Flight_Delay_Prediction.ipynb

{"cells":[{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":["'''\n","Pyspark Final Project\n","Shree Prada: C0887257\n","'''"]},{"cell_type":"code","execution_count":2,"metadata":{"executionInfo":{"elapsed":126,"status":"ok","timestamp":1713024156771,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"N8GF7UddLR8P"},"outputs":[],"source":["# Import SparkSession class from pyspark.sql module\n","from pyspark.sql import SparkSession"]},{"cell_type":"markdown","metadata":{"id":"By73WMNxtWDV"},"source":["### Create spark session"]},{"cell_type":"code","execution_count":3,"metadata":{"executionInfo":{"elapsed":7107,"status":"ok","timestamp":1713024165029,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"ERCuAb3xLXfm"},"outputs":[],"source":["# Create a SparkSession object and assign it to the variable 'spark'\n","spark = SparkSession.builder.appName('Dataframe').getOrCreate()"]},{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":219},"executionInfo":{"elapsed":1779,"status":"ok","timestamp":1713024183814,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"D-VXqpSELj8n","outputId":"aa5fc687-9e64-4a30-e901-d416aa496eb2"},"outputs":[{"data":{"text/html":["\n","            <div>\n","                <p><b>SparkSession - in-memory</b></p>\n","                \n","        <div>\n","            <p><b>SparkContext</b></p>\n","\n","            <p><a href=\"http://a14531a6fb39:4040\">Spark UI</a></p>\n","\n","            <dl>\n","              <dt>Version</dt>\n","                <dd><code>v3.5.1</code></dd>\n","              <dt>Master</dt>\n","                <dd><code>local[*]</code></dd>\n","              <dt>AppName</dt>\n","                <dd><code>Dataframe</code></dd>\n","            </dl>\n","        </div>\n","        \n","            </div>\n","        "],"text/plain":["<pyspark.sql.session.SparkSession at 0x7a63466358a0>"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["spark"]},{"cell_type":"code","execution_count":6,"metadata":{"executionInfo":{"elapsed":12157,"status":"ok","timestamp":1713024219507,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"Yqc2ZoOHLn7W"},"outputs":[],"source":["# Read the CSV file 'flights-larger.csv' into a Spark DataFrame named 'df'\n","\n","df = spark.read \\\n","  .option('header', 'true') \\\n","  .csv('/Spark final project/flights-larger.csv', inferSchema=True)\n"]},{"cell_type":"markdown","metadata":{"id":"UoALDxQrtfzd"},"source":["## Print Schema"]},{"cell_type":"code","execution_count":7,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":140,"status":"ok","timestamp":1713024221353,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"qoIJ-mfBL9PV","outputId":"014bd361-5ecf-4375-b2f8-eadfd74bdd9f"},"outputs":[{"name":"stdout","output_type":"stream","text":["root\n"," |-- mon: integer (nullable = true)\n"," |-- dom: integer (nullable = true)\n"," |-- dow: integer (nullable = true)\n"," |-- carrier: string (nullable = true)\n"," |-- flight: integer (nullable = true)\n"," |-- org: string (nullable = true)\n"," |-- mile: integer (nullable = true)\n"," |-- depart: double (nullable = true)\n"," |-- duration: integer (nullable = true)\n"," |-- delay: string (nullable = true)\n","\n"]}],"source":["# Print the schema of the DataFrame 'df'\n","df.printSchema()"]},{"cell_type":"markdown","metadata":{"id":"VlK9n1uatlFt"},"source":["## Simple data inspection"]},{"cell_type":"code","execution_count":8,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":187},"executionInfo":{"elapsed":150,"status":"ok","timestamp":1713024223666,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"1Xoiq9QKMO3b","outputId":"bce0f8ab-017b-4026-b723-edeeed32a56f"},"outputs":[{"data":{"text/html":["<div style=\"max-width:800px; border: 1px solid var(--colab-border-color);\"><style>\n","      pre.function-repr-contents {\n","        overflow-x: auto;\n","        padding: 8px 12px;\n","        max-height: 500px;\n","      }\n","\n","      pre.function-repr-contents.function-repr-contents-collapsed {\n","        cursor: pointer;\n","        max-height: 100px;\n","      }\n","    </style>\n","    <pre style=\"white-space: initial; background:\n","         var(--colab-secondary-surface-color); padding: 8px 12px;\n","         border-bottom: 1px solid var(--colab-border-color);\"><b>pyspark.sql.dataframe.DataFrame</b><br/>def __init__(jdf: JavaObject, sql_ctx: Union[&#x27;SQLContext&#x27;, &#x27;SparkSession&#x27;])</pre><pre class=\"function-repr-contents function-repr-contents-collapsed\" style=\"\"><a class=\"filepath\" style=\"display:none\" href=\"#\">/usr/local/lib/python3.10/dist-packages/pyspark/sql/dataframe.py</a>A distributed collection of data grouped into named columns.\n","\n",".. versionadded:: 1.3.0\n","\n",".. versionchanged:: 3.4.0\n","    Supports Spark Connect.\n","\n","Examples\n","--------\n","A :class:`DataFrame` is equivalent to a relational table in Spark SQL,\n","and can be created using various functions in :class:`SparkSession`:\n","\n","&gt;&gt;&gt; people = spark.createDataFrame([\n","...     {&quot;deptId&quot;: 1, &quot;age&quot;: 40, &quot;name&quot;: &quot;Hyukjin Kwon&quot;, &quot;gender&quot;: &quot;M&quot;, &quot;salary&quot;: 50},\n","...     {&quot;deptId&quot;: 1, &quot;age&quot;: 50, &quot;name&quot;: &quot;Takuya Ueshin&quot;, &quot;gender&quot;: &quot;M&quot;, &quot;salary&quot;: 100},\n","...     {&quot;deptId&quot;: 2, &quot;age&quot;: 60, &quot;name&quot;: &quot;Xinrong Meng&quot;, &quot;gender&quot;: &quot;F&quot;, &quot;salary&quot;: 150},\n","...     {&quot;deptId&quot;: 3, &quot;age&quot;: 20, &quot;name&quot;: &quot;Haejoon Lee&quot;, &quot;gender&quot;: &quot;M&quot;, &quot;salary&quot;: 200}\n","... ])\n","\n","Once created, it can be manipulated using the various domain-specific-language\n","(DSL) functions defined in: :class:`DataFrame`, :class:`Column`.\n","\n","To select a column from the :class:`DataFrame`, use the apply method:\n","\n","&gt;&gt;&gt; age_col = people.age\n","\n","A more concrete example:\n","\n","&gt;&gt;&gt; # To create DataFrame using SparkSession\n","... department = spark.createDataFrame([\n","...     {&quot;id&quot;: 1, &quot;name&quot;: &quot;PySpark&quot;},\n","...     {&quot;id&quot;: 2, &quot;name&quot;: &quot;ML&quot;},\n","...     {&quot;id&quot;: 3, &quot;name&quot;: &quot;Spark SQL&quot;}\n","... ])\n","\n","&gt;&gt;&gt; people.filter(people.age &gt; 30).join(\n","...     department, people.deptId == department.id).groupBy(\n","...     department.name, &quot;gender&quot;).agg({&quot;salary&quot;: &quot;avg&quot;, &quot;age&quot;: &quot;max&quot;}).show()\n","+-------+------+-----------+--------+\n","|   name|gender|avg(salary)|max(age)|\n","+-------+------+-----------+--------+\n","|     ML|     F|      150.0|      60|\n","|PySpark|     M|       75.0|      50|\n","+-------+------+-----------+--------+\n","\n","Notes\n","-----\n","A DataFrame should only be created as described above. It should not be directly\n","created via using the constructor.</pre>\n","      <script>\n","      if (google.colab.kernel.accessAllowed && google.colab.files && google.colab.files.view) {\n","        for (const element of document.querySelectorAll('.filepath')) {\n","          element.style.display = 'block'\n","          element.onclick = (event) => {\n","            event.preventDefault();\n","            event.stopPropagation();\n","            google.colab.files.view(element.textContent, 80);\n","          };\n","        }\n","      }\n","      for (const element of document.querySelectorAll('.function-repr-contents')) {\n","        element.onclick = (event) => {\n","          event.preventDefault();\n","          event.stopPropagation();\n","          element.classList.toggle('function-repr-contents-collapsed');\n","        };\n","      }\n","      </script>\n","      </div>"],"text/plain":["pyspark.sql.dataframe.DataFrame"]},"execution_count":8,"metadata":{},"output_type":"execute_result"}],"source":["type(df) #dataframe is a data structure"]},{"cell_type":"code","execution_count":9,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":4,"status":"ok","timestamp":1713024226119,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"ktvKcCENMrMX","outputId":"252a722c-bfa5-4db6-8c2e-4548395162b3"},"outputs":[{"data":{"text/plain":["['mon',\n"," 'dom',\n"," 'dow',\n"," 'carrier',\n"," 'flight',\n"," 'org',\n"," 'mile',\n"," 'depart',\n"," 'duration',\n"," 'delay']"]},"execution_count":9,"metadata":{},"output_type":"execute_result"}],"source":["# Get a list of column names from the DataFrame 'df'\n","column_names = df.columns"]},{"cell_type":"code","execution_count":41,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3,"status":"ok","timestamp":1713025823897,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"Vw678IPFS1zF","outputId":"a0fea5cc-9559-4866-f0c0-d2be3e002c32"},"outputs":[{"data":{"text/plain":["[('mon', 'int'),\n"," ('dom', 'int'),\n"," ('dow', 'int'),\n"," ('carrier', 'string'),\n"," ('flight', 'int'),\n"," ('org', 