pandas 熊猫 - 每个点具有不同颜色图例的散点图
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pandas - scatter plot with different color legend for each point
提问by Fabio Lamanna
Starting from the following example:
从以下示例开始：
fig, ax = plt.subplots()
df = pd.DataFrame({'n1':[1,2,1,3], 'n2':[1,3,2,1], 'l':['a','b','c','d']})
for label in df['l']:
df.plot('n1','n2', kind='scatter', ax=ax, s=50, linewidth=0.1, label=label)
what I obtained is the following scatterplot:
我得到的是以下散点图：
I'm now trying to set a different color for each of the four points. I know that I can loop over a set of, for instance, 4 colors in a list like:
我现在试图为四个点中的每一个设置不同的颜色。我知道我可以循环遍历列表中的一组，例如 4 种颜色，例如：
colorlist = ['b','r','c','y']
but since my real dataset comprise at least 20 different points, I was looking for a sort of "color generator" to loop within it.
但由于我的真实数据集至少包含 20 个不同的点，我一直在寻找一种“颜色生成器”来在其中循环。
回答by tmdavison
The following method will create a list of colors as long as your dataframe, and then plot a point with a label with each color:
以下方法将创建一个与数据框一样长的颜色列表，然后用每种颜色的标签绘制一个点：
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
import numpy as np
import pandas as pd
fig, ax = plt.subplots()
df = pd.DataFrame({'n1':[1,2,1,3], 'n2':[1,3,2,1], 'l':['a','b','c','d']})
colormap = cm.viridis
colorlist = [colors.rgb2hex(colormap(i)) for i in np.linspace(0, 0.9, len(df['l']))]
for i,c in enumerate(colorlist):
x = df['n1'][i]
y = df['n2'][i]
l = df['l'][i]
ax.scatter(x, y, label=l, s=50, linewidth=0.1, c=c)
ax.legend()
plt.show()
回答by SparkAndShine
How about this,
这个怎么样，
Here is the source code,
这是源代码，
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from matplotlib import cm
fig, ax = plt.subplots()
df = pd.DataFrame({'n1':[1,2,1,3], 'n2':[1,3,2,1], 'l':['a','b','c','d']})
#colors = ['b','r','c','y']
nrof_labels = len(df['l'])
colors = cm.rainbow(np.linspace(0, 1, nrof_labels)) # create a bunch of colors
for i, r in df.iterrows():
ax.plot(r['n1'], r['n2'], 'o', markersize=10, color=colors[i], linewidth=0.1, label=r['l'])
ax.set_xlim(0.5, 3.5)
ax.set_ylim(0.5, 3.5)
plt.legend(loc='best')
plt.show()
回答by MaxU
IIUC you can do it this way:
IIUC 你可以这样做：
import matplotlib.pyplot as plt
from matplotlib import colors
import pandas as pd
colorlist = list(colors.ColorConverter.colors.keys())
fig, ax = plt.subplots()
[df.iloc[[i]].plot.scatter('n1', 'n2', ax=ax, s=50, label=l,
color=colorlist[i % len(colorlist)])
for i,l in enumerate(df.l)]
colorlist:
颜色列表：
In [223]: colorlist
Out[223]: ['m', 'b', 'g', 'r', 'k', 'y', 'c', 'w']
PS colorlist[i % len(colorlist)]- should always remain in the list bounds
PS colorlist[i % len(colorlist)]- 应始终保持在列表范围内
