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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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Storage Node Vs Compute Node

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Here are the differences between compute node vs storage node Nodes are two types. Those are compute and storage. The compute node process business logic whereas the storage node stores the data.

Compute node Vs. Storage node



compute node vs storage node


Compute Node

  • A computer (machine) where you can execute actual business logic.
  • The two parameters it might have are RAM and CPU.


Compute node


Storage Node

  • Stores the processing-data where your file system resides
  • Compute and storage nodes you can find at one location.
  • It designates block storage.

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