How to Visualize NASA 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 NASA-connected Python applications and scripts for visualizing NASA data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to NASA data, execute queries, and visualize the results.

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

Connecting to NASA Data

Connecting to NASA 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.

Using API Key Authentication

Most NASA API endpoints (APOD, NeoWS, DONKI, TechTransfer) require a NASA API key. Register for a free key at https://api.nasa.gov. The default DEMO_KEY provides limited access (30 requests/hour, 50 requests/day); a registered key allows 1,000 requests/hour.

The following endpoints do not require an API key and work without authentication: EONET (Earth Observatory Natural Event Tracker), EPIC (Earth Polychromatic Imaging Camera), NASA Image and Video Library, and TechPort.

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your NASA API key. Use DEMO_KEY for limited testing.

Example Connection String

Profile=C:\profiles\NASA.apip;AuthScheme=APIKey;APIKey=YOUR_NASA_API_KEY

Connecting to NASA

Once the authentication is configured, you can connect to NASA and query data from any of the available tables such as AstronomyPictureOfDay, NearEarthObjectFeed, EonetEvents, and NasaImageLibrary.

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

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

engine = create_engine("api:///?Profile=C:\profiles\NASA.apip&AuthScheme=APIKey&APIKey=YOUR_NASA_API_KEY")

Execute SQL to NASA

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

df = pandas.read_sql("SELECT , FROM AstronomyPictureOfDay WHERE StartDate = '2024-01-01'", engine)

Visualize NASA Data

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

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

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

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 NASA 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("api:///?Profile=C:\profiles\NASA.apip&AuthScheme=APIKey&APIKey=YOUR_NASA_API_KEY")
df = pandas.read_sql("SELECT , FROM AstronomyPictureOfDay WHERE StartDate = '2024-01-01'", engine)

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