NumPy is the library that gives Python its ability to work with data at speed. Originally, launched in 1995 as ‘Numeric,’ NumPy is the foundation on which man importany Python data science libraries are built, including Pandas, SciPy and scikit-learn.
It’s common when first learning NumPy to have trouble remembering all the functions and methods that you need, and while at Dataquest we advocate getting used to consulting the NumPy documentation, sometimes it’s nice to have a handy reference, so we’ve put together this cheat sheet to help you out!
If you’re interested in learning pandas, you can consult our NumPy tutorial blog post, or you can signup for free and start learning NumPy through our interactive python data science course.
Numpy Cheat Sheet Python Package Created By: arianne Colton and Sean Chen SCN NDNSUBSN numPy (numerical Python) What is NumPy? Foundation package for scientific computing in Python Why NumPy?. Numpy ‘ndarray’ is a much more efficient way of storing and manipulating “numerical data” than the built-in Python data structures. Data Science Cheat Sheet NumPy KEY We’ll use shorthand in this cheat sheet arr - A numpy Array object IMPORTS Import these to start import numpy as np LEARN DATA SCIENCE ONLINE Start Learning For Free - www.dataquest.io LEARN DATA SCIENCE ONLINE Start Learning For Free - www.dataquest.io.
This beautiful cheat sheet by Justin covers all the primary syntactical techniques used in Numpy. It includes all the primary array operations, multidimensional access, etc. A quick view of the ordinary and binomial distribution is also provided. The Numpy machine learning cheat sheet can be accessed here. Pandas Cheat Sheet by Sanjeev. NumPy / SciPy / Pandas Cheat Sheet Select column. Select row by label. Return DataFrame index. Delete given row or column. Pass axis=1 for columns. Reindex df1 with index of df2. Reset index, putting old index in column named index. Change DataFrame index, new indecies set to NaN. Show first n rows. Show last n rows.
Key and Imports
In this cheat sheet, we use the following shorthand:
You’ll also need to import numpy to get started:
Importing/exporting
Creating Arrays
NumPy is a library for the Python programming language which is used for working with multi-dimensional arrays and matrices. This is very useful in large scientific computing. Because NumPy ndarrays is way faster compared to a regular python list. Arrays are very frequently used in data science too, where speed and resources are very important. That’s why NumPy is a very handy tool in data-science.
But remembering all the NumPy commands might be overwhelming for both beginners and professionals. So Datalators makes the complex simple.
It’s also a good idea to check the official NumPy documentation from time to time. Even if you can find what you need in the cheat sheet. Reading documentation is a skill every data professional needs. Also, the documentation goes into a lot more detail than we can fit in a single sheet anyway!
Creating Arrays:
Import Export:
Inspecting Array:
Data Types:
Array Mathematics:
Statistics on NumPy:
Indexing and Slicing
Array Manipulation:
I hope this cheat sheet will be useful to you. No matter you are new to python who is learning python for data science or a data professional. Happy Programming.
Python Numpy Cheat Sheet Pdf
Wordfast pro 3. You can also download the printable PDF file from here.
Datacamp Numpy Cheat Sheet
The source code for NumPy is located at this GitHub repository.
You might also be interested in Pandas Cheat Sheet For Data Science In Python.