Using Python data to analyze the series of Panda Learning notes

1 Series

　　A: Objects that resemble one-dimensional arrays, each of which is composed of data labels associated with them

　B: The left side of the build is indexed, and the default is 0.

1  from Pandas import Series,dataframe 2  as PD 3  4 obj=series ([4,7,-5,3])5 obj# Index on left value on right

C: You can get the representation of an array and the indexed object by using the values and index properties

1 4,  7,-5,  3], dtype=Int64)2 obj.index

d: Set index values

1 obj2=series ([4,7,-5,3],index=['d', ' b ','a','C'])2  obj23 obj2.index

e: Value is worth by index

1 obj2['a']2 obj2[['C','  a','d']]3 obj2[obj2>0 ]

F: If the data is in a Python dictionary, the series can be created directly from the dictionary

1 sdata={' ohio':35000,'Texas':71000 ,'Oregon':16000,'Utah':  2 obj3=Series (sdata)3 obj3

A very important feature in G:series is that it automatically matches the same index when multiple series operations are performed

1 #如果数据在Python字典中 can create a series directly from this dictionary.2sdata={'Ohio':35000,'Texas':7100,'Oregon': the,'Utah': the}3obj3=Series (sdata)4 obj35 6 #如果只是传入一个字典 The index in the result series is the dictionary key missing as Nan7states=['California','Ohio','Oregon','Texas']8Obj4=series (sdata,index=states)9 Ten #使用isnull notnull Judging missing values One  A  - #Series中一个非常重要的功能就是在算数运算中自动对其不同索引得数据 - obj3 the Obj4 -Obj3+obj4

　　　

　There is a special attribute in H:series Name property

1 bj4.name='population'2 obj4.index.name=' State ' 3 OB

Using Python data to analyze the series of Panda Learning notes