Suppose I have a df where I am sure the results are one-to-one like

How can I simply return one column given the other, as a string? So given 'Alaska', return 'AK'.

I tried

df['abbr'].where(df['state'] == 'Alaska')

But it just returns a Series. Do I need to just convert it to a dict or is there some simple solution I'm missing?

CodePudding user response：

You can use the .loc indexer to select the element in the 'Abbr' column that is in the same row as the value 'Alaska' in the 'State' column.

df.loc[df['State'] == 'Alaska', 'Abbr']

This will return a Pandas series with a single element, which you can access using .values[0] if you want to get the value as a string:

df.loc[df['State'] == 'Alaska', 'Abbr'].values[0]

Alternatively, you can use the .at indexer to directly access the value at the specified row and column:

df.at[df['State'] == 'Alaska', 'Abbr']

This will return the value as a string.

Note that both of these methods assume that there is only one row that matches the condition df['State'] == 'Alaska', which is the case in a one-to-one table. If there are multiple rows that match the condition, these methods will return a series with multiple elements, or an error will be raised if you use .at.

CodePudding user response：

There many ways to achieve this:

result_1 = df.query("State.eq('Alaska')")["Abbr"].squeeze()

result_2 = df.set_index("State").at["Alaska", "Abbr"]

result_3 = df[df["State"] == "Alaska"]["Abbr"].squeeze()