我想在以下条件下对数据框的特定列应用向后填充：我认为“ colum_A”只能假设四个值，称为A，B，C，D，并且向后填充应按如下方式工作下列：
if the first not NaN is A, then backward_filling with A;
if the first not NaN is B, then backward_filling with B;
if the first not NaN is C, then backward_filling with B;
if the first not NaN is D, then backward_filling with C;
if the column_A only contains NaN, then backward_filling with D
例如：
输入DF：
colum_A
NaN
NaN
B
B
C
C
输出DF：
colum_A
B
B
C
C
D
D
请任何帮助将不胜感激。
最好的祝福，
卡洛
最佳答案
我认为您需要按条件使用map和bfill：
#get mask for back filling NaNs
m = df['colum_A'].isnull()
d = {'A':'A','B':'B','C':'B','D':'C'}
#D if all values NaN
df['colum_B'] = 'D' if m.all() else np.where(m, df['colum_A'].map(d).bfill(),df['colum_A'])
#alternative
#df['colum_B'] = 'D' if m.all() else df['colum_A'].mask(m, df['colum_A'].map(d).bfill())
print (df)
colum_A colum_B
0 NaN B
1 NaN B
2 B B
3 A A
4 NaN B
5 C C
6 C C
7 NaN C
8 NaN C
9 NaN C
10 D D
11 D D
12 A A
13 C C
14 NaN A
15 A A
16 NaN NaN
关于python - 向后填充条件，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/46175104/