state_pct_change: pct_change_state: Create a map of states based upon the...

In tlcaputi/gtrendR: An R Complement to the gtrends Python package

pct_change_state: Create a map of states based upon the percentage increase in searches before or after the interruption

Description

pct_change_state: Create a map of states based upon the percentage increase in searches before or after the interruption

Usage

state_pct_change(
  df,
  interrupt,
  beginperiod = NA,
  preperiod = NA,
  endperiod = NA,
  scaletitle = "Pct. Increase\nin Searches",
  scalelimits = NULL,
  linecol = "gray",
  lowcol = NA,
  midcol = NULL,
  highcol = NA,
  colorscheme = "red",
  save = T,
  width = 6,
  height = 4,
  bootstrap = T,
  outfn = "./output/fig.png",
  bootnum = 1000,
  alpha = 0.05,
  return_df = T
)

Arguments

df	A dataframe including time as timestamp and searches for your given geography in one column.
interrupt	The date where things change. ARIMA will be predicted on all days before the interrupt.
beginperiod	How far back you want the "pre" period to go
preperiod	This creates a beginperiod but with a number of days instead of a date
endperiod	How far after the interruption you want to go
scaletitle	Title of the scale
scalelimits	vector of two values for min and max for the scale
linecol	Line color
lowcol	Color for low values
midcol	Color for mid values
highcol	Color for high values
save	Default is True, If False, don't save
width	Width of file in inches
height	Height of file in inches
outfn	Output filename

Examples

pct_change_state(
  df = read.csv("./temp/data.csv", header = T, stringsAsFactor = F),
  interrupt = "2020-03-01",
  beginperiod = NA,
  preperiod = 90,
  endperiod = "2020-03-23",
  scaletitle = "Pct. Increase in Searches",
  linecol = "gray",
  lowcol = "red",
  midcol = "white",
  highcol = "dodgerblue4"
)

tlcaputi/gtrendR documentation built on Nov. 3, 2022, 10:46 p.m.