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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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Data Science Real Advantages to Read Today

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Real business solution you can get from data science analysis. Your sales is the main requirement. No sales means no business. Data Analytics helps to boost your organization sales.

Real Advantages of Data Science

My presentation here gives you complete business picture of data analytics, and skills companies expecting from analytics team.
  1. Data analytics-The data can be from web, user devices, own databases and Social media
  2. AI-Delivering products based on artificial intelligence
  3. Big data-Data of any format and you need to make ready for analysis.
  4. You can understand patterns of people
  5. You can explore current market
  6. You can explore solutions to Agriculture
  7. You can show answers to weather
  8. Predicting the disaster like earth-quake 

Data Analytics what else you can read


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