An elegant way to update select cells based with column name

Use pd.where to mask correct values and then replace what you do not need using columns converted to series

df.where(df != '✓', df.columns.to_series(), axis=1)

Outcome

    Name  A  B  D
0  Stud1  A  C  D
1  Stud2  A  B  D
2  Stud3  B  B  A
3  Stud4  C  B  C

Convert columns names to pd.Series to use as a mapper and use replace to replace each tick mark '✓' with its corresponding column name:

df = df.replace('✓', pd.Series(df.columns, df.columns))

Example: For DataFrame df:

    Name  A  B  D
0  Stud1  ✓  C  ✓
1  Stud2  ✓  ✓  ✓
2  Stud3  B  ✓  A
3  Stud4  C  ✓  C

the above code produces:

    Name  A  B  D
0  Stud1  A  C  D
1  Stud2  A  B  D
2  Stud3  B  B  A
3  Stud4  C  B  C

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