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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 Syntax Errors Cheat Sheet

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Here's is the Python syntax errors cheat sheet. In Python, you can avoid errors, if you know syntax rules. These are missing semicolons, adding extra commas, and extra spaces. Further Python is case sensitive. So using the wrong identifier also will give error. Python Syntax Errors Cheat Sheet Indentation is unique to Python. You cannot find strict indentation in any other programming language. You need to focus on the three areas while writing a Python program. To avoid errors you need to learn indentation rules. Indentation or Syntax Errors Exceptions Handling Exceptions 1: Indentation If you do not follow the proper order, you will get an error. The details of one block shroud follow in one vertical line. The sub-block should be inside of that. In if loop, the IF, ELIF, and ELSE should have the same indentation. Not only, but the statement inside of them should also have the same indentation. Best Examples Understand these examples a good material on indentation for you. 2