return array(a, dtype, copy=False, order=order) ValueError: could not convert string to float: 'STRING' when building machine leaning model

Question

I'm getting the following error: return array(a, dtype, copy=False, order=order) ValueError: could not convert string to float: 'BOX72'(BOX72 is a value under column5).

The error seems to come at the line with code impute_knn.fit_transform(X)

Here is the code so far:

import pandas as pd
from sklearn.preprocessing import LabelEncoder
import numpy as np

dataframe = pd.read_csv('file.csv', delimiter=',')

le = LabelEncoder()
dfle = dataframe

dfle2 = dfle.apply(lambda col: le.fit_transform(col.astype(str)), axis=0, result_type='expand')

newdf = dfle2[['column1', 'column2', 'column3', 'column4', 'column5', 'column6', 'column7']]

X = dataframe[['column1', 'column2', 'column4', 'column5', 'column6', 'column7']].values

y = dfle.column3

from sklearn.preprocessing import OneHotEncoder
from sklearn.compose import ColumnTransformer
ohe = OneHotEncoder()

impute_knn = KNNImputer(n_neighbors=2)
impute_knn.fit_transform(X)

ColumnTransformer([('encoder', OneHotEncoder(), [0])], remainder='passthrough')
X = ohe.fit_transform(X).toarray()

I know I can probably use something like strip(), but I can't seem to figure out how I use it to remove any space before or after a string for all cells (in case there are other similar value entries). I also, don't know if this is actually the solution. Any pointers or help would be appreciated. Thank you.