Overview:
- A pandas DataFrame is a two-dimensional data container for processing voluminous data from various sources.
- DataFrame can store objects of various Python types.
- In Data Analytics it is a common requirement to publish final results such as a confusion matrix or a dashboard to an external format like excel, HTML, MySQL and others.
- The method to_html() of the DataFrame class, returns a HTML string that represents a DataFrame object as a HTML table.
Example:
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# Example Python program that exports a pandas DataFrame object # into a HTML table import pandas as pds
# A Python dictionary representing categories categories = {"A": [1512, 1245, 1234], "B": [1547, 1598, 1345], "C": [1676, 1436, 1452]};
# Dictionary loaded into a pandas DataFrame dataFrame = pds.DataFrame(data=categories);
# Emit the DataFrame as a HTML string html = dataFrame.to_html();
# Print the HTML print(html); |
Output:
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<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>A</th> <th>B</th> <th>C</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1512</td> <td>1547</td> <td>1676</td> </tr> <tr> <th>1</th> <td>1245</td> <td>1598</td> <td>1436</td> </tr> <tr> <th>2</th> <td>1234</td> <td>1345</td> <td>1452</td> </tr> </tbody> </table> |
Output as seen in an Internet browser:
