How to Visualize Microsoft Project 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 MS Project, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Microsoft Project-connected Python applications and scripts for visualizing Microsoft Project data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Microsoft Project data, execute queries, and visualize the results.

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

Connecting to Microsoft Project Data

Connecting to Microsoft Project 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 User and Password properties, under the Authentication section, must be set to valid Microsoft Project user credentials. In addition, you will need to specify a URL to a valid Microsoft Project server organization root or Microsoft Project services file.

Follow the procedure below to install the required modules and start accessing Microsoft Project 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 Microsoft Project Data in Python

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

engine = create_engine("microsoftproject:///?User=myuseraccount&Password=mypassword&URL=http://myserver/myOrgRoot")

Execute SQL to Microsoft Project

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

df = pandas.read_sql("SELECT ProjectName, ProjectActualCost FROM Projects WHERE ProjectName = 'Tax Checker'", engine)

Visualize Microsoft Project Data

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

df.plot(kind="bar", x="ProjectName", y="ProjectActualCost")
plt.show()

Free Trial & More Information

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

Full Source Code

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

engine = create_engine("microsoftproject:///?User=myuseraccount&Password=mypassword&URL=http://myserver/myOrgRoot")
df = pandas.read_sql("SELECT ProjectName, ProjectActualCost FROM Projects WHERE ProjectName = 'Tax Checker'", engine)

df.plot(kind="bar", x="ProjectName", y="ProjectActualCost")
plt.show()