The Austin Animal Center provides its animal intake and outcome datasets on Socrata. When an animal is taken into the shelter, it is given a unique identifier that is also used in the outcomes dataset. We have already investigated and performed exploratory data analysis on the Austin Animal Center's intakes and animal outcomes individually and found several interesting facets of information. In this analysis, we merge the intakes and outcomes dataset using pandas to enable us to perform exploratory data analysis on the merged data. With the data merged, we will be able to explore in more depth the transition from intake to outcome.
Articles in the nasapy category
In this example, we will walk through a possible use case of the nasapy library by extracting the next 10 years of close-approaching objects to Earth identified by NASA's Jet Propulsion Laboratory's Small-Body Database. The close_approach method of the nasapy library allows one to access the JPL SBDB to extract data related to known meteoroids and asteroids within proximity to Earth. Setting the parameter return_df=True automatically coerces the returned JSON data into a pandas DataFrame.
In this example, we will go through one possible use of the nasapy library by extracting a decade of fireball data from the NASA API and visualizing it on a map. Using the nasapy library, we can extract the last 10 years of fireball data as a pandas DataFrame by calling the fireballs function. The fireballs method does not require authentication to the NASA API, so we can go straight to getting the data.
- Linear Algebra
- Machine Learning
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