# Load libraries
library(tidyverse)
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## ✔ purrr 1.1.0
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library(lubridate)
library(nycflights13)
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library(tidyquant)
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## method from
## as.zoo.data.frame zoo
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library(tidyverse)
df <- read_csv("multipleChoiceResponses1.csv")
## Rows: 16716 Columns: 47
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (46): LearningPlatformUsefulnessArxiv, LearningPlatformUsefulnessBlogs, ...
## dbl (1): Age
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
###1. Count the usefulness by learning platform.
df1 <- df %>%
select(starts_with("LearningPlatformUsefulness")) %>%
pivot_longer(everything(), names_to = "learning_platform", values_to = "usefulness") %>%
filter(!is.na(usefulness)) %>%
mutate(learning_platform = str_remove(learning_platform, "LearningPlatformUsefulness")) %>%
count(learning_platform, usefulness)
###2. Compute the number of total reponses and number of reponses which are atleast useful
df2 <- df1 %>%
group_by(learning_platform) %>%
summarize(
tot = sum(n),
count = sum(n[usefulness != "Not Useful"])
) %>%
mutate(perc_usefulness = count / tot)
###3. Based on previous results, select the first two columns learning_platform and count.
df3 <- df2 %>%
select(learning_platform, count) %>%
arrange(desc(count)) %>%
mutate(
cum_pct = cumsum(count) / sum(count),
learning_platform = fct_reorder(learning_platform, count)
) %>%
mutate(learning_platform = fct_relevel(learning_platform, "Other", after = Inf))
## Warning: There was 1 warning in `mutate()`.
## ℹ In argument: `learning_platform = fct_relevel(learning_platform, "Other",
## after = Inf)`.
## Caused by warning:
## ! 1 unknown level in `f`: Other
df3 <- df2 %>%
arrange(desc(count)) %>%
mutate(rank = row_number(),
learning_platform = if_else(rank <= 10, learning_platform, "Other")) %>%
group_by(learning_platform) %>%
summarize(count = sum(count)) %>%
ungroup() %>%
arrange(desc(count)) %>%
mutate(
cum_pct = cumsum(count) / sum(count),
rank = row_number(),
label = paste0("Rank: ", rank,
"\nUseful: ", count,
"\nCumPct: ", scales::percent(cum_pct, accuracy = 0.1))
)
###4. Based on the previous results, show the plotting as follows.
library(tidyverse)
library(scales)
##
## Attaching package: 'scales'
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## discard
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##
## col_factor
library(forcats)
ggplot(df3, aes(x = fct_reorder(learning_platform, count), y = count)) +
geom_col(fill = "gray30", width = 0.7) +
coord_flip() +
# annotation boxes on the right
geom_label(aes(
label = paste0("Rank: ", rank,
"\nUseful: ", format(count, big.mark=","),
"\nCumPct: ", percent(cum_pct, accuracy = 0.1))
),
hjust = 0, vjust = 0.5, size = 1.5, label.size = 0.2, fill = "white"
) +
expand_limits(y = max(df3$count) * 1.25) + # add right margin for labels
labs(
title = "Top 10 learning platform",
x = "Learning platform",
y = "Number of responses with at least usefulness"
) +
theme_minimal(base_size = 12) +
theme(
plot.title = element_text(size = 16, hjust = 0.5, face = "bold"),
panel.grid.major.y = element_blank(),
panel.grid.minor = element_blank(),
axis.title.y = element_text(size = 12),
axis.title.x = element_text(size = 12)
)
## Warning: The `label.size` argument of `geom_label()` is deprecated as of ggplot2 3.5.0.
## ℹ Please use the `linewidth` argument instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
