利用Python数据分析：数据加载、存储与文件格式（一)

import pandas as pdfrom pandas import DataFrame,Seriesimport sysimport numpy as npdf = pd.read_csv('E:/Python for Data Analysis/pydata-book-master/ch06/ex1.csv')dfpd.read_table('E:/Python for Data Analysis/pydata-book-master/ch06/ex1.csv',sep =',') # read_table需要指定分隔符pd.read_csv('E:/Python for Data Analysis/pydata-book-master/ch06/ex2.csv',header = None) # 读取没有标题行的pd.read_csv('E:/Python for Data Analysis/pydata-book-master/ch06/ex2.csv',names=['a','b','c','d','message'])# 指定列名names = ['a','b','c','d','message']pd.read_csv('E:/Python for Data Analysis/pydata-book-master/ch06/ex2.csv',names= names,index_col='message')#把message列作为索引parsed = pd.read_csv('pydata-book-master/ch06/csv_mindex.csv',index_col=['key1','key2'])# 层次化的索引parsed# 使用正则表达式作为read_table的分隔符list(open('pydata-book-master/ch06/ex6.csv'))result = pd.read_table('pydata-book-master/ch06/ex6.csv',sep='/s+')resultpd.read_csv('pydata-book-master/ch06/ex4.csv',skiprows=[0,2,3]) # 跳过指定的行result = pd.read_csv('pydata-book-master/ch06/ex5.csv')resultresult = pd.read_csv('pydata-book-master/ch06/ex5.csv',na_values=['NULL'])result# 使用一个字典为各列指定不同的NA标记的值sentinels = {'message':['foo','NA'],'someting':['two']}pd.read_csv('pydata-book-master/ch06/ex5.csv',na_values=sentinels)#逐块读取文本文件result = pd.read_csv('pydata-book-master/ch06/ex6.csv')resultpd.read_csv('pydata-book-master/ch06/ex5.csv',nrows=5) # 只读取前五行chunker = pd.read_csv('pydata-book-master/ch06/ex5.csv',chunksize=1000) #分成1000块chunkertot = Series([]) # 定义一个Series来保存后面的数字for piece in chunker :    tot = tot.add(piece['key'].value_counts(),fill_value = 0)tot = tot.order(ascending=False)tot[:10]# 将数据写出到文本格式data = pd.read_csv('pydata-book-master/ch06/ex5.csv')datadata.to_csv('pydata-book-master/ch06/out.csv')data.to_csv(sys.stdout,sep='|') #以指定的分隔符输出data.to_csv(sys.stdout,na_rep='NULL') # 缺失值在结果中表示为空白符，也可以自己指定对应的符号# 不输出行列的标签data.to_csv(sys.stdout,index=False,header=False)data.to_csv(sys.stdout,index=False,cols=['a','b','c']) # 只写出一部分列并且指定列排序dates = pd.date_range('1/1/2000',periods=7)ts = Series(np.arange(7),index=dates)ts.to_csv('pydata-book-master/ch06/tseries.csv') # Series to_csv方法