Python: 在 matplotlib 和 seaborn 之间共享比例
Python: Sharing scale between matplotlib and seaborn
我想创建一个 seaborn 热图,它也有散点图色点。我希望最终结果使用散点图的网格,热图的正方形在散点上 "centered"。
遗憾的是,我没有找到如何在两层之间共享比例,如下例所示。
我能做什么?
非常感谢您的帮助。
%matplotlib inline
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
npoints = 3
x = np.tile(np.arange(npoints), npoints)
df = pd.DataFrame({'x': np.tile(np.arange(npoints), npoints), 'y': np.repeat(np.arange(npoints), npoints)})
df['z'] = 0
df.loc[df['x'] == df['y'], 'z'] = df.loc[df['x'] == df['y'], 'x']
df['c'] = np.random.choice(np.arange(3) + 1, df.shape[0])
df.loc[df['x'] != df['y'], 'c'] = 0
sns.heatmap(df[['x', 'y', 'z']].set_index(['x', 'y'])['z'].unstack())
plt.gca().set_title('Heatmap only')
df.plot(x='x', y='y', color=df['c'], kind='scatter')
plt.gca().set_title('Scatter points only')
fig, ax = plt.subplots()
sns.heatmap(df[['x', 'y', 'z']].set_index(['x', 'y'])['z'].unstack(), ax=ax)
df.plot(x='x', y='y', ax=ax, color=df['c'], kind='scatter')
ax.set_title('Heatmap and scatter points - scales problem')
解决方法是将您的散点数据移动 0.5
:
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
npoints = 3
x = np.tile(np.arange(npoints), npoints)
df = pd.DataFrame({'x': np.tile(np.arange(npoints), npoints), 'y': np.repeat(np.arange(npoints), npoints)})
df['z'] = 0
df.loc[df['x'] == df['y'], 'z'] = df.loc[df['x'] == df['y'], 'x']
df['c'] = np.random.choice(np.arange(3) + 1, df.shape[0])
df.loc[df['x'] != df['y'], 'c'] = 0
fig, ax = plt.subplots()
qp = sns.heatmap(df[['x', 'y', 'z']].set_index(['x', 'y'])['z'].unstack(), ax=ax)
# df.plot(x='x', y='y', ax=ax, color=df['c'], kind='scatter')
ax.scatter(df['x']+0.5,df['y']+0.5,c=df['c'])
ax.set_title('Heatmap and scatter points - scales problem')
plt.show()
结果:
我想创建一个 seaborn 热图,它也有散点图色点。我希望最终结果使用散点图的网格,热图的正方形在散点上 "centered"。
遗憾的是,我没有找到如何在两层之间共享比例,如下例所示。
我能做什么?
非常感谢您的帮助。
%matplotlib inline
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
npoints = 3
x = np.tile(np.arange(npoints), npoints)
df = pd.DataFrame({'x': np.tile(np.arange(npoints), npoints), 'y': np.repeat(np.arange(npoints), npoints)})
df['z'] = 0
df.loc[df['x'] == df['y'], 'z'] = df.loc[df['x'] == df['y'], 'x']
df['c'] = np.random.choice(np.arange(3) + 1, df.shape[0])
df.loc[df['x'] != df['y'], 'c'] = 0
sns.heatmap(df[['x', 'y', 'z']].set_index(['x', 'y'])['z'].unstack())
plt.gca().set_title('Heatmap only')
df.plot(x='x', y='y', color=df['c'], kind='scatter')
plt.gca().set_title('Scatter points only')
fig, ax = plt.subplots()
sns.heatmap(df[['x', 'y', 'z']].set_index(['x', 'y'])['z'].unstack(), ax=ax)
df.plot(x='x', y='y', ax=ax, color=df['c'], kind='scatter')
ax.set_title('Heatmap and scatter points - scales problem')
解决方法是将您的散点数据移动 0.5
:
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
npoints = 3
x = np.tile(np.arange(npoints), npoints)
df = pd.DataFrame({'x': np.tile(np.arange(npoints), npoints), 'y': np.repeat(np.arange(npoints), npoints)})
df['z'] = 0
df.loc[df['x'] == df['y'], 'z'] = df.loc[df['x'] == df['y'], 'x']
df['c'] = np.random.choice(np.arange(3) + 1, df.shape[0])
df.loc[df['x'] != df['y'], 'c'] = 0
fig, ax = plt.subplots()
qp = sns.heatmap(df[['x', 'y', 'z']].set_index(['x', 'y'])['z'].unstack(), ax=ax)
# df.plot(x='x', y='y', ax=ax, color=df['c'], kind='scatter')
ax.scatter(df['x']+0.5,df['y']+0.5,c=df['c'])
ax.set_title('Heatmap and scatter points - scales problem')
plt.show()
结果: