/Descriptive-Statistic-of-Commodities-Price-in-Box-Plot

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Descriptive-Statistic-of-Commodities-Price-in-Box-Plot

I try to visualize adjustment price of Commodities which contains Gold, Silver, Platinum, Crude Oil, and Copper. Using Python libraries, such as : pandas, numpy, matplotlib, and seaborn, box plot could be created and with inherent descritive statistics.

  1. First of all, download daily historical data from yahoo finance from each Commodities stock for 5 years, from 25 April 2016-23 April 2021. And sort the data into 1 file excel.

Descriptive-Statistic-of-Commodities-Price-in-Box-Plot

  1. Extracting excel data into pandaframes: Test Image 1

  2. Define df

Test Image 2

  1. Using the command: import plotly.express as px you can see the descriptive analytics of each stock in that looks user friendly

Test Image 3