best book on exploratory data analysis

columns, where the random number is generated by the standard uniform distribution (U (0,1)).RNG (' Default '); % for ReproducibiltyX = rand (20000,3);Use Ward's linkage to generate hierarchical clustering trees. Set ' savememory ' to ' on ' to construct the cluster but not to calculate the distance matrix.c = Clusterdata (X, ' linkage ', ' ward ', ' savememory ', ' on ', ' Maxclust ', 4);Plot the data into a graphic, where each category corresponds

Example Compare Cluster Assignments to ClustersImport the sample data.Load FisheririsFrom the Anderson Iris Floral Data set, the ward linkage calculates four clusters and ignores the type information.Z = Linkage (MEAs, ' Ward ', ' Euclidean ');c = Cluster (Z, ' Maxclust ', 4);The relationship between cluster results and three species was observed.Crosstab (c,species)Print the first 5 lines of Z.firstfive = Z (1:5,:)Generates a system tree graph

following conditions are available:Linkage is ' centroid ', ' median ' or ' ward 'Distance is ' Euclidean ' (default)When Savememory is ' on ', the linkage run time and the number of dimensions (number of columns in x) are proportional. When Savememory is ' off ', the demand for linkage memory is proportional to N2, where n is the number of observations. The best (and least time-consuming) savememory settings for all choices depend on the dimension of the problem, the number of observations, or

=-0.10993962467082698 View the statistical distribution of data Val Colarray = Array ("Age", "yearsmarried", "religiousness", "Education", "occupation", "rating")//view the statistical distribution of the data Val DESCRDF = Data.describe ("Age", "yearsmarried", "religiousness", "Education", "occupation", "rating") DESCRDF: Org.apache.spark.sql.DataFrame = [Summary:string, age:string ... 5 more

Exploratory analysis referred to as EDAI. Basic DESCRIPTIVE statistics1.summary functionMaximum, minimum, median, and mean values can be obtained2. Four decimal pointsThe quaternion can be obtained by quantile function, and diff gets the difference of each sub-number.> Library (RSADBE)> Data ("Thewall")> quantile (Thewall$score)> diff (quantile (thewall$score))3.

Essential Python Lib This section describes various types of libraries commonly used by Python for big data analysis. Numpy Python-specific standard module library for numerical computation, including: 1. A powerful n-dimensional Array object Array; 2. Mature (broadcast) function libraries; 3. toolkit for integrating C/C ++ and Fortran code; 4. Practical linear algebra, Fourier transformation, and ran

):int isprime (int N) {int i;if (n = = 1) return 0;if (n 2 = = 0) return 0;for (i = 3; I For B, obviously there is, B = O (LOGN).For C, because B = O (logn), 2B = O (N), that is, 2B/2 = O (√n), the worst-case run time in B is: O (2B/2)For D, the running time of the latter is the square of the former running time, which is easily known by the solution in C.For E,wiss said: B is the better measure because it more accurately represents the size of the input. All rights Reserved.author: Haifen

1. The data analysis (Douban) book is quite simple. The basic content is involved, and it is clear. Finally, we talked about R as a plus.Difficulty level: very easy.2. Beer and diapers (Douban) are the most typical cases.Difficulty level: very easy.3. The beauty of data (Douban) An introductory

: Network Disk DownloadFirst, the content of the book is a foreign data structure and algorithm analysis of the classic textbook, using the excellent Java programming language as the implementation tool to discuss the data structure (the method of organizing a large number of data