How to replace a value in a row with the previous row based on a condition in python?

Question

I have a data table:

Index Value

0      NaN

1      1.15

2      2.25

3      2.33

Condition: First check wherever previous row value is not NaN then replace current row value with previous row value.

Desired output:

Index Value

0      NaN

1      1.15

2      1.15

3      1.15

Answer 1

Compare values for missing values, then get first consecutive value and replace another by DataFrame.where , forward filling missing values and last replace original missing values:

df = pd.DataFrame({'Value':[np.nan,1.15,2.15,3.15,np.nan,2.1,2.2,2.3]})

m = df.notna()
df1 = df.where(m.ne(m.shift())).ffill().where(m)

print (df1)
   Value
0    NaN
1   1.15
2   1.15
3   1.15
4    NaN
5   2.10
6   2.10
7   2.10

Details :

print (m.ne(m.shift()))
  Value
0   True
1   True
2  False
3  False
4   True
5   True
6  False
7  False

print (df.where(m.ne(m.shift())))
 Value
0    NaN
1   1.15
2    NaN
3    NaN
4    NaN
5   2.10
6    NaN
7    NaN

print (df.where(m.ne(m.shift())).ffill())
   Value
0    NaN
1   1.15
2   1.15
3   1.15
4   1.15
5   2.10
6   2.10
7   2.10