NGSIM数据集Python处理（按照路段和车型筛选数据）

关于NGSIM数据集的介绍不再赘述，详见他人文章：(29条消息) NGSIM数据集相关解释_29世纪杀马特的博客-CSDN博客_ngsim数据集

本文章主要通过Python完成NGSIM数据集按路段和车型的筛选，话不多说，直接上代码：

import pandas as pd
from pathlib import Path
datas = pd.read_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data.csv')

def main():
    choice = int(input('请输入需要提取数据的路段(1.i-80;2.us-101;3.larkershim;4.peachtree)：'))
    if choice==1:
        i_80()
    if choice==2:
        us_101()
    if choice==3:
        larkershim()
    if choice==4:
        peachtree()

def i_80():
    """获取i-80道路上的数据"""
    datas_i_80=datas[datas.Location=='i-80']
    """"按车辆类型进行数据读取"""
    answer=int(input('请输出需要提取的车辆类型数据（1.摩托车；2.小型车；3.大型车):'))
    if answer==1:
        datas_i_80_m=datas_i_80[datas_i_80.v_Class==1]
        datas_i_80_m.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\I-80\\摩托车数据.csv')
        print('i-80路段，摩托车数据已导出完毕')
    if answer==2:
        datas_i_80_c = datas_i_80[datas_i_80.v_Class == 2]
        datas_i_80_c.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\I-80\\小型车数据.csv')
        if datas_i_80_c.shape[0]>1048765:
            split_i_80_c()
        print('i-80路段，小型车数据已导出完毕')
    if answer==3:
        datas_i_80_t = datas_i_80[datas_i_80.v_Class == 3]
        datas_i_80_t.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\I-80\\大型车数据.csv')
        print('i-80路段，大型车数据已导出完毕')
    quertion()

def us_101():
    datas_us_101 = datas[datas.Location == 'us-101']
    answer = int(input('请输出需要提取的车辆类型数据（1.摩托车；2.小型车；3.大型车):'))
    if answer == 1:
        datas_us_101_m = datas_us_101[datas_us_101.v_Class == 1]
        datas_us_101_m.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\US-101\\摩托车数据.csv')
        print('us-101路段，摩托车数据已导出完毕')
    if answer == 2:
        datas_us_101_c = datas_us_101[datas_us_101.v_Class == 2]
        datas_us_101_c.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\US-101\\小型车数据.csv')
        if datas_us_101_c.shape[0]>1048765:
            split_us_101_c()
        print('us-101路段，小型车数据已导出完毕')
    if answer == 3:
        datas_us_101_t = datas_us_101[datas_us_101.v_Class == 3]
        datas_us_101_t.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\US-101\\大型车数据.csv')
        print('us-101路段，大型车数据已导出完毕')
    quertion()

def larkershim():
    datas_lankershim = datas[datas.Location == 'lankershim']
    answer = int(input('请输出需要提取的车辆类型数据（1.摩托车；2.小型车；3.大型车):'))
    if answer == 1:
        datas_lankershim_m = datas_lankershim[datas_lankershim.v_Class == 1]
        datas_lankershim_m.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\lankershim\\摩托车数据.csv')
        print('lankershim路段，摩托车数据已导出完毕')
    if answer == 2:
        datas_lankershim_c = datas_lankershim[datas_lankershim.v_Class == 2]
        datas_lankershim_c.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\lankershim\\小型车数据.csv')
        if datas_lankershim_c.shape[0]>1048765:
            split_lankershim_c()
        print('lankershim路段，小型车数据已导出完毕')
    if answer == 3:
        datas_lankershim_t = datas_lankershim[datas_lankershim.v_Class == 3]
        datas_lankershim_t.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\lankershim\\大型车数据.csv')
        print('lankershim路段，大型车数据已导出完毕')
    quertion()

def peachtree():
    datas_peachtree = datas[datas.Location == 'peachtree']
    answer = int(input('请输出需要提取的车辆类型数据（1.摩托车；2.小型车；3.大型车):'))
    if answer == 1:
        datas_peachtree_m = datas_peachtree[datas_peachtree.v_Class == 1]
        datas_peachtree_m.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\peachtree\\摩托车数据.csv')
        print('peachtree路段，摩托车数据已导出完毕')
    if answer == 2:
        datas_peachtree_c = datas_peachtree[datas_peachtree.v_Class == 2]
        datas_peachtree_c.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\peachtree\\小型车数据.csv')
        if datas_peachtree_c.shape[0]>1048765:
            split_peachtree_c()
        print('peachtree路段，小型车数据已导出完毕')
    if answer == 3:
        datas_lankershim_t = datas_peachtree[datas_peachtree.v_Class == 3]
        datas_lankershim_t.to_csv('D:\\BaiduNetdiskDownload\\NGSIM_Data\\peachtree\\大型车数据.csv')
        print('peachtree路段，大型车数据已导出完毕')
    quertion()

