Homework

Import the data files using read_excel()to import excel files.

library("readxl")
library("dplyr")

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library("tidyverse")

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats   1.0.0     ✔ readr     2.1.4
## ✔ ggplot2   3.4.3     ✔ stringr   1.5.0
## ✔ lubridate 1.9.2     ✔ tibble    3.2.1
## ✔ purrr     1.0.2     ✔ tidyr     1.3.0

## ── 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("writexl")
bike_data <- read_excel("/cloud/project/bikes.xlsx")

Show “model” and “price” columns,sorted by “price” in descending order

task_1_sorted_bike<- bike_data %>%
 select(model,price) %>%
 arrange(desc(price))

Calculate the mean price

mean_price <- mean(bike_data$price)

Show “model” and “price” columns with condition”price”

task_2_high_price_bike <- bike_data %>%
 select(model,price) %>%
 filter(price>mean_price)