Concat the columns in Pandas Dataframe with separator

Question

I have a dataframe say df_dt_proc with 35 columns.

I want to add a column to the dataframe df_dt_proc['procedures'] which should have all the columns concatenated except column at index 0 separated by , .

I am able to achieve the result by the following script:

df_dt_proc['procedures'] = np.nan

_len = len(df_dt_proc.columns[1:-1])

for i in range(len(df_dt_proc)):
    res = ''

    for j in range(_len):
        try:
            res += df_dt_proc[j][i] + ', '
        except:
            break
    
    df_dt_proc['procedures'][i] = res

However, there must be a more pythonic way to achieve this.

jezrael · Accepted Answer · 2021-08-27 06:38:00Z

1

Use custom lambda function with remove NaN and Nones and converting to strings, for select all columns without first and last use DataFrame.iloc:

f = lambda x: ', '.join(x.dropna().astype(str))
df_dt_proc['procedures'] = df_dt_proc.iloc[:, 1:-1].agg(f, axis=1)

answered Aug 27, 2021 at 6:38

jezrael

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Comments

U13-Forward · Accepted Answer · 2021-08-27 06:32:53Z

0

Try this with agg:

df_dt_proc['procedures'] = df_dt_proc[df_dt_proc.columns[1:-1]].astype(str).agg(', '.join, axis=1)

edited Aug 27, 2021 at 6:32

answered Aug 27, 2021 at 6:27

U13-Forward

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3 Comments

gm-123 Over a year ago

This is working fine. What if we have blanks values in a few columns? I am getting error - expected str instance, float found.

U13-Forward Over a year ago

@gm-123 Edited my answer, please upvote and accept if it works

gm-123 Over a year ago

it appends nan for all the empty columns. Result looks like

'Atrial Septal Defect (ASD) Repair, Bentall Procedure, CABG - Redo, Cardiac Valve Replacement, Closed Heart Surgery, Coronary Artery Bypass Grafting (CABG), Heart Double Valve Replacement, Heart Port Surgery, Heart Transplant, VSD Closure / Repair (Adult), nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan'

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