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pythonpandaspandas-styles

Applying style to values of only one column in dataframe

I want apply some filter conditions on specific cols. Based on filter I want to highlight that cell.

I took this example from another post:

styled = (df.style
            .applymap(lambda v: 'background-color: %s' % 'green' if v=='col' else ''))
styled.to_excel('d:/temp/styled.xlsx', engine='openpyxl')

But problem with this is it applies to every cell. So I instead used apply function on a series by converting it to df like below:

df['a'] =df[['a']].style
            .apply(lambda v: 'background-color: %s' % 'green' if v=='col' else '')

In this case when I export df to excel it gives style object rather than values.

If I dont assign that styled result to df['a'] and directly convert to excel then I get desired result with style but then i will get only that column and not entire dataframe

Solution

  • Use subset parameter for specify column(s) for apply styles:

    f = lambda v: 'background-color: %s' % 'green' if v=='col' else ''
df = df.style.applymap(f, subset=['a'])

    For negation use Index.difference:

    df = df.style.applymap(f, subset=df.columns.difference(['a']))