<s>[INST] import pandas as pd

df = pd.read_csv('my_file.csv')
df['my_column'] = pd.to_datetime(df['my_column'], errors='coerce')

print(df['my_column'].value_counts())

df['my_column'] = pd.to_datetime(df['my_column'], format='%m/%d/%y')

print(df['my_column'])

This script reads in a CSV file, converts a column to datetime, and then tries to convert it again with a specific format. However, since the `errors='coerce'` argument in the first conversion already converted unparseable values to NaT (Not a Time), the second conversion will not work correctly and will raise an error on the second conversion. 

The problem is that we don't know the format of the date in the column beforehand. It could be in any format. 

How can we handle this situation and successfully convert the column to datetime?[/INST]