How to highlight a row in Pandas Data frame in Python

In this tutorial, we are going to learn how to highlight a row in Pandas Dataframe in Python. To achieve this, we use apply() function of the Styler class.

Styler.apply() function

Syntax:

Styler.apply(func,axis=0,subset=None,**kwargs)

Parameters:

• func: func should take a Series if axis in [0,1] and return a list-like object of same length, or a Series, not necessarily of same length, with valid index labels considering subset. func should take a DataFrame if axis is None and return either an ndarray with the same shape or a DataFrame not necessarily of the same shape, with valid index and columns labels considering subset.
• axis: It applies to each column if the value is 0 or ‘index’, to each row if the value is 1 or ‘columns’ or to the entire Dataframe if given ‘None’. The default value is 0.
• subset: It is an optional parameter used to limit data to before applying the function.
• **kwargs: dict which is passed along to the function.

Returns: Styler

Let’s go through some examples,

Example 1:

import pandas as pd
data = pd.DataFrame({"A" : [ 5, 23, 56, 7, 8],
                "B" : [ 2, 43, 52, 68, 6],
                "C" : [ 41, 5, 7, 2, 32],
                "D" : [ 14, 3, 16, 2, 36],
                "E" : [ 45, 23, 66, 32, 23]})

print("Original DataFrame :")
display(data)
def highlight_rows(x):
    if x.E>40:
        return['background-color: pink']*5
    else:
        return['background-color: blue']*5
print("Highlighted DataFrame :")
display(data.style.apply(highlight_rows, axis = 1))

Output:

In the above example, we are highlighting the rows which have the value of column ‘E’ greater than 40. To do so, we are writing a function that returns background-color multiplied by 5, as there are five columns in the data frame. This function is passed to the apply function of the styler class.

Example 2:

import pandas as pd
dt = pd.DataFrame({"Roll_number" : [ 23, 5, 14, 37],
                "Name" : ["Sara","Mukesh","Naina","Anand"],
                   "Score":[ 35, 46, 52, 37]})
print("Original DataFrame :")
display(dt)
def highlight_rows(x):
    if x.Roll_number>20 and x.Score<40:
        return['background-color: red']*3
    else:
        return['background-color: yellow']*3
print("Highlighted DataFrame :")
display(dt.style.apply(highlight_rows, axis = 1))

Output:

In this example, we are taking multiple conditions for highlighting a row. They all can be written in a single line using ‘and’ keyword. Since we need to color the whole row, we are going to multiply the return statement by 3.

You may also learn,

• Python program to find duplicate rows in a binary matrix
• Get values of all rows in a particular column in openpyxl in Python