Here is my code
```{r}
#Assign Variables
Categorical.Variables = c( "Race/Ethnicity" ,"Gender", "Education", "Intervention")
Numeric.Variables = c("Age", "Pre Weight", "Post Weight", "Follow-up Weight","Wieght Loss/Gain after Intervention","Wieght Loss/Gain on Follow Up" )
```
And I have this simple table I'm trying to make with dplyr.
```{r}
renderTable({
wl_data %>% group_by_at(input$categorical_variable) %>%
summarise("Average " = mean(wl_data[[input$numeric_variable]]),
"Median " = median(wl_data[[input$numeric_variable]])
)
})
```
This is the output I am getting which has the same value for the entire numerical input and not broken down by the categorical one.
My desired output is to have a reactive table that will give me summary statistics that change based on inputs. So far I've gotten really close but I can't figure out how to get it to work. What am I doing wrong?
Data
> dput(wl_data)
structure(list(ID = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28,
29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76,
77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92,
93, 94, 95, 96, 97, 98, 99, 100), Gender = c("Female", "Female",
"Female", "Female", "Female", "Female", "Female", "Female", "Female",
"Female", "Female", "Female", "Female", "Female", "Female", "Female",
"Female", "Female", "Female", "Female", "Female", "Female", "Female",
"Female", "Female", "Female", "Female", "Female", "Female", "Female",
"Female", "Female", "Female", "Female", "Female", "Female", "Female",
"Female", "Female", "Female", "Female", "Female", "Female", "Female",
"Female", "Female", "Female", "Male", "Male", "Male", "Male",
"Male", "Male", "Male", "Male", "Male", "Male", "Male", "Male",
"Male", "Male", "Male", "Male", "Male", "Male", "Male", "Male",
"Male", "Male", "Male", "Male", "Male", "Male", "Male", "Male",
"Male", "Male", "Male", "Male", "Male", "Male", "Male", "Male",
"Male", "Male", "Male", "Male", "Male", "Male", "Male", "Male",
"Male", "Male", "Male", "Male", "Male", "Male", "Male", "Male",
"Male"), Age = c(34.1958081813646, 38.342817530618, 31.4255555318668,
39.9174711825326, 30.4606180330738, 35.0906190911774, 33.4250614438206,
32.4111385603901, 30.9181484377477, 25.1908965916373, 33.1378793967888,
37.1778275772231, 33.7549078873126, 30.3750618664781, 40.9762685345486,
27.3728471407667, 36.3470769267296, 33.8341794455191, 36.9817041397328,
32.4507015799172, 31.736502675456, 29.6957238939358, 36.1113904697122,
33.9414452506462, 36.9691713027423, 34.3095768736093, 32.6794349499396,
32.5801726981881, 27.2223803373054, 34.2432519724825, 36.7139034247957,
27.5831041259225, 41.5007923189551, 37.1082421375904, 30.3266722008702,
33.9694667824078, 35.6325324142817, 35.2054973669583, 29.9515829434386,
25.677076079417, 31.1902828949387, 32.4210338627454, 28.3575206745882,
32.5940152075491, 31.9765592545155, 41.3789200289175, 36.1047693482833,
41.7112493929453, 31.2430063028005, 34.3678300092579, 33.7714243110968,
27.4467708701268, 31.7782484822674, 27.5600393402856, 33.2923297870439,
38.9376543504186, 36.1805939215701, 36.2597199606244, 30.7401512296638,
27.6097705105785, 37.7263165470213, 30.2310251905583, 32.0336846167338,
30.4912316247355, 37.9383197620045, 29.5154438541504, 36.9983115129871,
32.7947406882304, 33.9285486157751, 31.0574057190097, 26.5039522824809,
31.8339186529629, 32.5527787177707, 31.8562467478914, 34.1271822586423,
