Example of continued sales analysis in that region
> Mygoods
1 2 3 4 5 6 7 8 9 10 11 12
1 1200 3210 123 1111 688 2110 1123 6894 1470 1071 2250 1241
2 2222 1500 3200 1580 5562 58411860 981 658 789 1020 1120
3 2144 2243 134 235 486 985 235 1020 558 995 886 398
4 1820 1588 5440 470 1500 720 845 476 984 745 368 872
We can see that the sales volume in Region 1 and Region 2 is the best.
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Use python for data analysis and python for data analysis
1: How to parse json data
Import json, OS, syscurrent_dir = OS. path. abspath (". ") filename = [file for file in OS. listdir (current_dir) if ". txt "in filepath must be included in the current directory. The
Data analysis and presentation-Implementation of hand-drawn images and hand-drawn Data AnalysisNumPy database entry NumPy Data Access and function example: the array of the image indicates the RGB color mode of the image.
Generally, an image uses the RGB color mode, that is, the color of each pixel is composed of red (
also a personnel information table, but also a record of some people's properties, of course, it will not be the same as the sales personnel recorded information, but will contain the same set of attributes, such as: Birthday, age, annual income and so on, we have to do is from the table to find the people who will buy bicycles.(2) vs Data mining tools, installation database configuration good service, this all understand, there is nothing to say, bu
Clustering is the process of dividing a dataset into subsets, each of which is called a cluster (Cluster), and clustering makes the objects in the cluster highly similar, but unlike the objects in other clusters, the set of clusters generated by clustering is called a cluster. On the same data set, different clustering algorithms may produce different clusters.
Cluster analysis is used to gain insight into
Hello everyone, I am the Phantom of the Rain. For website data analysis, in addition to the above mentioned keyword ranking, content quality, chain quality of these three aspects, I believe that we are most concerned about the flow of the site, the site's traffic involved we need to pay attention to many aspects, through these different dimensions of the data
WireShark data packet analysis data encapsulation, wireshark data packetWireShark packet analysis data encapsulation
Data Encapsulation refers to the process of encapsulating a Protocol
pl1936-Big Data Fast Data mining platform RapidMiner data analysisEssay background: In a lot of times, many of the early friends will ask me: I am from other languages transferred to the development of the program, there are some basic information to learn from us, your frame feel too big, I hope to have a gradual tutorial or video to learn just fine. For learnin
1.R language important data set analysis needs to be collated and analyzed to clarify the concept of?In the previous section, we talked about the R language mapping, and this section is about how to analyze the data when you get a data set, the first step in the analysis, an
Statistical analysis of data is divided into descriptive statistical analysis and statistical inference, the former is also known as exploratory statistical analysis, which is to explore the main distribution characteristics of data by drawing statistical graphs, compiling s
article describes the Microsoft Linear regression analysis algorithm, the principle and the Microsoft Neural Network analysis algorithm, just like the focus is not the same, the Microsoft Neural Network algorithm is based on a certain purpose, using the existing data for "probing" analysis, focusing on
Tags: des http io ar os using for SP filesData mining Algorithm (analysis services–) Data mining algorithm are a set of heuristics and calculations that creates a data mining mOdel from data. "Xml:space=" preserve "> Data mining Algorithms" is a set of heuristics and calcula
height (x1), Weight (x2), Bust (x3) and sitting height (x4). Specific as follows:studentResults such as:After analysis of four indicators, 4 components were given, the importance of which was 0.887932, 0.08231182, 0.02393843, 0.005817781, and the cumulative contribution was: 0.887932, 0.97024379,0.99418222 1.000000000 The aggregate of the various components is also shown above, the cumulative contribution of the visible ingredient 1 and component 2 h
Tags: article vs2008 reg knowledge View HTM new research will notObjective This article continues our Microsoft Mining Series algorithm Summary, the previous articles have been related to the main algorithm to do a detailed introduction, I for the convenience of display, specially organized a directory outline: Big Data era: Easy to learn Microsoft Data Mining algorithm summary serial, interested children s
Statement: This series of blogs is the "Data structure and algorithm analysis C + + description" Reading notes seriesReference Blog: Click to open linkThis article is the second chapter of the original book, the main content includes: The algorithm of time complexity analysis/algorithm optimization, the analysis of the
11.2 Correspondence AnalysisIn many cases, we are not only concerned with the row or column variables themselves, but the relationship between the row and column variables, which is not explained by the factor analysis method. 1970 French statistician J.p.benzenci proposed correspondence analysis, also called Association analysis, R-Q type factor
Cluster analysis divides objects into clusters according to their differences, clusters are collections of data objects, and cluster analysis makes objects in the same cluster similar to objects in other clusters. Similarity and dissimilarity (dissimilarity) are evaluated based on the attribute values of the data objec
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