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# Use package dplyr to explore WestRoxbury real estate dataset
d = read.csv(“WestRoxbury.csv”)
# 1) Filter the data to show only houses whose total value
# is greater than 350 (thousand), less than 20 years of age,
# and tax is less than 5000. HINT: use Mutate to calculate
# age of the house as of 2020.
# 2) Sort the dataset by (age, total value), then show
# only age, total value, lot sqft, and rooms. Assign entire
# output to a variable named sortedD. Now using standard base R, show only
# first 10 rows of sortedD.
# 3) A potential buyer is looking for a house which will have at least 8 rooms,
# in exactly one floor, have a fireplace, and built in between 1970 and 1990.
# Arrange these houses sorted by total value.
# Finally, assign the result to a new variable named custList.
# View custList.
# 4) Summarize the dataset by first grouping on age, then calculate
# count of each group, mean, min, and max of total value. Then,
# order the resulting output (in descending order) by count. Finally, assign the result
# to a new variable named groupedD.
# View groupedD.
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