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library(datasets)

head(tobacco)

summary(tobacco)

gender age age.gr BMI smoker
F :489 Min. :18.0 18-34:258 Min. : 8.826 Yes:298
M :489 1st Qu.:34.0 35-50:241 1st Qu.:22.927 No :702
NA’s: 22 Median :50.0 51-70:317 Median :25.620
Mean :49.6 71 + :159 Mean :25.731
3rd Qu.:66.0 NA’s : 25 3rd Qu.:28.649
Max. :80.0 Max. :39.439
NA’s :25 NA’s :26
cigs.per.day diseased disease samp.wgts
Min. : 0.000 Yes:224 Length:1000 Min. :0.8614
1st Qu.: 0.000 No :776 Class :character 1st Qu.:0.8614
Median : 0.000 Mode :character Median :1.0442
Mean : 6.782 Mean :1.0000
3rd Qu.:11.000 3rd Qu.:1.0494
Max. :40.000 Max. :1.0625
NA’s :35

by(tobacco,tobacco$gender, summary)

tobacco\(gender: F gender age age.gr BMI smoker F:489 Min. :18.00 18-34:123 Min. : 9.009 Yes:147 M: 0 1st Qu.:34.00 35-50:118 1st Qu.:22.983 No :342 Median :50.00 51-70:157 Median :25.867 Mean :49.56 71 + : 77 Mean :26.099 3rd Qu.:66.00 NA's : 14 3rd Qu.:29.472 Max. :80.00 Max. :39.439 NA's :14 NA's :14 cigs.per.day diseased disease samp.wgts Min. : 0.000 Yes:111 Length:489 Min. :0.8614 1st Qu.: 0.000 No :378 Class :character 1st Qu.:0.8614 Median : 0.000 Mode :character Median :1.0442 Mean : 6.876 Mean :0.9998 3rd Qu.:10.250 3rd Qu.:1.0494 Max. :40.000 Max. :1.0625 NA's :21 -------------------------------------------------------- tobacco\)gender: M gender age age.gr BMI smoker
F: 0 Min. :18.00 18-34:130 Min. : 8.826 Yes:143
M:489 1st Qu.:34.00 35-50:118 1st Qu.:22.517 No :346
Median :49.50 51-70:151 Median :25.140
Mean :49.58 71 + : 79 Mean :25.308
3rd Qu.:66.00 NA’s : 11 3rd Qu.:27.956
Max. :80.00 Max. :36.761
NA’s :11 NA’s :12
cigs.per.day diseased disease samp.wgts
Min. : 0.000 Yes:110 Length:489 Min. :0.8614
1st Qu.: 0.000 No :379 Class :character 1st Qu.:0.8614
Median : 0.000 Mode :character Median :1.0442
Mean : 6.722 Mean :0.9998
3rd Qu.:11.000 3rd Qu.:1.0494
Max. :40.000 Max. :1.0625
NA’s :14

summary tool

print(dfSummary(tobacco, method = "browser", plain.ascii = FALSE, style="grid", valid.col = FALSE, tmp.img.dir = "/tmp"))

temporary images written to 'D:\tmp'

Data Frame Summary

tobacco
Dimensions: 1000 x 9
Duplicates: 2

No	Variable	Stats / Values	Freqs (% of Valid)	Graph	Missing
1	gender [factor]	1. F 2. M	489 (50.0%) 489 (50.0%)		22 (2.2%)
2	age [numeric]	Mean (sd) : 49.6 (18.3) min < med < max: 18 < 50 < 80 IQR (CV) : 32 (0.4)	63 distinct values		25 (2.5%)
3	age.gr [factor]	1. 18-34 2. 35-50 3. 51-70 4. 71 +	258 (26.5%) 241 (24.7%) 317 (32.5%) 159 (16.3%)		25 (2.5%)
4	BMI [numeric]	Mean (sd) : 25.7 (4.5) min < med < max: 8.8 < 25.6 < 39.4 IQR (CV) : 5.7 (0.2)	974 distinct values		26 (2.6%)
5	smoker [factor]	1. Yes 2. No	298 (29.8%) 702 (70.2%)		0 (0%)
6	cigs.per.day [numeric]	Mean (sd) : 6.8 (11.9) min < med < max: 0 < 0 < 40 IQR (CV) : 11 (1.8)	37 distinct values		35 (3.5%)
7	diseased [factor]	1. Yes 2. No	224 (22.4%) 776 (77.6%)		0 (0%)
8	disease [character]	1. Hypertension 2. Cancer 3. Cholesterol 4. Heart 5. Pulmonary 6. Musculoskeletal 7. Diabetes 8. Hearing 9. Digestive 10. Hypotension [ 3 others ]	36 (16.2%) 34 (15.3%) 21 ( 9.5%) 20 ( 9.0%) 20 ( 9.0%) 19 ( 8.6%) 14 ( 6.3%) 14 ( 6.3%) 12 ( 5.4%) 11 ( 5.0%) 21 ( 9.5%)		778 (77.8%)
9	samp.wgts [numeric]	Mean (sd) : 1 (0.1) min < med < max: 0.9 < 1 < 1.1 IQR (CV) : 0.2 (0.1)	0.86!: 267 (26.7%) 1.04!: 249 (24.9%) 1.05!: 324 (32.4%) 1.06!: 160 (16.0%) ! rounded		0 (0%)

freq(iris$Species, plain.ascii = FALSE, style = "rmarkdown")

Frequencies

iris$Species
Type: Factor

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
setosa	50	33.33	33.33	33.33	33.33
versicolor	50	33.33	66.67	33.33	66.67
virginica	50	33.33	100.00	33.33	100.00
<NA>	0			0.00	100.00
Total	150	100.00	100.00	100.00	100.00

freq(iris$Species, report.nas = FALSE, plain.ascii = FALSE, style = "rmarkdown")

Frequencies

iris$Species
Type: Factor

	Freq	%	% Cum.
setosa	50	33.33	33.33
versicolor	50	33.33	66.67
virginica	50	33.33	100.00
Total	150	100.00	100.00

descr(tobacco, style = "rmarkdown")

Non-numerical variable(s) ignored: gender, age.gr, smoker, diseased, disease

with(tobacco, print(ctable(smoker, diseased), method = 'render'))

with(tobacco, 
     print(ctable(smoker, diseased, prop = 'n', totals = FALSE), 
           omit.headings = TRUE, method = "render"))