将 DataFrameGroupBy 对象转换为 DataFrame pandas

Question

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.

Answer 1

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

Answer 2

 df_g.apply(lambda x: x) 

将返回原始数据帧。

Answer 3

Using pd.concat , just like this:

   pd.concat(map(lambda x: x[1], groups))

Or also keep index aligned:

   pd.concat(map(lambda x: x[1], groups)).sort_index()

Answer 4

You can output the results of the groupby with a .head('# of rows')to a variable.

Ex: df2 = grouped.head(100)

Now you have a Pandas data frame "df2" with all your grouped data.