如何用多列替换Pandas数据帧中的单元格？

Question

I have a dataframe with multiple columns and I would like to replace cells with 0 with the previous value in the column, in one shot.

It works with df['A'].replace(to_replace=0, method='ffill') but as soon as it's the all dataframe it throws an error, probably because to_replace is not a series.

How can I do that ?

import datetime
import pandas as pd
import numpy as np

todays_date = datetime.datetime.now().date()
index = pd.date_range(todays_date-datetime.timedelta(10), periods=4, freq='D')

columns = ['A','B', 'C']
data = np.array([[1, 2, 2], [3, 0, 5], [0, 4, 0], [3, 4, 5]])
df = pd.DataFrame(data, index=index, columns=columns)
df
Out[333]: 
            A  B  C
2018-07-16  1  2  2
2018-07-17  3  0  5
2018-07-18  0  4  0
2018-07-19  3  4  5

# Throws an error here :

df.replace(to_replace=0, method='ffill')
TypeError: cannot replace [0] with method ffill on a DataFrame

# Works column by column :

df['A'].replace(to_replace=0, method='ffill')
Out[338]: 
2018-07-16    1
2018-07-17    3
2018-07-18    3
2018-07-19    3
Freq: D, Name: A, dtype: int64

Answer 1

May be this:

print(df.replace(0,np.nan).ffill())

Output:

              A    B    C
2018-07-16  1.0  2.0  2.0
2018-07-17  3.0  2.0  5.0
2018-07-18  3.0  4.0  5.0
2018-07-19  3.0  4.0  5.0

Answer 2

Which version of pandas are you using? It seems like they added the possibility to use method in a DataFrame with version 0.23.0: see the docs .