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Im using django with postgres i was able to add multiple filters in my views but mu question here is is there any possibility that i can filter multiple same jsonfield with different values:
ex i can filter localhost:127.0.0.1:products?areaOfUse=residential
so is there any possibilty that i can get the result of /products?areaOfUse=residential&areaOfUse=test
So from here i need to query two different json objects.
-Here are my views
class SubcategoriesProductsAPI(APIView):
# #cache_control(must_revalidate=True, max_age=3600)
def get (self, request, subCategoryId = None, pk = None):
try:
filters = {}
design = self.request.query_params.get('design', None)
dimension = self.request.query_params.get('dimension', None)
collectionName = self.request.query_params.get('collectionName', None)
material = self.request.query_params.get('material',None)
min_price = self.request.query_params.get('min_price',None)
max_price = self.request.query_params.get('max_price',None)
page = self.request.query_params.get('page', None)
wearLayer = self.request.query_params.get('wearLayer',None)
areaOfUse = self.request.query_params.getlist('areaOfUse',None)
productType = self.request.query_params.get('type', None)
installationMethod = self.request.query_params.get('installationMethod',None)
format_type = self.request.query_params.get('format_type',None)
wearLayer = self.request.query_params.get('wearLayer',None)
levelOfUse = self.request.query_params.get('levelOfUse',None)
if design is not None:
filters['product_options__options__data__design'] = design
if productType is not None:
filters['product_options__options__data__type'] = productType
if dimension is not None:
filters['product_options__options__data__dimensions__contains'] = [{'dimension': dimension}]
if collectionName is not None:
filters['product_options__options__data__collectionName'] = collectionName
if material is not None:
filters['product_options__options__data__material'] = material
if wearLayer is not None:
filters['product_options__options__data__wearLayer'] = wearLayer
if installationMethod is not None:
filters['product_options__options__data__installationMethod'] =installationMethod
if format_type is not None:
filters['product_options__options__data__format'] = format_type
if areaOfUse is not None:
filters['product_options__options__data__areaOfUse__contains'] = areaOfUse
if levelOfUse is not None:
filters['product_options__options__data__levelOfUse'] = levelOfUse
if min_price and max_price:
filters['product_options__options__data__dimensions__range__price'] = float(min_price)
filters['product_options__options__data__dimensions__0__price__lte'] = float(max_price)
queryset = Products.objects.filter(sub_categories_id = subCategoryId, is_active = True).select_related().filter(**filters)
if not queryset:
return JsonResponse({ 'status': False, 'msg': 'No products found', 'data': {} }, status=400)
if page is not None:
paginator = PageNumberPagination()
page = paginator.paginate_queryset(queryset, request)
if page is not None:
serializer = ProductSerializer(page, many=True)
return JsonResponse({ 'status': True, 'msg': 'Succesfully retrived products ', 'data': serializer.data, 'count': paginator.page.paginator.count, 'previous':paginator.get_previous_link(), 'next':paginator.get_next_link() }, status=200)
serializer = ProductSerializer(queryset, many=True)
return JsonResponse({ 'status': True, 'msg': 'Succesfully retrived products ', 'data': serializer.data }, status=200)
except Products.DoesNotExist:
return JsonResponse({ 'status': False, 'msg': 'Internal system error', 'data': {}}, status=500)
areaOfUse = self.request.query_params.getlist('areaOfUse[]',None)
/products?areaOfUse%5B%5D=residential&areaOfUse%5B%5D=test
import operator
from django.db.models import Q
from functools import reduce
queryset = Products.objects.filter(sub_categories_id = subCategoryId, is_active = True).select_related().filter(**filters)
if areaOfUse:
queryset.filter(
reduce(
operator.and_,
(Q(product_options__options__data__areaOfUse__contains=x) for x in areaOfUse)
)
)
##This is a container that I am using in the data table, but br tag in the column name is not working.
