transbigdata 0.2.4

A tool for transportation big data

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TransBigData

Main Functions

TransBigData is a Python package developed for transportation spatio-temporal big data processing and analysis. TransBigData provides fast and concise methods for processing common traffic spatio-temporal big data such as Taxi GPS data, bicycle sharing data and bus GPS data. It includes general methods such as rasterization, data quality analysis, data pre-processing, data set counting, trajectory analysis, GIS processing, map base map loading, coordinate and distance calculation, and data visualization.

Technical Features

• Provide a variety of processing methods for each stage of transportation spatio-temporal big data analysis.
• The code with TransBigData is clean, efficient, flexible, and easy to use, allowing complex data tasks to be achieved with concise code.

For more details please see the documentation

Installation

Before installing TransBigData, make sure that you have installed the available geopandas package: https://geopandas.org/index.html If you already have geopandas installed, run the following code directly from the command prompt to install it

pip install -U transbigdata

Usage

The following example shows how to use the TransBigData to extract Origin-Destination(OD) information of taxi trips from taxi GPS data:

import transbigdata as tbd
#Read the data    
import pandas as pd
data = pd.read_csv('TaxiData-Sample.csv',header = None) 
data.columns = ['VehicleNum','time','slon','slat','OpenStatus','Speed'] 
data

Use the tbd.taxigps_to_od method and pass in the corresponding column name to extract the trip OD:

#Extract OD information from GPS
oddata = tbd.taxigps_to_od(data,col = ['VehicleNum','time','slon','slat','OpenStatus'])
oddata

Aggregate OD into grids:

#Defining study area
bounds = [113.6,22.4,114.8,22.9]
#Input the bounds for the study area and generates the rasterization parameters
params = tbd.grid_params(bounds = bounds,accuracy = 1500)
#Rasterized OD and aggregate them into grids, this function will also generates a GeoDataFrame of the OD, which contains the counts of the aggregation.
od_gdf = tbd.odagg_grid(oddata,params)
od_gdf.plot(column = 'count')

Related Links

• Bilibili: https://space.bilibili.com/3051484
• Data analytics course for beginner https://www.lifangshuju.com/#/introduce/166
• Transportation Big Data analysis course： https://www.lifangshuju.com/#/introduce/154
• Data Visualization course： https://www.lifangshuju.com/#/introduce/165
• Github for this project： https://github.com/ni1o1/transbigdata/
• Bug report： https://github.com/ni1o1/transbigdata/issues

Citation

And if you want to reference this GitHub repository, you can use the following bibtex.

@misc{transbigdata,
  author = {Qing Yu},
  title = {TransBigData},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub Repository},
  howpublished = {\url{https://github.com/ni1o1/transbigdata}},
}