def split_lankershim_c():
    res_file_path = Path(r'D:\\BaiduNetdiskDownload\\NGSIM_Data\\lankershim\\小型车数据.csv')  # 仅修改待分割文件路径即可
    split_size = 1000000
    tar_dir = res_file_path.parent / ("split_" + res_file_path.name.split(".")[0])
    if not tar_dir.exists():
        tar_dir.mkdir()
        print("创建文件夹\t" + str(tar_dir))
    print("目标路径：\t" + str(tar_dir))
    print("分割文件：\t" + str(res_file_path))
    print("分割大小：\t" + "{:,}".format(split_size))
    tmp = pd.read_csv(res_file_path, nrows=10)
    columns = tmp.columns.to_list()
    idx = 0
    while (len(tmp) > 0):
        start = 1 + (idx * split_size)
        tmp = pd.read_csv(res_file_path,
                          header=None,
                          names=columns,
                          skiprows=start,
                          nrows=split_size)
        if len(tmp) <= 0:
            break
        file_name = res_file_path.name.split(".")[0] + "_{}_{}".format(start, start + len(tmp)) + ".csv"
        file_path = tar_dir / file_name
        tmp.to_csv(file_path, index=False)
        idx += 1
        print(file_name + "\t切割成功")

def split_i_80_c():
    res_file_path = Path(r'D:\\BaiduNetdiskDownload\\NGSIM_Data\\I-80\\小型车数据.csv')  # 仅修改待分割文件路径即可
    split_size = 1000000
    tar_dir = res_file_path.parent / ("split_" + res_file_path.name.split(".")[0])
    if not tar_dir.exists():
        tar_dir.mkdir()
        print("创建文件夹\t" + str(tar_dir))
    print("目标路径：\t" + str(tar_dir))
    print("分割文件：\t" + str(res_file_path))
    print("分割大小：\t" + "{:,}".format(split_size))
    tmp = pd.read_csv(res_file_path, nrows=10)
    columns = tmp.columns.to_list()
    idx = 0
    while (len(tmp) > 0):
        start = 1 + (idx * split_size)
        tmp = pd.read_csv(res_file_path,
                          header=None,
                          names=columns,
                          skiprows=start,
                          nrows=split_size)
        if len(tmp) <= 0:
            break
        file_name = res_file_path.name.split(".")[0] + "_{}_{}".format(start, start + len(tmp)) + ".csv"
        file_path = tar_dir / file_name
        tmp.to_csv(file_path, index=False)
        idx += 1
        print(file_name + "\t切割成功")

def split_peachtree_c():
    res_file_path = Path(r'D:\\BaiduNetdiskDownload\\NGSIM_Data\\peachtree\\小型车数据.csv')  # 仅修改待分割文件路径即可
    split_size = 1000000
    tar_dir = res_file_path.parent / ("split_" + res_file_path.name.split(".")[0])
    if not tar_dir.exists():
        tar_dir.mkdir()
        print("创建文件夹\t" + str(tar_dir))
    print("目标路径：\t" + str(tar_dir))
    print("分割文件：\t" + str(res_file_path))
    print("分割大小：\t" + "{:,}".format(split_size))
    tmp = pd.read_csv(res_file_path, nrows=10)
    columns = tmp.columns.to_list()
    idx = 0
    while (len(tmp) > 0):
        start = 1 + (idx * split_size)
        tmp = pd.read_csv(res_file_path,
                          header=None,
                          names=columns,
                          skiprows=start,
                          nrows=split_size)
        if len(tmp) <= 0:
            break
        file_name = res_file_path.name.split(".")[0] + "_{}_{}".format(start, start + len(tmp)) + ".csv"
        file_path = tar_dir / file_name
        tmp.to_csv(file_path, index=False)
        idx += 1
        print(file_name + "\t切割成功")

def split_us_101_c():
    res_file_path = Path(r'D:\\BaiduNetdiskDownload\\NGSIM_Data\\US-101\\小型车数据.csv')  # 仅修改待分割文件路径即可
    split_size = 1000000
    tar_dir = res_file_path.parent / ("split_" + res_file_path.name.split(".")[0])
    if not tar_dir.exists():
        tar_dir.mkdir()
        print("创建文件夹\t" + str(tar_dir))
    print("目标路径：\t" + str(tar_dir))
    print("分割文件：\t" + str(res_file_path))
    print("分割大小：\t" + "{:,}".format(split_size))
    tmp = pd.read_csv(res_file_path, nrows=10)
    columns = tmp.columns.to_list()
    idx = 0
    while (len(tmp) > 0):
        start = 1 + (idx * split_size)
        tmp = pd.read_csv(res_file_path,
                          header=None,
                          names=columns,
                          skiprows=start,
                          nrows=split_size)
        if len(tmp) <= 0:
            break
        file_name = res_file_path.name.split(".")[0] + "_{}_{}".format(start, start + len(tmp)) + ".csv"
        file_path = tar_dir / file_name
        tmp.to_csv(file_path, index=False)
        idx += 1
        print(file_name + "\t切割成功")

def quertion():
        question=int(input('是否继续导出数据？(1.是；2.否）：'))
        if question==1:
            main()
        if question==2:
            print('程序关闭')


if __name__ == '__main__':
    main()

Excel中仅能显示1048765行数据，split_lankershim_c()，split_i_80_c()，split_peachtree_c()，split_us_101_c()四个函数对数据进行切割，以便于将最后筛选的数据在Excel中进行显示。

若有疑问或有交通数据处理需求欢迎VX探讨：A2528945820