Katie Quinn
library("wbstats")
meta <- wb_cache()
names(meta)
## [1] "countries" "indicators" "sources" "topics"
## [5] "regions" "income_levels" "lending_types" "languages"
meta$topics
library(quantmod)
## Loading required package: xts
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
## Loading required package: TTR
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
Question 5.
getSymbols(c("NVDA", "TSLA"), source = "oanda")
## [1] "NVDA" "TSLA"
getSymbols(c("NVDA", "TSLA"), source = "yahoo")
## [1] "NVDA" "TSLA"
getSymbols(c("NVDA", "TSLA"), source = "FRED")
## [1] "NVDA" "TSLA"
tail(TSLA,10)
## TSLA.Open TSLA.High TSLA.Low TSLA.Close TSLA.Volume TSLA.Adjusted
## 2025-01-24 414.45 418.88 405.78 406.58 56427100 406.58
## 2025-01-27 394.80 406.69 389.00 397.15 58125500 397.15
## 2025-01-28 396.91 400.59 386.50 398.09 48910700 398.09
## 2025-01-29 395.21 398.59 384.48 389.10 68033600 389.10
## 2025-01-30 410.78 412.50 384.41 400.28 98092900 400.28
## 2025-01-31 401.53 419.99 401.34 404.60 83568200 404.60
## 2025-02-03 386.68 389.17 374.36 383.68 93732100 383.68
## 2025-02-04 382.63 394.00 381.40 392.21 57072200 392.21
## 2025-02-05 387.51 388.39 375.53 378.17 57223300 378.17
## 2025-02-06 373.03 375.40 363.18 374.32 77918200 374.32
tail(NVDA,10)
## NVDA.Open NVDA.High NVDA.Low NVDA.Close NVDA.Volume NVDA.Adjusted
## 2025-01-24 148.37 148.97 141.88 142.62 234657600 142.62
## 2025-01-27 124.80 128.40 116.70 118.42 818830900 118.42
## 2025-01-28 121.81 129.00 116.25 128.99 579666400 128.99
## 2025-01-29 126.50 126.89 120.05 123.70 467120600 123.70
## 2025-01-30 123.10 125.00 118.10 124.65 392925500 124.65
## 2025-01-31 123.78 127.85 119.19 120.07 390372900 120.07
## 2025-02-03 114.75 118.57 113.01 116.66 371235700 116.66
## 2025-02-04 116.96 121.20 116.70 118.65 256550000 118.65
## 2025-02-05 121.76 125.00 120.76 124.83 262230800 124.83
## 2025-02-06 127.42 128.77 125.21 128.68 251483600 128.68
Question 6.
getSymbols("MSFT", src="yahoo",from = "2024-10-01", to = "2025-02-01")
## [1] "MSFT"
head(MSFT)
## MSFT.Open MSFT.High MSFT.Low MSFT.Close MSFT.Volume MSFT.Adjusted
## 2024-10-01 428.45 428.48 418.81 420.69 19092900 419.8496
## 2024-10-02 422.58 422.82 416.71 417.13 16582300 416.2967
## 2024-10-03 417.63 419.55 414.29 416.54 13686400 415.7079
## 2024-10-04 418.24 419.75 414.97 416.06 19169700 415.2289
## 2024-10-07 416.00 417.11 409.00 409.54 20919800 408.7219
## 2024-10-08 410.90 415.66 408.17 414.71 19229300 413.8816
Question 7.
nrow(MSFT)
## [1] 84
pacman::p_load(httr, jsonlite)
library(pageviews)
library(pacman)
Question 9.
microsoft_views <- article_pageviews(
project = "en.wikipedia", # English Wikipedia
article = "Microsoft", # Wikipedia page title
start = "2024100100", # Start date in YYYYMMDD format
end = "2025013123", # End date in YYYYMMDD format
user_type = "all" # Includes all users (bots + humans)
)
nrow(microsoft_views)
## [1] 123
ncol(microsoft_views)
## [1] 8
Questions 10.
views30000 <- subset(microsoft_views, views > 30000)
head(views30000)
Question 11.
nrow(MSFT)
## [1] 84
nrow(microsoft_views)
## [1] 123
mergedData2 <- merge(MSFT, microsoft_views)
## Warning in merge.xts(MSFT, microsoft_views): NAs introduced by coercion