Saving and exporting xts objects

Case Study: Analyzing City Time Series Data in R

Lore Dirick

Manager of Data Science Curriculum at Flatiron School

Saving as rds

  • Use saveRDS() and readRDS()

    saveRDS(citydata, file = "citydata.rds")

  • Maintains time index of xts objects

    readRDS("citydata.rds")

              pop pct_growth
1980-01-01 562994         NA
1990-01-01 574823   2.057851
2000-01-01 589141   2.430318
2010-01-01 617594   4.607072
Case Study: Analyzing City Time Series Data in R

Saving as csv

  • Use write.zoo() and read.zoo()

    write.zoo(citydata, file = "citydata.csv", sep = ",")

  • Must re-convert to xts

citydata <- read.zoo("citydata.csv", sep = ",", header = TRUE)

as.xts(citydata)

              pop pct_growth
1980-01-01 562994         NA
1990-01-01 574823   2.057851
2000-01-01 589141   2.430318
2010-01-01 617594   4.607072
Case Study: Analyzing City Time Series Data in R

Let's practice!

Case Study: Analyzing City Time Series Data in R

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