Python 使用 Pandas 将文本数据从请求对象转换为数据框
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/39213597/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Convert text data from requests object to dataframe with pandas
提问by sparrow
Using requests I am creating an object which is in .csv format. How can I then write that object to a DataFrame with pandas?
使用请求我正在创建一个 .csv 格式的对象。然后我怎样才能将该对象写入带有熊猫的 DataFrame 中？
To get the requests object in text format:
以文本格式获取请求对象：
import requests
import pandas as pd
url = r'http://test.url'
r = requests.get(url)
r.text #this will return the data as text in csv format
I tried (doesn't work):
我试过（不起作用）：
pd.read_csv(r.text)
pd.DataFrame.from_csv(r.text)
回答by Merlin
Try this
尝试这个
import requests
import pandas as pd
import io
urlData = requests.get(url).content
rawData = pd.read_csv(io.StringIO(urlData.decode('utf-8')))
回答by jezrael
I think you can use read_csvwith url:
我想你可以用read_csv用url：
pd.read_csv(url)
filepath_or_buffer: str, pathlib.Path, py._path.local.LocalPath or any object with a read() method (such as a file handle or 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
filepath_or_buffer: str, pathlib.Path, py._path.local.LocalPath 或任何具有 read() 方法的对象（例如文件句柄或 StringIO）
该字符串可以是一个 URL。有效的 URL 方案包括 http、ftp、s3 和文件。对于文件 URL，需要一个主机。例如，本地文件可以是 file://localhost/path/to/table.csv
import pandas as pd
import io
import requests
url = r'http://...'
r = requests.get(url)
df = pd.read_csv(io.StringIO(r))
If it doesnt work, try update last line:
如果它不起作用，请尝试更新最后一行：
import pandas as pd
import io
import requests
url = r'http://...'
r = requests.get(url)
df = pd.read_csv(io.StringIO(r.text))
回答by rkoots
if the url has no authentication then you can directly use read_csv(url)
如果 url 没有身份验证，那么您可以直接使用 read_csv(url)
if you have authentication you can use request to get it un-pickel and print the csv and make sure the result is CSV and use panda.
如果您有身份验证，您可以使用请求将其取消pickel并打印csv并确保结果为CSV并使用panda。
You can directly use importing import csv
可以直接使用importing import csv
回答by Bento
Using "read_csv with url" worked:
使用“read_csv with url”有效：
import requests, csv
import pandas as pd
url = 'https://arte.folha.uol.com.br/ciencia/2020//csv/mundo/dados-bra.csv'
corona_bra = pd.read_csv(url)
print(corona_bra.head())
