使用 matplotlib 在图例上添加标签不起作用 [英] Adding labels on legend does not work, using matplotlib
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问题描述
我有以下数据框
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame({'var': ['bid', 'on', 'off', 'bid', 'on', 'off'],
'aud': ['H', 'H', 'H', 'L', 'L', 'L'],
'eff': [0.1, 0.2, 0.3, 0.01, 0.02, 0.03],
'spend': [10, 20, 30, 1, 2, 3],
'marg': [0.001, 0.002, 0.003, 0.0001, 0.0002, 0.0003]})
我的最终目标是创建一个气泡图,为每个 var
、marg
和 specific color
s> 在 y_axis
上,图的 x_axis
上的 eff
和气泡的 size
相等使用 color
和 size
My end goal is to create a bubble plot, with specific color
s for every var
, the marg
on the y_axis
, the eff
on the x_axis
of the plot and the size
of the bubbles to be equal to spend
with respective legends for the color
and the size
我正在使用以下代码
x = df.loc[df.aud == 'H']['eff']
y = df.loc[df.aud == 'H']['marg']
z = df.loc[df.aud == 'H']['spend']
colours_dict = dict(zip(['bid', 'on', 'off'], ['#185177', '#FAA22C', '#8FC5E8']))
g, ax = plt.subplots()
scatter = ax.scatter(x, y, c=[ colours_dict[i] for i in df.loc[df.aud == 'H']['var'] ], s=z*10)
# produce a legend with the unique colors from the scatter
legend1 = ax.legend(*scatter.legend_elements(),
loc="center", title="var")
ax.add_artist(legend1)
# produce a legend with a cross section of sizes from the scatter
handles, labels = scatter.legend_elements(prop="sizes", alpha=0.6)
legend2 = ax.legend(handles, labels, loc="upper right", title="Spend")
plt.savefig('bubbles.png')
问题在于带有颜色的图例没有显示标签.
The problem is that the legend with the colors does not show the labels.
有帮助吗?
推荐答案
您有两个选择:
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame({'var': ['bid', 'on', 'off', 'bid', 'on', 'off'],
'aud': ['H', 'H', 'H', 'L', 'L', 'L'],
'eff': [0.1, 0.2, 0.3, 0.01, 0.02, 0.03],
'spend': [10, 20, 30, 1, 2, 3],
'marg': [0.001, 0.002, 0.003, 0.0001, 0.0002, 0.0003]})
x = df.loc[df.aud == 'H']['eff']
y = df.loc[df.aud == 'H']['marg']
z = df.loc[df.aud == 'H']['spend']
labels = ['bid', 'on', 'off']
colors = ['#185177', '#FAA22C', '#8FC5E8']
colours_dict = dict(zip(labels, colors))
fig, ax = plt.subplots()
c = [colours_dict[i] for i in df.loc[df.aud == 'H']['var']]
scatter = ax.scatter(x, y, c=c, s=z*10)
# produce a legend with the unique colors from the scatter
handles = [plt.Line2D([],[], ls="", marker="o", color=c) for c in colors]
legend1 = ax.legend(handles, labels, loc="lower right", title="var")
plt.show()
使用颜色映射
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap, BoundaryNorm
df = pd.DataFrame({'var': ['bid', 'on', 'off', 'bid', 'on', 'off'],
'aud': ['H', 'H', 'H', 'L', 'L', 'L'],
'eff': [0.1, 0.2, 0.3, 0.01, 0.02, 0.03],
'spend': [10, 20, 30, 1, 2, 3],
'marg': [0.001, 0.002, 0.003, 0.0001, 0.0002, 0.0003]})
x = df.loc[df.aud == 'H']['eff']
y = df.loc[df.aud == 'H']['marg']
z = df.loc[df.aud == 'H']['spend']
labels = ['bid', 'on', 'off',]
colors = ['#185177', '#FAA22C', '#8FC5E8']
inv = [labels.index(i) for i in df.loc[df.aud == 'H']['var']]
cmap = ListedColormap(colors)
norm = BoundaryNorm(np.arange(len(colors)+1)-0.5, len(colors))
fig, ax = plt.subplots()
scatter = ax.scatter(x, y, c=inv, s=z*10, cmap=cmap, norm=norm)
legend1 = ax.legend(scatter.legend_elements(num=len(labels))[0], labels,
loc="lower right", title="var")
plt.show()
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