在python3和pandas中,我有一个数据框,其浮点值显示如下:
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'
我希望这些数字以点分隔千位并用逗号隔开。像这样:
0 200,00
1 295,40
2 2.850,00
3 100,00
4 195,01
'$311.900.200,82'
请,有人知道我应该怎么做吗?
答案 0 :(得分:1)
在这里回答:
How to display pandas DataFrame of floats using a format string for columns?
从那里的评论中,我看到您可以轻松做到
df_despesas['Valor_dollars_fmt'] = df_despesas['Valor'].map('${:,.2f}'.format)
答案 1 :(得分:1)
我认为实现您正在寻找的最简单方法,即dot separating the thousands and comma the cents
是使用字符串操作。您可以创建一个新函数,然后使用apply
将其应用于相应的数据框列
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
现在创建一个函数,以将点更改为逗号并将逗号更改为点并将其应用于数据框列
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