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An exploratory analysis and application of Bayes Theorem to the Olist Ecommerce dataset.

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Applying Bayes' theorem to Olist ecommerce data

An exploratory analysis and application of Bayes Theorem to the Olist Ecommerce dataset.

Libraries Required

Data Manipulation: Pandas, datetime

Data Visualization: Seaborn, Matplotlib

Roadmap

  • Olist Ecommerce Dataset

  • Merging datasets

  • Exploratory Data Analysis and Feature Engineering

  • Applying Bayes' theorem

  • Insights

Olist Ecommerce Dataset

The datasets utilized in this analysis are available at https://www.kaggle.com/datasets/olistbr/brazilian-ecommerce.

This is a real dataset, that has been anonymised, containing information of 100k orders made at multiple marketplaces in Brazil, from 2016 to 2018.

Find out more about Olist at www.olist.com

Merging the datasets

The data was divided in multiple datasets, for this analysis we will merge those datasets into one.

The steps performed for merging all the seven datasets are in the Merging Notebook.

Exploratory Data Analysis

Insights

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An exploratory analysis and application of Bayes Theorem to the Olist Ecommerce dataset.

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