numSummary: Numerical Summary

In webr: Data and Functions for Web-Based Analysis

Description

Numerical Summary

Usage

numSummary(x, ..., digits = 2, lang = "en")

numSummary1(x, ..., digits = 2, lang = "en")

numSummary2(x, ..., digits = 2, lang = "en")

Arguments

x	A numeric vector or a data.frame or a grouped_df
...	further arguments to be passed
digits	integer indicating the number of decimal places
lang	Language. choices are one of c("en","kor")

Functions

• numSummary1: Numerical Summary of a data.frame or a vector

• numSummary2: Numerical Summary of a grouped_df

Examples

require(moonBook)
require(magrittr)
require(dplyr)
require(rrtable)
require(webr)
require(tibble)
numSummary(acs)
numSummary(acs$age)
numSummary(acs,age,EF)
acs %>% group_by(sex) %>% numSummary(age,BMI)
acs %>% group_by(sex) %>% select(age) %>% numSummary
acs %>% group_by(sex) %>% select(age,EF) %>% numSummary
acs %>% group_by(sex,Dx) %>% select(age,EF) %>% numSummary
acs %>% group_by(sex,Dx) %>% select(age) %>% numSummary
#acs %>% group_by(sex,Dx) %>% numSummary(age,EF,lang="kor")

Example output

Loading required package: moonBook
Loading required package: magrittr
Loading required package: 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

