pyspark.sql.DataFrame.corr¶

DataFrame.corr(col1: str, col2: str, method: Optional[str] = None) → float[source]¶

Calculates the correlation of two columns of a DataFrame as a double value. Currently only supports the Pearson Correlation Coefficient. DataFrame.corr() and DataFrameStatFunctions.corr() are aliases of each other.

New in version 1.4.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

col1str: The name of the first column
col2str: The name of the second column
methodstr, optional: The correlation method. Currently only supports “pearson”

Returns

float: Pearson Correlation Coefficient of two columns.

Examples

>>> df = spark.createDataFrame([(1, 12), (10, 1), (19, 8)], ["c1", "c2"])
>>> df.corr("c1", "c2")
-0.3592106040535498
>>> df = spark.createDataFrame([(11, 12), (10, 11), (9, 10)], ["small", "bigger"])
>>> df.corr("small", "bigger")
1.0

pyspark.sql.DataFrame.columns pyspark.sql.DataFrame.count