I used escape = FALSE in the data table but still facing the same issue.
and \n is also not working. I want something like this column name = first name (in the next line) last name.
test <- function(group,n){
htmltools::withTags(th(colspan = n, group, class = "dt-center"))
}
myContainer <- htmltools::withTags(table(
class = '',style="width:100%",
thead(
tr(
th(rowspan = 2, ' '),
th(colspan = 1, 'group 1', class = "dt-center"),
th(colspan = 2, 'group 2', class = "dt-center"),
th(colspan = 2, 'group 3', class = "dt-center")
),
tr(
th("new \\\\n ID"),
lapply(c("SUBJID","SITE<br>ID","AG<br>E","SUBJID","RACE"), th)
)
)
))
Server <- function(input, output, session) {
adae<-read_sas("C:/Arinjay_Intern/Work/ADaM/adae.sas7bdat")
output$intTable<-renderDT({adae_df %>%
datatable(class= 'compact', extensions = 'Buttons', rownames = F, container = myContainer,escape = FALSE,
callback = JS(c("$('table.dataTable thead th').css('border-top', 'none');",
"$('table.dataTable.no-footer').css('border-top', 'none');"
)),
options = list(dom = 'tB', pageLength = 5,
ordering = FALSE, class= "compact",
columnDefs = list(list(className = "dt-center", targets = "_all")),
buttons = 'pdf'
),
caption = htmltools::tags$caption(
style = 'caption-side: bottom; text-align: left;',
htmltools::em(HTML('N = number of subjects in the specified population. <br>n=number of subjects in each category. % = 100*n/N.')))
) %>%
formatStyle(c("USUBJID","SUBJID","SITEID","AGE", "SEX","RACE"), backgroundColor = 'white')
})
}
UI <-navbarPage(
"DT Interactive Tables",
tabPanel(
"ADaM DataSets",
fluidPage(
checkboxGroupInput('group','Please select a group',c('FD_Cohort','MRD_Cohort')),
textInput('n',"any value",value=2),
DTOutput("intTable")
)
)
)
shinyApp(UI,Server)
Expected output:
Neither \n or <br>, work in xtable. So, you could define the rows explicitly as shown below:
row1 <- c(" USUB","SUBJ","SITE","AG","SEX", "RACE")
row2 <- c("JID","ID","ID","E"," ", "")
myContainer <- htmltools::withTags(table(
class = 'dt-center', style="width:100%",
thead(
tr(
th(colspan = 2, 'group 1', class = "dt-center"),
th(colspan = 2, 'group 2', class = "dt-center"),
th(colspan = 2, 'group 3', class = "dt-center")
),
tr( lapply( row1, th)
),
tr( lapply( row2, th)
)
)
))
or you can write something in css or js to handle it. The above code gives the following output on a dummy dataset:
I am trying to make a custom UI in which i have to plot 4 plots inside each tab,
but i am getting scroll on plot rendering and when i add height as 240 scrollbar disappear and it works for the same size desktop but it behaves different on different size of desktop and i get scrollbar again.
motive is to fit the plots in screen without scrollbar, also i would like to get a feedback that am i creating UI in a right way
Thanks
UI
navbarPage("NarBar",
tabPanel("Tab1",
column(12,
column(4,
column(12,
checkboxInput("ID1", "Checkbox1", FALSE)
),
column(12,
checkboxInput("ID2", "Checkbox2", FALSE)
)
),
column(8,
column(3,
selectInput("ID1", "Select1:",
c("A" = "a",
"B" = "b",
"C" = "c"))
),
column(3,
selectInput("ID2", "Select2:",
c("A" = "a",
"B" = "b",
"C" = "c"))
),
column(3,
selectInput("ID3", "Select3:",
c("A" = "a",
"B" = "b",
"C" = "c"))
),
column(3,
selectInput("ID4", "Select4:",
c("A" = "a",
"B" = "b",
"C" = "c")
)
)
)
),
column(12,
column(4,
column(12,
selectInput("ID1", "Select1:",
c("A" = "a",
"B" = "b",
"C" = "c")
)
),
column(12,
selectInput("ID2", "Select2:",
c("A" = "a",
"B" = "b",
"C" = "c")
)
),
column(12,
selectInput("ID3", "Select3:",
c("A" = "a",
"B" = "b",
"C" = "c")
)
),
column(12,
selectInput("ID4", "Select4:",
c("A" = "a",
"B" = "b",
"C" = "c")
)
),
column(12,
selectInput("ID5", "Select5:",
c("A" = "a",
"B" = "b",
"C" = "c")
)
),
column(12,
selectInput("ID6", "Select6:",
c("A" = "a",
"B" = "b",
"C" = "c")
)
)
),
column(width = 8,
tabsetPanel(
tabPanel(title = 'Tab1',
column(width = 6,
plotOutput('plot1',height = 240)
),
column(width = 6,
plotOutput('plot2',height = 240)
),
column(width = 6,
plotOutput('plot3',height = 240)
),
column(width = 6,
plotOutput('plot4',height = 240)
)
),
tabPanel(title = 'Tab2',
column(width = 6,
plotOutput('plot5',height = 240)
),
column(width = 6,
plotOutput('plot6',height = 240)
),
column(width = 6,
plotOutput('plot7',height = 240)
),
column(width = 6,
plotOutput('plot8',height = 240)
)
),
tabPanel(title = 'Tab3',
column(width = 6,
plotOutput('plot9',height = 240)
),
column(width = 6,
plotOutput('plot10',height = 240)
),
column(width = 6,
plotOutput('plot11',height = 240)
),
column(width = 6,
plotOutput('plot12',height = 240)
)
)
)
)
)
),
tabPanel("Tab 2"
),
tabPanel("Tab 3"
),
tabPanel("Tab 4"
)
)
server just using same plot for every plotOutput
function(input, output, session) {
output$plot1 <- renderPlot({ #just use the same plot on different plots like plot2,plot3,etc
cars2 <- cars + rnorm(nrow(cars))
plot(cars2)
})
}
First, your code has a lot of repetitive parts. We can use lapply to creare these parts more efficiently as follow.
