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Intermediate Importing Data in Python

Improve your Python data importing skills and learn to work with web and API data.

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2 Hours7 Videos28 Exercises136,009 Learners2300 XPData Analyst TrackData Scientist TrackImporting & Cleaning Data Track

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Course Description

As a data scientist, you will need to clean data, wrangle and munge it, visualize it, build predictive models and interpret these models. Before you can do so, however, you will need to know how to get data into Python. In the prequel to this course, you learned many ways to import data into Python: from flat files such as .txt and .csv; from files native to other software such as Excel spreadsheets, Stata, SAS, and MATLAB files; and from relational databases such as SQLite and PostgreSQL. In this course, you'll extend this knowledge base by learning to import data from the web and by pulling data from Application Programming Interfaces— APIs—such as the Twitter streaming API, which allows us to stream real-time tweets.

  1. 1

    Importing data from the Internet


    The web is a rich source of data from which you can extract various types of insights and findings. In this chapter, you will learn how to get data from the web, whether it is stored in files or in HTML. You'll also learn the basics of scraping and parsing web data.

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    Importing flat files from the web
    50 xp
    Importing flat files from the web: your turn!
    100 xp
    Opening and reading flat files from the web
    100 xp
    Importing non-flat files from the web
    100 xp
    HTTP requests to import files from the web
    50 xp
    Performing HTTP requests in Python using urllib
    100 xp
    Printing HTTP request results in Python using urllib
    100 xp
    Performing HTTP requests in Python using requests
    100 xp
    Scraping the web in Python
    50 xp
    Parsing HTML with BeautifulSoup
    100 xp
    Turning a webpage into data using BeautifulSoup: getting the text
    100 xp
    Turning a webpage into data using BeautifulSoup: getting the hyperlinks
    100 xp
  2. 2

    Interacting with APIs to import data from the web

    In this chapter, you will gain a deeper understanding of how to import data from the web. You will learn the basics of extracting data from APIs, gain insight on the importance of APIs, and practice extracting data by diving into the OMDB and Library of Congress APIs.

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  3. 3

    Diving deep into the Twitter API

    In this chapter, you will consolidate your knowledge of interacting with APIs in a deep dive into the Twitter streaming API. You'll learn how to stream real-time Twitter data, and how to analyze and visualize it.

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In the following tracks

Data Analyst Data Scientist Importing & Cleaning Data


fgcastroFrancisco Castro
Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist at DataCamp

Hugo is a data scientist, educator, writer and podcaster at DataCamp. His main interests are promoting data & AI literacy, helping to spread data skills through organizations and society and doing amateur stand up comedy in NYC. If you want to know what he likes to talk about, definitely check out DataFramed, the DataCamp podcast, which he hosts and produces:
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I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

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Harvard Business School

DataCamp is by far my favorite website to learn from.

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Decision Science Analytics, USAA