Select a pandas DataFrame column by indices given in another column

Question

Given a dataframe such as

df = pd.DataFrame({1: [10,20,30,40], 2: [50,60,70,80], 3: [90,100,110,120], "select": [2, 3, 1, 1])

I can get a series of values selected from each row want to select values in each row corresponding to the column index given in the select column, like this:

df.apply(lambda r: r[r.select], axis=1)   # 50, 100, 30, 40

Is there a better way to do this that doesn't rely on apply?

Quang Hoang · Accepted Answer · 2020-10-23 21:19:01Z

1

Use lookup:

df.lookup(df.index, df['select'])

Output:

array([ 50, 100,  30,  40])

answered Oct 23, 2020 at 21:19

Quang Hoang

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2 Comments

Stuart Over a year ago

Now deprecated. Not clear what the new way is of doing this.

Quang Hoang Over a year ago

@Stuart The link you given has an example of a replacement. This is a result of the discussion here

Stuart · Accepted Answer · 2023-04-17 16:52:32Z

0

Since DataFrame.lookup is no longer available, something like this (adapted from the docs) seems to be the best way:

def vlookup(df, lookup_series):
    idx, cols = lookup_series.factorize()
    return np.diag(df[cols].to_numpy()[:, idx])

print(vlookup(df, df["select"]))

answered Apr 17, 2023 at 16:52

Stuart

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