Module 3 - Matplotlib - assignment.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Module 3 - Matplotlib - assignment.ipynb","provenance":[],"collapsed_sections":[],"toc_visible":true},"kernelspec":{"display_name":"Python 3","name":"python3"}},"cells":[{"cell_type":"code","metadata":{"id":"llMUSgPbmDIy"},"source":["simport matplotlib.pyplot as plt\n","import pandas as pd\n","import numpy as np\n","import seaborn"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"KE10smrHx_qX"},"source":["In this assignment, you will upload a dataset and reproduce a few visualizations. Start by uploading the \"datasets-agro.csv\" dataset. "]},{"cell_type":"code","metadata":{"id":"Z43emp8jyJmv"},"source":["# The following is code for uploading a file to the colab.research.google \n","# environment.\n","\n","# library for uploading files\n","from google.colab import files \n","\n","def upload_files():\n","    # initiates the upload - follow the dialogues that appear\n","    uploaded = files.upload()\n","\n","    # verify the upload\n","    for fn in uploaded.keys():\n","        print('User uploaded file \"{name}\" with length {length} bytes'.format(\n","            name=fn, length=len(uploaded[fn])))\n","\n","    # uploaded files need to be written to file to interact with them\n","    # as part of a file system\n","    for filename in uploaded.keys():\n","        with open(filename, 'wb') as f:\n","            f.write(uploaded[filename])"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"XvrxOc5nyKhe","colab":{"base_uri":"https://localhost:8080/","height":181},"executionInfo":{"status":"error","timestamp":1615050982516,"user_tz":420,"elapsed":597,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"8ed35119-991d-439a-9129-86ad9970752c"},"source":["# upload datasets-agro.csv\n","upload_files()"],"execution_count":41,"outputs":[{"output_type":"error","ename":"NameError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)","\u001b[0;32m<ipython-input-41-7aee5036274b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# upload datasets-agro.csv\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mupload_files\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;31mNameError\u001b[0m: name 'upload_files' is not defined"]}]},{"cell_type":"code","metadata":{"id":"V1mVldGd1nKw","executionInfo":{"status":"ok","timestamp":1615050986202,"user_tz":420,"elapsed":679,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}}},"source":["agro_df = pd.read_csv(\"datasets-agro.csv\")"],"execution_count":42,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"YnUuk4SmiZyX"},"source":["Next, use some of the EDA techniques in pandas to get a feel for the dataset scheme again."]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"KSzyAiWEfU3c","executionInfo":{"status":"ok","timestamp":1615050987242,"user_tz":420,"elapsed":341,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"173a6fe8-735a-499d-832c-5669eb8476ab"},"source":["agro_df.describe"],"execution_count":43,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<bound method NDFrame.describe of       id   water      uv   area  ...   yield  pesticides  region  categories\n","0      0   0.072  80.179  9.414  ...  29.878       2.231       6         c,b\n","1      1   5.413  58.359  9.681  ...  53.416       1.810       6         c,b\n","2      2   9.731  78.506  7.189  ...  63.391       2.455       1           d\n","3      3  10.995  69.248  1.738  ...  17.984       0.603       2           a\n","4      4   2.617  87.658  9.706  ...  49.768       2.910       6           c\n","..   ...     ...     ...    ...  ...     ...         ...     ...         ...\n","995  995   5.457  70.622  8.163  ...  89.809       4.224       2           c\n","996  996   6.931  75.326  5.675  ...  29.261       1.355       2       d,b,a\n","997  997  10.373  78.225  7.378  ...  76.608       5.459       2           b\n","998  998   9.158  79.257  9.011  ...  80.399       5.968       1     d,c,b,a\n","999  999   3.316  75.490  5.501  ...  