pandas 使用 Panda read_csv 列出超出范围的索引
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/37964504/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
List index out of range with Panda read_csv
提问by Nero Ouali
I'm trying to read large data (thousands of rows) through a python script from csv files which look like this:
我正在尝试通过 python 脚本从 csv 文件读取大数据（数千行），如下所示：
.....
2015-11-03 20:16:28,000;63,62;
2015-11-03 20:16:29,000;63,75;
2015-11-03 20:16:30,000;63,86;
2015-11-03 20:16:31,000;64,25;
but it appears that one of the files has extra empty rows that have 196541465 blank spaces — then the code crashes when reading it with read_csv of pandas lib.
但似乎其中一个文件有额外的空行，其中有 196541465 个空格 - 然后在使用 pandas lib 的 read_csv 读取它时代码崩溃。
File "/usr/lib/python2.7/dist-packages/pandas/core/frame.py", line 4221, in append
elif isinstance(other, list) and not isinstance(other[0], DataFrame):
IndexError: list index out of range
I'm using the folowing command:
我正在使用以下命令：
data = pd.read_csv(input_file,skiprows = [0],usecols=[0,1,2],delimiter=';',decimal=',', names = [ 'date','angle','Unnamed'],na_filter = False,parse_dates = [0],date_parser = reformat_date,error_bad_lines = False,skip_blank_lines=True)#,nrows = 8191)
the culprit row is the 8192'th, when limiting rows (by rows = 8191) it works just fine. I've tried many options from the doc but it doesn't seem to work! Any idea?
罪魁祸首是第 8192 行，当限制行（by rows = 8191）时，它工作得很好。我已经尝试了文档中的许多选项，但似乎不起作用！任何的想法？
回答by rogueleaderr
I got this error because I was trying to read a CSV file that had too few headers vs. the number of columns (e.g. 10 columns, but only 8 headers. If you set index_col=False, pandas doesn't know what to do with the extra columns)
我收到这个错误是因为我试图读取一个标题与列数相比太少的 CSV 文件（例如 10 列，但只有 8 个标题。如果你设置了index_col=False，pandas 不知道如何处理额外的列） )
回答by Marcus H?gen? Bohman
Edited according to Mitjas comment below.
根据下面的 Mitjas 评论进行编辑。
I just had the same issue and index_col = Falsedidn't work. I had 19 columns and only 17 headers. Solved it with reading columns and headers separately and then adding the header names.
我只是遇到了同样的问题，index_col = False但没有奏效。我有 19 列，只有 17 个标题。通过分别读取列和标题然后添加标题名称来解决它。
dfcolumns = pd.read_csv('file.csv',
nrows = 1)
df = pd.read_csv('file.csv',
header = None,
skiprows = 1,
usecols = list(range(len(dfcolumns.columns))),
names = dfcolumns.columns)
