legend-properties

问题 Below is a reproducible example of the issue I am trying to solve. I have created a heatmap of sorts in ggplot2 and things have been going well. Since I have put percentage signs on the data to use with geom_text I would like to make the legend of geom_tile also to display percent signs (I can only multiply the actual values by 100 right now). Ideally I would like the legend bar on the right to show 8%, 4%, 0%, -4%, -8%. #load in libraries require(plyr) require(dplyr) require(reshape2)

问题 Below is a reproducible example of the issue I am trying to solve. I have created a heatmap of sorts in ggplot2 and things have been going well. Since I have put percentage signs on the data to use with geom_text I would like to make the legend of geom_tile also to display percent signs (I can only multiply the actual values by 100 right now). Ideally I would like the legend bar on the right to show 8%, 4%, 0%, -4%, -8%. #load in libraries require(plyr) require(dplyr) require(reshape2)

问题 I am not sure whether this could be done in highcharter, however, I have a scenario where I have 7 series plotted of which by default I need to display only 3, however remaining 4 should be greyed out but be present, user can click and select if needed. So, how can we do that? All suggestions are welcome. I did some research, however i was not able to get any leads. Thanks! hc <- highchart(type = "stock") %>% hc_title(text = paste0("<span style=\"color:#000000\">", prod_line, ", ", sku , " at

来源： https://stackoverflow.com/questions/47584766/draw-a-box-around-a-legend-ggplot2

来源： https://stackoverflow.com/questions/47584766/draw-a-box-around-a-legend-ggplot2

问题 I made scatter_geo plot in Python within plotly. import plotly.express as px import pandas as pd rows=[['501-600','65','122.58333','45.36667'], ['till 500','54','12.5','27.5'], ['more 1001','51','-115.53333','38.08'], ['601-1000','54','120.54167','21.98'], ] colmns=['bins','data','longitude','latitude'] df=pd.DataFrame(data=rows, columns=colmns) fig=px.scatter_geo(df,lon='longitude', lat='latitude',color='bins', opacity=0.5, projection="natural earth") fig.show() Are there any possibility to

问题 i would like get the total value of Grades in Stacked Bar Graph Legend. picture attached how i wud like to have... for the following working snippet. and also the Column wise Total for the Table Chart... i think this can be done with following but how to get it done.. data.setFormattedValue(i, 0, key + ' (' + val + ')'); can have something like this.. when mouseover one location on Bar... need to show all the grades values in single annotation..?? is it possible to have the different values

问题 I´m trying to customize my legend I´m using the .generateLegend() to get the legend in a html way this is what the function gave me console.log(myBarChart.generateLegend()); <ul class="1-legend"><li><span style="background-color:#006666"></span>SECRETARIA MUNICIPAL DE DESENVOLVIMENTO URBANO </li> <li><span style="background-color:#339966"></span>SECRETARIA MUNICIPAL DE SAUDE</li> <li><span style="background-color:#3366ff"></span>SETOR DE RH</li> <li><span style="background-color:#66ccff"><

问题 I´m trying to customize my legend I´m using the .generateLegend() to get the legend in a html way this is what the function gave me console.log(myBarChart.generateLegend()); <ul class="1-legend"><li><span style="background-color:#006666"></span>SECRETARIA MUNICIPAL DE DESENVOLVIMENTO URBANO </li> <li><span style="background-color:#339966"></span>SECRETARIA MUNICIPAL DE SAUDE</li> <li><span style="background-color:#3366ff"></span>SETOR DE RH</li> <li><span style="background-color:#66ccff"><

问题 I have a scatter plot of multiple y-values for the same x-value, in matplotlib (python 2.7). There are different colors for all the plotted y-values. See the plot below. Now, here is the code: import numpy as np import pandas as pd import matplotlib.pyplot as plt import pylab as pl import matplotlib.cm as cm # Generate test x, y and y_error values: df2a = pd.DataFrame(np.random.rand(10,5), columns = list('ABCDE')) df2a.insert(0,'x_var_plot',range(1,df2a.shape[0]+1)) df2a_err = pd.DataFrame(np