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Introduction to Importing Data in Python

4.6+
88 reviews
Beginner

Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.

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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 this course, you'll learn the 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.
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In the following Tracks

Certification Available

Data Engineer in Python

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Associate Data Scientist in Python

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Importing & Cleaning Data in Python

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  1. 1

    Introduction and flat files

    Free

    In this chapter, you'll learn how to import data into Python from all types of flat files, which are a simple and prevalent form of data storage. You've previously learned how to use NumPy and pandas—you will learn how to use these packages to import flat files and customize your imports.

    Play Chapter Now
    Welcome to the course!
    50 xp
    Importing entire text files
    100 xp
    Importing text files line by line
    100 xp
    The importance of flat files in data science
    50 xp
    Pop quiz: what exactly are flat files?
    50 xp
    Why we like flat files and the Zen of Python
    50 xp
    Importing flat files using NumPy
    50 xp
    Using NumPy to import flat files
    100 xp
    Customizing your NumPy import
    100 xp
    Importing different datatypes
    100 xp
    Importing flat files using pandas
    50 xp
    Using pandas to import flat files as DataFrames (1)
    100 xp
    Using pandas to import flat files as DataFrames (2)
    100 xp
    Customizing your pandas import
    100 xp
    Final thoughts on data import
    50 xp
  2. 2

    Importing data from other file types

    You've learned how to import flat files, but there are many other file types you will potentially have to work with as a data scientist. In this chapter, you'll learn how to import data into Python from a wide array of important file types. These include pickled files, Excel spreadsheets, SAS and Stata files, HDF5 files, a file type for storing large quantities of numerical data, and MATLAB files.

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    Introduction to other file types
    50 xp
    Not so flat any more
    50 xp
    Loading a pickled file
    100 xp
    Listing sheets in Excel files
    100 xp
    Importing sheets from Excel files
    100 xp
    Customizing your spreadsheet import
    100 xp
    Importing SAS/Stata files using pandas
    50 xp
    How to import SAS7BDAT
    50 xp
    Importing SAS files
    100 xp
    Using read_stata to import Stata files
    50 xp
    Importing Stata files
    100 xp
    Importing HDF5 files
    50 xp
    Using File to import HDF5 files
    50 xp
    Using h5py to import HDF5 files
    100 xp
    Extracting data from your HDF5 file
    100 xp
    Importing MATLAB files
    50 xp
    Loading .mat files
    100 xp
    The structure of .mat in Python
    100 xp
  3. 3

    Working with relational databases in Python

    In this chapter, you'll learn how to extract meaningful data from relational databases, an essential skill for any data scientist. You will learn about relational models, how to create SQL queries, how to filter and order your SQL records, and how to perform advanced queries by joining database tables.

    Play Chapter Now
    Introduction to relational databases
    50 xp
    Pop quiz: The relational model
    50 xp
    Creating a database engine in Python
    50 xp
    Creating a database engine
    100 xp
    What are the tables in the database?
    100 xp
    Querying relational databases in Python
    50 xp
    The Hello World of SQL Queries!
    100 xp
    Customizing the Hello World of SQL Queries
    100 xp
    Filtering your database records using SQL's WHERE
    100 xp
    Ordering your SQL records with ORDER BY
    100 xp
    Querying relational databases directly with pandas
    50 xp
    Pandas and The Hello World of SQL Queries!
    100 xp
    Pandas for more complex querying
    100 xp
    Advanced querying: exploiting table relationships
    50 xp
    The power of SQL lies in relationships between tables: INNER JOIN
    100 xp
    Filtering your INNER JOIN
    100 xp
    Final Thoughts
    50 xp
For Business

Training 2 or more people?

Get your team access to the full DataCamp platform, including all the features.

In the following Tracks

Certification Available

Data Engineer in Python

Go To Track
Certification Available

Associate Data Scientist in Python

Go To Track

Importing & Cleaning Data in Python

Go To Track

datasets

Chinook (SQLite)LIGO (HDF5)Battledeath (XLSX)Extent of infectious diseases (DTA)Gene expressions (MATLAB)MNISTSales (SAS7BDAT)SeaslugsTitanic

collaborators

Collaborator's avatar
Francisco Castro

prerequisites

Intermediate Python
Hugo Bowne-Anderson HeadshotHugo Bowne-Anderson

Data Scientist

Hugo is a data scientist, educator, writer and podcaster formerly 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 hosted and produced.
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*4.6
from 88 reviews
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  • Andrés O.
    14 days

    Estoy aprendiendo muchisimo con sus videos. Son didacticos y explicativos. Me encanta!

  • Joseph A.
    23 days

    This course was very insightful.

  • Ma S.
    about 1 month

    We’ll explained and organized introduction to importing data in Python. It gives a solid background to importing data especially showcasing the power of pandas.

  • Ileana R.
    2 months

    Wonderful course! Very clear and interesting. Looking forward to continuing with part 2.

  • Mark C.
    3 months

    Very well laid out. Intuitive and easy to follw

"Estoy aprendiendo muchisimo con sus videos. Son didacticos y explicativos. Me encanta!"

Andrés O.

"This course was very insightful."

Joseph A.

"We’ll explained and organized introduction to importing data in Python. It gives a solid background to importing data especially showcasing the power of pandas."

Ma S.

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