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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' ]) ...

12 Must Read DevOps Principles That Give Fair Idea on The Concept

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Here're twelve essential DevOps Principles. Below is the useful list for your sure success in your next interview. 12 DevOps principles To deliver rapidly without affecting the quality. Improved Communication and Collaboration. Multiple deploys are possible if the code in the development team is automated. Once you commit to the repository, it tests the code automatically using the automated test scripts. If the Build passed, it installs automatically. Installs automatically to n number of servers. Minor changes take place in isolation - it creates a separate server to deploy minor changes. Speed in DevOps helps organizations to serve their clients faster and more effectively. Quality and Security teams. Automating the process improves productivity over the manual method. Deploy frequently - the changes can be small or big. DevOps has multiple benefits over traditional approach. Related What is DevOps