Use Dash to Build to Web Apps on Excel Data

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.

Connecting to Local or Cloud-Stored (Box, Google Drive, Amazon S3, SharePoint) Excel Files

CData Drivers let you work with Excel files stored locally and stored in cloud storage services like Box, Amazon S3, Google Drive, or SharePoint, right where they are.

Setting connection properties for local files

Set the URI property to local folder path.

Setting connection properties for files stored in Amazon S3

To connect to Excel file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended Excel files exist. In addition, at least set these properties:

• AWSAccessKey: AWS Access Key (username)
• AWSSecretKey: AWS Secret Key

Setting connection properties for files stored in Box

To connect to Excel file(s) within Box, set the URI property to the URI of the folder that includes the intended Excel file(s). Use the OAuth authentication method to connect to Box.

Dropbox

To connect to Excel file(s) within Dropbox, set the URI proprerty to the URI of the folder that includes the intended Excel file(s). Use the OAuth authentication method to connect to Dropbox. Either User Account or Service Account can be used to authenticate.

SharePoint Online (SOAP)

To connect to Excel file(s) within SharePoint with SOAP Schema, set the URI proprerty to the URI of the document library that includes the intended Excel file. Set User, Password, and StorageBaseURL.

SharePoint Online REST

To connect to Excel file(s) within SharePoint with REST Schema, set the URI proprerty to the URI of the document library that includes the intended Excel file. StorageBaseURL is optional. If not set, the driver will use the root drive. OAuth is used to authenticate.

Google Drive

To connect to Excel file(s) within Google Drive, set the URI property to the URI of the folder that includes the intended Excel file(s). Use the OAuth authentication method to connect and set InitiateOAuth to GETANDREFRESH.

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("URI='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("URI='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)