Python - Changing names of rows if they are repeated
I wanna change the column "Cuenta" of my dataframe from the left one to the right table, like I show you in the next picture:
entimaer image description here
As you can see the change depends of the number of repetitions of the value "Cuenta" over "Entidad".
df = pd.DataFrame({
"Entidad":["A","A&qu开发者_Python百科ot;,"A","A","A","A","A","B","B","B","B","B"],
"Cuenta": ["Surco","Lima","Miraflores","Lima","SMP","Surco","Lima","Surco","Lima","Miraflores","Lima","SMP"],
"Valor": [12,14,11,7,5,4,22,11,34,21,17,25],
})
Thank your again for your help.
First create a new "suffix" column in your pandas dataframe:
df['suffix']=1
Then create a new column consisting of "Entidad" and "Cuenta":
df['Entidad_Cuenta'] = df['Entidad']+'_'+df['Cuenta']
You can then groupby your dataframe by "Entidad_Cuenta" and compute the cumulative sum of the "suffix", in order to count the number of identical "Cuenta" values for each "Entidad"; you may then append this suffix to "Cuenta":
df['Cuenta'] = df['Cuenta'] + df.groupby('Entidad_Cuenta').cumsum()['suffix'].astype(str)
df['Cuenta']
returns
0 Surco1
1 Lima1
2 Miraflores1
3 Lima2
4 SMP1
5 Surco2
6 Lima3
7 Surco1
8 Lima1
9 Miraflores1
10 Lima2
11 SMP1
I will leave it to you to figure out how to drop "suffix" and "Entidad_Cuenta" from your output dataframe.
store = {}
def fun(item):
global store
_ = store.setdefault(item, 0)
store[item] += 1
return str(item) + ('' if store[item] == 1 else str(store[item]))
# make sure to put store = {} before each column
df.Cuenta.apply(fun)
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