categorical data analysis using sas

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Knimi Data Mining modeling and Analysis series _003_ using Knimi to do customer segmentation

FlowFour, according to the sales data to the customer hierarchical clustering calculation1. connect to query customer's consumer informationSetting connection and key columnsQuery results2. standardization before cluster computingSet up columns and standardized algorithms that require normalizationStandardized results3. Compute Hierarchical ClusteringSpecify distance functions, connection types, and columns that participate in cluster calculationsHie

Using the Website Data Analysis assistant work to carry on the good design

Article Description: Data-aided design-practice in search. Design can not be based on experience and intuition, because the target groups involved, the scene, the operation of the different habits. In order to obtain more accurate and effective information to assist and detect the design, the designer chooses the qualitative (user interview, focus Group) and quantitative (survey questionnaire, website

Commodity recommendation using association rules of SQL Server Analysis Services data mining (I)

If you have a shopping website, how do you recommend products to your customers? This function is available on many e-commerce websites. You can easily build similar functions through the data mining feature of SQL Server Analysis Services. It is divided into three parts to demonstrate how to implement this function. Build a Mining Model Write service interfaces for the Mining Model Develop simple front

"Data analysis using Python" reading notes--fifth Chapter pandas Introduction

Pandas is the preferred library for subsequent content in this book. The pandas can meet the following requirements: Data structure with automatic or explicit data alignment by axis. This prevents many common errors caused by data misalignment and data from different data

Using Python for data analysis (5) NumPy basics: ndarray index and slicing,

Using Python for data analysis (5) NumPy basics: ndarray index and slicing,Concept understanding IndexYou can use an unsigned integer to obtain the values in the array.SliceThat is, the description of a segment in a logarithm group. One-dimensional array Index of one-dimensional arrayThe indexing of one-dimensional arrays is similar to that of Python lists: T

"Data analysis using Python" reading notes--tenth chapter time series

, time data. And there are calendar features. The datetime, time, and calendar modules are used primarily. #-*-coding:utf-8-*-ImportNumPy as NPImportPandas as PDImportMatplotlib.pyplot as PltImportdatetime as DT fromDatetimeImportDatetimenow=DateTime.Now ()#datetime stores time in millisecondsPrintNow,now.year,now.month,now.day,now.microsecond,'\ n'#print datetime (2015,12,17,20,00,01,555555) #设置一个时间#Datetime.timedelta represents a time difference bet

"Data analysis using Python" NumPy basics: Arrays and vector Computing learning notes

I. Related NumPy(i) Official explanationsNumPy is the fundamental package for scientific computing with Python. It contains among other things: A powerful N-dimensional Array object Sophisticated (broadcasting) functions Tools for integrating C + + and Fortran code Useful linear algebra, Fourier transform, and random number capabilities Besides its obvious scientific uses, NumPy can also is used as an efficient multi-dimensional container of generic

Analysis of Gene Chip data using R and biocondu( 2): Missing Value Filling

The data used for the following analysis can be found here ( "Href =" http://dl.getdropbox.com/u/308058/blog/raw_data_3_replicates.txt "> http://dl.getdropbox.com/u/308058/blog/raw_data_3_replicates.txt) download, the data comes from a study on Gene Transfer of butterflies, 20 sample butterfly individuals, 10 of which are local inherent (old ), the other 10 are

Introduction to the second chapter, "Data analysis using Python" study notes _1

Returns a Series that contains only non-empty data and index valuesRemove the missing field first: Cframe=frame[frame.a.notnull ()]Second, it calculates whether the rows are Windows based on the value of a, #np. The WHERE function is a vectorization ifelse functionOperating_system=np.where (cframe[' a '].str.contains (' windows '), ' windows ', ' no windows ')Next, the data is grouped according to the time

Data analysis using Python d1--ch02 introduction

The Basic course has not finished, it came to this, because my usual research is based on data processing. Who says the woman is inferior to the male 650) this.width=650; "src=" Http://img.baidu.com/hi/jx2/j_0011.gif "alt=" J_0011.gif "/>do your own things well done carefully, Hee 650) this.width=650; "src=" Http://img.baidu.com/hi/jx2/j_0003.gif "alt=" J_0003.gif "/>Read the introductory section, download the dat

Analysis on thinkphp using getlist method to realize data searching function

This article mainly introduces the thinkphp using GetList method to achieve data search function, combined with the case form more detailed analysis of thinkphp based on the getlist implementation of the data according to the given conditions of the reading, display and other related operations skills, the need for fri

Python Data analysis 6: Shuangse qiu using linear regression algorithm to predict next-period winning results __ algorithm

This time will be the next issue of SHUANGSE Qiu number forecast, think of a little excitement ah. The code uses the linear regression algorithm, which uses this algorithm to predict the effect, and you can consider using other algorithms to try the results. Before discovering a lot of code is repetitive work, in order to make the code look more elegant, define the function, to call, suddenly tall #!/usr/bin/python #-*-Coding:utf-8-*-#导入需要的包 Import p

From the data structure analysis, we can see that using foreach... in is faster than for... in.

