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na freq, removed factors

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dr. M.S. (Matthijs) Berends
2018-10-23 09:42:26 +02:00
parent 9c56257da1
commit 299c5bea43
4 changed files with 76 additions and 115 deletions
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@@ -361,69 +361,36 @@ freq(mydata$myvariable)
mydata %>% freq(myvariable)
```
Factors sort on item by default:
Frequency are of course sorted by count at default:
```r
septic_patients %>% freq(hospital_id)
# Frequency table of `hospital_id`
# Class: factor (numeric)
# Length: 2000 (of which NA: 0 = 0.00%)
# Unique: 4
#
# Item Count Percent Cum. Count Cum. Percent (Factor Level)
# --- ----- ------ -------- ----------- ------------- ---------------
# 1 A 321 16.1% 321 16.1% 1
# 2 B 663 33.1% 984 49.2% 2
# 3 C 254 12.7% 1238 61.9% 3
# 4 D 762 38.1% 2000 100.0% 4
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------ -------- ----------- -------------
# 1 D 762 38.1% 762 38.1%
# 2 B 663 33.1% 1425 71.2%
# 3 A 321 16.1% 1746 87.3%
# 4 C 254 12.7% 2000 100.0%
```
This can be changed with the `sort.count` parameter:
```r
septic_patients %>% freq(hospital_id, sort.count = TRUE)
# Frequency table of `hospital_id`
septic_patients %>% freq(hospital_id, sort.count = FALSE)
# Class: factor (numeric)
# Length: 2000 (of which NA: 0 = 0.00%)
# Unique: 4
#
# Item Count Percent Cum. Count Cum. Percent (Factor Level)
# --- ----- ------ -------- ----------- ------------- ---------------
# 1 D 762 38.1% 762 38.1% 4
# 2 B 663 33.1% 1425 71.2% 2
# 3 A 321 16.1% 1746 87.3% 1
# 4 C 254 12.7% 2000 100.0% 3
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------ -------- ----------- -------------
# 1 A 321 16.1% 321 16.1%
# 2 B 663 33.1% 984 49.2%
# 3 C 254 12.7% 1238 61.9%
# 4 D 762 38.1% 2000 100.0%
```
All other types, like numbers, characters and dates, sort on count by default:
```r
septic_patients %>% freq(date)
# Frequency table of `date`
# Class: Date
# Length: 2000 (of which NA: 0 = 0.0%)
# Unique: 1151
#
# Oldest: 2 January 2002
# Newest: 28 December 2017 (+5839)
# Median: 31 July 2009 (~47%)
#
# Item Count Percent Cum. Count Cum. Percent
# --- ----------- ------ -------- ----------- -------------
# 1 2016-05-21 10 0.5% 10 0.5%
# 2 2004-11-15 8 0.4% 18 0.9%
# 3 2013-07-29 8 0.4% 26 1.3%
# 4 2017-06-12 8 0.4% 34 1.7%
# 5 2015-11-19 7 0.4% 41 2.1%
# 6 2005-12-22 6 0.3% 47 2.4%
# 7 2015-10-12 6 0.3% 53 2.6%
# 8 2002-02-27 5 0.2% 58 2.9%
# 9 2003-10-20 5 0.2% 63 3.1%
# 10 2004-02-02 5 0.2% 68 3.4%
# 11 2004-02-18 5 0.2% 73 3.6%
# 12 2004-06-22 5 0.2% 78 3.9%
# 13 2004-12-01 5 0.2% 83 4.2%
# 14 2005-08-16 5 0.2% 88 4.4%
# 15 2005-09-01 5 0.2% 93 4.7%
# [ reached getOption("max.print.freq") -- omitted 1136 entries, n = 1907 (95.3%) ]
```
For numeric values, some extra descriptive statistics will be calculated:
```r
freq(runif(n = 10, min = 1, max = 5))