Error converting format from object to float in pandas

I am trying to convert a data type object to a float in Pandas, but I cannot fix this error. How can I solve this?

dataset: https://drive.google.com/file/d/1fWUG__B-11mV2td-eoqS7eF1eADnsdRs/view

Output exceeds the size limit. Open the full output data in a text editor
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
d:\Overdose AI\part_a.ipynb Cell 4 in 1
----> 1 df["quantity tons"] = df["quantity tons"].astype(float)

File c:\Users\Admin\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\generic.py:6245, in NDFrame.astype(self, dtype, copy, errors)
   6238     results = [
   6239         self.iloc[:, i].astype(dtype, copy=copy)
   6240         for i in range(len(self.columns))
   6241     ]
   6243 else:
   6244     # else, only a single dtype is given
-> 6245     new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors)
   6246     return self._constructor(new_data).__finalize__(self, method="astype")
   6248 # GH 33113: handle empty frame or series

File c:\Users\Admin\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\internals\managers.py:446, in BaseBlockManager.astype(self, dtype, copy, errors)
    445 def astype(self: T, dtype, copy: bool = False, errors: str = "raise") -> T:
--> 446     return self.apply("astype", dtype=dtype, copy=copy, errors=errors)

File c:\Users\Admin\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\internals\managers.py:348, in BaseBlockManager.apply(self, f, align_keys, ignore_failures, **kwargs)
    346         applied = b.apply(f, **kwargs)
    347     else:
--> 348         applied = getattr(b, f)(**kwargs)
    349 except (TypeError, NotImplementedError):
...
    169     # Explicit copy, or required since NumPy can't view from / to object.
--> 170     return arr.astype(dtype, copy=True)
    172 return arr.astype(dtype, copy=copy)

ValueError: could not convert string to float: 'e'

>Solution :

The problem is that there is a sting "e" in ‘quantity tons’ column (line 173088) in the file you provided.

To avoid this issue, I would suggest to check whether a column has any strings before changing its dtype. You can use the following code:

df[df['quantity tons'].apply(lambda x: isinstance(x, str))]

The output will show you only the rows where ‘quantity tons’ column contains strings.