This article will introduce you to the small series. From the data structure analysis, we can see that using foreach... in is faster than for... in. For more information about the syntax that Firefox's JS engine supports for each in, see the following code: The Code is as follows: Var arr = [10, 20, 30, 40, 50];For each (var k in arr)Console. log (k ); You can

Linear/Nonlinear Regression fitting example using R language (1) _ Data analysis

A linear/Nonlinear regression fitting example using R language (1) 1. Generate a set of data vector vector Ofstreamfout ("Data2.txt"); for (int i =1;i { float x =i*0.8; Float randdnum= rand ()%10 * 10; Floatrandomflag = (rand ()%10)%2==0? (1):(-1); Float y = 3 *x*x + 2*x + 5 + randomflag*randdnum; fout Xxvec.push_back (x); Yyvec.push_back (y); } Fout.close (); Save the generated

Data analysis using Python-the Tenth Time series (1)

???IndexP.asfreq (' M ', ' Start ') #将年度数据转换为月度的形式, converted to the month of the yearP.asfreq (' M ', ' End ') #将年度数据转换为月度的形式, converted to December of the yearP1=PD. Period (' freq= ', ' A-jun ')P1.asfreq (' m ', ' Start ') #Period (' 2015-07 ', ' m ')P1.asfreq (' m ', ' End ') #Period (' 2016-06 ', ' m ')P2=PD. Period (' 2016-09 ', ' M ')P2.asfreq (' A-jun ') #2016年9月进行频率转换, equivalent to 2017 years in the time frequency ending in JuneRng=pd.period_range (' 2006 ', ' freq= ', ' A-dec ')Ts=ser

Using Python for data analysis (Pandas) Basics: string manipulation

the string object method Split () method splits the string:The Strip () method removes whitespace and line breaks:Split () in combination with strip () using:The "+" symbol allows you to concatenate multiple strings together:The join () method is also the connection string, comparing it to the "+" symbol:The In keyword determines whether a string is contained in another string:The index () method and the Find () method determine the location of a substring: the difference between the index ()

"Data analysis using Python" reading notes--tenth Chapter time series (iii)

said that the interactive way right-click and hold the date will be dynamically expanded or shrunk, actually do it, no effect ...plt.show ()>>>AA AAPL GE IBM JNJ MSFT PEP SPX XOM1990-02-01 4.98 7.86 2.87 16.79 4.27 0.51 6.04 328.79 6.121990-02-02 5.04 8.00 2.87 16.89 4.37 0.51 6.09 330.92 6.241990-02-05 5.07 8.18 2.87 17.32 4.34 0.51 6.05 331.85 6.251990-02-06 5.01 8.12 2.88 17.56 4.32 0.51 6.15 329.66 6.231990-02-07 5.04 7.77 2.91 17.93 4.38 0.51 6.17 333.75 6.33AAPL MSFT XOM1990-02-01 7.86 0

Using Python for Titanic survival predictions-data exploration and analysis

, indicating that age was related to survival.3.2.4 the relationship between brothers and sisters and whether they are alive or notFrom the data, siblings have the highest survival rate in 1-2.3.2.5 whether there is a relationship between parents ' children and survivalThe data show that the number of parents and children in 1-3 survival rate is the highest, the more the number is decreased survival rate.Th

Windows/linux installation of Python2.7,pycharm and pandas--"data analysis using Python"

--pylabImport Pandasplot (Arange (10))The appearance of the tablet is the success:PS: often easy to appear during installation of Pandas error :' ASCII ' codec can ' t decode byte 0xd5 Workaround: Add in python/lib/site.py Import sysreload (SYS) sys.setdefaultencoding ('gbk')2. Install the Pycharm and install the pandas (you can also add a package such as NumPy, the same way)Download and install Pycharm, and then add Pandas in Pycharm: (The process of installing pycharm is no longer explained)

Using Python for data analysis (one) Pandas Basics: Hierarchical indexing

Hierarchical Indexes Hierarchical indexing means you can have multiple indexes on an array, for example: a bit like a merged cell in Excel, right?Select a subset of the data based on the index to select a subset of the data from the other layer:Select data in the same way as the index in the layer:Multi-index series conversion to Dataframe hierarchical indexes pl

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