The lmplot function returns a FacetGrid instance. This object has a method called set, to which you can pass key=value pairs and they will be set on each Axes object in the grid. Secondly, you can set only one side of an Axes limit in matplotlib by passing None for the value you want to … Read more
I think you want units in the call to relplot and then add a layer of lineplot using map: import seaborn as sns import pandas as pd fm = sns.load_dataset(‘fmri’).query(“event == ‘stim'”) g = sns.relplot( data=fm, kind=’line’, col=”region”, x=’timepoint’, y=’signal’, units=”subject”, estimator=None, color=”.7″ ) g.data = fm # Hack needed to work around bug on … Read more
You can access the individual axes of the FacetGrid using the axes property, and then use set_xlabel() on each of them. For example: import seaborn as sns import matplotlib.pyplot as plt sns.set(style=”ticks”, color_codes=True) tips = sns.load_dataset(“tips”) g = sns.FacetGrid(tips, col=”time”, hue=”smoker”) g = g.map(plt.scatter, “total_bill”, “tip”, edgecolor=”w”) g.axes[0,0].set_xlabel(‘axes label 1’) g.axes[0,1].set_xlabel(‘axes label 2’) plt.show() Note … Read more
Updating slightly, with seaborn 0.11.1: Seaborn’s relplot function creates a FacetGrid and gives each subplot its own explanatory title. You can add a title over the whole thing: import seaborn as sns tips = sns.load_dataset(‘tips’) rp = sns.relplot(data=tips, x=’total_bill’, y=’tip’, col=”sex”, row=’smoker’, kind=’scatter’) # rp is a FacetGrid; # relplot is a nice organized way … Read more
You can get a list of axes used in the FacetGrid using FacetGrid.axes which returns the axes used. You can then do all of the normal matplotlib operations using these axes, such as axhline for horizontal lines, or plt.text for putting text on the axes: import seaborn as sns import matplotlib.pyplot as plt tips = … Read more
The answer by Bazingaa works for matplotlib version 2.0.2. For newer versions of matplotlib, using ax.tick_params() and setting labelbottom=True seems to work: for ax in g.axes.flatten(): ax.tick_params(labelbottom=True)
We can use (1) reorder_within() function to reorder term within tissue facets. library(tidyverse) library(forcats) tdat <- tdat %>% mutate(term = factor(term), tissue = factor(tissue, levels = c(“tissue-C”, “tissue-A”, “tissue-D”, “tissue-B”), ordered = TRUE)) reorder_within <- function(x, by, within, fun = mean, sep = “___”, …) { new_x <- paste(x, within, sep = sep) stats::reorder(new_x, by, … Read more
Typically you’d do something like this: ann_text <- data.frame(mpg = 15,wt = 5,lab = “Text”, cyl = factor(8,levels = c(“4″,”6″,”8”))) p + geom_text(data = ann_text,label = “Text”) It should work without specifying the factor variable completely, but will probably throw some warnings: