id=\"T_86b08_row35_col3\" class=\"data row35 col3\" >-0.23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fbfa5bb20a0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the columns being tested against pcs_m\n",
    "columns = [\"distance\", \"length\", \"size\", \"class\"]\n",
    "\n",
    "# conduct the test\n",
    "corellation_results = collectCorrelation(data, codes, columns)\n",
    "crp = pd.DataFrame(corellation_results)\n",
    "pvals = crp.pivot(index=\"code\", columns=\"variable\", values=\"p\")\n",
    "rhovals = crp.pivot(index=\"code\", columns=\"variable\", values=\"rho\")\n",
    "\n",
    "# display the results\n",
    "a_df = pd.DataFrame(resultsDf(rhovals, pvals))\n",
    "a_df[\"item\"] = a_df.index.map(lambda x: code_d_map.loc[x])\n",
    "a_df.set_index(\"item\", inplace=True, drop=True)\n",
    "a_df.index.name = None\n",
    "a_df.style.format(precision=2).set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "#### The number of correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_6528d tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_6528d tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_6528d tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_6528d th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_6528d\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >variable</th>\n",
       "      <th id=\"T_6528d_level0_col0\" class=\"col_heading level0 col0\" >class</th>\n",
       "      <th id=\"T_6528d_level0_col1\" class=\"col_heading level0 col1\" >distance</th>\n",
       "      <th id=\"T_6528d_level0_col2\" class=\"col_heading level0 col2\" >length</th>\n",
       "      <th id=\"T_6528d_level0_col3\" class=\"col_heading level0 col3\" >size</th>\n",
       "      <th id=\"T_6528d_level0_col4\" class=\"col_heading level0 col4\" >total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_6528d_level0_row0\" class=\"row_heading level0 row0\" >correlated</th>\n",
       "      <td id=\"T_6528d_row0_col0\" class=\"data row0 col0\" >24</td>\n",
       "      <td id=\"T_6528d_row0_col1\" class=\"data row0 col1\" >21</td>\n",
       "      <td id=\"T_6528d_row0_col2\" class=\"data row0 col2\" >10</td>\n",
       "      <td id=\"T_6528d_row0_col3\" class=\"data row0 col3\" >21</td>\n",
       "      <td id=\"T_6528d_row0_col4\" class=\"data row0 col4\" >76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6528d_level0_row1\" class=\"row_heading level0 row1\" >positive</th>\n",
       "      <td id=\"T_6528d_row1_col0\" class=\"data row1 col0\" >1</td>\n",
       "      <td id=\"T_6528d_row1_col1\" class=\"data row1 col1\" >21</td>\n",
       "      <td id=\"T_6528d_row1_col2\" class=\"data row1 col2\" >2</td>\n",
       "      <td id=\"T_6528d_row1_col3\" class=\"data row1 col3\" >0</td>\n",
       "      <td id=\"T_6528d_row1_col4\" class=\"data row1 col4\" >24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6528d_level0_row2\" class=\"row_heading level0 row2\" >negative</th>\n",
       "      <td id=\"T_6528d_row2_col0\" class=\"data row2 col0\" >23</td>\n",
       "      <td id=\"T_6528d_row2_col1\" class=\"data row2 col1\" >0</td>\n",
       "      <td id=\"T_6528d_row2_col2\" class=\"data row2 col2\" >8</td>\n",
       "      <td id=\"T_6528d_row2_col3\" class=\"data row2 col3\" >21</td>\n",
       "      <td id=\"T_6528d_row2_col4\" class=\"data row2 col4\" >52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc0343164c0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ncorrelated, total = countTheNumberOfCorrelationsPerBuffer(pvals, rhovals)\n",
    "ncorrelated.style.set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "__Notes:__\n",
    "\n",
    "__inverse correlations__ The __size__ and __class__ rankings start at zero, zero is the biggest. As an example the Aare and Rhône rivers are class 4. The correlations (if there are any) should be interpreted as 1/x:\n",
    "\n",
    "1. If the correlation is negative: the density is greater as the size get bigger or the river is more important\n",
    "2. If the correlation is positive: the density is greater as the size gets smaller of the river is less important\n",
    "\n",
    "Therefore, objects that are positively correlated with size and class were found more often at the intersects of smaller and less important rivers.\n",
    "\n",
    "__Lake samples__\n",
    "\n",
    "The survey results for lakes are tested for correlation, river samples are excluded. Each intersection is tested once. The same as the previous model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_50c6d tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_50c6d tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_50c6d tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_50c6d th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_50c6d\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >variable</th>\n",
       "      <th id=\"T_50c6d_level0_col0\" class=\"col_heading level0 col0\" >class</th>\n",
       "      <th id=\"T_50c6d_level0_col1\" class=\"col_heading level0 col1\" >distance</th>\n",
       "      <th id=\"T_50c6d_level0_col2\" class=\"col_heading level0 col2\" >length</th>\n",
       "      <th id=\"T_50c6d_level0_col3\" class=\"col_heading level0 col3\" >size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row0\" class=\"row_heading level0 row0\" >Food containers single use foamed or plastic</th>\n",
       "      <td id=\"T_50c6d_row0_col0\" class=\"data row0 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row0_col1\" class=\"data row0 col1\" >0.11</td>\n",
       "      <td id=\"T_50c6d_row0_col2\" class=\"data row0 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row0_col3\" class=\"data row0 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row1\" class=\"row_heading level0 row1\" >Clothing, towels & rags</th>\n",
       "      <td id=\"T_50c6d_row1_col0\" class=\"data row1 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row1_col1\" class=\"data row1 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row1_col2\" class=\"data row1 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row1_col3\" class=\"data row1 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row2\" class=\"row_heading level0 row2\" >Paper packaging</th>\n",
       "      <td id=\"T_50c6d_row2_col0\" class=\"data row2 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row2_col1\" class=\"data row2 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row2_col2\" class=\"data row2 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row2_col3\" class=\"data row2 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row3\" class=\"row_heading level0 row3\" >Fireworks paper tubes and fragments</th>\n",
       "      <td id=\"T_50c6d_row3_col0\" class=\"data row3 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row3_col1\" class=\"data row3 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row3_col2\" class=\"data row3 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row3_col3\" class=\"data row3 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row4\" class=\"row_heading level0 row4\" >Foil wrappers, aluminum foil</th>\n",
       "      <td id=\"T_50c6d_row4_col0\" class=\"data row4 col0\" >-0.19</td>\n",
