Seems to work for me without the StringIO:

test = pd.read_csv('https://docs.google.com/spreadsheets/d/' + 
                   '0Ak1ecr7i0wotdGJmTURJRnZLYlV3M2daNTRubTdwTXc' +
                   '/export?gid=0&format=csv',
                   # Set first column as rownames in data frame
                   index_col=0,
                   # Parse column values to datetime
                   parse_dates=['Quradate']
                  )
test.head(5)  # Same result as @TomAugspurger

BTW, including the ?gid= enables importing different sheets, find the gid in the URL.

My approach is a bit different. I just used pandas.Dataframe() but obviously needed to install and import gspread. And it worked fine!

gsheet = gs.open("Name")
Sheet_name ="today"
wsheet = gsheet.worksheet(Sheet_name)
dataframe = pd.DataFrame(wsheet.get_all_records())

I have been using the following utils and it worked so far:

def load_from_gspreadsheet(sheet_name, key):
    url = 'https://docs.google.com/spreadsheets/d/{key}/gviz/tq?tqx=out:csv&sheet={sheet_name}&headers=1'.format(
        key=key, sheet_name=sheet_name.replace(' ', '%20'))

    log.info('Loading google spreadsheet from {}'.format(url))

    df = pd.read_csv(url)
    return df.drop([col for col in df.columns if col.startswith('Unnamed')], axis=1)

You must specify the sheet_name and the key. The key is the string you get from the url in the following path: https://docs.google.com/spreadsheets/d/{key}/edit/.

You can change the value of headers if you have more than one row for the column names but I am not sure if it still work with multi-headers.

It may brake if Google will change their APIs.

Also please bear in mind that your spreadsheet must be public, everyone with the link can read it.

If the csv file was shared via drive and not via spreadsheet then the below change to the url would work

#Derive the id from the google drive shareable link.
#For the file at hand the link is as below
#<https://drive.google.com/open?id=1-tjNjMP6w0RUV4GhJWw08ql3wYwsNU69>
file_id='1-tjNjMP6w0RUV4GhJWw08ql3wYwsNU69'
link='https://drive.google.com/uc?export=download&id={FILE_ID}'
csv_url=link.format(FILE_ID=file_id)
#The final url would be as below:-
#csv_url='https://drive.google.com/uc?export=download&id=1-tjNjMP6w0RUV4GhJWw08ql3wYwsNU69'
df = pd.read_csv(csv_url)

And the dataframe would be (if you just ran the above code)

    a   b   c   d
0   0   1   2   3
1   4   5   6   7
2   8   9   10  11
3   12  13  14  15

See working code here.

Open the specific sheet you want in your browser. Make sure it’s at least viewable by anyone with the link. Copy and paste the URL. You’ll get something like https://docs.google.com/spreadsheets/d/BLAHBLAHBLAH/edit#gid=NUMBER.

sheet_url = 'https://docs.google.com/spreadsheets/d/BLAHBLAHBLAH/edit#gid=NUMBER'

First we turn that into a CSV export URL, like https://docs.google.com/spreadsheets/d/BLAHBLAHBLAH/export?format=csv&gid=NUMBER:

csv_export_url = sheet_url.replace('/edit#gid=', '/export?format=csv&gid=')

Then we pass it to pd.read_csv, which can take a URL.

df = pd.read_csv(csv_export_url)

This will break if Google changes its API (it seems undocumented), and may give unhelpful errors if a network failure occurs.

This works for me.

import pandas as pd

#Create a public URL
#https://docs.google.com/spreadsheets/d/0Ak1ecr7i0wotdGJmTURJRnZLYlV3M2daNTRubTdwTXc/edit?usp=sharing

#get spreadsheets key from url
gsheetkey = "0Ak1ecr7i0wotdGJmTURJRnZLYlV3M2daNTRubTdwTXc"

#sheet name
sheet_name = 'Sheet 1'

url=f'https://docs.google.com/spreadsheet/ccc?key={gsheetkey}&output=xlsx'
df = pd.read_excel(url,sheet_name=sheet_name)
print(df)

In Google Sheets file go to File > Publish to the web > Select .csv (see screenshot) > Copy link

Google Sheets: Publish to web

Code

import pandas as pd

path = 'https://docs.google.com/spreadsheets/d/e/2PACX-1vSvmELTzIjfSmX8GuV3HE2qomN3uRyvPX8RDzpw77JH33DUbj1bjech7H6NYPArvpZFux0DdJ5L5TKy/pub?output=csv'
data = pd.read_csv(path)
print(data)

Code in Google Colab

First

• Click on File
• Select Publish to the web tab
• Select which sheet you want as CSV(in case of multiple sheet) and also change the format from webpage to Comma-separated values
• Click on publish
• Copy the link eg: https://docs.google.com/spreadsheets/d/e/{}/pub?gid=0&single=true&output=csv

import pandas as pd
pd.read_csv("https://docs.google.com/spreadsheets/d/e/{}/pub?gid=0&single=true&output=csv")

Straight to the point:

• Get your google URL

https://docs.google.com/spreadsheets/d/ this is your sheet ID number/edit?gid=This will be your tab name, it will be a number. Each tab has its own

I like to make a function(not making here) so I separate my variables

• sheet_id = "Place your sheet ID here"
• sheet_name = "Place your sheet # here"

the next URL is the tricky part:

url = f"https://docs.google.com/spreadsheets/d/{sheet_id}/export?gid={sheet_name}&format=csv"

Then just read it in

df = pd.csv(url)

That’s it. If you need to select a different row as a header you can do this

df = pd.csv(url, header=1)