R 使用ggplotly将ggplot geom分幅转换为plotly图表时出现问题
我尝试使用ggplotly函数将ggplot geom平铺图转换为plotly。然而,我意识到结果是不同的。请参考下面的链接查看差异。除此之外,ggplotly图表也缺少颜色条。请帮忙 图片: 这就是我提到的代码: 代码:R 使用ggplotly将ggplot geom分幅转换为plotly图表时出现问题,r,shiny,plotly,ggplotly,geom-tile,R,Shiny,Plotly,Ggplotly,Geom Tile,我尝试使用ggplotly函数将ggplot geom平铺图转换为plotly。然而,我意识到结果是不同的。请参考下面的链接查看差异。除此之外,ggplotly图表也缺少颜色条。请帮忙 图片: 这就是我提到的代码: 代码: madeUp=read.table(“https://raw.githubusercontent.com/holtzy/R-graph-gallery/master/DATA/madeUp.csv,sep=“,”,页眉=T) 图书馆(tidyverse) 数据% 分组依据(
madeUp=read.table(“https://raw.githubusercontent.com/holtzy/R-graph-gallery/master/DATA/madeUp.csv,sep=“,”,页眉=T)
图书馆(tidyverse)
数据%
分组依据(X轴、Y轴、分组)%>%
dplyr::汇总(统计=平均值(随机数,na.rm=真))
图看起来您在ggplotly
中被一个(或两个)错误绊倒了(也许您应该在上提出问题)
第一个问题是,通过ggplotly
转换ggplot时,数据集中的“间隙”丢失
第二个问题是ggplotly
无法转换guides(fill=guides\u legend(title='legend'))
添加的装箱色条
作为解决方案
第一个问题是,您可以扩展数据集以包括X.Axis
、Y.Axis
和组的所有组合
第二个问题是,您可以移除装箱的颜色条,并用连续的颜色比例替换它
虽然不完美,但通过ggplotly
的转换可以为您提供正确的绘图和图例。试试这个:
madeUp=read.table("https://raw.githubusercontent.com/holtzy/R-graph-gallery/master/DATA/madeUp.csv", sep=",", header=T)
theData <- madeUp %>%
group_by(X.Axis, Y.Axis, Group) %>%
dplyr::summarize(statistic=mean(randVals, na.rm = TRUE)) %>%
ungroup()
# Expand the Dataset to includ all Combinations of X.Axis, Y.Axis and Group
theData1 <- tidyr::expand_grid(X.Axis = 0:49, Y.Axis = 0:30, Group = LETTERS[1:6]) %>%
dplyr::left_join(theData)
fig <- ggplot(theData1, aes(X.Axis, Y.Axis)) +
coord_cartesian(xlim = c(0,20), ylim = c(0,20)) +
scale_x_continuous(breaks = seq(0,20)) +
scale_y_continuous(breaks = seq(0,20))+
geom_tile(aes(fill=statistic))+
# Remove the binned colorbar
# guides(fill=guide_legend(title='Legend'))+
labs(fill = "Legend") +
theme(
panel.background = element_rect(fill= 'white', color = 'white'),
panel.grid.major = element_line(color='#E0E0E0'),
panel.grid.minor = element_line(color='#E0E0E0')
)+
ggtitle('Wafer Map')+
facet_wrap(~Group)+
# in case of ggplot2: Set the fill color for NA to "transparent"
scale_fill_gradientn(colors = rainbow(100), na.value = "transparent")
fig
ggplotly(fig)
madeUp=read.table(“https://raw.githubusercontent.com/holtzy/R-graph-gallery/master/DATA/madeUp.csv,sep=“,”,页眉=T)
数据%
分组依据(X轴、Y轴、分组)%>%
dplyr::汇总(统计=平均值(随机数,na.rm=真))%>%
解组()
#展开数据集以包含X轴、Y轴和组的所有组合
数据1%
dplyr::左联合(数据)
fig对于任何对填补空白感兴趣的人来说,有一个。
madeUp=read.table("https://raw.githubusercontent.com/holtzy/R-graph-gallery/master/DATA/madeUp.csv", sep=",", header=T)
theData <- madeUp %>%
group_by(X.Axis, Y.Axis, Group) %>%
dplyr::summarize(statistic=mean(randVals, na.rm = TRUE)) %>%
ungroup()
# Expand the Dataset to includ all Combinations of X.Axis, Y.Axis and Group
theData1 <- tidyr::expand_grid(X.Axis = 0:49, Y.Axis = 0:30, Group = LETTERS[1:6]) %>%
dplyr::left_join(theData)
fig <- ggplot(theData1, aes(X.Axis, Y.Axis)) +
coord_cartesian(xlim = c(0,20), ylim = c(0,20)) +
scale_x_continuous(breaks = seq(0,20)) +
scale_y_continuous(breaks = seq(0,20))+
geom_tile(aes(fill=statistic))+
# Remove the binned colorbar
# guides(fill=guide_legend(title='Legend'))+
labs(fill = "Legend") +
theme(
panel.background = element_rect(fill= 'white', color = 'white'),
panel.grid.major = element_line(color='#E0E0E0'),
panel.grid.minor = element_line(color='#E0E0E0')
)+
ggtitle('Wafer Map')+
facet_wrap(~Group)+
# in case of ggplot2: Set the fill color for NA to "transparent"
scale_fill_gradientn(colors = rainbow(100), na.value = "transparent")
fig
ggplotly(fig)