Apply a specific function to a column of a data frame in pandas

Question

I have a data frame as shown below

Date                         in_days
2020-02-01                   1
2020-02-06                   6
2020-02-09                   9
2020-02-03                   3
2020-02-11                   11
2020-02-21                   21
2020-02-13                   13
2020-02-29                   29
2020-02-26                   26

I would like to create a function which is will create a new column called t_factor from in_days as shown below.

t = in_days

if  0 < in_days <= 4:
    t_factor = (3*in_days) + 2
else if 4 < in_days <= 12:
    t_factor = 14
else:
    t_factor = (in_days)**2 + (2*in_days) + 2

Expected output:

Date                         in_days      t_factor
2020-02-01                   1            5
2020-02-06                   6            14     
2020-02-09                   9            14
2020-02-03                   3            11
2020-02-11                   11           14
2020-02-20                   20           442
2020-02-13                   10           12
2020-02-29                   25           677
2020-02-26                   2            8

Answer 1

t in your code is the same with in_days . In which case, you can do:

df['t_factor'] = np.select( (df['in_days'].gt(0) & df['in_days'].le(4),
                             df['in_days'].gt(4) & df['in_days'].le(12)),
                            (df['in_days']*3+2, 14),   # is this 12 or 14?
                            df['in_days']**2 + df['in_days']*2 + 2)

Output:

         Date  in_days  t_factor
0  2020-02-01        1         5
1  2020-02-06        6        14
2  2020-02-09        9        14
3  2020-02-03        3        11
4  2020-02-11       11        14
5  2020-02-20       20       442
6  2020-02-13       10        14
7  2020-02-29       25       677
8  2020-02-26        2         8

Answer 2

You can do it using map function as follow:

df['A'].map(multiply)

where multiply is the function name to apply.