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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

Top 20 highest paying working from home jobs

U.S. businesses will spend half a billion dollars hiring remote freelance workers in 2014. "The growth is a clear indicator of a transition of work online," says Fabio Rosati, CEO of Elance-oDesk. The company's platform — which serves as a broker between companies that need skills and freelancers eager to supply them — sees 2.7 millio n freelance jo bs posted a year. According to Elance-oDesk , the total earnings of freelancers have grown 50% compounded annually over the past five years. From Rosati's perspective, so many businesses are hiring these workers because they need work done on demand, typically for a short stint. In those cases... Read more