python - 如何使用 Pandas 从 Excel 中读取某些列 - Python

Question

我正在阅读 Excel 工作表，并且我想阅读某些列:第 0 列，因为它是行索引，第 22:37 列。现在这就是我要做的:

import pandas as pd
import numpy as np
file_loc = "path.xlsx"
df = pd.read_excel(file_loc, index_col=None, na_values=['NA'], parse_cols = 37)
df= pd.concat([df[df.columns[0]], df[df.columns[22:]]], axis=1)

但我希望有更好的方法来做到这一点!我知道如果我这样做 parse_cols=[0, 22,..,37] 我可以做到，但对于大型数据集，这没有意义。

我也这样做了:

s = pd.Series(0)
s[1]=22
for i in range(2,14):
    s[i]=s[i-1]+1
df = pd.read_excel(file_loc, index_col=None, na_values=['NA'], parse_cols = s)

但它会读取前 15 列，即 s 的长度。

Answer 1

您可以像这样使用列索引(字母):

import pandas as pd
import numpy as np
file_loc = "path.xlsx"
df = pd.read_excel(file_loc, index_col=None, na_values=['NA'], usecols="A,C:AA")
print(df)

Corresponding documentation :

usecols : int, str, list-like, or callable default None

• If None, then parse all columns.

• If str, then indicates comma separated list of Excel column letters and column ranges (e.g. “A:E” or “A,C,E:F”). Ranges are inclusive of both sides.

• If list of int, then indicates list of column numbers to be parsed.

• If list of string, then indicates list of column names to be parsed.

  New in version 0.24.0.

• If callable, then evaluate each column name against it and parse the column if the callable returns True.

Returns a subset of the columns according to behavior above.

New in version 0.24.0.