inst/doc/using_visdat.R

In visdat: Preliminary Visualisation of Data

## ----setup, echo = FALSE, include = FALSE-------------------------------------

knitr::opts_chunk$set(fig.width = 5,
                      fig.height = 4)


## ----head-iris----------------------------------------------------------------

head(iris)


## ----glimpse------------------------------------------------------------------
library(dplyr)
glimpse(iris)


## ----visdat-glimpse-----------------------------------------------------------
library(visdat)

glimpse(typical_data)


## ----load-data----------------------------------------------------------------

vis_dat(typical_data)


## ----example-vis-miss---------------------------------------------------------

vis_miss(typical_data)


## ----vis_dat------------------------------------------------------------------

vis_dat(airquality)


## ----visdat-typical-----------------------------------------------------------

vis_dat(typical_data)

vis_dat(typical_data, 
        sort_type = FALSE)


## ----vis_miss-----------------------------------------------------------------

vis_miss(airquality)


## ----vismiss-new-data---------------------------------------------------------

df_test <- data.frame(x1 = 1:10000,
                      x2 = rep("A", 10000),
                      x3 = c(rep(1L, 9999), NA))

vis_miss(df_test)


## ----vismiss-mtcars-----------------------------------------------------------

df_test <- data.frame(x1 = 1:10000,
                      x2 = rep("tidy", 10000),
                      x3 = rep("data", 10000))

vis_miss(df_test)


## ----vismiss------------------------------------------------------------------

vis_miss(airquality,
         sort_miss = TRUE)


## ----vis_miss-cluster---------------------------------------------------------

vis_miss(airquality, 
         cluster = TRUE)


## ----vis-compare-iris---------------------------------------------------------
set.seed(2019-04-03-1107)
chickwts_diff <- chickwts
chickwts_diff[sample(1:nrow(chickwts), 30),sample(1:ncol(chickwts), 2)] <- NA

vis_compare(chickwts_diff, chickwts)


## ----vis-compare-error, eval = FALSE------------------------------------------
#  
#  chickwts_diff_2 <- chickwts
#  chickwts_diff_2$new_col <- chickwts_diff_2$weight*2
#  
#  vis_compare(chickwts, chickwts_diff_2)
#  # Error in vis_compare(chickwts, chickwts_diff_2) :
#  #   Dimensions of df1 and df2 are not the same. vis_compare requires dataframes of identical dimensions.

## ----vis-expect---------------------------------------------------------------

vis_expect(airquality, ~.x >= 25)


## ----vis-expect-bad-strings---------------------------------------------------

bad_data <- data.frame(x = c(rnorm(100), rep("N/A", 10)),
                       y = c(rep("N A ", 30), rnorm(80)))

vis_expect(bad_data, ~.x %in% c("N/A", "N A "))

## ----vis-cor------------------------------------------------------------------

vis_cor(airquality)


## ----vis-cor-spearman---------------------------------------------------------

vis_cor(airquality, cor_method = "spearman")


## ----vis-cor-na-action--------------------------------------------------------

vis_cor(airquality,
        na_action = "complete.obs")


## ----vis-value----------------------------------------------------------------
vis_value(airquality)

## ----diamonds-error, eval = FALSE---------------------------------------------
#  vis_value(iris)

## ----diamonds-error-subset----------------------------------------------------

iris %>%
  select_if(is.numeric) %>%
  vis_value()

## ----airquality-arrange-------------------------------------------------------
airquality %>%
  arrange(Wind) %>%
  vis_value()

## ----vis-binary---------------------------------------------------------------
vis_binary(dat_bin)

## ----create-messy-vec---------------------------------------------------------

messy_vector <- c(TRUE,
                  T,
                  "TRUE",
                  "T",
                  "01/01/01",
                  "01/01/2001",
                  NA,
                  NaN,
                  "NA",
                  "Na",
                  "na",
                  "10",
                  10,
                  "10.1",
                  10.1,
                  "abc",
                  "$%TG")

set.seed(1114)
messy_df <- data.frame(var1 = messy_vector,
                       var2 = sample(messy_vector),
                       var3 = sample(messy_vector))


## ----vis-guess-messy-df, fig.show='hold', out.width='50%'---------------------

vis_guess(messy_df)
vis_dat(messy_df)


## ----intx, eval = FALSE-------------------------------------------------------
#  
#  library(plotly)
#  ggplotly(vis_dat(airquality))
#  ggplotly(vis_miss(airquality))
#  ggplotly(vis_guess(airquality))
#