As of Pandas 0.19.2, the function read_csv() can be passed a URL. See, for example, from this answer:
import pandas as pd
url="https://raw.githubusercontent.com/cs109/2014_data/master/countries.csv"
c=pd.read_csv(url)
The URL I'd like to use is: https://moz.com/top500/domains/csv
With the above code, this URL returns an error:
urllib2.HTTPError: HTTP Error 403: Forbidden
based on this post, I can get a valid response by passing a request header:
import urllib2,cookielib
site= "https://moz.com/top500/domains/csv"
hdr = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
'Accept-Encoding': 'none',
'Accept-Language': 'en-US,en;q=0.8',
'Connection': 'keep-alive'}
req = urllib2.Request(site, headers=hdr)
try:
page = urllib2.urlopen(req)
except urllib2.HTTPError, e:
print (e.fp.read())
content = page.read()
print (content)
Is there any way to use the web URL functionality of Pandas read_csv()
, but also pass a request header to make the request go through?
I would recommend you using the requests and the io library for your task. The following code should do the job:
import pandas as pd
import requests
from io import StringIO
url = "https://moz.com:443/top500/domains/csv"
headers = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.14; rv:66.0) Gecko/20100101 Firefox/66.0"}
req = requests.get(url, headers=headers)
data = StringIO(req.text)
df = pd.read_csv(data)
print(df)
(If you want to add a custom header just modify the headers
variable)
Hope this helps
As of pandas 1.3.0, you can now pass custom HTTP(s) headers using storage_options
argument:
url = "https://moz.com:443/top500/domains/csv"
hdr = {
'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
'Accept-Encoding': 'none',
'Accept-Language': 'en-US,en;q=0.8',
'Connection': 'keep-alive'
}
domains_df = pd.read_csv(url, storage_options=hdr)
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