Publications by Arif
IBM Applied Data Science with R
Welcome! In this section, we will explore several methods to see if certain characteristics or features can be used to predict arrival delay minutes. The main question we will be trying to answer throughout this lab is: what are the main characteristics which have the most impact on how long a flight arrives late? Table of Contents 1. Analyzi...
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Regression in R
Libraries library(tidyverse) library(anytime) library(lubridate) library(assertive) library(fst) library(broom) library(ggfortify) library(yardstick) library(moderndive) library(tidyr) library(plot3D) library(magrittr) library(infer) library(anytime) library(ggridges) library(zeallot) Data taiwan_real_estate <- read.fst("taiwan_real_estate.fst") ...
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Sampling and Hypothesis Testing in R
Libraries library(tidyverse) library(openintro) library(assertive) library(fst) library(broom) library(coin) # chiq_test library(infer) library(infer) library(anytime) library(lubridate) library(random) Data spotify_population <- read.fst("spotify_2000_2020.fst") attrition_pop <- read.fst("attrition.fst") late_shipments <- read.fst("late_shipment...
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Writing Functions in R
Libraries library(tidyverse) library(anytime) library(lubridate) library(assertive) library(fst) library(broom) library(ggfortify) library(yardstick) library(moderndive) library(tidyr) library(plot3D) library(magrittr) library(infer) library(anytime) library(ggridges) library(zeallot) Data std_and_poor500 <- readRDS("std_and_poor500_with_pe_2019-...
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Cleaning Data in R
Libraries library(tidyverse) library(forcats) library(assertive) library(stringr) library(lubridate) library(forcats) library(visdat) library(stringdist) library(reclin) library(fuzzyjoin) Data bike_share_rides <- readRDS("~/R Data/bike_share_rides_ch1_1.rds") sfo_survey <- readRDS("sfo_survey_ch2_1.rds") zagat <- readRDS("zagat.rds") accounts <-...
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Importing Data in R
Libraries library(tidyverse) library(forcats) library(lubridate) library(ggthemes) library(gdata) library(DBI) library(data.table) 0. Course Description Importing data into R should be the easiest step in your analysis. Unfortunately, that is almost never the case. Data can come in many formats, ranging from .csv and text files, to statistical s...
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Reporting with R Markdown
library(tidyverse) 1. Formatting HTML files HTML files do not use templates, but can have the styles configured within the YAML. HTMLs are interactive documents, and are particularly flexible. We cover some basic options here. Table of contents: We can add a table of contents with toc: true below, and also specify that it remains viewable (...
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Joining Data with dplyr
Libraries library(tidyverse) library(forcats) library(lubridate) Data parts <- readRDS("parts.rds") answers <- readRDS("answers.rds") colors <- readRDS("~/R Data/colors.rds") inventories <- readRDS("~/R Data/inventories.rds") inventory_parts <- readRDS("~/R Data/inventory_parts.rds") parts <- readRDS("~/R Data/parts.rds") part_categories <- readR...
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Data Manipulation with dplyr
Libraries library(tidyverse) counties <- readRDS("counties.rds") babynames <- readRDS("babynames.rds") 0. Course Description Say you’ve found a great dataset and would like to learn more about it. How can you start to answer the questions you have about the data? You can use dplyr to answer those questions—it can also help with basic transfo...
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Unsupervised Learning in Rt
Libraries library(tidyverse) ## -- Attaching packages --------------------------------------- tidyverse 1.3.1 -- ## v ggplot2 3.3.5 v purrr 0.3.4 ## v tibble 3.1.6 v dplyr 1.0.7 ## v tidyr 1.1.4 v stringr 1.4.0 ## v readr 2.1.1 v forcats 0.5.1 ## -- Conflicts ------------------------------------------ tidyverse_conflic...
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