Q1: This dataset is named poultry_tidy.csv which is downloaded from SampleDataset.
Q2: There are four columns in this dataset. Product is the name of production it’s string type. Year and Month are date type. Price_Dollar is numerical type.
Q3: Then we can use filter to select the product which is ‘Whole’ and arrange the rows based on asending Price_Dollar. Finally use slice to select 10 rows with the lowest price.
library(dplyr)
poultry <- read.csv("D:/601_workspace/poultry_tidy.csv")
poultry %>%
filter(Product=="Whole") %>%
arrange(Price_Dollar) %>%
slice(1:10)
Product Year Month Price_Dollar
1 Whole 2004 January 1.97500
2 Whole 2004 February 1.97500
3 Whole 2004 March 2.09000
4 Whole 2004 April 2.12000
5 Whole 2004 May 2.14500
6 Whole 2004 June 2.16375
7 Whole 2006 January 2.17000
8 Whole 2006 February 2.17000
9 Whole 2005 January 2.17000
10 Whole 2005 February 2.17000