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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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Course Topics You Need to Know Before You Take Course on Excel

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Hey, you want to be master in Excel. There are 4 parts in this course. These contents cover all the functionalities you need to work with Excel.
Excel is one of the tools to be used in data analytics
Why I have given contents means these you must ask your tutor if present in the course or not. This list useful to start a career in analytics.

List of Excel Course Topics

Part-1 - Importing Data from other sources

  • Import or Export data from multiple data sources

Part-2 - Converting data Excel ready

  • Formatting the data understand by EXCEL.

Part-3 - Data Mining

  • Formulas you need for Data cleaning.

Part-4- Excel Data Analysis Tools

  • Data analysis using statistical methods, Charts and Pivot Tables

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