[英]failing simple groupby example from “Python for Data Analysis” text
I just started learning python (mostly as open source replacement for matlab using "ipython --pylab" ), going through the examples from the "Python for Data Analysis" text. 我刚刚开始学习python(主要是使用“ipython --pylab”作为matlab的开源替换),通过“Python for Data Analysis”文本中的示例。 On page 253, a simple example is shown using 'groupby' (passing a list of arrays). 在页253,使用'groupby'(传递数组列表)显示一个简单的示例。 I repeat it exactly as in the text, but I get this error: "TypeError: 'Series' objects are mutable, thus they cannot be hashed" 我在文本中完全重复它,但是我得到了这个错误:“TypeError:'Series'对象是可变的,因此它们不能被散列”
import pandas as pd
from pandas import DataFrame
df = DataFrame({'key1' : ['a','a','b','b','a'],'key2' : ['one','two','one','two\
','one'],'data1' : np.random.randn(5),'data2' : np.random.randn(5)})
grouped = df['data1'].groupby(df['key1'])
means = df['data1'].groupby(df['key1'],df['key2']).mean()
-----DETAILS OF TYPEERROR------- ----- TYPEERROR的详细信息-------
TypeError Traceback (most recent call last)
<ipython-input-7-0412f2897849> in <module>()
----> 1 means = df['data1'].groupby(df['key1'],df['key2']).mean()
/home/joeblow/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/core/generic.pyc in groupby(self, by, axis, level, as_index, sort, group_keys, squeeze)
2725
2726 from pandas.core.groupby import groupby
-> 2727 axis = self._get_axis_number(axis)
2728 return groupby(self, by, axis=axis, level=level, as_index=as_index,
2729 sort=sort, group_keys=group_keys, squeeze=squeeze)
/home/joeblow/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/core/generic.pyc in _get_axis_number(self, axis)
283
284 def _get_axis_number(self, axis):
--> 285 axis = self._AXIS_ALIASES.get(axis, axis)
286 if com.is_integer(axis):
287 if axis in self._AXIS_NAMES:
/home/joeblow/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/core/generic.pyc in __hash__(self)
639 def __hash__(self):
640 raise TypeError('{0!r} objects are mutable, thus they cannot be'
--> 641 ' hashed'.format(self.__class__.__name__))
642
643 def __iter__(self):
TypeError: 'Series' objects are mutable, thus they cannot be hashed
What simple thing am I missing here? 我在这里错过了什么简单的事情?
You didn't do it exactly as in the text. 你没有完全像在文本中那样做。 :^) :^)
>>> means = df['data1'].groupby([df['key1'],df['key2']]).mean()
>>> means
key1 key2
a one 1.127536
two 1.220386
b one 0.402765
two -0.058255
dtype: float64
If you're grouping by two arrays, you need to pass a list of the arrays. 如果要按两个数组进行分组,则需要传递一个数组列表。 You instead passed two arguments: (df['key1'],df['key2'])
, which are being interpreted as by
and axis
. 您改为传递两个参数: (df['key1'],df['key2'])
,它们被解释为by
和axis
。
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