Mixing
merging plotly graphs r
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I am trying to merge different plotly plots in one view. The issue I am encountering is that the standard subplot() function merges the plots together. Is there a way to keep them separate as, for example, the par(mfrow) or the grid.arrange() function for ggplot?
r plotly subplot
edited Jan 3 at 10:30
Christian
11k3094159
asked Jan 3 at 10:27
Marco De VirgilisMarco De Virgilis
501217
add a comment |
0
I am trying to merge different plotly plots in one view. The issue I am encountering is that the standard subplot() function merges the plots together. Is there a way to keep them separate as, for example, the par(mfrow) or the grid.arrange() function for ggplot?
r plotly subplot
edited Jan 3 at 10:30
Christian
11k3094159
asked Jan 3 at 10:27
Marco De VirgilisMarco De Virgilis
501217
add a comment |
0
0
0
I am trying to merge different plotly plots in one view. The issue I am encountering is that the standard subplot() function merges the plots together. Is there a way to keep them separate as, for example, the par(mfrow) or the grid.arrange() function for ggplot?
r plotly subplot
edited Jan 3 at 10:30
Christian
11k3094159
asked Jan 3 at 10:27
Marco De VirgilisMarco De Virgilis
501217
I am trying to merge different plotly plots in one view. The issue I am encountering is that the standard subplot() function merges the plots together. Is there a way to keep them separate as, for example, the par(mfrow) or the grid.arrange() function for ggplot?
r plotly subplot
r plotly subplot
edited Jan 3 at 10:30
Christian
11k3094159
asked Jan 3 at 10:27
Marco De VirgilisMarco De Virgilis
501217
edited Jan 3 at 10:30
Christian
11k3094159
asked Jan 3 at 10:27
Marco De VirgilisMarco De Virgilis
501217
edited Jan 3 at 10:30
Christian
11k3094159
edited Jan 3 at 10:30
Christian
11k3094159
edited Jan 3 at 10:30
Christian
11k3094159
11k3094159
asked Jan 3 at 10:27
Marco De VirgilisMarco De Virgilis
501217
asked Jan 3 at 10:27
Marco De VirgilisMarco De Virgilis
501217
asked Jan 3 at 10:27
Marco De VirgilisMarco De Virgilis
501217
501217
add a comment |
add a comment |
1 Answer
1
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oldest
votes
1
Try ggarrange().
# Box plot (bp)
bxp <- ggboxplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco")
bxp
# Dot plot (dp)
dp <- ggdotplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco", binwidth = 1)
# Bar plot (bp)
bp <- ggbarplot(mtcars, x = "name", y = "mpg",
fill = "cyl", # change fill color by cyl
color = "white", # Set bar border colors to white
palette = "jco", # jco journal color palett. see ?ggpar
sort.val = "asc", # Sort the value in ascending order
sort.by.groups = TRUE, # Sort inside each group
x.text.angle = 90 # Rotate vertically x axis texts
)
bp + font("x.text", size = 8)
# Scatter plots (sp)
sp <- ggscatter(mtcars, x = "wt", y = "mpg",
add = "reg.line", # Add regression line
conf.int = TRUE, # Add confidence interval
color = "cyl", palette = "jco", # Color by groups "cyl"
shape = "cyl" # Change point shape by groups "cyl"
)+
stat_cor(aes(color = cyl), label.x = 3) # Add correlation coefficient
sp
ggarrange(bxp, dp, bp + rremove("x.text"),
labels = c("A", "B", "C"),
ncol = 2, nrow = 2)
Examples adopted from here
answered Jan 3 at 10:33
Vivek KalyanaranganVivek Kalyanarangan
5,1141830
Thank you for this, the problem in doing this is that i lose the interactivity that plotly offers.
– Marco De Virgilis
Jan 3 at 10:37
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
Try ggarrange().
# Box plot (bp)
bxp <- ggboxplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco")
bxp
# Dot plot (dp)
dp <- ggdotplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco", binwidth = 1)
# Bar plot (bp)
bp <- ggbarplot(mtcars, x = "name", y = "mpg",
fill = "cyl", # change fill color by cyl
color = "white", # Set bar border colors to white
palette = "jco", # jco journal color palett. see ?ggpar
sort.val = "asc", # Sort the value in ascending order
sort.by.groups = TRUE, # Sort inside each group
x.text.angle = 90 # Rotate vertically x axis texts
)
bp + font("x.text", size = 8)
# Scatter plots (sp)
sp <- ggscatter(mtcars, x = "wt", y = "mpg",
add = "reg.line", # Add regression line
conf.int = TRUE, # Add confidence interval
color = "cyl", palette = "jco", # Color by groups "cyl"
shape = "cyl" # Change point shape by groups "cyl"
)+
stat_cor(aes(color = cyl), label.x = 3) # Add correlation coefficient
sp
ggarrange(bxp, dp, bp + rremove("x.text"),
labels = c("A", "B", "C"),
ncol = 2, nrow = 2)
Examples adopted from here
answered Jan 3 at 10:33
Vivek KalyanaranganVivek Kalyanarangan
5,1141830
Thank you for this, the problem in doing this is that i lose the interactivity that plotly offers.
