![]() Read more on MySQL with SQLAlchemy connection. We will collect records from our sample student table in MySQL database and display as html using to_html().Ĭollect SQL dump of sample student table below. My_data.to_html('D:\my_student_file.html',index=False) Using SQLAlchemy Finally we will save them in an html file using to_html(). Read on how to connect to MySQL database and then collected the records of student table by using read_sql() to a DataFrame. We can use various other filters to manage the data and store in html file. My_data.to_html('my_file.html',index=False) Now let us store only two columns, class and name import pandas as pd For this we will use our test.csv file as we have more rows. We can filter the DataFrame and then save the rows in html file. How to handle if data is blank, we can use na_rep='*' my_data.to_html('D:\my_file.html',na_rep='*') Storing part of the data My_data.to_html('D:\data\my_file.html') na_rep Blank data ![]() We can remove index by using option index=False my_data.to_html('D:\my_html.html',index=False) Storing Path ![]() Errors should be errors, they shouldn't magically become print statements.Python Pandas html output from DataFrame
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