'string'),\n"," ('mile', 'int'),\n"," ('depart', 'double'),\n"," ('duration', 'int'),\n"," ('delay', 'string')]"]},"execution_count":41,"metadata":{},"output_type":"execute_result"}],"source":["# Get a list of tuples containing column names and data types for 'df'\n","df.dtypes"]},{"cell_type":"code","execution_count":43,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":144,"status":"ok","timestamp":1713025913608,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"kgWMT9pJMxxZ","outputId":"93fb9ddf-9bf2-4958-8dc3-2de0181504cb"},"outputs":[{"data":{"text/plain":["Row(mon=10, dom=10, dow=1, carrier='OO', flight=5836, org='ORD', mile=157, depart=8.18, duration=51, delay='27')"]},"execution_count":43,"metadata":{},"output_type":"execute_result"}],"source":["# Get the first row from DataFrame 'df'\n","df.head()"]},{"cell_type":"code","execution_count":44,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":149,"status":"ok","timestamp":1713025930659,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"A1JqsfMkTSz8","outputId":"121e110d-f61e-4ecc-84a5-fea748220d5d"},"outputs":[{"data":{"text/plain":["[Row(mon=10, dom=10, dow=1, carrier='OO', flight=5836, org='ORD', mile=157, depart=8.18, duration=51, delay='27'),\n"," Row(mon=1, dom=4, dow=1, carrier='OO', flight=5866, org='ORD', mile=466, depart=15.5, duration=102, delay='NA'),\n"," Row(mon=11, dom=22, dow=1, carrier='OO', flight=6016, org='ORD', mile=738, depart=7.17, duration=127, delay='-19'),\n"," Row(mon=2, dom=14, dow=5, carrier='B6', flight=199, org='JFK', mile=2248, depart=21.17, duration=365, delay='60')]"]},"execution_count":44,"metadata":{},"output_type":"execute_result"}],"source":["#Return first n rows()\n","df.take(4)"]},{"cell_type":"code","execution_count":42,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":326,"status":"ok","timestamp":1713025853437,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"8EQ2yErKS_pk","outputId":"d65785d3-ac89-4999-9bc9-c0e3978ef2f1"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+---+---+-------+------+---+----+------+--------+-----+\n","|mon|dom|dow|carrier|flight|org|mile|depart|duration|delay|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","| 10| 10|  1|     OO|  5836|ORD| 157|  8.18|      51|   27|\n","|  1|  4|  1|     OO|  5866|ORD| 466|  15.5|     102|   NA|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","only showing top 2 rows\n","\n"]}],"source":["# Display the first 2 rows of DataFrame 'df'\n","df.show(2)"]},{"cell_type":"code","execution_count":45,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5287,"status":"ok","timestamp":1713025955614,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"nRtpE6yETYMW","outputId":"79939ded-22d6-41e9-88f7-84fdfba2d22f"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-------+------------------+-----------------+------------------+-------+------------------+------+-----------------+------------------+------------------+-----------------+\n","|summary|               mon|              dom|               dow|carrier|            flight|   org|             mile|            depart|          duration|            delay|\n","+-------+------------------+-----------------+------------------+-------+------------------+------+-----------------+------------------+------------------+-----------------+\n","|  count|            275000|           275000|            275000| 275000|            275000|275000|           275000|            275000|            275000|           275000|\n","|   mean|           5.24232|15.71406909090909| 2.946090909090909|   NULL|2063.0542763636363|  NULL|881.2222872727273|14.124930981817384|151.64103636363637|28.34773064280709|\n","| stddev|3.4273573316203576|8.805568383848067|1.9635141531217672|   NULL| 2185.852169684581|  NULL|700.5178890821038| 4.683189503417866|  87.0845640768675|54.01489538326629|\n","|    min|                 0|                1|                 0|     AA|                 1|   JFK|               11|              0.12|                14|               -1|\n","|    max|                11|               31|                 6|     WN|              6941|   TUS|             4243|             23.98|               605|               NA|\n","+-------+------------------+-----------------+------------------+-------+------------------+------+-----------------+------------------+------------------+-----------------+\n","\n","None\n"]}],"source":["# Compute summary statistics for the numerical columns in 'df' and display them\n","print(df.describe().show())"]},{"cell_type":"code","execution_count":11,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":163,"status":"ok","timestamp":1713024231765,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"Va_x6BXyM92C","outputId":"e492d598-6b22-472d-adab-b83e5befc57c"},"outputs":[{"data":{"text/plain":["DataFrame[carrier: string]"]},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":["# Selecting the 'carrier' column from the DataFrame\n","df.select('carrier')"]},{"cell_type":"code","execution_count":12,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":592,"status":"ok","timestamp":1713024233636,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"5ME3_-UFNEfM","outputId":"f51a8a04-bdfe-4d28-b60a-17bda81a8188"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-------+\n","|carrier|\n","+-------+\n","|     OO|\n","|     OO|\n","|     OO|\n","|     B6|\n","|     WN|\n","|     B6|\n","|     B6|\n","|     UA|\n","|     US|\n","|     AA|\n","|     B6|\n","|     AA|\n","|     B6|\n","|     AA|\n","|     UA|\n","|     OH|\n","|     UA|\n","|     OH|\n","|     UA|\n","|     AA|\n","+-------+\n","only showing top 20 rows\n","\n"]}],"source":["# Selecting the 'carrier' column from the DataFrame and displaying its contents\n","df.select('carrier').show()"]},{"cell_type":"code","execution_count":13,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":533,"status":"ok","timestamp":1713024237612,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"08xAdK_5NJh5","outputId":"a9ab378b-644c-419c-e1b7-e74fb07a32d0"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-------+---+\n","|carrier|dom|\n","+-------+---+\n","|     OO| 10|\n","|     OO|  4|\n","|     OO| 22|\n","|     B6| 14|\n","|     WN| 25|\n","|     B6| 28|\n","|     B6| 28|\n","|     UA| 19|\n","|     US|  5|\n","|     AA| 27|\n","|     B6| 20|\n","|     AA|  3|\n","|     B6| 26|\n","|     AA|  9|\n","|     UA|  8|\n","|     OH| 10|\n","|     UA| 14|\n","|     OH|  8|\n","|     UA| 14|\n","|     AA|  2|\n","+-------+---+\n","only showing top 20 rows\n","\n"]}],"source":["# Selecting the columns 'carrier' and 'dom' from the DataFrame and displaying their contents\n","df.select(['carrier', 'dom']).show()"]},{"cell_type":"code","execution_count":14,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":10946,"status":"ok","timestamp":1713024250846,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"mllXNK8xNfG-","outputId":"1c9911cf-5fab-42bc-9962-0aa8f25b039c"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-------+------------------+-----------------+------------------+-------+------------------+------+-----------------+------------------+------------------+-----------------+\n","|summary|               mon|              dom|               dow|carrier|            flight|   org|             mile|            depart|          duration|            delay|\n","+-------+------------------+-----------------+------------------+-------+------------------+------+-----------------+------------------+------------------+-----------------+\n","|  count|            275000|           275000|            275000| 275000|            275000|275000|           275000|            275000|            275000|           275000|\n","|   mean|           5.24232|15.71406909090909| 2.946090909090909|   NULL|2063.0542763636363|  NULL|881.2222872727273|14.124930981817384|151.64103636363637|28.34773064280709|\n","| stddev|3.4273573316203576|8.805568383848067|1.9635141531217672|   NULL| 2185.852169684581|  NULL|700.5178890821038| 4.683189503417866|  87.0845640768675|54.01489538326629|\n","|    min|                 0|                1|                 0|     AA|                 1|   JFK|               11|              0.12|                14|               -1|\n","|    max|                11|               31|                 6|     WN|              6941|   TUS|             4243|             23.98|               605|               NA|\n","+-------+------------------+-----------------+------------------+-------+------------------+------+-----------------+------------------+------------------+-----------------+\n","\n"]}],"source":["# Generating descriptive statistics for all numerical columns in the DataFrame and displaying the results\n","df.describe().show()"]},{"cell_type":"code","execution_count":47,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":741,"status":"ok","timestamp":1713026004409,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"1QzNXi4ETipG","outputId":"202a88e4-ead8-417c-c3eb-967e540903eb"},"outputs":[{"data":{"text/plain":["275000"]},"execution_count":47,"metadata":{},"output_type":"execute_result"}],"source":["# Counting