– Marco De Virgilis
Jan 3 at 10:37
add a comment |
1
Try ggarrange().
# Box plot (bp)
bxp <- ggboxplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco")
bxp
# Dot plot (dp)
dp <- ggdotplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco", binwidth = 1)
# Bar plot (bp)
bp <- ggbarplot(mtcars, x = "name", y = "mpg",
fill = "cyl", # change fill color by cyl
color = "white", # Set bar border colors to white
palette = "jco", # jco journal color palett. see ?ggpar
sort.val = "asc", # Sort the value in ascending order
sort.by.groups = TRUE, # Sort inside each group
x.text.angle = 90 # Rotate vertically x axis texts
)
bp + font("x.text", size = 8)
# Scatter plots (sp)
sp <- ggscatter(mtcars, x = "wt", y = "mpg",
add = "reg.line", # Add regression line
conf.int = TRUE, # Add confidence interval
color = "cyl", palette = "jco", # Color by groups "cyl"
shape = "cyl" # Change point shape by groups "cyl"
)+
stat_cor(aes(color = cyl), label.x = 3) # Add correlation coefficient
sp
ggarrange(bxp, dp, bp + rremove("x.text"),
labels = c("A", "B", "C"),
ncol = 2, nrow = 2)
Examples adopted from here
answered Jan 3 at 10:33
Vivek KalyanaranganVivek Kalyanarangan
5,1141830
Thank you for this, the problem in doing this is that i lose the interactivity that plotly offers.
– Marco De Virgilis
Jan 3 at 10:37
add a comment |
1
1
1
Try ggarrange().
# Box plot (bp)
bxp <- ggboxplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco")
bxp
# Dot plot (dp)
dp <- ggdotplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco", binwidth = 1)
# Bar plot (bp)
bp <- ggbarplot(mtcars, x = "name", y = "mpg",
fill = "cyl", # change fill color by cyl
color = "white", # Set bar border colors to white
palette = "jco", # jco journal color palett. see ?ggpar
sort.val = "asc", # Sort the value in ascending order
sort.by.groups = TRUE, # Sort inside each group
x.text.angle = 90 # Rotate vertically x axis texts
)
bp + font("x.text", size = 8)
# Scatter plots (sp)
sp <- ggscatter(mtcars, x = "wt", y = "mpg",
add = "reg.line", # Add regression line
conf.int = TRUE, # Add confidence interval
color = "cyl", palette = "jco", # Color by groups "cyl"
shape = "cyl" # Change point shape by groups "cyl"
)+
stat_cor(aes(color = cyl), label.x = 3) # Add correlation coefficient
sp
ggarrange(bxp, dp, bp + rremove("x.text"),
labels = c("A", "B", "C"),
ncol = 2, nrow = 2)
Examples adopted from here
answered Jan 3 at 10:33
Vivek KalyanaranganVivek Kalyanarangan
5,1141830
Try ggarrange().
# Box plot (bp)
bxp <- ggboxplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco")
bxp
# Dot plot (dp)
dp <- ggdotplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco", binwidth = 1)
# Bar plot (bp)
bp <- ggbarplot(mtcars, x = "name", y = "mpg",
fill = "cyl", # change fill color by cyl
color = "white", # Set bar border colors to white
palette = "jco", # jco journal color palett. see ?ggpar
sort.val = "asc", # Sort the value in ascending order
sort.by.groups = TRUE, # Sort inside each group
x.text.angle = 90 # Rotate vertically x axis texts
)
bp + font("x.text", size = 8)
# Scatter plots (sp)
sp <- ggscatter(mtcars, x = "wt", y = "mpg",
add = "reg.line", # Add regression line
conf.int = TRUE, # Add confidence interval
color = "cyl", palette = "jco", # Color by groups "cyl"
shape = "cyl" # Change point shape by groups "cyl"
)+
stat_cor(aes(color = cyl), label.x = 3) # Add correlation coefficient
sp
ggarrange(bxp, dp, bp + rremove("x.text"),
labels = c("A", "B", "C"),
ncol = 2, nrow = 2)
Examples adopted from here
answered Jan 3 at 10:33
Vivek KalyanaranganVivek Kalyanarangan
5,1141830
answered Jan 3 at 10:33
Vivek KalyanaranganVivek Kalyanarangan
5,1141830
answered Jan 3 at 10:33
Vivek KalyanaranganVivek Kalyanarangan
5,1141830
answered Jan 3 at 10:33
Vivek KalyanaranganVivek Kalyanarangan
5,1141830
5,1141830
Thank you for this, the problem in doing this is that i lose the interactivity that plotly offers.
– Marco De Virgilis
Jan 3 at 10:37
add a comment |
Thank you for this, the problem in doing this is that i lose the interactivity that plotly offers.
– Marco De Virgilis
Jan 3 at 10:37
Thank you for this, the problem in doing this is that i lose the interactivity that plotly offers.
– Marco De Virgilis
Jan 3 at 10:37
Thank you for this, the problem in doing this is that i lose the interactivity that plotly offers.
– Marco De Virgilis
Jan 3 at 10:37
add a comment |
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