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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
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Top Tips You Need to Create Mobile Apps

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Before you start creating mobile applications, you need to understand two things. There are two mobile application types. Namely Native and Web applications.
Mobile applications are two types.Those are Native and Web applications. 
Mobile applications
Photo Credit: Srini

Native applications

  • Each mobile operating system you need to create one version. Native applications are platform dependent. The disadvantage is you need to create multiple versions.
  • Develop apps only on that platform
  • These apps not portable

Web applications

  1. The web applications are platform independent. They work for all mobile operating systems. These applications are browsable using any popular browsers.
  2. These apps are browsable from any popular web browsers

4 Top Mobile Platforms

  1. iOS 
  2. Android 
  3. Windows Phone 7 
  4. Blackberry OS 

4 Top Tablet Platforms

  1. iOS 
  2. Android 
  3. Blackberry OS 
  4. Windows 8

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