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 and Hello World
  2. Python: Arithmetic Operations and Variables
  3. Python: Print Variables and User Input
  4. Python: Printing with .format()
  5. Python: Lists and Dictionaries
  6. Python: Working with Lists
  7. Python: Working with Dictionaries
  8. Python: Tuples and Sets
  9. Python Conditional Logic
  10. Python Loops
  11. Python Functions
  12. Python: Enumerate() and Sort
  13. Python: Error handling
  14. Python lambda, map(), reduce(), filter()
  15. Python zip and unpack
  16. Python list comprehensions
  17. Python: Generators
  18. Python: Regular Expressions
  19. Python: **Kwargs and *Args
  20. Python: Closures
  21. Python: Decorators


  1. Python: Intro to Graphs
  2. Python: Line Graph
  3. Python: Create, Import, and Use a Module
  4. Python: Working with CSV Files

Working with files and folders

  1. Python: Read all files in a folder

Object Oriented Programming

  1. Python: Object Oriented Programming
  2. Python: Closures
  3. Python: Decorators

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: Rename Columns in a Dataframe
  7. Python: Working with Rows in a DataFrame
  8. Python: An Interesting Problem with Pandas
  9. Python: Pivot Tables with Pandas
  10. Python: Read CSV and Excel with Pandas
  11. Python: Accessing a SQL Server database
  12. Python: Connect to a MySQL Database
  13. Python: Convert Datetime to Date using Pandas


  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: Build a word cloud


  1. Python: Create a Blockchain Hash Function
  2. Python: Simulate Blockchain Mining

Web Scraping/Automation

  1. Python: Using Selenium to open a website in Chrome
  2. Python: Using Selenium to open a website in Firefox
  3. Python: Using Selenium to open a website in MS Edge
  4. Python: Setting Chrome browser size with Selenium
  5. Python: Using Selenium to interact with website
  6. Python: Webscraping using Requests
  7. Python: Webscraping with Requests and BeautifulSoup
  8. Python: Webscraping using Request and BeautifulSoup to identify website content