Matplotlib cheatsheets and handouts¶
Cheatsheets [pdf]
Handouts¶
Beginner [pdf]
Intermediate [pdf]
Tips [pdf]
Contribute¶
Issues, suggestions, or pull-requests gratefully accepted at matplotlib/cheatsheets
This section provides a few cheat sheets related with python, data wrangling and data visualization. Even with a perfect understanding of python and its libraries, it's almost impossible to remember the syntax of each function of the ecosystem. That's where cheatsheets are useful 🔥!
Matplotlib cheatsheet
Datacamp provides a
cheatsheet describing the basics of matplotlib. Matplotlib is the most widely used library for datavisualization with python. You can read more about it on its dedicated page.
The following 2 cheatsheets from the official matplotlib repository are also very handy:
Matplotlib cheatsheet by matplotlib [page 1].
Matplotlib cheatsheet by matplotlib [page 2].
Seaborn cheatsheet
Datacamp provides a cheatsheet describing the basics of seaborn. Seaborn is also a widely used library for datavisualization with python. It allows to get very clean chart with less code. You can read more about it on its
dedicated page.
Pandas cheatsheet
Datacamp provides a cheatsheet describing the basics of pandas. Pandas is mainly used for data manipulation with Python, but also offers some dataviz helpers.
Timeseries
Animation
List of Data Science Cheatsheets to rule the world.
Table of Contents
- Business Science
- Python
- R
- Math and Calculus
- Big Data
- Machine Learning
- Deep Learning
- SQL
- Data Visualization
- Data Science in General and Others
Business Science
Business Science Problem Framework [PDF]
Data Science with Python Workflow [PDF]
Data Science with R Workflow [PDF]
Python
Datacamp
Python Basics [PDF]
Pandas Basics [PDF]
Pandas [PDF]
Importing Data [PDF]
Jupyter [PDF]
Numpy Basics [PDF]
SciPy [PDF]
Python Crash Course
- Begginers Python Cheat Sheet [Long PDF]
Dataquest
- Intermediate Python [PDF]
Others
- Python 3 Memento [PDF]
R
Datacamp
Tidiverse [PDF]
data.table [PDF]
-xts [PDF]
RStudio
R Studio IDE [PDF]
Base R [PDF]
Data Import with readr [PDF]
Data Transformation with Dplyr [PDF]
Apply Functions with purrr [PDF]
Data transformation with data.table [PDF]
Dates and Times with lubridate [PDF]
Randomizr [PDF]
Regular Expressions [PDF]
Work with Strings with stringr [PDF]
Tidy Evaluation with rlang [PDF]
Xplain [PDF]
Syntax Comparison [PDF]
Data and Variable Transformation with sjmisc [PDF]
R Markdown [PDF]
Package Development with devtools [PDF]
Math and Calculus
From @afshinea, @stat110 and @wzchen:
Big Data
Python
- Pyspark RDD [PDF]
- Pyspark DF [PDF]
- Dask [PDF]
R
- Sparklyr [PDF]
Machine Learning
Python
- Scikit-Learn [PDF]
R
- Machine Learning Modelling in R [PDF]
- Caret [PDF]
- Estimatr [PDF]
_ H2O [PDF]
- mlr [PDF]
Supervised Learning
From @afshinea:
- VIP Supervised Learning [PDF]
Unsupervised Learning
From @afshinea:
- VIP Unsupervised Learning [PDF]
Hacks, tricks and tips
From @afshinea:
- VIP Machine Learning Tips and Tricks [PDF]
Chossing the right model
Microsoft Azure Machine Learning: Algorithm [PDF]
ML Map_Scikit-Learn [PDF]
Deep Learning
Neural Nets
Neural Network Cells [PDF]
Neural Network Graphs [PDF]
Complete Chart of Neural Networks [PDF]
R
- Keras RStudio [PDF]
Python
- Keras [PDF]
From @afshinea:
- Deep Learning Basics [PDF]
- Convolutional Neural Networkds [PDF]
- Recurrent Neural Networks [PDF]
- Tips and Tricks [PDF]
SQL
- SQL cheatsheet by sqltutorial [PDF]
- SQL cheatsheet by Rebel Labs
Data Visualization
Python
- Matplotlib [PDF]
- Seaborn [PDF]
- Bokeh [PDF]
- Comprehensive Guide to Data Visualization in Python
R
- Ggplot2 [PDF]
- Leaflet [PDF]
- Cartography [PDF]
- Comprehensive Guide to Data Visualization in R
- Simple Features sf [PDF]
- survminer [PDF]
Data Science in General and Others
- Shiny [PDF]
- Vim [PDF]
- Emacs [PDF]
- Git - Atlassian’s Cheatsheet [PDF]
- BASH [PDF]
By @ml874
- Data Science Cheatsheet [PDF]