# Load packages
library(tidyquant)
library(tidyverse) # for count() function
# Import S&P500 Stock Index
SP500 <- tq_index("SP500")
SP500## # A tibble: 505 x 8
## symbol company identifier sedol weight sector shares_held local_currency
## <chr> <chr> <chr> <chr> <dbl> <chr> <dbl> <chr>
## 1 AAPL Apple Inc. 03783310 20462~ 0.0696 Inform~ 173039940 USD
## 2 MSFT Microsoft~ 59491810 25881~ 0.0573 Inform~ 80524710 USD
## 3 AMZN Amazon.co~ 02313510 20000~ 0.0487 Consum~ 4448676 USD
## 4 FB Facebook ~ 30303M10 B7TL8~ 0.0240 Commun~ 25531082 USD
## 5 GOOGL Alphabet ~ 02079K30 BYVY8~ 0.0168 Commun~ 3188626 USD
## 6 GOOG Alphabet ~ 02079K10 BYY88~ 0.0164 Commun~ 3105180 USD
## 7 BRK.B Berkshire~ 08467070 20733~ 0.0150 Financ~ 20661764 USD
## 8 JNJ Johnson &~ 47816010 24758~ 0.0138 Health~ 27998392 USD
## 9 V Visa Inc.~ 92826C83 B2PZN~ 0.0122 Inform~ 17929224 USD
## 10 PG Procter &~ 74271810 27044~ 0.0121 Consum~ 26301280 USD
## # ... with 495 more rows505 rows ## Q2 How many columns does the data have? 8 columns ## Q3 How many companies are listed in S&P500 Index? 505 companies ## Q4 What are the top three stocks that have the greatest influence on ups and downs in S&P500 Index? Apple, Microsoft, Amazon
Information technology, Consumer discretionary, Communication services, Health Care
Communication services
Hint: Insert a R code chunk below, type the following code:
count(SP500, sector, sort = T)## # A tibble: 11 x 2
## sector n
## <chr> <int>
## 1 Industrials 73
## 2 Information Technology 71
## 3 Financials 66
## 4 Health Care 62
## 5 Consumer Discretionary 61
## 6 Consumer Staples 33
## 7 Real Estate 31
## 8 Materials 28
## 9 Utilities 28
## 10 Communication Services 26
## 11 Energy 26Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.