Append column and default data into new Pandas DataFrame

Question

I want to append data from column and a default phrase at the same time into a Pandas DataFrame, db has many columns, not only id_sin & extra...

I tried this:

import pandas as pd
db = pd.DataFrame({'id_sin':['s123','s124','s125','s126'],
                   'extra':['abc','def','ghi','jkl'],
                   ...
})
df = pd.DataFrame(columns=['id_sin','phrase'])
df = df.append([db['id_sin'],['default phrase']*len(db)])

This is the expected result:

>>> df
  id_sin          phrase
0   s123  default phrase
1   s124  default phrase
2   s125  default phrase
3   s126  default phrase

But I am getting an error, please help... thanks in advance!

I need to take the column and append it with the default phrase... please help! — Soufiane Sabiri
– Soufiane Sabiri, Commented Apr 15, 2019 at 17:29
Just to clarify, You have a DataFrame (db) with many columns and what you would like is to create another DataFrame with a subset of the original columns (in this case just 'id_sin') and another column called phrase which takes on a static value for all rows? If so, you want: df = db[['id_sin']].assign(phrase='default phrase'). Otherwise please try to explain the problem more clearly. — ALollz
– ALollz, Commented Apr 15, 2019 at 17:40

vb_rises · Accepted Answer · 2019-04-15 18:53:36Z

1

You can create a copy of existing DataFrame and then add new column to it.

import pandas as pd
db = pd.DataFrame({'id_sin':['s123','s124','s125','s126'],
               'extra':['abc','def','ghi','jkl'],
               ...
})

df = pd.DataFrame()
df['id_sin'] = db[['id_sin']]
df['Phrase'] = 'Default Phrase'

edited Apr 15, 2019 at 18:53

answered Apr 15, 2019 at 17:42

vb_rises

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