Data Mining¶
Seaborn cheat sheet Python notebook using data from no data sources 2,078 views 1y ago. Copy and Edit 6. Seaborn Exercises - Exercises Great Job! Input Execution Info Log Comments (4) Cell link copied. This Notebook has been released under.
- Datacamp provides 3 cheatsheets describing the basics of matplotlib, seaborn and pandas: the 3 most commonly used library for data analysis with python: Matplotlib cheat sheet. Pandas cheat sheet. Seaborn cheat sheet.
- Seaborn Cheatsheet This is a cheat sheet for using Seaborn in Python. Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
- Data Mining. PDF only.
Python Seaborn Cheat Sheet
Importing Data¶
- Importing Data. PDF.
Keras¶
- Keras. PDF.
Linear Algebra (with Numpy)¶
- Linear Algebra. PDF only.
- SciPy Linear Algebra. PDF.
Machine Learning¶
Machine Learning. PDF only.
- Supervised Learning;
- Unsupervised Learning;
- Deep Learning;
- Machine Learning Tips and Tricks;
- Probabilities and Statistics;
- Linear Algebra and Calculus.
Super pense-bête Machine Learning. PDF only.
Microsoft Azure Machine Learning. PDF.
- scikit-learn. PDF.
.
Numpy¶
- NumPy/SciPy/Pandas Cheat Sheet. PDF.
- Numpy. PDF.
Pandas¶
- Pandas DataFrame Notes. PDF only.
- Pandas. PDF.
- Pandas. PDF.
- Data Wrangling with Pandas. PDF.
Spark¶
- PySpark. PDF.
- PySpark SQL. PDF.
Visualization¶
Bokeh¶
- Bokeh. PDF.
Folium¶
- Folium. PDF.
Matplotlib¶
- Matplotlib Notes. PDF only.
- Matplotlib. PDF.
Plotly¶
- Plotly. PDF only.
Seaborn¶
- Seaborn. PDF.
Data Visualization Cheat Sheet
Karlijn Willems
You most probably will know by now that data storytelling, accomplished by data visualization, amongst other things, is an essential skill for every data scientist: after you have turned the raw data into understanding, insights and knowledge, you also need to communicate these findings effectively to your audience.
For most beginners, the first Python data visualization library that they use is, naturally, Matplotlib. It is a Python 2D plotting library that enables users to make publication-quality figures. It is quite an extensive library where a cheat sheet will definitely come in handy when you’re learning, but when you manage to use this library effectively, you’ll also be able to get insights and work better with other packages, such as Pandas, that intend to build more plotting integration with Matplotlib as time goes on.
Another package that you’ll be able to tackle is Seaborn, the statistical data visualization library of Python.
DataCamp has created a Seaborn cheat sheet for those who are ready to get started with this data visualization library with the help of a handy one-page reference.
You’ll see that this cheat sheet presents you with the five basic steps that you can go through to make beautiful statistical graphs in Python.