08-可视化操作-探索泰坦尼克灾难数据

利用python进行金融数据分析

import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns

pd.set_option('display.width',1000) url = 'train.csv'

titanic = pd.read_csv(url) print(titanic.head())

绘制一个展示男女乘客比例的扇形图

males = (titanic['Sex'] == 'male').sum() females = (titanic['Sex'] == 'female').sum()

proportions = [males, females]

plt.pie( proportions, labels = ['Males','Females'], shadow = False, colors= ['blue','red'], explode = (0.0,0.3), startangle = 0, autopct='%1.1f%%' ) plt.title('Sex Proportion')

plt.tight_layout() plt.show()

绘制一个展示船票Fare与乘客年龄和性别的散点图 lm = sns.lmplot(x = 'Age',y = 'Fare',data = titanic,hue = 'Sex' , fit_reg=False) lm.set(title = 'Fare x Age') axes = lm.axes axes[0,0].set_ylim(-5,) axes[0,0].set_xlim(-5,85) plt.show()

有多少人生还 print(titanic.Survived.sum())

绘制一个展示船票价格的直方图 df = titanic.Fare.sort_values(ascending=False)

print(df)

binsVal = np.arange(0,600,10) print(binsVal)

plt.hist(df,bins= binsVal)

plt.xlabel("Fare") plt.ylabel('Frequency') plt.title("Fare Payed Histrogram")

plt.show()

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