My original DataFrame looks like this:

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:

CodePudding user response：

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

CodePudding user response：

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