Algorithm-LOWB three-person group

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D Definition:

Pandas is a powerful toolkit for data analysis in Python.

Pandas is built on the basis of numpy.

Installation method:pip Install pandasimport pandas as PDMain functions of Pandas

A data structure with its functions dataframe, Series

Integrated time series capabilities

Provides a wealth of mathematical operations and operations

Flexible handling of missing data

Series

Definition: A series is an object that resembles a single array, consisting of a set of data and a set of data labels (indexes) associated with it.

How to create:

How to create: PD. Series ([4,7,-5,3]) PD. Series ([4,7,-5,3],index=['a','b','C','D']) PD. Series ({'a':1,'b':2}) PD. Series (0, index=['a','b','C','d '])

Get an array of values and an indexed array: Value property and Index property

Series comparison is a combination of a list (array) and a dictionary.

Instance:

SR=PD. Series ([1,2,3,4],index=['a','b','C','D']) sr['a':'C']==>a-4b3C5dtype:int64sr[['a','D']]==a-4D6Dtype:int64 The condition is that the key is not a value'b' inchSR==true1 inchSR==Flase: The method to take the value is similar to the dictionary Sr.Get('a',0)

Judging, slicing, taking value

SR=PD. Series ([1,2,3,4],index=['b','C','D','a']) b1C2D3a4dtype:int64sr.iloc[1] #取索引为1==2sr.ilc[2] #取索引为2==3

Fetch Index

SR=PD. Series ([1,2,3,4],index=['b','C','D','a']) SR1=PD. Series ([5,6,7,8,9],index=['a','b','C','D','e']) SR2=PD. Series ([5,6,7,8,9,Ten],index=['a','b','C','D','e','F']) SR+SR1==a9.0b7.0C9.0D11.0e nandtype:float64ps: The extra value is just the Nanadd method SR3=sr.add (sr2,fill_value=0) SR3:==a9.0b7.0C9.0D11.0e9.0F10.0Dtype:float64 with the Add method: No, the Nan is not present

Add method and A+b difference

sr4a9.0b7.0C9.0D11.0e NaNdtype:float64sr4.notnull () a trueb truec trued truee falsedtype:BOOLsr4[sr4.notnull ()] #把是NAN的去掉a9.0b7.0C9.0D11.0Sr4.dropna () #也是直接去掉为nan的a9.0b7.0C9.0D11.0Dtype:float64

Notnull () and Dropna ()

SR=PD. DataFrame ({' One':[1,2,3,4],' Both':[ +,4,5,6]},index=['a','s','D','Q'])

= [Random.uniform (ten, 6.3  list (map (lambda x:x*ratio, Li))

Map Function Call

DF = pd.read_csv ('601318.csv', Header=none, names=list ('asdfghjk') ))

DF = pd.read_csv ('601318.csv', index_col=1, parse_dates=['date  ']) DF

Df.groupby ('key1'). SUM ()

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Algorithm-LOWB three-person group