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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 Valuable Sources to Learn Predictive Analytics After Your Degree

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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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