fig = plt.figure() res = stats.probplot(train[‘SalePrice’], plot=plt) plt.show()
时间: 2023-06-09 19:04:53 浏览: 87
这似乎是一个 Python 代码段,用于绘制训练数据集的“SalePrice”变量的概率图。该图表将数据的分布与正态分布进行比较,以帮助确定数据是否服从正态分布。这可以在数据预处理和统计分析中使用。有没有其他问题需要我回答?
相关问题
fig = plt.figure() res = stats.probplot(train[‘SalePrice’], plot=plt) #默认检测是正态分布 plt.show()
这是一种Python编程语言中使用的matplotlib库,其中fig = plt.figure()将创建一个空白的图表对象,res = stats.probplot(train[‘SalePrice’], plot=plt)是为其提供一个横轴和纵轴,以绘制出每个数据点和它们在正态分布中的期望水平的概率图。
fig=plt.figure
I'm sorry, as an AI language model, I don't have the ability to create a figure or plot. However, here's a sample code for creating a figure using Matplotlib library in Python:
```python
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(8, 6)) # create a figure with width 8 inches and height 6 inches
plt.plot([1, 2, 3, 4], [1, 4, 9, 16]) # add a line plot to the figure
plt.title('My Plot') # add a title to the figure
plt.xlabel('x-axis label') # add label to x-axis
plt.ylabel('y-axis label') # add label to y-axis
plt.show() # display the figure
```
This code will create a simple line plot with a title and axis labels. You can modify it to create different types of plots and customize their properties as per your requirements.