How to Visualize MYOB AccountRight Data in Python with pandas

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for MYOB AccountRight, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build MYOB AccountRight-connected Python applications and scripts for visualizing MYOB AccountRight data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to MYOB AccountRight data, execute queries, and visualize the results.

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

Connecting to MYOB AccountRight Data

Connecting to MYOB AccountRight 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.

These properties are required when connecting to a company file (both for Cloud and On-Premise instances).

• CompanyFileId: You can find this by starting MYOB, opening your data file, and selecting Help -> About MYOB
• User: The username associated with your company file.
• Password: The password associated with your company file.

Connecting to a Cloud Instance

To connect to a cloud instance of MYOB, you can use the embedded OAuth credentials or create an OAuth app with MYOB. This process is detailed in the Help documentation.

Connecting to an On-Premise instance:

When connecting to an on-premise instance, set the following connection property in addition to those above:

• InitiateOauth: Set this to OFF.
• Url: The Url of your MYOB instance.

Follow the procedure below to install the required modules and start accessing MYOB AccountRight through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize MYOB AccountRight Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with MYOB AccountRight data.

engine = create_engine("myob:///?OAuthClientId=YourClientId& OAuthClientSecret=YourClientSecret& CompanyFileId=yourCompanyFileId& CallbackURL=http://localhost:33333& User=companyFileUser& Password=companyFilePassword&InitiateOAuth=GETANDREFRESH")

Execute SQL to MYOB AccountRight

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

df = pandas.read_sql("SELECT Id, Name FROM Accounts WHERE Type = 'Bank'", engine)

Visualize MYOB AccountRight Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the MYOB AccountRight data. The show method displays the chart in a new window.

df.plot(kind="bar", x="Id", y="Name")
plt.show()

👁 MYOB AccountRight data in a Python plot (Salesforce is shown).

Free Trial & More Information

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

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Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("myob:///?OAuthClientId=YourClientId& OAuthClientSecret=YourClientSecret& CompanyFileId=yourCompanyFileId& CallbackURL=http://localhost:33333& User=companyFileUser& Password=companyFilePassword&InitiateOAuth=GETANDREFRESH")
df = pandas.read_sql("SELECT Id, Name FROM Accounts WHERE Type = 'Bank'", engine)

df.plot(kind="bar", x="Id", y="Name")
plt.show()