Adding an np.array as a column in a pandas.DataFrame

Question

I have a pandas data frame and a numpy nd array with one dimension. Effectively it is a list.

How do I add a new column to the DataFrame with the values from the array?

test['preds'] = preds gives SettingWithCopyWarning And a warning:

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

And when I try pd.DataFrame({test,preds}) I get TypeError: unhashable type: 'list'

What is your original df? if test is already a df then test['preds']=preds would work. — EdChum
– EdChum, Commented Jun 28, 2015 at 18:11
To answer the SettingWithCopyWarning you need to post your original DataFrame — firelynx
– firelynx, Commented Jun 30, 2015 at 12:48

DolphinGenomePyramids · Accepted Answer · 2015-06-28 18:14:20Z

10

Thanks to EdChum the problem was this

test= DataFrame(test)
test['preds']=preds

It works!

answered Jun 28, 2015 at 18:14

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1 Comment

I get this warning:

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

firelynx · Accepted Answer · 2015-06-29 08:25:41Z

0

This is not a pandas error, this error is because you are trying to instantiate a set with two lists.

{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.

That being said, handing pandas a set will not work for your desired result.

Handing pandas a dict however, will work, like this:

pd.DataFrame({"test":test,"preds":preds})

answered Jun 29, 2015 at 8:25

firelynx

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