the number of rows in the DataFrame\n","df.count()"]},{"cell_type":"code","execution_count":48,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5738,"status":"ok","timestamp":1713026101938,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"lTY-pHXWT75E","outputId":"297e943a-181f-4a08-b5eb-239f54db67fc"},"outputs":[{"name":"stdout","output_type":"stream","text":["275000\n"]}],"source":["# Counting the number of distinct rows in the DataFrame\n","print(df.distinct().count())"]},{"cell_type":"code","execution_count":50,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":157,"status":"ok","timestamp":1713026120711,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"VYHzokG3UBis","outputId":"c12a41f9-e63c-434f-8854-c06078484a9b"},"outputs":[{"name":"stdout","output_type":"stream","text":["== Physical Plan ==\n","FileScan csv [mon#17,dom#18,dow#19,carrier#20,flight#21,org#22,mile#23,depart#24,duration#25,delay#26] Batched: false, DataFilters: [], Format: CSV, Location: InMemoryFileIndex(1 paths)[file:/content/drive/MyDrive/Spark final project/flights-larger.csv], PartitionFilters: [], PushedFilters: [], ReadSchema: struct<mon:int,dom:int,dow:int,carrier:string,flight:int,org:string,mile:int,depart:double,durati...\n","\n","\n"]}],"source":["# Printing the execution plan of DataFrame operations, including both physical and logical plans\n","df.explain()"]},{"cell_type":"code","execution_count":15,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":161,"status":"ok","timestamp":1713024253805,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"rjS-Ur7iN8xe","outputId":"bda10348-7eaa-4b66-8c49-8e640bd9c69d"},"outputs":[{"data":{"text/plain":["DataFrame[mon: int, dom: int, dow: int, carrier: string, flight: int, org: string, mile: int, depart: double, duration: int, delay: string, mon after 2: int]"]},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":["# Adding a new column 'mon after 2' to the DataFrame by adding 2 to the values in the 'mon' column\n","df.withColumn('mon after 2', df['mon'] + 2)"]},{"cell_type":"code","execution_count":51,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":441,"status":"ok","timestamp":1713026197964,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"6hYDSwrJUP3s","outputId":"f8c1528f-4ba5-4c10-c71a-0fe985f89620"},"outputs":[{"name":"stdout","output_type":"stream","text":["+------+\n","|flight|\n","+------+\n","|  5836|\n","|  5866|\n","|  6016|\n","|   199|\n","|  1675|\n","|   377|\n","|   904|\n","|   820|\n","|  2175|\n","|  1240|\n","+------+\n","only showing top 10 rows\n","\n"]}],"source":["# Selecting and displaying the 'flight' column from the DataFrame, showing the first 10 entries\n","df.select(\"flight\").show(10)"]},{"cell_type":"code","execution_count":52,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":335,"status":"ok","timestamp":1713026258216,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"sMWyZyD8UaGT","outputId":"bbc4f4a1-e89c-40a6-c9d9-fabc94031569"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+---+------+-----+\n","|mon|dom|flight|delay|\n","+---+---+------+-----+\n","| 10| 10|  5836|   27|\n","|  1|  4|  5866|   NA|\n","| 11| 22|  6016|  -19|\n","|  2| 14|   199|   60|\n","|  5| 25|  1675|   22|\n","|  3| 28|   377|   70|\n","|  5| 28|   904|   47|\n","|  1| 19|   820|  135|\n","|  8|  5|  2175|  -10|\n","|  5| 27|  1240|  -11|\n","+---+---+------+-----+\n","only showing top 10 rows\n","\n"]}],"source":["# Selecting and displaying the columns 'mon', 'dom', 'flight', and 'delay' from the DataFrame, showing the first 10 entries\n","df.select(\"mon\", \"dom\", \"flight\", \"delay\").show(10)"]},{"cell_type":"code","execution_count":16,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":575,"status":"ok","timestamp":1713024256499,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"2cODsRqVOSkz","outputId":"9c5553b0-8750-4a5e-a248-b7b469c9531c"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+---+---+-------+------+---+----+------+--------+-----+-----------+\n","|mon|dom|dow|carrier|flight|org|mile|depart|duration|delay|mon after 2|\n","+---+---+---+-------+------+---+----+------+--------+-----+-----------+\n","| 10| 10|  1|     OO|  5836|ORD| 157|  8.18|      51|   27|         12|\n","|  1|  4|  1|     OO|  5866|ORD| 466|  15.5|     102|   NA|          3|\n","| 11| 22|  1|     OO|  6016|ORD| 738|  7.17|     127|  -19|         13|\n","|  2| 14|  5|     B6|   199|JFK|2248| 21.17|     365|   60|          4|\n","|  5| 25|  3|     WN|  1675|SJC| 386| 12.92|      85|   22|          7|\n","|  3| 28|  1|     B6|   377|LGA|1076| 13.33|     182|   70|          5|\n","|  5| 28|  6|     B6|   904|ORD| 740|  9.58|     130|   47|          7|\n","|  1| 19|  2|     UA|   820|SFO| 679| 12.75|     123|  135|          3|\n","|  8|  5|  5|     US|  2175|LGA| 214|  13.0|      71|  -10|         10|\n","|  5| 27|  5|     AA|  1240|ORD|1197| 14.42|     195|  -11|          7|\n","|  8| 20|  6|     B6|   119|JFK|1182| 14.67|     198|   20|         10|\n","|  2|  3|  1|     AA|  1881|JFK|1090| 15.92|     200|   -9|          4|\n","|  8| 26|  5|     B6|    35|JFK|1028| 20.58|     193|  102|         10|\n","|  4|  9|  5|     AA|   336|ORD| 733|  20.5|     125|   32|          6|\n","|  3|  8|  2|     UA|   678|ORD| 733| 10.95|     129|   55|          5|\n","|  8| 10|  3|     OH|  6347|LGA| 292| 11.75|     102|    8|         10|\n","|  8| 14|  0|     UA|   624|ORD| 612| 17.92|     109|   57|         10|\n","|  4|  8|  4|     OH|  5585|JFK| 301| 13.25|      88|   23|          6|\n","|  1| 14|  4|     UA|  1524|SFO| 414| 14.87|      91|   27|          3|\n","|  1|  2|  6|     AA|  1341|ORD|1846|   7.5|     275|   26|          3|\n","+---+---+---+-------+------+---+----+------+--------+-----+-----------+\n","only showing top 20 rows\n","\n"]}],"source":["# Adding a new column 'mon after 2' to the DataFrame by adding 2 to the values in the 'mon' column and displaying the DataFrame\n","df.withColumn('mon after 2', df['mon'] + 2).show()"]},{"cell_type":"code","execution_count":17,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":140,"status":"ok","timestamp":1713024259666,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"xvQ1YysBOY0H","outputId":"3e5cbbcc-404d-4e74-f1e5-ebaa516f302c"},"outputs":[{"data":{"text/plain":["DataFrame[mon: int, dom: int, dow: int, carrier: string, flight: int, org: string, mile: int, depart: double, duration: int, delay: string]"]},"execution_count":17,"metadata":{},"output_type":"execute_result"}],"source":["# Dropping the column 'mon after 2' from the DataFrame\n","df.drop('mon after 2')"]},{"cell_type":"code","execution_count":18,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":392,"status":"ok","timestamp":1713024263013,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"qtAfviP8Otdr","outputId":"fdffa3bc-67d1-4cf0-cf96-29ae5cae66b9"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+---+---+-------+------+---+----+------+--------+-----+\n","|mon|dom|dow|carrier|flight|org|mile|depart|duration|delay|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","| 10| 10|  1|     OO|  5836|ORD| 157|  8.18|      51|   27|\n","|  1|  4|  1|     OO|  5866|ORD| 466|  15.5|     102|   NA|\n","| 11| 22|  1|     OO|  6016|ORD| 738|  7.17|     127|  -19|\n","|  2| 14|  5|     B6|   199|JFK|2248| 21.17|     365|   60|\n","|  5| 25|  3|     WN|  1675|SJC| 386| 12.92|      85|   22|\n","|  3| 28|  1|     B6|   377|LGA|1076| 13.33|     182|   70|\n","|  5| 28|  6|     B6|   904|ORD| 740|  9.58|     130|   47|\n","|  1| 19|  2|     UA|   820|SFO| 679| 12.75|     123|  135|\n","|  8|  5|  5|     US|  2175|LGA| 214|  13.0|      71|  -10|\n","|  5| 27|  5|     AA|  1240|ORD|1197| 14.42|     195|  -11|\n","|  8| 20|  6|     B6|   119|JFK|1182| 14.67|     198|   20|\n","|  2|  3|  1|     AA|  1881|JFK|1090| 15.92|     200|   -9|\n","|  8| 26|  5|     B6|    35|JFK|1028| 20.58|     193|  102|\n","|  4|  9|  5|     AA|   336|ORD| 733|  20.5|     125|   32|\n","|  3|  8|  2|     UA|   678|ORD| 733| 10.95|     129|   55|\n","|  8| 10|  3|     OH|  6347|LGA| 292| 11.75|     102|    8|\n","|  8| 14|  0|     UA|   624|ORD| 612| 17.92|     109|   57|\n","|  4|  8|  4|     OH|  5585|JFK| 301| 13.25|      88|   23|\n","|  1| 14|  4|     UA|  1524|SFO| 414| 14.87|      91|   27|\n","|  1|  2|  6|     AA|  1341|ORD|1846|   7.5|     275|   26|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","only showing top 20 rows\n","\n"]}],"source":["df.show()"]},{"cell_type":"markdown","metadata":{"id":"ZtVqVYzdnonP"},"source":["## Renaming Columns"]},{"cell_type":"code","execution_count":19,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":336,"status":"ok","timestamp":1713024265951,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"8MV6BOqpOywh","outputId":"9e758f76-d1ba-4906-8b99-25bdaae31c02"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+---+---+-------+------+---+----+------+--------+-----+\n","|mon|dom|dow|carrier|flight|org|mile|depart|duration|delay|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","| 