[](https://colab.research.google.com/github/ncsu-libraries-data-vis/python-open-labs/blob/main/Open_Lab_4_exploratory_analysis_with_pandas/Open_Lab_4_exploratory_analysis_with_pandas.ipynb)

This series provides an introduction to core concepts for working with data in Python using the Pandas data analysis library and an opportunity to apply these concepts in an open, supported environment. In this lab we will cover common exploratory analysis methods such as calculating summary statistics and aggregating and grouping data using pandas. The format of each open lab consists of a guided activity covering specific concepts followed by extended open time for self-guided practice using datasets and activities provided by the instructors. During this open time participants will have access to instructors and peers for questions and support.

To create a copy of the workshop materials, and run the code, click the "Open in Colab" button above, while signed in to a Google account. With the Colab notebook open, click the "Copy to Drive" button to make a copy attached to your own Google account.

These materials were created by Claire Cahoon and Walt Gurley, adapted from previous workshop materials by Scott Bailey and Simon Wiles, of Stanford Libraries.