What is Python?

Python is a high level, object oriented programming language. While Python is very powerful, it’s syntax makes Python simple to learn.

Python is very popular among data scientists, but it is not solely used for analytics. Here is a list of popular applications written in Python:

  • BitTorrent
  • Dropbox
  • Morpheus
  • Ubuntu Software Center
  • Battlefield 2

This website is dedicated to Analytics, so the Python tutorials have been shaped with that in mind. I have purposefully eliminated a lot of information that doesn’t lend itself well to data work. If you are looking for a soup to nuts Python tutorial, this is not it. However, if you are looking for a streamlined education in Python for Analytics, you have found it.



  1. Python: Install Python
  2. Python Fundamentals
  3. Python: Print Variables and User Input
  4. Python: Printing with .format()
  5. Python: Lists and Dictionaries
  6. Python: Tuples and Sets
  7. Python Loops
  8. Python Conditional Logic
  9. Python Functions
  10. Python: Working with Lists
  11. Python: Enumerate() and Sort
  12. Python: Error handling


  1. Python lambda, map(), reduce(), filter()
  2. Python zip and unpack
  3. Python list comprehensions
  4. Python: Intro to Graphs
  5. Python: Line Graph
  6. Python: Generators
  7. Python: Regular Expressions
  8. Python: **Kwargs and *Args
  9. Python: Create, Import, and Use a Module
  10. Python: Working with CSV Files

Object Oriented Programming

  1. Python: Object Oriented Programming

Numpy and Pandas

  1. Python: Numpy
  2. Python: Numpy Part II
  3. Python: Pandas Intro (Series)
  4. Python: Pandas Intro (Dataframes)
  5. Python: Pandas, Working with DataFrames
  6. Python: An Interesting Problem with Pandas
  7. Python: Pivot Tables with Pandas
  8. Python: Read CSV and Excel with Pandas
  9. Python: Accessing a SQL database


  1. Python: Fun with Central Tendency
  2. Python: Histograms and Frequency Distribution
  3. Python: Central Limit Theorem
  4. Python: Co-variance and Correlation
  5. Python: Hypothesis Testing(T Test)
  6. Python: Create a Box whisker plot


  1. Python: Linear Regression
  2. Python: Logistic Regression

Supervised Machine Learning

  1. Python: K Nearest Neighbor
  2. Python: Naive Bayes’
  3. Python: Support Vector Machine (SVM)

Unsupervised Machine Learning

  1. Python: K Means Cluster
  2. Python: K Means Clustering Part 2

Machine Learning Evaluation Metrics

  1. Python: Confusion Matrix


  1. Python: Create a Blockchain Hash Function