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

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

Connecting to Dropbox Data

Connecting to Dropbox 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.

Dropbox uses the OAuth authentication standard. To authenticate using OAuth, you can use the embedded credentials or register an app with Dropbox.

See the Getting Started guide in the CData driver documentation for more information.

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

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

engine = create_engine("dropbox:///?InitiateOAuth=GETANDREFRESH")

Execute SQL to Dropbox

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 Files WHERE Id = '1'", engine)

Visualize Dropbox Data

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

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Dropbox to start building Python apps and scripts with connectivity to Dropbox 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("dropbox:///?InitiateOAuth=GETANDREFRESH")
df = pandas.read_sql("SELECT Id, Name FROM Files WHERE Id = '1'", engine)

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