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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

2 Tricky Examples Python List Comprehension

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Here are the tricky examples of list comprehension. These examples useful for your project and interviews as well. 1. Printing odd numbers Reminder checking logic used here. If it is not equal to zero when you divide the number with 2, it treats the input number as odd and prints it. lst1 = [x for x in range(40) if x % 2 != 0] print('First 20 Odd Numbers:') print(lst1) 2. Printing even numbers Reminder checking logic used here. If it is equal to zero when you divide the number with 2, it treats the input number as even and prints it. lst2 = [x for x in range(40) if x % 2 == 0] print('First 20 Even Numbers:') print(lst2) Output from the Python scripts First 20 Odd Numbers:  [1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39] First 20 Even Numbers:  [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38]  ** Process exited - Return Code: 0 ** Press Enter to exit terminal Related The real use of Git in Dev Ops