python3.ML.Seaborn画图REG-回归分析绘图（是否付小费数据案例）
获取是否付小费数据
regplot（）和lmplot（）都可以绘制回归关系，推荐regplot（）
sns.lmplot(x="x", y="y", data=XXX, order=2); #曲线
利用hue参数画出男女给予小费的不同
sns.lmplot(palette="Set1");#lmplot中加入调色板palette
sns.lmplot(col="time", row="sex");#lmplot中加入col、row参数
参数ax
col_wrap:“包装”列变量在这个宽度,这列方面跨越多个行
size :身高(英寸)的每个方面
获取是否付小费数据
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#!/usr/bin/python
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# -*- coding: UTF-8 -*-
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# %matplotlib inline
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import numpy
as np
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import pandas
as pd
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import matplotlib
as mpl
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import matplotlib.pyplot
as plt
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import seaborn
as sns
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sns.set(color_codes=
True)
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np.random.seed(sum(map(ord,
"regression")))
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tips = sns.load_dataset(
"tips")
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print(tips.head())
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'''
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total_bill tip sex smoker day time size
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0 16.99 1.01 Female No Sun Dinner 2
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1 10.34 1.66 Male No Sun Dinner 3
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2 21.01 3.50 Male No Sun Dinner 3
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3 23.68 3.31 Male No Sun Dinner 2
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4 24.59 3.61 Female No Sun Dinner 4
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'''
regplot（）和lmplot（）都可以绘制回归关系，推荐regplot（）
sns.regplot(x="total_bill", y="tip", data=tips)
sns.lmplot(x="total_bill", y="tip", data=tips);
sns.regplot(data=tips,x="size",y="tip")
sns.regplot(x="size", y="tip", data=tips, x_jitter=.05)
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anscombe = sns.load_dataset(
"anscombe")
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sns.regplot(x=
"x", y=
"y", data=anscombe.query(
"dataset == 'I'"),
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ci=
None, scatter_kws={
"s":
100})
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anscombe = sns.load_dataset(
"anscombe")
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sns.lmplot(x=
"x", y=
"y", data=anscombe.query(
"dataset == 'II'"),
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ci=
None, scatter_kws={
"s":
80})
sns.lmplot(x="x", y="y", data=XXX, order=2); #曲线
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sns.lmplot(x=
"x", y=
"y", data=anscombe.query(
"dataset == 'II'"),
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order=
2, ci=
None, scatter_kws={
"s":
80});
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sns.lmplot(x=
"x", y=
"y", data=anscombe.query(
"dataset == 'I'"),
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order=
2, ci=
None, scatter_kws={
"s":
80});
利用hue参数画出男女给予小费的不同
sns.lmplot(x="total_bill", y="tip", hue="sex", data=tips);
sns.lmplot(palette="Set1");#lmplot中加入调色板palette
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sns.lmplot(x=
"total_bill", y=
"tip", hue=
"smoker",
data=tips,
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markers=[
"o",
"x"], palette=
"Set1");
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colors = [
"windows blue",
"amber",
"greyish",
"faded green",
"dusty purple"]
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sns.lmplot(x=
"total_bill", y=
"tip", hue=
"smoker",
data=tips,
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markers=[
"o",
"x"], palette=sns.xkcd_palette(colors));
sns.lmplot(col="time", row="sex");#lmplot中加入col、row参数
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sns.lmplot(x=
"total_bill", y=
"tip", hue=
"smoker",
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col=
"time", row=
"sex",
data=tips);
参数ax
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f, ax = plt.subplots(figsize=(
5,
5))
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sns.regplot(x=
"total_bill", y=
"tip",
data=tips, ax=ax);
col_wrap:“包装”列变量在这个宽度,这列方面跨越多个行
size :身高(英寸)的每个方面
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sns.lmplot(x=
"total_bill", y=
"tip", col=
"day",
data=tips,
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col_wrap=
2, size=
4);
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sns.lmplot(x=
"total_bill", y=
"tip", col=
"day",
data=tips,
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col_wrap=
3, size=
4);
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sns.lmplot(x=
"total_bill", y=
"tip", col=
"day",
data=tips,
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aspect=
.8);
