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StructField("salary", IntegerType(), True) \ĭf = spark.createDataFrame(data=data2,schema=schema) StructField("gender", StringType(), True), \ StructField("lastname",StringType(),True), \ StructField("middlename",StringType(),True), \ StructField("firstname",StringType(),True), \ If you wanted to specify the column names along with their data types, you should create the StructType schema first and then assign this while creating a DataFrame.įrom import StructType,StructField, StringType, IntegerTypeĭata2 = [("James","","Smith","36636","M",3000),
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To use this first we need to convert our “data” object from the list to list of Row.ĭfFromData3 = spark.createDataFrame(rowData,columns) and chain with toDF() to specify names to the columns.ĭfFromData2 = spark.createDataFrame(data).toDF(*columns)Ģ.2 Using createDataFrame() with the Row typeĬreateDataFrame() has another signature in PySpark which takes the collection of Row type and schema for column names as arguments. 2.1 Using createDataFrame() from SparkSessionĬalling createDataFrame() from SparkSession is another way to create PySpark DataFrame manually, it takes a list object as an argument. These examples would be similar to what we have seen in the above section with RDD, but we use the list data object instead of “rdd” object to create DataFrame.
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In this section, we will see how to create PySpark DataFrame from a list. and chain with toDF() to specify name to the columns.ĭfFromRDD2 = spark.createDataFrame(rdd).toDF(*columns) Using createDataFrame() from SparkSession is another way to create manually and it takes rdd object as an argument. 1.2 Using createDataFrame() from SparkSession We can change this behavior by supplying schema, where we can specify a column name, data type, and nullable for each field/column. use the show() method on PySpark DataFrame to show the DataFrameīy default, the datatype of these columns infers to the type of data. This yields the schema of the DataFrame with column names. If you wanted to provide column names to the DataFrame use toDF() method with column names as arguments as shown below.