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I have a huge pandas dataframe I am converting to html table i.e. dataframe.to_html(), its about 1000 rows. Any easy way to use pagination so that I dont have to scroll the whole 1000 rows. Say, view the first 50 rows then click next to see subsequent 50 rows?
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To get the nth row in a Pandas DataFrame, we can use the iloc() method. For example, df. iloc[4] will return the 5th row because row numbers start from 0.
You can use len(df. index) to find the number of rows in pandas DataFrame, df. index returns RangeIndex(start=0, stop=8, step=1) and use it on len() to get the count.
The to_string() function is used to render a DataFrame to a console-friendly tabular output. Buffer to write to. The subset of columns to write. Writes all columns by default.
iterrows() function in Python. Pandas DataFrame. iterrows() is used to iterate over a pandas Data frame rows in the form of (index, series) pair. This function iterates over the data frame column, it will return a tuple with the column name and content in form of series.
The best solution I can think of involves a couple of external JS libraries: JQuery and its DataTables plugin. This will allow for much more than pagination, with very little effort.
Let's set up some HTML, JS and python:
from tempfile import NamedTemporaryFile
import webbrowser
base_html = """
<!doctype html>
<html><head>
<meta http-equiv="Content-type" content="text/html; charset=utf-8">
<script type="text/javascript" src="https://ajax.googleapis.com/ajax/libs/jquery/2.2.2/jquery.min.js"></script>
<link rel="stylesheet" type="text/css" href="https://cdn.datatables.net/1.10.16/css/jquery.dataTables.css">
<script type="text/javascript" src="https://cdn.datatables.net/1.10.16/js/jquery.dataTables.js"></script>
</head><body>%s<script type="text/javascript">$(document).ready(function(){$('table').DataTable({
"pageLength": 50
});});</script>
</body></html>
"""
def df_html(df):
"""HTML table with pagination and other goodies"""
df_html = df.to_html()
return base_html % df_html
def df_window(df):
"""Open dataframe in browser window using a temporary file"""
with NamedTemporaryFile(delete=False, suffix='.html') as f:
f.write(df_html(df))
webbrowser.open(f.name)
And now we can load a sample dataset to test it:
from sklearn.datasets import load_iris
import pandas as pd
iris = load_iris()
df = pd.DataFrame(iris.data, columns=iris.feature_names)
df_window(df)
The beautiful result:
A few notes:
pageLength parameter in the base_html string. This is where I defined the default number of rows per page. You can find other optional parameters in the DataTable options page.df_window function was tested in a Jupyter Notebook, but should work in plain python as well.df_window and simply write the returned value from df_html into an HTML file.Edit: how to make this work with a remote session (e.g. Colab)
When working on a remote notebook, like in Colab or Kaggle the temporary file approach won't work, since the file is saved on the remote machine and not accessible by your browser. A workaround for that would be to download the constructed HTML and open it locally (adding to the previous code):
import base64
from IPython.core.display import display, HTML
my_html = df_html(df)
my_html_base64 = base64.b64encode(my_html.encode()).decode('utf-8')
display(HTML(f'<a download href="data:text/html;base64,{my_html_base64}" target="_blank">Download HTML</a>'))
This will result in a link containing the entire HTML encoded as a base64 string. Clicking it will download the HTML file and you can then open it directly and view the table.
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