Reading Data with Python and Pandas

Reading Data with Python and Pandas

Learn how to import data from the most common formats and external sources, such as SQL, Excel files, JSON, CSVs, and APIs.

6 hours

11 assignments

7 videos



Every data science project begins with importing data. In this course, you’ll learn the basics and beyond, starting with how data is imported using Python and Pandas. From there, you’ll focus on reading external data into Pandas data structures, using different methods. You’ll also be able to deal with data that contains wrong delimiters, encoding, or quote charts. We’ll cover all the steps, options, and issues you need to be aware of to successfully handle the data you’re working with.

"While it’s essential to know how to import data from all the most important sources, it’s also critical to understand the common pitfalls associated with them. My goal is to help you streamline your process, regardless of where your data comes from and what difficulties may arise."

Instructor Santiago Basulto

Santiago Basulto

Course Instructor


Basic file types

Relational Database connections

Advanced file types

Final Project


Health and Obesity trends


Reading CSV and TXT files

Reading CSV and TXT Exercises

Reading Excel files

Reading Excel Exercises

Reading JSON files

Reading JSON Exercises


Fetching data from a REST API

Fetching data from a REST API Exercises

Reading HTML tables

Reading HTML tables Exercises

Complementary file types and IO tools


Reading data from relational databases

Reading data from relational databases Exercises 1

Reading data from relational databases Exercises 2

Simple pricing

Gain access to RMOTR’s entire course library


per month

15% OFF!


per year

  • Full access to all videos & courses.
  • 200+ programming assignments.
  • 20+ Github Projects to add to your portfolio.
  • Access to exclusive community.
  • Exclusive access to members-only webinars and workshops.
Learn more

Course final project

Getting Health and Obesity trends

In this project we’ll get different food composition datasets and use them to analyze nutritional facts. Also, we’ll use Wikipedia information to analyze obesity trends on each state of the USA.

Learn more

What Our Students
Have to Say

The most trusted Data Science academy online.
1000+ students have trusted us with their Data Science careers.

Willian Ponton
William Ponton

The perfect combination of building real-world skills through challenging coursework and projects.

Aiya Akatayeva

I have tried multiple ways to learn Data Science. Now, with the lessons and practice provided here, I finally feel like I am making real progress.

Chris Mccluskey
Chris McCluskey

Clear guidance while providing detailed explanations. Greatly enhanced my knowledge in a short amount of time!

Course instructor

Santiago Basulto

Data Scientist at RMOTR

Santiago is an experienced Data Scientist and Python programmer with more than 10 years of experience in the field. He started as a Java developer working as a consultant on high performance and critical systems before moving to Python. In 2012 was hired as the CTO of, a startup analyzing data from runners. He then fell in love with Data processing with Python and in 2015 founded RMOTR, to provide expert-level Data Science training.