1. Austin Animal Center Intakes Exploratory Data Analysis with Python, Pandas and Seaborn

    The Austin Animal Center, the largest no-kill municipal shelter in the United States, makes available its collected data on Austin's Open Data Portal. This data includes both animals incoming into the shelter and the animals' outcome. In this post, we perform some exploratory data analysis on the intakes dataset to see if we can find any noticeable trends or interesting pieces of information of the data. First, we will extract the data from Austin's Data Portal, which is supported by Socrata

  2. Predicting Shelter Cat Adoptions and Transfers with Scikit-learn and Machine Learning

    In the previous notebook analysis, we identified several likely candidate features and variables that could be significant in predicting a cat's outcome as it enters the shelter. Using that information and scikit-learn, we can train a machine learning model to predict if a cat will be adopted or transferred to a partner facility. For this first task, we are only interested in the adoption and transfer outcomes to see if our assumptions based on experience and the information we learned from the previous analysis align with predicted results. Adoptions and transfers represent over 90% of all the outcomes in the Austin Animal Center shelter system, therefore focusing on these outcomes and their more specific subtype outcomes and building a model to predict these outcomes is still quite valuable.

  3. Exploratory Data Analysis of Shelter Cat Outcomes with Pandas and Seaborn

    In this step, we visualize the data we extracted from the AAC database with the additional features that were added to the data in the previous notebook. The visualization of the outcomes and variables of which we have an interest will help us better understand the data and how the variables relate to each other. This knowledge will be crucial when selecting which variables we should focus on and include in our prediction model during the model building phase.

  4. Extraction and Feature Engineering of Animal Austin Center's Shelter Outcomes Dataset using Requests and Pandas

    The Austin Animal Center is the largest no-kill animal shelter and shelters and protects over 18,000 animals each year. As part of the City of Austin's Open Data Initiative, the Center makes available their data detailing shelter pet intake and outcomes. According to the data portal, over 90% of animal outcomes are adoptions, transfers to other shelter partners or returning lost pets to owners.

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