10| 10|  1|     OO|  5836|ORD| 157|  8.18|      51|   27|\n","|  1|  4|  1|     OO|  5866|ORD| 466|  15.5|     102|   NA|\n","| 11| 22|  1|     OO|  6016|ORD| 738|  7.17|     127|  -19|\n","|  2| 14|  5|     B6|   199|JFK|2248| 21.17|     365|   60|\n","|  5| 25|  3|     WN|  1675|SJC| 386| 12.92|      85|   22|\n","|  3| 28|  1|     B6|   377|LGA|1076| 13.33|     182|   70|\n","|  5| 28|  6|     B6|   904|ORD| 740|  9.58|     130|   47|\n","|  1| 19|  2|     UA|   820|SFO| 679| 12.75|     123|  135|\n","|  8|  5|  5|     US|  2175|LGA| 214|  13.0|      71|  -10|\n","|  5| 27|  5|     AA|  1240|ORD|1197| 14.42|     195|  -11|\n","|  8| 20|  6|     B6|   119|JFK|1182| 14.67|     198|   20|\n","|  2|  3|  1|     AA|  1881|JFK|1090| 15.92|     200|   -9|\n","|  8| 26|  5|     B6|    35|JFK|1028| 20.58|     193|  102|\n","|  4|  9|  5|     AA|   336|ORD| 733|  20.5|     125|   32|\n","|  3|  8|  2|     UA|   678|ORD| 733| 10.95|     129|   55|\n","|  8| 10|  3|     OH|  6347|LGA| 292| 11.75|     102|    8|\n","|  8| 14|  0|     UA|   624|ORD| 612| 17.92|     109|   57|\n","|  4|  8|  4|     OH|  5585|JFK| 301| 13.25|      88|   23|\n","|  1| 14|  4|     UA|  1524|SFO| 414| 14.87|      91|   27|\n","|  1|  2|  6|     AA|  1341|ORD|1846|   7.5|     275|   26|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","only showing top 20 rows\n","\n"]}],"source":["# Renaming the column 'MMon' to 'mon' in the DataFrame and displaying the updated DataFrame\n","df.withColumnRenamed('MMon', 'mon').show()"]},{"cell_type":"markdown","metadata":{"id":"Rvm71T_dWAXr"},"source":["## 'isin' Operation"]},{"cell_type":"code","execution_count":53,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":512,"status":"ok","timestamp":1713026617224,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"OCLuITeUVURr","outputId":"bf9ba530-45b3-48a9-b9e1-34c53f8b2a9c"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+---+---+-------+------+---+----+------+--------+-----+\n","|mon|dom|dow|carrier|flight|org|mile|depart|duration|delay|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","| 10| 10|  1|     OO|  5836|ORD| 157|  8.18|      51|   27|\n","|  1|  4|  1|     OO|  5866|ORD| 466|  15.5|     102|   NA|\n","| 11| 22|  1|     OO|  6016|ORD| 738|  7.17|     127|  -19|\n","|  2| 14|  5|     B6|   199|JFK|2248| 21.17|     365|   60|\n","|  3| 28|  1|     B6|   377|LGA|1076| 13.33|     182|   70|\n","|  5| 28|  6|     B6|   904|ORD| 740|  9.58|     130|   47|\n","|  8| 20|  6|     B6|   119|JFK|1182| 14.67|     198|   20|\n","|  8| 26|  5|     B6|    35|JFK|1028| 20.58|     193|  102|\n","|  2| 22|  6|     OO|  6669|ORD|1186| 10.25|     194|   21|\n","|  0| 16|  3|     OO|  6026|SFO| 372| 14.77|      88|  -14|\n","|  0|  1|  2|     OO|  5886|ORD|  84| 16.83|      46|   NA|\n","|  0|  3|  4|     OO|  5655|SMF|  86|  10.7|      54|   42|\n","|  5|  8|  0|     OO|  3897|ORD|1249| 13.25|     216|  194|\n","|  2| 10|  1|     B6|   347|JFK|1041|  13.0|     178|   24|\n","| 11| 21|  0|     B6|   174|SJC|2569| 21.92|     321|   NA|\n","|  0| 18|  5|     OO|  6134|SFO| 363|  7.23|      80|   24|\n","|  4| 20|  2|     B6|   221|JFK|2465|  9.42|     361|   -9|\n","|  0|  7|  1|     B6|   904|ORD| 740|  9.42|     130|    4|\n","|  7| 14|  4|     B6|   399|LGA| 950| 21.08|     158|  101|\n","|  3|  2|  3|     B6|   395|LGA| 950| 14.92|     176|   88|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","only showing top 20 rows\n","\n"]}],"source":["# Selecting and displaying rows from the DataFrame where the 'carrier' column contains values \"OO\" or \"B6\"\n","df[df.carrier.isin(\"OO\", \"B6\")].show()"]},{"cell_type":"markdown","metadata":{"id":"danh6lP3WVns"},"source":["# Like Operation"]},{"cell_type":"code","execution_count":54,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":331,"status":"ok","timestamp":1713026924650,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"zY0YbLHdWZ9b","outputId":"f8cb98b0-e294-48cd-878a-2521799f7d6f"},"outputs":[{"name":"stdout","output_type":"stream","text":["+------+---+------------+\n","|flight|org|org LIKE %G%|\n","+------+---+------------+\n","|  5836|ORD|       false|\n","|  5866|ORD|       false|\n","|  6016|ORD|       false|\n","|   199|JFK|       false|\n","|  1675|SJC|       false|\n","|   377|LGA|        true|\n","|   904|ORD|       false|\n","|   820|SFO|       false|\n","|  2175|LGA|        true|\n","|  1240|ORD|       false|\n","|   119|JFK|       false|\n","|  1881|JFK|       false|\n","|    35|JFK|       false|\n","|   336|ORD|       false|\n","|   678|ORD|       false|\n","+------+---+------------+\n","only showing top 15 rows\n","\n"]}],"source":["# Selecting the 'flight', 'org', and a Boolean indicating if 'org' contains the letter \"G\" from the DataFrame and displaying the first 15 entries\n","df.select(\"flight\", \"org\", df.org.like(\"%G%\")).show(15)"]},{"cell_type":"markdown","metadata":{"id":"F20UA--SXV4W"},"source":["## StartsWith - EndsWith Operation"]},{"cell_type":"code","execution_count":55,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":287,"status":"ok","timestamp":1713027066936,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"NiPZS52-XXL7","outputId":"909d5bdc-f5fd-4743-c9ad-1732f26f2106"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+------+------------------+\n","|org|flight|startswith(org, O)|\n","+---+------+------------------+\n","|ORD|  5836|              true|\n","|ORD|  5866|              true|\n","|ORD|  6016|              true|\n","|JFK|   199|             false|\n","|SJC|  1675|             false|\n","+---+------+------------------+\n","only showing top 5 rows\n","\n"]}],"source":["# Selecting the 'org', 'flight', and a Boolean indicating if 'org' starts with \"O\" from the DataFrame and displaying the first 5 entries\n","df.select(\"org\", \"flight\", df.org.startswith(\"O\")).show(5)"]},{"cell_type":"markdown","metadata":{"id":"5aSY06IdYWbb"},"source":["## GroupBy Operations"]},{"cell_type":"code","execution_count":56,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1963,"status":"ok","timestamp":1713027309286,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"jkgPgUkkYZkT","outputId":"4c73fe02-2091-4148-8bb6-5237ba059cfe"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+------+\n","|org| count|\n","+---+------+\n","|SJC| 16701|\n","|LGA| 27826|\n","|SMF| 16854|\n","|SFO| 52424|\n","|ORD|106018|\n","|TUS|  6181|\n","|JFK| 43468|\n","|OGG|  5528|\n","+---+------+\n","\n"]}],"source":["# Grouping the DataFrame by the 'org' column and counting the occurrences of each value, then displaying the results\n","df.groupBy(\"org\").count().show(10)"]},{"cell_type":"markdown","metadata":{"id":"VtlFm4GXYray"},"source":["## Filter Operation"]},{"cell_type":"code","execution_count":58,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":425,"status":"ok","timestamp":1713027398745,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"E6l0F5yDYtBb","outputId":"76e54a2a-779e-4446-cfa9-489afa849632"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+---+---+-------+------+---+----+------+--------+-----+\n","|mon|dom|dow|carrier|flight|org|mile|depart|duration|delay|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","| 10| 10|  1|     OO|  5836|ORD| 157|  8.18|      51|   27|\n","|  1|  4|  1|     OO|  5866|ORD| 466|  15.5|     102|   NA|\n","| 11| 22|  1|     OO|  6016|ORD| 738|  7.17|     127|  -19|\n","|  5| 28|  6|     B6|   904|ORD| 740|  9.58|     130|   47|\n","|  5| 27|  5|     AA|  1240|ORD|1197| 14.42|     195|  -11|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","only showing top 5 rows\n","\n"]}],"source":["# Filtering the DataFrame to only include rows where the value in the 'org' column is 'ORD', then displaying the first 5 entries\n","df.filter(df.org == 'ORD').show(5)"]},{"cell_type":"markdown","metadata":{"id":"LV6PndjhZGQt"},"source":["## Running SQL commands in Spark"]},{"cell_type":"code","execution_count":59,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":316,"status":"ok","timestamp":1713027465366,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"uKWxpHrPZCk6","outputId":"e56d2d96-7a8f-48a8-9aa3-43491afc4852"},"outputs":[{"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.10/dist-packages/pyspark/sql/dataframe.py:329: FutureWarning: Deprecated in 2.0, use createOrReplaceTempView instead.\n","  warnings.warn(\"Deprecated in 2.0, use createOrReplaceTempView instead.