Publications by Alex Makos
Clean data
In this exercise you will learn to clean data using the dplyr package. To this end, you will follow through the codes in one of our e-texts, Data Visualization with R. The given example code below is from Chapter 1.2 Cleaning data. ## # A tibble: 87 x 13 ## name height mass hair_color skin_color eye_color birth_year gender ## <chr> <int>...
901 sym R (3087 sym/8 pcs)
Quiz 1
Use the given code below to answer the questions. ## Load package library(tidyverse) # for cleaning, plotting, etc library(tidyquant) # for financial analysis ## Import data stocks <- tq_get("NFLX", get = "stock.prices", from = "2016-01-01") stocks ## Visualize stocks %>% ggplot(aes(x = date, y = adjusted)) + geom_line() Q1 Import Netflix s...
1240 sym R (1323 sym/5 pcs)
Mock Quiz 1
Use the given code below to answer the questions. Q1 Get Walmart stock prices, instead of Apple. Hint: Insert a new code chunk below and type in the code, using the tq_get() function above. Replace the ticker symbol for Walmart. You may find the ticker symbol for Walmart from Yahoo Finance. ## # A tibble: 1,029 x 7 ## date open high ...
1944 sym R (760 sym/1 pcs) 2 img
My First Publication
Q1 What is R? R is a website tha can be used to record data, statistics, and records of anything. R ca be used by anyone, is free, and is a great tool that many people should use. Q2 What is RStudio? Rstudio is where you actually go and type in the coding to try to make the website. This is where you type up the code language and publish it. Q3...
621 sym
Correlation
In this exercise you will learn to visualize the pairwise relationships between a set of quantitative variables. To this end, you will make your own note of 8.1 Correlation plots from Data Visualization with R. Q1 What factors have strong positve correlation with home price? The Factors that have a positive correlation with home price are living...
2166 sym 2 img