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Selection of data viz jupyter notebooks using Seaborn and MatPlotLib

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A selection of data visualisation notebooks:

  1. EDA on Age Dataset: Drawing conclusions from a Kaggle dataset with 1.2 million rows on life, work, age and death. Conducted basic EDA, reduced the number of unique categories in columns, used Count Vectorizer to analyse text, cleaned text with nltk to develop word clouds, visualised results with barplots, histplots, catplots, scatterplots and summarised conclusions.

  2. Seaborn Basics: Exploring the tips and invoice dataset using catplot, histplot, pairplot, regplot, facetgrid

  3. MatPlotLib: Plotting points, functions, formatting, subplots, gridspec

  4. Oil and Gas Basic Analysis: Basic EDA and analysis of the Kaggle Oil and Gas dataset

Notebooks (2), (3) and (4) adapted from Le Wagon Data Science bootcamp.

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Selection of data viz jupyter notebooks using Seaborn and MatPlotLib

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