Python MatPlotLib：同一散点图上的多个数据集
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MatPlotLib: Multiple datasets on the same scatter plot
提问by Austin Richardson
I want to plot multiple data sets on the same scatter plot:
我想在同一个散点图上绘制多个数据集：
cases = scatter(x[:4], y[:4], s=10, c='b', marker="s")
controls = scatter(x[4:], y[4:], s=10, c='r', marker="o")
show()
The above only shows the most recent scatter()
以上只显示最近的 scatter()
I've also tried:
我也试过：
plt = subplot(111)
plt.scatter(x[:4], y[:4], s=10, c='b', marker="s")
plt.scatter(x[4:], y[4:], s=10, c='r', marker="o")
show()
采纳答案by nate c
You need a reference to an Axesobject to keep drawing on the same subplot.
您需要对Axes对象的引用才能继续在同一个子图上绘图。
import matplotlib.pyplot as plt
x = range(100)
y = range(100,200)
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax1.scatter(x[:4], y[:4], s=10, c='b', marker="s", label='first')
ax1.scatter(x[40:],y[40:], s=10, c='r', marker="o", label='second')
plt.legend(loc='upper left');
plt.show()
回答by Steve Tjoa
I don't know, it works fine for me. Exact commands:
我不知道，它对我来说很好用。确切的命令：
import scipy, pylab
ax = pylab.subplot(111)
ax.scatter(scipy.randn(100), scipy.randn(100), c='b')
ax.scatter(scipy.randn(100), scipy.randn(100), c='r')
ax.figure.show()
回答by MaVe
You can also do this easily in Pandas, if your data is represented in a Dataframe, as described here:
如果您的数据在 Dataframe 中表示，您也可以在 Pandas 中轻松完成此操作，如下所述：
http://pandas.pydata.org/pandas-docs/version/0.15.0/visualization.html#scatter-plot
http://pandas.pydata.org/pandas-docs/version/0.15.0/visualization.html#scatter-plot
回答by Sohaib Farooqi
I came across this question as I had exact same problem. Although accepted answer works good but with matplotlib version 2.1.0, it is pretty straight forward to have two scatter plots in one plot without using a reference to Axes
我遇到了这个问题，因为我遇到了完全相同的问题。虽然接受的答案效果很好，但使用 matplotlib 版本2.1.0，在一个图中有两个散点图而不使用对Axes
import matplotlib.pyplot as plt
plt.scatter(x,y, c='b', marker='x', label='1')
plt.scatter(x, y, c='r', marker='s', label='-1')
plt.legend(loc='upper left')
plt.show()