Loading required package: rrtable
Welcome to rrtable package
Register inputHandler for chooserInput
Loading required package: tibble
# A tibble: 9 x 13
  vars      n  mean    sd median trimmed   mad   min   max range   skew kurtosis
  <chr> <dbl> <dbl> <dbl>  <dbl>   <dbl> <dbl> <dbl> <dbl> <dbl>  <dbl>    <dbl>
1 age     857  63.3 11.7    64      63.6 13.3   28    91    63   -0.175  -0.566 
2 EF      723  55.8  9.62   58.1    56.8  7.86  18    79    61   -0.978   1.11  
3 heig…   764 163.   9.08  165     164.   7.41 130   185    55   -0.440  -0.0145
4 weig…   766  64.8 11.4    65      64.5 10.4   30   112    82    0.336   0.444 
5 BMI     764  24.3  3.35   24.2    24.2  3.01  15.6  41.4  25.8  0.668   2.12  
6 TC      834 185.  47.8   183     184.  43.0   25   493   468    0.737   3.77  
7 LDLC    833 117.  41.1   114     115.  40.0   15   366   351    0.787   2.33  
8 HDLC    834  38.2 11.1    38      38.0 10.4    4    89    85    0.366   1.46  
9 TG      842 125.  90.9   106.    111.  60.0   11   877   866    3.02   14.9   
# … with 1 more variable: se <dbl>
# A tibble: 1 x 12
      n  mean    sd median trimmed   mad   min   max range   skew kurtosis    se
  <dbl> <dbl> <dbl>  <dbl>   <dbl> <dbl> <dbl> <dbl> <dbl>  <dbl>    <dbl> <dbl>
1   857  63.3  11.7     64    63.6  13.3    28    91    63 -0.175   -0.566 0.400
# A tibble: 2 x 13
  vars      n  mean    sd median trimmed   mad   min   max range   skew kurtosis
  <chr> <dbl> <dbl> <dbl>  <dbl>   <dbl> <dbl> <dbl> <dbl> <dbl>  <dbl>    <dbl>
1 age     857  63.3 11.7    64      63.6 13.3     28    91    63 -0.175   -0.566
2 EF      723  55.8  9.62   58.1    56.8  7.86    18    79    61 -0.978    1.11 
# … with 1 more variable: se <dbl>
# A tibble: 4 x 14
# Groups:   sex [2]
  sex   vars      n  mean    sd median trimmed   mad   min   max range    skew
  <chr> <chr> <dbl> <dbl> <dbl>  <dbl>   <dbl> <dbl> <dbl> <dbl> <dbl>   <dbl>
1 Male  age     570  60.6 11.2    61      60.6 11.9   28    91    63   -0.0148
2 Male  BMI     509  24.3  3.24   24.2    24.2  2.98  16.3  41.4  25.1  0.616 
3 Fema… age     287  68.7 10.7    70      69.4 10.4   39    90    51   -0.593 
4 Fema… BMI     255  24.2  3.56   24.0    24.1  3.13  15.6  41.2  25.6  0.751 
# … with 2 more variables: kurtosis <dbl>, se <dbl>
Warning message:
`cols` is now required when using unnest().
Please use `cols = c(summary)` 
Adding missing grouping variables: `sex`
# A tibble: 2 x 13
# Groups:   sex [2]
  sex       n  mean    sd median trimmed   mad   min   max range    skew
  <chr> <dbl> <dbl> <dbl>  <dbl>   <dbl> <dbl> <dbl> <dbl> <dbl>   <dbl>
1 Male    570  60.6  11.2     61    60.6  11.9    28    91    63 -0.0148
2 Fema…   287  68.7  10.7     70    69.4  10.4    39    90    51 -0.593 
# … with 2 more variables: kurtosis <dbl>, se <dbl>
Warning message:
`cols` is now required when using unnest().
Please use `cols = c(summary)` 
Adding missing grouping variables: `sex`
# A tibble: 4 x 14
# Groups:   sex [2]
  sex   vars      n  mean    sd median trimmed   mad   min   max range    skew
  <chr> <chr> <dbl> <dbl> <dbl>  <dbl>   <dbl> <dbl> <dbl> <dbl> <dbl>   <dbl>
1 Male  age     570  60.6 11.2    61      60.6 11.9   28      91  63   -0.0148
2 Male  EF      483  55.6  9.40   57.3    56.4  8.01  18      79  61   -0.789 
3 Fema… age     287  68.7 10.7    70      69.4 10.4   39      90  51   -0.593 
4 Fema… EF      240  56.3 10.1    59.2    57.6  7.19  18.4    75  56.6 -1.30  
# … with 2 more variables: kurtosis <dbl>, se <dbl>
Warning message:
`cols` is now required when using unnest().
Please use `cols = c(summary)` 
Adding missing grouping variables: `sex`, `Dx`
# A tibble: 12 x 15
# Groups:   sex, Dx [6]
   sex   Dx    vars      n  mean    sd median trimmed   mad   min   max range
   <chr> <chr> <chr> <dbl> <dbl> <dbl>  <dbl>   <dbl> <dbl> <dbl> <dbl> <dbl>
 1 Male  STEMI age     220  59.4 11.7    59.5    59.4 11.1   30    86    56  
 2 Male  STEMI EF      195  52.4  8.90   54      52.9  8.45  18    73.6  55.6
 3 Fema… STEMI age      84  69.1 10.4    70      70.0 10.4   42    89    47  
 4 Fema… STEMI EF       77  52.3 10.9    55.7    53.7  9.04  18.4  67.1  48.7
 5 Male  NSTE… age     103  61.1 11.6    59      61.3 13.3   28    85    57  
 6 Male  NSTE… EF       94  55.1  9.42   58      55.9  7.12  21.8  74    52.2
 7 Fema… Unst… age     153  67.7 10.7    70      68.3  8.90  39    90    51  
 8 Fema… Unst… EF      118  59.4  8.76   61.1    60.8  5.49  22    71.9  49.9
 9 Male  Unst… age     247  61.4 10.6    61      61.4 10.4   35    91    56  
10 Male  Unst… EF      194  59.1  8.67   60      60.2  5.93  24.7  79    54.3
11 Fema… NSTE… age      50  70.9 11.4    74.5    71.9  8.90  42    88    46  
12 Fema… NSTE… EF       45  54.8  9.10   57      55.3  9.79  36.8  75    38.2
# … with 3 more variables: skew <dbl>, kurtosis <dbl>, se <dbl>
Warning message:
`cols` is now required when using unnest().
Please use `cols = c(summary)` 
Adding missing grouping variables: `sex`, `Dx`
# A tibble: 6 x 14
# Groups:   sex, Dx [6]
  sex   Dx        n  mean    sd median trimmed   mad   min   max range     skew
  <chr> <chr> <dbl> <dbl> <dbl>  <dbl>   <dbl> <dbl> <dbl> <dbl> <dbl>    <dbl>
1 Male  STEMI   220  59.4  11.7   59.5    59.4 11.1     30    86    56  0.00433
2 Fema… STEMI    84  69.1  10.4   70      70.0 10.4     42    89    47 -0.654  
3 Male  NSTE…   103  61.1  11.6   59      61.3 13.3     28    85    57 -0.110  
4 Fema… Unst…   153  67.7  10.7   70      68.3  8.90    39    90    51 -0.540  
5 Male  Unst…   247  61.4  10.6   61      61.4 10.4     35    91    56  0.0710 
6 Fema… NSTE…    50  70.9  11.4   74.5    71.9  8.90    42    88    46 -0.721  
# … with 2 more variables: kurtosis <dbl>, se <dbl>
Warning message:
`cols` is now required when using unnest().
Please use `cols = c(summary)` 

webr documentation built on March 26, 2020, 6:22 p.m.