Style a dataframe

DataFrame output in the notebook can be personalised with some CSS syntaxe applied to the style attribute.

Basic styling

Basic styling, color nan values in red, max values in blue for each Line and the min value in gold for each column.

# Import modules
import pandas as pd
# Example dataframe

raw_data  = {'fruit': ['Banana', 'Orange', 'Apple', 'lemon', "lime", "plum"], 
        'color': ['yellow', 'orange', 'red', 'yellow', "green", "purple"], 
        'kcal': [89, 47, 52, 15, 30, 28],
        'size_cm' : [20, 10, 9, 7, None, 4]
    }

df = pd.DataFrame(raw_data, columns = ['fruit', 'color', 'kcal', "size_cm"])
(df.style
.highlight_null('red')
.highlight_max(color='steelblue', axis=0)
.highlight_min(color='gold',axis=1)
)

	fruit	color	kcal	size_cm
0	Banana	yellow	89	20
1	Orange	orange	47	10
2	Apple	red	52	9
3	lemon	yellow	15	7
4	lime	green	30	nan
5	plum	purple	28	4

Gradient

Color the value of the dataframe with a color gradient based on the value of the cell

raw_data  = {'fruit': ['Banana', 'Orange', 'Apple', 'lemon', "lime", "plum"], 
        'color': ['yellow', 'orange', 'red', 'yellow', "green", "purple"], 
        'kcal': [89, 47, 52, 15, 30, 28],
        'size_cm' : [20, 10, 9, 7, 6, 4]
    }
df = pd.DataFrame(raw_data, columns = ['fruit', 'color', 'kcal', "size_cm"])

df.style.background_gradient()

	fruit	color	kcal	size_cm
0	Banana	yellow	89	20
1	Orange	orange	47	10
2	Apple	red	52	9
3	lemon	yellow	15	7
4	lime	green	30	6
5	plum	purple	28	4

Custom style

Create a custom style using CSS

def custom_style(val):
    if val < 5:
        return 'background-color:red'
    elif val > 50: 
        return 'background-color:green'
    elif abs(val) <20:
        return 'background-color:yellow'
    else:
        return ''

df[["kcal", 'size_cm']].style.applymap(custom_style)

	kcal	size_cm
0	89	20
1	47	10
2	52	9
3	15	7
4	30	6
5	28	4

Colorbars

Draw bars in the cell based on the value in the cell

(df.style
.bar(subset=['kcal','size_cm'],color='steelblue')
)

	fruit	color	kcal	size_cm
0	Banana	yellow	89	20
1	Orange	orange	47	10
2	Apple	red	52	9
3	lemon	yellow	15	7
4	lime	green	30	6
5	plum	purple	28	4

import numpy as np
df["random"] = np.random.rand(6)-0.5
(df.style
.bar(subset=['kcal', 'size_cm'],color='steelblue')
.bar(subset=['random'],color=['indianred','limegreen'], align='mid')
)

	fruit	color	kcal	size_cm	random
0	Banana	yellow	89	20	0.432301
1	Orange	orange	47	10	0.104051
2	Apple	red	52	9	0.107809
3	lemon	yellow	15	7	-0.281298
4	lime	green	30	6	-0.122744
5	plum	purple	28	4	0.452038