Category: 1 SPL&Code

An antivirus software company’s products are sold on a time-based purchase basis, and users must continuously renew their”license keys”to continue using the software.”License keys” are divided into six-month authorization, one-year authorization, and lifetime authorization. The details are as follows: ID Key Type TermOfValidity Price 1 Six months 6 months 20 2 One Year 12 months 36 3 Unlimited Infinity 500 The following is the sales record table AVwareSales.txt of the company in the first few years after implementing this sales mode: If the customer’s authorization expires without renewing the authorization, the software will be discontinued and the user will no

There is a restaurant that can accommodate 1000 people. They number the seats in order and record them in a database table. After each guest sits down, the waiter will mark it in the seat table. When the guest leaves, this mark will be deleted. At a certain moment, the table is as follows: Due to the frequent occurrence of multiple guests sitting together in consecutive seats, the restaurant requires a synchronized “free seat area table” to facilitate the search for such consecutive seats. This table is used to record which sections of available seats are currently available and the

A certain enterprise’s finance department needs to calculate employee salaries and export the data to the bank. The calculation of salaries first needs to refer to the employee’s absenteeism rate and job performance. The specific rules are: Basic salary * (1- absenteeism rate + performance) Then pay personal income tax. The calculation method for personal income tax is to subtract the tax-free portion of 2000 USD from the income salary, and the remaining portion is calculated by the excess accumulation method, that is, segmented taxation. The tax rate for each segment is shown in the following table: Levels Containing tax

The following is the competition data of a certain Olympic Games. Country Table Country.txt: The athlete table Athlete.txt records the country to which each athlete belongs: The Match result table MatchResult.txt records all the results of the competition: Please list the gold medal standings for this Olympic Game, including the number of gold, silver, and bronze medals from each country, sorted by the number of gold medals, and provide rankings, taking into account the tie situation. As long as the country field in the athlete table is replaced with the record in the country table, and the athlete field in

Prepare simulated data for testing a sales management system. Request to generate 4 tables, with the following data requirements: Salesperson table, requires 50 salespersons in 5 regions: NorthChina, SouthChina, CentralChina, Southwest, Northwest; 4 types of educational backgrounds: Senior High School, Associate Degree, Bachelor, Master. The table structure is as follows: The client table requires 200 client data, with the following structure: Product table, requiring simulation of 30 types of products, with the following structure: Sales contract table, requiring simulation of 10000 sales records, distributed over a period of one year in 2024: There are two key issues that need to

Grouping is a common structured data calculation, with corresponding statements and functions available in both SQL and Python. However, these languages are far less powerful than the grouping operations offered by esProc SPL. Ordinary grouping often involves aggregation. For example, to calculate the number of employees for each department, the SQL code would be: Of course, SPL also supports such basic grouping and aggregation operations: It’s similar to SQL. In addition, SPL offers richer grouping operations. Below are two scenarios: 1. Grouped subset We are sometimes interested not only in grouped aggregate values, but also in the detailed data contained

esProc uses simple SQL queries on structured text files Structured text files refer to TXT files separated by tabs or CSV files separated by commas, which can be seen as data tables. Using simple SQL of esProc can easily operate such files, avoiding the hassle of importing into databases. This article uses text files as an example, but it also applies to Excel files, assuming that the first row of the file is the title. A B 1 $select * from scores.txt where // filter 2 $select avg(Chinese),max(Math),sum(English) from scores.txt // aggregation 3 $select *,English+Chinese+Math as total_score from scores.txt //

Conventional operations of esProc SPL on structured text files Structured text files refer to TXT files separated by tabs or CSV files separated by commas, which can be seen as data tables. Using esProc SPL makes it easy to perform common SQL-like operations on such files. Assuming that the first row of the file is the field title. A B 1 =T(“scores.txt”) 2 =A1.select(CLASS==2) // filter 3 =A1.avg(Chinese) 4 =A1.max(Math) 5 =A1.sum(English) 6 =A1.derive(English+Chinese+Math:total_score) // derive a total_score column 7 =A1.derive(if(Chinese>=90:”A”,Chinese>=80:”B”,Chinese>=60:”C”;”D”):Chinese_evaluation) // evaluate Chinese score 8 =A1.sort(English) 9 =A1.sort(CLASS,-Math) 10 =A1.groups(CLASS;min(English),max(Chinese),avg(Math)) 11 =A1.groups(CLASS;avg(English):avg_En).select(avg_En<85) 12 =A1.top(-3;English) // Top 3 high English

Correlation analysis is a commonly used method in data analysis and mining. By analyzing the relationships between the feature and target variables, it helps identify influential factors in business operations, enabling the prediction of future business trends. The relationships between two variables can be described as follows: (1) Completely positive linear correlation: A value increases as another value increases, and their relationship perfectly falls on a straight line with a slope greater than 0. (2) Completely negative linear correlation: A value decreases as another value increases, and their relationship perfectly falls on a straight line with a slope less than

The following is the LeaveRecords table for employee leave records of a certain company in 2009. The start and end dates of each employee’s leave are recorded: The following table is a detailed information table of employees: Please identify employees who have taken leave for more than 2 days for 3 consecutive times during this year. Firstly, calculate the leave time for each record in the leave table, and then use cross row calculation to find the situation where the leave time for the three consecutive records is greater than 2 days. A 1 =T(“LeaveRecords.txt”) 2 =T(“Employees.txt”).keys(ID) 3 =A1.group(Employee;~.(EndDate-StartDate):Length) 4