Create A New DataFrame Based on Conditions of Multiple DataFrames

Question

I have two datasets: one with cancer positive patients (df_pos), and the other with the cancer negative patients (df_neg).

df_pos

df_neg

I want to compile these datasets into one with an extra column if the patient has cancer or not (yes or no).

Here is my desired outcome:

    id  outcome
0   123 yes
1   124 yes
2   125 yes
3   234 no
4   235 no
5   236 no

What would be a smarter approach to compile these?

Any suggestions would be appreciated. Thanks!

Sayandip Dutta · Accepted Answer · 2021-01-29 19:17:59Z

3

Use pandas.DataFrame.append and pandas.DataFrame.assign:

>>> df_pos.assign(outcome='Yes').append(df_neg.assign(outcome='No'), ignore_index=True)
    id outcome
0  123     Yes
1  124     Yes
2  125     Yes
3  234      No
4  235      No
5  236      No

answered Jan 29, 2021 at 19:17

Sayandip Dutta

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1 Comment

Roy Over a year ago

That's perfect, @Sayandip. Thanks!

simon · Accepted Answer · 2021-01-29 19:25:10Z

2

df_pos['outcome'] = True
df_neg['outcome'] = False

df = pd.concat([df_pos, df_neg]).reset_index(drop=True)

answered Jan 29, 2021 at 19:25

simon

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