Pandas - get value of some no specified previous / next row with condition

Question

I've got an example DataFrame:

import pandas as pd
import numpy as np
df = pd.DataFrame(
    {"col1": ["A", "B", "C", "D", "E", "A", "E", "B", "D"],
     "col2": [1, np.NAN, 3, 4, np.NAN, 6, np.NAN, np.NAN, 8],
    })

Id col1  col2
0    A   1.0
1    B   NaN
2    C   3.0
3    D   4.0
4    E   NaN
5    A   6.0
6    E   NaN
7    B   NaN
8    D   8.0

And would like the row with col1 "E" value to get the value for row's empty col2 from col2 of previous col1 "A" , but we don't know if it is one row above or more.

The same thing I would want to do with row with col1 "B" to get the value for empty col2 from col2 of next col1 "D" .

It would look like this:

id  col1  col2
0    A     1
1    B     4
2    C     3
3    D     4
4    E     1
5    A     6
6    E     6
7    B     8
8    D     8

Is it possible to be done in short script (not many if , else etc.?) Thank you for help!

Answer 1

Idea is first replace non match values to missing values by Series.where , forward or back filling missing values and assign new rows by another masks:

m1 = df['col1'].eq('A')
m11 = df['col1'].eq('E')

m2 = df['col1'].eq('D')
m22 = df['col1'].eq('B')

df.loc[m11, 'col2'] = df['col2'].where(m1).ffill()
df.loc[m22, 'col2'] = df['col2'].where(m2).bfill()
print (df)
  col1  col2
0    A   1.0
1    B   4.0
2    C   3.0
3    D   4.0
4    E   1.0
5    A   6.0
6    E   6.0
7    B   8.0
8    D   8.0