I've been messing around with the 'gtrendsR' package to see how the big two 'GIS' packages are squaring up on google searches. It shows a slow but steady improvement for 'QGIS' but a 'spike' in 'ArcGIS' too in early 2020. Will try to get some more detailed 'monthly' analysis asap.
Updated: 14:56 pm Tue 9th June 2020
RStudio code:-
library(gtrendsR)
library(tidyverse)
library(ggplot2)
# You only need to change "QGIS" and "ARCGIS" to alternative google 'keywords'
# Assign 'QGIS' and 'ARCGIS' to 'res'
res <- gtrends(c("QGIS", "ARCGIS"))
# Assign 'res$interest_over_time' to 'iot'
iot <- res$interest_over_time
# Assign 'iot (and then) filter date' to 'iot2020'
iot2020 <- iot %>%
filter(date > as.Date("2015-01-01"))
# Assign 'iot2020' to 'ggplot'
iot2020 %>%
ggplot() + geom_line(aes(x = date,
y = hits,
color = keyword)) +
theme_minimal() +
labs(title = "QGIS vs ARGIS 2015-2020",
subtitle = "Google Trends Report",
caption = "Courtesy: gtrendsR package")
Updated: 14:56 pm Tue 9th June 2020
RStudio code:-
library(gtrendsR)
library(tidyverse)
library(ggplot2)
# You only need to change "QGIS" and "ARCGIS" to alternative google 'keywords'
# Assign 'QGIS' and 'ARCGIS' to 'res'
res <- gtrends(c("QGIS", "ARCGIS"))
# Assign 'res$interest_over_time' to 'iot'
iot <- res$interest_over_time
# Assign 'iot (and then) filter date' to 'iot2020'
iot2020 <- iot %>%
filter(date > as.Date("2015-01-01"))
# Assign 'iot2020' to 'ggplot'
iot2020 %>%
ggplot() + geom_line(aes(x = date,
y = hits,
color = keyword)) +
theme_minimal() +
labs(title = "QGIS vs ARGIS 2015-2020",
subtitle = "Google Trends Report",
caption = "Courtesy: gtrendsR package")
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