Tag: Learn Python

Python Cheat Sheet for Data Science: Basics

It’s common when first learning Python for Data Science to have trouble remembering all the syntax that you need. While at Dataquest we advocate getting used to consulting the Python documentation, sometimes it’s nice to have a handy reference, so we’ve put together this cheat sheet to help you out! This cheat sheet is the […]

Should I Learn Python 2 or 3?

One of the biggest sources of confusion and misinformation for people wanting to learn Python is which version they should learn. Should I learn Python 2.x or Python 3.x? Indeed, this is one of the questions we are asked most often at Dataquest, where we teach Python as part of our Data Science curriculum. This […]

SettingwithCopyWarning: How to Fix This Warning in Pandas

SettingWithCopyWarning: Everything you need to know about the most common (and most misunderstood) warning in pandas and how to fix it!

Getting Started with Kaggle: House Prices Competition

Founded in 2010, Kaggle is a Data Science platform where users can share, collaborate, and compete. One key feature of Kaggle is “Competitions”, which offers users the ability to practice on real-world data and to test their skills with, and against, an international community. This guide will teach you how to approach and enter a […]

NumPy Cheat Sheet — Python for Data Science

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 many important 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 […]

Turbocharge Your Data Acquisition using the data.world Python Library

When working with data, a key part of your workflow is finding and importing data sets. Being able to quickly locate data, understand it and combine it with other sources can be difficult. One tool to help with this is data.world, where you can search for, copy, analyze, and download data sets. In addition, you […]

1 tip for effective data visualization in Python

Yes, you read correctly — this post will only give you 1 tip. I know most posts like this have 5 or more tips. I once saw a post with 15 tips, but I may have been daydreaming at the time. You’re probably wondering what makes this 1 tip so special. “Vik”, you may ask, […]

How to present your data science portfolio on GitHub

This is the fifth and final post in a series of posts on how to build a Data Science Portfolio. In the previous posts in our portfolio series, we talked about how to build a storytelling project, how to create a data science blog, how to create a machine learning project, and how to construct […]

How to get a data science job

You’ve done it. You just spent months learning how to analyze data and make predictions. You’re now able to go from raw data to well structured insights in a matter of hours. After all that effort, you feel like it’s time to take the next step, and get your first data science job. Unfortunately for […]

Pandas Tutorial: Data analysis with Python: Part 2

We covered a lot of ground in Part 1 of our pandas tutorial. We went from the basics of pandas DataFrames to indexing and computations. If you’re still not confident with Pandas, you might want to check out the Dataquest pandas Course. In this tutorial, we’ll dive into one of the most powerful aspects of […]

What’s New in Dataquest v1.9: Console, hotkeys, and more!

Whenever you send us feedback or an ideas for a feature, we read and catalogue your suggestions. We then use this to help planning features and improvements for Dataquest. Today we’re excited to launch two of our most-requested features: Hotkeys and a Python Console. Introducing the Python console Many of you have told us that […]

NumPy Tutorial: Data Analysis with Python

Don’t miss our FREE NumPy cheat sheet at the bottom of this post NumPy is a commonly used Python data analysis package. By using NumPy, you can speed up your workflow, and interface with other packages in the Python ecosystem, like scikit-learn, that use NumPy under the hood. NumPy was originally developed in the mid […]

28 Jupyter Notebook Tips, Tricks, and Shortcuts

Jupyter Notebook is a powerful tool for data analysis. Here are 28 tips, tricks, and shortcuts to turn you into a Jupyter notebooks power user!

Working with SQLite Databases using Python and Pandas

In this post, you’ll learn to query, update, and create SQLite databases in Python. And learn how to use the pandas package to speed up your workflow.

Tutorial: Working with Streaming Data and the Twitter API in Python

Learn how to work with streaming data for data science in Python by using Twitter’s API in this intermediate Python tutorial.