Use Dash to Build to Web Apps on Excel Data



Create Python applications that use pandas and Dash to build Excel-connected web apps.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Microsoft Excel, the pandas module, and the Dash framework, you can build Excel-connected web applications for Excel data. This article shows how to connect to Excel with the CData Connector and use pandas and Dash to build a simple web app for visualizing Excel data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Excel data in Python. When you issue complex SQL queries from Excel, the driver pushes supported SQL operations, like filters and aggregations, directly to Excel and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Excel Data

Connecting to Excel data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

The ExcelFile, under the Authentication section, must be set to a valid Excel File.

After installing the CData Excel Connector, follow the procedure below to install the other required modules and start accessing Excel through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install pandas
pip install dash
pip install dash-daq

Visualize Excel Data in Python

Once the required modules and frameworks are installed, we are ready to build our web app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.excel as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData Excel Connector to create a connection for working with Excel data.

cnxn = mod.connect("Excel File='C:/MyExcelWorkbooks/SampleWorkbook.xlsx';")

Execute SQL to Excel

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT Name, Revenue FROM Sheet WHERE Name = 'Bob'", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-exceledataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our Excel data and configure the app layout.

trace = go.Bar(x=df.Name, y=df.Revenue, name='Name')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Excel Sheet Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
    app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the Excel data.

python excel-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Microsoft Excel to start building Python apps with connectivity to Excel data. Reach out to our Support Team if you have any questions.



Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.excel as mod
import plotly.graph_objs as go

cnxn = mod.connect("Excel File='C:/MyExcelWorkbooks/SampleWorkbook.xlsx';")

df = pd.read_sql("SELECT Name, Revenue FROM Sheet WHERE Name = 'Bob'", cnxn)
app_name = 'dash-exceldataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df.Name, y=df.Revenue, name='Name')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Excel Sheet Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
    app.run_server(debug=True)

Ready to get started?

Download a free trial of the Excel Connector to get started:

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Learn more:

Microsoft Excel Icon Microsoft Excel Python Connector

Python Connector Libraries for Microsoft Excel Data Connectivity. Integrate Microsoft Excel with popular Python tools like Pandas, SQLAlchemy, Dash & petl.