       "      <td id=\"T_50c6d_row4_col1\" class=\"data row4 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row4_col2\" class=\"data row4 col2\" >0.09</td>\n",
       "      <td id=\"T_50c6d_row4_col3\" class=\"data row4 col3\" >-0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row5\" class=\"row_heading level0 row5\" >Metal bottle caps, lids & pull tabs from cans</th>\n",
       "      <td id=\"T_50c6d_row5_col0\" class=\"data row5 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row5_col1\" class=\"data row5 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row5_col2\" class=\"data row5 col2\" >0.11</td>\n",
       "      <td id=\"T_50c6d_row5_col3\" class=\"data row5 col3\" >-0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row6\" class=\"row_heading level0 row6\" >Glass drink bottles, pieces</th>\n",
       "      <td id=\"T_50c6d_row6_col0\" class=\"data row6 col0\" >0.12</td>\n",
       "      <td id=\"T_50c6d_row6_col1\" class=\"data row6 col1\" >-0.13</td>\n",
       "      <td id=\"T_50c6d_row6_col2\" class=\"data row6 col2\" >0.11</td>\n",
       "      <td id=\"T_50c6d_row6_col3\" class=\"data row6 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row7\" class=\"row_heading level0 row7\" >Construction material; bricks, pipes, cement</th>\n",
       "      <td id=\"T_50c6d_row7_col0\" class=\"data row7 col0\" >0.09</td>\n",
       "      <td id=\"T_50c6d_row7_col1\" class=\"data row7 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row7_col2\" class=\"data row7 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row7_col3\" class=\"data row7 col3\" >0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row8\" class=\"row_heading level0 row8\" >Glass or ceramic fragments > 2.5 cm</th>\n",
       "      <td id=\"T_50c6d_row8_col0\" class=\"data row8 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row8_col1\" class=\"data row8 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row8_col2\" class=\"data row8 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row8_col3\" class=\"data row8 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row9\" class=\"row_heading level0 row9\" >Drink lids</th>\n",
       "      <td id=\"T_50c6d_row9_col0\" class=\"data row9 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row9_col1\" class=\"data row9 col1\" >0.13</td>\n",
       "      <td id=\"T_50c6d_row9_col2\" class=\"data row9 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row9_col3\" class=\"data row9 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row10\" class=\"row_heading level0 row10\" >Lids for chemicals, detergents (non-food)</th>\n",
       "      <td id=\"T_50c6d_row10_col0\" class=\"data row10 col0\" >-0.09</td>\n",
       "      <td id=\"T_50c6d_row10_col1\" class=\"data row10 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row10_col2\" class=\"data row10 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row10_col3\" class=\"data row10 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row11\" class=\"row_heading level0 row11\" >Lids unidentified</th>\n",
       "      <td id=\"T_50c6d_row11_col0\" class=\"data row11 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row11_col1\" class=\"data row11 col1\" >0.12</td>\n",
       "      <td id=\"T_50c6d_row11_col2\" class=\"data row11 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row11_col3\" class=\"data row11 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row12\" class=\"row_heading level0 row12\" >Lid/cap rings from plastic bottles/containers</th>\n",
       "      <td id=\"T_50c6d_row12_col0\" class=\"data row12 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row12_col1\" class=\"data row12 col1\" >0.12</td>\n",
       "      <td id=\"T_50c6d_row12_col2\" class=\"data row12 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row12_col3\" class=\"data row12 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row13\" class=\"row_heading level0 row13\" >Tobacco; plastic packaging, containers</th>\n",
       "      <td id=\"T_50c6d_row13_col0\" class=\"data row13 col0\" >-0.09</td>\n",
       "      <td id=\"T_50c6d_row13_col1\" class=\"data row13 col1\" >0.13</td>\n",
       "      <td id=\"T_50c6d_row13_col2\" class=\"data row13 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row13_col3\" class=\"data row13 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row14\" class=\"row_heading level0 row14\" >Cigarette filters</th>\n",
       "      <td id=\"T_50c6d_row14_col0\" class=\"data row14 col0\" >-0.13</td>\n",
       "      <td id=\"T_50c6d_row14_col1\" class=\"data row14 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row14_col2\" class=\"data row14 col2\" >0.17</td>\n",
       "      <td id=\"T_50c6d_row14_col3\" class=\"data row14 col3\" >-0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row15\" class=\"row_heading level0 row15\" >Bags; plastic shopping/carrier/grocery and pieces</th>\n",
       "      <td id=\"T_50c6d_row15_col0\" class=\"data row15 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row15_col1\" class=\"data row15 col1\" >0.10</td>\n",
       "      <td id=\"T_50c6d_row15_col2\" class=\"data row15 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row15_col3\" class=\"data row15 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row16\" class=\"row_heading level0 row16\" >Food wrappers; candy, snacks</th>\n",
       "      <td id=\"T_50c6d_row16_col0\" class=\"data row16 col0\" >-0.12</td>\n",
       "      <td id=\"T_50c6d_row16_col1\" class=\"data row16 col1\" >0.11</td>\n",
       "      <td id=\"T_50c6d_row16_col2\" class=\"data row16 col2\" >0.12</td>\n",
       "      <td id=\"T_50c6d_row16_col3\" class=\"data row16 col3\" >-0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row17\" class=\"row_heading level0 row17\" >Coverings; plastic packaging, sheeting for protecting large cargo items</th>\n",
       "      <td id=\"T_50c6d_row17_col0\" class=\"data row17 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row17_col1\" class=\"data row17 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row17_col2\" class=\"data row17 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row17_col3\" class=\"data row17 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row18\" class=\"row_heading level0 row18\" >Industrial sheeting</th>\n",
       "      <td id=\"T_50c6d_row18_col0\" class=\"data row18 col0\" >-0.16</td>\n",
       "      <td id=\"T_50c6d_row18_col1\" class=\"data row18 col1\" >0.09</td>\n",
       "      <td id=\"T_50c6d_row18_col2\" class=\"data row18 col2\" >0.14</td>\n",
       "      <td id=\"T_50c6d_row18_col3\" class=\"data row18 col3\" >-0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row19\" class=\"row_heading level0 row19\" >Shotgun cartridges</th>\n",
       "      <td id=\"T_50c6d_row19_col0\" class=\"data row19 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row19_col1\" class=\"data row19 col1\" >0.09</td>\n",
       "      <td id=\"T_50c6d_row19_col2\" class=\"data row19 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row19_col3\" class=\"data row19 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row20\" class=\"row_heading level0 row20\" >Foamed items & pieces (non packaging/insulation) foamed sponge material</th>\n",