Based on this answer (https://stackoverflow.com/a/26785047/7669809), I added tags$head(tags$style(".shiny-plot-output{height:40vh !important;}")) to your navbarPage. It seems to work. You can change 40vh to other number you would like to use.
library(shiny)
library(htmlwidgets)
ui <- navbarPage("NarBar",
tags$head(tags$style(".shiny-plot-output{height:40vh !important;}")),
tabPanel("Tab1",
column(12,
column(4,
lapply(1:2, function(x){
column(12,
checkboxInput(paste0("ID", x),
paste0("Checkbox", x),
FALSE)
)
})
),
column(8,
lapply(1:4, function(x){
column(3,
selectInput(paste0("ID", x),
paste0("Select", x, ":"),
c("A" = "a",
"B" = "b",
"C" = "c")))
})
)
),
column(12,
column(4,
lapply(1:6, function(x){
column(12,
selectInput(paste0("ID", x),
paste0("Select", x, ":"),
c("A" = "a",
"B" = "b",
"C" = "c")
)
)
})
),
column(width = 8,
tabsetPanel(
tabPanel(title = 'Tab1',
lapply(1:4, function(x){
column(width = 6,
plotOutput(paste0('plot', x))
)
})
),
tabPanel(title = 'Tab2',
lapply(5:8, function(x){
column(width = 6,
plotOutput(paste0('plot', x))
)
})
),
tabPanel(title = 'Tab3',
lapply(9:12, function(x){
column(width = 6,
plotOutput(paste0('plot', x))
)
})
)
)
)
)
),
tabPanel("Tab 2"
),
tabPanel("Tab 3"
),
tabPanel("Tab 4"
)
)
server <- function(input, output, session) {
lapply(1:12, function(x) {
output[[paste0('plot', x)]] <- renderPlot({
cars2 <- cars + rnorm(nrow(cars))
plot(cars2)
})
})
}
shinyApp(ui, server)
I have 2 individual (differently styled) buttons in my shiny App that unfortunately have no vertical padding between them. One of them is a simple HTML button while the other is a shiny actionButton.
