How do I find the row # of a string index?

Question

I have a dataframe where the indexes are not numbers but strings (specifically, name of countries) and they are all unique. Given the name of a country, how do I find its row number (the 'number' value of the index)?

I tried df[df.index == 'country_name'].index but this doesn't work.

Answer 1

We can use Index.get_indexer:

df.index.get_indexer(['Peru'])

[3]

Or we can build a RangeIndex based on the size of the DataFrame then subset that instead:

pd.RangeIndex(len(df))[df.index == 'Peru']

Int64Index([3], dtype='int64')

---

Since we're only looking for a single label and the indexes are "all unique" we can also use Index.get_loc:

df.index.get_loc('Peru')

3

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Sample DataFrame:

import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3, 4, 5]
}, index=['Bahamas', 'Cameroon', 'Ecuador', 'Peru', 'Japan'])

df:

          A
Bahamas   1
Cameroon  2
Ecuador   3
Peru      4
Japan     5

Answer 2

pd.Index.get_indexer

We can use pd.Index.get_indexer to get integer index.

idx = df.index.get_indexer(list_of_target_labels)
# If you only have single label we can use tuple unpacking here.
[idx] = df.index.get_indexer([country_name])

NB: pd.Index.get_indexer takes a list and returns a list. Integers from 0 to n - 1 indicating that the index at these positions matches the corresponding target values. Missing values in the target are marked by -1.

np.where

You could also use np.where here.

idx = np.where(df.index == country_name)[0]

list.index

We could also use list.index after converting Pd.Index to list using pd.Index.tolist

idx = df.index.tolist().index(country_name)