Loading Up Libraries
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.3 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(lubridate)
library(tidyquant)
## Loading required package: PerformanceAnalytics
## Loading required package: xts
## Loading required package: zoo
##
## Attaching package: 'zoo'
##
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
##
##
## ######################### Warning from 'xts' package ##########################
## # #
## # The dplyr lag() function breaks how base R's lag() function is supposed to #
## # work, which breaks lag(my_xts). Calls to lag(my_xts) that you type or #
## # source() into this session won't work correctly. #
## # #
## # Use stats::lag() to make sure you're not using dplyr::lag(), or you can add #
## # conflictRules('dplyr', exclude = 'lag') to your .Rprofile to stop #
## # dplyr from breaking base R's lag() function. #
## # #
## # Code in packages is not affected. It's protected by R's namespace mechanism #
## # Set `options(xts.warn_dplyr_breaks_lag = FALSE)` to suppress this warning. #
## # #
## ###############################################################################
##
## Attaching package: 'xts'
##
## The following objects are masked from 'package:dplyr':
##
## first, last
##
##
## Attaching package: 'PerformanceAnalytics'
##
## The following object is masked from 'package:graphics':
##
## legend
##
## Loading required package: quantmod
## Loading required package: TTR
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
library(readxl)
library(writexl)
Importing Dataset
bikes <- read_excel("C:/Users/Admin/Downloads/bikes.xlsx")
head(bikes)
## # A tibble: 6 × 4
## bike.id model description price
## <dbl> <chr> <chr> <dbl>
## 1 1 Supersix Evo Black Inc. Road - Elite Road - Carbon 12790
## 2 2 Supersix Evo Hi-Mod Team Road - Elite Road - Carbon 10660
## 3 3 Supersix Evo Hi-Mod Dura Ace 1 Road - Elite Road - Carbon 7990
## 4 4 Supersix Evo Hi-Mod Dura Ace 2 Road - Elite Road - Carbon 5330
## 5 5 Supersix Evo Hi-Mod Utegra Road - Elite Road - Carbon 4260
## 6 6 Supersix Evo Red Road - Elite Road - Carbon 3940
Working with data
Show “model” and “price” column with “price” in descending
order
bikes %>%
select(model, price) %>%
arrange(desc(price))
## # A tibble: 97 × 2
## model price
## <chr> <dbl>
## 1 Supersix Evo Black Inc. 12790
## 2 Scalpel-Si Black Inc. 12790
## 3 Habit Hi-Mod Black Inc. 12250
## 4 F-Si Black Inc. 11190
## 5 Supersix Evo Hi-Mod Team 10660
## 6 Synapse Hi-Mod Disc Black Inc. 9590
## 7 Scalpel-Si Race 9060
## 8 F-Si Hi-Mod Team 9060
## 9 Trigger Carbon 1 8200
## 10 Supersix Evo Hi-Mod Dura Ace 1 7990
## # ℹ 87 more rows
Show “model” and “price” column with “price” greater than mean value
of price
bikes %>%
select(model, price) %>%
filter(price>mean(price))
## # A tibble: 35 × 2
## model price
## <chr> <dbl>
## 1 Supersix Evo Black Inc. 12790
## 2 Supersix Evo Hi-Mod Team 10660
## 3 Supersix Evo Hi-Mod Dura Ace 1 7990
## 4 Supersix Evo Hi-Mod Dura Ace 2 5330
## 5 Supersix Evo Hi-Mod Utegra 4260
## 6 CAAD12 Black Inc 5860
## 7 CAAD12 Disc Dura Ace 4260
## 8 Synapse Hi-Mod Disc Black Inc. 9590
## 9 Synapse Hi-Mod Disc Red 7460
## 10 Synapse Hi-Mod Dura Ace 5860
## # ℹ 25 more rows