Update README.md

Author: Emon-ProCoder7

README.md

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 ### i) Data Visualization With Pandas, Seaborn & Matplotlib
 
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+#### Project Goals:
 For this project I have explored data from the [Fifa World Cup](https://en.wikipedia.org/wiki/FIFA_World_Cup) from 1930-2014 to analyze trends and discover insights about the world’s game, fútbol!
 
 This Fifa World Cup data is from [Kaggle](https://www.kaggle.com/abecklas/fifa-world-cup). Kaggle is a platform for data science competitions that hosts many datasets online.
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 ### ii) Sales Data Cleaning With Python
 
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 Getting financial insights from data. Breaking up `daily_sales` in easy to understand lists `customers`, `sales`, and `threads_sold`.
 
 
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 ### iii) A/B Test Analytics With Pandas
 
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 **Shoefly.com** has two different versions of an ad, which they have placed in emails, as well as in banner ads on **Facebook, Twitter**, and **Google**. They want to know how the two ads are performing on each of the different platforms on each day of the week.
 
 
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 ### a) Python Script Recommending Cheapest Shipping Price
 
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 Sal runs the biggest shipping company in the tri-county area, Sal’s Shippers. Sal wants to make sure that every single one of his customers has the best, and most affordable experience shipping their packages. In this project, I’ll build a program that will take the weight of a package and determine the **cheapest way to ship** that package using Sal’s Shippers.
 
 Sal’s Shippers has several different options for a customer to ship their package. They have ground shipping, which is a small flat charge plus a rate based on the weight of the package. Premium ground shipping, which is a much higher flat charge, but I aren’t charged for weight. They recently also implemented drone shipping, which has no flat charge, but the rate based on weight is triple the rate of ground shipping. 
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 ## **b) Object Oriented Programming (OOPs)**
 
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 Creating automated business objects running a Restaurant Business Chain.
 
  - Creating Organised Menu System according to time of The Day.