\", FutureWarning)\n"]}],"source":["# Registering the DataFrame as a temporary table named \"df_temp\"\n","df.registerTempTable(\"df_temp\")"]},{"cell_type":"code","execution_count":60,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":329,"status":"ok","timestamp":1713027544719,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"i_lDqu7vZO9K","outputId":"108ddd68-f795-42a5-9f48-f9f34707011e"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+---+---+-------+------+---+----+------+--------+-----+\n","|mon|dom|dow|carrier|flight|org|mile|depart|duration|delay|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","| 10| 10|  1|     OO|  5836|ORD| 157|  8.18|      51|   27|\n","|  1|  4|  1|     OO|  5866|ORD| 466|  15.5|     102|   NA|\n","| 11| 22|  1|     OO|  6016|ORD| 738|  7.17|     127|  -19|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","only showing top 3 rows\n","\n"]}],"source":["# Executing a SQL query to select all columns from the temporary table \"df_temp\" and displaying the first 3 rows\n","spark.sql(\"SELECT * FROM df_temp\").show(3)"]},{"cell_type":"code","execution_count":61,"metadata":{"executionInfo":{"elapsed":1151,"status":"ok","timestamp":1713033337974,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"4CVJkU8ivkfL"},"outputs":[],"source":["import matplotlib.pyplot as plt\n","import seaborn as sns"]},{"cell_type":"markdown","metadata":{"id":"CjMYdGl7vw8T"},"source":[]},{"cell_type":"markdown","metadata":{"id":"zoyq4Cu4RVmN"},"source":["#**Flight Delay Prediction**"]},{"cell_type":"code","execution_count":20,"metadata":{"executionInfo":{"elapsed":922,"status":"ok","timestamp":1713024270095,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"bJUY6YVQRe4s"},"outputs":[],"source":["import numpy as np  # Importing NumPy library\n","import pandas as pd  # Importing Pandas library\n","import os  # Importing os module for operating system functionalities\n","import pyspark  # Importing PySpark library\n","from pyspark.sql import SparkSession  # Importing SparkSession from PySpark SQL module\n","from pyspark.sql.types import StructType, StructField, IntegerType, StringType  # Importing data types from PySpark SQL module\n","\n","from pyspark.sql.functions import round  # Importing round function from PySpark SQL functions module\n","from pyspark.ml.feature import StringIndexer  # Importing StringIndexer for string indexing\n","from pyspark.ml.feature import VectorAssembler  # Importing VectorAssembler for vectorization of features\n","from pyspark.ml.classification import DecisionTreeClassifier  # Importing DecisionTreeClassifier for classification\n","from pyspark.ml.classification import LogisticRegression  # Importing LogisticRegression for classification\n","from pyspark.ml.evaluation import MulticlassClassificationEvaluator, BinaryClassificationEvaluator  # Importing evaluators for model evaluation"]},{"cell_type":"code","execution_count":21,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":219},"executionInfo":{"elapsed":167,"status":"ok","timestamp":1713024273406,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"02PdeypNRhWj","outputId":"682ee2ad-cc2b-43f5-a730-6e38505d1f9a"},"outputs":[{"data":{"text/html":["\n","            <div>\n","                <p><b>SparkSession - in-memory</b></p>\n","                \n","        <div>\n","            <p><b>SparkContext</b></p>\n","\n","            <p><a href=\"http://a14531a6fb39:4040\">Spark UI</a></p>\n","\n","            <dl>\n","              <dt>Version</dt>\n","                <dd><code>v3.5.1</code></dd>\n","              <dt>Master</dt>\n","                <dd><code>local[*]</code></dd>\n","              <dt>AppName</dt>\n","                <dd><code>Dataframe</code></dd>\n","            </dl>\n","        </div>\n","        \n","            </div>\n","        "],"text/plain":["<pyspark.sql.session.SparkSession at 0x7a63466358a0>"]},"execution_count":21,"metadata":{},"output_type":"execute_result"}],"source":["# Creating a SparkSession with specified configurations\n","spark = SparkSession.builder \\\n","                    .master('local[*]') \\  # Running Spark locally using all available cores\n","                    .appName('MachineLearning with PySpark') \\  # Setting the application name\n","                    .getOrCreate()  # Creating or getting an existing SparkSession\n","spark"]},{"cell_type":"code","execution_count":22,"metadata":{"executionInfo":{"elapsed":2358,"status":"ok","timestamp":1713024280447,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"zPmkMCc4Rqp5"},"outputs":[],"source":["# Reading a CSV file into a DataFrame with specified options\n","flights_df = spark.read.csv('/Spark final project/flights-larger.csv',  # Path to the CSV file\n","                             sep=',',  # Separator for the CSV file\n","                             header=True,  # Treating the first row as header\n","                             inferSchema=True,  # Inferring the schema of the DataFrame\n","                             nullValue='NA')  # Specifying the null value for the DataFrame\n"]},{"cell_type":"code","execution_count":23,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1637,"status":"ok","timestamp":1713024288352,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"Glh9-aRlR3-i","outputId":"dbe1aced-c6ee-42ea-b5cb-e78e7d7b5938"},"outputs":[{"name":"stdout","output_type":"stream","text":["The data contain 275000 records.\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","|mon|dom|dow|carrier|flight|org|mile|depart|duration|delay|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","| 10| 10|  1|     OO|  5836|ORD| 157|  8.18|      51|   27|\n","|  1|  4|  1|     OO|  5866|ORD| 466|  15.5|     102| NULL|\n","| 11| 22|  1|     OO|  6016|ORD| 738|  7.17|     127|  -19|\n","|  2| 14|  5|     B6|   199|JFK|2248| 21.17|     365|   60|\n","|  5| 25|  3|     WN|  1675|SJC| 386| 12.92|      85|   22|\n","+---+---+---+-------+------+---+----+------+--------+-----+\n","only showing top 5 rows\n","\n"]}],"source":["# Printing the number of records in the DataFrame\n","print(\"The data contain %d records.\" % flights_df.count())\n","\n","# Displaying the first 5 rows of the DataFrame\n","flights_df.show(5)"]},{"cell_type":"code","execution_count":25,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":139,"status":"ok","timestamp":1713024342990,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"ccFIxrIINPBG","outputId":"f76fc213-0097-49ba-92a4-fd1f83223bb4"},"outputs":[{"name":"stdout","output_type":"stream","text":["Schema:\n","root\n"," |-- mon: integer (nullable = true)\n"," |-- dom: integer (nullable = true)\n"," |-- dow: integer (nullable = true)\n"," |-- carrier: string (nullable = true)\n"," |-- flight: integer (nullable = true)\n"," |-- org: string (nullable = true)\n"," |-- mile: integer (nullable = true)\n"," |-- depart: double (nullable = true)\n"," |-- duration: integer (nullable = true)\n"," |-- delay: integer (nullable = true)\n","\n"]}],"source":["# Printing the schema of the DataFrame\n","print(\"Schema:\")\n","flights_df.printSchema()"]},{"cell_type":"code","execution_count":24,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":141,"status":"ok","timestamp":1713024296988,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"RoOZA3kaSJUo","outputId":"349077d8-68ea-471a-dee1-831fc034f30a"},"outputs":[{"data":{"text/plain":["[('mon', 'int'),\n"," ('dom', 'int'),\n"," ('dow', 'int'),\n"," ('carrier', 'string'),\n"," ('flight', 'int'),\n"," ('org', 'string'),\n"," ('mile', 'int'),\n"," ('depart', 'double'),\n"," ('duration', 'int'),\n"," ('delay', 'int')]"]},"execution_count":24,"metadata":{},"output_type":"execute_result"}],"source":["# Getting the data types of each column in the DataFrame\n","flights_df.dtypes"]},{"cell_type":"markdown","metadata":{"id":"w_vMFWc8wB2j"},"source":["### **Exploratory data analysis (EDA)**"]},{"cell_type":"code","execution_count":63,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":564},"executionInfo":{"elapsed":5700,"status":"ok","timestamp":1713033479665,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"lnaGuaxDwGKD","outputId":"10eeb905-6386-4364-fad9-76b73cb9dfc1"},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1000x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Visualizing the distribution of delays\n","plt.figure(figsize=(10, 6))\n","sns.histplot(flights_df.select('delay').toPandas(), bins=30, kde=True, color='skyblue')\n","plt.title('Distribution of Delays')\n","plt.xlabel('Delay (minutes)')\n","plt.ylabel('Frequency')\n","plt.show()"]},{"cell_type":"code","execution_count":71,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":564},"executionInfo":{"elapsed":7756,"status":"ok","timestamp":1713034389379,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"UgymtiFTwLb8","outputId":"4f4602bc-6266-4699-e0fa-045f0c78e6e9"},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1000x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Visualizing the relationship between delay and distance\n","import seaborn as sns\n","plt.figure(figsize=(10, 6))\n","sns.scatterplot(x='duration', y='delay', data=flights_df.toPandas(), alpha=0.5)\n","plt.title('Delay vs Distance')\n","plt.xlabel('Distance (km)')\n","plt.ylabel('Delay (minutes)')\n","plt.show()"]},{"cell_type":"code","execution_count":72,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":651},"executionInfo":{"elapsed":10044,"status":"ok","timestamp":1713034493197,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"5EEX9Fs5zzTF","outputId":"a57b2555-dd6a-4170-9ac2-c97b654bb3e7"},"outputs":[{"name":"stderr","output_type":"stream","text":["<ipython-input-72-d1223ff9862c>:3: FutureWarning: \n","\n","Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n","\n","  sns.boxplot(x='carrier', y='delay', data=flights_df.toPandas(), palette='viridis')\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Visualizing the distribution of delays by carrier\n","plt.figure(figsize=(12, 6))\n","sns.boxplot(x='carrier', y='delay', data=flights_df.toPandas(), palette='viridis')\n","plt.title('Distribution of Delays by Carrier')\n","plt.xlabel('Carrier')\n","plt.ylabel('Delay (minutes)')\n","plt.show()"]},{"cell_type":"code","execution_count":73,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":651},"executionInfo":{"elapsed":8648,"status":"ok","timestamp":1713034515279,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"HuAQ9kZG0BBi","outputId":"fe56b0ee-26c6-44b9-82c1-cf7fd8ce3686"},"outputs":[{"name":"stderr","output_type":"stream","text":["<ipython-input-73-e25aebe92a8a>:3: FutureWarning: \n","\n","Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n","\n","  sns.violinplot(x='org', y='delay', data=flights_df.toPandas(), palette='Set2')\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Visualizing the distribution of delays by origin airport\n","plt.figure(figsize=(12, 6))\n","sns.violinplot(x='org', y='delay', data=flights_df.toPandas(), palette='Set2')\n","plt.title('Distribution of Delays by Origin Airport')\n","plt.xlabel('Origin Airport')\n","plt.ylabel('Delay (minutes)')\n","plt.show()"]},{"cell_type":"code","execution_count":74,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":651},"executionInfo":{"elapsed":7697,"status":"ok","timestamp":1713034535352,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"nVNjZzNa0Hlq","outputId":"eb3f45d8-33b4-4777-8ee9-8e08113b1722"},"outputs":[{"name":"stderr","output_type":"stream","text":["<ipython-input-74-9ae2d1c21b8d>:3: FutureWarning: \n","\n","Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n","\n","  sns.boxplot(x='mon', y='delay', data=flights_df.toPandas(), palette='pastel')\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Visualizing the distribution of delays by month\n","plt.figure(figsize=(12, 6))\n","sns.boxplot(x='mon', y='delay', data=flights_df.toPandas(), palette='pastel')\n","plt.title('Distribution of Delays by Month')\n","plt.xlabel('Month')\n","plt.ylabel('Delay (minutes)')\n","plt.show()"]},{"cell_type":"markdown","metadata":{"id":"SzhtQMzRK_Ch"},"source":["### Handling missing values"]},{"cell_type":"code","execution_count":26,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2135,"status":"ok","timestamp":1713024452066,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"Bo__17FlSOw4","outputId":"a4f782f5-e44f-46cf-d1e9-a8d6af7f27ad"},"outputs":[{"name":"stdout","output_type":"stream","text":["Data after dropping rows with missing values: 258289\n"]}],"source":["# Dropping the 'flight' column from the DataFrame\n","flights_df = flights_df.drop('flight')\n","\n","# Dropping rows with missing values from the DataFrame\n","flights_df = flights_df.dropna()\n","\n","# Printing the number of records after dropping rows with missing values\n","print(f\"Data after dropping rows with missing values: {flights_df.count()}\")"]},{"cell_type":"markdown","metadata":{"id":"an0epwEt42-X"},"source":["### **RDD**"]},{"cell_type":"code","execution_count":29,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":11080,"status":"ok","timestamp":1713024991813,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"n-fPy0ifNwpG","outputId":"7f0c8d30-5358-43de-d987-ef19860a5121"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-----------+------------------+\n","|column_name|     unique_values|\n","+-----------+------------------+\n","|    summary|             count|\n","|        mon|            258289|\n","|        dom|            258289|\n","|        dow|            258289|\n","|    carrier|            258289|\n","|        org|            258289|\n","|       mile|            258289|\n","|     depart|            258289|\n","|   duration|            258289|\n","|      delay|            258289|\n","|    summary|              mean|\n","|        mon| 5.287941027298879|\n","|        dom|15.725110244725869|\n","|        dow|2.9510044949649425|\n","|    carrier|              NULL|\n","|        org|              NULL|\n","|       mile| 890.2974458842614|\n","|     depart|14.088846911791904|\n","|   duration|152.54255117329814|\n","|      delay| 28.34773064280709|\n","+-----------+------------------+\n","only showing top 20 rows\n","\n"]}],"source":["# Getting schema information using summary and extracting schema\n","schema = flights_df.select(*flights_df.columns).summary().schema\n","\n","# Calculating unique value counts for each column\n","unique_value_counts = flights_df.select(*flights_df.columns).summary().rdd.flatMap(lambda x: [(col.name, x[i]) for i, col in enumerate(schema)]).toDF(['column_name', 'unique_values'])\n","\n","# Displaying unique value counts for each column\n","unique_value_counts.show()\n"]},{"cell_type":"markdown","metadata":{"id":"_VtnMJAuPrhm"},"source":["## Data Preprocessing (conversions, feature engineering)"]},{"cell_type":"code","execution_count":30,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":510,"status":"ok","timestamp":1713025162776,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"ZIDQDjIdScWn","outputId":"ab5d8602-69fe-4f24-9dff-3fb84eceea05"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+---+---+-------+---+------+--------+-----+------+-----+\n","|mon|dom|dow|carrier|org|depart|duration|delay|    km|label|\n","+---+---+---+-------+---+------+--------+-----+------+-----+\n","| 10| 10|  1|     OO|ORD|  8.18|      51|   27| 253.0|    1|\n","| 11| 22|  1|     OO|ORD|  7.17|     127|  -19|1188.0|    0|\n","|  2| 14|  5|     B6|JFK| 21.17|     365|   60|3618.0|    1|\n","|  5| 25|  3|     WN|SJC| 12.92|      85|   22| 621.0|    1|\n","|  3| 28|  1|     B6|LGA| 13.33|     182|   70|1732.0|    1|\n","+---+---+---+-------+---+------+--------+-----+------+-----+\n","only showing top 5 rows\n","\n"]}],"source":["# Adding a new column 'km' to represent distance in kilometers and rounding it to the nearest integer\n","flights_km = flights_df.withColumn('km', round(flights_df.mile * 1.60934, 0)) \\\n","                    .drop('mile')\n","\n","# Adding a new column 'label' to indicate whether the flight was delayed by 15 minutes or more, and converting it to integer type\n","flights_km = flights_km.withColumn('label', (flights_km.delay >= 15).cast('integer'))\n","\n","# Displaying the first 5 rows of the DataFrame after preprocessing\n","flights_km.show(5)"]},{"cell_type":"markdown","metadata":{"id":"AN-t20srHT5a"},"source":["### **Encoding Categorical variables through Indexing**"]},{"cell_type":"code","execution_count":31,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":8732,"status":"ok","timestamp":1713025306347,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"XXV9_0twTMWH","outputId":"69fa93ef-af9d-47d0-ada9-ff58183c4cd1"},"outputs":[{"name":"stdout","output_type":"stream","text":["+---+---+---+-------+---+------+--------+-----+------+-----+-----------+-------+\n","|mon|dom|dow|carrier|org|depart|duration|delay|    km|label|carrier_idx|org_idx|\n","+---+---+---+-------+---+------+--------+-----+------+-----+-----------+-------+\n","| 10| 10|  1|     OO|ORD|  8.18|      51|   27| 253.0|    1|        2.0|    0.0|\n","| 11| 22|  1|     OO|ORD|  7.17|     127|  -19|1188.0|    0|        2.0|    0.0|\n","|  2| 14|  5|     B6|JFK| 21.17|     365|   60|3618.0|    1|        4.0|    2.0|\n","|  5| 25|  3|     WN|SJC| 12.92|      85|   22| 621.0|    1|        3.0|    5.0|\n","|  3| 28|  1|     B6|LGA| 13.33|     182|   70|1732.0|    1|        4.0|    3.0|\n","+---+---+---+-------+---+------+--------+-----+------+-----+-----------+-------+\n","only showing top 5 rows\n","\n"]}],"source":["# Indexing the 'carrier' column and adding a new column 'carrier_idx' to the DataFrame\n","flights_indexed = StringIndexer(inputCol='carrier', outputCol='carrier_idx').fit(flights_km).transform(flights_km)\n","\n","# Indexing the 'org' column and adding a new column 'org_idx' to the DataFrame\n","flights_indexed = StringIndexer(inputCol='org', outputCol='org_idx').fit(flights_indexed).transform(flights_indexed)\n","\n","# Displaying the first 5 rows of the DataFrame after indexing\n","flights_indexed.show(5)"]},{"cell_type":"code","execution_count":32,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":781,"status":"ok","timestamp":1713025322104,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"1okLgEWJTRip","outputId":"358e478a-3e7d-437c-ad35-03cb3e163396"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-----------------------------------------+-----+\n","|features                                 |delay|\n","+-----------------------------------------+-----+\n","|[10.0,10.0,1.0,2.0,0.0,253.0,8.18,51.0]  |27   |\n","|[11.0,22.0,1.0,2.0,0.0,1188.0,7.17,127.0]|-19  |\n","|[2.0,14.0,5.0,4.0,2.0,3618.0,21.17,365.0]|60   |\n","|[5.0,25.0,3.0,3.0,5.0,621.0,12.92,85.0]  |22   |\n","|[3.0,28.0,1.0,4.0,3.0,1732.0,13.33,182.0]|70   |\n","+-----------------------------------------+-----+\n","only showing top 5 rows\n","\n"]}],"source":["# Creating a VectorAssembler to assemble input features into a single vector column\n","assembler = VectorAssembler(inputCols=['mon', 'dom', 'dow', 'carrier_idx', 'org_idx', 'km', 'depart', 'duration'], outputCol='features')\n","\n","# Transforming the DataFrame by assembling the input features into the 'features' column\n","flights_assembled = assembler.transform(flights_indexed)\n","\n","# Selecting the 'features' column and 'delay' column and displaying the first 5 rows\n","flights_assembled.select('features', 'delay').show(5, truncate=False)"]},{"cell_type":"markdown","metadata":{"id":"6pem1w7_uLnm"},"source":["### Data Transformation"]},{"cell_type":"code","execution_count":34,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3068,"status":"ok","timestamp":1713025530464,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"r8_XLw_XRhYX","outputId":"be24c9ed-80ee-4faf-f13a-79c40e569436"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-----------------------------------------+-----+\n","|features                                 |delay|\n","+-----------------------------------------+-----+\n","|[10.0,10.0,1.0,2.0,0.0,253.0,8.18,51.0]  |27   |\n","|[11.0,22.0,1.0,2.0,0.0,1188.0,7.17,127.0]|-19  |\n","|[2.0,14.0,5.0,4.0,2.0,3618.0,21.17,365.0]|60   |\n","|[5.0,25.0,3.0,3.0,5.0,621.0,12.92,85.0]  |22   |\n","|[3.0,28.0,1.0,4.0,3.0,1732.0,13.33,182.0]|70   |\n","+-----------------------------------------+-----+\n","only showing top 5 rows\n","\n"]}],"source":["from pyspark.ml.feature import StandardScaler\n","\n","# Feature scaling using StandardScaler\n","scaler = StandardScaler(inputCol=\"features\", outputCol=\"scaled_features\", withMean=True, withStd=True)\n","\n","# Fitting the StandardScaler to the data and transforming the DataFrame\n","flights_scaled = scaler.fit(flights_assembled).transform(flights_assembled)\n","\n","# Displaying the 'features' column and 'delay' column of the scaled DataFrame\n","flights_scaled.select('features', 'delay').show(5, truncate=False)"]},{"cell_type":"markdown","metadata":{"id":"PJR6ISVVTaAv"},"source":["### Model Building"]},{"cell_type":"code","execution_count":35,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":7091,"status":"ok","timestamp":1713025606730,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"9u8qdfxoTc0Q","outputId":"b5aaf86e-c7cb-4bea-94ad-88e343879ce7"},"outputs":[{"data":{"text/plain":["0.7997359546864171"]},"execution_count":35,"metadata":{},"output_type":"execute_result"}],"source":["# Splitting the scaled DataFrame into training and testing sets\n","flights_train, flights_test = flights_scaled.randomSplit([0.8, 0.2], seed=42)\n","\n","# Calculating the ratio of training data to the total data\n","training_ratio = flights_train.count() / flights_scaled.count()\n","\n","# Displaying the training data ratio\n","training_ratio"]},{"cell_type":"markdown","metadata":{"id":"8nlQeKFREwee"},"source":["### DecisionTreeClassifier"]},{"cell_type":"code","execution_count":36,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":24605,"status":"ok","timestamp":1713025636313,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"vpU7rcWhTori","outputId":"4f5356ae-7c57-46da-e89a-313c4504e7d9"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-----+----------+----------------------------------------+\n","|label|prediction|probability                             |\n","+-----+----------+----------------------------------------+\n","|0    |1.0       |[0.31545301069217785,0.6845469893078222]|\n","|1    |1.0       |[0.31545301069217785,0.6845469893078222]|\n","|0    |1.0       |[0.31545301069217785,0.6845469893078222]|\n","|0    |1.0       |[0.4469993101862497,0.5530006898137503] |\n","|0    |1.0       |[0.31545301069217785,0.6845469893078222]|\n","+-----+----------+----------------------------------------+\n","only showing top 5 rows\n","\n"]}],"source":["# Creating a DecisionTreeClassifier model\n","tree = DecisionTreeClassifier()\n","\n","# Fitting the DecisionTreeClassifier model to the training data\n","tree_model = tree.fit(flights_train)\n","\n","# Making predictions on the testing data\n","prediction = tree_model.transform(flights_test)\n","\n","# Selecting and displaying the 'label', 'prediction', and 'probability' columns of the prediction DataFrame\n","prediction.select('label', 'prediction', 'probability').show(5, False)"]},{"cell_type":"markdown","metadata":{"id":"taz__Iv4TvPJ"},"source":["### Evaluation of the model"]},{"cell_type":"code","execution_count":37,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":19865,"status":"ok","timestamp":1713025661910,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"hjDMjb-ATzDh","outputId":"52e3b1dc-1e8b-4d0d-b484-a3981d6b2448"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-----+----------+-----+\n","|label|prediction|count|\n","+-----+----------+-----+\n","|    1|       0.0| 9213|\n","|    0|       0.0|16340|\n","|    1|       1.0|16680|\n","|    0|       1.0| 9493|\n","+-----+----------+-----+\n","\n"]},{"data":{"text/plain":["0.638363685573986"]},"execution_count":37,"metadata":{},"output_type":"execute_result"}],"source":["# Grouping the prediction DataFrame by 'label' and 'prediction' columns and counting the occurrences\n","prediction.groupBy('label', 'prediction').count().show()\n","\n","# Calculating the elements of the confusion matrix\n","TN = prediction.filter('prediction = 0 AND label = prediction').count()  # True Negative\n","TP = prediction.filter('prediction = 1 AND label = prediction').count()  # True Positive\n","FN = prediction.filter('prediction = 0 AND label != prediction').count()  # False Negative\n","FP = prediction.filter('prediction = 1 AND label != prediction').count()  # False Positive\n","\n","# Calculating the accuracy using elements of the confusion matrix\n","accuracy = (TN + TP) / (TN + TP + FN + FP)\n","\n","# Displaying the accuracy\n","accuracy\n"]},{"cell_type":"markdown","metadata":{"id":"z2ReaOsDE0vV"},"source":["### Logistic Regression"]},{"cell_type":"code","execution_count":38,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":18230,"status":"ok","timestamp":1713025683148,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"JEpRnmcIT3BH","outputId":"327f22af-b493-4269-f787-dc489476b77c"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-----+----------+-----+\n","|label|prediction|count|\n","+-----+----------+-----+\n","|    1|       0.0| 9378|\n","|    0|       0.0|15026|\n","|    1|       1.0|16515|\n","|    0|       1.0|10807|\n","+-----+----------+-----+\n","\n"]}],"source":["# Creating a LogisticRegression model and fitting it to the training data\n","logistic = LogisticRegression().fit(flights_train)\n","\n","# Making predictions on the testing data\n","prediction = logistic.transform(flights_test)\n","\n","# Grouping the prediction DataFrame by 'label' and 'prediction' columns and counting the occurrences\n","prediction.groupBy('label', 'prediction').count().show()"]},{"cell_type":"markdown","metadata":{"id":"2IbQhF0-H6vC"},"source":["### Evaluating Logistic Regression Model"]},{"cell_type":"code","execution_count":75,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":648},"executionInfo":{"elapsed":20395,"status":"ok","timestamp":1713035722592,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"VSHltL7FUFiv","outputId":"e552f8c3-6c42-4a7a-f342-98823855bc34"},"outputs":[{"name":"stdout","output_type":"stream","text":["precision = 0.64\n","recall    = 0.64\n"]},{"data":{"text/html":["<div style=\"max-width:800px; border: 1px solid var(--colab-border-color);\"><style>\n","      pre.function-repr-contents {\n","        overflow-x: auto;\n","        padding: 8px 12px;\n","        max-height: 500px;\n","      }\n","\n","      pre.function-repr-contents.function-repr-contents-collapsed {\n","        cursor: pointer;\n","        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If None, the previous value is left as is.\n","\n","loc : {&#x27;bottom&#x27;, &#x27;center&#x27;, &#x27;top&#x27;}, default: :rc:`yaxis.labellocation`\n","    The label position. This is a high-level alternative for passing\n","    parameters *y* and *horizontalalignment*.\n","\n","Other Parameters\n","----------------\n","**kwargs : `.Text` properties\n","    `.Text` properties control the appearance of the label.\n","\n","See Also\n","--------\n","text : Documents the properties supported by `.Text`.