在 pandas.DataFrame 中添加一个 np.array 作为列
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Adding an np.array as a column in a pandas.DataFrame
提问by DolphinGenomePyramids
I have a pandas data frame and a numpy nd array with one dimension. Effectively it is a list.
我有一个Pandas数据框和一个一维的 numpy nd 数组。实际上它是一个列表。
How do I add a new column to the DataFrame with the values from the array?
如何使用数组中的值向 DataFrame 添加新列？
test['preds'] = predsgives SettingWithCopyWarningAnd a warning:
test['preds'] = preds给出SettingWithCopyWarning并警告：
A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead
试图在来自 DataFrame 的切片副本上设置值。尝试使用 .loc[row_indexer,col_indexer] = value 代替
And when I try pd.DataFrame({test,preds})I get TypeError: unhashable type: 'list'
当我尝试时，pd.DataFrame({test,preds})我得到TypeError: unhashable type: 'list'
回答by DolphinGenomePyramids
Thanks to EdChum the problem was this
感谢 EdChum 问题是这样的
test= DataFrame(test)
test['preds']=preds
It works!
有用！
回答by firelynx
This is not a pandas error, this error is because you are trying to instantiate a set with two lists.
这不是 Pandas 错误，这个错误是因为您试图用两个列表实例化一个集合。
{test,preds}
#TypeError: unhashable type: 'list'
A set is a container which needs all its content to be hashable, since sets may not contain the same element twice.
集合是一个容器，它需要它的所有内容都是可散列的，因为集合可能不会两次包含相同的元素。
That being said, handing pandas a set will not work for your desired result.
话虽这么说，给大Pandas一套不会为你想要的结果工作。
Handing pandas a dict however, will work, like this:
但是，将 dict 交给 pandas 会起作用，如下所示：
pd.DataFrame({"test":test,"preds":preds})
