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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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How to Work on Re-skill Legacy to Recent

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How to work on your reskill plan to grow your career from any level. Just you need to learn and be ready with proficiency. Someone will absorb you.



Skills You Need To Grow in Your Career



How to work on Re-skill Legacy to Recent



The popular IT skills you need for the digital age are — ML(Machine Learning), AR (Augmented reality), VR (Virtual reality), AI (Artificial intelligence), and IoT. 


 Skills Rank
 Machine Learning  01
 IoT                             03
 Augmented Reality 04
 Artificial Intelligence 02


That's machine learning, augmented reality, virtual reality, artificial intelligence, and the Internet of Things.


How a COBOL Developer Changed His Career


Ramanujan who has been at TCS for 26 years has himself re-skilled several times — from COBOL to client-server to ERP to cloud, before moving into more stable managerial roles. But the reskilling he's witnessing now is like none he's seen before.

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