Inserting values in DataFrame according to column

Question

My original DataFrame looks like this:

windcodes	name	matu	CLAUSE	WEIGHTEDRT
163197.SH	shangguo comp	2.9248	NO	2.582
154563.SH	guosheng comp	2.886	YES	2.773
789645.IB	guoyou comp		YES	3.098
1880260.IB	shagui comp		YES	2.657

What I want to do now is that for every row if CLAUSE equal to yes, then substitute the matu value of that row with its WEIGHTEDRT value, and if CLAUSE equal to NO then just leave the original matu and weightedrt as they were.

I wish my outcome DataFrame to be look like this:

windcodes	name	matu	CLAUSE	WEIGHTEDRT
163197.SH	shangguo comp	2.9248	NO	2.582
154563.SH	guosheng comp	2.773	YES	2.773
789645.IB	guoyou comp	3.098	YES	3.098
1880260.IB	shagui comp	2.657	YES	2.657

wonjae Kim · Accepted Answer · 2021-11-16 04:17:40Z

2

clause_yes = df['CLAUSE'] == 'YES' df.loc[clause_yes, 'matu'] = df.loc[clause_yes, 'WEIGHTEDRT']

answered Nov 16, 2021 at 4:17

wonjae Kim

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sammywemmy · Accepted Answer · 2021-11-16 08:30:04Z

You can use pd.where here:

df.assign(matu = df.matu.where(df.CLAUSE.eq('NO'), df.WEIGHTEDRT)) windcodes name matu CLAUSE WEIGHTEDRT 0 163197.SH shangguo comp 2.9248 NO 2.582 1 154563.SH guosheng comp 2.7730 YES 2.773 2 789645.IB guoyou comp 3.0980 YES 3.098 3 1880260.IB shagui comp 2.6570 YES 2.657

You can also use np.where too:

df.assign(matu = np.where(df.CLAUSE.eq('YES'), # condition df.WEIGHTEDRT, # result if True df.matu)) # result if False windcodes name matu CLAUSE WEIGHTEDRT 0 163197.SH shangguo comp 2.9248 NO 2.582 1 154563.SH guosheng comp 2.7730 YES 2.773 2 789645.IB guoyou comp 3.0980 YES 3.098 3 1880260.IB shagui comp 2.6570 YES 2.657

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