Datacamp Cheat Sheet



Data Science Cheat Sheet (Datacamp) The datacamp cheat sheets are always worth a look. However, I would recommend this cheat sheet only for absolute beginners in the field of data science. If you focus on learning core machine learning concepts and you already have some experience, please skip this cheat sheet. Now, DataCamp has created a Keras cheat sheet for those who have already taken the course and that still want a handy one-page reference or for those who need an extra push to get started.

  1. Pandas Cheat Sheet Datacamp
  2. Datacamp Cheat Sheet Numpy

This post updates a previous very popular post 50+ Data Science, Machine Learning Cheat Sheets by Bhavya Geethika. If we missed some popular cheat sheets, add them in the comments below.

Cheatsheets on Python, R and Numpy, Scipy, Pandas

Datacamp Cheat Sheet

Data science is a multi-disciplinary field. Thus, there are thousands of packages and hundreds of programming functions out there in the data science world! An aspiring data enthusiast need not know all. A cheat sheet or reference card is a compilation of mostly used commands to help you learn that language’s syntax at a faster rate. Here are the most important ones that have been brainstormed and captured in a few compact pages.

Mastering Data science involves understanding of statistics, mathematics, programming knowledge especially in R, Python & SQL and then deploying a combination of all these to derive insights using the business understanding & a human instinct—that drives decisions.

  • SpaCy Cheat Sheet: Advanced NLP in Python March 12th, 2019 spaCy is a popular Natural Language Processing library with a concise API. This cheat sheet shows you how to load models, process text, and access linguistic annotations, all with a few handy objects and functions.
  • Python For Data Science Cheat Sheet Kickstart your data science journey with this Python cheat sheet that contains code examples for strings, lists, importing libraries and NumPy arrays. Find more cheat sheets and learn data science with Python at www.datacamp.com.

Here are the cheat sheets by category:

Cheat sheets for Python:

Python is a popular choice for beginners, yet still powerful enough to back some of the world’s most popular products and applications. It's design makes the programming experience feel almost as natural as writing in English. Python basics or Python Debugger cheat sheets for beginners covers important syntax to get started. Community-provided libraries such as numpy, scipy, sci-kit and pandas are highly relied on and the NumPy/SciPy/Pandas Cheat Sheet provides a quick refresher to these.

  1. Python Cheat Sheet by DaveChild via cheatography.com
  2. Python Basics Reference sheet via cogsci.rpi.edu
  3. OverAPI.com Python cheatsheet
  4. Python 3 Cheat Sheet by Laurent Pointal

Cheat sheets for R:

Cheat

The R's ecosystem has been expanding so much that a lot of referencing is needed. The R Reference Card covers most of the R world in few pages. The Rstudio has also published a series of cheat sheets to make it easier for the R community. The data visualization with ggplot2 seems to be a favorite as it helps when you are working on creating graphs of your results.

At cran.r-project.org:

Datacamp

At Rstudio.com:

  1. R markdown cheatsheet, part 2

Others:

  1. DataCamp’s Data Analysis the data.table way

Cheat sheets for MySQL & SQL:

For a data scientist basics of SQL are as important as any other language as well. Both PIG and Hive Query Language are closely associated with SQL- the original Structured Query Language. Download anydesk. SQL cheatsheets provide a 5 minute quick guide to learning it and then you may explore Hive & MySQL!

  1. SQL for dummies cheat sheet

Cheat sheets for Spark, Scala, Java:

Apache Spark is an engine for large-scale data processing. For certain applications, such as iterative machine learning, Spark can be up to 100x faster than Hadoop (using MapReduce). The essentials of Apache Spark cheatsheet explains its place in the big data ecosystem, walks through setup and creation of a basic Spark application, and explains commonly used actions and operations.

  1. Dzone.com’s Apache Spark reference card
  2. DZone.com’s Scala reference card
  3. Openkd.info’s Scala on Spark cheat sheet
  4. Java cheat sheet at MIT.edu
  5. Cheat Sheets for Java at Princeton.edu

Cheat sheets for Hadoop & Hive:

Hadoop emerged as an untraditional tool to solve what was thought to be unsolvable by providing an open source software framework for the parallel processing of massive amounts of data. Explore the Hadoop cheatsheets to find out Useful commands when using Hadoop on the command line. A combination of SQL & Hive functions is another one to check out.

Cheat sheets for web application framework Django:

Django is a free and open source web application framework, written in Python. If you are new to Django, you can go over these cheatsheets and brainstorm quick concepts and dive in each one to a deeper level.

  1. Django cheat sheet part 1, part 2, part 3, part 4

Cheat sheets for Machine learning:

We often find ourselves spending time thinking which algorithm is best? And then go back to our big books for reference! These cheat sheets gives an idea about both the nature of your data and the problem you're working to address, and then suggests an algorithm for you to try.