       "      <td id=\"T_50c6d_row20_col0\" class=\"data row20 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row20_col1\" class=\"data row20 col1\" >0.09</td>\n",
       "      <td id=\"T_50c6d_row20_col2\" class=\"data row20 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row20_col3\" class=\"data row20 col3\" >-0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row21\" class=\"row_heading level0 row21\" >Foam packaging/insulation/polyurethane</th>\n",
       "      <td id=\"T_50c6d_row21_col0\" class=\"data row21 col0\" >-0.13</td>\n",
       "      <td id=\"T_50c6d_row21_col1\" class=\"data row21 col1\" >0.14</td>\n",
       "      <td id=\"T_50c6d_row21_col2\" class=\"data row21 col2\" >0.09</td>\n",
       "      <td id=\"T_50c6d_row21_col3\" class=\"data row21 col3\" >-0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row22\" class=\"row_heading level0 row22\" >Plastic construction waste</th>\n",
       "      <td id=\"T_50c6d_row22_col0\" class=\"data row22 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row22_col1\" class=\"data row22 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row22_col2\" class=\"data row22 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row22_col3\" class=\"data row22 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row23\" class=\"row_heading level0 row23\" >Fireworks; rocket caps, exploded parts & packaging</th>\n",
       "      <td id=\"T_50c6d_row23_col0\" class=\"data row23 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row23_col1\" class=\"data row23 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row23_col2\" class=\"data row23 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row23_col3\" class=\"data row23 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row24\" class=\"row_heading level0 row24\" >Ceramic tile and pieces</th>\n",
       "      <td id=\"T_50c6d_row24_col0\" class=\"data row24 col0\" >0.17</td>\n",
       "      <td id=\"T_50c6d_row24_col1\" class=\"data row24 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row24_col2\" class=\"data row24 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row24_col3\" class=\"data row24 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row25\" class=\"row_heading level0 row25\" >Labels, bar codes</th>\n",
       "      <td id=\"T_50c6d_row25_col0\" class=\"data row25 col0\" >-0.11</td>\n",
       "      <td id=\"T_50c6d_row25_col1\" class=\"data row25 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row25_col2\" class=\"data row25 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row25_col3\" class=\"data row25 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row26\" class=\"row_heading level0 row26\" >Tissue, toilet paper, napkins, paper towels</th>\n",
       "      <td id=\"T_50c6d_row26_col0\" class=\"data row26 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row26_col1\" class=\"data row26 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row26_col2\" class=\"data row26 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row26_col3\" class=\"data row26 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row27\" class=\"row_heading level0 row27\" >Ribbons and bows</th>\n",
       "      <td id=\"T_50c6d_row27_col0\" class=\"data row27 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row27_col1\" class=\"data row27 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row27_col2\" class=\"data row27 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row27_col3\" class=\"data row27 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row28\" class=\"row_heading level0 row28\" >Foamed EVA (flexible plastic) for crafts & watersports</th>\n",
       "      <td id=\"T_50c6d_row28_col0\" class=\"data row28 col0\" >-0.11</td>\n",
       "      <td id=\"T_50c6d_row28_col1\" class=\"data row28 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row28_col2\" class=\"data row28 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row28_col3\" class=\"data row28 col3\" >-0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row29\" class=\"row_heading level0 row29\" >Packaging films nonfood or unknown</th>\n",
       "      <td id=\"T_50c6d_row29_col0\" class=\"data row29 col0\" >-0.13</td>\n",
       "      <td id=\"T_50c6d_row29_col1\" class=\"data row29 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row29_col2\" class=\"data row29 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row29_col3\" class=\"data row29 col3\" >-0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row30\" class=\"row_heading level0 row30\" >Pellet mass from injection molding</th>\n",
       "      <td id=\"T_50c6d_row30_col0\" class=\"data row30 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row30_col1\" class=\"data row30 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row30_col2\" class=\"data row30 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row30_col3\" class=\"data row30 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row31\" class=\"row_heading level0 row31\" >Cotton bud/swab sticks</th>\n",
       "      <td id=\"T_50c6d_row31_col0\" class=\"data row31 col0\" >-0.12</td>\n",
       "      <td id=\"T_50c6d_row31_col1\" class=\"data row31 col1\" >0.10</td>\n",
       "      <td id=\"T_50c6d_row31_col2\" class=\"data row31 col2\" >0.11</td>\n",
       "      <td id=\"T_50c6d_row31_col3\" class=\"data row31 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row32\" class=\"row_heading level0 row32\" >Sanitary pads /panty liners/tampons and applicators</th>\n",
       "      <td id=\"T_50c6d_row32_col0\" class=\"data row32 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row32_col1\" class=\"data row32 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row32_col2\" class=\"data row32 col2\" >0.13</td>\n",
       "      <td id=\"T_50c6d_row32_col3\" class=\"data row32 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row33\" class=\"row_heading level0 row33\" >Diapers - wipes</th>\n",
       "      <td id=\"T_50c6d_row33_col0\" class=\"data row33 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row33_col1\" class=\"data row33 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row33_col2\" class=\"data row33 col2\" >0.18</td>\n",
       "      <td id=\"T_50c6d_row33_col3\" class=\"data row33 col3\" >-0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row34\" class=\"row_heading level0 row34\" >Expanded polystyrene</th>\n",
       "      <td id=\"T_50c6d_row34_col0\" class=\"data row34 col0\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row34_col1\" class=\"data row34 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row34_col2\" class=\"data row34 col2\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row34_col3\" class=\"data row34 col3\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_50c6d_level0_row35\" class=\"row_heading level0 row35\" >Fragmented plastics</th>\n",
       "      <td id=\"T_50c6d_row35_col0\" class=\"data row35 col0\" >-0.10</td>\n",
       "      <td id=\"T_50c6d_row35_col1\" class=\"data row35 col1\" >0.00</td>\n",
       "      <td id=\"T_50c6d_row35_col2\" class=\"data row35 col2\" >0.10</td>\n",
