Library Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with data in Python.
Prerequisites
Learners need to understand the concepts of files and directories (including the working directory) and how to start a Python interpreter before tackling this lesson.
To get started, follow the directions in the “Setup” tab to download data to your computer and follow any installation instructions.
| 00:00 | Python introduction | What is Python? |
| 00:00 | Starting With Data | How does Python deal with data tables? |
| 00:00 | Indexing, Slicing and Subsetting DataFrames in Python | How do we access different parts of a DataFrame? |
| 00:00 | Data Types and Formats | How do we explore and better understand the structure and format of our data. |
| 00:00 | Combining DataFrames with pandas | How do we combine data from multiple sources? |
| 00:00 | Data workflows and automation | How do we automate repetitive tasks? |
| 00:00 | Plotting Your Data - Matplotlib | How can you visualize your data? |
| 00:00 | Plotting Your Data - Pandas | How can you visualize your data? |
| 00:00 | Data Ingest & Visualization - Matplotlib & Pandas | How does it all tie in together? |
| 01:10 | Accessing SQLite Databases Using Python & Pandas | How to interact with SQL from Python? |
| 01:10 | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.