Gregory Saxton Gregory Saxton - 1 year ago 131
Python Question

Cumulative Set in PANDAS

I have a dataframe of tweets and I'm looking to group the dataframe by date and generate a column that contains a cumulative list of all the unique users who have posted up to that date. None of the existing functions (e.g., cumsum) would appear to work for this. Here's a sample of the original tweet dataframe, where the index (created_at) is in datetime format:

In [3]: df
04-01-16 Bob
04-01-16 Bob
04-01-16 Sally
04-01-16 Sally
04-02-16 Bob
04-02-16 Miguel
04-02-16 Tim

I can collapse the dataset by date and get a column with the unique users per day:

In [4]: df[['screen_name']].groupby( x: set(list(x)))

Out[4]: from_user_screen_name
2016-04-02 {Bob, Sally}
2016-04-03 {Bob, Miguel, Tim}

So far so good. But what I'd like is to have a "cumulative set" like this:

Out[4]: Cumulative_list_up_to_this_date Cumulative_number_of_unique_users
2016-04-02 {Bob, Sally} 2
2016-04-03 {Bob, Sally, Miguel, Tim} 4

Ultimately, what I am really interested in is the cumulative number in the last column so I can plot it. I've considered looping over dates and other things but can't seem to find a good way. Thanks in advance for any help.

Answer Source

You cannot add sets, but can add lists! So build a list of users, then take the cumulative sum and finally apply the set constructor to get rid of duplicates.

cum_names = (df['screen_name'].groupby(
                              .agg(lambda x: list(x))
# 2016-04-01                 {Bob, Sally}
# 2016-04-02    {Bob, Miguel, Tim, Sally}
# dtype: object

cum_count = cum_names.apply(len)
# 2016-04-01    2
# 2016-04-02    4
# dtype: int64
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