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A tool for transportation big data

Project description

TransBigData 针对交通时空大数据处理的Python包

Build Status Documentation Status PyPI bilibili

TransBigData工具针对时空大数据处理而开发,依托于GeoPandas,集成了交通时空大数据处理过程中常用的方法。包括栅格化、预处理、集计、轨迹、近邻匹配、地图底图、坐标与距离等通用方法,以及出租车GPS、共享单车数据等各类数据处理方法。更多细节请查看:TransBigData的说明文档

安装

pip install -U transbigdata

使用

下面例子展示如何使用TransBigData工具快速地从出租车GPS数据中提取出行OD:

#导入TransBigData包
import transbigdata as tbd
#读取数据    
import pandas as pd
data = pd.read_csv('TaxiData-Sample.csv',header = None) 
data.columns = ['VehicleNum','time','slon','slat','OpenStatus','Speed'] 
data

使用transbigdata.taxigps_to_od方法,传入对应的列名,即可提取出行OD:

#从GPS数据提取OD
oddata = tbd.taxigps_to_od(data,col = ['VehicleNum','time','slon','slat','OpenStatus'])
oddata

对提取出的OD进行OD的栅格集计:

#定义研究范围
bounds = [113.6,22.4,114.8,22.9]
#输入研究范围边界bounds与栅格宽度accuracy,获取栅格化参数
params = tbd.grid_params(bounds = bounds,accuracy = 1500)
#栅格化OD并集计
od_gdf = tbd.odagg_grid(oddata,params)
od_gdf.plot(column = 'count')

相关链接

引用

而如果你想要引用这个 GitHub 仓库,可以使用如下的 bibtex:

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

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