Air Quality Data Analysis

SK ENAMUL HUDA

Individula Assignement

library(tidyverse)

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## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.1.0     
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library(dplyr)
library(gtsummary)

airquality %>% 
tbl_summary()

Characteristic	N = 1531
Ozone	32 (18, 64)
Unknown	37
Solar.R	205 (115, 259)
Unknown	7
Wind	9.7 (7.4, 11.5)
Temp	79 (72, 85)
Month
5	31 (20%)
6	30 (20%)
7	31 (20%)
8	31 (20%)
9	30 (20%)
Day	16 (8, 23)
1 Median (Q1, Q3); n (%)

airquality <-  airquality %>% 
  select(Wind, Temp, Ozone, Solar.R)
airquality

##     Wind Temp Ozone Solar.R
## 1    7.4   67    41     190
## 2    8.0   72    36     118
## 3   12.6   74    12     149
## 4   11.5   62    18     313
## 5   14.3   56    NA      NA
## 6   14.9   66    28      NA
## 7    8.6   65    23     299
## 8   13.8   59    19      99
## 9   20.1   61     8      19
## 10   8.6   69    NA     194
## 11   6.9   74     7      NA
## 12   9.7   69    16     256
## 13   9.2   66    11     290
## 14  10.9   68    14     274
## 15  13.2   58    18      65
## 16  11.5   64    14     334
## 17  12.0   66    34     307
## 18  18.4   57     6      78
## 19  11.5   68    30     322
## 20   9.7   62    11      44
## 21   9.7   59     1       8
## 22  16.6   73    11     320
## 23   9.7   61     4      25
## 24  12.0   61    32      92
## 25  16.6   57    NA      66
## 26  14.9   58    NA     266
## 27   8.0   57    NA      NA
## 28  12.0   67    23      13
## 29  14.9   81    45     252
## 30   5.7   79   115     223
## 31   7.4   76    37     279
## 32   8.6   78    NA     286
## 33   9.7   74    NA     287
## 34  16.1   67    NA     242
## 35   9.2   84    NA     186
## 36   8.6   85    NA     220
## 37  14.3   79    NA     264
## 38   9.7   82    29     127
## 39   6.9   87    NA     273
## 40  13.8   90    71     291
## 41  11.5   87    39     323
## 42  10.9   93    NA     259
## 43   9.2   92    NA     250
## 44   8.0   82    23     148
## 45  13.8   80    NA     332
## 46  11.5   79    NA     322
## 47  14.9   77    21     191
## 48  20.7   72    37     284
## 49   9.2   65    20      37
## 50  11.5   73    12     120
## 51  10.3   76    13     137
## 52   6.3   77    NA     150
## 53   1.7   76    NA      59
## 54   4.6   76    NA      91
## 55   6.3   76    NA     250
## 56   8.0   75    NA     135
## 57   8.0   78    NA     127
## 58  10.3   73    NA      47
## 59  11.5   80    NA      98
## 60  14.9   77    NA      31
## 61   8.0   83    NA     138
## 62   4.1   84   135     269
## 63   9.2   85    49     248
## 64   9.2   81    32     236
## 65  10.9   84    NA     101
## 66   4.6   83    64     175
## 67  10.9   83    40     314
## 68   5.1   88    77     276
## 69   6.3   92    97     267
## 70   5.7   92    97     272
## 71   7.4   89    85     175
## 72   8.6   82    NA     139
## 73  14.3   73    10     264
## 74  14.9   81    27     175
## 75  14.9   91    NA     291
## 76  14.3   80     7      48
## 77   6.9   81    48     260
## 78  10.3   82    35     274
## 79   6.3   84    61     285
## 80   5.1   87    79     187
## 81  11.5   85    63     220
## 82   6.9   74    16       7
## 83   9.7   81    NA     258
## 84  11.5   82    NA     295
## 85   8.6   86    80     294
## 86   8.0   85   108     223
## 87   8.6   82    20      81
## 88  12.0   86    52      82
## 89   7.4   88    82     213
## 90   7.4   86    50     275
## 91   7.4   83    64     253
## 92   9.2   81    59     254
## 93   6.9   81    39      83
## 94  13.8   81     9      24
## 95   7.4   82    16      77
## 96   6.9   86    78      NA
## 97   7.4   85    35      NA
## 98   4.6   87    66      NA
## 99   4.0   89   122     255
## 100 10.3   90    89     229
## 101  8.0   90   110     207
## 102  8.6   92    NA     222
## 103 11.5   86    NA     137
## 104 11.5   86    44     192
## 105 11.5   82    28     273
## 106  9.7   80    65     157
## 107 11.5   79    NA      64
## 108 10.3   77    22      71
## 109  6.3   79    59      51
## 110  7.4   76    23     115
## 111 10.9   78    31     244
## 112 10.3   78    44     190
## 113 15.5   77    21     259
## 114 14.3   72     9      36
## 115 12.6   75    NA     255
## 116  9.7   79    45     212
## 117  3.4   81   168     238
## 118  8.0   86    73     215
## 119  5.7   88    NA     153
## 120  9.7   97    76     203
## 121  2.3   94   118     225
## 122  6.3   96    84     237
## 123  6.3   94    85     188
## 124  6.9   91    96     167
## 125  5.1   92    78     197
## 126  2.8   93    73     183
## 127  4.6   93    91     189
## 128  7.4   87    47      95
## 129 15.5   84    32      92
## 130 10.9   80    20     252
## 131 10.3   78    23     220
## 132 10.9   75    21     230
## 133  9.7   73    24     259
## 134 14.9   81    44     236
## 135 15.5   76    21     259
## 136  6.3   77    28     238
## 137 10.9   71     9      24
## 138 11.5   71    13     112
## 139  6.9   78    46     237
## 140 13.8   67    18     224
## 141 10.3   76    13      27
## 142 10.3   68    24     238
## 143  8.0   82    16     201
## 144 12.6   64    13     238
## 145  9.2   71    23      14
## 146 10.3   81    36     139
## 147 10.3   69     7      49
## 148 16.6   63    14      20
## 149  6.9   70    30     193
## 150 13.2   77    NA     145
## 151 14.3   75    14     191
## 152  8.0   76    18     131
## 153 11.5   68    20     223

