plot_trend: Plot trendline for run_visual_dive()

In southwick-associates/sadash: Prepare Agency Dashboard Data for state-level dashboards

Description

To be run from run_visual_dive. This will plot a count of participants, optionally facetted down and/or across by additional variables. If facetting (i.e., grouping) missing values will be removed from the corresponding variables before plotting.

Usage

plot_trend(tbl, down = "None", across = "None")

Arguments

tbl	data frame holding table produced by summarize_trend
down	variable name for optional facetting down. If "None", no facetting will be done.
across	variable name for optional facetting across. If "None", no facetting will be done.

See Also

Other data dive functions: drop_state_code(), filter_demo(), get_county_map_dive(), load_cust_samp(), plot_county_dive(), plot_dist(), run_visual_dive(), set_nonres_county_na(), set_other_county_na(), summarize_trend()

Examples

library(dplyr)
data(hist_samp)
priv <- filter(hist_samp, priv == "all_sports")

summarize_trend(priv, pct = 1) %>% plot_trend()
summarize_trend(priv, "sex", pct = 1) %>% plot_trend("sex")
summarize_trend(priv, "sex", "age", pct = 1) %>% plot_trend("sex", "age")

summarize_trend(priv, pct = 1, metric = "churn") %>% plot_trend()
summarize_trend(priv, "sex", pct = 1, metric = "churn") %>% plot_trend("sex")

southwick-associates/sadash documentation built on Jan. 6, 2022, 5:17 p.m.