Homepage: https://kwstat.github.io/lucid
Repository: https://github.com/kwstat/lucid
The ‘lucid’ package provides a simple function to improve the format of floating-point numbers for humans. The ‘lucid()’ function is primarily a formatting function similar to ‘round’ and ‘signif’, but output is always character.
Note: The lucid package was created before the tibble package. The tibble package now uses a similar style of formatting dataframes.
Installation
# Install the released version from CRAN:
install.packages("lucid")
# Install the development version from GitHub:
install.packages("devtools")
devtools::install_github("kwstat/lucid")Usage
In the short example below, a separate regression line is fit to each of five trees’ circumference versus age. The default output is difficult to interpret quickly. The lucid function makes the results much cleaner by reducing visual clutter and aligning decimals.
require(lucid)
require(dplyr)
require(broom)
# Fit a separate regression line to each tree.
# Use `as.data.frame` to remove formatting done by `tibble`.
Orange %>% group_by(Tree) %>% do(tidy(lm(circumference ~ age, data=.))) %>% as.data.frame
Source: local data frame [10 x 6]
Groups: Tree [5]
Tree term estimate std.error statistic p.value
<ord> <chr> <dbl> <dbl> <dbl> <dbl>
1 3 (Intercept) 19.20353638 5.863410215 3.275148 2.207255e-02
2 3 age 0.08111158 0.005628105 14.411881 2.901046e-05
3 1 (Intercept) 24.43784664 6.543311039 3.734783 1.350409e-02
4 1 age 0.08147716 0.006280721 12.972581 4.851902e-05
5 5 (Intercept) 8.75834459 8.176436207 1.071169 3.330518e-01
6 5 age 0.11102891 0.007848307 14.146861 3.177093e-05
7 2 (Intercept) 19.96090337 9.352361105 2.134317 8.593318e-02
8 2 age 0.12506176 0.008977041 13.931291 3.425041e-05
9 4 (Intercept) 14.63762022 11.233762751 1.303002 2.493507e-01
10 4 age 0.13517222 0.010782940 12.535748 5.733090e-05
# Now extend the pipe to include 'lucid'
Orange %>% group_by(Tree) %>% do(tidy(lm(circumference ~ age, data=.))) %>% as.data.frame %>% lucid
# Note: `tibble` now uses formatting almost identical to `lucid`
# Orange %>% group_by(Tree) %>% do(tidy(lm(circumference ~ age, data=.)))
Source: local data frame [10 x 6]
Groups: Tree [5]
Tree term estimate std.error statistic p.value
<ord> <chr> <chr> <chr> <chr> <chr>
1 3 (Intercept) 19.2 5.86 3.28 0.0221
2 3 age 0.0811 0.00563 14.4 0.0000290
3 1 (Intercept) 24.4 6.54 3.73 0.0135
4 1 age 0.0815 0.00628 13 0.0000485
5 5 (Intercept) 8.76 8.18 1.07 0.333
6 5 age 0.111 0.00785 14.1 0.0000318
7 2 (Intercept) 20 9.35 2.13 0.0859
8 2 age 0.125 0.00898 13.9 0.0000343
9 4 (Intercept) 14.6 11.2 1.3 0.249
10 4 age 0.135 0.0108 12.5 0.0000573