       "      <td id=\"T_50c6d_row35_col3\" class=\"data row35 col3\" >0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fbfa5b0a910>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datax = data[data.w_t == \"l\"]\n",
    "columns = [\"distance\", \"length\", \"size\", \"class\"]\n",
    "corellation_results = collectCorrelation(datax, codes, columns)\n",
    "crp = pd.DataFrame(corellation_results)\n",
    "pvals = crp.pivot(index=\"code\", columns=\"variable\", values=\"p\")\n",
    "rhovals = crp.pivot(index=\"code\", columns=\"variable\", values=\"rho\")\n",
    "\n",
    "# display the results\n",
    "a_df = pd.DataFrame(resultsDf(rhovals, pvals))\n",
    "a_df[\"item\"] = a_df.index.map(lambda x: code_d_map.loc[x])\n",
    "a_df.set_index(\"item\", inplace=True, drop=True)\n",
    "a_df.index.name = None\n",
    "a_df.style.format(precision=2).set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "#### The number of correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_c1747 tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_c1747 tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_c1747 tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_c1747 th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_c1747\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >variable</th>\n",
       "      <th id=\"T_c1747_level0_col0\" class=\"col_heading level0 col0\" >class</th>\n",
       "      <th id=\"T_c1747_level0_col1\" class=\"col_heading level0 col1\" >distance</th>\n",
       "      <th id=\"T_c1747_level0_col2\" class=\"col_heading level0 col2\" >length</th>\n",
       "      <th id=\"T_c1747_level0_col3\" class=\"col_heading level0 col3\" >size</th>\n",
       "      <th id=\"T_c1747_level0_col4\" class=\"col_heading level0 col4\" >total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_c1747_level0_row0\" class=\"row_heading level0 row0\" >correlated</th>\n",
       "      <td id=\"T_c1747_row0_col0\" class=\"data row0 col0\" >15</td>\n",
       "      <td id=\"T_c1747_row0_col1\" class=\"data row0 col1\" >13</td>\n",
       "      <td id=\"T_c1747_row0_col2\" class=\"data row0 col2\" >11</td>\n",
       "      <td id=\"T_c1747_row0_col3\" class=\"data row0 col3\" >11</td>\n",
       "      <td id=\"T_c1747_row0_col4\" class=\"data row0 col4\" >50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c1747_level0_row1\" class=\"row_heading level0 row1\" >positive</th>\n",
       "      <td id=\"T_c1747_row1_col0\" class=\"data row1 col0\" >3</td>\n",
       "      <td id=\"T_c1747_row1_col1\" class=\"data row1 col1\" >12</td>\n",
       "      <td id=\"T_c1747_row1_col2\" class=\"data row1 col2\" >11</td>\n",
       "      <td id=\"T_c1747_row1_col3\" class=\"data row1 col3\" >1</td>\n",
       "      <td id=\"T_c1747_row1_col4\" class=\"data row1 col4\" >27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c1747_level0_row2\" class=\"row_heading level0 row2\" >negative</th>\n",
       "      <td id=\"T_c1747_row2_col0\" class=\"data row2 col0\" >12</td>\n",
       "      <td id=\"T_c1747_row2_col1\" class=\"data row2 col1\" >1</td>\n",
       "      <td id=\"T_c1747_row2_col2\" class=\"data row2 col2\" >0</td>\n",
       "      <td id=\"T_c1747_row2_col3\" class=\"data row2 col3\" >10</td>\n",
       "      <td id=\"T_c1747_row2_col4\" class=\"data row2 col4\" >23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fbfa5b2cc40>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ncorrelated, total = countTheNumberOfCorrelationsPerBuffer(pvals, rhovals)\n",
    "ncorrelated.style.set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Aggregated intersection and length\n",
    "\n",
    "The length and distance parameters are aggregated in the following way:\n",
    "\n",
    "1. length: the sum of the length of all intersections in the buffer\n",
    "2. distance: the average distance to an intersection\n",
    "\n",
    "Because we are aggregating, the size and class values for each intersection are not considered. The example for St. Gingolph is below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_2e7a6 tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_2e7a6 tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_2e7a6 tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_2e7a6 th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_2e7a6\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_2e7a6_level0_col0\" class=\"col_heading level0 col0\" >loc_date</th>\n",
       "      <th id=\"T_2e7a6_level0_col1\" class=\"col_heading level0 col1\" >location</th>\n",
       "      <th id=\"T_2e7a6_level0_col2\" class=\"col_heading level0 col2\" >river_bassin</th>\n",
       "      <th id=\"T_2e7a6_level0_col3\" class=\"col_heading level0 col3\" >feature</th>\n",
       "      <th id=\"T_2e7a6_level0_col4\" class=\"col_heading level0 col4\" >city</th>\n",
       "      <th id=\"T_2e7a6_level0_col5\" class=\"col_heading level0 col5\" >w_t</th>\n",
       "      <th id=\"T_2e7a6_level0_col6\" class=\"col_heading level0 col6\" >code</th>\n",
       "      <th id=\"T_2e7a6_level0_col7\" class=\"col_heading level0 col7\" >pcs_m</th>\n",
       "      <th id=\"T_2e7a6_level0_col8\" class=\"col_heading level0 col8\" >quantity</th>\n",
       "      <th id=\"T_2e7a6_level0_col9\" class=\"col_heading level0 col9\" >distance</th>\n",
       "      <th id=\"T_2e7a6_level0_col10\" class=\"col_heading level0 col10\" >length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_2e7a6_level0_row0\" class=\"row_heading level0 row0\" >17351</th>\n",
       "      <td id=\"T_2e7a6_row0_col0\" class=\"data row0 col0\" >('grand-clos', '2020-05-07')</td>\n",
       "      <td id=\"T_2e7a6_row0_col1\" class=\"data row0 col1\" >grand-clos</td>\n",
       "      <td id=\"T_2e7a6_row0_col2\" class=\"data row0 col2\" >rhone</td>\n",
       "      <td id=\"T_2e7a6_row0_col3\" class=\"data row0 col3\" >lac-leman</td>\n",
       "      <td id=\"T_2e7a6_row0_col4\" class=\"data row0 col4\" >Saint-Gingolph</td>\n",
       "      <td id=\"T_2e7a6_row0_col5\" class=\"data row0 col5\" >l</td>\n",
       "      <td id=\"T_2e7a6_row0_col6\" class=\"data row0 col6\" >Gfrags</td>\n",
       "      <td id=\"T_2e7a6_row0_col7\" class=\"data row0 col7\" >2.56</td>\n",
       "      <td id=\"T_2e7a6_row0_col8\" class=\"data row0 col8\" >82</td>\n",
       "      <td id=\"T_2e7a6_row0_col9\" class=\"data row0 col9\" >1039.92</td>\n",
       "      <td id=\"T_2e7a6_row0_col10\" class=\"data row0 col10\" >1995.34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc0343166d0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "intersects_agg = ind.groupby([\"location\"], as_index=False).agg({'distance':'mean', 'length':'sum'})\n",
    "\n",
    "ints_and_data = df.merge(intersects_agg, on=[\"location\"])\n",
    "locations = df.location.unique()\n",
    "\n",
    "data = ints_and_data[(ints_and_data.code.isin(codes)) & (ints_and_data.location.isin(locations))].copy()\n",
    "data.fillna(0, inplace=True)\n",
    "data.rename(columns=n_c_names, inplace=True)\n",
    "data.drop(\"intersects\", inplace=True, axis=1)\n",
    "\n",
    "ddxf = data[(data.location == 'grand-clos') & (data.code == \"Gfrags\")&(data.loc_date == (\"grand-clos\", \"2020-05-07\"))]\n",
