library(datavyu)
library(tidyverse)
# find_unique_values("ex-data/datavyu_output_07-06-2020_14-46", what = "codes")[1]
f <- datavyur::datavyu_search(folder = "data/datavyu_output_03-15-2021_10-40") %>% as_tibble()
f$column %>% unique()
## [1] "LogClass_AS_ActivityFormat" "LogClass_AS_ParticipationFormat"
## [3] "LogClass_AS_TeacherPrompt" "LogClass_IG"
## [5] "LogClass_IS" "LogClass_IT"
## [7] "LogClass_TO_MathPresent" "LogClass_TaskUsed"
f$file %>% unique()
## [1] "EP 15-02-26 T602 Content Log Spinup Updated"
options(directory = "data/datavyu_output_03-15-2021_10-40")
{datavyu} can help to summarize a column. It defaults to summarizing the frequency of codes for a specified column.
summarize_column(column = "LogClass_AS_ActivityFormat",
code = "code01")
## # A tibble: 4 x 3
## code01 n percent
## * <chr> <dbl> <dbl>
## 1 g 5 0.385
## 2 cd 4 0.308
## 3 l 2 0.154
## 4 o 2 0.154
summarize_column(column = "LogClass_IT",
code = "code01")
## # A tibble: 1 x 3
## code01 n percent
## * <chr> <dbl> <dbl>
## 1 s 12 1
p1 <- prep_time_series(column = "LogClass_AS_ActivityFormat",
code = "code01")
p1i <- p1 %>%
select(-file) %>%
rename(code_af = code)
p2 <- prep_time_series(column = "LogClass_IT",
code = "code01")
p2i <- p2 %>%
select(-file) %>%
rename(code_it = code)
pp <- full_join(p1i, p2i)
pp <- pp %>%
filter(ts > 216) %>%
mutate(ts = ts - 216)
pp %>%
ggplot(aes(x = ts, y = 1, color = code_af)) +
geom_point() +
geom_point(data = pp, aes(x = ts, y = 1, color = code_it), shape = 8, size = 3) +
ylab(NULL) +
xlab("Time (m)") +
theme(axis.title.y = element_blank(),
axis.text.y = element_blank(),
axis.ticks.y = element_blank()) +
scale_y_discrete(breaks = NULL) +
labs(subtitle = stringr::str_c("Units: s")) +
theme(text = element_text(family = "Times", size = 14)) +
scale_x_time() +
theme_minimal() +
scale_color_brewer("Activity Format", type = "qual", palette = 1) +
labs(caption = "Asterisk indicates the presence of a spin-up")
ggsave("2021-03-12-tca2-plot10.png", width = 8, height = 4)