hist(airquality$Wind, main = "Wind Distribution", xlab = "Wind", col = "lightblue", border = "black")

barplot(table(airquality$Solar.R), main = "Solar Distribution", xlab = "Solar.R", ylab = "Frequency", col = "lightgreen")

airquality <- airquality %>%
  mutate(Temp_group = case_when(
    Temp <= 70 ~ "Low",
    Temp > 70 & Temp <= 85 ~ "Medium",
    Temp > 85 ~ "High"
  ))

install.packages("tidyverse")

## Warning: package 'tidyverse' is in use and will not be installed

library(tidyverse)

airquality %>%
  tbl_summary(by = Temp)

Characteristic	56 N = 11	57 N = 31	58 N = 21	59 N = 21	61 N = 31	62 N = 21	63 N = 11	64 N = 21	65 N = 21	66 N = 31	67 N = 41	68 N = 41	69 N = 31	70 N = 11	71 N = 31	72 N = 31	73 N = 51	74 N = 41	75 N = 41	76 N = 91	77 N = 71	78 N = 61	79 N = 61	80 N = 51	81 N = 111	82 N = 91	83 N = 41	84 N = 51	85 N = 51	86 N = 71	87 N = 51	88 N = 31	89 N = 21	90 N = 31	91 N = 21	92 N = 51	93 N = 31	94 N = 21	96 N = 11	97 N = 11
Wind	14.3 (14.3, 14.3)	16.6 (8.0, 18.4)	14.1 (13.2, 14.9)	11.8 (9.7, 13.8)	12.0 (9.7, 20.1)	10.6 (9.7, 11.5)	16.6 (16.6, 16.6)	12.1 (11.5, 12.6)	8.9 (8.6, 9.2)	12.0 (9.2, 14.9)	12.9 (9.7, 15.0)	11.2 (10.6, 11.5)	9.7 (8.6, 10.3)	6.9 (6.9, 6.9)	10.9 (9.2, 11.5)	14.3 (8.0, 20.7)	11.5 (10.3, 14.3)	8.3 (6.9, 11.2)	11.8 (9.5, 13.5)	7.4 (6.3, 10.3)	13.2 (6.3, 14.9)	9.5 (8.0, 10.3)	10.6 (6.3, 11.5)	11.5 (10.9, 13.8)	9.7 (6.9, 14.9)	8.6 (8.0, 10.3)	7.7 (6.0, 9.5)	9.2 (6.3, 10.9)	8.6 (8.0, 9.2)	8.6 (7.4, 11.5)	6.9 (5.1, 7.4)	5.7 (5.1, 7.4)	5.7 (4.0, 7.4)	10.3 (8.0, 13.8)	10.9 (6.9, 14.9)	6.3 (5.7, 8.6)	4.6 (2.8, 10.9)	4.3 (2.3, 6.3)	6.3 (6.3, 6.3)	9.7 (9.7, 9.7)
Ozone	NA (NA, NA)	6 (6, 6)	18 (18, 18)	10 (1, 19)	8 (4, 32)	15 (11, 18)	14 (14, 14)	14 (13, 14)	22 (20, 23)	28 (11, 34)	23 (18, 41)	22 (17, 27)	12 (7, 16)	30 (30, 30)	13 (9, 23)	36 (9, 37)	12 (11, 18)	12 (7, 16)	18 (14, 21)	20 (13, 23)	22 (21, 25)	38 (27, 45)	59 (45, 115)	20 (7, 65)	42 (32, 48)	23 (16, 29)	64 (40, 64)	61 (32, 135)	56 (42, 86)	63 (50, 78)	57 (43, 73)	80 (77, 82)	104 (85, 122)	89 (71, 110)	96 (96, 96)	97 (78, 97)	82 (73, 91)	102 (85, 118)	84 (84, 84)	76 (76, 76)
Unknown	1	2	1	0	0	0	0	0	0	0	1	0	1	0	0	0	1	1	2	3	3	2	3	2	1	2	1	2	1	1	1	1	0	0	1	2	1	0	0	0
Solar.R	NA (NA, NA)	72 (66, 78)	166 (65, 266)	54 (8, 99)	25 (19, 92)	179 (44, 313)	20 (20, 20)	286 (238, 334)	168 (37, 299)	299 (290, 307)	207 (102, 233)	256 (231, 298)	194 (49, 256)	193 (193, 193)	24 (14, 112)	118 (36, 284)	259 (120, 264)	149 (7, 287)	211 (163, 243)	131 (91, 250)	150 (71, 238)	229 (190, 244)	218 (64, 264)	157 (98, 252)	236 (139, 254)	148 (127, 273)	214 (157, 284)	186 (101, 269)	222 (220, 236)	204 (137, 275)	230 (141, 298)	213 (153, 276)	215 (175, 255)	229 (207, 291)	229 (167, 291)	250 (222, 267)	189 (183, 259)	207 (188, 225)	237 (237, 237)	203 (203, 203)
Unknown	1	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	1	1	0	0	0	0	0	0	0	0	0
Temp_group
High	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	7 (100%)	5 (100%)	3 (100%)	2 (100%)	3 (100%)	2 (100%)	5 (100%)	3 (100%)	2 (100%)	1 (100%)	1 (100%)
Low	1 (100%)	3 (100%)	2 (100%)	2 (100%)	3 (100%)	2 (100%)	1 (100%)	2 (100%)	2 (100%)	3 (100%)	4 (100%)	4 (100%)	3 (100%)	1 (100%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)
Medium	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	3 (100%)	3 (100%)	5 (100%)	4 (100%)	4 (100%)	9 (100%)	7 (100%)	6 (100%)	6 (100%)	5 (100%)	11 (100%)	9 (100%)	4 (100%)	5 (100%)	5 (100%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)
1 Median (Q1, Q3); n (%)

install.packages("dplyr")

## Warning: package 'dplyr' is in use and will not be installed

install.packages("gtsummary")

## Warning: package 'gtsummary' is in use and will not be installed

library(dplyr)
library(gtsummary)

airquality %>%
  tbl_summary(
    by = Ozone,
    statistic = list(
      all_continuous() ~ "{mean} ({sd})",
      all_categorical() ~ "{n} / {N} ({p}%)"
    )
  )

## 37 missing rows in the "Ozone" column have been removed.

Characteristic	1 N = 11	4 N = 11	6 N = 11	7 N = 31	8 N = 11	9 N = 31	10 N = 11	11 N = 31	12 N = 21	13 N = 41	14 N = 41	16 N = 41	18 N = 41	19 N = 11	20 N = 41	21 N = 41	22 N = 11	23 N = 61	24 N = 21	27 N = 11	28 N = 31	29 N = 11	30 N = 21	31 N = 11	32 N = 31	34 N = 11	35 N = 21	36 N = 21	37 N = 21	39 N = 21	40 N = 11	41 N = 11	44 N = 31	45 N = 21	46 N = 11	47 N = 11	48 N = 11	49 N = 11	50 N = 11	52 N = 11	59 N = 21	61 N = 11	63 N = 11	64 N = 21	65 N = 11	66 N = 11	71 N = 11	73 N = 21	76 N = 11	77 N = 11	78 N = 21	79 N = 11	80 N = 11	82 N = 11	84 N = 11	85 N = 21	89 N = 11	91 N = 11	96 N = 11	97 N = 21	108 N = 11	110 N = 11	115 N = 11	118 N = 11	122 N = 11	135 N = 11	168 N = 11
Wind	9.7 (NA)	9.7 (NA)	18.4 (NA)	10.5 (3.7)	20.1 (NA)	13.0 (1.8)	14.3 (NA)	11.8 (4.1)	12.1 (0.8)	11.2 (1.1)	13.3 (2.6)	8.0 (1.2)	11.6 (2.6)	13.8 (NA)	10.1 (1.4)	14.2 (2.2)	10.3 (NA)	9.3 (1.7)	10.0 (0.4)	14.9 (NA)	10.9 (4.3)	9.7 (NA)	9.2 (3.3)	10.9 (NA)	12.2 (3.2)	12.0 (NA)	8.9 (2.1)	9.2 (1.6)	14.1 (9.4)	9.2 (3.3)	10.9 (NA)	7.4 (NA)	12.2 (2.4)	12.3 (3.7)	6.9 (NA)	7.4 (NA)	6.9 (NA)	9.2 (NA)	7.4 (NA)	12.0 (NA)	7.8 (2.1)	6.3 (NA)	11.5 (NA)	6.0 (2.0)	9.7 (NA)	4.6 (NA)	13.8 (NA)	5.4 (3.7)	9.7 (NA)	5.1 (NA)	6.0 (1.3)	5.1 (NA)	8.6 (NA)	7.4 (NA)	6.3 (NA)	6.9 (0.8)	10.3 (NA)	4.6 (NA)	6.9 (NA)	6.0 (0.4)	8.0 (NA)	8.0 (NA)	5.7 (NA)	2.3 (NA)	4.0 (NA)	4.1 (NA)	3.4 (NA)
Temp	59 (NA)	61 (NA)	57 (NA)	74 (6)	61 (NA)	75 (6)	73 (NA)	67 (6)	74 (1)	72 (6)	68 (5)	77 (6)	66 (8)	59 (NA)	74 (9)	76 (1)	77 (NA)	73 (7)	71 (4)	81 (NA)	75 (8)	82 (NA)	69 (1)	78 (NA)	75 (13)	66 (NA)	84 (2)	77 (6)	74 (3)	84 (4)	83 (NA)	67 (NA)	82 (4)	80 (1)	78 (NA)	87 (NA)	81 (NA)	85 (NA)	86 (NA)	86 (NA)	80 (1)	84 (NA)	85 (NA)	83 (0)	80 (NA)	87 (NA)	90 (NA)	90 (5)	97 (NA)	88 (NA)	89 (4)	87 (NA)	86 (NA)	88 (NA)	96 (NA)	92 (4)	90 (NA)	93 (NA)	91 (NA)	92 (0)	85 (NA)	90 (NA)	79 (NA)	94 (NA)	89 (NA)	84 (NA)	81 (NA)
Solar.R	8 (NA)	25 (NA)	78 (NA)	49 (1)	19 (NA)	28 (7)	264 (NA)	218 (151)	135 (21)	129 (87)	205 (136)	135 (114)	183 (108)	99 (NA)	148 (105)	235 (32)	71 (NA)	135 (113)	249 (15)	175 (NA)	256 (25)	127 (NA)	258 (91)	244 (NA)	140 (83)	307 (NA)	274 (NA)	129 (15)	282 (4)	203 (170)	314 (NA)	190 (NA)	206 (26)	232 (28)	237 (NA)	95 (NA)	260 (NA)	248 (NA)	275 (NA)	82 (NA)	153 (144)	285 (NA)	220 (NA)	214 (55)	157 (NA)	NA (NA)	291 (NA)	199 (23)	203 (NA)	276 (NA)	197 (NA)	187 (NA)	294 (NA)	213 (NA)	237 (NA)	182 (9)	229 (NA)	189 (NA)	167 (NA)	270 (4)	223 (NA)	207 (NA)	223 (NA)	225 (NA)	255 (NA)	269 (NA)	238 (NA)
Unknown	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Temp_group
High	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 3 (0%)	0 / 1 (0%)	0 / 3 (0%)	0 / 1 (0%)	0 / 3 (0%)	0 / 2 (0%)	0 / 4 (0%)	0 / 4 (0%)	0 / 4 (0%)	0 / 4 (0%)	0 / 1 (0%)	0 / 4 (0%)	0 / 4 (0%)	0 / 1 (0%)	0 / 6 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 3 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 3 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 2 (0%)	0 / 2 (0%)	1 / 2 (50%)	0 / 1 (0%)	0 / 1 (0%)	1 / 3 (33%)	0 / 2 (0%)	0 / 1 (0%)	1 / 1 (100%)	0 / 1 (0%)	0 / 1 (0%)	1 / 1 (100%)	1 / 1 (100%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	1 / 1 (100%)	1 / 1 (100%)	2 / 2 (100%)	1 / 1 (100%)	1 / 1 (100%)	2 / 2 (100%)	1 / 1 (100%)	1 / 1 (100%)	1 / 1 (100%)	1 / 1 (100%)	2 / 2 (100%)	1 / 1 (100%)	1 / 1 (100%)	1 / 1 (100%)	2 / 2 (100%)	0 / 1 (0%)	1 / 1 (100%)	0 / 1 (0%)	1 / 1 (100%)	1 / 1 (100%)	0 / 1 (0%)	0 / 1 (0%)
Low	1 / 1 (100%)	1 / 1 (100%)	1 / 1 (100%)	1 / 3 (33%)	1 / 1 (100%)	0 / 3 (0%)	0 / 1 (0%)	2 / 3 (67%)	0 / 2 (0%)	1 / 4 (25%)	3 / 4 (75%)	1 / 4 (25%)	3 / 4 (75%)	1 / 1 (100%)	2 / 4 (50%)	0 / 4 (0%)	0 / 1 (0%)	2 / 6 (33%)	1 / 2 (50%)	0 / 1 (0%)	1 / 3 (33%)	0 / 1 (0%)	2 / 2 (100%)	0 / 1 (0%)	1 / 3 (33%)	1 / 1 (100%)	0 / 2 (0%)	0 / 2 (0%)	0 / 2 (0%)	0 / 2 (0%)	0 / 1 (0%)	1 / 1 (100%)	0 / 3 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)
Medium	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	2 / 3 (67%)	0 / 1 (0%)	3 / 3 (100%)	1 / 1 (100%)	1 / 3 (33%)	2 / 2 (100%)	3 / 4 (75%)	1 / 4 (25%)	3 / 4 (75%)	1 / 4 (25%)	0 / 1 (0%)	2 / 4 (50%)	4 / 4 (100%)	1 / 1 (100%)	4 / 6 (67%)	1 / 2 (50%)	1 / 1 (100%)	2 / 3 (67%)	1 / 1 (100%)	0 / 2 (0%)	1 / 1 (100%)	2 / 3 (67%)	0 / 1 (0%)	2 / 2 (100%)	2 / 2 (100%)	2 / 2 (100%)	1 / 2 (50%)	1 / 1 (100%)	0 / 1 (0%)	2 / 3 (67%)	2 / 2 (100%)	1 / 1 (100%)	0 / 1 (0%)	1 / 1 (100%)	1 / 1 (100%)	0 / 1 (0%)	0 / 1 (0%)	2 / 2 (100%)	1 / 1 (100%)	1 / 1 (100%)	2 / 2 (100%)	1 / 1 (100%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 1 (0%)	0 / 2 (0%)	1 / 1 (100%)	0 / 1 (0%)	1 / 1 (100%)	0 / 1 (0%)	0 / 1 (0%)	1 / 1 (100%)	1 / 1 (100%)
1 Mean (SD); n / N (%)

library(dplyr)
library(gtsummary)

airquality <- airquality %>%
  mutate(Temp_group = case_when(
    Temp <= 60 ~ "Low",
    Temp > 60 & Temp <= 80 ~ "Medium",
    Temp > 80 ~ "High",
    TRUE ~ "NA"
  ))

airquality %>%
  tbl_summary(by = Temp_group) %>%
  add_p(test = list(all_continuous() ~ "anova"))

## The following errors were returned during `add_p()`:
## ✖ For variable `Ozone` (`Temp_group`) and "estimate", "std.error", "parameter",
##   "statistic", "conf.low", "conf.high", and "p.value" statistics: no applicable
##   method for 'anova' applied to an object of class "data.frame"
## ✖ For variable `Solar.R` (`Temp_group`) and "estimate", "std.error",
##   "parameter", "statistic", "conf.low", "conf.high", and "p.value" statistics:
##   no applicable method for 'anova' applied to an object of class "data.frame"
## ✖ For variable `Temp` (`Temp_group`) and "estimate", "std.error", "parameter",
##   "statistic", "conf.low", "conf.high", and "p.value" statistics: no applicable
##   method for 'anova' applied to an object of class "data.frame"
## ✖ For variable `Wind` (`Temp_group`) and "estimate", "std.error", "parameter",
##   "statistic", "conf.low", "conf.high", and "p.value" statistics: no applicable
##   method for 'anova' applied to an object of class "data.frame"

Characteristic	High N = 681	Low N = 81	Medium N = 771	p-value
Wind	8.0 (6.6, 10.6)	14.1 (11.5, 15.8)	10.3 (8.6, 12.6)
Temp	86 (82, 90)	58 (57, 59)	74 (68, 77)
Ozone	64 (39, 84)	12 (4, 19)	21 (13, 30)
Unknown	14	4	19
Solar.R	220 (175, 259)	72 (65, 99)	191 (71, 259)
Unknown	3	2	2
1 Median (Q1, Q3)

airquality %>%
  tbl_summary(by = Ozone) %>%
  add_p() %>%
  add_overall() %>%
  add_n()

## 37 missing rows in the "Ozone" column have been removed.
## The following errors were returned during `add_p()`:
## ✖ For variable `Temp_group` (`Ozone`) and "estimate", "p.value", "conf.low",
##   and "conf.high" statistics: FEXACT error 30.  Stack length exceeded in
##   f3xact, (ldst=200, key=5842, ipn=43, itp=43, ist[ii=243]=12226). Increase
##   workspace or consider using 'simulate.p.value=TRUE'

Characteristic	N	Overall N = 1161	1 N = 11	4 N = 11	6 N = 11	7 N = 31	8 N = 11	9 N = 31	10 N = 11	11 N = 31	12 N = 21	13 N = 41	14 N = 41	16 N = 41	18 N = 41	19 N = 11	20 N = 41	21 N = 41	22 N = 11	23 N = 61	24 N = 21	27 N = 11	28 N = 31	29 N = 11	30 N = 21	31 N = 11	32 N = 31	34 N = 11	35 N = 21	36 N = 21	37 N = 21	39 N = 21	40 N = 11	41 N = 11	44 N = 31	45 N = 21	46 N = 11	47 N = 11	48 N = 11	49 N = 11	50 N = 11	52 N = 11	59 N = 21	61 N = 11	63 N = 11	64 N = 21	65 N = 11	66 N = 11	71 N = 11	73 N = 21	76 N = 11	77 N = 11	78 N = 21	79 N = 11	80 N = 11	82 N = 11	84 N = 11	85 N = 21	89 N = 11	91 N = 11	96 N = 11	97 N = 21	108 N = 11	110 N = 11	115 N = 11	118 N = 11	122 N = 11	135 N = 11	168 N = 11	p-value2
Wind	116	9.7 (7.4, 11.5)	9.7 (9.7, 9.7)	9.7 (9.7, 9.7)	18.4 (18.4, 18.4)	10.3 (6.9, 14.3)	20.1 (20.1, 20.1)	13.8 (10.9, 14.3)	14.3 (14.3, 14.3)	9.7 (9.2, 16.6)	12.1 (11.5, 12.6)	10.9 (10.3, 12.1)	12.9 (11.2, 15.5)	7.7 (7.2, 8.9)	12.4 (9.8, 13.5)	13.8 (13.8, 13.8)	10.1 (8.9, 11.2)	15.2 (12.9, 15.5)	10.3 (10.3, 10.3)	8.9 (8.0, 10.3)	10.0 (9.7, 10.3)	14.9 (14.9, 14.9)	11.5 (6.3, 14.9)	9.7 (9.7, 9.7)	9.2 (6.9, 11.5)	10.9 (10.9, 10.9)	12.0 (9.2, 15.5)	12.0 (12.0, 12.0)	8.9 (7.4, 10.3)	9.2 (8.0, 10.3)	14.1 (7.4, 20.7)	9.2 (6.9, 11.5)	10.9 (10.9, 10.9)	7.4 (7.4, 7.4)	11.5 (10.3, 14.9)	12.3 (9.7, 14.9)	6.9 (6.9, 6.9)	7.4 (7.4, 7.4)	6.9 (6.9, 6.9)	9.2 (9.2, 9.2)	7.4 (7.4, 7.4)	12.0 (12.0, 12.0)	7.8 (6.3, 9.2)	6.3 (6.3, 6.3)	11.5 (11.5, 11.5)	6.0 (4.6, 7.4)	9.7 (9.7, 9.7)	4.6 (4.6, 4.6)	13.8 (13.8, 13.8)	5.4 (2.8, 8.0)	9.7 (9.7, 9.7)	5.1 (5.1, 5.1)	6.0 (5.1, 6.9)	5.1 (5.1, 5.1)	8.6 (8.6, 8.6)	7.4 (7.4, 7.4)	6.3 (6.3, 6.3)	6.9 (6.3, 7.4)	10.3 (10.3, 10.3)	4.6 (4.6, 4.6)	6.9 (6.9, 6.9)	6.0 (5.7, 6.3)	8.0 (8.0, 8.0)	8.0 (8.0, 8.0)	5.7 (5.7, 5.7)	2.3 (2.3, 2.3)	4.0 (4.0, 4.0)	4.1 (4.1, 4.1)	3.4 (3.4, 3.4)	0.045
Temp	116	79 (71, 85)	59 (59, 59)	61 (61, 61)	57 (57, 57)	74 (69, 80)	61 (61, 61)	72 (71, 81)	73 (73, 73)	66 (62, 73)	74 (73, 74)	74 (68, 76)	66 (64, 72)	78 (72, 82)	65 (60, 72)	59 (59, 59)	74 (67, 81)	77 (76, 77)	77 (77, 77)	74 (67, 78)	71 (68, 73)	81 (81, 81)	77 (66, 82)	82 (82, 82)	69 (68, 70)	78 (78, 78)	81 (61, 84)	66 (66, 66)	84 (82, 85)	77 (72, 81)	74 (72, 76)	84 (81, 87)	83 (83, 83)	67 (67, 67)	81 (78, 86)	80 (79, 81)	78 (78, 78)	87 (87, 87)	81 (81, 81)	85 (85, 85)	86 (86, 86)	86 (86, 86)	80 (79, 81)	84 (84, 84)	85 (85, 85)	83 (83, 83)	80 (80, 80)	87 (87, 87)	90 (90, 90)	90 (86, 93)	97 (97, 97)	88 (88, 88)	89 (86, 92)	87 (87, 87)	86 (86, 86)	88 (88, 88)	96 (96, 96)	92 (89, 94)	90 (90, 90)	93 (93, 93)	91 (91, 91)	92 (92, 92)	85 (85, 85)	90 (90, 90)	79 (79, 79)	94 (94, 94)	89 (89, 89)	84 (84, 84)	81 (81, 81)	0.007
Solar.R	111	207 (112, 256)	8 (8, 8)	25 (25, 25)	78 (78, 78)	49 (48, 49)	19 (19, 19)	24 (24, 36)	264 (264, 264)	290 (44, 320)	135 (120, 149)	125 (70, 188)	233 (106, 304)	139 (42, 229)	178 (98, 269)	99 (99, 99)	152 (59, 238)	245 (211, 259)	71 (71, 71)	132 (14, 220)	249 (238, 259)	175 (175, 175)	256 (238, 273)	127 (127, 127)	258 (193, 322)	244 (244, 244)	92 (92, 236)	307 (307, 307)	274 (274, 274)	129 (118, 139)	282 (279, 284)	203 (83, 323)	314 (314, 314)	190 (190, 190)	192 (190, 236)	232 (212, 252)	237 (237, 237)	95 (95, 95)	260 (260, 260)	248 (248, 248)	275 (275, 275)	82 (82, 82)	153 (51, 254)	285 (285, 285)	220 (220, 220)	214 (175, 253)	157 (157, 157)	NA (NA, NA)	291 (291, 291)	199 (183, 215)	203 (203, 203)	276 (276, 276)	197 (197, 197)	187 (187, 187)	294 (294, 294)	213 (213, 213)	237 (237, 237)	182 (175, 188)	229 (229, 229)	189 (189, 189)	167 (167, 167)	270 (267, 272)	223 (223, 223)	207 (207, 207)	223 (223, 223)	225 (225, 225)	255 (255, 255)	269 (269, 269)	238 (238, 238)	0.4
Unknown		5	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Temp_group	116
High		54 (47%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	1 (33%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	2 (50%)	0 (0%)	0 (0%)	1 (25%)	0 (0%)	0 (0%)	1 (17%)	0 (0%)	1 (100%)	1 (33%)	1 (100%)	0 (0%)	0 (0%)	2 (67%)	0 (0%)	2 (100%)	1 (50%)	0 (0%)	2 (100%)	1 (100%)	0 (0%)	2 (67%)	1 (50%)	0 (0%)	1 (100%)	1 (100%)	1 (100%)	1 (100%)	1 (100%)	1 (50%)	1 (100%)	1 (100%)	2 (100%)	0 (0%)	1 (100%)	1 (100%)	2 (100%)	1 (100%)	1 (100%)	2 (100%)	1 (100%)	1 (100%)	1 (100%)	1 (100%)	2 (100%)	1 (100%)	1 (100%)	1 (100%)	2 (100%)	1 (100%)	1 (100%)	0 (0%)	1 (100%)	1 (100%)	1 (100%)	1 (100%)
Low		4 (3.4%)	1 (100%)	0 (0%)	1 (100%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	1 (25%)	1 (100%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)
Medium		58 (50%)	0 (0%)	1 (100%)	0 (0%)	3 (100%)	1 (100%)	2 (67%)	1 (100%)	3 (100%)	2 (100%)	4 (100%)	4 (100%)	2 (50%)	3 (75%)	0 (0%)	3 (75%)	4 (100%)	1 (100%)	5 (83%)	2 (100%)	0 (0%)	2 (67%)	0 (0%)	2 (100%)	1 (100%)	1 (33%)	1 (100%)	0 (0%)	1 (50%)	2 (100%)	0 (0%)	0 (0%)	1 (100%)	1 (33%)	1 (50%)	1 (100%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	1 (50%)	0 (0%)	0 (0%)	0 (0%)	1 (100%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	1 (100%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)
1 Median (Q1, Q3); n (%)
2 Kruskal-Wallis rank sum test; NA

airquality %>%
  tbl_summary(by = Wind) %>%                     
  add_p() %>%                                    
  add_overall() %>%                             
  add_n() %>%                                    
  modify_header(label ~ "**Variable**") %>%       
  modify_spanning_header(c("stat_1", "stat_2") ~ "**Wind**") %>%  
  modify_footnote(
    all_stat_cols() ~ "Median (IQR) or Frequency (%)"  
  ) %>%
  modify_caption("**Table 1. Summary of Wind Quality**") %>%  
  bold_labels()

## The following errors were returned during `modify_caption()`:
## ✖ For variable `Temp_group` (`Wind`) and "estimate", "p.value", "conf.low", and
##   "conf.high" statistics: integer overflow in exact computation

Table 1. Summary of Wind Quality

Variable	N	Overall N = 1531	Wind		2.8 N = 11	3.4 N = 11	4 N = 11	4.1 N = 11	4.6 N = 41	5.1 N = 31	5.7 N = 31	6.3 N = 81	6.9 N = 91	7.4 N = 101	8 N = 111	8.6 N = 81	9.2 N = 81	9.7 N = 111	10.3 N = 111	10.9 N = 81	11.5 N = 151	12 N = 41	12.6 N = 31	13.2 N = 21	13.8 N = 51	14.3 N = 61	14.9 N = 81	15.5 N = 31	16.1 N = 11	16.6 N = 31	18.4 N = 11	20.1 N = 11	20.7 N = 11	p-value2
			1.7 N = 11	2.3 N = 11
Temp	153	79 (72, 85)	76 (76, 76)	94 (94, 94)	93 (93, 93)	81 (81, 81)	89 (89, 89)	84 (84, 84)	85 (80, 90)	88 (87, 92)	88 (79, 92)	82 (77, 93)	81 (74, 86)	84 (76, 87)	82 (75, 85)	82 (74, 86)	81 (69, 85)	74 (62, 81)	77 (73, 81)	79 (73, 84)	79 (68, 85)	67 (64, 77)	74 (64, 75)	68 (58, 77)	80 (67, 81)	74 (72, 79)	79 (72, 81)	77 (76, 84)	67 (67, 67)	63 (57, 73)	57 (57, 57)	61 (61, 61)	72 (72, 72)	0.020
Ozone	116	32 (18, 64)	NA (NA, NA)	118 (118, 118)	73 (73, 73)	168 (168, 168)	122 (122, 122)	135 (135, 135)	66 (64, 91)	78 (77, 79)	106 (97, 115)	73 (59, 85)	43 (23, 63)	44 (35, 64)	36 (18, 108)	23 (20, 80)	28 (20, 49)	24 (11, 45)	24 (13, 36)	21 (14, 31)	24 (14, 39)	33 (28, 43)	13 (12, 13)	18 (18, 18)	19 (14, 45)	10 (8, 12)	28 (27, 44)	21 (21, 32)	NA (NA, NA)	13 (11, 14)	6 (6, 6)	8 (8, 8)	37 (37, 37)	<0.001
Unknown		37	1	0	0	0	0	0	1	0	1	2	1	0	4	5	2	2	1	2	5	0	1	1	1	2	3	0	1	1	0	0	0
Solar.R	146	205 (115, 259)	59 (59, 59)	225 (225, 225)	183 (183, 183)	238 (238, 238)	255 (255, 255)	269 (269, 269)	175 (91, 189)	197 (187, 276)	223 (153, 272)	238 (169, 259)	193 (83, 260)	190 (115, 253)	143 (131, 207)	221 (167, 290)	242 (112, 252)	203 (44, 258)	139 (49, 229)	248 (166, 267)	223 (120, 322)	87 (48, 200)	238 (149, 255)	105 (65, 145)	224 (99, 291)	191 (48, 264)	236 (175, 266)	259 (92, 259)	242 (242, 242)	66 (20, 320)	78 (78, 78)	19 (19, 19)	284 (284, 284)	0.7
Unknown		7	0	0	0	0	0	0	1	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0
Temp_group	153
High		68 (44%)	0 (0%)	1 (100%)	1 (100%)	1 (100%)	1 (100%)	1 (100%)	3 (75%)	3 (100%)	2 (67%)	4 (50%)	5 (56%)	7 (70%)	6 (55%)	5 (63%)	5 (63%)	3 (27%)	3 (27%)	3 (38%)	6 (40%)	1 (25%)	0 (0%)	0 (0%)	2 (40%)	0 (0%)	4 (50%)	1 (33%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)
Low		8 (5.2%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	1 (9.1%)	0 (0%)	0 (0%)	1 (9.1%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	1 (50%)	1 (20%)	1 (17%)	1 (13%)	0 (0%)	0 (0%)	1 (33%)	1 (100%)	0 (0%)	0 (0%)
Medium		77 (50%)	1 (100%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	1 (25%)	0 (0%)	1 (33%)	4 (50%)	4 (44%)	3 (30%)	4 (36%)	3 (38%)	3 (38%)	7 (64%)	8 (73%)	5 (63%)	9 (60%)	3 (75%)	3 (100%)	1 (50%)	2 (40%)	5 (83%)	3 (38%)	2 (67%)	1 (100%)	2 (67%)	0 (0%)	1 (100%)	1 (100%)
1 Median (IQR) or Frequency (%)
2 Kruskal-Wallis rank sum test; NA

install.packages("tidyverse", repos = "https://cran.r-project.org/")

## Warning: package 'tidyverse' is in use and will not be installed

library(tidyverse)

install.packages("tidyverse", repos = "https://cran.r-project.org/")

## Warning: package 'tidyverse' is in use and will not be installed

install.packages("tidyverse", repos = "[https://cran.r-project.org/](https://cran.r-project.org/)")

## Warning: package 'tidyverse' is in use and will not be installed