Next, we will convert the date.

Check the datatypes of each column as shown here:

dfs.dtypes

The output of the preceding code is as follows:

subject object
from object
date object
to object
label object
thread float64
dtype: object

Note that a date field is an object. So, we need to convert it into a DateTime argument. In the next step, we are going to convert the date field into an actual DateTime argument. We can do this by using the pandas to_datetime() method. See the following code:

dfs['date'] = dfs['date'].apply(lambda x: pd.to_datetime(x, errors='coerce', utc=True))

Let's move onto the next step, that is, removing NaN values from the fields.