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How to Check Column Nulls and Replace: Pandas

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

Excel: 10 Key Topics You Need to Learn

The below-listed topics help you get a solid footing in Excel Analytics. Just practice these 10 topics step by step and by completing all, you will be an expert in Excel. 10 Top Excel Topics Tables in Excel  Grabbing data from external sources  Cleaning data with functions  Working with Pivot tables  Writing Formulae for Pivot tables  Pivot Charts  How to use database functions  How to use statistics  Inferential Statistics  Descriptive statistics Also Read : 5 Tips why macros need in Excel