import scipy.stats as ss

这段代码主要是将scipy库中的统计模块stats导入，并将其命名为ss，方便在代码中使用。Scipy库是一个开源的Python科学计算库，包含了许多常用的数学、科学和工程计算功能，涵盖了优化、插值、积分、图像处理、信号处理、线性代数、统计学等领域。其中stats模块提供了各种统计分布、随机变量、假设检验、描述统计等相关的函数和方法，可以方便地进行各种统计分析。

相关问题

import numpy as np import scipy.stats as ss import pandas as pd import matplotlib.pyplot as plt import seaborn as sns df=pd.read_excel("./tmp_apply.xlsx") sns.set_context(font_scale=10) plv_tb=pd.pivot_table(df,values="sale",index=["FactoryName","JiJXH"],columns=["Xian"],aggfunc=np.mean) print(plv_tb) plt.figure(figsize=(200, 8)) sns.heatmap(plv_tb,vmin=0,vmax=4000,cmap=sns.color_palette("Blues",n_colors=200)) plt.show()怎么能使vmax最大值

你可以尝试将vmax的值设置为数据中的最大值，这样就能保证vmax是最大值了。具体的代码如下：

import numpy as np 
import scipy.stats as ss 
import pandas as pd 
import matplotlib.pyplot as plt 
import seaborn as sns 

df=pd.read_excel("./tmp_apply.xlsx") 

sns.set_context(font_scale=10) 

plv_tb=pd.pivot_table(df,values="sale",index=["FactoryName","JiJXH"],columns=["Xian"],aggfunc=np.mean) 

print(plv_tb) 

vmax = plv_tb.values.max()

plt.figure(figsize=(200, 8)) 

sns.heatmap(plv_tb,vmin=0,vmax=vmax,cmap=sns.color_palette("Blues",n_colors=200)) 

plt.show()

这样就能够保证vmax是最大值了。

from scipy import stats as ss

The `scipy.stats` module provides a large number of probability distributions and statistical functions. Here's an example of importing `scipy.stats` and using the `norm` function to generate a normal distribution:

import scipy.stats as ss

# generate a normal distribution with mean=0 and standard deviation=1
dist = ss.norm(0, 1)

# calculate the probability density function at x=0
pdf_at_0 = dist.pdf(0)

# calculate the cumulative distribution function at x=1.96
cdf_at_1_96 = dist.cdf(1.96)

# generate a random sample of size 1000 from the distribution
sample = dist.rvs(1000)

In this example, we first create a `norm` object with mean 0 and standard deviation 1, which represents a standard normal distribution. We then use several methods of this object to calculate the probability density function and cumulative distribution function at specific values, as well as generate a random sample of size 1000 from the distribution.