Zoom all facets at the same time

[todd-davidson-beis]

There seems to be a discrepancy between plotly for R and for python in how it handles zooming across facets.

To take my examples directly from the documentation: https://plotly.com/ggplot2/facet-plots/ vs https://plotly.com/python/facet-plots/

In the python version, if I select a region to zoom in on, the same zoom is applied to all facets, regardless of position.

In the r version, if I zoom on one facet, the 'x' zoom is applied to facets in the same column, and the 'y' zoom is applied to facets in the same row - but other facets are unaffected.

I would like to replicate the python behaviour in r. Any clues for how to do this?

Reprex: Compare zoom behaviour between R and python

library(reshape2)
library(plotly)

p <- ggplot(tips, aes(x=total_bill)) + geom_histogram(binwidth=2,colour="white")

# Histogram of total_bill, divided by sex and smoker
p <- p + facet_grid(sex ~ smoker)

ggplotly(p)

import plotly.express as px
df = px.data.gapminder()
fig = px.scatter(df, x='gdpPercap', y='lifeExp', color='continent', size='pop',
                facet_col='year', facet_col_wrap=4)
fig.show()

[jmuhlenkamp]

For anyone who comes across this in the future, I was able to manually achieve this via the Layout Axis Matches setting. Here is the updated R Reprex that I believe achieves the original ask.

library(reshape2)
library(plotly)

p <- ggplot(tips, aes(x=total_bill)) + geom_histogram(binwidth=2,colour="white")

# Histogram of total_bill, divided by sex and smoker
p <- p + facet_grid(sex ~ smoker)

ggplotly(p) %>%
  layout(
    xaxis = list(matches = 'x2'),
    yaxis = list(matches = 'y2')
  )

Note that if you have more than 2X2, then you will need to set additional match settings as shown in this 3X3 example.

library(dplyr)
tips2 <- tips %>%
  mutate(sex = ifelse(sample(0:1, n(), replace = TRUE) == 1, '3', sex),
         smoker = ifelse(sample(0:1, n(), replace = TRUE) == 1, '3', smoker))

p2 <- ggplot(tips2, aes(x=total_bill)) + geom_histogram(binwidth=2,colour="white")

# Histogram of total_bill, divided by sex and smoker
p2 <- p2 + facet_grid(sex ~ smoker)

ggplotly(p2) %>%
  layout(
    xaxis = list(matches = 'x2'),
    yaxis = list(matches = 'y2'),
    xaxis2 = list(matches = 'x3'),
    yaxis2 = list(matches = 'y3')
  )