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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

Python Tuple: Here're 2 Ways to Calculate Sum Easily

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Python tuple is nothing but a set of data. It can have an 'n' number of elements. Here, in my example, the tuple has 20 Elements. The below logic helps you to calculate the sum of its 20 Elements easily.  A tuple is simply a set, and it can have both positive and negative Elements. So, don't worry. You can calculate the sum even the tuple has negative numbers. Here are 2 Ways You can calculate Sum Display sum after adding each element Display sum at once   Python Logic: #1 Method - The Print Displays Sum in Vertcle after Adding Each Element my_tuple = (1,20, -30, 50, 10, 11, 6, 7, 22, 88, 10, 20, 565, 121, 211, 5, 2, 18, 20, 21) sum = 0 for index in my_tuple:             sum = sum+ index          print("sum of elements:", sum) Note*** Here the print statement is within the For Loop. You May Also Like: How to Use For Loop  in Python Complete Tutorial Python Logic: #2 Method - The Print Displays Total Sum at once my_tuple = (1,20, -30, 50, 10, 11, 6, 7, 22, 88, 10