How to efficiently replace items between Dataframes in pandas?

Question

I have 2 df

df = pd.DataFrame({'Ages':[20, 22, 57], 'Label':[1,1,2]})
label_df = pd.DataFrame({'Label':[1,2,3], 'Description':['Young','Old','Very Old']})

I want to replace the label values in df to the description in label_df

Wanted result:

df = pd.DataFrame({'Ages':[20, 22, 57], 'Label':['Young','Young','Old']})

score 2 · Accepted Answer · answered Jun 15 '21 at 12:08

2

Use Series.map with Series by label_df:

df['Label'] = df['Label'].map(label_df.set_index('Label')['Description'])
print (df)
   Ages  Label
0    20  Young
1    22  Young
2    57    Old

answered Jun 15 '21 at 12:08

jezrael

What would happen if there is no match between the indexes, what would map do? – Moshe Jun 15 '21 at 13:58
@Moshe then is returned NaN – jezrael Jun 15 '21 at 16:06

nay · Answer 2 · 2021-06-15T12:35:57.280

1

simple use merge

df['Label'] = df.merge(label_df,on='Label')['Description']

    Ages    Label
0   20  Young
1   22  Young
2   57  Old

edited Jun 15 '21 at 12:35

answered Jun 15 '21 at 12:12

nay

That's great, but I guess that it would not work in a situation where column name is not equal, for example 'Label' and 'Age_Label', right ? – Moshe Jun 15 '21 at 12:56
if column name not the same.you can use left_on and right_on – nay Jun 15 '21 at 14:24

2 Answers2