In python3 and pandas I have a dataframe with float values that are displayed like this:
import pandas as pd
df_despesas = pd.read_csv("resultados/despesas_dep_est_sp_julho.csv", sep=',',encoding = 'utf-8', converters={'CNPJ': lambda x: str(x), 'cnpj_raiz_fornecedor': lambda x: str(x), 'Ano': lambda x: str(x)}, decimal=',')
#Configuration to show float with two decimals
pd.options.display.float_format = '{:,.2f}'.format
df_despesas.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 455156 entries, 0 to 455155
Data columns (total 9 columns):
Ano 455156 non-null object
CNPJ 455156 non-null object
Deputado 455156 non-null object
Fornecedor 455156 non-null object
Matricula 455156 non-null object
Mes 455156 non-null object
Tipo 455156 non-null object
Valor 455156 non-null float64
cnpj_raiz_fornecedor 455156 non-null object
dtypes: float64(1), object(8)
memory usage: 31.3+ MB
df_despesas.reset_index().Valor.head()
0 200.00
1 295.40
2 2,850.00
3 100.00
4 195.01
"${:,.2f}".format(df_despesas.Valor.sum())
'$311,900,200.82'
I would like these numbers to appear with dot separating the thousands and comma the cents. Like this:
0 200,00
1 295,40
2 2.850,00
3 100,00
4 195,01
'$311.900.200,82'
Please, does anyone know how I should do it?
I think the simplest way to achieve what you are looking for, i.e. dot separating the thousands and comma the cents would be to use string manipulation. You can create a new function to do so and then use apply to apply it on the respective dataframe column
x = [200, 295.40, 2850, 100, 195.01]
df = pd.DataFrame(x, columns=["value"])
df.value = df.value.map('{:,.2f}'.format)
df
value
0 200.00
1 295.40
2 2,850.00
3 100.00
4 195.01
now create a function to change dots to commas and commas to dots and apply it to the dataframe column
def change_format(x):
return str(x).replace('.', '/').replace(',', '.').replace('/', ',')
df.value = df.value.apply(change_format)
df
value
0 200,00
1 295,40
2 2.850,00
3 100,00
4 195,01