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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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Another way is you can develop your own website and you can learn how to build your website. This is also one kind of advantage, so I am stressing to learn this course.

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By the end of this course, you will have the confidence and ability to create beautiful, functional websites. This course is project based so you be jumping into building your first website in no time. Don't worry if you have little or no experience, I will take it easy and try to clearly explain what we are doing and learn as we build.

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  • Project 1- Begin by creating static recipe website from scratch, learn the fundamentals of HTML & CSS by hand coding your first website.
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