diff --git a/README.Rmd b/README.Rmd
index 7ddc9cc..6c30adb 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -71,7 +71,7 @@ When used on a data.frame, it returns a descriptive table:
```{r}
iris %>%
- desctable
+ desctable()
desctable(mtcars)
```
@@ -85,8 +85,8 @@ Methods for reduction to a simple dataframe (`as.data.frame`, automatically used
```{r}
iris %>%
- desctable %>%
- pander
+ desctable() %>%
+ pander()
```
You need to load these two packages first (and prior to **desctable** for **DT**) if you want to use them.
@@ -128,10 +128,10 @@ You can also provide your own automatic function, which needs to
* return a named list of statistical functions to use, as defined in the subsequent paragraphs.
```{r}
-# Strictly equivalent to iris %>% desctable %>% pander
+# Strictly equivalent to iris %>% desctable() %>% pander()
iris %>%
desctable(stats = stats_auto) %>%
- pander
+ pander()
```
### Statistical functions
@@ -145,7 +145,7 @@ As mentioned above, they need to be used inside a named list, such as
```{r}
mtcars %>%
desctable(stats = list("N" = length, "Mean" = mean, "SD" = sd)) %>%
- pander
+ pander()
```
@@ -183,7 +183,7 @@ iris %>%
desctable(stats = list("N" = length,
"%/Mean" = is.factor ~ percent | (is.normal ~ mean),
"Median" = is.normal ~ NA | median)) %>%
- pander
+ pander()
```
@@ -216,7 +216,7 @@ mtlabels <- c(mpg = "Miles/(US) gallon",
mtcars %>%
dplyr::mutate(am = factor(am, labels = c("Automatic", "Manual"))) %>%
desctable(labels = mtlabels) %>%
- pander
+ pander()
```
@@ -233,7 +233,7 @@ It uses the well known `group_by` function from **dplyr**:
```{r}
iris %>%
group_by(Species) %>%
- desctable -> iris_by_Species
+ desctable() -> iris_by_Species
iris_by_Species
```
@@ -254,16 +254,16 @@ You can specify groups based on any variable, not only factors:
# With pander output
mtcars %>%
group_by(cyl) %>%
- desctable %>%
- pander
+ desctable() %>%
+ pander()
```
Also with conditions:
```{r}
iris %>%
group_by(Petal.Length > 5) %>%
- desctable %>%
- pander
+ desctable() %>%
+ pander()
```
@@ -273,8 +273,8 @@ And even on multiple nested groups:
mtcars %>%
dplyr::mutate(am = factor(am, labels = c("Automatic", "Manual"))) %>%
group_by(vs, am, cyl) %>%
- desctable %>%
- pander
+ desctable() %>%
+ pander()
```
@@ -320,7 +320,7 @@ This function will be used on every variable and every grouping factor to determ
iris %>%
group_by(Species) %>%
desctable(tests = tests_auto) %>%
- pander
+ pander()
```
@@ -341,7 +341,7 @@ iris %>%
group_by(Petal.Length > 5) %>%
desctable(tests = list(.auto = tests_auto,
Species = ~chisq.test)) %>%
- pander
+ pander()
```
@@ -351,7 +351,7 @@ mtcars %>%
group_by(am) %>%
desctable(tests = list(.default = ~wilcox.test,
mpg = ~t.test)) %>%
- pander
+ pander()
```
@@ -376,7 +376,7 @@ mtcars %>%
"Sum of squares" = function(x) sum(x^2),
"Q1" = . %>% quantile(prob = .25),
"Q3" = purrr::partial(quantile, probs = .75))) %>%
- pander
+ pander()
```
@@ -388,7 +388,7 @@ iris %>%
Sepal.Width = ~function(f) oneway.test(f, var.equal = F),
Petal.Length = ~. %>% oneway.test(var.equal = T),
Sepal.Length = ~purrr::partial(oneway.test, var.equal = T))) %>%
- pander
+ pander()
```
@@ -403,5 +403,5 @@ bladder %>%
group_by(rx) %>%
desctable(tests = list(.default = ~wilcox.test,
surv = ~. %>% survdiff %>% .$chisq %>% pchisq(1, lower.tail = F) %>% list(p.value = .))) %>%
- pander
+ pander()
```
diff --git a/vignettes/desctable.Rmd b/vignettes/desctable.Rmd
index 126a7d2..25d3d6a 100644
--- a/vignettes/desctable.Rmd
+++ b/vignettes/desctable.Rmd
@@ -50,7 +50,7 @@ When used on a data.frame, it returns a descriptive table:
```{r}
iris %>%
- desctable
+ desctable()
desctable(mtcars)
```
@@ -64,12 +64,12 @@ Methods for reduction to a simple dataframe (`as.data.frame`, automatically used
```{r}
iris %>%
- desctable %>%
- pander
+ desctable() %>%
+ pander()
mtcars %>%
- desctable %>%
- datatable
+ desctable() %>%
+ datatable()
```
You need to load these two packages first (and prior to **desctable** for **DT**) if you want to use them.
