ASSESSMENT 3: VISUALIZING AND DATA DISTRIBUTION BY PYTHON-BASED GUI APPLICATIONS

 

Table of Contents

Introduction. 3

Task 1. 3

Task 2. 4

Task 3. 5

Task 4. 9

 

 

 

Introduction

The report illustrates use of tools and libraries in Python for data visualization and GUI application development. The goal is to show mastery of Matplotlib, Seaborn, Geopandas, and Tkinter. The report is structured around four main tasks: stock data analysis, data distribution analysis, geographic data manipulation, and writing an inventory control application. For example, task 1 consists of fetching stock prices from a CSV file and generating a line graph of the closing prices over time. In task 2, box plots are created using Seaborn to represent the distribution of data across multiple categories. In task 3, geographic data is handled using Geopandas and a choropleth map with features such as population density is created. In task 4 an inventory control application is developed based on Tkinter with facilities for login and password management, product entry, stock management, and data archiving. All tasks are accompanied with appropriate Python scripts, graphics, and their interpretations.

Task 1

Figure 1: Stock closing prices over time line plot

In task 1, a line graph is made for the closing price of a certain stock within a specific date range. A line graph aids in spotting price shifts. With the x-axis as time and the y-axis as the closing price of the stock, the main goal of identifying shifts in time periods is simpler. The plot is first created using Matplotlib, and then enhancements are added to the name of the title, labels of axes, and context of the graph to improve the plot description. In addition to other customizations, the lattice aids in distinguishing numbers during the plot. Further in case it is essential; the lines and markers can be altered. This specific visualization stands out due to its ability to clearly track the historical changes in the performance of stocks, while at the same time, seeking to find trends.

Task 2

Figure 2: Distribution of closing prices across categories box plot

For Task 2, a box plot with the Seaborn library is made to visualize the stock closing price distribution by category. Box plots are ideal for describing the spread of data which include the median, quartiles, and outliers if any. The box plot is improved by coloring it with specific hues to make it easier to understand. Titles are assigned to the axis, and other improvements like the color scheme used in the boxes is changed or the boxes are resized have been made to increase the readability and comprehensibility of the box plot.

 

 

Task 3

(a)

Figure 3: Create shapefile using Geopandas library

This diagram demonstrates the process of forming a shapefile from geographic data using the Geopandas library in Python. Shapefiles are one of the most popular methods for representing geographic entities, both spatially and in terms of descriptive data. For this activity, the shapefile defines the area of interest as the country or region. The figure also describes the relevant procedures of data loading, shapefile creation, and further steps necessary for geographic representation purposes within the system.

Figure 4: Geographic boundaries of country regions plot

The figure provides a depiction of the countries or regions geographic boundaries made in Geopandas. The plot displays the outline of countries or regions which helps in visualizing the spatial distribution of the area. The borders shown are obtained from a shapefile, thus ensuring the geographic representation is bound to the actual locations of each region. Such representations are important as far as spatial data is concerned and also understanding the inter-relationships between geographic territories. It is useful as a backdrop for more sophisticated geographic illustrations like choropleth representation of statistics or analyzing the population density of a region enabling better insight into the data within the regional or global sphere.

 

(b)

Figure 5: Choropleth map (population distribution)

In subsection (b), the work entails that a choropleth map be constructed. A choropleth map serves the unique purpose of showing attributes such as population density or GDP by coloring regions based on their values. Variances in value are easier to analyze in the map with the aid of the color scale which distinguishes areas with higher values from those with lower values. The added features of the custom color scheme and the legend further increase the clarity of the map.

(c)

Figure 6: Customized choropleth map (population distribution)

This customized map displays a choropleth representation of the population distribution over several areas of interest. Changes in the maps colors have been made in order to clearly distinguish between the regions of high and low population density. Customization includes modifications of the populations color gradient and legend as well as outlining of each population region. The custom map improves clarity and comparison between regions at a glance. The customized map enables users to analyze the patterns of population distribution which is important for demographic analysis, urban planning, or targeted strategic planning for specific areas.

 

 

 

 

Task 4

1.

Figure 7: User authentication

The inventory system developed in Tkinter contains a login screen as shown is the figure above. The system requests the entry of a username and password. The authentication system in place ensures that bogus users will not be able to access the inventory information which ensures some sort of system access control. Such a surveilling mechanism assists in protecting delicate inventory data and also prevents unwanted access or control by unauthorized users in the inventory system.

 

 

 

2.

Figure 8: Add product

This figure illustrates the screen corresponding to the addition of new products into the inventory system. Users are able to enter product name, quantity, price, and categorize the item. Upon entering the details of the product, it is stored in the database, consequently replenishing the inventory. This capability functions to maintain accuracy within the inventory system and helps users in the effective tracking and management of products within the system.

 

 

 

 

 

 

 

3.

Figure 9: Stock tracking (record purchase)

This figure demonstrates tracking stock feature which permits recording purchases in the inventory system. The stock quantity is automatically updated upon purchase. This ensures proper inventory level tracking and provides support for stock management in real-time. Additionally, the feature also sets off alerts when a products stock level goes below the defined level to aid in stock replenishment.

 

4.

Figure 10: Search and filter

This figure depicts the search and filter option in the inventory management system. Users can search for products by name, category, or even a specific price range. The filter option narrows down searches to make searching for specific products in the system easier. This capability improves the management of inventory as users can locate and manage products faster without scrolling through the full list of inventories.

 

5.

Figure 11: Sales and reporting

This figure depicts functions of sales and reporting in an inventory system. Users have the option of recording sales transactions which can then be stored in the system. Reports generated by the system provide sales summary, the most sold products, and revenue analysis. The reports are useful for assessing the business performance for knowing useful information, and discovering patterns in product sales, which will help in improving the business in terms of the inventory and pricing policy.

 

6.

Figure 12: Check low stock

In this figure, the systems low stock alert feature is demonstrated in context with the inventory system. The system automatically notifies the user when a products stock level falls below a certain threshold. Keeps tabs on products so that they can be reordered in a timely manner. For that reason, there are always products available for sale which enables seamless operations for business. This feature is extremely important for keeping quantities of stock levels within the desired range.

 

Figure 13: Check pending orders

This image illustrates the Check Pending Orders feature of the system that shows the balance between orders waiting for shipment and those that have already been shipped. This feature enables users to view pending orders together with pertinent details like customer name, order date, and product details. This property aids in ensuring that no orders are forgotten, helps in monitoring workflows, and clarifies the volume of tasks that remain to be accomplished. The feature assists the inventory system in remaining orderly so that customer orders are processed promptly as backlog can be avoided. This has an impact on customer relations, business operations and business efficiency.

 

 

 

7.

Figure 14: Data backup and restore

The figure shows the "Data Backup and Restore" option of the inventory management system. The backup feature enables users to regularly backup the inventory database to protect it from data loss due to system failures or other unpredictable events. Users can restore data to a specific backup in case of data loss or corruption to mitigate the risk of permanent loss of critical information. Such an enhancement allows for increased security and reliability pertaining to sensitive data storage within the inventory system; thereby helping reduce system downtime. Maintaining operational efficiency while safeguarding inventory information is achieved through this advanced feature.