df ['X'].unique()和TypeError:无法散列的类型:'numpy.ndarray' [英] df ['X'].unique() and TypeError: unhashable type: 'numpy.ndarray'

问题描述

全部

我在数据框中有一个看起来像这样的列:

I have a column in a dataframe that looks like this:

allHoldingsFund['BrokerMixed']
Out[419]: 
78         ML
81       CITI
92         ML
173      CITI
235        ML
262        ML
264        ML
25617      GS
25621    CITI
25644    CITI
25723      GS
25778    CITI
25786    CITI
25793      GS
25797    CITI
Name: BrokerMixed, Length: 2554, dtype: object

尽管该列是一个对象.我无法按该列分组，甚至无法提取该列的唯一值.例如，当我这样做时:

Although the column is an object. I am not able to group by that column or even extract the unique values of that column. For example when I do:

allHoldingsFund['BrokerMixed'].unique()

我得到一个错误

     uniques = table.unique(values)
  File "pandas/_libs/hashtable_class_helper.pxi", line 1340, in pandas._libs.hashtable.PyObjectHashTable.unique
TypeError: unhashable type: 'numpy.ndarray'

分组时也会出现错误.

欢迎任何帮助.谢谢

推荐答案

首先，我建议您检查一下column中的type.您可以尝试如下

First I would suggest you to check what's type of your column. You may try as follows

print (type(allHoldingsFund['BrokerMixed']))

如果这是dataframe series，则可以尝试

allHoldingsFund['BrokerMixed'].reset_index()['BrokerMixed'].unique()

，然后检查它是否适合您.

and check if this works for you.

EDIT 2020:获得唯一和提及的答案的方法使用Python 3获取相同的结果

EDIT 2020 : Your way to get unique and mentioned answers fetch same results using Python 3

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