LossySetItemError when converting column type of 'int64' to 'float64' with astype()

Try to avoid .loc for type conversion. Assigning directly to the column name tells Pandas to replace the entire Series/pointer rather than trying to update the values within the existing block.

Instead of: df.loc[:, 'col'] = df['col'].astype('float64')

Try to use: df['col'] = df['col'].astype('float64')

The error happens because your DataFrame columns are int64.
But normalization produces decimal numbers (float) between 0 and 1.

Pandas does not allow putting float values into an int64 column, so it raises the error.
Simple solution is to convert the DataFrame to float first.
data = pd.readexcel("filename.xlsx", header=[10,11])
data = data.astype(float)

Then normalize.
data = (data - data.min()) / (data.max() - data.min())