Data Collection & Storage
Learning Path ⋅ Skills: Data Science, Databases
Knowing how to collect and store data is an important part of any data scientist’s tool belt! You’ll go beyond toy data sets and learn how you can use Python to handle the data you can find in the real world.
Data Collection & Storage
Learning Path ⋅ 9 Resources
Reading and Writing CSV Files
This short course covers how to read and write data to CSV files using Python's built in "csv" module and the "pandas" library. You'll learn how to handle standard and non-standard data such as CSV files without headers, or files containing delimeters in the data.
Reading and Writing Files With Pandas
Learn about the Pandas IO tools API and how you can use it to read and write files. You'll use the Pandas read_csv() function to work with CSV files. You'll also cover similar methods for efficiently working with Excel, CSV, JSON, HTML, SQL, pickle, and big data files.
Editing Excel Spreadsheets in Python With openpyxl
Learn how to handle spreadsheets in Python using the openpyxl package. You'll learn how to manipulate Excel spreadsheets, extract information from spreadsheets, create simple or more complex spreadsheets, including adding styles, charts, and so on.
Introduction to Python SQL Libraries
Learn how to connect to different database management systems by using various Python SQL libraries. You'll interact with SQLite, MySQL, and PostgreSQL databases and perform common database queries using a Python application.
Data Management With Python, SQLite, and SQLAlchemy
Learn how to store and retrieve data using Python, SQLite, and SQLAlchemy as well as with flat files. Using SQLite with Python brings with it the additional benefit of accessing data with SQL. By adding SQLAlchemy, you can work with data in terms of objects and methods.
Python, Boto3, and AWS S3: Demystified
Get started working with Python, Boto3, and AWS S3. Learn how to create objects, upload them to S3, download their contents, and change their attributes directly from your script, all while avoiding common pitfalls.
Three Ways of Storing and Accessing Lots of Images in Python
In this tutorial, you'll cover three ways of storing and accessing lots of images in Python. You'll also see experimental evidence for the performance benefits and drawbacks of each one.
First Steps With PySpark and Big Data Processing
Take your first steps with Spark, PySpark, and Big Data processing concepts using intermediate Python concepts.
Data Version Control With Python and DVC
Learn to use DVC, a powerful tool that solves many problems encountered in machine learning and data science. You'll find out how data version control helps you to track your data, share development machines with your team, and create easily reproducible experiments!