    "ddxf.style.format(precision=2).set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "__River and lake samples aggregated__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_ad559 tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_ad559 tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_ad559 tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_ad559 th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_ad559\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >variable</th>\n",
       "      <th id=\"T_ad559_level0_col0\" class=\"col_heading level0 col0\" >distance</th>\n",
       "      <th id=\"T_ad559_level0_col1\" class=\"col_heading level0 col1\" >length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row0\" class=\"row_heading level0 row0\" >Food containers single use foamed or plastic</th>\n",
       "      <td id=\"T_ad559_row0_col0\" class=\"data row0 col0\" >0.21</td>\n",
       "      <td id=\"T_ad559_row0_col1\" class=\"data row0 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row1\" class=\"row_heading level0 row1\" >Clothing, towels & rags</th>\n",
       "      <td id=\"T_ad559_row1_col0\" class=\"data row1 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row1_col1\" class=\"data row1 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row2\" class=\"row_heading level0 row2\" >Paper packaging</th>\n",
       "      <td id=\"T_ad559_row2_col0\" class=\"data row2 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row2_col1\" class=\"data row2 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row3\" class=\"row_heading level0 row3\" >Fireworks paper tubes and fragments</th>\n",
       "      <td id=\"T_ad559_row3_col0\" class=\"data row3 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row3_col1\" class=\"data row3 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row4\" class=\"row_heading level0 row4\" >Foil wrappers, aluminum foil</th>\n",
       "      <td id=\"T_ad559_row4_col0\" class=\"data row4 col0\" >0.11</td>\n",
       "      <td id=\"T_ad559_row4_col1\" class=\"data row4 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row5\" class=\"row_heading level0 row5\" >Metal bottle caps, lids & pull tabs from cans</th>\n",
       "      <td id=\"T_ad559_row5_col0\" class=\"data row5 col0\" >0.19</td>\n",
       "      <td id=\"T_ad559_row5_col1\" class=\"data row5 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row6\" class=\"row_heading level0 row6\" >Glass drink bottles, pieces</th>\n",
       "      <td id=\"T_ad559_row6_col0\" class=\"data row6 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row6_col1\" class=\"data row6 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row7\" class=\"row_heading level0 row7\" >Construction material; bricks, pipes, cement</th>\n",
       "      <td id=\"T_ad559_row7_col0\" class=\"data row7 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row7_col1\" class=\"data row7 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row8\" class=\"row_heading level0 row8\" >Glass or ceramic fragments > 2.5 cm</th>\n",
       "      <td id=\"T_ad559_row8_col0\" class=\"data row8 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row8_col1\" class=\"data row8 col1\" >-0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row9\" class=\"row_heading level0 row9\" >Drink lids</th>\n",
       "      <td id=\"T_ad559_row9_col0\" class=\"data row9 col0\" >0.22</td>\n",
       "      <td id=\"T_ad559_row9_col1\" class=\"data row9 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row10\" class=\"row_heading level0 row10\" >Lids for chemicals, detergents (non-food)</th>\n",
       "      <td id=\"T_ad559_row10_col0\" class=\"data row10 col0\" >0.14</td>\n",
       "      <td id=\"T_ad559_row10_col1\" class=\"data row10 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row11\" class=\"row_heading level0 row11\" >Lids unidentified</th>\n",
       "      <td id=\"T_ad559_row11_col0\" class=\"data row11 col0\" >0.23</td>\n",
       "      <td id=\"T_ad559_row11_col1\" class=\"data row11 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row12\" class=\"row_heading level0 row12\" >Lid/cap rings from plastic bottles/containers</th>\n",
       "      <td id=\"T_ad559_row12_col0\" class=\"data row12 col0\" >0.25</td>\n",
       "      <td id=\"T_ad559_row12_col1\" class=\"data row12 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row13\" class=\"row_heading level0 row13\" >Tobacco; plastic packaging, containers</th>\n",
       "      <td id=\"T_ad559_row13_col0\" class=\"data row13 col0\" >0.29</td>\n",
       "      <td id=\"T_ad559_row13_col1\" class=\"data row13 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row14\" class=\"row_heading level0 row14\" >Cigarette filters</th>\n",
       "      <td id=\"T_ad559_row14_col0\" class=\"data row14 col0\" >0.24</td>\n",
       "      <td id=\"T_ad559_row14_col1\" class=\"data row14 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row15\" class=\"row_heading level0 row15\" >Bags; plastic shopping/carrier/grocery and pieces</th>\n",
       "      <td id=\"T_ad559_row15_col0\" class=\"data row15 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row15_col1\" class=\"data row15 col1\" >0.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row16\" class=\"row_heading level0 row16\" >Food wrappers; candy, snacks</th>\n",
       "      <td id=\"T_ad559_row16_col0\" class=\"data row16 col0\" >0.30</td>\n",
       "      <td id=\"T_ad559_row16_col1\" class=\"data row16 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row17\" class=\"row_heading level0 row17\" >Coverings; plastic packaging, sheeting for protecting large cargo items</th>\n",
       "      <td id=\"T_ad559_row17_col0\" class=\"data row17 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row17_col1\" class=\"data row17 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row18\" class=\"row_heading level0 row18\" >Industrial sheeting</th>\n",
       "      <td id=\"T_ad559_row18_col0\" class=\"data row18 col0\" >0.17</td>\n",
       "      <td id=\"T_ad559_row18_col1\" class=\"data row18 col1\" >0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row19\" class=\"row_heading level0 row19\" >Shotgun cartridges</th>\n",
       "      <td id=\"T_ad559_row19_col0\" class=\"data row19 col0\" >0.14</td>\n",
       "      <td id=\"T_ad559_row19_col1\" class=\"data row19 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row20\" class=\"row_heading level0 row20\" >Foamed items & pieces (non packaging/insulation) foamed sponge material</th>\n",
       "      <td id=\"T_ad559_row20_col0\" class=\"data row20 col0\" >0.18</td>\n",
       "      <td id=\"T_ad559_row20_col1\" class=\"data row20 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row21\" class=\"row_heading level0 row21\" >Foam packaging/insulation/polyurethane</th>\n",
       "      <td id=\"T_ad559_row21_col0\" class=\"data row21 col0\" >0.29</td>\n",
       "      <td id=\"T_ad559_row21_col1\" class=\"data row21 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row22\" class=\"row_heading level0 row22\" >Plastic construction waste</th>\n",
       "      <td id=\"T_ad559_row22_col0\" class=\"data row22 col0\" >0.16</td>\n",
