For Every duplicated value in Id Column how can i append a string 'duplicated' with that v-CodePudding

I have created a dataframe

df=pd.DataFrame({'Weather':[32,45,12,18,19,27,39,11,22,42],
            'Id':[1,2,3,4,5,1,6,7,8,2]})
df.head()

You can see Id on index 5th and 9th are duplicated. So, I want to append string --duplicated with Id on 5th and 9th index.

df.loc[df['Id'].duplicated()]

Output

   Weather  Id
5   27      1
9   42      2

Expected output

    Weather Id
5   27      1--duplicated
9   42      2--duplicated

CodePudding user response：

Do you want an aggregated DataFrame with modification of your previous output using assign?

(df.loc[df['Id'].duplicated()]
   .assign(Id=lambda d: d['Id'].astype(str).add('--duplicated'))
)

output:

   Weather             Id
5       27  1--duplicated
9       42  2--duplicated

Or, in place modification of the original DataFrame with boolean indexing?

m = df['Id'].duplicated()
df.loc[m, 'Id'] = df.loc[m, 'Id'].astype(str) '--duplicated'

Output:

   Weather             Id
0       32              1
1       45              2
2       12              3
3       18              4
4       19              5
5       27  1--duplicated
6       39              6
7       11              7
8       22              8
9       42  2--duplicated

CodePudding user response：

If need add suffix to filtered rows use DataFrame.loc by mask :

m = df['Id'].duplicated()
df.loc[m,'Id' ] = df.loc[m,'Id' ].astype(str).add('--duplicated')
print (df)
   Weather             Id
0       32              1
1       45              2
2       12              3
3       18              4
4       19              5
5       27  1--duplicated
6       39              6
7       11              7
8       22              8
9       42  2--duplicated

Or use boolean indexing and then add suffix:

df1 = df[df['Id'].duplicated()].copy()
df1['Id'] = df1['Id'].astype(str)   '--duplicated'
print (df1)
   Weather             Id
5       27  1--duplicated
9       42  2--duplicated