python-3.7 pycharm serborn-0.9.0
""" 可视化库Seaborn 时间：2018\9\13 0013 分析图绘制,Seaborn封装自Matplotlib """ import numpy as np import pandas as pd import matplotlib.pyplot as plt from scipy import stats, integrate import seaborn as sns sns.set(color_codes = True) np.random.seed(sum(map(ord, 'distributions'))) print("""\n-------------------单变量分析绘图-------------------------------------- ---------------------------------------------------------------\n""") x = np.random.normal(size = 100) sns.distplot(x, kde = True) # 直方图，kde密度曲线 plt.show() sns.distplot(x, bins = 20, kde = True) # 切分成20个小块 plt.show() x = np.random.gamma(6, size = 200) sns.distplot(x, bins = 20, kde = False, fit = stats.gamma) # 传入统计指标 plt.show() print("""\n-------------------二维分析绘图-------------------------------------- -------------------------------散点图--------------------------\n""") mean, cov = [0, 1], [(1, 0.5), (0.5, 1)] data = np.random.multivariate_normal(mean, cov, 200) df = pd.DataFrame(data, columns = ['x', 'y']) print(df) sns.jointplot(x = 'x', y = 'y', data = df) plt.show() x, y = np.random.multivariate_normal(mean, cov, 1000).T with sns.axes_style('white'): sns.jointplot(x = x, y = y, kind = 'hex', color = 'blue') plt.show() iris = sns.load_dataset('iris') sns.pairplot(iris) plt.show() print("""\n-------------------回归分析图-------------------------------------- --------------------------regplot(),lmplot()推荐使用regplot()-------------------------------\n""") tips = sns.load_dataset('tips') print(tips.head()) sns.regplot(x = 'total_bill', y = 'tip', data = tips) # x轴，y轴，数据DataFrame plt.show() sns.lmplot(x = 'total_bill', y = 'tip', data = tips) plt.show() sns.regplot(x = 'size', y = 'tip', data = tips) plt.show() sns.regplot(x = 'size', y = 'tip', data = tips, x_jitter = 0.05) # x加入抖动0.05 plt.show() print("""\n-------------------多变量分析图-------------------------------------- --------------------------stripplot(),swarmplot()-------------------------------\n""") titanic = sns.load_dataset('titanic') sns.stripplot(x = 'day', y = 'total_bill', data = tips, jitter = False) plt.show() sns.stripplot(x = 'day', y = 'total_bill', data = tips, jitter = True) # 左右摆动 plt.show() sns.swarmplot(x = 'day', y = 'total_bill', data = tips) plt.show() sns.swarmplot(x = 'day', y = 'total_bill', data = tips, hue = 'sex') # 指标 plt.show() print("""\n-------------------盒图-------------------------------------- --------------------------boxplot()-------------------------------\n""") sns.boxplot(x = 'day', y = 'total_bill', data = tips, hue = 'time') # orient = h横着画 plt.show() print("""\n-------------------小提琴图-------------------------------------- --------------------------violinplot()-------------------------------\n""") sns.violinplot(x = 'day', y = 'total_bill', data = tips, hue = 'time') plt.show() sns.violinplot(x = 'day', y = 'total_bill', data = tips, hue = 'time', split = True) plt.show() print("""\n-------------------组合图-------------------------------------- --------------------------violinplot()-------------------------------\n""") sns.violinplot(x = 'day', y = 'total_bill', data = tips, hue = 'time') sns.swarmplot(x = 'day', y = 'total_bill', data = tips, hue = 'time', color = 'w', alpha = 0.5) plt.show() print("""\n-------------------柱状图-------------------------------------- --------------------------barplot()-------------------------------\n""") sns.barplot(x = 'sex', y = 'survived', hue = 'class', data = titanic) plt.show() print("""\n-------------------点状差异图-------------------------------------- --------------------------barplot()-------------------------------\n""") sns.pointplot(x = 'sex', y = 'survived', hue = 'class', data = titanic) plt.show() sns.pointplot(x = 'class', y = 'survived', hue = 'sex', data = titanic, palette = {'male': 'g', 'female': "m"}, markers = ['^', 'o'], linestyles = ['-', '--']) plt.show() print("""\n-------------------多层面板分类图-------------------------------------- --------------------------catplot()-------------------------------\n""") sns.catplot(x = 'day', y = 'total_bill', data = tips, hue = 'smoker') plt.show() sns.catplot(x = 'day', y = 'total_bill', data = tips, hue = 'smoker', kind = 'bar') plt.show() sns.catplot(x = 'day', y = 'total_bill', data = tips, hue = 'smoker', col = 'time', kind = 'swarm') plt.show() sns.catplot(x = 'day', y = 'total_bill', data = tips, hue = 'smoker', col = 'day', kind = 'box', height = 4, width = 5) # 大小是4，长宽比是5 plt.show()
运行结果
