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

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

Connecting to SpaceX Data

Connecting to SpaceX 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 SpaceX Profile on disk (e.g. C:\profiles\SpaceX.apip). Next, set the ProfileSettings connection property to the connection string for SpaceX (see below).

SpaceX API Profile Settings

No authentication is required to access SpaceX data — the SpaceX API is publicly available. Simply set the Profile connection property to the path of the SpaceX profile file.

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

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

engine = create_engine("api:///?Profile=C:\profiles\SpaceX.apip")

Execute SQL to SpaceX

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

df = pandas.read_sql("SELECT CapsuleSerial, CapsuleId FROM Capsules WHERE Status = 'active'", engine)

Visualize SpaceX Data

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

df.plot(kind="bar", x="CapsuleSerial", y="CapsuleId")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to SpaceX 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("api:///?Profile=C:\profiles\SpaceX.apip")
df = pandas.read_sql("SELECT CapsuleSerial, CapsuleId FROM Capsules WHERE Status = 'active'", engine)

df.plot(kind="bar", x="CapsuleSerial", y="CapsuleId")
plt.show()