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Update Rmd example
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@DivadNojnarg
DivadNojnarg authored Oct 19, 2023
1 parent 1f05b4b commit 23aa1d3
Showing 1 changed file with 167 additions and 80 deletions.
247 changes: 167 additions & 80 deletions inst/examples/simple-rmd/analysis.Rmd
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Expand Up @@ -5,7 +5,7 @@ date: "`r Sys.Date()`"
output:
html_document:
theme:
version: 4
version: 5
runtime: shiny
---

Expand All @@ -14,6 +14,9 @@ runtime: shiny
library(connectapi) # Tested with 0.1.0.9031
library(connectViz)
library(dplyr)
library(shiny)
library(bslib)
rsc_client <- create_rsc_client()
knitr::opts_chunk$set(echo = FALSE, warning=FALSE)
```
Expand All @@ -30,143 +33,227 @@ shiny_apps <- rsc_content %>% filter(app_mode == "shiny")
# rsc_static <- rsc_client %>% get_usage_static(limit = Inf)
```

### General metrics
### General metrics (n)

```{r general-metric}
general_metrics <- list(
"Onboarded Users (n)" = nrow(rsc_users),
"Publishers (n)" = nrow(publishers),
"Deployments (n)" = nrow(rsc_content),
"Shiny Apps (n)" = nrow(shiny_apps)
)
shiny::fluidRow(
align = "center",
purrr::map(
seq_along(general_metrics),
function(i) {
shinydashboard::infoBox(
value = general_metrics[[i]],
title = names(general_metrics)[[i]]
)
}
)
"Onboarded Users" = nrow(rsc_users),
"Publishers" = nrow(publishers),
"Deployments" = nrow(rsc_content),
"Shiny Apps" = nrow(shiny_apps)
)
general_metrics_cards <- purrr::map(
seq_along(general_metrics),
function(i) {
value_box(
value = general_metrics[[i]],
title = names(general_metrics)[[i]]
)
}
)
layout_column_wrap(
width = 1/4,
!!!general_metrics_cards
)
```

### Shiny Apps usage

Important note: with a basic __publisher__ API key, we can only recover the data for the app we own. It means that we are not able to track any other apps, including the one shared with us as maintainer. An admin API has access to all usage data.

#### Most used apps

```{r}
apps_ranking <- create_app_ranking(rsc_content, rsc_users, apps_usage)
create_app_ranking_table(apps_ranking)
card(
full_screen = TRUE,
create_app_ranking_table(apps_ranking),
)
```

#### Daily app usage

```{r}
selectInput("selected_app", "Select an application", apps_ranking[[2]]$app_name)
daily_app_usage <- get_app_daily_usage(apps_ranking[[2]], reactive(input$selected_app))
create_app_daily_usage_chart(daily_app_usage)
```

#### Cumulated duration / user
```{r duration-plot}
create_cumulated_duration_per_user(apps_ranking[[1]], reactive(input$selected_app))
daily_app_usage <- get_app_daily_usage(apps_ranking[[2]], reactive(input$selected_app))
```

#### Number Hits / user

```{r sessions-plot}
create_cumulated_hits_per_user(apps_ranking[[1]], reactive(input$selected_app))
```{r}
card(
full_screen = TRUE,
card_header("App usage"),
layout_sidebar(
sidebar = sidebar(
width = 150,
selectInput(
"selected_app",
"Select an application",
apps_ranking[[2]]$app_name
)
),
p("Daily app usage"),
create_app_daily_usage_chart(daily_app_usage),
create_cumulated_duration_per_user(
apps_ranking[[1]],
selected_app = reactive(input$selected_app)
),
create_cumulated_hits_per_user(
apps_ranking[[1]],
selected_app = reactive(input$selected_app)
)
)
)
```

### Consumer data


#### Consumer ranking
```{r consumer-session-ranking}
numericInput(
"views_threshold",
"N view threshold",
100,
min = 0
consumer_ranking <- create_apps_consumer_ranking(apps_usage, rsc_users)
consumer_ranking_card <- card(
full_screen = TRUE,
card_header("Consumer ranking"),
layout_sidebar(
sidebar = sidebar(
width = 150,
numericInput(
"views_threshold",
"N view threshold",
round(max(consumer_ranking$n / 2)),
min = 0
)
),
create_apps_consumer_ranking_chart(
consumer_ranking, reactive(input$views_threshold)
)
)
)
consumer_ranking <- create_apps_consumer_ranking(apps_usage, rsc_users, reactive(input$views_threshold))
create_apps_consumer_ranking_chart(consumer_ranking)
```

#### Daily app consumption

