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The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build VWO-connected Python applications and scripts for visualizing VWO data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to VWO data, execute queries, and visualize the results.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live VWO data in Python. When you issue complex SQL queries from VWO, the driver pushes supported SQL operations, like filters and aggregations, directly to VWO and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to VWO 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.
Start by setting the Profile connection property to the location of the VWO Profile on disk (e.g. C:\profiles\VWO.apip). Next, set the ProfileSettings connection property to the connection string for VWO (see below).
Generate your VWO API authentication token by visiting app.vwo.com/#/developers/tokens.
Follow the procedure below to install the required modules and start accessing VWO through Python objects.
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
You can now connect with a connection string. Use the create_engine function to create an Engine for working with VWO data.
engine = create_engine("api:///?Profile=C:\profiles\VWO.apip&ProfileSettings='APIKey=your_api_key'")
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 Enabled = 'true'", engine)
With the query results stored in a DataFrame, use the plot function to build a chart to display the VWO data. The show method displays the chart in a new window.
df.plot(kind="bar", x="Id", y="Name") plt.show()👁 VWO data in a Python plot (Salesforce is shown).
Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to VWO data. Reach out to our Support Team if you have any questions.
import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin
engine = create_engine("api:///?Profile=C:\profiles\VWO.apip&ProfileSettings='APIKey=your_api_key'")
df = pandas.read_sql("SELECT Id, Name FROM Accounts WHERE Enabled = 'true'", engine)
df.plot(kind="bar", x="Id", y="Name")
plt.show()
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