Resources

Here is collection of resources, mainly from this website and others, for learning Python and R for data science. Basically, this is mainly a collated list of posts on Python and R, all in one place categorized by topic.

Python: Pandas

  1. 7 Tips to Read a CSV File as Pandas Data Frame
  2. How to Create Pandas Dataframe from Multiple Lists?
  3. How To Reset Index in Pandas Dataframe?
  4. How To Drop One or More Columns in Pandas Dataframe?
  5. How To Change Column Names and Row Indexes in Pandas?
  6. How to Get Frequency Counts of a Column in Pandas Dataframe?
  7. How to Get Unique Values from a Column in Pandas Data Frame?
  8. How to Filter a Pandas Dataframe Based on Null Values of a Column?
  9. How To Filter Pandas Dataframe By Values of Column?
  10. How To Randomly Select Rows in Pandas?: Pandas Tutorial
  11. Introduction to Split-Apply-Combine with Pandas
  12. 6 ways to Sort Pandas Dataframe: Pandas Tutorial
  13. How To Add a New Column to Using a Dictionary in Pandas Data Frame ?
  14. How to Load a Massive File as small chunks in Pandas?

Python: Data Visualizations

  1. An Introduction to Altair: A Python Visualization Library
  2. How to Make Boxplots in Python with Pandas and Seaborn?
  3. Python’s Matplotlib Version 2.2 is here
  4. Probability Distributions in Python with SciPy and Seaborn

Python: NumPy and SciPy

  1. 12 Basic Commands with NumPy Array
  2. How to read a numerical data/file in Python with numpy?
  3. How To Concatenate Arrays in NumPy?
  4. Probability Distributions in Python with SciPy and Seaborn?
  5. Introduction to Sparse Matrices in Python with SciPy

R Resources for Data Science

Python Resources for Data Science

  1. Materials and Jupyter notebooks for “Python for Data Analysis 2nd Edition” by Wes McKinney,
  2. Code from IPython book Second Edition, by Cyrille Rossan
  3. Code from Introduction to Machine Learning with Python  book by Andreas Muller and Sarah