pyspark

How to change dataframe column names in pyspark?

There are many ways to do that: Option 1. Using selectExpr. data = sqlContext.createDataFrame([(“Alberto”, 2), (“Dakota”, 2)], [“Name”, “askdaosdka”]) data.show() data.printSchema() # Output #+——-+———-+ #| Name|askdaosdka| #+——-+———-+ #|Alberto| 2| #| Dakota| 2| #+——-+———-+ #root # |– Name: string (nullable = true) # |– askdaosdka: long (nullable = true) df = data.selectExpr(“Name as name”, “askdaosdka as age”) … Read more

Manually create a pyspark dataframe

Simple dataframe creation: According to official doc: when schema is a list of column names, the type of each column will be inferred from data. (example above ↑) When schema is pyspark.sql.types.DataType or a datatype string, it must match the real data. (examples below ↓) Additionally, you can create your dataframe from Pandas dataframe, schema will be inferred from Pandas … Read more

How to change dataframe column names in pyspark?

Option 1. Using selectExpr. data = sqlContext.createDataFrame([(“Alberto”, 2), (“Dakota”, 2)], [“Name”, “askdaosdka”]) data.show() data.printSchema() # Output #+——-+———-+ #| Name|askdaosdka| #+——-+———-+ #|Alberto| 2| #| Dakota| 2| #+——-+———-+ #root # |– Name: string (nullable = true) # |– askdaosdka: long (nullable = true) df = data.selectExpr(“Name as name”, “askdaosdka as age”) df.show() df.printSchema() # Output #+——-+—+ #| name|age| … Read more

Spark RDD to DataFrame python

See, There are two ways to convert an RDD to DF in Spark. toDF() and createDataFrame(rdd, schema) I will show you how you can do that dynamically. toDF() The toDF() command gives you the way to convert an RDD[Row] to a Dataframe. The point is, the object Row() can receive a **kwargs argument. So, there is an easy way to do that. This way you … Read more