防止 pandas read_csv 将第一行视为列名的 header

Prevent pandas read_csv treating first row as header of column names

我正在使用 pd.read_csvpandas DataFrame 中阅读。我想将第一行保留为数据,但它不断转换为列名。

(注意我的输入数据:我有一个字符串 (st = '\n'.join(lst)),我将其转换为 file-like object (io.StringIO(st)),然后构建 csv 来自那个文件 object.)

你想要 header=None False 类型提升到 int0 看到 docs 强调我的:

header : int or list of ints, default ‘infer’ Row number(s) to use as the column names, and the start of the data. Default behavior is as if set to 0 if no names passed, otherwise None. Explicitly pass header=0 to be able to replace existing names. The header can be a list of integers that specify row locations for a multi-index on the columns e.g. [0,1,3]. Intervening rows that are not specified will be skipped (e.g. 2 in this example is skipped). Note that this parameter ignores commented lines and empty lines if skip_blank_lines=True, so header=0 denotes the first line of data rather than the first line of the file.

您可以看到行为上的差异,首先是 header=0:

In [95]:
import io
import pandas as pd
t="""a,b,c
0,1,2
3,4,5"""
pd.read_csv(io.StringIO(t), header=0)

Out[95]:
   a  b  c
0  0  1  2
1  3  4  5

现在 None:

In [96]:
pd.read_csv(io.StringIO(t), header=None)

Out[96]:
   0  1  2
0  a  b  c
1  0  1  2
2  3  4  5

请注意,在最新版本 0.19.1 中,这将引发 TypeError:

In [98]:
pd.read_csv(io.StringIO(t), header=False)

TypeError: Passing a bool to header is invalid. Use header=None for no header or header=int or list-like of ints to specify the row(s) making up the column names

我想你需要参数 header=Noneread_csv:

样本:

import pandas as pd
from pandas.compat import StringIO

temp=u"""a,b
2,1
1,1"""

df = pd.read_csv(StringIO(temp),header=None)
print (df)
   0  1
0  a  b
1  2  1
2  1  1

如果您使用 pd.ExcelFile 阅读所有 excel 文件表,则:

df = pd.ExcelFile("path_to_file.xlsx")    
df.sheet_names                       # Provide the sheet names in the excel file

df = df.parse(2, header=None)        # Parsing the 2nd sheet in the file with header = None
df

输出:

   0  1  
0  a  b
1  1  1
2  0  1
3  5  2

您可以设置自定义列名以防止出现这种情况:

假设您的数据集中有两列,那么:

df = pd.read_csv(your_file_path, names = ['first column', 'second column'])

如果您有多个列,您还可以通过编程方式生成列名,并且可以在名称属性前面传递一个列表。