I have tried using tags$style but don't think I am using it correctly. My code for the relevant parts are
HTML('<button data-toggle="collapse" data-target="#addtools">Additional tools</button>'),
tags$div(id = 'addtools', class="collapse",
checkboxInput("cluster", "Cluster customers", value = TRUE),
checkboxInput("circle", "Add circles", value = FALSE),
conditionalPanel("input.circle",
selectInput("sizes", "Radius:",
c("5 miles" = "5",
"10 miles" = "10",
"20 miles" = "20"))
)
),
actionButton("runfilters", label = "Apply filters")
The entire UI part of this file is:
tabPanel("Map",
div(class="outer",
tags$head(
includeCSS("styles.css"),
includeScript("gomap.js")
),
leafletOutput(outputId = "map", width = "100%", height = "100%"),
absolutePanel(id = "controls", class = "panel panel-default", fixed = TRUE,
draggable = TRUE, top = 60, left = "auto", right = 20, bottom = "auto",
width = 330, height = "auto",
h2("Select your filters:"),
selectInput("level",
"Detail level:",
c("Customer level", "County level"),
selected = "County level"),
selectInput("mapstates","States:", c("All states"="",
structure(state.abb, names=state.name),
"Washington, DC"="DC"),
multiple = TRUE
),
conditionalPanel("input.mapstates",
selectInput("mapcounties", "Counties", c("All counties"=""),
multiple = TRUE
)
),
radioButtons("retailcorrection","Customer ownership:",
c("Private",
"Public"),
selected = "Private",
inline = TRUE),
conditionalPanel("input.level == 'Customer level'",
selectInput("var",
label = "Customer type:",
choices = c("ALL",
"ESSENTIAL",
"NON-ESSENTIAL"),
selected = "ALL"
),
radioButtons("custoporoh","Widget Category:",
c("Widget A",
"Widget B"),
selected = "Widget A",
inline = TRUE),
conditionalPanel("input.custoporoh == 'Widget A'",
numericInput("oprange",
label = "Minimum average monthly Widget A ordering (in dosage units):",
min = 0, max = 1000000, value = 0
),
numericInput("opprange",
label = "Minimum average monthly Widget A ordering as a percentage of total ordering:",
min = -1, max = 1, value = -1
)
),
conditionalPanel("input.custoporoh == 'Widget B'",
numericInput("ohrange","Minimum average monthly Widget B ordering (in dosage units):",
min = 0, max = 1000000, value = 0
),
numericInput("ohprange",
label = "Minimum average monthly Widget B ordering as a percentage of total ordering:",
min = -1, max = 1, value = -1
)
),
HTML('<button data-toggle="collapse" data-target="#addtools">Additional tools</button>'),
tags$div(id = 'addtools', class="collapse",
checkboxInput("cluster", "Cluster customers", value = TRUE),
checkboxInput("circle", "Add circles", value = FALSE),
conditionalPanel("input.circle",
selectInput("sizes", "Radius:",
c("5 miles" = "5",
"10 miles" = "10",
"20 miles" = "20"))
)
)
),
conditionalPanel("input.level == 'County level'",
selectInput("countyvar",
label = "Customer type:",
choices = c("ALL",
"ESSENTIAL"),
selected = "ALL"
),
selectInput("year", "Year:",
choices = c("2006","2007","2008","2009","2010","2011", "2012",
"2013","2014","2015","2016","2017","2018", "All years" = "2019"),
selected = "2019"
),
radioButtons("oporoh","Widget Category:",
c("Widget A",
"Widget B"),
selected = "Widget A",
inline = TRUE),
conditionalPanel("input.oporoh == 'Widget A'",
numericInput("opppcrange",
label = HTML("Minimum Widget A units per adult per month:"),
min = 0, max = 160, value = 0
),
numericInput("opcrange",
label = "Minimum average monthly Widget A ordering (in dosage units):",
min = 0, max = 10000000, value = 0
),
numericInput("oppcrange",
label = "Minimum average monthly Widget A ordering as a percentage of total ordering:",
min = -1, max = 1, value = -1
)
),
conditionalPanel("input.oporoh == 'Widget B'",
numericInput("ohppcrange",
label = "Minimum Widget B units per adult per month:",
min = 0, max = 160, value = 0
),
numericInput("ohcrange","Minimum average monthly Widget B ordering (in dosage units):",
min = 0, max = 10000000, value = 0
),
numericInput("ohpcrange",
label = "Minimum average monthly Widget B ordering as a percentage of total ordering:",
min = -1, max = 1, value = -1
)
)
),
actionButton("runfilters", label = "Apply filters")
)
)
)
I have tried to implement:
HTML('<button data-toggle="collapse" data-target="#addtools">Additional tools</button>'),
tags$div(id = 'addtools', class="collapse", tags$style = "padding=10px"
but that doesn't seem to be working. Any help would be appreciated.
I am trying to read files that has json content and convert that to tabular data based on some fields.
The file includes content like this:
{"senderDateTimeStamp":"2016/04/08 10:03:18","senderHost":null,"senderCode":"web_app","senderUsecase":"appinternalstats_prod","destinationTopic":"web_app_appinternalstats_realtimedata_topic","correlatedRecord":false,"needCorrelationCacheCleanup":false,"needCorrelation":false,"correlationAttributes":null,"correlationRecordCount":0,"correlateTimeWindowInMills":0,"lastCorrelationRecord":false,"realtimeESStorage":true,"receiverDateTimeStamp":1460124283554,"payloadData":{"timestamp":"2016-04-08T10:03:18.244","status":"get","source":"MSG1","ITEM":"TEST1","basis":"","pricingdate":"","content":"","msgname":"","idlreqno":"","host":"web01","Webservermember":"Web"},"payloadDataText":"","key":"web_app:appinternalstats_prod","destinationTopicName":"web_app_appinternalstats_realtimedata_topic","esindex":"web_app","estype":"appinternalstats_prod","useCase":"appinternalstats_prod","Code":"web_app"}
I need to be able to convert timestamp, source, host, status fields withing payloadData section for each line into a data frame in R.
