PySpark: Convert Python Dictionary List to Spark DataFrame

This articles show you how to convert a Python dictionary list to a Spark DataFrame. The code snippets runs on Spark 2.x environments.

Input

The input data (dictionary list looks like the following):

data = [{"Category": 'Category A', 'ItemID': 1, 'Amount': 12.40},
        {"Category": 'Category B', 'ItemID': 2, 'Amount': 30.10},
        {"Category": 'Category C', 'ItemID': 3, 'Amount': 100.01},
        {"Category": 'Category A', 'ItemID': 4, 'Amount': 110.01},
        {"Category": 'Category B', 'ItemID': 5, 'Amount': 70.85}
        ]

Solution 1 - Infer schema

In Spark 2.x, DataFrame can be directly created from Python dictionary list and the schema will be inferred automatically. 

def infer_schema():
    # Create data frame
    df = spark.createDataFrame(data)
    print(df.schema)
    df.show()

StructType(List(StructField(Amount,DoubleType,true),StructField(Category,StringType,true),StructField(ItemID,LongType,true)))
+------+----------+------+
|Amount|  Category|ItemID|
+------+----------+------+
|  12.4|Category A|     1|
|  30.1|Category B|     2|
|100.01|Category C|     3|
|110.01|Category A|     4|
| 70.85|Category B|     5|
+------+----------+------+

Solution 2 - Explicit schema

Of course, you can also define the schema directly when creating the data frame:

def explicit_schema():
    # Create a schema for the dataframe
    schema = StructType([
        StructField('Category', StringType(), False),
        StructField('ItemID', IntegerType(), False),
        StructField('Amount', FloatType(), True)
    ])

    # Create data frame
    df = spark.createDataFrame(data, schema)
    print(df.schema)
    df.show()

In this way, you can control the data types explicitly. The output looks like the following:

StructType(List(StructField(Category,StringType,false),StructField(ItemID,IntegerType,false),StructField(Amount,FloatType,true)))
+----------+------+------+
|  Category|ItemID|Amount|
+----------+------+------+
|Category A|     1|  12.4|
|Category B|     2|  30.1|
|Category C|     3|100.01|
|Category A|     4|110.01|
|Category B|     5| 70.85|
+----------+------+------+

Summary

You can easily convert Python list to Spark DataFrame in Spark 2.x. 

Complete code

Code is available in GitHub:

https://github.com/FahaoTang/spark-examples/tree/master/python-dict-list