python - Reshaping pandas DataFrame from long to wide while adding many columns -


i have long dataframe df in following format:

user_id day action1 action2 action3 action4 action5       1   0       4       2       0       1       0       1   1       4       2       0       1       0       2   1       4       2       0       1       0

the values in action columns represent number of times user took action on day. translate wide dataframe able extend time frame arbitrarily (say, 365 days).

i can reshape wide with:

df_indexed = df.set_index(['user_id', 'day']) df_wide = df_indexed.unstack().fillna()

how go adding remaining 358 days filled 0 each of 5 actions?

you can use multiindexed dataframe, create new index itertools.product combining users dataframe , days want, , replace index filling missing values 0.

import itertools  users = df.user_id.unique() df_indexed = df.set_index(['user_id', 'day']) index = pd.multiindex.from_tuples(list(itertools.product(users, range(365)))) reindexed = df_indexed.reindex(index, fill_value=0)

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