I've tried this:
library(rjson)
d<-fromJSON(file="file.txt")
dput(d)
structure(list(senderDateTimeStamp = "2016/04/08 10:03:18", senderHost = NULL,
senderAppcode = "web", senderUsecase = "appinternalstats_prod",
destinationTopic = "web_appinternalstats_realtimedata_topic",
correlatedRecord = FALSE, needCorrelationCacheCleanup = FALSE,
needCorrelation = FALSE, correlationAttributes = NULL, correlationRecordCount = 0,
correlateTimeWindowInMills = 0, lastCorrelationRecord = FALSE,
realtimeESStorage = TRUE, receiverDateTimeStamp = 1460124283554,
payloadData = structure(list(timestamp = "2016-04-08T10:03:18.244",
status = "get", source = "MSG1",
region = "", evetid = "", osareqid = "", basis = "",
pricingdate = "", content = "", msgname = "", recipient = "",
objid = "", idlreqno = "", host = "web01", webservermember = "webSingleton"),
.Names = c("timestamp",
"status", "source", "region", "evetid",
"osareqid", "basis", "pricingdate", "content", "msgname",
"recipient", "objid", "idlreqno", "host", "webservermember"
)), payloadDataText = "", key = "web:appinternalstats_prod",
destinationTopicName = "web_appinternalstats_realtimedata_topic",
hdfsPath = "web/appinternalstats_prod", esindex = "web",
estype = "appinternalstats_prod", useCase = "appinternalstats_prod",
appCode = "web"), .Names = c("senderDateTimeStamp", "senderHost",
"senderAppcode", "senderUsecase", "destinationTopic", "correlatedRecord",
"needCorrelationCacheCleanup", "needCorrelation", "correlationAttributes",
"correlationRecordCount", "correlateTimeWindowInMills", "lastCorrelationRecord",
"realtimeESStorage", "receiverDateTimeStamp", "payloadData",
"payloadDataText", "key", "destinationTopicName", "hdfsPath",
"esindex", "estype", "useCase", "appCode"))
Any ideas how I could convert payloadData section of the json entry into a data frame?
This might be something you want:
library(rjson)
d<-fromJSON(file="file.txt")
myDf <- do.call("rbind", lapply(d, function(x) {
data.frame(TimeStamp = x$payloadData$timestamp,
Source = x$payloadData$source,
Host = $payloadData$host,
Status = x$payloadData$status)}))
Consider the package tidyjson:
library(tidyjson)
library(magrittr)
json <- '{"senderDateTimeStamp":"2016/04/08 10:03:18","senderHost":null,"senderCode":"web_app","senderUsecase":"appinternalstats_prod","destinationTopic":"web_app_appinternalstats_realtimedata_topic","correlatedRecord":false,"needCorrelationCacheCleanup":false,"needCorrelation":false,"correlationAttributes":null,"correlationRecordCount":0,"correlateTimeWindowInMills":0,"lastCorrelationRecord":false,"realtimeESStorage":true,"receiverDateTimeStamp":1460124283554,"payloadData":{"timestamp":"2016-04-08T10:03:18.244","status":"get","source":"MSG1","ITEM":"TEST1","basis":"","pricingdate":"","content":"","msgname":"","idlreqno":"","host":"web01","Webservermember":"Web"},"payloadDataText":"","key":"web_app:appinternalstats_prod","destinationTopicName":"web_app_appinternalstats_realtimedata_topic","esindex":"web_app","estype":"appinternalstats_prod","useCase":"appinternalstats_prod","Code":"web_app"}'
json %>%
gather_keys()
# head() of above
# document.id key
# 1 1 senderDateTimeStamp
# 2 1 senderHost
# 3 1 senderCode
# 4 1 senderUsecase
# 5 1 destinationTopic
# 6 1 correlatedRecord
json %>%
enter_object("payloadData") %>%
gather_keys() %>%
append_values_string()
# head() of above
# document.id key string
# 1 1 timestamp 2016-04-08T10:03:18.244
# 2 1 status get
# 3 1 source MSG1
# 4 1 ITEM TEST1
# 5 1 basis
# 6 1 pricingdate