How to merge these 2 dataframes with pandas efficiently?

Question

I need to merge the label dataframe to the feature dataframe like this:

Label Dataframe:

Time (integer)	Label
0	a
1	b
2	c
...	...

Feature Dataframe:

Time (float)	Feature1	Feature2
0	...	...
0.5	...	...
1	...	...
1.5	...	...
2	...	...
...	...	...

the result dataframe should be something like this:

Time (float)	Feature1	Feature2	Label
0	...	...	a
0.5	...	...	a
1	...	..	b
1.5	...	...	b
2	...	...	c
...	...	...	...

which means, for example in 0~1s , the label is a ; in 1~2s ,the label is b ; etc.

I have 100,000+ rows in the actural dataframe. Is there any efficient way to do this?

Answer 1

One option is

df2['Label'] = df2['Time'].astype(int).map(df1.set_index('Time').squeeze())

Answer 2

You can try this: df1.merge(df2)

The official documentation