43.152       4.220       3           c\n","\n","[1000 rows x 9 columns]>"]},"metadata":{"tags":[]},"execution_count":43}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"qieuhUHqfdx7","executionInfo":{"elapsed":630,"status":"ok","timestamp":1615050176554,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"},"user_tz":420},"outputId":"e2ddfea5-b655-4e29-c662-9f734f0d9a13"},"source":["agro_df.info()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 1000 entries, 0 to 999\n","Data columns (total 9 columns):\n"," #   Column            Non-Null Count  Dtype  \n","---  ------            --------------  -----  \n"," 0   id                1000 non-null   int64  \n"," 1   water             1000 non-null   float64\n"," 2   uv                1000 non-null   float64\n"," 3   area              1000 non-null   float64\n"," 4   fertilizer_usage  1000 non-null   int64  \n"," 5   yield             1000 non-null   float64\n"," 6   pesticides        1000 non-null   float64\n"," 7   region            1000 non-null   int64  \n"," 8   categories        1000 non-null   object \n","dtypes: float64(5), int64(3), object(1)\n","memory usage: 70.4+ KB\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":359},"id":"qCIILTF6fkPg","executionInfo":{"elapsed":679,"status":"ok","timestamp":1615050201753,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"},"user_tz":420},"outputId":"24aa9ed8-88bb-4754-ea8d-b3f7197d6261"},"source":["agro_df.head(10)"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>id</th>\n","      <th>water</th>\n","      <th>uv</th>\n","      <th>area</th>\n","      <th>fertilizer_usage</th>\n","      <th>yield</th>\n","      <th>pesticides</th>\n","      <th>region</th>\n","      <th>categories</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>0.072</td>\n","      <td>80.179</td>\n","      <td>9.414</td>\n","      <td>0</td>\n","      <td>29.878</td>\n","      <td>2.231</td>\n","      <td>6</td>\n","      <td>c,b</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>5.413</td>\n","      <td>58.359</td>\n","      <td>9.681</td>\n","      <td>2</td>\n","      <td>53.416</td>\n","      <td>1.810</td>\n","      <td>6</td>\n","      <td>c,b</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>9.731</td>\n","      <td>78.506</td>\n","      <td>7.189</td>\n","      <td>1</td>\n","      <td>63.391</td>\n","      <td>2.455</td>\n","      <td>1</td>\n","      <td>d</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>10.995</td>\n","      <td>69.248</td>\n","      <td>1.738</td>\n","      <td>3</td>\n","      <td>17.984</td>\n","      <td>0.603</td>\n","      <td>2</td>\n","      <td>a</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>2.617</td>\n","      <td>87.658</td>\n","      <td>9.706</td>\n","      <td>1</td>\n","      <td>49.768</td>\n","      <td>2.910</td>\n","      <td>6</td>\n","      <td>c</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>5</td>\n","      <td>2.190</td>\n","      <td>51.727</td>\n","      <td>9.152</td>\n","      <td>0</td>\n","      <td>35.488</td>\n","      <td>1.788</td>\n","      <td>3</td>\n","      <td>b</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>6</td>\n","      <td>10.679</td>\n","      <td>79.767</td>\n","      <td>6.311</td>\n","      <td>1</td>\n","      <td>43.157</td>\n","      <td>0.458</td>\n","      <td>2</td>\n","      <td>a</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>7</td>\n","      <td>3.620</td>\n","      <td>80.430</td>\n","      <td>9.473</td>\n","      <td>0</td>\n","      <td>32.752</td>\n","      <td>3.533</td>\n","      <td>5</td>\n","      <td>b,a,c</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>8</td>\n","      <td>9.857</td>\n","      <td>61.683</td>\n","      <td>5.240</td>\n","      <td>1</td>\n","      <td>57.811</td>\n","      <td>5.090</td>\n","      <td>1</td>\n","      <td>a</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>9</td>\n","      <td>4.321</td>\n","      <td>79.671</td>\n","      <td>6.818</td>\n","      <td>0</td>\n","      <td>11.650</td>\n","      <td>1.255</td>\n","      <td>5</td>\n","      <td>b,d</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   id   water      uv   area  ...   yield  pesticides  region  categories\n","0   0   0.072  80.179  9.414  ...  29.878       2.231       6         c,b\n","1   1   5.413  58.359  9.681  ...  53.416       1.810       6         c,b\n","2   2   9.731  78.506  7.189  ...  63.391       2.455       1           d\n","3   3  10.995  69.248  1.738  ...  17.984       0.603       2           a\n","4   4   2.617  87.658  9.706  ...  