从日期列表中删除单词 DateTimeIndex

Question

I have a multiple list of dates in a pandas dataframe in this format:

col1                       col2
1                          [DatetimeIndex(['2018-10-01', '2018-10-02', 
                           '2018-10-03', '2018-10-04'],
                            dtype='datetime64[ns]', freq='D')

I would like to take off the words DatetimeIndex and dtype='datetime64[ns]', freq='D' and turn the list into a set. The format I would be looking for is: {'2018-10-01', '2018-10-02', '2018-10-03', '2018-10-04}

Answer 1

Pandas is not designed to hold collections within series values, so what you are looking to do is strongly discouraged . A much better idea, especially if you have a consistent number of values in each DatetimeIndex series value, is to join extra columns:

D = pd.DatetimeIndex(['2018-10-01', '2018-10-02', '2018-10-03', '2018-10-04'],
                     dtype='datetime64[ns]', freq='D')

df = pd.DataFrame({'col1': [1], 'col2': [D]})

df = df.join(pd.DataFrame(df.pop('col2').values.tolist()))

print(df)

   col1          0          1          2          3
0     1 2018-10-01 2018-10-02 2018-10-03 2018-10-04

---

If you really want a set as each series value, you can do so via map + set :

df['col2'] = list(map(set, df['col2'].values))

print(df)

   col1                                               col2
0     1  {2018-10-01 00:00:00, 2018-10-02 00:00:00, 201...

Answer 2

Have you tried:

set(index_object.tolist())

I suspect this will return you a set of timestamp objects rather than strings so depends on your use case whether this is something you want

if it's the strings you want you can modify the code as follows:

set(index_object.dt.strftime("%Y-%m-%d").tolist())

For your specific format (which I don't necessarily approve of!) you can try this:

import itertools
string_lists = col2.apply(lambda x: x.dt.strftime("%Y-%m-%d").tolist())
unique_set = set(itertools.chain.from_iterable(string_lists.tolist()))