How to replace values in a row with first non zero value in pandas?-CodePudding

I am attempting to replace all values in the row that have length > 0 with the first nonzero value. If the row has length 0, replace it with float 0.0

This is the expected input:

    VOL1    VOL2    D
    0       1       3
    21      21      
    19      0       0
    18      0

This is the expected output:

    VOL1    VOL2    D
    1       1       1
    21      21      0.0
    19      19      19  
    18      18      0.0

Thus far, this is what I have attempted:

import pandas as pd
import numpy as np

data = {
        'VOL1':[0, 21, 19, 18],
        'VOL2':[1, 21, 0, 0],
       }
 
# Create DataFrame
df = pd.DataFrame(data)
df['D'] = [3,"",0,""]

#get first nonzero
first_nonzero_df = df[df!=0].cumsum(axis=1).min(axis=1)
if df.isnull().any(axis=1):
  df.any(axis=1).replace(df, first_nonzero_df)

It's unclear to me what I'm doing wrong here, any help is appreciated. Thanks!

CodePudding user response：

IIUC, try:

>>> df.where(df!=0, df[df!=0].ffill(axis=1).bfill(axis=1)).replace("",0)
   VOL1  VOL2     D
0     1     1   3.0
1    21    21   0.0
2    19    19  19.0
3    18    18   0.0

CodePudding user response：

import pandas as pd
data = {
        'VOL1':[0, 21, 19, 18],
        'VOL2':[1, 21, 0, 0],
       }
 
# Create DataFrame
df = pd.DataFrame(data)
df['D'] = [None] * len(df)

first_nonzero_df = df[df!=0].cumsum(axis=1).min(axis=1)

keys = df.keys()
for i in range(len(df)):
    for j in range(len(keys)):
        if df[f'{keys[j]}'][i] == 0:
            df[f'{keys[j]}'][i] = first_nonzero_df[i]
df = df.fillna(0)
df

Output: