How to automate the creation of histograms in R, saving the result in a list of hist() objects?
0
I have a code to process data, and I need to save some histograms that I will use in a Shiny application.
What I need is basically automate the creation of histograms, saving the result in a list of hist() objects, that I will save in an RDS file and then simply call in my Shiny app.
The code below shows the output that I want, but the variables names are hard coded, and it's not viable for me.
# Create data for this example
list_dfs <- list(
dfA = data.frame(Var1 = rnorm(100), Date1 = rep(1:50, 2), Var2 = rnorm(100)*.55),
dfB = data.frame(Var3 = rnorm(100), Date2 = rep(1:50, 2), Var4 = rnorm(100)*.55),
dfC = data.frame(Var5 = rnorm(100), Date3 = rep(1:50, 2), Var6 = rnorm(100)*.55)
)
# Part that I want to automate
list_plots <- list(
dfA = NULL,
dfB = NULL,
dfC = NULL
)
list_plots$dfA <- lapply(list_dfs[[1]], function(x){hist(x, plot = FALSE)})
list_plots$dfB <- lapply(list_dfs[[2]], function(x){hist(x, plot = FALSE)})
list_plots$dfC <- lapply(list_dfs[[3]], function(x){hist(x, plot = FALSE)})
# Desired output - Histograms saved in a list
list_plots$dfA$Var1 %>% plot
list_plots$dfA$Date1 %>% plot
list_plots$dfA$Var2 %>% plot
list_plots$dfB$Var3 %>% plot
list_plots$dfB$Date2 %>% plot
list_plots$dfB$Var4 %>% plot
list_plots$dfC$Var5 %>% plot
list_plots$dfC$Date3 %>% plot
list_plots$dfC$Var6 %>% plot
Thanks in advance.
Wlademir.
r shiny dplyr histogram tibble
asked Nov 22 '18 at 16:04
Wlademir Ribeiro PratesWlademir Ribeiro Prates
16912
add a comment |
0
I have a code to process data, and I need to save some histograms that I will use in a Shiny application.
What I need is basically automate the creation of histograms, saving the result in a list of hist() objects, that I will save in an RDS file and then simply call in my Shiny app.
The code below shows the output that I want, but the variables names are hard coded, and it's not viable for me.
# Create data for this example
list_dfs <- list(
dfA = data.frame(Var1 = rnorm(100), Date1 = rep(1:50, 2), Var2 = rnorm(100)*.55),
dfB = data.frame(Var3 = rnorm(100), Date2 = rep(1:50, 2), Var4 = rnorm(100)*.55),
dfC = data.frame(Var5 = rnorm(100), Date3 = rep(1:50, 2), Var6 = rnorm(100)*.55)
)
# Part that I want to automate
list_plots <- list(
dfA = NULL,
dfB = NULL,
dfC = NULL
)
list_plots$dfA <- lapply(list_dfs[[1]], function(x){hist(x, plot = FALSE)})
list_plots$dfB <- lapply(list_dfs[[2]], function(x){hist(x, plot = FALSE)})
list_plots$dfC <- lapply(list_dfs[[3]], function(x){hist(x, plot = FALSE)})
# Desired output - Histograms saved in a list
list_plots$dfA$Var1 %>% plot
list_plots$dfA$Date1 %>% plot
list_plots$dfA$Var2 %>% plot
list_plots$dfB$Var3 %>% plot
list_plots$dfB$Date2 %>% plot
list_plots$dfB$Var4 %>% plot
list_plots$dfC$Var5 %>% plot
list_plots$dfC$Date3 %>% plot
list_plots$dfC$Var6 %>% plot
Thanks in advance.
Wlademir.
r shiny dplyr histogram tibble
asked Nov 22 '18 at 16:04
Wlademir Ribeiro PratesWlademir Ribeiro Prates
16912
add a comment |
0
0
0
I have a code to process data, and I need to save some histograms that I will use in a Shiny application.
What I need is basically automate the creation of histograms, saving the result in a list of hist() objects, that I will save in an RDS file and then simply call in my Shiny app.
The code below shows the output that I want, but the variables names are hard coded, and it's not viable for me.
# Create data for this example
list_dfs <- list(
dfA = data.frame(Var1 = rnorm(100), Date1 = rep(1:50, 2), Var2 = rnorm(100)*.55),
dfB = data.frame(Var3 = rnorm(100), Date2 = rep(1:50, 2), Var4 = rnorm(100)*.55),
dfC = data.frame(Var5 = rnorm(100), Date3 = rep(1:50, 2), Var6 = rnorm(100)*.55)
)
# Part that I want to automate
list_plots <- list(
dfA = NULL,
dfB = NULL,
dfC = NULL
)
list_plots$dfA <- lapply(list_dfs[[1]], function(x){hist(x, plot = FALSE)})
list_plots$dfB <- lapply(list_dfs[[2]], function(x){hist(x, plot = FALSE)})
list_plots$dfC <- lapply(list_dfs[[3]], function(x){hist(x, plot = FALSE)})
# Desired output - Histograms saved in a list
list_plots$dfA$Var1 %>% plot
list_plots$dfA$Date1 %>% plot
list_plots$dfA$Var2 %>% plot
list_plots$dfB$Var3 %>% plot
list_plots$dfB$Date2 %>% plot
list_plots$dfB$Var4 %>% plot
list_plots$dfC$Var5 %>% plot
list_plots$dfC$Date3 %>% plot
list_plots$dfC$Var6 %>% plot
Thanks in advance.