       "      <td id=\"T_ad559_row22_col1\" class=\"data row22 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row23\" class=\"row_heading level0 row23\" >Fireworks; rocket caps, exploded parts & packaging</th>\n",
       "      <td id=\"T_ad559_row23_col0\" class=\"data row23 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row23_col1\" class=\"data row23 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row24\" class=\"row_heading level0 row24\" >Ceramic tile and pieces</th>\n",
       "      <td id=\"T_ad559_row24_col0\" class=\"data row24 col0\" >0.15</td>\n",
       "      <td id=\"T_ad559_row24_col1\" class=\"data row24 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row25\" class=\"row_heading level0 row25\" >Labels, bar codes</th>\n",
       "      <td id=\"T_ad559_row25_col0\" class=\"data row25 col0\" >0.13</td>\n",
       "      <td id=\"T_ad559_row25_col1\" class=\"data row25 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row26\" class=\"row_heading level0 row26\" >Tissue, toilet paper, napkins, paper towels</th>\n",
       "      <td id=\"T_ad559_row26_col0\" class=\"data row26 col0\" >0.13</td>\n",
       "      <td id=\"T_ad559_row26_col1\" class=\"data row26 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row27\" class=\"row_heading level0 row27\" >Ribbons and bows</th>\n",
       "      <td id=\"T_ad559_row27_col0\" class=\"data row27 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row27_col1\" class=\"data row27 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row28\" class=\"row_heading level0 row28\" >Foamed EVA (flexible plastic) for crafts & watersports</th>\n",
       "      <td id=\"T_ad559_row28_col0\" class=\"data row28 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row28_col1\" class=\"data row28 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row29\" class=\"row_heading level0 row29\" >Packaging films nonfood or unknown</th>\n",
       "      <td id=\"T_ad559_row29_col0\" class=\"data row29 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row29_col1\" class=\"data row29 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row30\" class=\"row_heading level0 row30\" >Pellet mass from injection molding</th>\n",
       "      <td id=\"T_ad559_row30_col0\" class=\"data row30 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row30_col1\" class=\"data row30 col1\" >0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row31\" class=\"row_heading level0 row31\" >Cotton bud/swab sticks</th>\n",
       "      <td id=\"T_ad559_row31_col0\" class=\"data row31 col0\" >0.27</td>\n",
       "      <td id=\"T_ad559_row31_col1\" class=\"data row31 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row32\" class=\"row_heading level0 row32\" >Sanitary pads /panty liners/tampons and applicators</th>\n",
       "      <td id=\"T_ad559_row32_col0\" class=\"data row32 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row32_col1\" class=\"data row32 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row33\" class=\"row_heading level0 row33\" >Diapers - wipes</th>\n",
       "      <td id=\"T_ad559_row33_col0\" class=\"data row33 col0\" >0.00</td>\n",
       "      <td id=\"T_ad559_row33_col1\" class=\"data row33 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row34\" class=\"row_heading level0 row34\" >Expanded polystyrene</th>\n",
       "      <td id=\"T_ad559_row34_col0\" class=\"data row34 col0\" >0.24</td>\n",
       "      <td id=\"T_ad559_row34_col1\" class=\"data row34 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ad559_level0_row35\" class=\"row_heading level0 row35\" >Fragmented plastics</th>\n",
       "      <td id=\"T_ad559_row35_col0\" class=\"data row35 col0\" >0.24</td>\n",
       "      <td id=\"T_ad559_row35_col1\" class=\"data row35 col1\" >0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fbfa5bb2280>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns = [\"distance\", \"length\"]\n",
    "\n",
    "corellation_results = collectCorrelation(data, codes, columns)\n",
    "crp = pd.DataFrame(corellation_results)\n",
    "pvals = crp.pivot(index=\"code\", columns=\"variable\", values=\"p\")\n",
    "rhovals = crp.pivot(index=\"code\", columns=\"variable\", values=\"rho\")\n",
    "\n",
    "# display the results\n",
    "a_df = pd.DataFrame(resultsDf(rhovals, pvals))\n",
    "a_df[\"item\"] = a_df.index.map(lambda x: code_d_map.loc[x])\n",
    "a_df.set_index(\"item\", inplace=True, drop=True)\n",
    "a_df.index.name = None\n",
    "a_df.style.format(precision=2).set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "#### The number of correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_36d80 tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_36d80 tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_36d80 tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_36d80 th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_36d80\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >variable</th>\n",
       "      <th id=\"T_36d80_level0_col0\" class=\"col_heading level0 col0\" >distance</th>\n",
       "      <th id=\"T_36d80_level0_col1\" class=\"col_heading level0 col1\" >length</th>\n",
       "      <th id=\"T_36d80_level0_col2\" class=\"col_heading level0 col2\" >total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_36d80_level0_row0\" class=\"row_heading level0 row0\" >correlated</th>\n",
       "      <td id=\"T_36d80_row0_col0\" class=\"data row0 col0\" >21</td>\n",
       "      <td id=\"T_36d80_row0_col1\" class=\"data row0 col1\" >4</td>\n",
       "      <td id=\"T_36d80_row0_col2\" class=\"data row0 col2\" >25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_36d80_level0_row1\" class=\"row_heading level0 row1\" >positive</th>\n",
       "      <td id=\"T_36d80_row1_col0\" class=\"data row1 col0\" >21</td>\n",
       "      <td id=\"T_36d80_row1_col1\" class=\"data row1 col1\" >3</td>\n",
       "      <td id=\"T_36d80_row1_col2\" class=\"data row1 col2\" >24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_36d80_level0_row2\" class=\"row_heading level0 row2\" >negative</th>\n",
       "      <td id=\"T_36d80_row2_col0\" class=\"data row2 col0\" >0</td>\n",
       "      <td id=\"T_36d80_row2_col1\" class=\"data row2 col1\" >1</td>\n",
       "      <td id=\"T_36d80_row2_col2\" class=\"data row2 col2\" >1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fbfa5b2c7f0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ncorrelated, total = countTheNumberOfCorrelationsPerBuffer(pvals, rhovals)\n",
    "ncorrelated.style.set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "__Lake samples aggregated__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_dcdbe tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_dcdbe tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_dcdbe tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_dcdbe th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_dcdbe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >variable</th>\n",
       "      <th id=\"T_dcdbe_level0_col0\" class=\"col_heading level0 col0\" >distance</th>\n",
