Subtracting datetimes in pandas always equals 0 : <p>two columns of dates in my dataframe. The first column is df['schedule_day'] and the second is df['appointment_day']. I am trying to create another column that will be the different between these two. However, when I do the subtraction, the new column just has 0 for each answer. </p>

<p>The original data has these dates as strings and I convert them to datetime objects before doing the subtraction and the result is still a datetime object. 
Here is the code I have used so far. </p>

<pre><code>df = pd.read_csv('noshowappointments-kagglev2-may-2016.csv')

df['schedule_day'] = pd.to_datetime(df['schedule_day'])
df['appointment_day'] = pd.to_datetime(df['schedule_day'])

df['difference'] = df['schedule_date'] - df['appointment_date']
</code></pre>

<p>When I inspect the dtypes the after the initial read they are object / string types. After I do the conversion they are datetime64[ns].</p>

<p>I also tried to split the date and time apart into seperate columns to do the subtractions but I still just get 0 days for each row. </p>