49.768       2.910       6           c\n","5   5   2.190  51.727  9.152  ...  35.488       1.788       3           b\n","6   6  10.679  79.767  6.311  ...  43.157       0.458       2           a\n","7   7   3.620  80.430  9.473  ...  32.752       3.533       5       b,a,c\n","8   8   9.857  61.683  5.240  ...  57.811       5.090       1           a\n","9   9   4.321  79.671  6.818  ...  11.650       1.255       5         b,d\n","\n","[10 rows x 9 columns]"]},"metadata":{"tags":[]},"execution_count":7}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"EwOLkHIsfpwf","executionInfo":{"elapsed":634,"status":"ok","timestamp":1615050242109,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"},"user_tz":420},"outputId":"c11b6e31-0a4c-4230-d050-5930c75f08ed"},"source":["agro_df['region'].value_counts()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["2    314\n","6    200\n","1    143\n","3    125\n","4    102\n","0     59\n","5     57\n","Name: region, dtype: int64"]},"metadata":{"tags":[]},"execution_count":10}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lzia_mbtfxE5","executionInfo":{"elapsed":591,"status":"ok","timestamp":1615050260185,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"},"user_tz":420},"outputId":"86567592-0621-4410-d589-bb25482e5ac1"},"source":["agro_df['fertilizer_usage'].value_counts()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["3    231\n","1    204\n","0    189\n","2    171\n","4    141\n","5     64\n","Name: fertilizer_usage, dtype: int64"]},"metadata":{"tags":[]},"execution_count":11}]},{"cell_type":"markdown","metadata":{"id":"E6Er961xTTnM"},"source":["# Visualization 1\n","\n","Reproduce the bar graph found in section 1) of the supplementary document. You must choose your own title. If there are any enhancements you think would make the graph more useful (color changes or extra text), feel free to add that.\n","\n","1 mark each:\n","\n","*   Getting data into the correct shape\n","*   Plotting the bar graph\n","*   Having a title and axis labels\n","\n"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":170},"id":"IOxsGv-7gZE7","executionInfo":{"elapsed":540,"status":"ok","timestamp":1615050500846,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"},"user_tz":420},"outputId":"44709e47-6666-4756-fe61-3dc069551f52"},"source":["average_yield_by_region = agro_df.groupby('region').mean()['yield']\n","display(average_yield_by_region)"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["region\n","0    57.152678\n","1    61.532329\n","2    55.769118\n","3    60.660840\n","4    79.794902\n","5    48.546193\n","6    52.935595\n","Name: yield, dtype: float64"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vJ3N-THKg96z","executionInfo":{"elapsed":660,"status":"ok","timestamp":1615050578069,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"},"user_tz":420},"outputId":"de72ec15-2ede-4b4b-e22a-0d7ab8a71216"},"source":["list(average_yield_by_region.index)"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[0, 1, 2, 3, 4, 5, 6]"]},"metadata":{"tags":[]},"execution_count":22}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":416},"id":"_t5FOmPFdQa-","executionInfo":{"status":"ok","timestamp":1615050991783,"user_tz":420,"elapsed":866,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"90aae5e9-904a-4e1a-d6f9-e0c7b24d0146"},"source":["plt.figure()\n","\n","plt.bar(list(average_yield_by_region.index),average_yield_by_region)\n","plt.xlabel('Region')\n","plt.ylabel('Average Yield')\n","plt.title('Average Yield of crops by region')\n","\n","i = 0\n","for v in average_yield_by_region:\n","    plt.text(i-0.4 , v + .8, f'{v:.2f}', color='green', fontweight='bold')\n","    i += 1\n","    print(i,v)\n","\n","plt.tight_layout()\n","plt.show()"],"execution_count":44,"outputs":[{"output_type":"stream","text":["1 57.15267796610169\n","2 61.532328671328656\n","3 55.76911783439487\n","4 60.660840000000015\n","5 79.7949019607843\n","6 48.54619298245613\n","7 52.93559500000004\n"],"name":"stdout"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"BO47N2wahHID"},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"FKD4RU_UXpbw"},"source":["#Visualization 2\n","\n","Reproduce the figure found in section 2 of the supplementary document. Notice that this graph requires subplots. Please add titles and appropriate axis labels to each plot. Each plot shows data for a different region. It is very important to this task that each plot shows only the data from a single region.\n","\n","Marks (1 each):\n","\n","*    Identify and use the correct method for making the plot\n","*    Set up the subplots correctly\n","*    Plot data for each region in its own subplot\n","*    Have each subplot use a different colour\n","*    Include useful titles, axis labels, and have the figure be an appropriate size"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"W9ladfkxjYiv","executionInfo":{"status":"ok","timestamp":1615051271249,"user_tz":420,"elapsed":542,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"61aacd9c-cc6a-4ba2-9e9e-6fbc9ecb3deb"},"source":["agro_df.columns"],"execution_count":48,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['id', 'water', 'uv', 'area', 'fertilizer_usage', 'yield', 'pesticides',\n","       'region', 'categories'],\n","      dtype='object')"]},"metadata":{"tags":[]},"execution_count":48}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"IpvRguHRpEAm","executionInfo":{"status":"ok","timestamp":1615052817921,"user_tz":420,"elapsed":680,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"5e108d80-00d0-499f-b91e-9b4904967385"},"source":["sorted(list(agro_df['region'].unique()))\n"],"execution_count":69,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[0, 1, 2, 3, 4, 5, 6]"]},"metadata":{"tags":[]},"execution_count":69}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"_HvjKCIMivwH","executionInfo":{"status":"ok","timestamp":1615053688648,"user_tz":420,"elapsed":3232,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"ed97d0c5-cde0-4d6f-c9cc-a8e7b428b4c2"},"source":["plt.figure(figsize = (11,16))\n","color = ['red', 'blue', 'green', 'purple','pink','yellow','orange']\n","#initiates a 4x2 subplot and selects subplot 1\n","for each_region in sorted(list(agro_df['region'].unique())):\n","\n","  plt.subplot(4,2,each_region+1)\n","\n","  seaborn.regplot(x=\"water\",\n","                  y=\"yield\",\n","                  data=agro_df[agro_df['region'] == each_region],\n","                  fit_reg=True,\n","                  color = color[each_region])\n","\n","  title = \"Water vs Yield - Region \" + str(each_region)\n","  \n","  plt.xlim(0,15)\n","  plt.ylim(0,160)\n","  # Not in example figures but setting up limits to be able to compare in same ranges\n","  plt.title(title)\n","  plt.tight_layout()\n","\n","\n","\n","plt.show()\n"],"execution_count":87,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 792x1152 with 7 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"fcpWDK0ZZEF_"},"source":["#Visualization 3\n","\n","Reproduce the figure found in section 3 of the supplementary document. The plot is showing the co-occurence frequency of two categorical variables: fertilizer_usage and region. Notice that this requires you to use a method not shown in the notes. In Data Science it is very common to have to look through an API and find an appropriate function. You can use the Seaborn API as reference:\n","\n","https://seaborn.pydata.org/api.html\n","\n","Also feel free to use google or stackoverflow to point you in the right direction. Please add an appropriate title and axis labels to the plot. \n","\n","Hint: In my solution, I use both groupby and pivot (dataframe methods from pandas) to help transform my data. There is probably multiple ways of transforming the required variables.\n","\n","Marks:\n","\n","*    Identify and use the correct method for making the plot (1 mark)\n","*    Transform data for use with the method you found (2 marks)\n","*    Normalize data (notice the range of values on the right side of the graph) (1 mark)\n","*    Include useful titles, axis labels, and have the figure be an appropriate size (1 mark)"]},{"cell_type":"markdown","metadata":{"id":"KzMXF1Gxtl-_"},"source":["Correct method: https://seaborn.pydata.org/generated/seaborn.heatmap.html#seaborn.heatmap"]},{"cell_type":"code","metadata":{"id":"D-h8Xm_FzNf7","executionInfo":{"status":"ok","timestamp":1615055508867,"user_tz":420,"elapsed":684,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}}},"source":[""],"execution_count":125,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"70LzxfiTto8_","executionInfo":{"status":"ok","timestamp":1615055876349,"user_tz":420,"elapsed":596,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"55002a30-12b8-44d2-d939-9456a1da23c4"},"source":["agro_df_3 = agro_df.groupby(['fertilizer_usage','region']).count()\n","\n","agro_df_3 = agro_df_3.pivot_table(values = 'id', index=['fertilizer_usage'], columns = 'region')\n","print(agro_df_3)\n"],"execution_count":138,"outputs":[{"output_type":"stream","text":["region             0   1   2   3   4   5   6\n","fertilizer_usage                            \n","0                  9  25  62  19  19  13  42\n","1                 14  32  66  26  19   8  39\n","2                 15  24  49  24  15  11  33\n","3                 12  31  78  35  29   9  37\n","4                  8  20  41  15  17  10  30\n","5                  1  11  18   6   3   6  19\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"0PLD_F2ct7Yj","executionInfo":{"status":"ok","timestamp":1615059510450,"user_tz":420,"elapsed":621,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"7ec20f6b-0e9a-4c76-b23d-6bbe1c1966d4"},"source":["agro_df_3.max().max()"],"execution_count":170,"outputs":[{"output_type":"execute_result","data":{"text/plain":["78"]},"metadata":{"tags":[]},"execution_count":170}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":266},"id":"gvoSTVTmuHMY","executionInfo":{"status":"ok","timestamp":1615059519678,"user_tz":420,"elapsed":622,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"4a94464e-6d9e-4714-9451-d883a0fbf2f0"},"source":["agro_df_3_norm = agro_df_3/ agro_df_3.max().max()\n","agro_df_3_norm"],"execution_count":171,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th>region</th>\n","      <th>0</th>\n","      <th>1</th>\n","      <th>2</th>\n","      <th>3</th>\n","      <th>4</th>\n","      <th>5</th>\n","      <th>6</th>\n","    </tr>\n","    <tr>\n","      <th>fertilizer_usage</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.115385</td>\n","      <td>0.320513</td>\n","      <td>0.794872</td>\n","      <td>0.243590</td>\n","      <td>0.243590</td>\n","      <td>0.166667</td>\n","      <td>0.538462</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0.179487</td>\n","      <td>0.410256</td>\n","      <td>0.846154</td>\n","      <td>0.333333</td>\n","      <td>0.243590</td>\n","      <td>0.102564</td>\n","      <td>0.500000</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.192308</td>\n","      <td>0.307692</td>\n","      <td>0.628205</td>\n","      <td>0.307692</td>\n","      <td>0.192308</td>\n","      <td>0.141026</td>\n","      <td>0.423077</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0.153846</td>\n","      <td>0.397436</td>\n","      <td>1.000000</td>\n","      <td>0.448718</td>\n","      <td>0.371795</td>\n","      <td>0.115385</td>\n","      <td>0.474359</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.102564</td>\n","      <td>0.256410</td>\n","      <td>0.525641</td>\n","      <td>0.192308</td>\n","      <td>0.217949</td>\n","      <td>0.128205</td>\n","      <td>0.384615</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>0.012821</td>\n","      <td>0.141026</td>\n","      <td>0.230769</td>\n","      <td>0.076923</td>\n","      <td>0.038462</td>\n","      <td>0.076923</td>\n","      <td>0.243590</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["region                   0         1         2  ...         4         5         6\n","fertilizer_usage                                ...                              \n","0                 0.115385  0.320513  0.794872  ...  0.243590  0.166667  0.538462\n","1                 0.179487  0.410256  0.846154  ...  0.243590  0.102564  0.500000\n","2                 0.192308  0.307692  0.628205  ...  0.192308  0.141026  0.423077\n","3                 0.153846  0.397436  1.000000  ...  0.371795  0.115385  0.474359\n","4                 0.102564  0.256410  0.525641  ...  0.217949  0.128205  0.384615\n","5                 0.012821  0.141026  0.230769  ...  