I use urlopen to acquire a string of data as follows.I want to convert the string to a data frame and reserve several columns, like state, AQI and so on. I do not know how to do it and want to seek advice from you. Thank you!

 response=urlopen(URL).read().decode('utf-8') print(response) "DateIssue","DateForecast","ReportingArea","StateCode","Latitude","Longitude","ParameterName","AQI","CategoryNumber","CategoryName","ActionDay","Discussion" "2017-05-01 ","2017-05-01 ","Metropolitan Washington","DC","38.919","-77.013","O3","42","1","Good","false","" "2017-05-01 ","2017-05-01 ","Metropolitan Washington","DC","38.919","-77.013","PM2.5","46","1","Good","false","" "2017-05-01 ","2017-05-02 ","Metropolitan Washington","DC","38.919","-77.013","O3","44","1","Good","false","" "2017-05-01 ","2017-05-02 ","Metropolitan Washington","DC","38.919","-77.013","PM2.5","25","1","Good","false","" "2017-05-01 ","2017-05-03 ","Metropolitan Washington","DC","38.919","-77.013","O3","44","1","Good","false","" "2017-05-01 ","2017-05-03 ","Metropolitan Washington","DC","38.919","-77.013","PM2.5","25","1","Good","false","" "2017-05-01 ","2017-05-04 ","Metropolitan Washington","DC","38.919","-77.013","O3","42","1","Good","false","" "2017-05-01 ","2017-05-04 ","Metropolitan Washington","DC","38.919","-77.013","PM2.5","29","1","Good","false",""
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2 Answers

It seems you can use:

from pandas.compat import StringIO df = pd.read_csv(StringIO(response))

But maybe also works:

df = read_csv(URL)
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use read_fwf and to_csv() then read_csv()

import io import pandas as pd df = pd.read_fwf(io.StringIO(response)) df.to_csv('data.csv') result_df = pd.read_csv('data.csv',)
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