根据第三个变量更改散点图中的标记样式 [英] Changing marker style in scatter plot according to third variable

问题描述

我正在处理多列字典.我想绘制两列，然后根据第三列和第四列更改标记的颜色和样式.

I am dealing with a multi-column dictionary. I want to plot two columns and subsequently change color and style of the markers according to a third and fourth column.

我很难改变 pylab 散点图中的标记样式.不幸的是，我的方法适用于颜色，但不适用于标记样式.

I struggle with changing the marker style in the pylab scatter plot. My approach, which works for color, unfortunately does not work for marker style.

x=[1,2,3,4,5,6]
y=[1,3,4,5,6,7]
m=['k','l','l','k','j','l']

for i in xrange(len(m)):
    m[i]=m[i].replace('j','o')
    m[i]=m[i].replace('k','x')
    m[i]=m[i].replace('l','+')

plt.scatter(x,y,marker=m)
plt.show()

推荐答案

问题在于 marker 只能是单个值而不是标记列表，如 color参数.

The problem is that marker can only be a single value and not a list of markers, as the color parmeter.

您可以按标记值进行分组，以便您拥有具有相同标记的 x 和 y 列表并绘制它们:

You can either do a grouping by marker value so you have the x and y lists that have the same marker and plot them:

xs = [[1, 2, 3], [4, 5, 6]]
ys = [[1, 2, 3], [4, 5, 6]]
m = ['o', 'x']
for i in range(len(xs)):
    plt.scatter(xs[i], ys[i], marker=m[i])
plt.show()

或者你可以绘制每个点(我不推荐):

Or you can plot every single dot (which I would not recommend):

x=[1,2,3,4,5,6]
y=[1,3,4,5,6,7]
m=['k','l','l','k','j','l']

mapping = {'j' : 'o', 'k': 'x', 'l': '+'}

for i in range(len(x)):
    plt.scatter(x[i], y[i], marker=mapping[m[i]])
plt.show()

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