更多机器学习知识请查收于： https://blog.csdn.net/weixin_45316122/article/details/109854595
Trick：纯demo，心在哪里，结果就在那里
14 import pandas as pd data = pd.Series([2,1,3,4,5]) data data.values data.index data[0] data[0:3] data1 = pd.Series([1,2,3],index=['first','second','third']) data1 data1.index data2 = pd.Series([1,2,3,4],index=list("abcd")) data2 14 a 1 b 2 c 3 d 4 dtype: int64 Series对象的字典属性 22 p = {"b":3000,"sh":2800,"gz":'1500',"sz":1200} p p_Series = pd.Series(p) p_Series #对象可以按照字典的方式索引 p_Series['b'] # 对于字典式索引，切片操作不同于往常习惯，采取了左闭右闭的方式 p_Series["b":"sh"] pop_series = pd.Series(p,index=['b','sz']) pop_series pop_series = pd.Series(p,index=['xian']) pop_series s= pd.Series(5,index=[2,3,5,7]) s 22 2 5 3 5 5 5 7 5 dtype: int64 DataFrame对象 45 # dataframe对象 和sieries对象类似 既可以看作是一个二维数组，也可看做字典的字典 import pandas as pd import numpy as np area_dict = {'beijing':300,'shanghai':200,'gz':180} area = pd.Series(area_dict) print(area) pop = pd.Series({'beijing':3000,'shanghai':2900,'gz':1600}) print(pop) cities = pd.DataFrame({'population':pop,'area':area}) cities cities.index cities.values cities['area'] cities.iloc[0,1] df = pd.DataFrame([pop,area],index=['population','area']) # 在pandas中行索引叫index，列索引叫columns,此处应该显式指定index df data = pd.DataFrame([{'a':i,'b':2*i}for i in range(3)]) #通过一个关于字典的列表创建了df对象 data data2 = pd.DataFrame(np.random.randint(0,10,(3,2)),columns=list('ab'),index =list('efg')) print(data2.columns) print(data2.index) print(data2) beijing 300 shanghai 200 gz 180 dtype: int64 beijing 3000 shanghai 2900 gz 1600 dtype: int64 Index(['a', 'b'], dtype='object') Index(['e', 'f', 'g'], dtype='object') a b e 3 8 f 6 3 g 1 4 No output