0.038462  0.076923  0.243590\n","\n","[6 rows x 7 columns]"]},"metadata":{"tags":[]},"execution_count":171}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":509},"id":"e2eV3iG02gFQ","executionInfo":{"status":"ok","timestamp":1615056727714,"user_tz":420,"elapsed":866,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"1e5dd893-25fe-49b7-8d1e-8a44e94834d5"},"source":["\n","plt.figure(figsize = (10,8))\n","ax = seaborn.heatmap(agro_df_3_norm, cmap = 'Blues')\n","\n","plt.tick_params(axis='both', length = 0)\n","\n","plt.title('Heat map of fertilizer usage in different regions')\n","\n","plt.show()"],"execution_count":154,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x576 with 2 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"FPlkJi_32sEr"},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"H_YDfIPnBEjo"},"source":["A bit of exploration with pivot tables "]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":419},"id":"1B2iuRytBJFJ","executionInfo":{"status":"ok","timestamp":1615059012175,"user_tz":420,"elapsed":652,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"74790507-1b53-4104-fd28-4272bd756623"},"source":["agro_df"],"execution_count":155,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>id</th>\n","      <th>water</th>\n","      <th>uv</th>\n","      <th>area</th>\n","      <th>fertilizer_usage</th>\n","      <th>yield</th>\n","      <th>pesticides</th>\n","      <th>region</th>\n","      <th>categories</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>0.072</td>\n","      <td>80.179</td>\n","      <td>9.414</td>\n","      <td>0</td>\n","      <td>29.878</td>\n","      <td>2.231</td>\n","      <td>6</td>\n","      <td>c,b</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>5.413</td>\n","      <td>58.359</td>\n","      <td>9.681</td>\n","      <td>2</td>\n","      <td>53.416</td>\n","      <td>1.810</td>\n","      <td>6</td>\n","      <td>c,b</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>9.731</td>\n","      <td>78.506</td>\n","      <td>7.189</td>\n","      <td>1</td>\n","      <td>63.391</td>\n","      <td>2.455</td>\n","      <td>1</td>\n","      <td>d</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>10.995</td>\n","      <td>69.248</td>\n","      <td>1.738</td>\n","      <td>3</td>\n","      <td>17.984</td>\n","      <td>0.603</td>\n","      <td>2</td>\n","      <td>a</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>2.617</td>\n","      <td>87.658</td>\n","      <td>9.706</td>\n","      <td>1</td>\n","      <td>49.768</td>\n","      <td>2.910</td>\n","      <td>6</td>\n","      <td>c</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>995</th>\n","      <td>995</td>\n","      <td>5.457</td>\n","      <td>70.622</td>\n","      <td>8.163</td>\n","      <td>3</td>\n","      <td>89.809</td>\n","      <td>4.224</td>\n","      <td>2</td>\n","      <td>c</td>\n","    </tr>\n","    <tr>\n","      <th>996</th>\n","      <td>996</td>\n","      <td>6.931</td>\n","      <td>75.326</td>\n","      <td>5.675</td>\n","      <td>0</td>\n","      <td>29.261</td>\n","      <td>1.355</td>\n","      <td>2</td>\n","      <td>d,b,a</td>\n","    </tr>\n","    <tr>\n","      <th>997</th>\n","      <td>997</td>\n","      <td>10.373</td>\n","      <td>78.225</td>\n","      <td>7.378</td>\n","      <td>3</td>\n","      <td>76.608</td>\n","      <td>5.459</td>\n","      <td>2</td>\n","      <td>b</td>\n","    </tr>\n","    <tr>\n","      <th>998</th>\n","      <td>998</td>\n","      <td>9.158</td>\n","      <td>79.257</td>\n","      <td>9.011</td>\n","      <td>2</td>\n","      <td>80.399</td>\n","      <td>5.968</td>\n","      <td>1</td>\n","      <td>d,c,b,a</td>\n","    </tr>\n","    <tr>\n","      <th>999</th>\n","      <td>999</td>\n","      <td>3.316</td>\n","      <td>75.490</td>\n","      <td>5.501</td>\n","      <td>1</td>\n","      <td>43.152</td>\n","      <td>4.220</td>\n","      <td>3</td>\n","      <td>c</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>1000 rows × 9 columns</p>\n","</div>"],"text/plain":["      id   water      uv   area  ...   yield  pesticides  region  categories\n","0      0   0.072  80.179  9.414  ...  29.878       2.231       6         c,b\n","1      1   5.413  58.359  9.681  ...  53.416       1.810       6         c,b\n","2      2   9.731  78.506  7.189  ...  63.391       2.455       1           d\n","3      3  10.995  69.248  1.738  ...  17.984       0.603       2           a\n","4      4   2.617  87.658  9.706  ...  