A Selection Of Python Tutorials for Analysts - Issue 61

A roundup of my favorite tutorials for data analysts to either get started with or upkeep existing Python skills

Hello analysts! As promised earlier, today’s newsletter is all about Python tutorials. I am sure every one of you has your own list of handy videos, courses, and go-to pages for Python solutions and tips. In this issue, I am going to save you countless hours of research and share my favorite list of Python tutorials for data processing, transformations, cleaning, analysis, and visualizations. 

A little pre-history: I started my analytical journey with R (like any gray-haired medieval analyst today). And after all that time, I still think R language is the most suited for statistics and analysis. I had to make a switch because every team I was a part of was using Python, and many projects we collaborated on were also done in Python. 

My transition from R to Python was … long. I think I went through every Python class out there. After too many tutorials, I started making a list of my favorite go-to videos and lessons which I still use and keep updating to this day. Most of those are (or were) free, but things change, so it is possible some of the classes below are not free anymore.  

You probably have noticed already that I’m a fan of Real Python tutorials. I think they have a good combination of theory and examples, covering everything from basics to advanced development. So many of my favorite sources come from there.

Installation

• Python Basics: Setting Up Python

• Installing Python on Windows, macOS, and Linux

• Setting up a Python Development Environment in Sublime Text (if anyone is using Sublime)

• Python Tutorial: Anaconda - Installation

Basics

• How To Import Data Into Python?

• Reading and Writing CSV Files

• Reading and Writing Files With Pandas

• Using Jupyter Notebooks

• The Pandas DataFrame: Working With Data Efficiently

• Pandas, Data Frame, and Data Series - really like this channel. Data frame and series explanations are very good.

• Pandas DataFrames 101

Data Types

• Basic Data Types in Python

• Python cheatsheet - basics

• Data Structures and Algorithms in Python - Full Course for Beginners

• Variables in Python

• Lists and Tuples in Python

• Python Tuple

• Python Lists - Basics

• Dictionaries and Arrays: Selecting the Ideal Data Structure

• Python Dictionaries

• Defining and Calling Python Functions

Data cleaning and EDA

• Data Preprocessing with NumPy

• Pythonic Data Cleaning With Pandas and NumPy

• Pandas Sort: Your Guide to Sorting Data in Python

• Pandas GroupBy: Your Guide to Grouping Data in Python

• Grouping and Aggregating - Analyzing and Exploring Your Data

• Filtering - Using Conditionals to Filter Rows and Columns

• Cheat Sheet for Exploratory Data Analysis in Python - infographic by Analytics Vidhya

• Explore Your Dataset With Pandas

• Data Analysis with Python (EDA)

• Cleaning Data - Casting Datatypes and Handling Missing Values

• Working with Dates and Time Series Data

• Generating Random Data in Python (not cleaning or EDA, but helpful for testing)

Analysis and some simple ML

• Python Statistics Fundamentals: How to Describe Your Data

• Introduction - Data Analysis and Data Science with Python and Pandas

• NumPy, SciPy, and Pandas: Correlation With Python

• Seaborn Tutorial

• Linear Regression in Python

• Linear Regression

• Logistic Regression in Python

• Splitting Datasets - train_test_split()

• Intro into NLP

• Machine Learning Tutorial with Python Intro

• Creating an SVM from scratch

SQL

• Introduction to Python SQL Libraries

• SQLite Databases With Python - Full Course

• Practical SQL for Data Analysis

Plots

• Plot With Pandas: Python Data Visualization Basics

• Matplotlib – An Intro to Creating Graphs with Python

• Creating and Customizing Our First Plots

• Python Plotting With Matplotlib

• Chart Visualization - pandas documentation

• Python Histogram Plotting: NumPy, Matplotlib, Pandas & Seaborn

• Bar Charts

• Stack Plots

• Plotting Time Series Data

• Scatter Plots

• Histograms

Other

• Learn Python - Full Course for Beginners - a full complete course (4 hours) of Python Intro.

• Python Data Science Handbook - The entire Python Data Science Handbook, in the form of free Jupyter notebooks.

• Astronomical Data in Python - the code is written in Jupyter notebooks. You can run the notebooks either on Colab or in your own environment (you can download them from the repository and follow the instructions to set up your environment).

• StatQuest with Josh Starmer - less Python and mostly ML.

• Ultimate Python study guide - all in one: a good resource and guide. 

• Python from Nisha M - a good explanation about data types.

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I have another list for SQL and Statistics tutorials, which I’ll share soon as well. I continually update this list to keep it fresh and relevant, so please, send me your favorite Python links and sources that you think I should add!  

Thanks for reading, everyone. Until next Wednesday!