pandas automatically create dataframe from list of series with column names

Question

I have a list of pandas series objects. I have a list of functions that generate them. How do I create a dataframe of the objects with the column names being the names of the functions that created the objects?

So, to create the regular dataframe, I've got:

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.

How would I preserve the same conciseness, and set the column names?

How do you generate the list of series objects? Because you could also ensure that there the series name is set to the function name, then this name will be used as column name after concatting. — joris
– joris, Commented Dec 12, 2015 at 15:24

Fabio Lamanna · Accepted Answer · 2015-12-12 15:23:01Z

2

IIUC, given your concat dataframe df you can:

df = pandas.concat([list of series objects],axis=1,join='inner')

and then assign the column names as a list of functions names:

df.columns = [functionA.__name__, functionB.__name__, etc.]

Hope that helps.

answered Dec 12, 2015 at 15:23

Fabio Lamanna

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Mike Müller · Accepted Answer · 2015-12-12 15:22:40Z

2

You can set the column names in a second step:

df = pandas.concat([list of series objects],axis=1,join='inner')
df.columns = [functionA.__name__, functionB.__name__]

answered Dec 12, 2015 at 15:22

Mike Müller

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