Python – seaborn.pointplot() 方法

Seaborn是一个惊人的Python统计图形绘图可视化库。它提供了漂亮的默认样式和调色板，使统计图更具吸引力。它建立在 matplotlib 库之上，并且与 pandas 的数据结构紧密集成。

seaborn.pointplot() ：

• 此方法用于使用散点图字形显示点估计值和置信区间。点图表示通过散点图点的位置对数值变量的集中趋势的估计，并使用误差条提供该估计周围的不确定性的一些指示。
• 此函数始终将其中一个变量视为分类变量，并在相关轴上的序数位置 (0, 1, ... n) 处绘制数据，即使数据具有数字或日期类型也是如此。

Syntax: seaborn.pointplot(x=None, y=None, hue=None, data=None, order=None,hue_order=None, estimator=, ci=95, n_boot=1000, units=None, markers=’o’, linestyles=’-‘, dodge=False, join=True, scale=1, orient=None, color=None, palette=None, errwidth=None, capsize=None, ax=None, **kwargs)

Parameters: The description of some main parameters are given below:

• x, y: Inputs for plotting long-form data.
• hue: (optional) column name for color encoding.
• data: dataframe as a Dataset for plotting.
• markers: (optional) Markers to use for each of the ‘hue’ levels.
• linestyles: (optional) Line styles to use for each of the ‘hue’ levels.
• dodge: (optional) Amount to separate the points for each level of the ‘hue’ variable along the categorical axis.
• color: (optional) Color for all the elements, or seed for a gradient palette.
• capsize: (optional) Width of the ‘caps’ on error bars.

Return: The Axes object with the plot drawn onto it.

下面是上述方法的实现：

示例 1：

Python3

# importing required packages
import seaborn as sns
import matplotlib.pyplot as plt
  
# loading dataset
data = sns.load_dataset("tips")
  
# draw pointplot
sns.pointplot(x = "sex",
              y = "total_bill",
              data = data)
# show the plot
plt.show()
# This code is contributed 
# by Deepanshu Rustagi.

输出：

示例 2：

Python3

# importing required packages
import seaborn as sns
import matplotlib.pyplot as plt
  
# loading dataset
data = sns.load_dataset("tips")
  
# draw pointplot with
# hue = smoker
sns.pointplot(x = "sex",
              y = "total_bill",
              hue = "smoker",
              data = data)
# show the plot
plt.show()
# This code is contributed 
# by Deepanshu Rustagi.

输出 ：

示例 3：

Python3

# importing required packages
import seaborn as sns
import matplotlib.pyplot as plt
  
# loading dataset
data = sns.load_dataset("tips")
  
# draw pointplot
sns.pointplot(x = "size",
              y = "total_bill",
              linestyles = '-.',
              markers = '^',
              hue = "sex",
              data = data)
# show the plot
plt.show()
  
# This code is contributed 
# by Deepanshu Rustagi.

输出：