python - 用每行增加的列偏移量填充 pandas 数据框

Question

我正在尝试创建一个 pandas 数据框，其中每行都填充相同的值集，但对于向下迭代数据框的每一行，每行的起始列都会增加 1。这是我当前的方法，以及我希望获得的数据框的示例。我在这里做错了什么？

谢谢!

import pandas as pd
import numpy as np

df_to_fill = pd.DataFrame(data=np.zeros((4,6)),columns=[1,2,3,4,5,6])

values_to_fill = pd.Series(np.arange(1,4))

# vars to iterate over dataframe
num_rows = len(df_to_fill)
# counter to keep track of how many columns to offset from to fill dataframe in loop below
col_offset = 0

for row in range(0,num_rows):
    # Fill the first row from first column onwards, 2nd from 2nd column onwards,...
    df_to_fill.iloc[row,col_offset:] = values_to_fill
    # Fill the remaining columns in the row with the last value from the values to fill series
    df_to_fill.iloc[row,:].fillna(values_to_fill.values[-1],inplace=True)    
    col_offset += 1

offset_array = np.array([[1,2,3,3,3,3],[0,1,2,3,3,3],[0,0,1,2,3,3]])
desired_df = pd.DataFrame(data=offset_array,columns=[1,2,3,4,5,6])

Answer 1

您可以使用 shift + concat 创建与第一行相同的填充值

values_to_fill = pd.Series(np.arange(1,4),index=np.arange(1,4)).reindex(np.arange(1,7)).ffill().astype(int)

pd.concat([values_to_fill.shift(x) for x in range(num_rows)],axis = 1 ).T.fillna(0)
     1    2    3    4    5    6
0  1.0  2.0  3.0  3.0  3.0  3.0
1  0.0  1.0  2.0  3.0  3.0  3.0
2  0.0  0.0  1.0  2.0  3.0  3.0
3  0.0  0.0  0.0  1.0  2.0  3.0