Compute Pandas Correlation Matrix of a Spark Data Frame

compute_correlation_matrix.py

from pyspark.mllib.stat import Statistics
import pandas as pd

# result can be used w/ seaborn's heatmap
def compute_correlation_matrix(df, method='pearson'):
    # wrapper around
    # https://forums.databricks.com/questions/3092/how-to-calculate-correlation-matrix-with-all-colum.html
    df_rdd = df.rdd.map(lambda row: row[0:])
    corr_mat = Statistics.corr(df_rdd, method=method)
    corr_mat_df = pd.DataFrame(corr_mat,
                    columns=df.columns, 
                    index=df.columns)
    return corr_mat_df

Thank you! works perfectly, can't believe they don't have a internally built method to handle dataframe -> dataframe correlation tables