style object of DataFrame


Create the sample DataFrame from here.
By using lower() we will change the name column data to lower case.
df.style.format({'name':lambda x:x.lower()})
DataFrame style format
df.style.highlight_max(color='lightgreen')
DataFrame style max value
df.style.highlight_min(color='red')\
.highlight_max(color='lightgreen')
df.style.format({'name':lambda x:x.lower()})\
.background_gradient(cmap='Blues')
DataFrame style format

Highlighting the row based on condition

If the mark column is more than or equal to 60 then highlight the row with background colour. ( Note the *4 for number of columns )
def highlight(s):
    if s.mark >= 60: # change this condition 
        return ['background-color: yellow']*4
    else:
        return ['background-color: white']*4
df.style.apply(highlight, axis=1)
DataFrame style with conditions


Creating HTML table from DataFrame

DataFrame to HTML table
We will use set_table_styles() to add style property to our DataFrame and then we can display or create one html file ( my_html.html). Note that to display output we have to use our local setting. This code is tested in Google Colab.
import pandas as pd
import numpy as np
from IPython.core.display import display, HTML
my_dict={
	'NAME':['Ravi','Raju','Alex'],
	'ID':[1,2,3],'MATH':[30,40,50],
	'ENGLISH':[20,30,40]
	}
df= pd.DataFrame(data=my_dict)
my_styles = [
    {
       'selector': 'th',
       'props': [('background-color', 'blue'),
                 ('font-size',16),('style','bold'),
                 ('font-family','Segoe UI')]
   },{
       'selector':'td',
      'props':[('background-color', 'yellow'),
               ('font-size',12)]
   }
]
dfs = df.style.set_table_styles(my_styles)

html = dfs.hide_index().render() # get html 
#create one html file#
with open("my_html.html","w") as fp:
   fp.write(html)

html = dfs.hide_index().render()
#*to display in a jupyter notebook*
display(HTML(html))
Pandas Pandas DataFrame
contains() to display and delete row based on Conditions

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