代码如下,步骤流程在代码注释中可见:

# -*- coding: utf-8 -*-
import pandas as pd
from pyspark.sql import SparkSession
from pyspark.sql import SQLContext
from pyspark import SparkContext
 
#初始化数据
 
#初始化pandas Data 
df = pd.Data ([[1, 2, 3], [4, 5, 6]], index=['row1', 'row2'], columns=['c1', 'c2', 'c3'])
 
#打印数据
print df
 
#初始化spark Data 
sc = SparkContext()
if __name__ == "__main__":
 spark = SparkSession\
  .builder\
  .appName("testData ")\
  .getOrCreate()
 
sentenceData = spark.createData ([
 (0.0, "I like Spark"),
 (1.0, "Pandas is useful"),
 (2.0, "They are coded by Python ")
], ["label", "sentence"])
 
#显示数据
sentenceData.select("label").show()
 
#spark.Data  转换成 pandas.Data 
sqlContest = SQLContext(sc)
spark_df = sqlContest.createData (df)
 
#显示数据
spark_df.select("c1").show()
 
 
# pandas.Data  转换成 spark.Data 
pandas_df = sentenceData.toPandas()
 
#打印数据
print pandas_df

程序结果:

以上这篇pyspark.sql.Data 与pandas.Data 之间的相互转换实例就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持脚本之家。

收藏 打印