this file is written in markdown
This is the project conducted by group10, based on dash.plotly, using real-world dataset to create a local interactive Web interface, at a total of 366 observations. More specifically, we focus on the analyze of "The Demand of Rental Bikes During year 2012 in Capital Bikeshare System" by visualizing as a preliminary research.
research object: with three qualitative variables:
*season*: season (1:winter, 2:spring, 3:summer, 4:fall)
*holiday*: weather day is holiday or not
*weathersit*:
1: Clear, Few clouds, Partly cloudy, Partly cloudy
2: Mist + Cloudy, Mist + Broken clouds, Mist + Few clouds, Mist
3: Light Snow, Light Rain + Thunderstorm + Scattered clouds, Light Rain + Scattered clouds
4: Heavy Rain + Ice Pallets + Thunderstorm + Mist, Snow + Fog
and quantitative variables selecting from:
*temp*: Normalized temperature in Celsius. The values are derived via (t-t_min)/(t_max-t_min), t_min=-8, t_max=+39 (only in hourly scale)
*atemp*: Normalized feeling temperature in Celsius. The values are derived via (t-t_min)/(t_max-t_min), t_min=-16, t_max=+50 (only in hourly scale)
*hum*: Normalized humidity. The values are divided to 100 (max)
*windspeed*: Normalized wind speed. The values are divided to 67 (max)
*cnt* (more in a dependent variable sense for mldm): count of total rental bikes including both casual and registered
.../app.py
dash>=2.6.1
dash-bootstrap-components>=1.1.0
dash-mantine-components>=0.10.1
dash-iconify>=0.1.2
numpy
pandas
dash-bootstrap-templates
Python 3.8.2,
dash==2.7.1, dash-bootstrap-components==1.2.1, dash-bootstrap-templates==1.0.7, dash-core-components==2.0.0, dash-html-components==2.0.0, dash-table==5.0.0,plotly==5.11.0, numpy==1.18.2, pandas==1.0.3
This app has structure as in the following:
- app.py
- pages
- #for visualization
|-- bar_charts.py
|-- box_whisker.py
|-- cluster_bar_charts.py
|-- histograms.py
|-- scatter_charts.py
- #for table
|-- dashboard.py
- #for setting
|-- __init__.py
|-- not_found_404.py
|-- default_fig.py
- home.py
- views
- #original dataset
|-- bike.xlsx
|-- data_content.txt
- #processed dataframes
- data.py
For more pages eg. more visualization, add in -pages
folder and modify -app.py
line 41. For updating data, check -views-bike.xisx
.
For modifying dataframe, check -views-data.py
. Overall the filename is very story-telling.
- with a light and dark theme switch component from the dash-bootstrap-templates library
- defalt_fig style
- selecting columns/ rows of the table with some reasonable restrictions (one qualitative and at most two quantitative, and can choose range of cnt)
- good robustness
- Source Code: github.com/Lecter314/dash.poltly-in-python (a private one, please contact author before browsing)
If you are having using/developing related issues, please let us know. We have a mailing list located at: [email protected]
The project is licensed under the BSD license.