英文:
Display both axes in sorted order for non numerical data
问题
如何实现两个轴的正确顺序：
- 要实现 a-b-c 而不是 c-a-b
- 要实现 x-y-z 而不是 y-z-x
import matplotlib.pyplot as pltcategories_x = ["c", "a", "b", "c", "b"]categories_y = ["y", "z", "y", "x", "z"]plt.scatter(categories_x, categories_y)plt.show()
在Stack Overflow上有很多解决方案，它们依赖于以下两种属性之一：
- 数据可以转换为数字，例如（"1"，"0"，...）-> 转换为数字
- 只有一个轴的顺序不正确 -> 按此轴对两个数组进行排序（这样做的原因是轴刻度按首次出现的顺序排列）
但对于我的示例，这些解决方案都不适用。
我正在寻找一种如何在matplotlib中实现这一目标的解决方案。我知道可能有其他方法来传达相同的信息，或者可能有其他不会出现这个问题的库。
英文:
How to achieve the correct order for both axes:
- a-b-c instead of c-a-b
- x-y-z instead of y-z-x
import matplotlib.pyplot as pltcategories_x = ["c", "a", "b", "c", "b"]categories_y = ["y", "z", "y", "x", "z"]plt.scatter(categories_x, categories_y)plt.show()
There are a lot of solutions on SO, that rely on either of two properties:
- The data can be cast to numerical, e.g. ("1", "0", ...) -> cast to numerical
- Only one axis has the wrong order -> sort the two arrays by this axis (the reason why this works is, that the axis-ticks are ordered by first occurrence)
But for my example neither of these solutions work.
I'm looking for a solution, of how to get this to work in matplotlib. I am aware, that there are other probably even better ways to convey the same message, or maybe other libraries that don't have this issue.
答案1
得分: 1
关于使用[tag:pandas]和有序的分类数据，您可以尝试以下代码：
ax = plt.subplot()X = pd.Categorical(categories_x, ordered=True)Y = pd.Categorical(categories_y, ordered=True)ax.scatter(X.codes, Y.codes)ax.set_xticks(range(len(X.categories)), X.categories)ax.set_yticks(range(len(Y.categories)), Y.categories)
输出结果如下：
英文:
What about using [tag:pandas] and an ordered Categorical?
ax = plt.subplot()X = pd.Categorical(categories_x, ordered=True)Y = pd.Categorical(categories_y, ordered=True)ax.scatter(X.codes, Y.codes)ax.set_xticks(range(len(X.categories)), X.categories)ax.set_yticks(range(len(Y.categories)), Y.categories)
Output:
答案2
得分: 1
以下是您要翻译的代码部分：
import matplotlib.pyplot as pltcategories_x = ["c", "a", "b", "c", "b"]categories_y = ["y", "z", "y", "x", "z"]def axis_to_number(values):# 可以自定义的映射函数return {j:i for i, j in enumerate(sorted(set(values))}map_x = axis_to_number(categories_x)map_y = axis_to_number(categories_y)# 现在将原始数组转换为映射值以保持顺序cx = [map_x[i] for i in categories_x]cy = [map_y[i] for i in categories_y]xticks, xticklabels = [x for x in map_x.values()], [x for x in map_x.keys()]yticks, yticklabels = [y for y in map_y.values()], [y for y in map_y.keys()]# 绘图fig, ax = plt.subplots()ax.plot(cx, cy, 'o')ax.set_xticks(xticks)ax.set_xticklabels(xticklabels)ax.set_yticks(yticks)ax.set_yticklabels(yticklabels)
希望这有帮助！
英文:
How about simply converting everything to numerical values and playing with the x- and y-ticklabels
import matplotlib.pyplot as pltcategories_x = ["c", "a", "b", "c", "b"]categories_y = ["y", "z", "y", "x", "z"]def axis_to_number(values):# this mapping function can be customizedreturn {j:i for i, j in enumerate(sorted(set(values)))}map_x = axis_to_number(categories_x)map_y = axis_to_number(categories_y)# now convert the original arrays to the# mapped values to keep the ordercx = [map_x[i] for i in categories_x]cy = [map_y[i] for i in categories_y]xticks, xticklabels = [x for x in map_x.values()], [x for x in map_x.keys()]yticks, yticklabels = [y for y in map_y.values()], [y for y in map_y.keys()]# plotfig, ax = plt.subplots()ax.plot(cx, cy, 'o')ax.set_xticks(xticks)ax.set_xticklabels(xticklabels)ax.set_yticks(yticks)ax.set_yticklabels(yticklabels)
答案3
得分: 0
我们可以使用排序函数将它们按顺序排列。
import matplotlib.pyplot as pltcategories_x = ["c", "a", "b", "c", "b"]categories_y = ["y", "z", "y", "x", "z"]plt.scatter(sorted(categories_x), sorted(categories_y))plt.show()
英文:
We can use sort function to arrange them in sequence.
import matplotlib.pyplot as pltcategories_x = ["c", "a", "b", "c", "b"]categories_y = ["y", "z", "y", "x", "z"]plt.scatter(sorted(categories_x), sorted(categories_y))plt.show()
答案4
得分: 0
以下是翻译好的代码部分：
import matplotlib.pyplot as pltcategories_x = ["c", "a", "b", "c", "b"]categories_y = ["y", "z", "y", "x", "z"]p1 = plt.scatter(sorted(categories_x), sorted(categories_y), c='#00000000')# p1.set_visible(False)plt.scatter(categories_x, categories_y)plt.show()
如果你有大量的数据点并且性能成为问题，你可以考虑使用 sorted(set(categ...))。
英文:
You could draw a first scatter with the ordered strings, to get the ticks setup properly, then hide it (or use a transparent color) and draw the actual diagram:
import matplotlib.pyplot as pltcategories_x = ["c", "a", "b", "c", "b"]categories_y = ["y", "z", "y", "x", "z"]p1 = plt.scatter(sorted(categories_x),sorted(categories_y),c='#00000000')# p1.set_visible(False)plt.scatter(categories_x,categories_y)plt.show()
You may want to use sorted(set(categ...)) if you have large number of points and performance becomes a concern
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