I have a pandas dataframe that consist of 5000 rows with different countries and emission data, and looks like the following:

The country label is an index.

eg. df = emission.loc[['peru']]

would give me a new dataframe consisting only of the emission data attached to peru. My goal is to use a variable name instead of 'peru' and store the country-specific emission data into a new dataframe.

what I search for is a code that would work the same way as the code below:

country = 'zanzibar'

df = emissions.loc[[{country}]]

From what I can tell the problem arises with the iloc function which does not accept variables as input. Is there a way I could circumvent this problem?

In other words I want to be able to create a new dataframe with country specific emission data, based on a variable that matches one of the countries in my emission.index()all without having to change anything but the given variable.

One way could be to iterate through or maybe create a function in some way? Thank you in advance for any help.

CodePudding user response：

You should be able to select by a certain string for your index. For example:

df = pd.DataFrame({'a':[1,2,3,4]}, index=['Peru','Peru','zanzibar','zanzibar'])
country = 'zanzibar'
df.loc[{country}]

This will return:

          a
zanzibar  3
zanzibar  4

In your case, removing one set of square brackets should work:

country = 'zanzibar'
df = emissions.loc[{country}]

CodePudding user response：

An alternative approach where you dont use a country name for your index:

emissions = pd.DataFrame({'Country' : ['Peru', 'Peru', 'Peru', 'Chile', 'Chile', 'Chile'], "Year" : [2021,2020,2019,2021,2020,2019], 'Emissions' : [100,200,400,300,200,100]})
country = 'Peru'

Then to filter:

df = emissions[emissions.Country == country]

or

df = emissions.loc[emissions.Country == country]

Giving:

   Country  Year  Emissions
0  Peru     2021  100
1  Peru     2020  200
2  Peru     2019  400