Wlademir.
r shiny dplyr histogram tibble
asked Nov 22 '18 at 16:04
Wlademir Ribeiro PratesWlademir Ribeiro Prates
16912
I have a code to process data, and I need to save some histograms that I will use in a Shiny application.
What I need is basically automate the creation of histograms, saving the result in a list of hist() objects, that I will save in an RDS file and then simply call in my Shiny app.
The code below shows the output that I want, but the variables names are hard coded, and it's not viable for me.
# Create data for this example
list_dfs <- list(
dfA = data.frame(Var1 = rnorm(100), Date1 = rep(1:50, 2), Var2 = rnorm(100)*.55),
dfB = data.frame(Var3 = rnorm(100), Date2 = rep(1:50, 2), Var4 = rnorm(100)*.55),
dfC = data.frame(Var5 = rnorm(100), Date3 = rep(1:50, 2), Var6 = rnorm(100)*.55)
)
# Part that I want to automate
list_plots <- list(
dfA = NULL,
dfB = NULL,
dfC = NULL
)
list_plots$dfA <- lapply(list_dfs[[1]], function(x){hist(x, plot = FALSE)})
list_plots$dfB <- lapply(list_dfs[[2]], function(x){hist(x, plot = FALSE)})
list_plots$dfC <- lapply(list_dfs[[3]], function(x){hist(x, plot = FALSE)})
# Desired output - Histograms saved in a list
list_plots$dfA$Var1 %>% plot
list_plots$dfA$Date1 %>% plot
list_plots$dfA$Var2 %>% plot
list_plots$dfB$Var3 %>% plot
list_plots$dfB$Date2 %>% plot
list_plots$dfB$Var4 %>% plot
list_plots$dfC$Var5 %>% plot
list_plots$dfC$Date3 %>% plot
list_plots$dfC$Var6 %>% plot
Thanks in advance.
Wlademir.
r shiny dplyr histogram tibble
r shiny dplyr histogram tibble
asked Nov 22 '18 at 16:04
Wlademir Ribeiro PratesWlademir Ribeiro Prates
16912
asked Nov 22 '18 at 16:04
Wlademir Ribeiro PratesWlademir Ribeiro Prates
16912
edited Nov 22 '18 at 16:19
Wlademir Ribeiro Prates
asked Nov 22 '18 at 16:04
Wlademir Ribeiro PratesWlademir Ribeiro Prates
16912
asked Nov 22 '18 at 16:04
Wlademir Ribeiro PratesWlademir Ribeiro Prates
16912
asked Nov 22 '18 at 16:04
Wlademir Ribeiro PratesWlademir Ribeiro Prates
16912
16912
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
1
res <- lapply(list_dfs, function(z){
ll <- lapply(z, function(x){
hist(x, plot = FALSE)
})
names(ll) <- names(z)
return(ll)
})
names(res) <- names(list_dfs)
You may wan't to modify object naming to your liking, and not necessarily nest the plots.
answered Nov 22 '18 at 16:24
NutleNutle
308215
Thanks! It's exactly what I need!
– Wlademir Ribeiro Prates
Nov 22 '18 at 16:30
1
This can be simplified tores <- lapply(list_dfs, function(z) lapply(z, hist, plot = FALSE))
– Ista
Nov 22 '18 at 16:56
1
Yeah, pardon the style, this indeed can be golfed down if there is a need for it
– Nutle
Nov 22 '18 at 18:35
Both solutions are great. I did the same for density(), then I will plot these results with highcharter package in a shiny app. The goal is that I don't need to load all the data into the shiny app. Thanks.
– Wlademir Ribeiro Prates
Nov 22 '18 at 19:01
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
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oldest
votes
1
res <- lapply(list_dfs, function(z){
ll <- lapply(z, function(x){
hist(x, plot = FALSE)
})
names(ll) <- names(z)
return(ll)
})
names(res) <- names(list_dfs)
You may wan't to modify object naming to your liking, and not necessarily nest the plots.
answered Nov 22 '18 at 16:24
NutleNutle
308215
Thanks! It's exactly what I need!
