Apply CSS class to Pandas DataFrame using to_html
Essentially, the pandas.to_html() just exports a plain HTML table. You can insert the table wherever you want in the body and control the style via CSS in the style section.
<html>
<head>
<style>
table, th, td {{font-size:10pt; border:1px solid black; border-collapse:collapse; text-align:left;}}
th, td {{padding: 5px;}}
</style>
</head>
<body>
{
pandas.to_html()
}
</body>
</html>
Pandas' to_html simply outputs a large string containing HTML table markup. The classes argument is a convenience handler to give the <table> a class attribute that will be referenced in a previously created CSS document that styles it. Therefore, incorporate to_html into a wider HTML document build that references an external CSS.
Interestingly, to_html adds dual classes <table class="dataframe mystyle"> which can be referenced in CSS individually, .dataframe {...} .mystyle{...}, or together .dataframe.mystyle {...}. Below demonstrates with random data.
Data
import pandas as pd
import numpy as np
pd.set_option('display.width', 1000)
pd.set_option('colheader_justify', 'center')
np.random.seed(6182018)
demo_df = pd.DataFrame({'date': np.random.choice(pd.date_range('2018-01-01', '2018-06-18', freq='D'), 50),
'analysis_tool': np.random.choice(['pandas', 'r', 'julia', 'sas', 'stata', 'spss'],50),
'database': np.random.choice(['postgres', 'mysql', 'sqlite', 'oracle', 'sql server', 'db2'],50),
'os': np.random.choice(['windows 10', 'ubuntu', 'mac os', 'android', 'ios', 'windows 7', 'debian'],50),
'num1': np.random.randn(50)*100,
'num2': np.random.uniform(0,1,50),
'num3': np.random.randint(100, size=50),
'bool': np.random.choice([True, False], 50)
},
columns=['date', 'analysis_tool', 'num1', 'database', 'num2', 'os', 'num3', 'bool']
)
print(demo_df.head(10))
# date analysis_tool num1 database num2 os num3 bool
# 0 2018-04-21 pandas 153.474246 mysql 0.658533 ios 74 True
# 1 2018-04-13 sas 199.461669 sqlite 0.656985 windows 7 11 False
# 2 2018-06-09 stata 12.918608 oracle 0.495707 android 25 False
# 3 2018-04-24 spss 88.562111 sql server 0.113580 windows 7 42 False
# 4 2018-05-05 spss 110.231277 oracle 0.660977 windows 10 76 True
# 5 2018-04-05 sas -68.140295 sql server 0.346894 windows 10 0 True
# 6 2018-05-07 julia 12.874660 postgres 0.195217 ios 79 True
# 7 2018-01-22 r 189.410928 mysql 0.234815 windows 10 56 False
# 8 2018-01-12 pandas -111.412564 sql server 0.580253 debian 30 False
# 9 2018-04-12 r 38.963967 postgres 0.266604 windows 7 46 False
CSS (save as df_style.css)
/* includes alternating gray and white with on-hover color */
.mystyle {
font-size: 11pt;
font-family: Arial;
border-collapse: collapse;
border: 1px solid silver;
}
.mystyle td, th {
padding: 5px;
}
.mystyle tr:nth-child(even) {
background: #E0E0E0;
}
.mystyle tr:hover {
background: silver;
cursor: pointer;
}
Pandas
pd.set_option('colheader_justify', 'center') # FOR TABLE <th>
html_string = '''
<html>
<head><title>HTML Pandas Dataframe with CSS</title></head>
<link rel="stylesheet" type="text/css" href="df_style.css"/>
<body>
{table}
</body>
</html>.
'''
# OUTPUT AN HTML FILE
with open('myhtml.html', 'w') as f:
f.write(html_string.format(table=demo_df.to_html(classes='mystyle')))
OUTPUT
HTML (references df_style.css, assumed in same directory; see class argument in table)
<html>
<head><title>HTML Pandas Dataframe with CSS</title></head>
<link rel="stylesheet" type="text/css" href="df_style.css"/>
<body>
<table border="1" class="dataframe mystyle">
<thead>
<tr style="text-align: center;">
<th></th>
<th>date</th>
<th>analysis_tool</th>
<th>num1</th>
<th>database</th>
<th>num2</th>
<th>os</th>
<th>num3</th>
<th>bool</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2018-04-21</td>
<td>pandas</td>
<td>153.474246</td>
<td>mysql</td>
<td>0.658533</td>
<td>ios</td>
<td>74</td>
<td>True</td>
</tr>
<tr>
<th>1</th>
<td>2018-04-13</td>
<td>sas</td>
<td>199.461669</td>
<td>sqlite</td>
<td>0.656985</td>
<td>windows 7</td>
<td>11</td>
<td>False</td>
</tr>
<tr>
<th>2</th>
<td>2018-06-09</td>
<td>stata</td>
<td>12.918608</td>
<td>oracle</td>
<td>0.495707</td>
<td>android</td>
<td>25</td>
<td>False</td>
</tr>
<tr>
<th>3</th>
<td>2018-04-24</td>
<td>spss</td>
<td>88.562111</td>
<td>sql server</td>
<td>0.113580</td>
<td>windows 7</td>
<td>42</td>
<td>False</td>
</tr>
<tr>
<th>4</th>
<td>2018-05-05</td>
<td>spss</td>
<td>110.231277</td>
<td>oracle</td>
<td>0.660977</td>
<td>windows 10</td>
<td>76</td>
<td>True</td>
</tr>
...
</tbody>
</table>
</body>
</html>
