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basic-plotly-charts

Big Mart Sales Analysis Using Plotly

china_electricity_consumption

crude-oil-production-forecast

How to Use Facebook’s Prophet library to Forecast the Canadian Crude Oil Production?

dcf

A Step-by-step guide on how to build a sturdy discounted cash flow model to calculate NPV, IRR, Payback Period and Multiple Invested Capital (MOIC) using Python.

decision-trees-for-ml

Building Decision Trees From Scratch In Python

forecast

medium

Scraping Medium.com

natural_gas_production

In this example, we will try to adopt a pure data-based approach to forecast Canada’s natural gas production using Facebook’s Prophet library. The idea of this post is to use a univariate time-series dataset and produce a best-fit model that allows us to confidently predict future production. We will be using the model to forecast the production for the next 10 years i.e. until 2030.

plotly

Basic Plotly visualizations for the purpose of data analysis

sarima_example

This model is built to show the functionality of SARIMA model using Python.

sarimavsprophet

testingprophetsarima

I will try to forecast the U.S. consumer price index i.e. average monthly change in the price for goods and services paid by urban consumers between any two time periods. It can also represent the buying habits of urban consumers I will be using Prophet and SARIMA models to accomplish this task.

time_series_dataset

time_series_datasets

web-scraping

Web scraping examples

xgboost

XGBoost Example in Python