       "      <th id=\"T_dcdbe_level0_col1\" class=\"col_heading level0 col1\" >length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row0\" class=\"row_heading level0 row0\" >Food containers single use foamed or plastic</th>\n",
       "      <td id=\"T_dcdbe_row0_col0\" class=\"data row0 col0\" >0.12</td>\n",
       "      <td id=\"T_dcdbe_row0_col1\" class=\"data row0 col1\" >0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row1\" class=\"row_heading level0 row1\" >Clothing, towels & rags</th>\n",
       "      <td id=\"T_dcdbe_row1_col0\" class=\"data row1 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row1_col1\" class=\"data row1 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row2\" class=\"row_heading level0 row2\" >Paper packaging</th>\n",
       "      <td id=\"T_dcdbe_row2_col0\" class=\"data row2 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row2_col1\" class=\"data row2 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row3\" class=\"row_heading level0 row3\" >Fireworks paper tubes and fragments</th>\n",
       "      <td id=\"T_dcdbe_row3_col0\" class=\"data row3 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row3_col1\" class=\"data row3 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row4\" class=\"row_heading level0 row4\" >Foil wrappers, aluminum foil</th>\n",
       "      <td id=\"T_dcdbe_row4_col0\" class=\"data row4 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row4_col1\" class=\"data row4 col1\" >0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row5\" class=\"row_heading level0 row5\" >Metal bottle caps, lids & pull tabs from cans</th>\n",
       "      <td id=\"T_dcdbe_row5_col0\" class=\"data row5 col0\" >0.13</td>\n",
       "      <td id=\"T_dcdbe_row5_col1\" class=\"data row5 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row6\" class=\"row_heading level0 row6\" >Glass drink bottles, pieces</th>\n",
       "      <td id=\"T_dcdbe_row6_col0\" class=\"data row6 col0\" >-0.20</td>\n",
       "      <td id=\"T_dcdbe_row6_col1\" class=\"data row6 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row7\" class=\"row_heading level0 row7\" >Construction material; bricks, pipes, cement</th>\n",
       "      <td id=\"T_dcdbe_row7_col0\" class=\"data row7 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row7_col1\" class=\"data row7 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row8\" class=\"row_heading level0 row8\" >Glass or ceramic fragments > 2.5 cm</th>\n",
       "      <td id=\"T_dcdbe_row8_col0\" class=\"data row8 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row8_col1\" class=\"data row8 col1\" >-0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row9\" class=\"row_heading level0 row9\" >Drink lids</th>\n",
       "      <td id=\"T_dcdbe_row9_col0\" class=\"data row9 col0\" >0.13</td>\n",
       "      <td id=\"T_dcdbe_row9_col1\" class=\"data row9 col1\" >0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row10\" class=\"row_heading level0 row10\" >Lids for chemicals, detergents (non-food)</th>\n",
       "      <td id=\"T_dcdbe_row10_col0\" class=\"data row10 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row10_col1\" class=\"data row10 col1\" >0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row11\" class=\"row_heading level0 row11\" >Lids unidentified</th>\n",
       "      <td id=\"T_dcdbe_row11_col0\" class=\"data row11 col0\" >0.12</td>\n",
       "      <td id=\"T_dcdbe_row11_col1\" class=\"data row11 col1\" >0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row12\" class=\"row_heading level0 row12\" >Lid/cap rings from plastic bottles/containers</th>\n",
       "      <td id=\"T_dcdbe_row12_col0\" class=\"data row12 col0\" >0.13</td>\n",
       "      <td id=\"T_dcdbe_row12_col1\" class=\"data row12 col1\" >0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row13\" class=\"row_heading level0 row13\" >Tobacco; plastic packaging, containers</th>\n",
       "      <td id=\"T_dcdbe_row13_col0\" class=\"data row13 col0\" >0.17</td>\n",
       "      <td id=\"T_dcdbe_row13_col1\" class=\"data row13 col1\" >0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row14\" class=\"row_heading level0 row14\" >Cigarette filters</th>\n",
       "      <td id=\"T_dcdbe_row14_col0\" class=\"data row14 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row14_col1\" class=\"data row14 col1\" >0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row15\" class=\"row_heading level0 row15\" >Bags; plastic shopping/carrier/grocery and pieces</th>\n",
       "      <td id=\"T_dcdbe_row15_col0\" class=\"data row15 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row15_col1\" class=\"data row15 col1\" >0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row16\" class=\"row_heading level0 row16\" >Food wrappers; candy, snacks</th>\n",
       "      <td id=\"T_dcdbe_row16_col0\" class=\"data row16 col0\" >0.14</td>\n",
       "      <td id=\"T_dcdbe_row16_col1\" class=\"data row16 col1\" >0.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row17\" class=\"row_heading level0 row17\" >Coverings; plastic packaging, sheeting for protecting large cargo items</th>\n",
       "      <td id=\"T_dcdbe_row17_col0\" class=\"data row17 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row17_col1\" class=\"data row17 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row18\" class=\"row_heading level0 row18\" >Industrial sheeting</th>\n",
       "      <td id=\"T_dcdbe_row18_col0\" class=\"data row18 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row18_col1\" class=\"data row18 col1\" >0.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row19\" class=\"row_heading level0 row19\" >Shotgun cartridges</th>\n",
       "      <td id=\"T_dcdbe_row19_col0\" class=\"data row19 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row19_col1\" class=\"data row19 col1\" >0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row20\" class=\"row_heading level0 row20\" >Foamed items & pieces (non packaging/insulation) foamed sponge material</th>\n",
       "      <td id=\"T_dcdbe_row20_col0\" class=\"data row20 col0\" >0.13</td>\n",
       "      <td id=\"T_dcdbe_row20_col1\" class=\"data row20 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row21\" class=\"row_heading level0 row21\" >Foam packaging/insulation/polyurethane</th>\n",
       "      <td id=\"T_dcdbe_row21_col0\" class=\"data row21 col0\" >0.14</td>\n",
       "      <td id=\"T_dcdbe_row21_col1\" class=\"data row21 col1\" >0.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row22\" class=\"row_heading level0 row22\" >Plastic construction waste</th>\n",
       "      <td id=\"T_dcdbe_row22_col0\" class=\"data row22 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row22_col1\" class=\"data row22 col1\" >0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row23\" class=\"row_heading level0 row23\" >Fireworks; rocket caps, exploded parts & packaging</th>\n",
       "      <td id=\"T_dcdbe_row23_col0\" class=\"data row23 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row23_col1\" class=\"data row23 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row24\" class=\"row_heading level0 row24\" >Ceramic tile and pieces</th>\n",
