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diff --git a/doc/qstacktseries.R b/doc/qstacktseries.R
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+## ---- include = FALSE---------------------------------------------------------
+knitr::opts_chunk$set(
+ collapse = TRUE,
+ comment = "#>"
+)
+
+## ----setup--------------------------------------------------------------------
+library(timeseries)
+library(gapminder)
+library(dplyr)
+
+## ----dataset------------------------------------------------------------------
+ testdf <- data.frame(year = rep(seq(from = 1980, to= 1990, 1), 3),
+ rainfall = c(runif(11, 0, 100), rnorm(11, 70, 10),
+ rnorm(11, 20, 20)),
+ temp = c(rnorm(11, 70, 30), rnorm(11, 45, 20),
+ rnorm(11, 100, 10)),
+ daysofsun = c(NA, NA, rnorm(9, 280, 50), rnorm(11, 300, 30), NA,
+ rnorm(10, 340, 15)),
+ region = c(rep("A",11), rep("B", 11), rep("C", 11)))
+
+## ----example 1----------------------------------------------------------------
+qstacktseries(testdf, year, rainfall, region, verbose = TRUE)
+
+## ----example 2----------------------------------------------------------------
+qstacktseries(gapminder %>%
+ filter(continent == "Asia"), year, gdpPercap, country, verbose = TRUE)
+
+## ----example 3: Errors, error=TRUE--------------------------------------------
+
+qstacktseries(gapminder %>%
+ filter(continent == "Asia"),continent, pop, country, verbose = TRUE)
+
+qstacktseries(gapminder %>%
+ filter(continent == "Africa"), year, country, continent, verbose = TRUE)
+
diff --git a/doc/qstacktseries.Rmd b/doc/qstacktseries.Rmd
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+---
+title: "qstacktseries"
+output: rmarkdown::html_vignette
+vignette: >
+ %\VignetteIndexEntry{qstacktseries}
+ %\VignetteEngine{knitr::rmarkdown}
+ %\VignetteEncoding{UTF-8}
+---
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+ collapse = TRUE,
+ comment = "#>"
+)
+```
+
+```{r setup}
+library(timeseries)
+library(gapminder)
+library(dplyr)
+```
+
+This is how the function `qstacktseries` works:
+
+Building a stacked area time series plot with a dummy data set:
+
+```{r dataset}
+ testdf <- data.frame(year = rep(seq(from = 1980, to= 1990, 1), 3),
+ rainfall = c(runif(11, 0, 100), rnorm(11, 70, 10),
+ rnorm(11, 20, 20)),
+ temp = c(rnorm(11, 70, 30), rnorm(11, 45, 20),
+ rnorm(11, 100, 10)),
+ daysofsun = c(NA, NA, rnorm(9, 280, 50), rnorm(11, 300, 30), NA,
+ rnorm(10, 340, 15)),
+ region = c(rep("A",11), rep("B", 11), rep("C", 11)))
+```
+
+```{r example 1}
+qstacktseries(testdf, year, rainfall, region, verbose = TRUE)
+```
+Building a stacked area time series plot with a pre-existing data set: *gapminder*
+
+```{r example 2}
+qstacktseries(gapminder %>%
+ filter(continent == "Asia"), year, gdpPercap, country, verbose = TRUE)
+```
+These are some errors you might see if `qstacktseries` is given non-numeric input for the *time* or *voi* inputs:
+
+```{r example 3: Errors, error=TRUE}
+
+qstacktseries(gapminder %>%
+ filter(continent == "Asia"),continent, pop, country, verbose = TRUE)
+
+qstacktseries(gapminder %>%
+ filter(continent == "Africa"), year, country, continent, verbose = TRUE)
+```
+
diff --git a/doc/qstacktseries.html b/doc/qstacktseries.html
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+library(timeseries)
+library(gapminder)
+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
This is how the function qstacktseries works:
+Building a stacked area time series plot with a dummy data set:
+ testdf <- data.frame(year = rep(seq(from = 1980, to= 1990, 1), 3),
+ rainfall = c(runif(11, 0, 100), rnorm(11, 70, 10),
+ rnorm(11, 20, 20)),
+ temp = c(rnorm(11, 70, 30), rnorm(11, 45, 20),
+ rnorm(11, 100, 10)),
+ daysofsun = c(NA, NA, rnorm(9, 280, 50), rnorm(11, 300, 30), NA,
+ rnorm(10, 340, 15)),
+ region = c(rep("A",11), rep("B", 11), rep("C", 11)))
qstacktseries(testdf, year, rainfall, region, verbose = TRUE)
+#> Plotting time series...Done labelling plot!...Done applying default theme aesthetics!
