排序之后重置索引，从0开始

import pandas as pd
import numpy as np

# read train data
train = pd.read_csv("my.csv")
print(train.shape)  #(5, 300)
print(train)
print('_________')
train.drop(1,axis=0,inplace=True)
print(train.shape)
print(train)
print('_______')
train=train.reset_index(drop=True)   #重置索引，从0开始排
print(train)

print(train.loc[0])

运行结果如下：

D:\software\anaconda\install\python.exe D:/project/contest/program/my/test.py (5, 300) id label date f1 f2 \ 0 f10eb20f31cf7063ee8bdbd1272214e4d7e0193c8dbce4... 0 20171103 0 0 1 d861929b67938d06538b910b9f6b85f5eb62b6ad7361ba... 0 20170917 0 1 2 1270cb8a85eedd57672b2c6297fa5633e36773a2c3a351... 0 20171022 0 0 3 9fa009724ee7ff9d688ae321304fbc78f608cdabbfdd2b... 0 20171029 0 0 4 1da482485d7e8bcefae7e9d0d1167cec3ac111cfa71d8b... 0 20171002 1 1 f3 f4 f5 f6 f7 ... f288 f289 f290 f291 f292 f293 \ 0 0 0 100807 0 5 ... 301.0 312.0 328.0 85.0 302.0 201.0 1 1 1 100805 1 5 ... 302.0 324.0 391.0 13.0 302.0 160.0 2 1 0 100102 0 6 ... NaN NaN NaN NaN NaN NaN 3 0 1 100807 1 4 ... 302.0 322.0 341.0 57.0 251.0 175.0 4 0 1 100805 1 5 ... 302.0 301.0 301.0 74.0 302.0 182.0 f294 f295 f296 f297 0 203.0 203.0 61.0 201.0 1 160.0 161.0 8.0 160.0 2 NaN NaN NaN NaN 3 176.0 176.0 49.0 150.0 4 181.0 182.0 51.0 181.0 [5 rows x 300 columns] _________ (4, 300) id label date f1 f2 \ 0 f10eb20f31cf7063ee8bdbd1272214e4d7e0193c8dbce4... 0 20171103 0 0 2 1270cb8a85eedd57672b2c6297fa5633e36773a2c3a351... 0 20171022 0 0 3 9fa009724ee7ff9d688ae321304fbc78f608cdabbfdd2b... 0 20171029 0 0 4 1da482485d7e8bcefae7e9d0d1167cec3ac111cfa71d8b... 0 20171002 1 1 f3 f4 f5 f6 f7 ... f288 f289 f290 f291 f292 f293 \ 0 0 0 100807 0 5 ... 301.0 312.0 328.0 85.0 302.0 201.0 2 1 0 100102 0 6 ... NaN NaN NaN NaN NaN NaN 3 0 1 100807 1 4 ... 302.0 322.0 341.0 57.0 251.0 175.0 4 0 1 100805 1 5 ... 302.0 301.0 301.0 74.0 302.0 182.0 f294 f295 f296 f297 0 203.0 203.0 61.0 201.0 2 NaN NaN NaN NaN 3 176.0 176.0 49.0 150.0 4 181.0 182.0 51.0 181.0 [4 rows x 300 columns] _______ id label date f1 f2 \ 0 f10eb20f31cf7063ee8bdbd1272214e4d7e0193c8dbce4... 0 20171103 0 0 1 1270cb8a85eedd57672b2c6297fa5633e36773a2c3a351... 0 20171022 0 0 2 9fa009724ee7ff9d688ae321304fbc78f608cdabbfdd2b... 0 20171029 0 0 3 1da482485d7e8bcefae7e9d0d1167cec3ac111cfa71d8b... 0 20171002 1 1 f3 f4 f5 f6 f7 ... f288 f289 f290 f291 f292 f293 \ 0 0 0 100807 0 5 ... 301.0 312.0 328.0 85.0 302.0 201.0 1 1 0 100102 0 6 ... NaN NaN NaN NaN NaN NaN 2 0 1 100807 1 4 ... 302.0 322.0 341.0 57.0 251.0 175.0 3 0 1 100805 1 5 ... 302.0 301.0 301.0 74.0 302.0 182.0 f294 f295 f296 f297 0 203.0 203.0 61.0 201.0 1 NaN NaN NaN NaN 2 176.0 176.0 49.0 150.0 3 181.0 182.0 51.0 181.0 [4 rows x 300 columns] id f10eb20f31cf7063ee8bdbd1272214e4d7e0193c8dbce4... label 0 date 20171103 f1 0 f2 0 f3 0 f4 0 f5 100807 f6 0 f7 5 f8 1 f9 1 f10 1 f11 1 f12 2 f13 0 f14 2 f15 0 f16 2 f17 2 f18 2 f19 1 f20 31 f21 61 f22 142 f23 245 f24 0 f25 1 f26 0 f27 1 ... f268 1 f269 1 f270 2 f271 2 f272 2 f273 2 f274 1 f275 1 f276 1 f277 1 f278 27 f279 297 f280 302 f281 384 f282 770 f283 20 f284 99 f285 102 f286 124 f287 140 f288 301 f289 312 f290 328 f291 85 f292 302 f293 201 f294 203 f295 203 f296 61 f297 201 Name: 0, dtype: object

排序之后重置索引，从0开始

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