多个熊猫数据框列的重叠密度图

Question

import numpy as np
import pandas as pd

col1 = np.random.normal(0, 1, (1000, ))
col2 = np.random.normal(0, 1, (1000, ))
col3 = np.random.normal(0, 1, (1000, ))
df = pd.DataFrame({'col1':col1, 'col2':col2, 'col3':col3})

• 将每一列绘制为连续线
• 在同一轴上绘制所有 3 列
• 使用不同颜色的线条（无填充）

提前致谢！

Answer 1

我明白你的问题！下面是我在 matplotlib 中的做法。

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

col1 = np.random.normal(0, 1, (1000, ))
col2 = np.random.normal(1, 1, (1000, ))
col3 = np.random.normal(-1, 1, (1000, ))
df = pd.DataFrame({'col1':col1, 'col2':col2, 'col3':col3})

df['col1_bins'] = pd.cut(df['col1'], bins=np.arange(-10, 11, 0.5))
df['col2_bins'] = pd.cut(df['col2'], bins=np.arange(-10, 11, 0.5))
df['col3_bins'] = pd.cut(df['col3'], bins=np.arange(-10, 11, 0.5))

col1_counts = df[['col1_bins', 'col1']].groupby(['col1_bins']).count().reset_index()
col2_counts = df[['col2_bins', 'col1']].groupby(['col2_bins']).count().reset_index()
col3_counts = df[['col3_bins', 'col1']].groupby(['col3_bins']).count().reset_index()

plt.plot(col1_counts['col1_bins'].astype(str), col1_counts['col1'], 'r')
plt.plot(col2_counts['col2_bins'].astype(str), col2_counts['col1'], 'b')
plt.plot(col3_counts['col3_bins'].astype(str), col3_counts['col1'], 'g')

基本上，您必须先对数据点进行分类，然后才能绘制它们。