将列数超过预期的数据读取到数据帧中

最好是在上游修复文件,这样丢失的值就不会被 , . 但是如果有必要,您可以在python中通过替换 ,, 只是 , (逐行)。把你的坏文件当作 test.csv

import re
import csv

patt = re.compile(r",,")

with open('corrected.csv', 'w') as f2:
    with open('test.csv') as f:
        for line in csv.reader(map(lambda s: patt.sub(',', s), f)):
            f2.write(','.join(str(x) for x in line))
            f2.write('\n')
f2.close()
f.close()

输出: corrected.csv

09/07/2014,26268315,
10/07/2014,6601181,16.3857
11/07/2014,916651,12.5879
14/07/2014,213357,
15/07/2014,205019,10.8607

那么你应该可以毫无疑问地读入这个文件

import pandas as pd

df = pd.read_csv('corrected.csv', names=['DATE', 'PX', 'RAW'])

         DATE        PX      RAW
0  09/07/2014  26268315      NaN
1  10/07/2014   6601181  16.3857
2  11/07/2014    916651  12.5879
3  14/07/2014    213357      NaN
4  15/07/2014    205019  10.8607

昨天有这个问题。

pd.read_csv(adj_directory+'\\'+filename, 
            error_bad_lines=False,names=['DATE', 'PX', 'RAW'], 
            keep_default_na=False,
            na_values=[''])