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In two separate Python scripts, I perform financial analysis of csv datasets. This analysis features two examples, each with a separate dataset, and each exploring different Python methods and data structures.

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Python for Finance: Methods / Data Structures

PyBank / PyRamen: Financial Analysis Examples

PyBankImage

In two separate Python scripts, I perform financial analysis of csv datasets. This analysis features two examples, each with a separate dataset, and each exploring different Python methods and data structures.

The two examples are as follows:

PyBank: where I utilize a Python script for analyzing the financial records of a fictional company.

PyRamen: The purpose of this code is to analyze a business’s financial performance by cross-referencing their sales data with internal product data to figure out revenues and costs for the year.

Live Deployed Page:

https://benjaminweymouth.github.io/PyBank-Python-Data-Structures-Analysis/

Selected Screenshots:

Financial Analysis in Python Examples: PyBank

This analysis is a Python script for analyzing the financial records of a fictional company.

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Financial Analysis in Python Examples: PyRamen

This script is mean to analyze a business’s financial performance by cross-referencing their sales data with internal product data to figure out revenues and costs for the year.

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It utilizes nested loops to iterate through the dataset

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And provides an analytical report at the concluding stage of the analysis:

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In two separate Python scripts, I perform financial analysis of csv datasets. This analysis features two examples, each with a separate dataset, and each exploring different Python methods and data structures.

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