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How to convert Row from SQL TO Pandas?

I have this table:
Country Value

I wish to generate a single value based on the following criteria:

If 2 or more rows in the same Country have the same Value, the last row of that same Country is the value.
If a row in Country1 doesn’t have Value, look up for Country2
Take the last row of the above situation

The result of this would be:
Country Value

Is it possible? I know how to do this in excel, but was wondering if this can be done in python using pandas.
I appreciate your help.


You can look for an accumulator Series and assign the value to that in a dict comprehension.
import pandas as pd
df = pd.DataFrame({‘Country’: [‘Country1’, ‘Country2’, ‘Country3’, ‘Country1’, ‘Country3’, ‘Country2’]})
grouped = df.groupby(‘Country’)
result = dict(tuple(e.last_row for _, e in grouped))
{‘Country1’: [Country3, Country2

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