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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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Excel Analytics: The complete best explained Free Tutorials

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Can you do analytics—either kind—using Excel? Sure. Excel has a large array of tools that bear directly on analytics, including various mathematical and statistical functions that calculate logarithms, regression statistics, matrix multiplication and inversion, and many of the other tools needed for different kinds of analytics. But not all the tools are native to Excel. 

 For example, some situations call for you to use logistic regression: a technique that can work much better than ordinary least-squares regression when you have an outcome variable that takes on a very limited range of values, perhaps only two. Odds ratios are the workhorses of logistic regression, but although Excel offers a generous supply of least-squares functions, it doesn’t offer a maximum likelihood odds ratio function. 

The below list makes you strong in Excel analytics

  1. Microsoft Excel 2010 Data Analysis With Functions
  2. Analytics with Excel - Book
  3. Cloud data analytics from Excel
  4. Quantitative Analysis with Excel
  5. Data Analysis Using SQL and Excel
  6. Excel Analytics 

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