using similar method like .isin but with row number returned-CodePudding

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

CodePudding user response：

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

CodePudding user response：

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']