How to style the rows of a multiindex dataframe?-CodePudding

I have the following dataframe:

dic = {'US':{'Traffic':{'new':1415, 'repeat':670}, 'Sales':{'new':67068, 'repeat':105677}},
      'UK': {'Traffic':{'new':230, 'repeat':156}, 'Sales':{'new':4568, 'repeat':10738}}}
d1 = defaultdict(dict)
for k, v in dic.items():
    for k1, v1 in v.items():
        for k2, v2 in v1.items():
            d1[(k, k2)].update({k1: v2})


df.insert(loc=2, column=' ', value=None)
df.insert(loc=0, column='Mode', value='Website')
df.columns = df.columns.rename("Metric", level=1)

It looks like:

I need help with applying the font and background color using the conditions in the following functions, to the traffic and sales row of the data frame:

def sales_color(val):
    font_color = ''
    background_color = ''
    
    if val <= 10000:
        font_color = 'red'
        background_color = 'light red'
    elif val >= 100000:
        font_color = 'green'
    else:
        font_color = 'grey'
        
    return [font_color, background_color]

def traffic_color(val):
    font_color = 'orange' if val < 300 else 'black'
    background_color = 'light orange' if val < 300 else ''
    return [font_color, background_color]

I was trying an inefficient way - applying the colors individually to the cell, but that is not working:

df['US']['new']['Sales'].style.apply(sales_color)
df['US']['new']['Traffic'].style.apply(traffic_color)
df['US']['Repeat']['Sales'].style.apply(sales_color)
df['US']['Repeat']['Traffic'].style.apply(traffic_color)

df['UK']['new']['Sales'].style.apply(sales_color)
df['UK']['new']['Traffic'].style.apply(traffic_color)
df['UK']['Repeat']['Sales'].style.apply(sales_color)
df['UK']['Repeat']['Traffic'].style.apply(traffic_color)

CodePudding user response：

Use custom function with select by DataFrame.loc, then set values by conditions by numpy.where and numpy.select.

For me not working light red and light orange color, I use colors hex codes instead:

def color(x):

    idx = pd.IndexSlice

    t = x.loc['Traffic', idx[:, ['new','repeat']]]
    s = x.loc['Sales', idx[:, ['new','repeat']]]
    
    df1 = pd.DataFrame('', index=x.index, columns=x.columns)
    
    s1 = np.select([s <= 10000, s >= 100000],  ['background-color: #fa8072; color: red',
                                                 'color: green'], 
                                              default='color: grey')
    t1 = np.where(t <= 300, 'background-color: #ffcc99; color: orange',
                                                       'color: black')
    df1.loc['Sales', idx[:, ['new','repeat']]] = s1
    df1.loc['Traffic', idx[:, ['new','repeat']]] = t1
                                                      
    return df1

df.style.apply(color, axis=None)