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.

Welcome to the course!

Importing entire text files

Importing text files line by line

The importance of flat files in data science

Pop quiz: what exactly are flat files?

Why we like flat files and the Zen of Python

Importing flat files using NumPy

Using NumPy to import flat files

Customizing your NumPy import

Importing different datatypes

Importing flat files using pandas

Using pandas to import flat files as DataFrames (1)

Using pandas to import flat files as DataFrames (2)

Customizing your pandas import

Final thoughts on data import

Introduction and flat files

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.

Introduction to other file types

Not so flat any more

Loading a pickled file

Listing sheets in Excel files

Importing sheets from Excel files

Customizing your spreadsheet import

Importing SAS/Stata files using pandas

How to import SAS7BDAT

Importing SAS files

Using read_stata to import Stata files

Importing Stata files

Importing HDF5 files

Using File to import HDF5 files

Using h5py to import HDF5 files

Extracting data from your HDF5 file

Importing MATLAB files

Loading .mat files

The structure of .mat in Python

Importing data from other file types

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.

Introductie tot relationele databases

Popquiz: Het relationele model

Een database-engine maken in Python

Een database-engine maken

Welke tabellen staan er in de database?

Relationale databases bevragen in Python

De Hello World van SQL-queries!

Het Hello World van SQL-queries aanpassen

Je databaserecords filteren met SQL's WHERE

Je SQL-records ordenen met ORDER BY

Relationale databases rechtstreeks bevragen met pandas

Pandas en de Hello World van SQL-queries!

Pandas voor complexere queries

Geavanceerde queries: relaties tussen tabellen benutten

De kracht van SQL zit in relaties tussen tabellen: INNER JOIN

Je INNER JOIN filteren

Tot slot

Working with relational databases in Python

Chinook (SQLite)

LIGO (HDF5)

Battledeath (XLSX)

Extent of infectious diseases (DTA)

Gene expressions (MATLAB)

MNIST

Sales (SAS7BDAT)

Seaslugs

Titanic

Course Glossary

Als data scientist moet je data opschonen, verwerken en transformeren, visualiseren, voorspellende modellen bouwen en deze modellen interpreteren. Maar eerst moet je weten hoe je data in Python krijgt. In deze cursus leer je de vele manieren om data in Python te importeren: uit platte bestanden zoals .txt en .csv; uit bestanden van andere software zoals Excel-spreadsheets en Stata-, SAS- en MATLAB-bestanden; en uit relationele databases zoals SQLite en PostgreSQL.

De video's bevatten live-transcripts die je kunt tonen door linksonder in de video op "Show transcript" te klikken.
De cursuswoordenlijst vind je rechts in de sectie met bronnen.
Om CPE-credits te behalen moet je de cursus afronden en een score van 70% halen op de kwalificerende toets. Je gaat naar de toets via de CPE-creditsvermelding aan de rechterkant.

Intermediate Python

Leer data in Python inlezen: van CSV-bestanden tot Excel en relationele databases zoals SQLite & PostgreSQL.

Introductie tot data importeren in Python

Leer hoe je gegevens in Python importeert vanuit verschillende bronnen, zoals Excel, SQL, SAS en direct vanaf het web.

Associate Data Scientist  in Python

Data-engineer in Python

Gegevens importeren en opschonen  in Python

Data Scientist at DataCamp

Tabelnamen ophalen

Laten we oefenen!

Working with relational databases in Python - Een database-engine maken in Python

Een database-engine maken in Python

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