49.768       2.910       6           c\n","..   ...     ...     ...    ...  ...     ...         ...     ...         ...\n","995  995   5.457  70.622  8.163  ...  89.809       4.224       2           c\n","996  996   6.931  75.326  5.675  ...  29.261       1.355       2       d,b,a\n","997  997  10.373  78.225  7.378  ...  76.608       5.459       2           b\n","998  998   9.158  79.257  9.011  ...  80.399       5.968       1     d,c,b,a\n","999  999   3.316  75.490  5.501  ...  43.152       4.220       3           c\n","\n","[1000 rows x 9 columns]"]},"metadata":{"tags":[]},"execution_count":155}]},{"cell_type":"code","metadata":{"id":"NiPUi0kvBMcn","executionInfo":{"status":"ok","timestamp":1615059547667,"user_tz":420,"elapsed":718,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}}},"source":["agro_df_pivot = agro_df.pivot_table(columns = 'region', index = 'fertilizer_usage', values = 'id', aggfunc = 'count')"],"execution_count":173,"outputs":[]},{"cell_type":"code","metadata":{"id":"GlfhgPPOBXF6","executionInfo":{"status":"ok","timestamp":1615059554053,"user_tz":420,"elapsed":528,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}}},"source":["agro_df_pivot_norm = agro_df_pivot/agro_df_pivot.max().max()"],"execution_count":174,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":266},"id":"DUGv56rJBZ75","executionInfo":{"status":"ok","timestamp":1615059560919,"user_tz":420,"elapsed":639,"user":{"displayName":"Ojaswi Dhoubhadel","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjk3OnSPDc1uQhfMW3FBpomzJ6GO3jVp0HlKO4XmUg=s64","userId":"06018964124818252092"}},"outputId":"3034d9ee-52dc-4b75-ba2b-a89574febf87"},"source":["agro_df_pivot_norm"],"execution_count":175,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th>region</th>\n","      <th>0</th>\n","      <th>1</th>\n","      <th>2</th>\n","      <th>3</th>\n","      <th>4</th>\n","      <th>5</th>\n","      <th>6</th>\n","    </tr>\n","    <tr>\n","      <th>fertilizer_usage</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.115385</td>\n","      <td>0.320513</td>\n","      <td>0.794872</td>\n","      <td>0.243590</td>\n","      <td>0.243590</td>\n","      <td>0.166667</td>\n","      <td>0.538462</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0.179487</td>\n","      <td>0.410256</td>\n","      <td>0.846154</td>\n","      <td>0.333333</td>\n","      <td>0.243590</td>\n","      <td>0.102564</td>\n","      <td>0.500000</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.192308</td>\n","      <td>0.307692</td>\n","      <td>0.628205</td>\n","      <td>0.307692</td>\n","      <td>0.192308</td>\n","      <td>0.141026</td>\n","      <td>0.423077</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0.153846</td>\n","      <td>0.397436</td>\n","      <td>1.000000</td>\n","      <td>0.448718</td>\n","      <td>0.371795</td>\n","      <td>0.115385</td>\n","      <td>0.474359</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.102564</td>\n","      <td>0.256410</td>\n","      <td>0.525641</td>\n","      <td>0.192308</td>\n","      <td>0.217949</td>\n","      <td>0.128205</td>\n","      <td>0.384615</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>0.012821</td>\n","      <td>0.141026</td>\n","      <td>0.230769</td>\n","      <td>0.076923</td>\n","      <td>0.038462</td>\n","      <td>0.076923</td>\n","      <td>0.243590</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["region                   0         1         2  ...         4         5         6\n","fertilizer_usage                                ...                              \n","0                 0.115385  0.320513  0.794872  ...  0.243590  0.166667  0.538462\n","1                 0.179487  0.410256  0.846154  ...  0.243590  0.102564  0.500000\n","2                 0.192308  0.307692  0.628205  ...  0.192308  0.141026  0.423077\n","3                 0.153846  0.397436  1.000000  ...  0.371795  0.115385  0.474359\n","4                 0.102564  0.256410  0.525641  ...  0.217949  0.128205  0.384615\n","5                 0.012821  0.141026  0.230769  ...  0.038462  0.076923  0.243590\n","\n","[6 rows x 7 columns]"]},"metadata":{"tags":[]},"execution_count":175}]},{"cell_type":"code","metadata":{"id":"6Dww0O-uDSat"},"source":[""],"execution_count":null,"outputs":[]}]}