df['DataFrame Column'] = pd.to_numeric(df['DataFrame Column'], errors='coerce')
print(df.dtypes)
Product Price
0 AAA 250.0
1 BBB NaN
2 CCC 270.0
3 DDD NaN
Product object
Price float64
dtype: objectdf['DataFrame Column'] = df['DataFrame Column'].astype(float)
print(df.dtypes)
Product Price
0 AAA 250.0
1 BBB NaN
2 CCC 270.0
3 DDD NaN
Product object
Price float64
dtype: objectdf = df.astype(float)
print(df.dtypes)
Price_1 Price_2 Price_3
0 300.0 250.0 530.0
1 750.0 270.0 480.0
2 600.0 950.0 420.0
3 770.0 580.0 290.0
4 920.0 410.0 830.0
Price_1 float64
Price_2 float64
Price_3 float64
dtype: object