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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
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Here is Sample Logic to get Random numbers in Bash

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How to generate random number



Here's a bash script to generate a random number. You can use this logic to generate a random number, and it is useful for AWS engineers.

Random number


Script - Here's sample logic to get a random number



RANDOM=$$ # Set the seed to the PID of the script
UPPER_LIMIT=$1
RANDOM_NUMBER=$(($RANDOM % $UPPER_LIMIT + 1))
echo "$RANDOM_NUMBER"



If you select UPPER_LIMIT as 100, then the result would be a pseudo-random number between 1 and 100.

Her is the output after executing the script





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