Python-challenge

Python - "The one common language loved across all programmers !"

Background

This repository brings a python solution for real-life situations. The situations encompass financial, election, human resources, and linguistic research data. The financial data sourced under PyBank/Resources folder, the election data sourced under PyPoll/Resources folder, the human resource data sourced under PyBoss/Resources folder, and the research data sourced under PyParagraph/Resources folder.

The code's organized to analyze the data, and create an output file in the Analysis subfolder in each project.

Note : All the main codes are set up to the relative path to be auto-adjusted in your working directory, however, the path in the video below is just my directory for demonstration.

For example the relative directories looks as follows:

To import data_path=os.path.join('Resources', 'budget_data.csv')

To export Output output_file = os.path.join('Analysis', 'pyBank_output.txt')

Table of Contents

• PyBank
  • Resources
  • Main Code
  • Analysis output
• PyPoll
  • Resources
  • Main Code
  • Analysis output
• PyBoss
  • Resources
  • Main Code
  • Analysis output
• PyParagraph
  • Resources
  • Main Code
  • Analysis output

PyBank

In this challenge, a python script created to analyze the financial data of a company and give an output. The dataset budget data is composed of two columns: Date and Profit/Losses.

Image Source: https://globalcompliancepaneltraining.wordpress.com/

The main script analyzes, and create an output in PyBank Analysis sub-folder.

The code looks as follows:

The code compute the following tasks:

• The total number of months included in the dataset

• The net total amount of "Profit/Losses" over the entire period

• The average of the changes in "Profit/Losses" over the entire period

• The greatest increase in profits (date and amount) over the entire period

• The greatest decrease in losses (date and amount) over the entire period

The output looks as follows:

PyPoll

In this challenge, a python script created to modernize a vote-counting process of a small rural town. This script used election dataset, and it is composed of three columns: Voter ID, County, and Candidate.

Image Source https://www.thedp.com/staff/camille-rapay

The main script analyzes, and create an output in PyPoll Analysis sub-folder.

The code looks as follows:

The code compute the following tasks:

• The total number of votes cast

• A complete list of candidates who received votes

• The percentage of votes each candidate won

• The total number of votes each candidate won

• The winner of the election based on popular vote.

The output looks as follows:

PyBoss

In this challenge, a python script created to convert older employee's data into the new format. The dataset generated from a Tuna 2.0 company, a world-changing snack food based on canned tuna fish. A new format is needed because the company recently decided to purchase a new HR system, and this new system requires employee records to be stored completely differently.

The main script analyzes, and create the new format as an output in PyBoss Analysis sub-folder.

The code looks as follows:

The code compute the following tasks:

• The Name column should be split into separate First Name and Last Name columns.

• The DOB data should be re-written into MM/DD/YYYY format.

• The SSN data should be re-written such that the first five numbers are hidden from view.

• The State data should be re-written as simple two-letter abbreviations.

Before it looks as follows:

After the output looks as follows:

PyParagraph

In this challenge, a python script created to automate and assess the complexity of the passage used for a linguistic research program. The passage is originated from the sophomoric Twilight novel to the nauseatingly high-minded article. You can find the passages passages in the resources folder.

The main script analyzes, and create a text output in pyParagraph Analysis sub-folder.

The code looks as follows:

The code compute the following tasks:

• Import a text file filled with a paragraph of your choosing.

• Count approximate word

• Count approximate sentence

• Count approximate letter (per word)

• Average sentence length (in words)

The output looks as follows:

The passage output looks as follows:

This Code is compiled and written for the Python class Homework in the Data Analytics Bootcamp class given by-Trilogy Education Services at the University of Toronto, continuing studies. The code used learning resources from the class.

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