My Datatype:
TEAM object
NATIONALITY object
TYPE object
PRICE PAID object
dtype: object
Code goes here: I want convert 'PRICE PAID' Column
top_buys_df['PRICE PAID'] = pd.to_numeric(top_buys_df['PRICE PAID'])
[ top_buys_df['PRICE PAID'] = pd.to_numeric(top_buys_df['PRICE PAID'].str.replace(',', '.')) ]
When I am trying to run this line in Jupyter Notebook.
I am getting "ValueError: Unable to parse string " 24,75,00,000" at position 0"
I have tried different methods of converting
top_buys_df.dtypes
TEAM object
NATIONALITY object
TYPE object
PRICE PAID object
dtype: object
top_buys_df['PRICE PAID']
PRICE PAID
column values:
0 24,75,00,000
1 20,50,00,000
2 14,00,00,000
3 11,75,00,000
4 11,50,00,000
5 10,00,00,000
6 8,40,00,000
7 8,00,00,000
8 7,40,00,000
9 7,40,00,000
Name: PRICE PAID, dtype: object
Tried these methods individually for converting my PRICE PAID: object
to int
:
#top_buys_df['PRICE PAID'] = top_buys_df['PRICE PAID'].astype(int)
Error: invalid literal for int() with base 10: ' 24,75,00,000'
top_buys_df['PRICE PAID'] = pd.to_numeric(top_buys_df['PRICE PAID'].str.replace(',', '.'))
Error: ValueError: Unable to parse string " 24.75.00.000"
top_buys_df['PRICE PAID'] = pd.to_numeric(top_buys_df['PRICE PAID'])
Error: ValueError: Unable to parse string " 24.75.00.000"
You should replace the commas with empty strings, not dots (i.e delete the commas). Here you want to remove the thousands separator, not change the decimal separator.
top_buys_df['PRICE PAID'] = pd.to_numeric(top_buys_df['PRICE PAID']
.str.replace(',', ''))
Output:
PRICE PAID
0 247500000
1 205000000
2 140000000
3 117500000
4 115000000
5 100000000
6 84000000
7 80000000
8 74000000
9 74000000