Building a stacked area time series plot with a pre-existing data set: gapminder
+qstacktseries(gapminder %>%
+ filter(continent == "Asia"), year, gdpPercap, country, verbose = TRUE)
+#> Plotting time series...Done labelling plot!...Done applying default theme aesthetics!
These are some errors you might see if qstacktseries is given non-numeric input for the time or voi inputs:
+
+qstacktseries(gapminder %>%
+ filter(continent == "Asia"),continent, pop, country, verbose = TRUE)
+#> Error in qstacktseries(gapminder %>% filter(continent == "Asia"), continent, : Sorry, the time variable needs to be a numeric variable!
+
+qstacktseries(gapminder %>%
+ filter(continent == "Africa"), year, country, continent, verbose = TRUE)
+#> Error in qstacktseries(gapminder %>% filter(continent == "Africa"), year, : Sorry, the variable of interest (dependent) needs to be a numeric variable!
qtseries
-
+library(timeseries)
+library(gapminder)
+library(dplyr)
This is how the function qtseries works:
-Building a time series plot with a dummy data set
+Building a time series plot with a dummy data set:
testdf <- data.frame(year = rep(seq(from = 1980, to= 1990, 1), 3),
rainfall = c(rnorm(11, 100, 30), rnorm(11, 70, 10),rnorm(11, 20, 20)),
temp = c(rnorm(11, 70, 30), rnorm(11, 100, 10),rnorm(11, 45, 20)),
@@ -331,33 +333,20 @@ qtseries
#> Plotting time series...Done labelling plot!...Done applying default theme aesthetics!
#> Warning: Removed 3 rows containing missing values (geom_point).
#> Warning: Removed 3 row(s) containing missing values (geom_path).
-Building a time series plot with the gapminder data set:
-library(gapminder)
-library(magrittr)
-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
-gapminder %>%
- filter(continent == "Europe")%>%
- qtseries(year, pop, country, verbose = TRUE)
-#> Plotting time series...Done labelling plot!...Done applying default theme aesthetics!
Some errors you might see if qtseries is given non-numeric variables for the time or voi inputs:
-gapminder %>%
- filter(continent == "Europe")%>%
- qtseries(continent, pop, country, verbose = TRUE)
-#> Error in qtseries(., continent, pop, country, verbose = TRUE): Sorry, the time variable needs to be a numeric variable!
-
-gapminder %>%
- filter(continent == "Europe")%>%
- qtseries(year, country, continent, verbose = TRUE)
-#> Error in qtseries(., year, country, continent, verbose = TRUE): Sorry, the variable of interest (dependent) needs to be a numeric variable!
+Building a time series plot with the gapminder data set:
+qtseries(gapminder %>%
+ filter(continent == "Europe"), year, pop, country, verbose = TRUE)
+#> Plotting time series...Done labelling plot!...Done applying default theme aesthetics!
+Some errors you might see if qtseries is given non-numeric variables for the time or voi inputs:
+qtseries(gapminder %>%
+ filter(continent == "Americas"),continent, pop, country, verbose = TRUE)
+#> Error in qtseries(gapminder %>% filter(continent == "Americas"), continent, : Sorry, the time variable needs to be a numeric variable!
+
+qtseries(gapminder %>%
+ filter(continent == "Europe"),year, country, continent, verbose = TRUE)
+#> Error in qtseries(gapminder %>% filter(continent == "Europe"), year, country, : Sorry, the variable of interest (dependent) needs to be a numeric variable!