I had a dataframe and did a groupby in FIPS and summed the groups that worked fine.
kl = ks.groupby('FIPS') kl.aggregate(np.sum)
I just want a normal Dataframe back but I have a pandas.core.groupby.DataFrameGroupBy
object.
to_frame() function is used to convert the given series object to a dataframe. Parameter : name : The passed name should substitute for the series name (if it has one).
The Hello, World! of pandas GroupBygroupby() and pass the name of the column that you want to group on, which is "state" . Then, you use ["last_name"] to specify the columns on which you want to perform the actual aggregation. You can pass a lot more than just a single column name to . groupby() as the first argument.
The result of kl.aggregate(np.sum)
is a normal DataFrame, you just have to assign it to a variable to further use it. With some random data:
>>> df = DataFrame({'A' : ['foo', 'bar', 'foo', 'bar', >>> 'foo', 'bar', 'foo', 'foo'], ... 'B' : ['one', 'one', 'two', 'three', ... 'two', 'two', 'one', 'three'], ... 'C' : randn(8), 'D' : randn(8)}) >>> grouped = df.groupby('A') >>> grouped <pandas.core.groupby.DataFrameGroupBy object at 0x04E2F630> >>> test = grouped.aggregate(np.sum) >>> test C D A bar -1.852376 2.204224 foo -3.398196 -0.045082
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