Creating a separate column from the string values from another column in Python

Question

I have a dataframe called df that looks like this:

Provider	fid	pid	datetime	score	system
CHE-229	2bfc9a62	2f43d557	2021-09-26	-3.0	SOFA
CHE-229	78d5d845	88c59d92	2021-09-12	-4.0	SAPS

I would like to create a new column specific to the values from system. e.g. I want to create a new column called SOFA and another column called SAPS with their respective scores in their table.

The output I want is:

Provider	fid	pid	datetime	SOFA	SAPS
CHE-229	2bfc9a62	2f43d557	2021-09-26	-3.0
CHE-229	78d5d845	88c59d92	2021-09-12		-4.0

martineau · Accepted Answer · 2022-04-27 20:24:38Z

1

You can get this with an iterative procedure using numpy.where() to choose the value depending on a condition, and then dropping the original columns:

for sys in df["system"].unique():
    df[sys] = np.where(df["system"] == sys, df["score"], None)
df = df.drop(columns=["system", "score"])

edited Apr 27, 2022 at 20:24

martineau

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answered Apr 27, 2022 at 20:04

mattiatantardini

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Onyambu · Accepted Answer · 2022-04-27 21:05:21Z

0

df.pivot(df.columns[:-2], 'system', 'score').fillna('').reset_index()

system Provider       fid       pid    datetime SAPS SOFA
0       CHE-229  2bfc9a62  2f43d557  2021-09-26      -3.0
1       CHE-229  78d5d845  88c59d92  2021-09-12 -4.0

If you want them as numeric, then you can remove the fillna() part or even fill the nan with 0. ie .fillna(0)

answered Apr 27, 2022 at 21:05

Onyambu

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