根据第三个变量改变散点图中的标记样式 [英] Changing marker style in scatter plot according to third variable
问题描述
我在pylab散点图中更改标记样式, 。我的方法,适用于颜色,不幸的是不适用于标记样式。
x = [1,2,3,4 ,5,6]
y = [1,3,4,5,6,7]
m = ['k','l','l','k','j'
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()
问题是标记
只能是一个值,而不是标记列表,因为 / code> parmeter。
您可以按标记值进行分组,以便您的x和y列表具有相同的标记并绘制它们: / p>
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()
或者你可以绘制每一个点(我不推荐):
x = [1,2,3,4, 5,6]
y = [1,3,4,5,6,7]
m = ['k','l','l','k','j',' ']
mapping = {'j':'o','k':'x','l':'+'}
len(x)):
plt.scatter(x [i],y [i],marker = mapping [m [i]])
plt.show()
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.
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()
The problem is that marker
can only be a single value and not a list of markers, as the color
parmeter.
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()
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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