df

df_sum_price = df['Price'].sum()
df_sum_tax = df['Tax'].sum()
df_sum_price 
df_sum_tax 

output wanted:

>>> U$ 83,00
U$ 2,93

HOW CAN I DO THIS? Because i need before convert Object to Int or Float but i don't know why! .-. help me please

CodePudding user response：

To my knowledge, there is no currency type in Python. I guess your "Price" column is a string? The first operation would be to turn this column into a float. To do so, you have to remove the "U$ " in front of the digits, and then turn the "," into "." to be able to turn your string into a float. So a function doing that would be:

def price_to_float(price):
    return(float(price[3:].replace(',','.')))`

Then, just apply this function to your whole column with:

df['Price']=df.apply(lambda row : price_to_float(row['Price']), axis = 1)
df['Tax']=df.apply(lambda row : price_to_float(row['Price']), axis = 1)

Now you can perform all the operations you want to! You can then turn your column back to a currency string if you need to.

CodePudding user response：

if you have an option to convert datatype in dataframe the you can do this

df['Tax']=(df['Tax'].str[3:]).str.replace(',','').astype(int)
df['Price']=(df['Price'].str[3:]).str.replace(',','').astype(int)

output:

  Product  Price  Tax
0    Fork   1400   40
1   Knife   2300   85
2   Knife   2300   91
3   Knife   2300   77

df_sum_price = df['Price'].sum()
df_sum_tax = df['Tax'].sum()
df_sum_price 
df_sum_tax 

output:

8300
293

if you dont have the freedom to change datatype and just want to perform the sum then do this:

df_sum_price = (df['Tax'].str[3:]).str.replace(',','').astype(int).sum()
df_sum_tax = (df['Price'].str[3:]).str.replace(',','').astype(int).sum()
df_sum_price 
df_sum_tax 

output is same in both the cases.