       "      <td id=\"T_dcdbe_row24_col0\" class=\"data row24 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row24_col1\" class=\"data row24 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row25\" class=\"row_heading level0 row25\" >Labels, bar codes</th>\n",
       "      <td id=\"T_dcdbe_row25_col0\" class=\"data row25 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row25_col1\" class=\"data row25 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row26\" class=\"row_heading level0 row26\" >Tissue, toilet paper, napkins, paper towels</th>\n",
       "      <td id=\"T_dcdbe_row26_col0\" class=\"data row26 col0\" >0.13</td>\n",
       "      <td id=\"T_dcdbe_row26_col1\" class=\"data row26 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row27\" class=\"row_heading level0 row27\" >Ribbons and bows</th>\n",
       "      <td id=\"T_dcdbe_row27_col0\" class=\"data row27 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row27_col1\" class=\"data row27 col1\" >0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row28\" class=\"row_heading level0 row28\" >Foamed EVA (flexible plastic) for crafts & watersports</th>\n",
       "      <td id=\"T_dcdbe_row28_col0\" class=\"data row28 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row28_col1\" class=\"data row28 col1\" >0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row29\" class=\"row_heading level0 row29\" >Packaging films nonfood or unknown</th>\n",
       "      <td id=\"T_dcdbe_row29_col0\" class=\"data row29 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row29_col1\" class=\"data row29 col1\" >0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row30\" class=\"row_heading level0 row30\" >Pellet mass from injection molding</th>\n",
       "      <td id=\"T_dcdbe_row30_col0\" class=\"data row30 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row30_col1\" class=\"data row30 col1\" >0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row31\" class=\"row_heading level0 row31\" >Cotton bud/swab sticks</th>\n",
       "      <td id=\"T_dcdbe_row31_col0\" class=\"data row31 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row31_col1\" class=\"data row31 col1\" >0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row32\" class=\"row_heading level0 row32\" >Sanitary pads /panty liners/tampons and applicators</th>\n",
       "      <td id=\"T_dcdbe_row32_col0\" class=\"data row32 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row32_col1\" class=\"data row32 col1\" >0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row33\" class=\"row_heading level0 row33\" >Diapers - wipes</th>\n",
       "      <td id=\"T_dcdbe_row33_col0\" class=\"data row33 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row33_col1\" class=\"data row33 col1\" >0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row34\" class=\"row_heading level0 row34\" >Expanded polystyrene</th>\n",
       "      <td id=\"T_dcdbe_row34_col0\" class=\"data row34 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row34_col1\" class=\"data row34 col1\" >0.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_dcdbe_level0_row35\" class=\"row_heading level0 row35\" >Fragmented plastics</th>\n",
       "      <td id=\"T_dcdbe_row35_col0\" class=\"data row35 col0\" >0.00</td>\n",
       "      <td id=\"T_dcdbe_row35_col1\" class=\"data row35 col1\" >0.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc0343237f0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datax = data[data.w_t == 'l']\n",
    "corellation_results = collectCorrelation(datax, codes, columns)\n",
    "crp = pd.DataFrame(corellation_results)\n",
    "pvals = crp.pivot(index=\"code\", columns=\"variable\", values=\"p\")\n",
    "rhovals = crp.pivot(index=\"code\", columns=\"variable\", values=\"rho\")\n",
    "\n",
    "# display the results\n",
    "a_df = pd.DataFrame(resultsDf(rhovals, pvals))\n",
    "a_df[\"item\"] = a_df.index.map(lambda x: code_d_map.loc[x])\n",
    "a_df.set_index(\"item\", inplace=True, drop=True)\n",
    "a_df.index.name = None\n",
    "a_df.style.format(precision=2).set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "#### The number of correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_10ccd tr:nth-child(even) {\n",
       "  background-color: rgba(139, 69, 19, 0.08);\n",
       "}\n",
       "#T_10ccd tr:nth-child(odd) {\n",
       "  background: #FFF;\n",
       "}\n",
       "#T_10ccd tr {\n",
       "  font-size: 12px;\n",
       "}\n",
       "#T_10ccd th:nth-child(1) {\n",
       "  background-color: #FFF;\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_10ccd\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >variable</th>\n",
       "      <th id=\"T_10ccd_level0_col0\" class=\"col_heading level0 col0\" >distance</th>\n",
       "      <th id=\"T_10ccd_level0_col1\" class=\"col_heading level0 col1\" >length</th>\n",
       "      <th id=\"T_10ccd_level0_col2\" class=\"col_heading level0 col2\" >total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_10ccd_level0_row0\" class=\"row_heading level0 row0\" >correlated</th>\n",
       "      <td id=\"T_10ccd_row0_col0\" class=\"data row0 col0\" >11</td>\n",
       "      <td id=\"T_10ccd_row0_col1\" class=\"data row0 col1\" >23</td>\n",
       "      <td id=\"T_10ccd_row0_col2\" class=\"data row0 col2\" >34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_10ccd_level0_row1\" class=\"row_heading level0 row1\" >positive</th>\n",
       "      <td id=\"T_10ccd_row1_col0\" class=\"data row1 col0\" >10</td>\n",
       "      <td id=\"T_10ccd_row1_col1\" class=\"data row1 col1\" >22</td>\n",
       "      <td id=\"T_10ccd_row1_col2\" class=\"data row1 col2\" >32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_10ccd_level0_row2\" class=\"row_heading level0 row2\" >negative</th>\n",
       "      <td id=\"T_10ccd_row2_col0\" class=\"data row2 col0\" >1</td>\n",
       "      <td id=\"T_10ccd_row2_col1\" class=\"data row2 col1\" >1</td>\n",
       "      <td id=\"T_10ccd_row2_col2\" class=\"data row2 col2\" >2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fbfa5b8bf40>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ncorrelated, total = countTheNumberOfCorrelationsPerBuffer(pvals, rhovals)\n",
    "ncorrelated.style.set_table_styles(table_css_styles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "\n",
       "\n",
       "This script updated 08/08/2023 in Biel, CH\n",
       "\n",
       "> ❤️ what you do everyday\n",
       "\n",
       "*analyst at hammerdirt*\n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "today = dt.datetime.now().date().strftime(\"%d/%m/%Y\")\n",
    "where = \"Biel, CH\"\n",
    "\n",
    "my_block = f\"\"\"\n",
    "\n",
    "This script updated {today} in {where}\n",
    "\n",
    "> \\u2764\\ufe0f what you do everyday\n",
    "\n",
    "*analyst at hammerdirt*\n",
    "\"\"\"\n",
    "\n",
    "md(my_block)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Git repo: https://github.com/hammerdirt-analyst/landuse.git\n",
      "\n",
      "Git branch: main\n",
      "\n",
      "PIL    : 9.5.0\n",
      "pandas : 2.0.0\n",
      "numpy  : 1.24.2\n",
      "IPython: 8.12.0\n",
      "scipy  : 1.10.1\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%watermark --iversions -b -r"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}