Turn pandas dataframe into numpy values

Question

I have the following dataset:

df = pd.DataFrame([['Tree', 1], ['Tree, Hug']], columns=('Tag', 'ticketID'))

What I would like to do now I transform the tag category to a numpy array like this

df = df[['Tag']]
tags = df.values

This however gives me

[['Tree']
 ['Tree, Hug']]

While I am looking for

[['Tree']
 ['Tree', 'Hug']]

Any thoughts on how I can get this working?

greedy52 · Accepted Answer · 2017-01-31 17:18:01Z

1

>>> import pandas as pd
>>> df = pd.DataFrame([['Tree', 1], ['Tree, Hug']], columns=('Tag', 'ticketID'))
>>> [ x.split(', ') for row in df[['Tag']].values for x in row ]
[['Tree'], ['Tree', 'Hug']]

Be careful with the split call. Have to split ', ' here since original string has a space.

answered Jan 31, 2017 at 17:18

greedy52

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Ted Petrou · Accepted Answer · 2017-01-31 17:21:09Z

0

To keep everything in Pandas you can iterate over the Tag column with apply and convert with tolist

df.Tag.apply(lambda x: [s.strip() for s in x.split(',')]).tolist()

[['Tree'], ['Tree', 'Hug']]

answered Jan 31, 2017 at 17:21

Ted Petrou

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