How to flatten a column containing a list of dates as strings into just date?

I have a dataframe containing a column that has a list of dates stored as strings:

# sample dataframe
data = [[1, ["2019-08-02 08:30:56"]], [2, ["2020-08-02 08:30:56"]]]

df = pd.DataFrame(data, columns=["items", "dates"])
df["dates"] = df["dates"].astype(str)
df

  items                  dates
0   1   ['2019-08-02 08:30:56']
1   2   ['2020-08-02 08:30:56']

I would like to do several things:

• Convert from a list to a string.
• Convert the string to a date.
• Eliminate the time stamp.

So that the final dataset would look like this:

    items       dates
0   1      2019-08-02
1   2      2020-08-02

I am able to remove the list brackets by doing this:

df["dates_2"] = df["dates"].apply(lambda x: x[1:-1])

But I am wondering if there is a better way to do all of these things in one step?

>Solution :

Another solution is to apply ast.literal_eval to convert the column to list. Then .explode() it, convert to datetime and get a date part:

from ast import literal_eval

df["dates"] = df["dates"].apply(literal_eval)
df = df.explode("dates")
df["dates"] = pd.to_datetime(df["dates"]).dt.date

print(df)

Prints:

   items       dates
0      1  2019-08-02
1      2  2020-08-02