How to copy missing column values from previous row in pandas

Question

I have csv file, which contains missing column values, how to copy missing column value from previous row ?

product_id,name,modifier
1,test,cheese
,test,eggs
,test,onions
2,test2,cheese
,test2,eggs
,test2,onions

Above CSV data, gets below output

import pandas as pd
import numpy as np
df = pd.read_csv("pivot-products.csv")
df.pivot(index='product_id',columns='modifier') # <-- throws error

Above pivot code works fine with below dataset, where I manually copied it, how to cleanup in pandas to look like below ?

product_id,name,modifier
1,test,cheese
1,test,eggs
1,test,onions
2,test2,cheese
2,test2,eggs
2,test2,onions

Answer 1

Try using ffill. For example:

df = pd.read_csv("pivot-products.csv")
df["product_id"] = df["product_id"].ffill()

Answer 2

Try:

df['product_id'].ffill(inplace=True)

Answer 3

pandas.fillna

but look specifically for the method='ffill' option

Answer 4

df.fillna(mehtod='ffill').fillna(value)

You do fillna twice because the 'ffill' will fail to fill nan values in the first row. You can define the value.