26.0893318378367, 32.6484211806091, 32.8446673998842, 35.6959423848893,
38.4928932513576, 30.124668880133, 29.9166947266785, 35.4745850168983,
31.8399849826237, 34.1574638847378, 33.9537143341731, 32.5872485669679,
33.5270658220979, 31.9265234034974, 32.4627478372422, 29.9351938489126,
34.0414714779472, 31.2413191901287, 27.0438647172414, 19.2909317016602,
33.415520844399, 27.2705926514463, 42.3596463557333, 29.8770043778932,
33.5144147507963), Education = c("Less than HS", "Less than HS",
"Less than HS", "Less than HS", "Less than HS", "Less than HS",
"Less than HS", "Less than HS", "Less than HS", "Less than HS",
"Less than HS", "Less than HS", "Less than HS", "Less than HS",
"Less than HS", "Less than HS", "Less than HS", "Less than HS",
"Less than HS", "Less than HS", "Less than HS", "Less than HS",
"Less than HS", "Less than HS", "HS Diploma", "HS Diploma", "HS Diploma",
"HS Diploma", "HS Diploma", "HS Diploma", "HS Diploma", "HS Diploma",
"HS Diploma", "HS Diploma", "HS Diploma", "HS Diploma", "HS Diploma",
"HS Diploma", "HS Diploma", "HS Diploma", "HS Diploma", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "Some College", "Some College", "Some College",
"Some College", "College Degree"), Ethnicity = c(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, 1, 1, 1, 1, 1, 1, 1, 1,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), `Pre Weight` = c(192.056576386152,
199.200034264708, 206.876365089032, 195.881563220086, 200.023472577799,
209.835274224519, 197.638006672991, 188.53439444449, 197.556054379151,
195.261374235473, 183.834639690234, 206.592420843139, 201.388593429714,
210.134243322886, 210.711872502929, 191.050579749048, 197.758412402822,
194.271341504122, 198.923689983916, 198.967602661854, 192.920791894197,
203.365595032141, 199.845179783937, 196.529509982996, 209.761359590106,
195.030192050966, 191.221678439819, 188.893717611267, 205.644104360021,
193.924385191553, 195.469716734282, 205.8901999839, 201.684244009288,
199.956401891017, 202.022335022251, 204.845240593771, 201.497865807527,
214.361511032097, 190.574097748526, 197.017952975715, 200.709252046567,
196.371000972635, 185.010079737753, 197.991679603932, 201.731562744884,
206.684686806897, 198.528149601247, 190.756862982584, 201.257889946122,
201.911622232205, 202.823506631306, 192.12975887733, 196.74718730805,
197.705610551042, 198.324502368836, 199.593768163526, 183.679870976834,
195.266928974364, 195.89751916776, 209.72831764759, 198.465869677806,
207.538604561181, 205.284033133852, 195.080391611031, 193.136535406142,
202.807351731666, 194.04551510654, 201.363628937019, 200.066255208571,
203.038557790409, 191.260291037383, 200.227987240782, 201.838208956746,
196.743805124628, 195.478231878427, 202.583284069464, 191.771438428463,
206.52146661398, 193.483762293385, 190.160595982365, 206.933106189739,
206.326923423534, 205.130903784651, 198.517406195082, 202.249084556955,
200.390387751599, 199.138963969221, 204.348338163458, 198.339567011702,
197.763306621186, 198.144029061426, 191.630341694166, 202.501124865579,
210.04412604036, 202.621188398029, 207.952265488915, 197.56589056435,
197.411320802916, 199.215568434214, 195.430133251124), Intervention = c("Placebo Diet",
"Placebo Diet", "Placebo Diet", "Placebo Diet", "Placebo Diet",
"Placebo Diet", "Placebo Diet", "Placebo Diet", "Placebo Diet",
"Placebo Diet", "Placebo Diet", "Placebo Diet", "Placebo Diet",
"Placebo Diet", "Placebo Diet", "Placebo Diet", "Placebo Diet",
"Placebo Diet", "Placebo Diet", "Placebo Diet", "Placebo Diet",
"Placebo Diet", "Placebo Diet", "Placebo Diet", "Placebo Diet",
"Placebo Diet", "Placebo Diet", "Placebo Diet", "Placebo Diet",
"Placebo Diet", "Placebo Diet", "Placebo Diet", "Placebo Diet",
"Adjusted Diet", "Adjusted Diet", "Adjusted Diet", "Adjusted Diet",
"Adjusted Diet", "Adjusted Diet", "Adjusted Diet", "Adjusted Diet",
"Adjusted Diet", "Adjusted Diet", "Adjusted Diet", "Adjusted Diet",
"Adjusted Diet", "Adjusted Diet", "Adjusted Diet", "Adjusted Diet",
"Adjusted Diet", "Adjusted Diet", "Adjusted Diet", "Adjusted Diet",
"Adjusted Diet", "Adjusted Diet", "Adjusted Diet", "Adjusted Diet",
"Adjusted Diet", "Adjusted Diet", "Adjusted Diet", "Adjusted Diet",
"Adjusted Diet", "Adjusted Diet", "Adjusted Workout", "Adjusted Workout",
"Adjusted Workout", "Adjusted Workout", "Adjusted Workout", "Adjusted Workout",
"Adjusted Workout", "Adjusted Workout", "Adjusted Workout", "Adjusted Workout",
"Adjusted Workout", "Adjusted Workout", "Adjusted Workout", "Adjusted Workout",
"Adjusted Workout", "Adjusted Workout", "Adjusted Workout", "Adjusted Workout",
"Adjusted Workout", "Adjusted Workout", "Adjusted Workout", "Adjusted Workout",
"Adjusted Workout", "Adjusted Workout", "Adjusted Workout", "Adjusted Workout",
"Adjusted Workout", "Adjusted Workout", "Adjusted Workout", "Adjusted Workout",
"Adjusted Workout", "Adjusted Workout", "Adjusted Workout", "Adjusted Workout",
"Adjusted Workout", "Adjusted Workout", "Adjusted Workout"),
`Post Weight` = c(183.884925652295, 199.800326915851, 194.671078067971,
203.366324901639, 200.073624389392, 198.747637957626, 197.077328200452,
205.294385457295, 203.63121523353, 202.319217967146, 194.309724454273,
204.37792175237, 201.774254426186, 199.169666236616, 196.435276100077,
188.147545420565, 192.339179127361, 197.267082901293, 193.759855326265,
194.147504705528, 210.371321306797, 198.317242327379, 193.102086020575,
186.002956913784, 187.153649610467, 197.444735638259, 199.397255917051,
199.896955043572, 200.289578221986, 200.359694579151, 194.154234966321,
201.103945462295, 198.381657289632, 174.026079230011, 195.176185252116,
192.193440534233, 189.540944711247, 195.402285634977, 190.26270833789,
188.311830833904, 193.327807801019, 186.754787273152, 189.741880512578,
184.221094195585, 194.408037395682, 187.552772240146, 178.570551406359,
199.402663974673, 189.554024381927, 195.699110599584, 196.260223355843,
184.848634171125, 194.972185590508, 186.89522462379, 195.963659870962,
189.975194325292, 185.117492173653, 188.429422814501, 191.845467861334,
184.460234458733, 181.766015566303, 195.604591362702, 185.29349076713,
185.749602360069, 186.493563341777, 194.774700184702, 170.250064507127,
192.264929460362, 194.279346537951, 194.095480815304, 192.09355792118,
205.814604264742, 201.010346295516, 205.747699560743, 209.566269909556,
196.717178873951, 190.261858329177, 210.87666987587, 184.596615831833,
200.588227067055, 204.084495230927, 185.477325026295, 206.07568608757,
199.725719135313, 193.537903719698, 202.579156443971, 204.824664756597,
197.221812009229, 181.948258209741, 198.307839632616, 212.828922990593,
183.819634508109, 209.631753528083, 201.93635969481, 191.993820458447,
210.423491403344, 196.130759427615, 216.762351151556, 194.786605839181,
214.179886420607), `Follow-up Weight` = c(196.754451103698,
216.156309357029, 210.484507129149, 180.150482770114, 192.390769421036,
203.047307473025, 212.955081274413, 181.630344336736, 194.986069395964,
189.119214660604, 210.027861208073, 191.293032053363, 210.267319794366,
209.707298431749, 187.987575877924, 174.893785292807, 205.768015398644,
198.770255160707, 211.5933289635, 182.237056883605, 175.814034769428,
202.397501930318, 180.344375671848, 211.968205626545, 222.363337848219,
179.163385432912, 205.026072358305, 188.93023303026, 198.485623109445,
219.364188119653, 175.826722220518, 176.65140654135, 198.980842974561,
232.273055694532, 202.227960749224, 221.662799554178, 212.652799341595,
164.536254992709, 181.760834089073, 197.487373093463, 204.981188794773,
219.285266716906, 230.166802389431, 185.610656949575, 202.313856839464,
191.789445630275, 198.555966840286, 181.177552399458, 200.24041355573,
198.072104290259, 190.301193975029, 186.122213613271, 180.075892835885,
207.392077350232, 193.10916223294, 192.415564520343, 208.723270639166,
214.108275081526, 206.051982381905, 205.617556553261, 223.241295821208,
206.747063707735, 222.621179596172, 193.962939015546, 191.982042502059,
183.000486736273, 194.58624415638, 203.504464984871, 192.261302850238,
217.979959920922, 206.377081263054, 190.020876339258, 207.567484772153,
191.626350492879, 206.334397539831, 214.376621493284, 204.515487717072,
195.394387042325, 190.006551797705, 179.74960024294, 223.11257958354,
205.544995929085, 191.169158874982, 177.952415974869, 190.496962709585,
200.471106886835, 185.645138167456, 214.420277238969, 219.606989098975,
183.150109983399, 209.9404815046, 205.259732915874, 195.812441966336,
197.740712842642, 181.31540905888, 221.787286641484, 207.900393939053,
180.352527018113, 245.932392822579, 213.72185352011), `Race/Ethnicity` = c("Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "Hispanic",
"Hispanic", "Hispanic", "Hispanic", "Hispanic", "White",
"White", "White", "White", "White", "White", "White", "White",
"Black", "Black", "Black", "Black", "Black", "Black", "Black",
"Black", "Black", "Black", "Black", "Black"), `Wieght Loss/Gain after Intervention` = c(8.17165073385695,
-0.600292651142809, 12.2052870210609, -7.48476168155321,
-0.0501518115925137, 11.0876362668932, 0.560678472538712,
-16.7599910128047, -6.07516085437965, -7.05784373167262,
-10.4750847640389, 2.2144990907691, -0.385660996471415, 10.9645770862699,
14.2765964028513, 2.90303432848305, 5.41923327546101, -2.99574139717151,
5.16383465765102, 4.82009795632621, -17.4505294125993, 5.04835270476178,
6.74309376336168, 10.5265530692122, 22.6077099796385, -2.41454358729243,
-8.17557747723185, -11.0032374323055, 5.354526138035, -6.43530938759795,
1.31548176796059, 4.78625452160486, 3.30258671965566, 25.9303226610064,
6.84614977013553, 12.6518000595388, 11.95692109628, 18.9592253971205,
0.311389410635456, 8.70612214181165, 7.38144424554775, 9.61621369948261,
-4.73180077482539, 13.770585408347, 7.3235253492021, 19.1319145667512,
19.9575981948874, -8.64580099208979, 11.7038655641954, 6.21251163262059,
6.56328327546362, 7.28112470620545, 1.77500171754218, 10.8103859272524,
2.36084249787382, 9.61857383823371, -1.43762119681924, 6.83750615986355,
4.05205130642571, 25.2680831888574, 16.6998541115026, 11.9340131984791,
19.9905423667224, 9.33078925096197, 6.64297206436459, 8.03265154696419,
23.795450599413, 9.0986994766572, 5.7869086706196, 8.94307697510521,
-0.833266883797478, -5.58661702396057, 0.827862661230029,
-9.00389443611493, -14.0880380311282, 5.86610519551323, 1.50958009928581,
-4.35520326188998, 8.88714646155131, -10.4276310846908, 2.84861095881206,
20.8495983972389, -0.944782302918611, -1.20831294023083,
8.71118083725742, -2.18876869237283, -5.68570078737685, 7.12652615422849,
16.3913088019617, -0.544533011430758, -14.6848939291667,
7.8107071860577, -7.13062866250402, 8.10776634555077, 10.6273679395817,
-2.47122591442894, 1.43513113673544, -19.3510303486401, 4.42896259503323,
-18.7497531694826), `Wieght Loss/Gain on Follow Up` = c(-12.8695254514023,
-16.3559824411786, -15.8134290611779, 23.2158421315253, 7.68285496835597,
-4.29966951539973, -15.8777530739608, 23.664041120559, 8.64514583756682,
13.2000033065415, -15.7181367537996, 13.0848896990065, -8.4930653681804,
-10.5376321951335, 8.4477002221538, 13.2537601277581, -13.4288362712832,
-1.50317225941399, -17.8334736372344, 11.9104478219233, 34.5572865373688,
-4.0802596029389, 12.7577103487274, -25.9652487127605, -35.2096882377518,
18.2813502053468, -5.62881644125446, 10.9667220133124, 1.80395511254028,
-19.0044935405022, 18.3275127458037, 24.4525389209448, -0.599185684928671,
-58.2469764645211, -7.05177549710788, -29.4693590199458,
-23.1118546303478, 30.866030642268, 8.50187424881733, -9.17554225955973,
-11.6533809937537, -32.5304794437543, -40.4249218768527,
-1.38956275398959, -7.90581944378209, -4.236673390129, -19.9854154339264,
18.2251115752151, -10.686389173803, -2.37299369067478, 5.95902938081417,
-1.273579442146, 14.8962927546236, -20.4968527264427, 2.85449763802171,
-2.44037019505049, -23.6057784655131, -25.6788522670249,
-14.2065145205706, -21.1573220945284, -41.4752802549046,
-11.1424723450327, -37.327688829042, -8.21333665547718, -5.48847916028171,
11.7742134484288, -24.3361796492536, -11.2395355245098, 2.01804368771263,
-23.8844791056181, -14.2835233418737, 15.7937279254838, -6.55713847663719,
14.1213490678638, 3.23187236972444, -17.6594426193333, -14.2536293878948,
15.4822828335455, -5.40993596587214, 20.8386268241156, -19.0280843526125,
-20.0676709027903, 14.9065272125881, 21.7733031604439, 3.04094101011287,
2.10804955713684, 19.1795265891415, -17.1984652297397, -37.658730889234,
15.1577296492178, 2.8884414859931, -21.4400984077656, 13.8193115617469,
4.19564685216756, 10.6784113995673, -11.3637952381396, -11.7696345114382,
36.4098241334432, -51.1457869833976, 0.458032900496619)), row.names = c(NA,
-100L), class = c("tbl_df", "tbl", "data.frame"))
Additional Code Chunk Error Photo: ```{r}
renderTable({
wl_data %>% group_by(across(all_of(input$categorical_variable))) %>%
summarise("Average " = mean(.data[[input$numeric_variable]]),
"Median " = median(.data[[input$numeric_variable]]),
"Freq " = count(.data[[input$categorical_variable]])
)
})
```
mean(wl_data[[input$numeric_variable]])
is extracting the mean from the entire dataframe and does not respect the grouping. Try using .data
instead.
Also group_by_at
has been superseded and we may use across
.
renderTable({
wl_data %>%
group_by(across(all_of(input$categorical_variable))) %>%
summarise(Average = mean(.data[[input$numeric_variable]]),
Median = median(.data[[input$numeric_variable]])
)
})