I have a pandas dataframe in which the date information is a string with the month and year:

```
date = ["JUN 17", "JULY 17", "AUG 18", "NOV 19"]

```

Note that the month is usually written as the 3 digit abbreviation, but is sometimes written as the full month for June and July.

I would like to convert this into a datetime format which assumes each date is on the first of the month:

```
date = [06-01-2017, 07-01-2017, 08-01-2018, 11-01-2019]

```

Edit to provide more information:
Two main issues I wasn't sure how to handle:

1. Month is not in a consistent format. Tried to solve this using by just taking a subset of the first three characters of the string.
2. Year is last two digits only, was struggling to specify that it is 2020 without it getting very messy
I have tried a dozen different things that didn't work, most recent attempt is below:

```
df['date'] = pd.to_datetime(dict(year = df['Record Month'].astype(str).str[-2:], month = df['Record Month'].astype(str).str[0:3], day=1))

```

This has the error "Unable to parse string "JUN" at position 0