Pandas: iterate through a list to match values in a dataframe

Question

I'm working with a dataframe of covid counts for all counties in the US. I've figured out how to isolate one county and export the result to a csv like this:

import pandas as pd
covid = pd.read_csv('https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv')
agh = covid[covid['county'] == 'Allegheny']
agh.to_csv('AlleghenyCovid.csv')

Now I want to create a list of counties like this:

countyList = covid.county.unique()

and loop through them to create a csv for each. That's where I'm stuck. How can I use a list of known values to iterate through the dataframe and create new dataframes from each iteration? I've been thinking something like:

for i in countyList:
    if covid['county'] == i:
        ...

but that gives an ambiguous value error. I'm not sure exactly what needs to be defined.

Answer 1

Solution iterate unique list of county column:

for name in covid.county.unique()
    covid.loc[covid.county == name,:].to_csv(name+'.csv')

For each county named by name :

• we are selecting rows from dataframe covid where county is equal to name
• then such selection is saved to CSV file named: name + .csv .