Efficient way to assign values from another column pandas df

Question

I\'m trying to create a more efficient script that creates a new column based off values in another column. The script below performs this but I can only select

Answer 1

You can use:

def f(x):
    #get unique days
    u = x['Day'].unique()
    #mapping dictionary
    d = dict(zip(u, np.arange(len(u)) // 3 + 1))
    x['new'] = x['Day'].map(d)
    return x

df = df.groupby('Location', sort=False).apply(f)
#add Location column
s = df['new'].astype(str) + df['Location']
#encoding by factorize
df['new'] = pd.Series(pd.factorize(s)[0] + 1).map(str).radd('C')
print (df)
      Day Location new
0     Mon     Home  C1
1    Tues     Home  C1
2     Wed     Away  C2
3     Wed     Home  C1
4   Thurs     Away  C2
5   Thurs     Home  C3
6     Fri     Home  C3
7     Mon     Home  C1
8     Sat     Home  C3
9     Fri     Away  C2
10    Sun     Home  C4