• A file selection dialog box opens allowing browsing to/selection of your desired CSV file.
• CSV is imported and cleaned.
• All serial numbers are printed to the terminal.
• All unique model types along with their total number of machines are printed to the terminal.
• A visualization displays a bar graph of the model data by total number of each machine.

Code and Resources Used

• Python 3.9
  • Pandas
  • Matplotlib
  • Easygui
  • Pyperclip
• From the command line, input pip install -r requirements.txt from within the project directory to add required modules.

This program begins by simply opening a (system agnostic) file selection dialog box. Upon navigation to and selection of the proper DT_Export.csv file, the data is extracted to a Pandas dataframe. All serials are printed to the terminal and automatically copied to the (system agnostic) operating system's clipboard. This print serves as a hard method against which to check your serials upon pasting. All models received on the purchase order CSV are then printed to the terminal as well as their totals. Finally, a visualization of total models is displayed.

Two common occurances at my workplace are; the need for every serial number from a certain purchase order, and a quick breakdown of machines received.

• Often batches of machines will need their statuses shifted, or designated to another warehouse. This is done through a tool on the company's website, however extracting the serials in the past had to be done manually. This is time consuming.
• Each purchase order is an investment. Many orders do not exactly match the numbers and types of machines planned during purchasing. The company owners/operators are eager for clear data as fast as possible.

GNU GENERAL PUBLIC LICENSE