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How to Check Column Nulls and Replace: Pandas

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Here is a post that shows how to count Nulls and replace them with the value you want in the Pandas Dataframe. We have explained the process in two steps - Counting and Replacing the Null values. Count null values (column-wise) in Pandas ## count null values column-wise null_counts = df.isnull(). sum() print(null_counts) ``` Output: ``` Column1    1 Column2    1 Column3    5 dtype: int64 ``` In the above code, we first create a sample Pandas DataFrame `df` with some null values. Then, we use the `isnull()` function to create a DataFrame of the same shape as `df`, where each element is a boolean value indicating whether that element is null or not. Finally, we use the `sum()` function to count the number of null values in each column of the resulting DataFrame. The output shows the count of null values column-wise. to count null values column-wise: ``` df.isnull().sum() ``` ##Code snippet to count null values row-wise: ``` df.isnull().sum(axis=1) ``` In the above code, `df` is the Panda

Mainframe study materials for interviews

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Mainframe self-study materials provided to refresh quickly before your next interview.   Top Links for Mainframe Self Study Materials - You Can Download Free of Cost VSAM 1.0 REXX 1.0 MVSQuest Second Edition MVSQuest Second Edition – Tools MQSeries 1.0 MAINFRAME Q&A Mainframe reference questions JCL 1.0 ISPF V 1.0 DB2 1.0 IMS 1.0 IDMS 1.0 COBOL 1.0 CICS V1.0 Abend codes in MF ALL interview questions References Mainframe-srini blogs