# To drop duplicate columns duplicate_cols = df.columns[df.columns.duplicated()] df.drop(columns=duplicate_cols, inplace=True) Now, let’s create a DataFrame with a few duplicate rows and columns, execute these
Duplicate rows could be remove or drop from Spark SQL DataFrame using distinct() and dropDuplicates() functions, distinct() can be used to remove rows
Select column Choose one or more columns to keep, and delete the rest Rename column Rename a column Drop missing values Remove rows with missing values Drop duplicate rows Drop all rows that have duplicate values in one or more columns Fill missing values Replace cells with missing values with...
Learn how to explore and transform Spark DataFrames with Data Wrangler, generating PySpark code in real time.
# Example 6: Get count duplicate rows df2 = len(df)-len(df.drop_duplicates()) # Example 7: Get count duplicates for each unique row df2 = df.groupby(df.columns.tolist(), as_index=False).size() Now, Let’s create Pandas DataFrame using data from a Python dictionary, where the colu...
Select column Choose one or more columns to keep, and delete the rest Rename column Rename a column Drop missing values Remove rows with missing values Drop duplicate rows Drop all rows that have duplicate values in one or more columns Fill missing values Replace cells with missing values with...