02-pandas数据Serious
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import pandas as pd from pandas import Series import numpy as np from pandas import DataFrame obj=Series([1,2,3,4,5])#Series包含行索引,列索引。默认0,1,2,3,4 obj2=Series([1,2,3,4,5],index=["a","b","c","d","e"])#自定义索引 arr1=np.arange(10) obj3=Series(arr1,index=["a","b","c","d","e","f","h","j","k","l"])#索引对不上就会报错,索引要唯一 obj3=Series({"11111":1234,"abcabc":2222}) gk=Series([150,150,150,300],index=["数学","英语","语文","理科综合"]) obj4=Series([11,12,13,14,15]) print(obj4[0:2])#前提索引是数字 # print(testobj.loc(3))#标识索引对象 print(obj4.loc[0])#loc下标取值 obj5=Series([11,12,13,14,15],index=["a","b","c","d","e"]) # print(obj5.loc[3])#非数字索引loc取值就会报错 print(obj5[0:3])#非数字索引但是常规取值可以 print(obj5["a":"c"]) print(obj5.loc["d"])#loc取值 print(obj5.iloc[0:2 ]) #自定义索引obj[]既可以是数字也可以是自定义 #obj.loc[]只能是自己定义索引 #loc按照实际索引 #iloc按照数字所以 """ Series A=对象 A[0]:根据数字索引取出数据 A[1:3]:根据数字索引切片 A["a"]:根据自定义索引取出数据 A["a","b"]:根据自定义索引切片 loc:#按照自定义索引 iloc:按照索引 """ print(obj5.shape)#形状 print(obj5.size)#多少元素 print(obj5.values)#返回数组的数值,numpy print(obj5.head())#查看默认前五行,输入10就是前十行 print(obj5.tail())#查看尾部 mydict={"a":1,"b":2,"c":3} index=["a","b","x"]#不在索引的数据会被狐狸,Nan不存在 obj6=Series(mydict,index=index) print(pd.isnull(obj6))#判断数据是否完整 print(pd.notnull(obj6))#判断数据不为空 obj6.name="自定义名称" print(obj6.name) print(obj6+2)#表示每个数都加二 print(obj6[obj6>1])#数据筛选 A=Series([1,2,3],index=["a","b","c"]) B=Series([11,22,33],index=["a","b","c"]) print(A+B)#计算索引要一致 A=Series([1,2,3],index=["a","b","c1"]) B=Series([11,22,33],index=["a","b","c"]) print(A.add(B,fill_value=0))#索引不对等的加上零 #a 12.0 # b 24.0 # c 33.0 # c1 3.0
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