转换数据帧的 Pandas dtype
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Convert Pandas dtype of dataframe
提问by conr404
I have a Pandasdataframe which is stored as an 'object', but I need to change the dataframe structure to an 'int' as the 'object' dtype will not process in the kmeans()function of numpylibrary
我有一个存储为“对象”的Pandas数据帧，但我需要将数据帧结构更改为“int”，因为“对象”数据类型不会在numpy库的kmeans()函数中处理
I have managed to convert each column of the dataframe into an float64,based on this example Pandas: change data type of columnsbut I can't change the whole thing into anything else.
我已经设法将数据帧的每一列转换为 float64，基于这个示例Pandas：更改列的数据类型，但我无法将整个内容更改为其他任何内容。
#create subset of user variables
user.posts = user.posts.astype('int')
user.views = user.views.astype('int')
user.kudos = user.kudos.astype('int')
Y = user[['posts','views','kudos']]
#convert dataframe into float
X.convert_objects(convert_numeric=True).dtypes
Out[205]:
posts float64
views float64
kudos float64
dtype: object
This then causes issues when I try and run
当我尝试运行时，这会导致问题
K = range(1,10)
# scipy.cluster.vq.kmeans
KM = [kmeans(X,k) for k in K] # apply kmeans 1 to 10
I get the error
我收到错误
--->KM = [kmeans(X,k) for k in K] # apply kmeans 1 to 10
^
AttributeError: 'DataFrame' object has no attribute 'dtype'
What is the issue kmeans is having with either the K or X dataframe, and how can it be resolved? Thanks
kmeans 对 K 或 X 数据帧有什么问题，如何解决？谢谢
回答by conr404
save it just as the values, not the objects. per this post How to convert a pandas DataFrame subset of columns AND rows into a numpy array?
将它保存为值，而不是对象。根据这篇文章 如何将列和行的 Pandas DataFrame 子集转换为 numpy 数组？
user.posts = user.posts.astype('float')
user.views = user.views.astype('float')
user.kudos = user.kudos.astype('float')
Y = user[['posts','views','kudos']].values
