在seaborn heatmap中自动调整字体大小

Gab*_*iel 17 python matplotlib seaborn

当使用seaborn热图时,有没有办法自动调整字体大小以使其完全适合方块内?例如:

sns.heatmap(corrmat, vmin=corrmat.values.min(), vmax=1, square=True, cmap="YlGnBu", 
        linewidths=0.1, annot=True, annot_kws={"size":8})  
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这里的大小设置在"annot_kws"中.

小智 19

你也可以这样做:

sns.heatmap(corrmat, vmin=corrmat.values.min(), vmax=1, square=True, cmap="YlGnBu", linewidths=0.1, annot=True, annot_kws={"fontsize":8})  
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Rug*_*rra 7

如果你想要一些自动的东西,这还不错:

annot_kws={"size": 35 / np.sqrt(len(corrmat))},
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小智 6

调整seaborn热图的字体大小,有不同的方法

import seaborn as sns # for data visualization
flight = sns.load_dataset('flights') # load flights datset from GitHub seaborn repository

# reshape flights dataeset in proper format to create seaborn heatmap
flights_df = flight.pivot('month', 'year', 'passengers') 

sns.heatmap(flights_df) # create seaborn heatmap

sns.set(font_scale=2) # font size 2
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输出 >>>

在此处输入图片说明

sns.set(font_scale=2) # font size 2所有seaborn图形标签的设置大小,如果你喜欢,请遵循另一种方法

import seaborn as sns # for data visualization
import matplotlib.pyplot as plt # for data visualization

flight = sns.load_dataset('flights') # load flights datset from GitHub seaborn repository

# reshape flights dataeset in proper format to create seaborn heatmap
flights_df = flight.pivot('month', 'year', 'passengers') 

sns.heatmap(flights_df) # create seaborn heatmap


plt.title('Heatmap of Flighr Dataset', fontsize = 20) # title with fontsize 20
plt.xlabel('Years', fontsize = 15) # x-axis label with fontsize 15
plt.ylabel('Monthes', fontsize = 15) # y-axis label with fontsize 15

plt.show()
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输出 >>>

在此处输入图片说明


dji*_*inn 3

尽管它扭曲了热图,但此示例说明了如何使用.set(...)上下文缩放字体

import matplotlib.pyplot as plt
import seaborn as sns
sns.set(font_scale=3)

# Load the example flights dataset and conver to long-form
flights_long = sns.load_dataset("flights")
flights = flights_long.pivot("month", "year", "passengers")

# Draw a heatmap with the numeric values in each cell
f, ax = plt.subplots(figsize=(9, 6))
sns.heatmap(flights, annot=True, fmt="d", linewidths=.5, ax=ax)
f.savefig("output.png")
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