pandas DataFrameGroupBy 对象的计算模式时出错
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Error when computing mode of a DataFrameGroupBy object
提问by user2314737
I have a dataframe with a Datecolumn, I group the data by year and I can compute mean and median. But how to compute the mode? Here is the error I get:
我有一个带Date列的数据框，我按年份对数据进行分组，并且可以计算平均值和中位数。但是如何计算模式呢？这是我得到的错误：
>>> np.random.seed(0)
>>> rng = pd.date_range('2010-01-01', periods=10, freq='2M')
>>> df = pd.DataFrame({ 'Date': rng, 'Val': np.random.random_integers(0,100,size=10) })
>>> df
Date Val
0 2010-01-31 44
1 2010-03-31 47
2 2010-05-31 64
3 2010-07-31 67
4 2010-09-30 67
5 2010-11-30 9
6 2011-01-31 83
7 2011-03-31 21
8 2011-05-31 36
9 2011-07-31 87
>>> df.groupby(pd.Grouper(key='Date',freq='A')).mean()
Val
Date
2010-12-31 49.666667
2011-12-31 56.750000
>>> df.groupby(pd.Grouper(key='Date',freq='A')).median()
Val
Date
2010-12-31 55.5
2011-12-31 59.5
>>> df.groupby(pd.Grouper(key='Date',freq='A')).mode()
Traceback (most recent call last):
File "<pyshell#109>", line 1, in <module>
df.groupby(pd.Grouper(key='Date',freq='A')).mode()
File "C:\Python27\lib\site-packages\pandas\core\groupby.py", line 554, in __getattr__
return self._make_wrapper(attr)
File "C:\Python27\lib\site-packages\pandas\core\groupby.py", line 571, in _make_wrapper
raise AttributeError(msg)
AttributeError: Cannot access callable attribute 'mode' of 'DataFrameGroupBy' objects, try using the 'apply' method
采纳答案by piRSquared
- use
np.uniquewith thereturn_countsparameter. - use the
argmaxon the counts array to get value from unique array. - use
np.apply_along_axisfor a custom functionmode
np.unique与return_counts参数一起使用。- 使用
argmaxcounts 数组从唯一数组中获取值。 - 使用
np.apply_along_axis自定义功能mode
def mode(a):
u, c = np.unique(a, return_counts=True)
return u[c.argmax()]
df.groupby(pd.Grouper(key='Date',freq='A')).Val.apply(mode)
Date
2010-12-31 67
2011-12-31 21
Freq: A-DEC, Name: Val, dtype: int64
回答by 3novak
modeisn't a built in function that's automatically compatible with pandas groupby objects. You could use the scipy.statsmodule. This feels a little clunky, though.
mode不是自动与 Pandas groupby 对象兼容的内置函数。您可以使用该scipy.stats模块。不过，这感觉有点笨拙。
from scipy import stats
df.groupby(pd.Grouper(key='Date',freq='A')).apply(stats.mode)
Alternatively, you could use the value_counts()function and take the first index value returned. This is the route I would go.
或者，您可以使用该value_counts()函数并获取返回的第一个索引值。这是我要走的路线。
df.groupby(pd.Grouper(key='Date', freq='A')).value_counts()[0].index.values[0]
回答by Vaid?tas Iv??ka
modeis problematic as others have mentioned, however a DataFrameGroupby object can be applied a trivial lambda function, just as the AttributeError suggests using (and contains no ugly slicing or anything else):
模式是有问题的，正如其他人所提到的，但是 DataFrameGroupby 对象可以应用一个简单的 lambda 函数，就像 AttributeError 建议使用的那样（并且不包含丑陋的切片或其他任何东西）：
df.groupby(grouping_column)[[i for i in pivotable_columns]].apply(lambda x: x.mode())]
