Data Explorer : Traveling the world on a mission to discover new data
Author: Ruturaj Kiran Vaidya
├── LICENSE
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
Project based on the cookiecutter data science project template. #cookiecutterdatascience
If you are only interested in looking at the notebook then go to (There are notebook rendering problems in github ecosystem, in particularly with plotly):
Also, all the values are estimates and from 2018 United States census and homelessness estimated data. All the graphs are plotted using plotly.
Jimmy Wrangler - Data Explorer is an introductory data science project. The objectives of this project are:
- Find public data sets
- Do exploratory data analysis by combining them
- Plot results
Homelessness count vs Total resident population - 2018, United States
I believe that the datasets we use for analysis must come from credible sources. Hence, for this project I used data from United States government. I used a couple of datasets - homelessness dataset and US census dataset.
Dataset source:
- Homelessness data: https://www.hudexchange.info/resources/documents/2007-2018-PIT-Counts-by-CoC.xlsx
- United States census estimate data - https://www2.census.gov/programs-surveys/popest/tables/2010-2018/state/totals/nst-est2018-01.xlsx
- Following plot shows an estimated percentage of homelessness in 2018 by state.
100 * Homeless Count / Total population
- Following plot shows an estimated count of homeless population in 2018 by state (per 10000 population). Note that the following graph is almost same as above, I though it would be better to plot realistic numbers (greater than 1).
10000 * Homeless Count / Total population
- Following geo-plot shows an estimated percentage of homelessness in 2018 by state.
MIT