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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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Hadoop 2x vs 3x top differences

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In many interviews, the first question for Hadoop developers is what are the differences between Hadoop 2 and 3. You already know that Hadoop upgraded from version 1.

Hadoop features


The below list is useful to know the differences. I have given Hadoop details in the form of questions and answers so that beginners can understand.

Hadoop 2.x Vs 3.x


hadoop v2 vs 3
The major change in hadoop 3 is no storage overhead. So, you may be curious about how Hadoop 3 is managing storage.

My plan is for you is first to go through the list of differences and check the references section, to learn more about Hadoop storage management.

References

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