PYTHON

create spark dataframe in python

spark.createDataFrame(["10","11","13"], "string").toDF("age")

spark to pandas

pandas_df = spark_df.select("*").toPandas()

dataframe pandas to spark

from pyspark.sql import SparkSession
#Create PySpark SparkSession
spark = SparkSession.builder 
    .master("local[1]") 
    .appName("SparkByExamples.com") 
    .getOrCreate()
#Create PySpark DataFrame from Pandas
sparkDF=spark.createDataFrame(pandasDF) 
sparkDF.printSchema()
sparkDF.show()

#Outputs below schema & DataFrame

root
 |-- Name: string (nullable = true)
 |-- Age: long (nullable = true)

+------+---+
|  Name|Age|
+------+---+
| Scott| 50|
|  Jeff| 45|
|Thomas| 54|
|   Ann| 34|
+------+---+

create spark dataframe from pandas

import numpy as np
import pandas as pd

# Enable Arrow-based columnar data transfers
spark.conf.set("spark.sql.execution.arrow.enabled", "true")

# Generate a pandas DataFrame
pdf = pd.DataFrame(np.random.rand(100, 3))

# Create a Spark DataFrame from a pandas DataFrame using Arrow
df = spark.createDataFrame(pdf)

spark to pandas

pandas_df = some_df.toPandas()

Create spark dataframe in python

spark.createDataFrame([("10", ), ("11", ), ("13",  )], ["age"])