Skip to main content

A package for analysing public transport data

Project description

Python module for the analysis of public busses in Warsaw, Poland

A Python module that analyzes publicly available data on public busses in Warsaw, Poland. The data is available at the Warsaw Public Transport Authority. The project's goals are to: (1) visualize where the busses exceed the speed of 50 km/h, (2) analyze the punctuality of the busses as well as evaluate in which districts do the busses tends to be late, and (3) analyze whether there is a correlation between busses exceeding the speed of 50 km/h and them speeding in the vicinity of theaters.

Installation

Documentation

collect_all_data(api_key, data_set_size: int = 60, spacing: int = 60) -> None - Collects all the data from the API (ie. the bus schedules, bus routes, bus stops, the positions of theaters in Warsaw and the current positions of the busses) and saves it in appropriate directories.

collect_bus_routes(api_key: str) -> None - Collects the bus routes and saves them in the "bus_routes" directory.

collect_bus_schedules(apikey: str) -> None - Collects the bus schedules and saves them in the "bus_data/bus_lines" directory.

fetch_bus_stops(apikey: str) -> None - Fetches the bus stops and saves them in the "bus_data/bus_stops" directory.

fetch_current_positions(api_key: str, iterations: int, spacing: int = 10) -> None - Fetches the current positions of the busses and saves them in the "data_sets" directory.

fetch_theaters(api_key: str) -> None - Fetches the positions of theaters in Warsaw and saves them in the "theaters_data" directory.

analyze_all(data_set: int, streets: bool = False) -> None - analyzes all the data collected and saves the plots in the "plots" directory. The streets parameter is used to determine whether to analyze the data in the context of streets as well as districts (by default only districts are analyzed).

calculate_total_lateness(data_set: int) -> None - transforms the data into a format that allows for the calculation of the total delays of the busses in Warsaw.

filter_data_set(data_set: int, streets: bool = False, radius: int = 700) -> None - filters the data set into a more friendly format for the analysis. If the streets parameter is set to True, the data is filtered to include the streets at which the busses sent out data by sending a request to the GUGiK API. The radius parameter is used to determine the radius around the positions in which to look for streets.

plot_theaters_map(data_set: int) -> None - plots the positions of the theaters in Warsaw and the positions of the busses that exceed the speed of 50 km/h.

plot_street_percentage(data_set: int, number: int = 10) -> None - plots the percentage of infractions that happened on the top {number} streets in a bar chart.

plot_district_percentage(data_set: int) -> None - plots the percentage of infractions that happened in each district in a bar chart.

plot_percentage_per_district(data_set: int) -> None - plots the percentage of infractions that happened in each district as a part of the total number of infractions in a pie chart.

plot_number_of_infractions(data_set: int) -> None - plots the number of infractions that happened in each district.

draw_map(data_set: int) -> None - draws a map of Warsaw with the speeding busses and alongside the percentage of infractions in each district. Red lines represent the places where the busses were speeding.

plot_lateness(data_set: int) -> None - Plots the number of minutes late for all of Warsaw and all of Warsaw's districts.

Usage

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bus_project_NJ-0.0.1.tar.gz (16.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

bus_project_NJ-0.0.1-py3-none-any.whl (40.5 kB view details)

Uploaded Python 3

File details

Details for the file bus_project_NJ-0.0.1.tar.gz.

File metadata

  • Download URL: bus_project_NJ-0.0.1.tar.gz
  • Upload date:
  • Size: 16.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 colorama/0.4.4 importlib-metadata/7.0.1 keyring/23.5.0 pkginfo/1.8.2 readme-renderer/34.0 requests-toolbelt/0.9.1 requests/2.25.1 rfc3986/1.5.0 tqdm/4.57.0 urllib3/1.26.5 CPython/3.10.12

File hashes

Hashes for bus_project_NJ-0.0.1.tar.gz
Algorithm Hash digest
SHA256 639617cd2aad68ffa6ae5ee1247db3286764c922c5b41acb47a9c7693c4fcee6
MD5 150df0d69ce374b793a4bd052eba1a06
BLAKE2b-256 01792a81ec6902f0161bca82df01b92a28243ee71f498f99a3e1628d89c4bb42

See more details on using hashes here.

File details

Details for the file bus_project_NJ-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: bus_project_NJ-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 40.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 colorama/0.4.4 importlib-metadata/7.0.1 keyring/23.5.0 pkginfo/1.8.2 readme-renderer/34.0 requests-toolbelt/0.9.1 requests/2.25.1 rfc3986/1.5.0 tqdm/4.57.0 urllib3/1.26.5 CPython/3.10.12

File hashes

Hashes for bus_project_NJ-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 cdc55b1e76a43a53a42591b8f1eea2a60db7bac203ac8ab39b0f7cec0c43ba2c
MD5 9fd9f1d9abd4b635d50e39981e1aaae3
BLAKE2b-256 5507b7abf75b721ef87a148c0114c07946483e47678a606e720dcf3663788fde

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page