Importing Data: Python Data Playbook

In order to work with data in Python, you need to know how to get data into Python. This playbook defines data import recipes for common data import problems you’ll encounter using Python.
Course info
Level
Beginner
Updated
Nov 17, 2018
Duration
1h 36m
Table of contents
Description
Course info
Level
Beginner
Updated
Nov 17, 2018
Duration
1h 36m
Description

Python is one of the most powerful and widely used languages to work with data. In this course, Importing Data: Python Data Playbook, you will learn foundational knowledge and gain the ability to import data from multiple different file formats, including: text, tabular data, binary formats as well as from databases. First, you will learn how to import text and CSV files. Next, you will discover how to import data from JSON, XML, SAS, Stata, HDF5, Matlab, Pickle files, and more. Finally, you will explore how to import relational data from databases, including: SQLite, MySQL, and PostgreSQL. When you're finished with this course, you will have the skills and knowledge of importing data into Python needed to analyze, visualize, and in general work with data.

About the author
About the author

Xavier is very passionate about teaching, helping others understand search and Big Data. He is also an entrepreneur, project manager, technical author, trainer, and holds a few certifications with Cloudera, Microsoft, and the Scrum Alliance, along with being a Microsoft MVP.

More from the author
Programming Python Using an IDE
Intermediate
2h 0m
Jun 26, 2019
More courses by Xavier Morera
Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
(Music playing) Hi everyone, my name is Xavier Morera, and welcome to my course Importing Data: Python Data Playbook. I am very passionate about working with data, and you know which is one of the most powerful and widely used languages to work with data? If you said Python, you are right. In this course, we're going to learn how to import data from multiple different formats with Python. We will learn which are the libraries used for this purpose, CSV, Pandas, NumPy, ElementTree, JSON, and more. Some of the formats we will work with include text, CSV, JSON, XML, Excel, SAS, HDF5, Stata, Pickle files, as well as other file formats. But we will also cover how to import data from different relational databases, including SQLite, MySQL, and PostgreSQL using Python's SQL toolkit, SQLAlchemy. By the end of this course, you will be able to quickly and easily import data stored in different formats in Python, but before beginning the course, you should be familiar with the basic mechanics of Python, including how to use the REPL and how to import libraries. This course is not a deep dive on Python. Instead, it complements your existing Python knowledge to help you get the data you need for your work, so if you need to import data, get your environment up and running, have your packages ready, and come join me on this journey to learn how to load data with the Importing Data Python Data Playbook at Pluralsight.