  1. Machine Learning cheat sheet at scikit-learn.org
  2. Scikit-Learn Cheat Sheet: Python Machine Learning from yhat (added by GP)
  3. Patterns for Predictive Learning cheat sheet at Dzone.com
  4. Equations and tricks Machine Learning cheat sheet at Github.com
  5. Supervised learning superstitions cheatsheet at Github.com

Cheat sheets for Matlab/Octave

MATLAB (MATrix LABoratory) was developed by MathWorks in 1984. Matlab d has been the most popular language for numeric computation used in academia. It is suitable for tackling basically every possible science and engineering task with several highly optimized toolboxes. MATLAB is not an open-sourced tool however there is an alternative free GNU Octave re-implementation that follows the same syntactic rules so that most of coding is compatible to MATLAB.

Cheat sheets for Cross Reference between languages

Related:

Hey Finxters! I have another set of cheat sheets for you! This time, I am going to focus on the more advanced aspects of Python and what you can do with it! As you know Python is a flexible language used in web development, games, and desktop applications. I am not going to waste too much of your time so let’s hop right to it and dive into these more advanced Python cheat sheets!

Cheat Sheet 0: Finxter Full Cheat Sheet Course

Cheat Sheet 1: DataQuest

This cheat sheet is from DataQuest and it shows all of the intermediate Python

Regular expressions, date/time module, and counter. This is one you will want to have pinned to the wall or in your developers binder to keep handy as you work.

Pros: Great for budding Python developers, keep it handy as you work.

Cons: None that I can see.

Cheat Sheet 2: DataCamp

It is important to know how to import data during your career no matter what stage you are at. As an intermediate Pythoner, you should keep this cheat sheet handy when working an entry level job of data entry and developing you own projects.

Backblaze cloud storage. Pros: Great for learning importing data sets in Python.

Cons: None that I can see.

Cheat Sheet 3: DataCamp

You have to import data and you have to be able to plot it as a visual representation for businesses to understand and use to their benefit. This cheat sheet will help you to learn matplotlib and write some amazing graphical visualizations with Python.

Pros: Great to have for matplotlib development.

Cons: None that I can see.

Cheat Sheet 4: GitHub

This cheat sheet is for Machine learning and one you will want to keep in your developers binder as you work. Machine learning and Python go together like peanut butter and jelly, and Scikit is going to be your best friend. If your developers journey takes you to machine learning then make sure to keep this cheat handy for yourself.

Pros: Scikit is easily learnable with this cheat sheet

Cons: None that I can see.

Cheat Sheet 5: DataCamp

SQL is a database system used in programming for all kinds of data sets and is extremely scalable. Keep this cheat sheet handy to you! BI and other business applications rely on you being able to use SQL!

Pros: Rated ‘E’ for everyone. Easy to read and implement

Python pandas cheat sheet pdf

Cons: None that I can see.

Cheat Sheet 6: Pytorch

This cheat sheet is more a tutorial that will teach you pytorch for deep learning projects. Here you will get hands on practice on pytorch.

Pros: You will get a deep understanding pytorch and how it used

Cons: It is an online tutorial.

Cheat Sheet 7: DataCamp

Yet another from Datacamp!! This one is called SpaCy and allows you to understand the natural text from documents. This is one I have in my development folder and is used for Natural language programming. T shirt design software, free download for mac.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 8: Ask Python

This cheat sheet is also more a tutorial for you to learn image processing in Python. The best way to learn is to get your hands dirty! Ask Python is good for doing that so you can learn what you need to and boost your skills.

Pros: Rated ‘E’ for everyone.

Pandas Cheat Sheet Datacamp

Cons: None that I can see.

Cheat Sheet 9: TutorialsPoint

This cheat sheet is also a tutorial on learning database access with Python. This is an incredibly important skill when you freelance your skills or end up working for a company at a data entry position.

Datacamp Cheat Sheet Numpy

Pros: Rated ‘E’ for everyone. This tutorial is one I have used myself! It includes code snippets to learn from.

Cons: It is a tutorial, not a cheat sheet to print.

Cheat Sheet 10: FullStack Python

This is also a tutorial for you to learn from. This particular cheat sheet discusses Deployment of web applications in Python!! It has explanations that go into depth with tools, resources and learning checklist which is started off with an introductory on deployment what it is and why it is necessary.

Pros: Rated ‘E’ for everyone. This is important to know if you are a Pythoner in Web development.

Cons: Needs to be bookmarked on your browser.

These are the cheat sheets and tutorials I think you will find helpful as a Pythonista developing in your particular field. As you can see this time, I wanted to really give you a wide berth of cheat sheets that intermediate Pythonista use with their career choices. I hope at least one of these cheat sheets or tutorials is useful to you on your journey! Thank you once again for joining me and I can’t wait to see you again! 😉😉

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