Is there any way to customize the outlier points in an Altair boxplot? Suppose I had the following plot: penguins_data="https://raw.githubusercontent.com/datavi
I am using matplotlib to plot a box figure but there are some missing values (NaN). Then I found it doesn't display the box figure within the columns having NaN
I have used boxplot.stats$out to get outliers of a list in R. However I noticed that many times it fails to identify outliers. For example: list = c(3,4,7,500)
I need to change the colors of the boxplot drawn using pandas utility function. I can change most properties using the color argument but can't figure out how t
I am making a boxplot conditioned by a factor similar to this example: p <- ggplot(mtcars, aes(factor(cyl), mpg)) p + geom_boxplot(aes(fill = factor(am)))
I have a dataframe like this import seaborn as sns import pandas as pd %pylab inline df = pd.DataFrame({'a' :['one','one','two','two','one','two','one','one','
Is there a way to group boxplots in matplotlib? Assume we have three groups "A", "B", and "C" and for each we want to create a boxplot for both "apples" and "o