```{r daily-app-consumption-per-user}
selectInput("selected_user", "Select an application", rsc_users$username)
daily_consumption <- get_user_daily_consumption(rsc_content, rsc_users, apps_usage, reactive(input$selected_user))
create_user_daily_consumption_chart(daily_consumption)
daily_consumption_card <- card(
full_screen = TRUE,
card_header("Daily app consumption"),
layout_sidebar(
sidebar = sidebar(
width = 150,
selectInput("selected_user", "Select a user", rsc_users$username)
),
create_user_daily_consumption_chart(daily_consumption[[2]])
)
)
```

```{r}
layout_column_wrap(
width = 1/2,
daily_consumption_card,
consumer_ranking_card
)
```

### Developers data


#### Developers ranking (number of deployments: api, static, shiny, rmd, ...)

```{r developers-ranking}
developers_apps_ranking <- create_dev_ranking(rsc_users, rsc_content)
numericInput(
"apps_threshold",
"N app threshold",
5,
min = 1,
max = developers_apps_ranking %>% pull(n_apps) %>% max()
max_app <- developers_apps_ranking %>% pull(n_apps) %>% max()
dev_ranking_card <- card(
full_screen = TRUE,
card_header("Developers ranking n deployments (static, shiny, rmd, ...)"),
layout_sidebar(
sidebar = sidebar(
width = 150,
numericInput(
"apps_threshold",
"N app threshold",
round(max_app / 2),
min = 1,
max = max_app
)
),
create_dev_ranking_chart(
developers_apps_ranking,
reactive(input$apps_threshold)
)
)
)
create_dev_ranking_chart(developers_apps_ranking, reactive(input$apps_threshold))
```

#### Developer projects overview

```{r}
selectInput(
"app_developer",
"Select a developer",
developers_apps_ranking$username
dev_projects_card <- card(
full_screen = TRUE,
card_header("Dev projects overview (Shiny apps only)"),
layout_sidebar(
sidebar = sidebar(
width = 150,
selectInput(
"app_developer",
"Select a developer",
developers_apps_ranking$username
)
),
create_dev_project_overview(
rsc_client, apps_ranking[[1]],
reactive(input$app_developer)
)
)
)
```

create_dev_project_overview(developers_apps_ranking, rsc_client, apps_ranking[[1]], reactive(input$app_developer))
```{r}
layout_column_wrap(
width = 1/2,
dev_ranking_card,
dev_projects_card
)
```


### Other data
### General data

#### Users repartition (%)

```{r user-repartition}
# I realized some users are not active (ie active_time is NA).
# Maybe to remove from the viz in the future?
sort_users_by_role(rsc_users) %>% create_pie_chart("user_role")
user_roles <- card(
full_screen = TRUE,
card_header("User roles"),
sort_users_by_role(rsc_users) |> create_pie_chart("user_role")
)
```

#### Content access

How do people protect their content?

```{r content-access-type}
sort_content_by_access(rsc_content) %>% create_pie_chart("access_type")
content_access <- card(
full_screen = TRUE,
card_header("Content access type"),
sort_content_by_access(rsc_content) |> create_pie_chart("access_type")
)
```


#### R versions

What are the R versions used?

```{r content-r-version}
sort_content_by_rversion(rsc_content) %>% create_pie_chart("r_version")
r_versions <- card(
full_screen = TRUE,
card_header("R versions"),
sort_content_by_rversion(rsc_content) |> create_pie_chart("r_version")
)
```

#### Content type

```{r content-type}
sort_content_by_appmode(rsc_content) %>% create_pie_chart("app_mode")
content_type <- card(
full_screen = TRUE,
card_header("Content type"),
sort_content_by_appmode(rsc_content) |> create_pie_chart("app_mode")
)
```

```{r}
layout_column_wrap(
width = 1/2,
user_roles,
content_access,
r_versions,
content_type
)
```

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