Render Pandas DataFrame as HTML Table - Python Examples

Pandas - Render DataFrame as HTML Table

You can convert a Pandas DataFrame into an HTML table to represent it on web pages.

To render a Pandas DataFrame as an HTML Table, use the pandas.DataFrame.to_html() method.

The entire DataFrame is converted into a <table> HTML element, with column names wrapped in the <thead> (table head) element. Each row of the DataFrame is then represented as a <tr> (table row) in the HTML table.

Examples

1. Render DataFrame as HTML Table

In this example, we will initialize a DataFrame and render it into an HTML table.

Python Program

import pandas as pd

# Create DataFrame
df_marks = pd.DataFrame({'name': ['Somu', 'Kiku', 'Amol', 'Lini'],
     'physics': [68, 74, 77, 78],
     'chemistry': [84, 56, 73, 69],
     'algebra': [78, 88, 82, 87]})

# Render DataFrame as HTML
html = df_marks.to_html()
print(html)

Explanation:

  1. The DataFrame is created using a dictionary containing student names and their marks in various subjects.
  2. The to_html() method is called on the DataFrame, converting it into an HTML table.
  3. The resulting HTML table includes the column names as table headers and each row of data as a table row.

Output

<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>name</th>
      <th>physics</th>
      <th>chemistry</th>
      <th>algebra</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Somu</td>
      <td>68</td>
      <td>84</td>
      <td>78</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Kiku</td>
      <td>74</td>
      <td>56</td>
      <td>88</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Amol</td>
      <td>77</td>
      <td>73</td>
      <td>82</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Lini</td>
      <td>78</td>
      <td>69</td>
      <td>87</td>
    </tr>
  </tbody>
</table>

Let us now write the HTML data to a file using Python.

Python Program

import pandas as pd

#create dataframe
df_marks = pd.DataFrame({'name': ['Somu', 'Kiku', 'Amol', 'Lini'],
     'physics': [68, 74, 77, 78],
     'chemistry': [84, 56, 73, 69],
     'algebra': [78, 88, 82, 87]})

#render dataframe as html
html = df_marks.to_html()

#write html to file
with open("index.html", "w") as text_file:
    text_file.write(html)

This will create an index.html file in your working directory containing the HTML table. Open this file in a web browser to view the table.

2. Render DataFrame with Customizing Table Attributes

You can customize the appearance of the HTML table by passing additional parameters to the to_html() method, such as adding borders, aligning content, or using custom classes for styling.

Python Program

import pandas as pd

# Create DataFrame
df_marks = pd.DataFrame({'name': ['Somu', 'Kiku', 'Amol', 'Lini'],
     'physics': [68, 74, 77, 78],
     'chemistry': [84, 56, 73, 69],
     'algebra': [78, 88, 82, 87]})

# Render DataFrame as HTML with custom styles
html = df_marks.to_html(border=2, justify='center', classes='styled-table')

# Write HTML to file
with open('styled_table.html', 'w') as text_file:
    text_file.write(html)

Explanation:

  1. The border attribute adds a border around the table, the justify option centers the table, and the classes attribute adds a custom class for styling.
  2. This HTML table can now be styled using the specified class (e.g., in a CSS file or inline). This makes it more flexible for styling when integrated into a web page.

Output

<table border="2" class="styled-table">
  <thead>
    <tr style="text-align: center;">
      <th></th>
      <th>name</th>
      <th>physics</th>
      <th>chemistry</th>
      <th>algebra</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Somu</td>
      <td>68</td>
      <td>84</td>
      <td>78</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Kiku</td>
      <td>74</td>
      <td>56</td>
      <td>88</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Amol</td>
      <td>77</td>
      <td>73</td>
      <td>82</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Lini</td>
      <td>78</td>
      <td>69</td>
      <td>87</td>
    </tr>
  </tbody>
</table>

3. Render DataFrame with Missing Values

If your DataFrame contains missing values, NaN will be displayed in the table.

Python Program

import pandas as pd

# Create DataFrame with NaN values
df_marks = pd.DataFrame({'name': ['Somu', 'Kiku', 'Amol', 'Lini'],
     'physics': [68, 74, None, 78],
     'chemistry': [84, None, 73, 69],
     'algebra': [78, 88, None, 87]})

# Render DataFrame with NaN values
html = df_marks.to_html()

# Write HTML to file
with open('nan_table.html', 'w') as text_file:
    text_file.write(html)

Explanation:

  1. The DataFrame contains missing values, represented by None in Python, which will be shown as NaN in the HTML table.
  2. This is useful for displaying incomplete data or handling missing information in a dataset.

Output

<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>name</th>
      <th>physics</th>
      <th>chemistry</th>
      <th>algebra</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Somu</td>
      <td>68</td>
      <td>84</td>
      <td>78</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Kiku</td>
      <td>74</td>
      <td>NaN</td>
      <td>88</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Amol</td>
      <td>NaN</td>
      <td>73</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Lini</td>
      <td>78</td>
      <td>69</td>
      <td>87</td>
    </tr>
  </tbody>
</table>

Summary

In this tutorial, we have learned how to render a Pandas DataFrame as an HTML table using the to_html() method. We covered basic usage as well as advanced customizations like adding borders, aligning the table, and handling missing data.

For more examples, visit the Pandas Tutorial.



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