r

问题 I am trying to display sales (y-axis) week over week (x-axis) for 890 vendors. I want to display this data using a facet wrap to quickly see where vendors are having a spike in sales. The plot in my RStudio console looks as such. This Makes sense, as rendering the plot here isnt the best view, however how can I properly format my plots onto a PDF even if it requires multiple pages of PDFs. Code for plot ggplot(Holiday_Spike_Table, aes(x = FSCL_WK, y = SLS))+ geom_col()+ facet_wrap(~MVNDR_NM)

问题 I'd like to train a convolutional network to solve a multi-class, multi-label problem on image data. Due to the nature of the data, and for reasons I'll spare you, it would be best if I could use a custom R generator function to feed to the fit_generator command, instead of its built-in image_data_generator and flow_images_from_directory commands (which I was successfully able to get working, just not for this particular problem). Here (https://www.rdocumentation.org/packages/keras/versions/2

问题 I am trying to display sales (y-axis) week over week (x-axis) for 890 vendors. I want to display this data using a facet wrap to quickly see where vendors are having a spike in sales. The plot in my RStudio console looks as such. This Makes sense, as rendering the plot here isnt the best view, however how can I properly format my plots onto a PDF even if it requires multiple pages of PDFs. Code for plot ggplot(Holiday_Spike_Table, aes(x = FSCL_WK, y = SLS))+ geom_col()+ facet_wrap(~MVNDR_NM)

问题 I have two multipolygons and I want to test intersections between their geometries based on groups of years. Basically I have a flood multipolygon that contains flood events and their geometry and an election dataset which has each election as ward*year units, containing the geometry of that ward. I want to see if there are any intersections in the electoral ward each cycle prior to each election. So if the election was in 2009 and the cycle was 2007-2009 I want to see if its ward was flooded

问题 This post makes it clear that the function bq_auth() should be used to authenticate BigQuery in R. However, I have created a BigQuery-Admin service account, downloaded a service account key, and have passed that key into the bq_auth() function, yet I continue to receive the error: > bigrquery::bq_auth(path = '/Users/nicholas/Downloads/just_downladed_this_key.json') trying token_fetch() trying credentials_service_account() adding 'userinfo.email' scope Error: unable to load shared object '

问题 This post makes it clear that the function bq_auth() should be used to authenticate BigQuery in R. However, I have created a BigQuery-Admin service account, downloaded a service account key, and have passed that key into the bq_auth() function, yet I continue to receive the error: > bigrquery::bq_auth(path = '/Users/nicholas/Downloads/just_downladed_this_key.json') trying token_fetch() trying credentials_service_account() adding 'userinfo.email' scope Error: unable to load shared object '

问题 This post makes it clear that the function bq_auth() should be used to authenticate BigQuery in R. However, I have created a BigQuery-Admin service account, downloaded a service account key, and have passed that key into the bq_auth() function, yet I continue to receive the error: > bigrquery::bq_auth(path = '/Users/nicholas/Downloads/just_downladed_this_key.json') trying token_fetch() trying credentials_service_account() adding 'userinfo.email' scope Error: unable to load shared object '

问题 Compiling a report with bookdown I encounter difficulties in referencing tables generated with the huxtable package. For my work, LaTex/PDF, as well as an HTML version of the report, need to be created. When rendering the document knitr::is_XXX_output() selects the optimal way to display the tables, see MWE: ```{r chunk-label, results='asis', fig.cap='chunk-caption'} set.seed(1234) dat <- data.frame(cond = factor(rep(c("A","B"), each=2)), rating = c(rnorm(2),rnorm(2, mean=.8))) hux <- as_hux

问题 I have a time series data frame in R that has a column, V1, which consists of integers with a few NAs interspersed throughout. I want to iterate over this column and subtract V1 from itself one time step previously. However, I want to ignore the NA values in V1 and use the last non-NA value in the subtraction. If the current value of V1 is NA, then the difference should return NA. See below for an example V1 <- c(1, 3, 4, NA, NA, 6, 9, NA, 10) time <- 1:length(V1) dat <- data.frame(time =

问题 I want refresh data every hour in my shiny dashboard. So that the graphs in shinydashboard automatically update hourly basis. Is there any source where I can learn or any sample code to practice ? Thank you. 回答1: I have got this with invalidateLater function. In the below code i just tried to get distinct names from a MySQL table. After running the shinyApp for first time, i have added a unique row to the same table so that after the specified time(i have checked with 60000 ms) we can check