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Top Questions People Ask About Pandas, NumPy, Matplotlib & Scikit-learn — Answered!

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 Whether you're a beginner or brushing up on your skills, these are the real-world questions Python learners ask most about key libraries in data science. Let’s dive in! 🐍 🐼 Pandas: Data Manipulation Made Easy 1. How do I handle missing data in a DataFrame? df.fillna( 0 ) # Replace NaNs with 0 df.dropna() # Remove rows with NaNs df.isna(). sum () # Count missing values per column 2. How can I merge or join two DataFrames? pd.merge(df1, df2, on= 'id' , how= 'inner' ) # inner, left, right, outer 3. What is the difference between loc[] and iloc[] ? loc[] uses labels (e.g., column names) iloc[] uses integer positions df.loc[ 0 , 'name' ] # label-based df.iloc[ 0 , 1 ] # index-based 4. How do I group data and perform aggregation? df.groupby( 'category' )[ 'sales' ]. sum () 5. How can I convert a column to datetime format? df[ 'date' ] = pd.to_datetime(df[ 'date' ]) ...
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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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