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How to Check Column Nulls and Replace: Pandas

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

Top Valuable Sources to Learn Predictive Analytics After Your Degree

The word predictive analytics is to increase competitive advantage and at the same time to suggest the best value products to end customers.

Data analytics
Data analytics

Why you need to go for predictive analytics

The reasons are

  • Growing data
  • Cheaper computers and servers
  • Easy to use software
  • Tough economic conditions

The predictive analytics helps in the following areas:

  • Detecting fraud
  • Improve marketing campaigns
  • Reduce risk
  • Improving operations
Growing data analytics creating many job opportunities.

Where You Need to Learn

  1. Do PG or post graduation in data analytics
  2. Attend Class Room Coachings


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