How to group a Series by values in pandas?

Question

I currently have a pandas Series with dtype Timestamp, and I want to group it by date (and have many rows with different times in each group).

Answer 1

Three methods:

DataFrame: pd.groupby(['column']).size()

Series： sel.groupby(sel).size()

Series to DataFrame:

pd.DataFrame( sel, columns=['column']).groupby(['column']).size()

Answer 2

You should convert it to a DataFrame, then add a column that is the date(). You can do groupby on the DataFrame with the date column.

df = pandas.DataFrame(s, columns=["datetime"])
df["date"] = df["datetime"].apply(lambda x: x.date())
df.groupby("date")

Then "date" becomes your index. You have to do it this way because the final grouped object needs an index so you can do things like select a group.

Answer 3

To add another suggestion, I often use the following as it uses simple logic:

pd.Series(index=s.values).groupby(level=0)

Answer 4

grouped = s.groupby(s)

Or:

grouped = s.groupby(lambda x: s[x])

Answer 5

For anyone else who wants to do this inline without throwing a lambda in (which tends to kill performance):

s.to_frame(0).groupby(0)[0]