Ctrl+K

Application

Application#

Click here for a Jupyter Notebook template for this chapter’s application problems.

All the materials to reproduce your work (notebook and data files, API call, etc) should be included in the assignment Google Drive folder.

Question 1#

Q1A: Identify an aspect of your final project data (or another civic dataset) that you want to analyze. Answer to this question briefly describes the data you’re working with and what aspects of it you want to analyze.

Q1B: Develop an outline for your data analysis workflow. This could be a list with bullet points, a narrative, or a visual diagram (or a combination of these elements). Answer to this question includes notes on a desired final data structure and preliminary outputs.

  • NOTE: No code is required as part of this answer.

Q1C: Develop a Python program that uses plotly plotting functions to generate at least three different plot types using your Q1A dataset and Q1B workflows. Answer to this question includes code + comments.

  • I encourage folks to use this question to explore visualizations you might use for the final project.

Each plot should include the following elements:

  • Title

  • Axis labels

  • Legend

  • Scale or tickmarks

  • Hover label

  • Data source

Plot types to choose from:

  • Line plots

  • Bar chart

  • Grouped bar chart

  • Horizontal bar chart

  • Stacked bar chart

  • Histogram

  • Box plot

  • Area plot

  • Scatter plot

  • Pie chart

  • Donut chart

  • Sunburst chart

  • Table

Q1D: Add to the code for at least one of your Q1C figures to save the figure as a static image. Answer to this question includes code + comments. Include the image file output in the assignment Google Drive folder.

Q1E: Add to the code for at least one of your Q1C figures to save the figure as an .html file. Answer to this question includes code + comments. Include the output file in the assignment Google Drive folder.

Q1F: What challenges did you encounter? How did you approach solving them?

Question 2#

Q2A: Build on your Q1 work to develop an analysis outline or workflow for your final project data. Start by briefly describing the data you’re working with and what aspects of it you want to analyze. Answer to this question briefly describes what workflows you’re wanting to explore and how they’re a good fit for your dataset.

Types of charts:

Plotly resources:

Q2B: Develop an outline for this data analysis workflow. This could be a list with bullet points, a narrative, or a visual diagram (or a combination of these elements). Answer to this question includes notes on a desired final data structure and preliminary outputs.

Q2C: Develop a Python program that implements your Q2B outline. Answer to this question includes code + comments.

  • NOTE: You may not get to a full working programs for everything. That’s fine! Get as far as you can. Pseudocode can be helpful.

Q2D: What challenges did you encounter? How did you approach solving them?

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