Publications by Hannah Mandell

Art and Artists - Using a Random Forest Model

12.01.2021

The data today come from the Tate Art Gallery (https://github.com/tategallery/collection) library(tidyverse) library(tidytuesdayR) library(lubridate) library(dplyr) library(tidyr) library(broom) library(countrycode) library(praise) #install.packages("tidymodels") library(tidymodels) #install.packages("ranger") praise() ## [1] "You are tiptop!" G...

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Social Media & Market Value Exploration

22.02.2021

library(tidyverse) library(dplyr) library(ggplot2) library(lubridate) library(plotly) #install.packages("GGally") #install.packages("reshape2") followers <- read.csv("socialmedia_followers.csv") player_value <- read.csv("player_market_values.csv") followers <- followers %>% select(-X_) %>% select(-X_.1) %>% select(-Sport) player_value <- p...

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New York AirBNBs

22.03.2021

Airbnb Listings in NY Hannah Mandell Overview Column Location Column Number of stays 48895 Average price per day 153 Number of Stays by Neighborhood Average Price by Neighborhood Room type Column Average price per day of common room Average price per day of high-class room Column Number of normal stays 48509 Average price...

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Superbowl Ads

02.03.2021

Done with the lovely, Prof. Jo Hardin! library(tidytuesdayR) library(tidyverse) library(dplyr) #install.packages('tuber') library(tuber) library(rvest) library(httr) #install.packages('ggforce') library(ggforce) tuesdata <- tidytuesdayR::tt_load('2021-03-02') ## ## Downloading file 1 of 1: `youtube.csv` youtube <- readr::read_csv('https://raw....

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NWSL Analysis

22.03.2021

#install.packages("rlang") #install.packages("ggplot2") #install.packages("tidyverse") #install.packages("dplyr") #install.packages("stringr") #install.packages("lubridate") #install.packages("tidymodels") #install.packages("ggmap") #install.packages("devtools") #install.packages("devtools") #devtools::install_github("adror1/nwslR") library(ggpl...

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Plastics & Corporations

22.03.2021

TidyTuesday Join the R4DS Online Learning Community in the weekly #TidyTuesday event! Every week we post a raw dataset, a chart or article related to that dataset, and ask you to explore the data. While the dataset will be “tamed”, it will not always be tidy! As such you might need to apply various R for Data Science techniques to wrangle the...

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Makeup Shades

01.04.2021

TidyTuesday Load the weekly Data Dowload the weekly data and make available in the tt object. tt <- tt_load("2021-03-30") ## ## Downloading file 1 of 5: `ulta.csv` ## Downloading file 2 of 5: `sephora.csv` ## Downloading file 3 of 5: `allShades.csv` ## Downloading file 4 of 5: `allNumbers.csv` ## Downloading file 5 of 5: `allCategories.csv...

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