Publications by Ryan Best, Elena Mejía
Final Project_Data 607
Libraries Abstract This project investigates the relationship between socioeconomic factors and the housing market in the United States, focusing on three metropolitan areas: New York City, Miami, and Los Angeles. Utilizing datasets on median housing prices, homeownership rates, education, jobs, and household income across multiple years and quart...
21079 sym Python (58406 sym/125 pcs) 34 img
Week 7_Data 607
Several libraries needed to be installed before importing the HTML, XML, and JSON files. It also required a manual CRAN setup. Once installed, we were able to load the packages. We load each file in a similar way, but they differ in how the data is structured. The HTML file is read in multiple lines and includes tags, such as “head” and “body...
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Project 2_Data607
Supermarket Sales supermarketdata <- read.csv("/Users/crys/Downloads/SuperMarket Analysis.csv") After loading in our data from a csv file, we’re going to clean it up by isolating relevant variables. clean_supermarket <- supermarketdata %>% select("City","Gender", "Product.line", "Sales", "gross.income", "Rating") The first analysis focuses on...
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Tidying and Transformation
arr_delay <- read_csv("Tidying and Transforming - Arrival Delays.csv", show_col_types = FALSE) ## New names: ## • `` -> `...1` ## • `` -> `...2` arr_delay ## # A tibble: 5 × 7 ## ...1 ...2 `Los Angeles` Phoenix `San Diego` `San Francisco` Seattle ## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 ALASKA...
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Project 1_Data 607
First, we must import the txt file into RStudio. We can remove the first few lines to start cleaning up the data. rawchessdata <- readLines("tournamentinfo.txt") ## Warning in readLines("tournamentinfo.txt"): incomplete final line found on ## 'tournamentinfo.txt' rawchessdata <- rawchessdata[-(1:4)] lines <- length(rawchessdata) head(rawchessdata) ...
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Week 3 Transformations - Expressions
#3 (.)\1\1 - Should this read “(.)\1\” ? This would repeat a character three times. “(.)(.)\2\1” - This would repeat two characters twice and then reverse. (..)\1 - This would repeat two characters twice. “(.).\1.\ 1” - This would repeat two characters three times. “(.)(.)(.).*\3\2\1” - This would call three characters and then reve...
564 sym
Fruit Transformation
list <- read_csv("https://github.com/crystaliquezada/week3transformations/raw/main/Fruits%20-%20Sheet1.csv", show_col_types = FALSE) new_list <- list%>% mutate (Fruit_Name = c("bell pepper", "bilberry", "blackberry", "blood orange", "blueberry", "cantaloupe", "chili pepper", "cloudberry", "elderberry", "...
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Week 3 Transformations
## # A tibble: 3 × 1 ## Major ## <chr> ## 1 MANAGEMENT INFORMATION SYSTEMS AND STATISTICS ## 2 COMPUTER PROGRAMMING AND DATA PROCESSING ## 3 STATISTICS AND DECISION SCIENCE...
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Loading_Transformations_1
Overview The Lasting Legacy of Redlining explores the discriminatory practice of redlining in an analysis of the racial segregation within 138 metropolitan cities. Ultimately, redlining has led to economic disparities and unequal opportunities for people of color to create generational wealth. As of 2020, Best and Mejia concluded that neighborhood...
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