Pivot a dataframe directly using Spark SQL

demo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql import SparkSession, DataFrame\n",
    "\n",
    "spark = (\n",
    "    SparkSession.builder\n",
    "    .getOrCreate()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def display_df(df: DataFrame, n_rows: int = 5):\n",
    "    pandas_df = df.limit(n_rows).toPandas()\n",
    "    return pandas_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = spark.read.parquet(\"./in_Progress/Pivot using Spark SQL/data.parquet\")\n",
    "df.createOrReplaceTempView(\"data\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "display_df(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"./in_Progress/Pivot using Spark SQL/query.sql\", \"r\") as f:\n",
    "    query = f.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "count_df = spark.sql(query.format(agg_func=\"count\"))\n",
    "count_df = count_df.toPandas().set_index(\"passenger_count\")\n",
    "count_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sum_df = spark.sql(query.format(agg_func=\"sum\"))\n",
    "sum_df = sum_df.toPandas().set_index(\"passenger_count\")\n",
    "sum_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sum_df / count_df"
   ]
  }
 ],
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query.sql

SELECT
    *
FROM
    (
        SELECT
            date_format (tpep_pickup_datetime, 'EEEE') AS day_of_week,
            fare_amount,
            passenger_count
        FROM
            data
    ) PIVOT (
        {agg_func}(fare_amount) FOR day_of_week IN (
            'Monday',
            'Tuesday',
            'Wednesday',
            'Thursday',
            'Friday',
            'Saturday',
            'Sunday'
        )
    )
ORDER BY
    passenger_count;