Multiplying two columns in pandas-CodePudding

I have two columns, which are unit price and quantity (through input by user) and I have to multiply them together to get the total price.

price="{:0.2f}".format(float(input("Enter price: ")))
quantity=int(input("Enter quantity: "))
print("Enter expired date: ")
year = int(input('Enter a year'))
                            
                            
month = int(input('Enter a month'))
            
day = int(input('Enter a day'))
expired_date = datetime.date(year, month, day)
       
df1 = pd.DataFrame(data=[[name,price,quantity,expired_date,today<=expired_date]],columns=["Name","Unit Price","Quantity","Expiry Date","Expired?"])
            

df = df.append(df1,ignore_index=True)
            
**df['Price'] = (df["Quantity"]*(df["Unit Price"]))**
            
df["Expired?"] = df["Expired?"].replace({True: 'Yes', False: 'No'})

However, the result I get is as follows:

Unit Price   Quantity     Price 
  2.00       2            2.002.00

What is the solution for this?

CodePudding user response：

You should not format your price as a string, here:

price = "{:0.2f}".format(float(input("Enter price: ")))

Just leave

price = float(input("Enter price: "))

and that should handle your multiplication correctly

CodePudding user response：

Looks like when you're inserting to dataframe you're inserting as string and not as floats

CodePudding user response：

You are passing the unit price as a string in the dataframe. You need to convert it to float.

price = float("{:0.2f}".format(float(input("Enter price: "))))

or you can simply ignore format and use float as well

price = float(input("Enter price: "))

CodePudding user response：

Firstly you should not treat your price in the string format.

But if you are doing so, cast it to float again:

price="{:0.2f}".format(float(input("Enter price: ")))
price = float(price)

This way you will get a proper output:

Enter price: 2
Enter quantity: 2
Enter expired date: 
Enter a year2022
Enter a month10
Enter a day1
      Name  Unit Price  Quantity Expiry Date Expired?  Price
0  product         2.0         2  2022-10-01      Yes    4.0