</pre>\n","      <script>\n","      if (google.colab.kernel.accessAllowed && google.colab.files && google.colab.files.view) {\n","        for (const element of document.querySelectorAll('.filepath')) {\n","          element.style.display = 'block'\n","          element.onclick = (event) => {\n","            event.preventDefault();\n","            event.stopPropagation();\n","            google.colab.files.view(element.textContent, 3097);\n","          };\n","        }\n","      }\n","      for (const element of document.querySelectorAll('.function-repr-contents')) {\n","        element.onclick = (event) => {\n","          event.preventDefault();\n","          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**kwargs)>"]},"execution_count":75,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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","text/plain":["<Figure size 640x480 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Calculating precision and recall\n","precision = TP / (TP + FP)\n","recall = TP / (TP + FN)\n","print('precision = {:.2f}\\nrecall    = {:.2f}'.format(precision, recall))\n","\n","# Finding weighted precision using MulticlassClassificationEvaluator\n","multi_evaluator = MulticlassClassificationEvaluator()\n","weighted_precision = multi_evaluator.evaluate(prediction, {multi_evaluator.metricName: \"weightedPrecision\"})\n","\n","# Finding AUC using BinaryClassificationEvaluator\n","binary_evaluator = BinaryClassificationEvaluator()\n","auc = binary_evaluator.evaluate(prediction, {binary_evaluator.metricName: \"areaUnderROC\"})\n","\n","# Visualizing the confusion matrix\n","confusion_matrix = prediction.groupBy('label', 'prediction').count().toPandas()\n","confusion_matrix.pivot(index='label', columns='prediction', values='count').plot(kind='bar', stacked=True)\n","plt.xlabel('True Label')\n","plt.ylabel\n"]},{"cell_type":"markdown","metadata":{"id":"vXGRgqAlE6DA"},"source":["### Random Forest Classifier"]},{"cell_type":"code","execution_count":77,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":73576,"status":"ok","timestamp":1713038635277,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"4-pSAVlGDgLV","outputId":"4713ad6b-1556-43e4-85db-b6e723a3b04f"},"outputs":[{"name":"stdout","output_type":"stream","text":["+-----+----------+----------------------------------------+\n","|label|prediction|probability                             |\n","+-----+----------+----------------------------------------+\n","|0    |1.0       |[0.3589499435548624,0.6410500564451376] |\n","|1    |1.0       |[0.35125087072048233,0.6487491292795178]|\n","|0    |1.0       |[0.3588491112854081,0.6411508887145919] |\n","|0    |1.0       |[0.40657095333012394,0.5934290466698761]|\n","|0    |1.0       |[0.3534426735568953,0.6465573264431048] |\n","+-----+----------+----------------------------------------+\n","only showing top 5 rows\n","\n","+-----+----------+-----+\n","|label|prediction|count|\n","+-----+----------+-----+\n","|    1|       0.0| 8549|\n","|    0|       0.0|15932|\n","|    1|       1.0|17344|\n","|    0|       1.0| 9901|\n","+-----+----------+-----+\n","\n","Random Forest - Precision = 0.64\n","Random Forest - Recall    = 0.67\n","Random Forest - Weighted Precision: 0.6436839059658439\n","Random Forest - AUC: 0.6914454570968717\n"]}],"source":["from pyspark.ml.classification import RandomForestClassifier\n","\n","# Using Random Forest Classifier\n","rf = RandomForestClassifier()\n","rf_model = rf.fit(flights_train)\n","\n","# Prediction using Random Forest\n","rf_prediction = rf_model.transform(flights_test)\n","rf_prediction.select('label', 'prediction', 'probability').show(5, False)\n","\n","# Evaluation of the Random Forest model\n","rf_prediction.groupBy('label', 'prediction').count().show()\n","\n","# Calculate the elements of the confusion matrix for Random Forest\n","rf_TN = rf_prediction.filter('prediction = 0 AND label = prediction').count()\n","rf_TP = rf_prediction.filter('prediction = 1 AND label = prediction').count()\n","rf_FN = rf_prediction.filter('prediction = 0 AND label != prediction').count()\n","rf_FP = rf_prediction.filter('prediction = 1 AND label != prediction').count()\n","\n","# Calculate accuracy for Random Forest\n","rf_accuracy = (rf_TN + rf_TP) / (rf_TN + rf_TP + rf_FN + rf_FP)\n","rf_accuracy\n","\n","# Calculate precision and recall for Random Forest\n","rf_precision = rf_TP / (rf_TP + rf_FP)\n","rf_recall = rf_TP / (rf_TP + rf_FN)\n","print('Random Forest - Precision = {:.2f}\\nRandom Forest - Recall    = {:.2f}'.format(rf_precision, rf_recall))\n","\n","# Find weighted precision for Random Forest\n","rf_weighted_precision = multi_evaluator.evaluate(rf_prediction, {multi_evaluator.metricName: \"weightedPrecision\"})\n","\n","# Find AUC for Random Forest\n","rf_auc = binary_evaluator.evaluate(rf_prediction, {binary_evaluator.metricName: \"areaUnderROC\"})\n","\n","# Print Random Forest results\n","print(\"Random Forest - Weighted Precision:\", rf_weighted_precision)\n","print(\"Random Forest - AUC:\", rf_auc)\n"]},{"cell_type":"markdown","metadata":{"id":"9F6rttQsILys"},"source":["### Evaluating Random Forest Classifier model"]},{"cell_type":"code","execution_count":80,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":695},"executionInfo":{"elapsed":6584,"status":"ok","timestamp":1713038856089,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"hGB6MB8NERZs","outputId":"b2c735ca-19a7-4798-f55c-0924cfcf6aa4"},"outputs":[{"name":"stdout","output_type":"stream","text":["Confusion matrix, without normalization\n","[[15932  9901]\n"," [ 8549 17344]]\n","              precision    recall  f1-score   support\n","\n","     Delayed       0.65      0.62      0.63     25833\n"," Not Delayed       0.64      0.67      0.65     25893\n","\n","    accuracy                           0.64     51726\n","   macro avg       0.64      0.64      0.64     51726\n","weighted avg       0.64      0.64      0.64     51726\n","\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 640x480 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["import numpy as np\n","import matplotlib.pyplot as plt\n","import itertools  # Add this line for itertools\n","from sklearn.metrics import confusion_matrix, classification_report\n","\n","# Compute confusion matrix\n","rf_prediction_pd = rf_prediction.select('label', 'prediction').toPandas()\n","y_true = rf_prediction_pd['label']\n","y_pred = rf_prediction_pd['prediction']\n","cm = confusion_matrix(y_true, y_pred)\n","\n","# Plot confusion matrix\n","def plot_confusion_matrix(cm, classes,\n","                          normalize=False,\n","                          title='Confusion matrix',\n","                          cmap=plt.cm.Blues):\n","    \"\"\"\n","    This function prints and plots the confusion matrix.\n","    Normalization can be applied by setting `normalize=True`.\n","    \"\"\"\n","    if normalize:\n","        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n","        print(\"Normalized confusion matrix\")\n","    else:\n","        print('Confusion matrix, without normalization')\n","\n","    print(cm)\n","\n","    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n","    plt.title(title)\n","    plt.colorbar()\n","    tick_marks = np.arange(len(classes))\n","    plt.xticks(tick_marks, classes, rotation=45)\n","    plt.yticks(tick_marks, classes)\n","\n","    fmt = '.2f' if normalize else 'd'\n","    thresh = cm.max() / 2.\n","    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n","        plt.text(j, i, format(cm[i, j], fmt),\n","                 horizontalalignment=\"center\",\n","                 color=\"white\" if cm[i, j] > thresh else \"black\")\n","\n","    plt.ylabel('True label')\n","    plt.xlabel('Predicted label')\n","    plt.tight_layout()\n","\n","# Plot non-normalized confusion matrix\n","plt.figure()\n","plot_confusion_matrix(cm, classes=['Delayed', 'Not Delayed'],\n","                      title='Confusion matrix, without normalization')\n","\n","# Calculate precision, recall, f1-score, and accuracy\n","print(classification_report(y_true, y_pred, target_names=['Delayed', 'Not Delayed']))\n"]},{"cell_type":"code","execution_count":82,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":607},"executionInfo":{"elapsed":1118,"status":"ok","timestamp":1713040079656,"user":{"displayName":"Shreeprada","userId":"04819289040060824317"},"user_tz":240},"id":"ePnsrZlmJGjT","outputId":"7b039ce1-2c02-40ad-8402-676d6c80edd0"},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1000x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["import matplotlib.pyplot as plt\n","\n","# Define models and their performance metrics\n","models = ['Decision Tree', 'Random Forest', 'Logistic Regression']\n","accuracy_scores = [accuracy, rf_accuracy, weighted_precision]\n","\n","# Plotting\n","plt.figure(figsize=(10, 6))\n","\n","# Accuracy\n","plt.subplot(1, 2, 1)\n","plt.bar(models, accuracy_scores, color='skyblue')\n","plt.title('Accuracy Comparison')\n","plt.ylabel('Accuracy')\n","\n","plt.tight_layout()\n","plt.show()\n"]}],"metadata":{"colab":{"provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}