@@ -114,7 +114,7 @@ You can also provide your own automatic function, which needs to
# Strictly equivalent to iris %>% desctable %>% datatable
iris %>%
desctable(stats = stats_auto) %>%
- datatable
+ datatable()
```
### Statistical functions
@@ -128,7 +128,7 @@ As mentioned above, they need to be used inside a named list, such as
```{r}
mtcars %>%
desctable(stats = list("N" = length, "Mean" = mean, "SD" = sd)) %>%
- datatable
+ datatable()
```
@@ -166,7 +166,7 @@ iris %>%
desctable(stats = list("N" = length,
"%/Mean" = is.factor ~ percent | (is.normal ~ mean),
"Median" = is.normal ~ NA | median)) %>%
- datatable
+ datatable()
```
@@ -199,7 +199,7 @@ mtlabels <- c(mpg = "Miles/(US) gallon",
mtcars %>%
dplyr::mutate(am = factor(am, labels = c("Automatic", "Manual"))) %>%
desctable(labels = mtlabels) %>%
- datatable
+ datatable()
```
@@ -216,7 +216,7 @@ It uses the well known `group_by` function from **dplyr**:
```{r}
iris %>%
group_by(Species) %>%
- desctable -> iris_by_Species
+ desctable() -> iris_by_Species
iris_by_Species
```
@@ -237,8 +237,8 @@ You can specify groups based on any variable, not only factors:
# With pander output
mtcars %>%
group_by(cyl) %>%
- desctable %>%
- pander
+ desctable() %>%
+ pander()
```
Also with conditions:
@@ -246,8 +246,8 @@ Also with conditions:
# With datatable output
iris %>%
group_by(Petal.Length > 5) %>%
- desctable %>%
- datatable
+ desctable() %>%
+ datatable()
```
@@ -257,8 +257,8 @@ And even on multiple nested groups:
mtcars %>%
dplyr::mutate(am = factor(am, labels = c("Automatic", "Manual"))) %>%
group_by(vs, am, cyl) %>%
- desctable %>%
- datatable
+ desctable() %>%
+ datatable()
```
@@ -304,7 +304,7 @@ This function will be used on every variable and every grouping factor to determ
iris %>%
group_by(Species) %>%
desctable(tests = tests_auto) %>%
- datatable
+ datatable()
```
@@ -325,7 +325,7 @@ iris %>%
group_by(Petal.Length > 5) %>%
desctable(tests = list(.auto = tests_auto,
Species = ~chisq.test)) %>%
- datatable
+ datatable()
```
@@ -335,7 +335,7 @@ mtcars %>%
group_by(am) %>%
desctable(tests = list(.default = ~wilcox.test,
mpg = ~t.test)) %>%
- datatable
+ datatable()
```
@@ -360,7 +360,7 @@ mtcars %>%
"Sum of squares" = function(x) sum(x^2),
"Q1" = . %>% quantile(prob = .25),
"Q3" = purrr::partial(quantile, probs = .75))) %>%
- datatable
+ datatable()
```
@@ -372,7 +372,7 @@ iris %>%
Sepal.Width = ~function(f) oneway.test(f, var.equal = F),
Petal.Length = ~. %>% oneway.test(var.equal = T),
Sepal.Length = ~purrr::partial(oneway.test, var.equal = T))) %>%
- datatable
+ datatable()
```
@@ -387,5 +387,5 @@ bladder %>%
group_by(rx) %>%
desctable(tests = list(.default = ~wilcox.test,
surv = ~. %>% survdiff %>% .$chisq %>% pchisq(1, lower.tail = F) %>% list(p.value = .))) %>%
- datatable
+ datatable()
```