AnExLearningSummit2023

Materials for AnExLearningSummit2023

Plotly 101: Building Interactive plots in Python

Polina Tikhonova, Graduate Research Assistant, The Pennsylvania State University

Link to the .ipynb with a rendered plotly graphs.

Agenda

Goal

The main goal of this workshop is to learn, how we can use plotly library, to construct various types of plots and perform initial descriptive analysis.

Datasets

Department of Buildings (DoB) complaints dataset. The main dataset we use for the analysis, stored at the NYC Open Data Database (link). NYC Zip Codes. A dataset with geographical coordinates of zip code area boundaries, used for the complaints mapping, stored at the NYC Open Data Database (link)

Plotly examples covered in this workshop:

• Maps
• Interactive plots
• Bar plots
• Line plots
• Scatter (marker) plots
• Boxplots

Plots modifications and saving:

• Save in .html format
• Save in .jpg/png format
• Combining different types of plots
• Modifying plots hover descriptions
• Changing colors/line types and other visual parameters

Libraries, requiered by this notebook:

pip install pandas os urllib json plotly datetime itertools sodapy sklearn geopandas requests zipfile io kaleido