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Here are the best examples of Pandas fillna(), dropna() and sum() methods. We have explained the process in two steps - Counting and Replacing the Null values. Count Nulls ## 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 Pandas DataFrame for which you want to cou...

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