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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

Talent Analytics on employees to measure real worth

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Human resource managers are currently embracing talent analytics like never before. Companies are evaluating and analysing raw data to derive valuable insights which are helping them to hire the right talent, retain them as well as help them learn and grow internally. Data to do analytics Talent analytics companies take into account all the data, rather than limited samples, so a full-fledged picture emerges.  It looks for patterns in the data and discovers critical connections that might otherwise go unnoticed. Such data can be related to employees' pre-employment assessments to background checks to social media profiles. How data will gather They also gather data on the characteristics of their most successful employees. When big data is tapped this way, HR managers no longer need to depend on intuitions of interviewers and hiring managers or rely on obsolete hiring tools of yesteryears.  Organisations are also leveraging big data to hire and promote t