I'm trying to read a csv-file from given URL, using Python 3.x:

import pandas as pd import requests url = "" s = requests.get(url).content c = pd.read_csv(s) 

I have the following error

"Expected file path name or file-like object, got <class 'bytes'> type"

How can I fix this? I'm using Python 3.4

6 Answers

In the latest version of pandas (0.19.2) you can directly pass the url

import pandas as pd url="" c=pd.read_csv(url) 

UPDATE: From pandas 0.19.2 you can now just pass read_csv() the url directly, although that will fail if it requires authentication.

For older pandas versions, or if you need authentication, or for any other HTTP-fault-tolerant reason:

Use pandas.read_csv with a file-like object as the first argument.

• If you want to read the csv from a string, you can use io.StringIO.

• For the URL , you get html response, not raw csv; you should use the url given by the Raw link in the github page for getting raw csv response , which is

Example:

import pandas as pd import io import requests url="" s=requests.get(url).content c=pd.read_csv(io.StringIO(s.decode('utf-8'))) 

Notes:

in Python 2.x, the string-buffer object was StringIO.StringIO

As I commented you need to use a StringIO object and decode i.e c=pd.read_csv(io.StringIO(s.decode("utf-8"))) if using requests, you need to decode as .content returns bytes if you used .text you would just need to pass s as is s = requests.get(url).text c = pd.read_csv(StringIO(s)).

A simpler approach is to pass the correct url of the raw data directly to read_csv, you don't have to pass a file like object, you can pass a url so you don't need requests at all:

c = pd.read_csv("") print(c) 

Output:

 Country Region 0 Algeria AFRICA 1 Angola AFRICA 2 Benin AFRICA 3 Botswana AFRICA 4 Burkina AFRICA 5 Burundi AFRICA 6 Cameroon AFRICA .................................. 

From the docs:

filepath_or_buffer :

string or file handle / StringIO The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. For instance, a local file could be file ://localhost/path/to/table.csv

The problem you're having is that the output you get into the variable 's' is not a csv, but a html file. In order to get the raw csv, you have to modify the url to:

''

Your second problem is that read_csv expects a file name, we can solve this by using StringIO from io module. Third problem is that request.get(url).content delivers a byte stream, we can solve this using the request.get(url).text instead.

End result is this code:

from io import StringIO import pandas as pd import requests url=' s=requests.get(url).text c=pd.read_csv(StringIO(s)) 

output:

>>> c.head() Country Region 0 Algeria AFRICA 1 Angola AFRICA 2 Benin AFRICA 3 Botswana AFRICA 4 Burkina AFRICA 

url = "" c = pd.read_csv(url, sep = "\t") 

To Import Data through URL in pandas just apply the simple below code it works actually better.

import pandas as pd train = pd.read_table("") train.head() 

If you are having issues with a raw data then just put 'r' before URL

import pandas as pd train = pd.read_table(r"") train.head()