Jerry Licun Pages

处理数据的基本操作

Libraries
	import matplotlib.pyplot as plt
	%matplotlib inline
	import pandas as pd
	import numpy as np
	import seaborn as sns
	
Exploratory Data Analysis Demos.ipynb
Panda基本作图方法：
• Bar Plot: plt.bar([10, 20, 30], [5, 8, 2])
• Histogram: plt.hist(y1)
• Boxplot: y_outliers = y1+[-10]
	   plt.boxplot([y1,y_outliers])
	   plt.show()
• Line plot: plt.plot(x,y1,'-')
• Scatter plot: plt.plot(x,y1,'.r')

统计unique值： df1['sex'].unique()
统计值个数： df1['fare'].value_counts()
统计空值：sum(df1['embarked'].isnull())

Week 6  tutorial Data Auditing answer.ipynb
描述数据：
	titanic.describe()
	titanic.info()
按条件提取： titanic[titanic.title == "Rev"]
             titanic[((titanic.who == "man") | (titanic.who == "woman")) & (titanic.age < 18)]
替换值：titanic.embark_town.replace({"Cherborg": "Cherbourg", "Cherbourge": "Cherbourg"}, inplace=True)
        titanic['sex'].replace({'F':'female', 'M':'male'},inplace=True)
处理重复值(只留第一个): titanic[titanic.duplicated(["firstName", "lastName", "age"], keep="first")]

分割一个列里面的不同字段