我有一个使用
seaborn
库创建的基本热图,并且希望将颜色条从默认的垂直右侧移动到热图上方的水平颜色条。我该怎么做?
以下是一些示例数据和默认值的示例:
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
# Create data
df = pd.DataFrame(np.random.random((5,5)), columns=["a","b","c","d","e"])
# Default heatma
ax = sns.heatmap(df)
plt.show()
查看文档,我们发现一个论点
cbar_kws
。这允许指定传递给 matplotlib 的 fig.colorbar
方法的参数。
:键字典,值映射,可选。cbar_kws
. 的关键字参数fig.colorbar
因此我们可以使用
fig.colorbar
的任何可能的参数,为 cbar_kws
提供字典。
在这种情况下,您需要
location="top"
将颜色条放在顶部。因为 colorbar
默认情况下使用 gridspec 定位颜色条,然后不允许设置位置,所以我们需要关闭该 gridspec (use_gridspec=False
)。
sns.heatmap(df, cbar_kws = dict(use_gridspec=False,location="top"))
完整示例:
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.random((5,5)), columns=["a","b","c","d","e"])
ax = sns.heatmap(df, cbar_kws = dict(use_gridspec=False,location="top"))
plt.show()
我想展示带有子图的示例,它允许控制图的大小以保留热图的方形几何形状。这个例子很短:
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
# Create data
df = pd.DataFrame(np.random.random((5,5)), columns=["a","b","c","d","e"])
# Define two rows for subplots
fig, (cax, ax) = plt.subplots(nrows=2, figsize=(5,5.025), gridspec_kw={"height_ratios":[0.025, 1]})
# Draw heatmap
sns.heatmap(df, ax=ax, cbar=False)
# colorbar
fig.colorbar(ax.get_children()[0], cax=cax, orientation="horizontal")
plt.show()
您必须使用轴分隔器将颜色条放在seaborn图形的顶部。看看评论。
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
from mpl_toolkits.axes_grid1.colorbar import colorbar
# Create data
df = pd.DataFrame(np.random.random((5,5)), columns=["a","b","c","d","e"])
# Use axes divider to put cbar on top
# plot heatmap without colorbar
ax = sns.heatmap(df, cbar = False)
# split axes of heatmap to put colorbar
ax_divider = make_axes_locatable(ax)
# define size and padding of axes for colorbar
cax = ax_divider.append_axes('top', size = '5%', pad = '2%')
# make colorbar for heatmap.
# Heatmap returns an axes obj but you need to get a mappable obj (get_children)
colorbar(ax.get_children()[0], cax = cax, orientation = 'horizontal')
# locate colorbar ticks
cax.xaxis.set_ticks_position('top')
plt.show()
有关更多信息,请阅读 matplotlib 的官方示例:https://matplotlib.org/gallery/axes_grid1/demo_colorbar_with_axes_divider.html?highlight=demo%20colorbar%20axes%20divider
像sns.heatmap(df, cbar_kws = {'orientation':'horizontal'})
这样的
Heatmap参数是无用的,因为它将颜色条放在底部位置。