Return the index of a row based on value in different dataframe's row

Question

I have two Pandas dataframes. They all contain 3 decimal point float values.

Dataframe A is a one column dataframe with 12 rows. Dataframe B is a one column dataframe with over 40,000 rows, which contain the 12 values in Dataframe A spread out randomly.

I need to find the indices of the values in Dataframe A within Dataframe B.

I have tried .query() , .index.value() and .where() but am unable to return the indices.

Dataframe A

Row Index	Time
0	148.521
1	112.379
...	...
12	510.121

Dataframe B

Row Index	Time
0	0.000
1	0.025
...	...
46871	1171.675

Answer 1

You can use df.loc[]

for i in dataframe_A['Time']:
  dataframe_B.loc[dataframe_B['Time'] == i]

This should return the twelve values along with their row index from dataframe B