Publications by Sangeetha Sasikumar
Lab 5 - 606, Part 1
global_monitor <- tibble( scientist_work = c(rep("Benefits", 80000), rep("Doesn't benefit", 20000)) ) global_monitor ## # A tibble: 100,000 × 1 ## scientist_work ## <chr> ## 1 Benefits ## 2 Benefits ## 3 Benefits ## 4 Benefits ## 5 Benefits ## 6 Benefits ## 7 Benefits ## 8 Benefi...
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Lab 5 - 606, Part 2
library(tidyverse) ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ── ## ✔ ggplot2 3.3.6 ✔ purrr 0.3.4 ## ✔ tibble 3.1.8 ✔ dplyr 1.0.9 ## ✔ tidyr 1.2.0 ✔ stringr 1.4.1 ## ✔ readr 2.1.2 ✔ f...
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Assignment 5 - 607
For Assignment 5, we were asked to create HTML, XML and JSON files with our favorite books and some information about it. I chose the books: Beautiful Creatures (I never read this one), East of Eden (I love this book) and The Catcher in the Rye (an interesting read). To read in data from HTML into R, I did play around with it a bit. I even tried ...
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Lab 6 - 606
Getting Started Load packages In this lab, we will explore and visualize the data using the tidyverse suite of packages, and perform statistical inference using infer. The data can be found in the companion package for OpenIntro resources, openintro. Let's load the packages. library(tidyverse) library(openintro) library(infer) set.seed(500) data...
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Assignment 6 -607
For assignment 6, we were asked to use the New York Times API to import data. I chose the Movie Reviews API. I passed in the key through a text file on my local machine just so the key wouldn't be public in RPubs/Github. NYTIMES_KEY <- readLines("NYTIMES_KEY.txt") ## Warning in readLines("NYTIMES_KEY.txt"): incomplete final line found on ## 'NYTI...
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606-Final Proposal
From the FiveThirtyEight page, I found a dataset to figure out which state has the "worst" drivers: https://github.com/fivethirtyeight/data/blob/master/bad-drivers/bad-drivers.csv. This caught my attention because all of my relatives from other states laugh at me and say I am a bad driver since I am from NY (I don't think I am a bad driver at all...
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Project 2- RESUBMIT
Part 1 Loaded the data as csv. In this dataset, the columns are gender, department, admitted and whether or not they are rejected. I am going to try to clean up this dataset. rejected<-read.csv("https://raw.githubusercontent.com/Sangeetha-007/R-Practice/master/607/Projects/Project%202/Admitted_Rejected%20-%20Sheet1.csv") rejected ## Gender De...
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Assignment 7-607
Example from https://www.tidytextmining.com/sentiment.html. This was something very new to me, so I kept it all in the markdown. get_sentiments("afinn") ## # A tibble: 2,477 × 2 ## word value ## <chr> <dbl> ## 1 abandon -2 ## 2 abandoned -2 ## 3 abandons -2 ## 4 abducted -2 ## 5 abduction -2 ## 6 ab...
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Discussion 11-607
Recommender Systems- Spotify Perform a Scenario Design analysis as described below. Consider whether it makes sense for your selected recommender system to perform scenario design twice, once for the organization (e.g. Amazon.com) and once for the organization's customers. -Who are your target users? -What are their key goals? -How can you help...
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Data Science for Context Presentation
What's the Zip Code? library(tmaptools) library(sf) ## Linking to GEOS 3.10.2, GDAL 3.4.2, PROJ 8.2.1; sf_use_s2() is TRUE library(tmap) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, se...
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