– Wlademir Ribeiro Prates
Nov 22 '18 at 16:30
1
This can be simplified tores <- lapply(list_dfs, function(z) lapply(z, hist, plot = FALSE))
– Ista
Nov 22 '18 at 16:56
1
Yeah, pardon the style, this indeed can be golfed down if there is a need for it
– Nutle
Nov 22 '18 at 18:35
Both solutions are great. I did the same for density(), then I will plot these results with highcharter package in a shiny app. The goal is that I don't need to load all the data into the shiny app. Thanks.
– Wlademir Ribeiro Prates
Nov 22 '18 at 19:01
add a comment |
1
res <- lapply(list_dfs, function(z){
ll <- lapply(z, function(x){
hist(x, plot = FALSE)
})
names(ll) <- names(z)
return(ll)
})
names(res) <- names(list_dfs)
You may wan't to modify object naming to your liking, and not necessarily nest the plots.
answered Nov 22 '18 at 16:24
NutleNutle
308215
Thanks! It's exactly what I need!
– Wlademir Ribeiro Prates
Nov 22 '18 at 16:30
1
This can be simplified tores <- lapply(list_dfs, function(z) lapply(z, hist, plot = FALSE))
– Ista
Nov 22 '18 at 16:56
1
Yeah, pardon the style, this indeed can be golfed down if there is a need for it
– Nutle
Nov 22 '18 at 18:35
Both solutions are great. I did the same for density(), then I will plot these results with highcharter package in a shiny app. The goal is that I don't need to load all the data into the shiny app. Thanks.
– Wlademir Ribeiro Prates
Nov 22 '18 at 19:01
add a comment |
1
1
1
res <- lapply(list_dfs, function(z){
ll <- lapply(z, function(x){
hist(x, plot = FALSE)
})
names(ll) <- names(z)
return(ll)
})
names(res) <- names(list_dfs)
You may wan't to modify object naming to your liking, and not necessarily nest the plots.
answered Nov 22 '18 at 16:24
NutleNutle
308215
res <- lapply(list_dfs, function(z){
ll <- lapply(z, function(x){
hist(x, plot = FALSE)
})
names(ll) <- names(z)
return(ll)
})
names(res) <- names(list_dfs)
You may wan't to modify object naming to your liking, and not necessarily nest the plots.
answered Nov 22 '18 at 16:24
NutleNutle
308215
answered Nov 22 '18 at 16:24
NutleNutle
308215
answered Nov 22 '18 at 16:24
NutleNutle
308215
answered Nov 22 '18 at 16:24
NutleNutle
308215
308215
Thanks! It's exactly what I need!
– Wlademir Ribeiro Prates
Nov 22 '18 at 16:30
1
This can be simplified tores <- lapply(list_dfs, function(z) lapply(z, hist, plot = FALSE))
– Ista
Nov 22 '18 at 16:56
1
Yeah, pardon the style, this indeed can be golfed down if there is a need for it
– Nutle
Nov 22 '18 at 18:35
Both solutions are great. I did the same for density(), then I will plot these results with highcharter package in a shiny app. The goal is that I don't need to load all the data into the shiny app. Thanks.
– Wlademir Ribeiro Prates
Nov 22 '18 at 19:01
add a comment |
Thanks! It's exactly what I need!
– Wlademir Ribeiro Prates
Nov 22 '18 at 16:30
1
This can be simplified tores <- lapply(list_dfs, function(z) lapply(z, hist, plot = FALSE))
– Ista
Nov 22 '18 at 16:56
1
Yeah, pardon the style, this indeed can be golfed down if there is a need for it
– Nutle
Nov 22 '18 at 18:35
Both solutions are great. I did the same for density(), then I will plot these results with highcharter package in a shiny app. The goal is that I don't need to load all the data into the shiny app. Thanks.
– Wlademir Ribeiro Prates
Nov 22 '18 at 19:01
Thanks! It's exactly what I need!
– Wlademir Ribeiro Prates
Nov 22 '18 at 16:30
Thanks! It's exactly what I need!
– Wlademir Ribeiro Prates
Nov 22 '18 at 16:30
1
1
This can be simplified to
res <- lapply(list_dfs, function(z) lapply(z, hist, plot = FALSE))– Ista
Nov 22 '18 at 16:56
This can be simplified to
res <- lapply(list_dfs, function(z) lapply(z, hist, plot = FALSE))– Ista
Nov 22 '18 at 16:56
1
1
Yeah, pardon the style, this indeed can be golfed down if there is a need for it
– Nutle
Nov 22 '18 at 18:35
Yeah, pardon the style, this indeed can be golfed down if there is a need for it
– Nutle
Nov 22 '18 at 18:35
Both solutions are great. I did the same for density(), then I will plot these results with highcharter package in a shiny app. The goal is that I don't need to load all the data into the shiny app. Thanks.
– Wlademir Ribeiro Prates
Nov 22 '18 at 19:01
Both solutions are great. I did the same for density(), then I will plot these results with highcharter package in a shiny app. The goal is that I don't need to load all the data into the shiny app. Thanks.
– Wlademir Ribeiro Prates
Nov 22 '18 at 19:01
add a comment |
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