Subtracting a constant value from one column when condition on another column holds

Question

I have a Pandas data frame that has the following columns: foo and bar. foo values are integers and bar values are strings. For each row, if the value of bar is some particular value, say, ‘ABC’, then I want to set the value of the foo column (for that row) to its current value minus one.

For example, I want to convert this data frame:

foo	bar
98	‘ABC’
53	‘DEF’
22	‘ABC’
34	‘FGH’

converted to this:

foo	bar
97	‘ABC’
53	‘DEF’
21	‘ABC’
34	‘FGH’

How is this done?

Asked By: Paul Reiners

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Source

Answer 1

In [2]: df
Out[2]:
   foo  bar
0   98  ABC
1   53  DEF
2   22  ABC
3   34  FGH

In [3]: df.loc[df.bar=='ABC', 'foo'] = df[df.bar=='ABC']['foo']-1

In [4]: df
Out[4]:
   foo  bar
0   97  ABC
1   53  DEF
2   21  ABC
3   34  FGH

Answered By: inspectorG4dget

Answer 2

You can do this via the .loc on dataframe:

CONSTANT_VAL = 1
df.loc[df['bar'] == 'ABC', 'foo'] -= CONSTANT_VAL

Answered By: Sanyam Khurana

Answer 3

.loc and np.where both can work as a possible solution here.

np.where works like an if-else statement, where it checks whether the condition is met, which in this case is df['bar'] == 'ABC', and if its true, subtract 1 from df[‘foo’], else dont do anything.

df['foo'] = np.where(df['bar']=='ABC', df['foo']-1, df['foo'])

Answered By: P. Shroff

Subtracting a constant value from one column when condition on another column holds

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