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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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R Language: Data types and structures

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To make the best of the R language, you'll need a strong understanding of the basic data types and data structures and how to operate on those. Very Important to understand because these are the things you will manipulate on a day-to-day basis in R. Everything in R is an object.

R language
The basic data types 
  • logical (e.g., TRUE, FALSE)
  • integer (e.g,, 2L, as.integer(3))
  • numeric (real or decimal) (e.g, 2, 2.0, pi)
  • complex (e.g, 1 + 0i, 1 + 4i)
  • character (e.g, "a", "swc")
The basic data structures in R
  • vector
  • list
  • matrix
  • data frame
  • factors
  • tables
Vector in R
A vector is the most common and basic data structure in R and is pretty much the workhorse of R. 
Vectors can be of two types:
  • atomic vectors
  • lists

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