comparing two pandas columns particular content and changing the color as per condition

I have a data frame as shown below.

summary_FR =pd.concat([Chip_Cur_Summary_funct_mode2,Noise_Summary_funct_mode2,VCM_Summary_funct_mode2,Sens_Summary_funct_mode2,Vbias_Summary_funct_mode2,vcm_delta_Summary_funct_mode2,THD_FUN_M2,F_LOW_FUNC_Summary_mode2,OSC_FUNC_Summary_mode2,FOSC_FUNC_Summary_mode2,VREF_CP_FUNC_Summary_mode2,Summary_PSRR_1KHz_funct_mode2,Summary_PSRR_20Hzto20KHz_funct_mode2])
summary_FR

cell_hover = {  # for row hover use <tr> instead of <td>
    'selector': 'td:hover',
    'props': [('background-color', '#ffffb3')]
}
index_names = {
    'selector': '.index_name',
    'props': 'font-style: italic; color: darkgrey; font-weight:normal;'
}
headers = {
    'selector': 'th:not(.index_name)',
    'props': 'background-color: #000066; color: white;'
}
summary_FR.style.set_table_styles([cell_hover, index_names, headers])

In the first row I need to compare SPEC_TYP with max. In the 2nd row I need to compare SPEC_MAX with max.In the 3rd row SPEC_TYP with max and in some other cases I need to compare SPEC_MIN with min ,SPEC_MAX with max and so on.

I searched in SO and google to see how can I do this but all the results I obtained show comparing two columns directly. This is not possible in my case .Because in my case some time I need to compare SPEC_TYP with max and in other cases SPEC_MAX with max and so on.

May I know how to approach this condition.

When I am adding more items I am getting an error ” unexpected indent”

def compare_to(row, what, to, prop=''):
    return np.where(row.index == to, prop if row[to] > row[what] else '', '')

summary_FR.style.apply(compare_to, what='SPEC_TYP', to='max', prop='background-color:red', axis=1, subset=(['Chip_Cur(uAmp)'],))
                .apply(compare_to, what='SPEC_MAX', to='max', prop='background-color:red', axis=1, subset=(['Noise[uVrms]'],))
                .apply(compare_to, what='SPEC_MAX', to='max', prop='background-color:red', axis=1, subset=(['Output_Common_Mode_Voltage[V]'],))

Answer

You can apply different styles to different subsets:

import pandas as pd
import numpy as np

df = pd.DataFrame({'SPEC_TYP': [1, 2, 3], 'SPEC_MAX': [2, 4, 6], 'max': [3, 5, 3]}, index=list('abc'))

def compare_to(row, what, to, prop=''):
    return np.where(row.index == to, prop if row[to] > row[what] else '', '')

df.style.apply(compare_to, what='SPEC_TYP', to='max', prop='background-color:tomato', axis=1, subset=(['a', 'c'],))
        .apply(compare_to, what='SPEC_MAX', to='max', prop='background-color:orange', axis=1, subset=(['b'],))

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Answer