Hello friends and welcome to my article in this magnificent lesson, in the SLC: S21/W3 I would outrightly perform my duties immediately.
I harnessed an advanced employee record management system using python data class. Program created had updating, adding, displaying employee information, which supports calculations of performance score, identifying top performers. Here is the code.
Code
Interpretation:
employee data class contains Employee name, ID, salary, position performance.
Average_score helps calculate employee average score performance.
Employment record class: manages variety of employees providing approach to update, beautify, identify information and calculating scores. Classes help display employees with array of their average_score performance.
Program is shared using NumPy designed to scrutinize students grade. Program provides function that calculate average, identify top students, analyse subjects performance which is visibly seen.
Interpretation:
Structural array is structured bearing student_dtype to include student_ID name & grade for subjects as English, History, Mathematics. It helps calculate students average grade through averaging 4 grades with class name. Calculate average grades asides other classes to identify students with average grades in a specified threshold.
Implemented an inventory management system using named tuple a python program to highlight products, update quantities, generate low stock alert which is shown in the code. Program in code provides us with comprehensive inventory management system that can be further expanded with additional functionalities like product evaluation or product supplier trackers.
A program was created using NumPy structured to process customers order as demanded including several functions for calculating order total analyzing customers spending and frequently ordered products.
Interpretation; Order students array we define structural string order type with field for order_Id customer _name product quantity, order dare and price_per_unit To track pair of products ordered on the dame date by the same customers, display pairs ordered together more than once a frequently_ordered_together which uses counter is being used.
Implementation was done in depth weather data analysis using data class and NumPy Program includes functionalities for calculating averages, identifying trends and detecting abnormalities in data as observed.
Interpretation: Convert to NumPy Arrays where weather data is stored as a list of weather record instances. Convert to NumPy function then convert list into a structured NumPy Array for efficient numerical operations. Calculate averages compute temperature max humidity, total precipitation and average with special using functions of NumPy. Identify temperature threshold, find days where temperature below or above specified threshold is achieved.
Detecting trend makes use of np. diff to calculate the difference between consecutive values and detect the overall trend. Detecting anomalies also highlights sudden drop in specific temperature using nup diff a special threshold.
Cc;
@kouba01