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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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12 Top Tableau Small Projects for Practice

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Tableau is one of the best visualization tools. With Tableau Desktop you can connect to multiple data sources. Tableau Desktop is based on breakthrough technology from Stanford University that lets you drag & drop to analyze data.

Good Tableau Exercises to excell your skills
Best 12 Tableau Exercises:

Small Projects for Practice.


You can connect to data in a few clicks, then visualize and create interactive dashboards with a few more. We’ve done years of research to build a system that supports people’s natural ability to think visually. 

Shift fluidly between views, following your natural train of thought. You’re not stuck in wizards or bogged down writing scripts. 

You just create beautiful, rich data visualizations. It's so easy to use that any Excel user can learn it. Get more results for less effort. And it’s 10 –100x faster than existing solutions

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