data analysis for dummies

cats.labels #查看水平 (factor) cats.levels #区间计数 Pd.value_count (CATS) #自定义分区的标签 group_names=[' Youth ', ' Youngadult ', ' middleage ', ' Senior '] pd.cut (ages,bins,labels= Group_names) Split -digit Division DATA=NP.RANDOM.RANDN (1000) pd.qcut (data,4) #四分位数 #自定义分位数, including endpoint Pd.qcut (data,[ 0,0.3,0.5,0.9,1]) Exception Value #查看各个统计量 data.describe

The project is mainly aimed at the needs of chemical transfer, sales, receivables, procurement of three modules to carry out a comprehensive statistical analysis, the purpose is through the analysis of historical data, to find valuable information to assist leaders in decision-making, to give the salesman real-time reminders. This paper mainly analyzes the Receiv

DPC Usability Analysis and case study of Ali yun large data processing tools The cloud-collecting room (data Process Center, referred to as DPC) is a DW/BI tool solution based on Open Data processing services (ODPS). DPC provides a full link of easy-to-use data processing t

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

We know that the principal component analysis is a dimensionality reduction method, but it is essentially a matrix transformation process, the extracted principal component does not all have the actual meaning, and this meaning is often what we need, the next factor analysis can solve the problemFactor analysis can be regarded as the generalization of principal c

This example, through numpy analysis of stock price CSV file reading and writing CSV (comma-separated value, comma separated values) is a common file format, usually the database is the file is a CSV format, each field in the file corresponds to the columns in the database table. Here is a file in CSV format, this article is an example of this file data.Data structure as follows diagram Each data correspon

From the user level of the website, we divide users into different types based on the behavior characteristics of user access, because the user behavior is different, the behavior statistical indicators are different, and the analysis angle is different, therefore, if you want to classify users in detail, you can implement different classifications based on various rules from many perspectives. We have seen that some

Original: (original) Big Data era: a summary of knowledge points based on Microsoft Case Database Data Mining (Microsoft Decision Tree Analysis algorithm)With the advent of the big data age, the importance of data mining becomes apparent, and several simple

Analysis of recruitment data related to big data of pull hook netAudience: Job data for big data-related jobsObservation Time: 2016.3.28Data source: Pull Hook Net1. Purpose of analysisAt present, big data is a very hot topic, by m