# Module 5.2: Answering Data Driven Questions Computationally

## Introduction

In this module we will show some examples of *using* open civic data to answer a data driven question. This module will dive into several open civic datasets and use the Python programming language to manipulate and merge these datasets to gain new insights from the information they contain.

This module will also demonstrate how to download and manipulate open civic data using the Python programming language.

#### Guiding Questions

* How can we use data and computation to learn about our communities?
* How can we join datasets together to gain new insights?
* What tools exist to engage and explore our data computationally?

#### Vignette

The librarian would like to investigate the usage of Public-wifi at various branches in their library system. Specifically, what neighborhood uses the most wifi? They use the Python programming language and Jupyter Notebooks to perform calculations and generate data visualizations. The librarian visits a local data portal, downloads the datasets of interested, and then write Python code to manipulate the data, join multiple datasets together, and produce a data visualization and answer a data driven question.

## Instructional Materials

### Computational Notebook

The instructional materials for this module have been written in the form of a Jupyter Notebook. The notebook is accessible in two different ways. There is a read-only mode and there is an interactive mode.

* [Click here to launch the INTERACTIVE instructional materials](https://mybinder.org/v2/gh/mcburton/civic-data-deep-dive/HEAD?labpath=Using%20Civic%20Data.ipynb)

{% file src="/files/rXsiXkpRi0XUaj8JLiJ5" %}
Module 5.2 Instructional Materials PDF
{% endfile %}

### Video

{% embed url="<https://files.gitbook.com/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FiHhyQLuCq600FlDt9jWx%2Fuploads%2F3oaHpFcSOnjiNejELUQ0%2FModule5.2_Instructions.mp4?alt=media&token=25a41086-e64a-4ecc-a435-42460471b6f9>" %}
Module 5.2 Answering Data Driven Questions Computationally Instructional Video
{% endembed %}

#### Video Files

{% file src="/files/1467nCM2dU1iHDN62Q6M" %}
Module 5.2 Instructions Video
{% endfile %}

## Activity

**Overview:**

After answering the computational questions in the instructional materials above. Open the activity notebook and work with the data.

**Supplies:** An Internet-connected device and web-browser.

**Time:** 20 mins.

**Activity:**

Open the computational notebook at the link below and follow the instructions in the notebook.

* [Click here to launch the INTERACTIVE activities ](https://mybinder.org/v2/gh/mcburton/civic-data-deep-dive/HEAD?labpath=Activities.ipynb)

{% file src="/files/eWZCtptBhZSRLA6oNPbj" %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://civic-switchboard.gitbook.io/education-series/segment-5-using-civic-data/module-5.2-answering-data-driven-questions-computationally.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.