import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns

% matplotlib inline

sns.set_style("ticks")

sns.set_context("paper")

# 设置风格、尺度

import warnings

warnings.filterwarnings('ignore')

# 不发出警告

# 1、基本设置

# 绘制直方图

tips = sns.load_dataset("tips")

print(tips.head())

# 导入数据

g = sns.FacetGrid(tips, col="time", row="smoker")

# 创建一个绘图表格区域，设置好row、col并分组

g.map(plt.hist, "total_bill",alpha = 0.5,color = 'k',bins = 10)

# 以total_bill字段数据分别做直方图统计

# 1、基本设置

# 绘制直方图

g = sns.FacetGrid(tips, col="day",

                  size=4,    # 图表大小

                  aspect=.5) # 图表长宽比

g.map(plt.hist, "total_bill", bins=10,

      histtype = 'step',   #'bar', 'barstacked', 'step', 'stepfilled'

      color = 'k')

# 1、基本设置

# 绘制散点图

g = sns.FacetGrid(tips, col="time",  row="smoker")

# 创建一个绘图表格区域，设置好row、col并分组

g.map(plt.scatter,

      "total_bill", "tip",    # share{x,y} → 设置x、y数据

      edgecolor="w", s = 40, linewidth = 1)   # 设置点大小，描边宽度及颜色

g.add_legend()

# 添加图例

# 1、基本设置

# 分类

g = sns.FacetGrid(tips, col="time",  hue="smoker")

# 创建一个绘图表格区域，设置好col并分组，按hue分类

g.map(plt.scatter,

      "total_bill", "tip",    # share{x,y} → 设置x、y数据

      edgecolor="w", s = 40, linewidth = 1)   # 设置点大小，描边宽度及颜色

g.add_legend()

# 添加图例

# 2、图表矩阵

attend = sns.load_dataset("attention")

print(attend.head())

# 加载数据

g = sns.FacetGrid(attend, col="subject", col_wrap=5,   # 设置每行的图表数量

                  size=1.5)

g.map(plt.plot, "solutions", "score",

      marker="o",color = 'gray',linewidth = 2)

# 绘制图表矩阵

g.set(xlim = (0,4),

      ylim = (0,10),

      xticks = [0,1,2,3,4],

      yticks = [0,2,4,6,8,10]

      )

# 设置x，y轴刻度