Python - Create a column based on multiple other columns in a dataframe

Question

I want to create a new column that outputs ascending or descending depending on values in other columns

  Index Leg  Map Number
   0     AD  J1   1
   1     AD  J1   2
   2     AD  J1   3
   3     AD  J2   5
   4     AD  J2   3
   4     AF  J1   9
   5     AF  J1   6

So looking at this dataframe, I want to create a new column "updown" that is either ascending or descending depending based on the leg, map and number columns. Basically for every leg and map pairings, look at the number column in order to determine whether the numbers are ascending or descending....which will result in a dataframe like:

  Index Leg  Map Number Updown
   0     AD  J1   1     ascending
   1     AD  J1   2     ascending
   2     AD  J1   3     ascending
   3     AD  J2   5     descending
   4     AD  J2   3     descending
   4     AF  J1   9     descending
   5     AF  J1   6     descending

Any help will be appreciated

Answer 1

IIUC, you need:

s=df.groupby(['Leg','Map'])['Number'].transform(lambda x: (x.diff()>0).any())

Or:

s=df.groupby(['Leg','Map'])['Number'].transform(lambda x: x.is_monotonic) #thanks Mark Wang
df['Updown']=np.where(s,'ascending','descending')
print(df)

---

   Index Leg Map  Number      Updown
0      0  AD  J1       1   ascending
1      1  AD  J1       2   ascending
2      2  AD  J1       3   ascending
3      3  AD  J2       5  descending
4      4  AD  J2       3  descending
5      4  AF  J1       9  descending
6      5  AF  J1       6  descending