Assign values to newly created column by matching certain words in Python-CodePudding

I have a dataset where, whenever I see a certain word that contains specific words, I'd like to match specific values to within a new column.

Data

id           status
see-dd-2333     y
see-dd-aaaaa    y
sal-led-sss     y
sal-led-sss     n
dis-dd-red      n

Desired

id           status pw  
see-dd-2333     y   14  
see-dd-aaaaa    y   14  
sal-led-sss     y   8   
sal-led-sss     n   8   
dis-dd-red      n   5

Doing

I am thinking I can use a dictionary. Whenever I see a pattern of 'see-dd', I'd like to supply the numerical value of 14. When I see a word that contains 'sal-led' I wish to supply the 8 numerical value. Whenever I see 'dis-dd' I would like to match this with the value of 5.

out= {
    'see-dd': 14,
    'sal-led': 8,
}

Any suggestion is appreciated.

CodePudding user response：

The simplest would be to use the replace method. As the doc noted:

This method has a lot of options. You are encouraged to experiment and play with this method to gain intuition about how it works.

df['id'].replace(regex=out)

0    14
1    14
2     8
3     8
4     5
Name: id, dtype: int64

with out as:

out= {
    'see-dd': 14,
    'sal-led': 8,
    'dis-dd':  5
}

df['pw'] = df['id'].replace(regex=out)

df
             id status  pw
0   see-dd-2333      y  14
1  see-dd-aaaaa      y  14
2   sal-led-sss      y   8
3   sal-led-sss      n   8
4    dis-dd-red      n   5

CodePudding user response：

You can also use:

df['pw'] = df['id'].str.rsplit('-', 1).str.get(0).map(out)

Output:

            id status  pw
0   see-dd-2333      y  14
1  see-dd-aaaaa      y  14
2   sal-led-sss      y   8
3   sal-led-sss      n   8
4    dis-dd-red      n   5