How to assign a value to the variable based on the existing variables in python?

Question

I want to assign a value to the variable based on the existing variable values. I will give you a brief explanation of the data.

mydata

      category  original_wt  predicted_wt   categorized
    1 xxxxx      2.5          3.0            original
    2 yyyyy      3.5          4.0            predicted
    3 zzzzz      3.0          5.0            predicted
    4 aaaaa      4.0          2.5            original
    5 bbbbb      3.2          5.5            original
    6 ccccc      4.6          3.5            predicted

From the above data i want to assign a value based on categorized type.
If it is original the categorized value should be original_wt of same row.
If it is predicted the categorized value should be predicted_wt of same row.

Expected output:

mydata

  category  original_wt  predicted_wt   categorized   categorized_value
1 xxxxx      2.5          3.0            original      2.5
2 yyyyy      3.5          4.0            predicted     4.0
3 zzzzz      3.0          5.0            predicted     5.0
4 aaaaa      4.0          2.5            original      4.0
5 bbbbb      3.2          5.5            original      3.2
6 ccccc      4.6          3.5            predicted     3.5

Tried:

mydata['categorized_value'] = 
     if mydata['categorized'] == 'original':
        mydata['categorized_value'] = mydata['original_wt']
     else:
     mydata['categorized_value'] = mydata['predicted_wt']

How do i get my expected output in python?

Is the code indented correctly? The else: branch is not indented now and will always be run, so value is always predicted — Sami Kuhmonen
– Sami Kuhmonen, Commented May 14, 2015 at 9:20

EdChum · Accepted Answer · 2015-05-14 09:24:07Z

3

Use loc and a boolean mask to set the values you desire:

In [221]:

df.loc[df['categorized'] == 'original', 'categorized_value'] = df['original_wt']
df.loc[df['categorized'] == 'predicted', 'categorized_value'] = df['predicted_wt']
df
Out[221]:
  category  original_wt  predicted_wt categorized  categorized_value
1    xxxxx          2.5           3.0    original                2.5
2    yyyyy          3.5           4.0   predicted                4.0
3    zzzzz          3.0           5.0   predicted                5.0
4    aaaaa          4.0           2.5    original                4.0
5    bbbbb          3.2           5.5    original                3.2
6    ccccc          4.6           3.5   predicted                3.5

answered May 14, 2015 at 9:24

EdChum

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Comments

Julien Spronck · Accepted Answer · 2015-05-14 09:25:30Z

1

You can use apply:

mydata['categorized_value'] = mydata.apply(lambda x: x['original_wt'] if x['categorized'] == 'original' else x['predicted_wt'], axis=1)

answered May 14, 2015 at 9:25

Julien Spronck

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