Pandas/Pyplot 中的散点图:如何按类别绘制 [英] Scatter plots in Pandas/Pyplot: How to plot by category

问题描述

我正在尝试使用 Pandas DataFrame 对象在 pyplot 中制作一个简单的散点图，但想要一种绘制两个变量的有效方法，但让符号由第三列(键)指示.我尝试了各种使用 df.groupby 的方法，但都没有成功.下面是一个示例 df 脚本.这会根据key1"为标记着色，但我希望看到带有key1"类别的图例.我很亲近吗?谢谢.

I am trying to make a simple scatter plot in pyplot using a Pandas DataFrame object, but want an efficient way of plotting two variables but have the symbols dictated by a third column (key). I have tried various ways using df.groupby, but not successfully. A sample df script is below. This colours the markers according to 'key1', but Id like to see a legend with 'key1' categories. Am I close? Thanks.

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame(np.random.normal(10,1,30).reshape(10,3), index = pd.date_range('2010-01-01', freq = 'M', periods = 10), columns = ('one', 'two', 'three'))
df['key1'] = (4,4,4,6,6,6,8,8,8,8)
fig1 = plt.figure(1)
ax1 = fig1.add_subplot(111)
ax1.scatter(df['one'], df['two'], marker = 'o', c = df['key1'], alpha = 0.8)
plt.show()

推荐答案

您可以为此使用 scatter，但这需要您的 key1 具有数值，并且您正如你所注意到的，不会有传说.

You can use scatter for this, but that requires having numerical values for your key1, and you won't have a legend, as you noticed.

对于像这样的离散类别，最好只使用 plot.例如:

It's better to just use plot for discrete categories like this. For example:

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
np.random.seed(1974)

# Generate Data
num = 20
x, y = np.random.random((2, num))
labels = np.random.choice(['a', 'b', 'c'], num)
df = pd.DataFrame(dict(x=x, y=y, label=labels))

groups = df.groupby('label')

# Plot
fig, ax = plt.subplots()
ax.margins(0.05) # Optional, just adds 5% padding to the autoscaling
for name, group in groups:
    ax.plot(group.x, group.y, marker='o', linestyle='', ms=12, label=name)
ax.legend()

plt.show()

如果您希望事情看起来像默认的 pandas 样式，那么只需使用 pandas 样式表更新 rcParams 并使用其颜色生成器.(我也在稍微调整图例):

If you'd like things to look like the default pandas style, then just update the rcParams with the pandas stylesheet and use its color generator. (I'm also tweaking the legend slightly):

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
np.random.seed(1974)

# Generate Data
num = 20
x, y = np.random.random((2, num))
labels = np.random.choice(['a', 'b', 'c'], num)
df = pd.DataFrame(dict(x=x, y=y, label=labels))

groups = df.groupby('label')

# Plot
plt.rcParams.update(pd.tools.plotting.mpl_stylesheet)
colors = pd.tools.plotting._get_standard_colors(len(groups), color_type='random')

fig, ax = plt.subplots()
ax.set_color_cycle(colors)
ax.margins(0.05)
for name, group in groups:
    ax.plot(group.x, group.y, marker='o', linestyle='', ms=12, label=name)
ax.legend(numpoints=1, loc='upper left')

plt.show()

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