using similar method like .isin but with row number returned

user_12771524 0
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I want to get the row number of matching condition similar like .isin, part of dataframe are shown like this

df1

0    452525
1    110101
2    393910

df2

0     100000
1     110000
2     110100
3     110101
4     110102
5     110105
6     110106
7     110107
8     110108
9     110109
10    110111
11    110112
12    110113
13    110114
14    110115

when I use

t1.isin(t2)

I got

0    False
1     True
2    False

My desired output is

0    NaN
1    3
2    NaN

Is there a method to do this? But I want to avoid using pd.merge() since both dataframe is big, if merging them would take long time to execute

pandas numpy python
2 Answers

Use Series.map by dictionary with swap values and index of t2:

#if t1, t2 are Series
out = t1.map(dict(zip(t2, t2.index)))

#if t1, t2 are Dataframes
out = t1['col'].map(dict(zip(t2['col'], t2.index)))
print (out)
0    NaN
1    3.0
2    NaN
Name: col, dtype: float64
user_29010020

Assuming t1 and t2 Series, I would use a merge:

t1.to_frame().merge(t2.reset_index(), how='left')['index']

output:

0    NaN
1    3.0
2    NaN
Name: index, dtype: float64

From the dataframes df1 and df2 and using "col" as column name:

df1.merge(df2.reset_index(), on='col', how='left')['index']
user_163434640
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