具有Seaborn的PairGrid中的Hexbin图 [英] Hexbin plot in PairGrid with Seaborn

问题描述

我正在尝试在 Seaborn Grid 中获取 hexbin 图.我有以下代码，

# 使用 Python 2 内核在 Jupyter 中工作.%matplotlib 内联将 seaborn 作为 sns 导入将Matplotlib导入为mpl导入matplotlib.pyplot作为plt提示= sns.load_dataset(提示")# 借鉴自 http://stackoverflow.com/a/31385996/4099925def hexbin(x，y，color，** kwargs):cmap = sns.light_palette(颜色，as_cmap=True)plt.hexbin(x, y, gridsize=15, cmap=cmap, extent=[min(x), max(x), min(y), max(y)], **kwargs)g = sns.PairGrid(提示，hue='sex')g.map_diag(plt.hist)g.map_lower(sns.stripplot, jitter=True, alpha=0.5)g.map_upper(hexbin)

但是，这给了我以下图像，

如何固定六边形图，使其覆盖图形的整个表面，而不仅仅是显示的图谱区域的一部分?

解决方案

您在此处尝试执行的操作存在(至少)三个问题.

1. stripplot 用于至少有一个轴是分类的数据.在这种情况下，这是不正确的.Seaborn猜想x轴是分类轴，它弄乱了子图的x轴.来自

   I am trying to get a hexbin plot in a Seaborn Grid. I have the following code,

   # Works in Jupyter with Python 2 Kernel.
   %matplotlib inline
   
   import seaborn as sns
   import matplotlib as mpl
   import matplotlib.pyplot as plt
   
   tips = sns.load_dataset("tips")
   
   # Borrowed from http://stackoverflow.com/a/31385996/4099925
   def hexbin(x, y, color, **kwargs):
       cmap = sns.light_palette(color, as_cmap=True)
       plt.hexbin(x, y, gridsize=15, cmap=cmap, extent=[min(x), max(x), min(y), max(y)], **kwargs)
   
   g = sns.PairGrid(tips, hue='sex')
   g.map_diag(plt.hist)
   g.map_lower(sns.stripplot, jitter=True, alpha=0.5)
   g.map_upper(hexbin)
   

   However, that gives me the following image,

   How can I fix the hexbin plots in such a way that they cover the entire surface of the graph and not just a subset of the shown plot area?

   解决方案

   There are (at least) three problems with what you are trying to do here.

   1. stripplot is for data where at least one axis is categorical. This is not true in this case. Seaborn guesses that the x axis is the categorical one which messes up the x axes of your subplots. From the docs for stripplot:

      Draw a scatterplot where one variable is categorical.

      In my suggested code below I have changed it to a simple scatter plot.

   2. Drawing two hexbin-plots on top of eachother will only show the latter one. I added some alpha=0.5 to the hexbin arguments, but the result is far from pretty.

   3. The extent parameter in your code adjusted the hexbin plot to x and y of each sex one at a time. But both of the hexbin plots need to be equal in size so they should use min/max of an entire series over both sexes. To achieve this I passed in the minimum and maximum values for all series to the hexbin function which can then pick and use the relevant ones.

   Here is what I came up with:

   # Works in Jupyter with Python 2 Kernel.
   %matplotlib inline
   
   import seaborn as sns
   import matplotlib as mpl
   import matplotlib.pyplot as plt
   
   tips = sns.load_dataset("tips")
   
   # Borrowed from http://stackoverflow.com/a/31385996/4099925
   def hexbin(x, y, color, max_series=None, min_series=None, **kwargs):
       cmap = sns.light_palette(color, as_cmap=True)
       ax = plt.gca()
       xmin, xmax = min_series[x.name], max_series[x.name]
       ymin, ymax = min_series[y.name], max_series[y.name]
       plt.hexbin(x, y, gridsize=15, cmap=cmap, extent=[xmin, xmax, ymin, ymax], **kwargs)
   
   g = sns.PairGrid(tips, hue='sex')
   g.map_diag(plt.hist)
   g.map_lower(plt.scatter, alpha=0.5)
   g.map_upper(hexbin, min_series=tips.min(), max_series=tips.max(), alpha=0.5)
   

   And here is the result:

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