[英]pandas automatically create dataframe from list of series with column names
I have a list of pandas series objects. 我有一个熊猫系列对象列表。 I have a list of functions that generate them. 我列出了生成它们的函数。 How do I create a dataframe of the objects with the column names being the names of the functions that created the objects? 如何使用列名作为创建对象的函数的名称来创建对象的数据框?
So, to create the regular dataframe, I've got: 因此,要创建常规数据框,我需要:
pandas.concat([list of series objects],axis=1,join='inner')
But I don't currently have a way to insert all the functionA.__name__, functionB.__name__, etc.
as column names in the dataframe. 但是我目前functionA.__name__, functionB.__name__, etc.
无法将所有functionA.__name__, functionB.__name__, etc.
作为列名插入数据functionA.__name__, functionB.__name__, etc.
。
How would I preserve the same conciseness, and set the column names? 如何保持相同的简洁性并设置列名?
You can set the column names in a second step: 您可以在第二步中设置列名称:
df = pandas.concat([list of series objects],axis=1,join='inner')
df.columns = [functionA.__name__, functionB.__name__]
IIUC, given your concat
dataframe df
you can: IIUC,鉴于您的concat
数据框df
您可以:
df = pandas.concat([list of series objects],axis=1,join='inner')
and then assign the column names as a list of functions names: 然后将列名称分配为函数名称列表:
df.columns = [functionA.__name__, functionB.__name__, etc.]
Hope that helps. 希望能有所帮助。
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