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authoredJul 28, 2020
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‎README.md

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# 01. Jupyter Notebooks
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# **01. Jupyter Notebooks**
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### i) Sales Data Cleaning With Python
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### i) Data Visualization With Pandas, Seaborn & Matplotlib
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#### Project Goals
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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!
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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. [Click Here For Notebook File](https://github.com/Emon-ProCoder7/python_projects/blob/master/Visualization_kaggle.ipynb)
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### ii) Sales Data Cleaning With Python
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#### Project Goals
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Getting financial insights from data. Breaking up `daily_sales` in easy to understand lists `customers`, `sales`, and `threads_sold`. [Click Here For Notebook File](https://github.com/Emon-ProCoder7/python_projects/blob/master/Sales%20Data%20Cleaning.ipynb)
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### ii) A/B Test Analytics With Pandas
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### iii) A/B Test Analytics With Pandas
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#### Project Goals
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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.[Click Here For The Project](https://github.com/Emon-ProCoder7/python_projects/blob/master/A_B%20Test%20Analytics.ipynb)
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# 02. Python Scripts
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# **02. Python Scripts**
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### a) Python Script Recommending Cheapest Shipping Price
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## b) Object Oriented Programming (OOPs)
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## **b) Object Oriented Programming (OOPs)**
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#### Project Goals
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Creating automated business objects running a Restaurant Business Chain.

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