Create Spark Data Frames from Csv and Excel files

Create a Spark Data Frame from a CSV File 

from pyspark.context import SparkContext

from pyspark.sql.session import SparkSession

sc = SparkContext.getOrCreate()

spark = SparkSession(sc)

df1 = spark.read.format("csv") \

.option("inferschema","True") \

.option("header","True") \

.load("/FileStore/tables/insurance.csv")

df1.show(5000)

Create a Temporary View on Spark Data Frame

Create a Pandas Data Frame from a CSV File 

import pandas as pd

pd_df = pd.read_csv('/FileStore/tables/insurance.csv')

print(pd_df)

Create a Pandas Data Frame from a Excel File 

import pandas as pd

pd_df = pd.read_excel('C:\\Move\\test.xlsx')

#print(pd_df)

from pyspark.context import SparkContext

from pyspark.sql.session import SparkSession

sc = SparkContext.getOrCreate()

spark = SparkSession(sc)

# Before that make sure to install PyArrow

# PIP INSTALL PyArrow

spark.conf.set("spark.sql.execution.arrow.enabled","true")

sparkDF=spark.createDataFrame(pd_df)

#sparkDF.printSchema()

sparkDF.show(500)