从 python 中的 URL 读取 xls 文件

Question

I'm trying to read data from the link below in python https://drive.google.com/file/d/16cp23cJxeyUfnBHMp-sNCuFNQxe8cqOV/view

I've tried this:

import pandas as pd

path = pd.read_excel('https://drive.google.com/file/d/16cp23cJxeyUfnBHMp-sNCuFNQxe8cqOV/view')

That returned this error:

XLRDError: Unsupported format, or corrupt file: Expected BOF record; found b'<!DOCTYP'

Then I tried using cvs format

path = pd.read_csv('https://drive.google.com/file/d/16cp23cJxeyUfnBHMp-sNCuFNQxe8cqOV/view')

Returned this

ParserError: Error tokenizing data. C error: Expected 298 fields in line 133, saw 440

finnaly I tried this:

path = pd.read_csv("https://drive.google.com/file/d/16cp23cJxeyUfnBHMp-sNCuFNQxe8cqOV/view")

This read data but that is not what I expected after seen the link (283 rows, 7 columns). Photo below.

Error reading data

Any ideas of how could I read the data?

Thanks

Answer 1

Use this example to download the excel from Google Drive (the fileid is the ID after the /d/ part in your URL):

fileid = "16cp23cJxeyUfnBHMp-sNCuFNQxe8cqOV"

df = pd.read_excel(
    "https://drive.google.com/uc?export=download&id={fileid}".format(
        fileid=fileid
    ),
    skiprows=17,
)
print(df)

Prints:

     Unnamed: 0                                         Unnamed: 1                                         Unnamed: 2 Petajoules Gigajoules           %
0           NaN                                        Afghanistan                                        Afghanistan        321         10   78.669280
1           NaN                                            Albania                                            Albania        102         35  100.000000
2           NaN                                            Algeria                                            Algeria       1959         51    0.551010
3           NaN                                     American Samoa                                     American Samoa        ...        ...    0.641026
4           NaN                                            Andorra                                            Andorra          9        121   88.695650
5           NaN                                             Angola                                             Angola        642         27   70.909090

...and so on.