Value error in Python
Valueerror in Python occurs when an invalid type of value is passed to a function other than the type specified in the function argument. Developers generally handle this type of error using the try-except block or the raise keyword.
Python3
#importing pandas libraryimport pandas as pd# Create a DataFrame with strings containing symbolsdf = pd.DataFrame({'Prices': ['23-00', '56-50', '78-10', '9-05']})#Convert the column to floatdf['Prices'] = df['Prices'].astype(float)#Print the DataFrameprint(df) |
Output:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-1-d082d5acca01> in <cell line: 11>()
9
10 #Convert the column to float
---> 11 df['Prices'] = df['Prices'].astype(float)
12
13 #Print the DataFrame
168 if copy or is_object_dtype(arr.dtype) or is_object_dtype(dtype):
169 # Explicit copy, or required since NumPy can't view from / to object.
--> 170 return arr.astype(dtype, copy=True)
171
172 return arr.astype(dtype, copy=copy)
ValueError: could not convert string to float: '23-00'
How To Handle Pandas Value Error Could Not Convert String To Float
Pandas is an open-source Python library used for data manipulation and analysis. It is a powerful package that provides fast, flexible, and meaningful data structures that help with practical, real-world data analysis. Its functions help in working with structured and labelled data like spreadsheets, tables, etc. It is considered a powerful tool by the developers for data analysis, as it helps in importing the data efficiently. It is used in various fields like data science, machine learning, etc., as it provides many functions for data analysis.