Dataframe Application of Pandas Library of Python data analysis

　　

This section describes the basic methods of data in series and Dataframe

1. Re-index

An important method of Pandas objects is reindex, which is to create a new object that adapts to the new index

" "Created on 2016-8-10@author:xuzhengzhu" "" "Created on 2016-8-10@author:xuzhengzhu" " fromPandasImport*Print "--------------obj Result:-----------------"obj=series ([4.5,7.2,-5.3,3.6],index=['D','b','a','C'])PrintobjPrint "--------------obj2 Result:-----------------"Obj2=obj.reindex (['a','b','C','D','e'])PrintObj2Print "--------------obj3 Result:-----------------"obj3=obj.reindex (['a','b','C','D','e'],fill_value=0)PrintObj3

Reindex

#reindex对索引值进行重排, if the current index value does not exist, a missing value is introduced
#可以指定fill_value =% to replace missing values

--------------obj Result:-----------------d    4.5b    7.2a   -5.3c    3.6Dtype:float64--------------obj2 Result:-----------------a   -5.3b     7.2C    3.6d    4.5e    nandtype:float64--------------obj3 Result:------ -----------a   -5.3b    7.2C    3.6d    4.5e    0.0Dtype:float64

Reindex_index

2. Interpolation

For ordered data such as time series, it may be necessary to do some interpolation when re-indexing, the method option can achieve this purpose:

For ordered data such as time series, it may be necessary to do some interpolation when re-indexing, the method option can achieve this purpose:

Method Parameter Introduction
Parameters	Description
Ffill or pad	Forward padding
Bfill or Backfill	Back to fill

" "Created on 2016-8-10@author:xuzhengzhu" " fromPandasImport*Print "--------------obj3 Result:-----------------"obj3=series (['Blue','Red','Yellow'],index=[0,2,4])Printobj3Print "--------------obj4 Result:-----------------"Obj4=obj3.reindex (Range (6), method='Ffill')PrintObj4

Ffill Front padding

--------------obj3 Result:-----------------0      Blue2       Red4    Yellowdtype:object --------------obj4 Result:-----------------0      Blue1      Blue2       Red 3       Red4    yellow5    yellowdtype:object

Ffill Results:

Dataframe Application of the pandas Library of Python data analysis two