Publications by Marco Castro
Fair Market Rents (FMR) vs Market Rate Rents
Fair Market Rents (FMR) vs Market Rate Rents This project aims to ascertain whether the market rate rental costs for 1 and 2 bedroom apartments are consistent with the federal government’s Fair Market Rents (FMR) — the 40th percentile of gross rents for typical rental units paid by tenants that moved within the last 20 months. FMR is used to ca...
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Fair Market Rents (FMR) vs Market Rate Rents
2024-12-16 Project Overview Goal of the Project Analyze if market rate apartment rents are consistent with federal defined Fair Market Rents (FMR) levels in three distinct metropolitan areas. What is FMR? FMR is the 40th percentile of gross rents for typical rental units paid by tenants that moved within the last 20 months. FMR provides an estima...
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GBE
Recommender Systems - Global Baseline Estimate In this lab, we are asked to use the Global Baseline Estimate (GBE) algorithm to calculate how a viewer would rate a movie based on a) how that specific viewer has rated other movies and b) how all movies in a dataset have been rated by all users. The formula to calculate the GBE predicted value is: GB...
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Recommender System
Recommender Systems Apple Music is a music streaming service from the Apple Inc. that allows users to pay a monthly subscription fee to play unlimited tracks and albums. The service is marketed as an alternative to streaming music giant Spotify. However, despite being an early innovator in the digital music space, Apple Music holds only a 12.6% sh...
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Purrr Vignette
Working with Purrr In this sample vignette, I will walk through some of the functionalities of the the purrr Tidyverse package using an agriculture dataset from Kaggle. According the Tidyverse site, purrr “enhances R’s functional programming (FP) toolkit by providing a complete and consistent set of tools for working with functions and vectors....
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Week9-Web-APIs
Overview This week, we were taseked with choosing a New York Times API, constructing an interface in R to read in the JSON data, and transform it into an R DataFrame. I saved my key in an external file and loaded it into R. source("api_credentials.R") Method 1: Calling the API with JSONlite I used the fromJSON function from the jsonlite package to...
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Project 3
Overview For Project 3, our team was asked to answer the question, Which are the most valued data science skills? To answer this question, we decided to explore the top skills that companies search for in a job candidate. We sourced data from Indeed, a popular job listing site. We were able to source a dataset featuring over 12,000 US Data Science ...
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Project 3
Overview / Introduction Overview For Project 3, our team was asked to answer the question, Which are the most valued data science skills? To answer this question, we decided to explore the top skills that companies search for in a job candidate. We sourced data from Indeed, a popular job listing site. We were able to source a dataset featuring ove...
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week7
Preparing different file formats In this assigname, we were asked to prepare a dataset by first formatting into four different file formats (JSON, HTML, XML, and Parquet) and then reading it into R. I began by creating an HTML table from the data that was provided, then imported the it using the readHTMLTable from the XML package. The package did a...
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Project 2
Overview For project 2, we were asked to import three untidy datasets, make it tidy and conduct some analysis with the newly tranformed dataframe. For my project, I worked with the following: Florida Demographics Marital Status (1960-2020) Spotify Most Streamed Songs of 2023 Florida Demographics This dataset was compiled to help assess people’s...
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