Task 4 Technohack Pivot Table

Load Dataset

house_prices <- read.csv("train.csv",header = TRUE)
datatable(house_prices, options = list(scrollX = TRUE))

Descriptive Statistics

# Generate descriptive statistics using summarytools
desc_stats <- descr(house_prices)
# Create an interactive DT table for the descriptive statistics
datatable(desc_stats, options = list(scrollX = TRUE, paging = FALSE))

Create Pivot Table

Pivot Table 1: Summarize data for YearBuilt

# Pivot Table 1: Summarize data for YearBuilt
pivot_table_year_built <- house_prices %>%
  select(SalePrice, YearBuilt) %>%
  group_by(YearBuilt) %>%
  summarise(
    AvgSalePrice = mean(SalePrice),
    MedianSalePrice = median(SalePrice)
  )
datatable(pivot_table_year_built)

Pivot Table 2: Summarize data for Neighborhood

# Pivot Table 2: Summarize data for Neighborhood
pivot_table_neighborhood <- house_prices %>%
  select(SalePrice, Neighborhood) %>%
  group_by(Neighborhood) %>%
  summarise(
    AvgSalePrice = mean(SalePrice),
    MedianSalePrice = median(SalePrice)
  )
datatable(pivot_table_neighborhood)

Pivot Table 3: Summarize data for GarageType

# Pivot Table 3: Summarize data for GarageType
pivot_table_garage_type <- house_prices %>%
  select(SalePrice, GarageType) %>%
  group_by(GarageType) %>%
  summarise(
    AvgSalePrice = mean(SalePrice),
    MedianSalePrice = median(SalePrice)
  )
datatable(pivot_table_garage_type)

Pivot Table 4: Summarize data for BedroomAbvGr

# Pivot Table 4: Summarize data for BedroomAbvGr
pivot_table_bedrooms <- house_prices %>%
  select(SalePrice, BedroomAbvGr) %>%
  group_by(BedroomAbvGr) %>%
  summarise(
    AvgSalePrice = mean(SalePrice),
    MedianSalePrice = median(SalePrice)
  )
datatable(pivot_table_bedrooms)

Pivot Table 5: Summarize data for FullBath

# Pivot Table 5: Summarize data for FullBath
pivot_table_full_bath <- house_prices %>%
  select(SalePrice, FullBath) %>%
  group_by(FullBath) %>%
  summarise(
    AvgSalePrice = mean(SalePrice),
    MedianSalePrice = median(SalePrice)
  )
datatable(pivot_table_full_bath)

Pivot Table 6: Summarize data for LotArea

# Pivot Table 6: Summarize data for LotArea
pivot_table_lot_area <- house_prices %>%
  select(SalePrice, LotArea) %>%
  group_by(LotArea) %>%
  summarise(
    AvgSalePrice = mean(SalePrice),
    MedianSalePrice = median(SalePrice)
  )
datatable(pivot_table_lot_area)

Pivot Table 7: Summarize data for KitchenQual

# Pivot Table 7: Summarize data for KitchenQual
pivot_table_kitchen_qual <- house_prices %>%
  select(SalePrice, KitchenQual) %>%
  group_by(KitchenQual) %>%
  summarise(
    AvgSalePrice = mean(SalePrice),
    MedianSalePrice = median(SalePrice)
  )
datatable(pivot_table_kitchen_qual)

Pivot Table 8: Summarize data for GarageCars

# Pivot Table 8: Summarize data for GarageCars
pivot_table_garage_cars <- house_prices %>%
  select(SalePrice, GarageCars) %>%
  group_by(GarageCars) %>%
  summarise(
    AvgSalePrice = mean(SalePrice),
    MedianSalePrice = median(SalePrice)
  )
datatable(pivot_table_garage_cars)

Pivot Table 9: Summarize data for Fireplaces

# Pivot Table 9: Summarize data for Fireplaces
pivot_table_fireplaces <- house_prices %>%
  select(SalePrice, Fireplaces) %>%
  group_by(Fireplaces) %>%
  summarise(
    AvgSalePrice = mean(SalePrice),
    MedianSalePrice = median(SalePrice)
  )
datatable(pivot_table_fireplaces)

Pivot Table 10: Summarize data for SaleType

# Pivot Table 10: Summarize data for SaleType
pivot_table_sale_type <- house_prices %>%
  select(SalePrice, SaleType) %>%
  group_by(SaleType) %>%
  summarise(
    AvgSalePrice = mean(SalePrice),
    MedianSalePrice = median(SalePrice)
  )
datatable(pivot_table_sale_type)