https://github.com/vipul2001/time-series-prediction-arima-and-prophet

https://github.com/vipul2001/time-series-prediction-arima-and-prophet

Last synced: 2 months ago
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• Host: GitHub
• URL: https://github.com/vipul2001/time-series-prediction-arima-and-prophet
• Owner: vipul2001
• Created: 2019-11-24T12:39:04.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-11-24T13:05:10.000Z (over 5 years ago)
• Last Synced: 2025-01-17T06:44:46.258Z (4 months ago)
• Language: Jupyter Notebook
• Size: 1.44 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Time-Series-Prediction-ARIMA-and-PROPHET

A time series is a sequence where a metric is recorded over regular time intervals.

Depending on the frequency, a time series can be of yearly (ex: annual budget), quarterly (ex: expenses), monthly (ex: air traffic), weekly (ex: sales qty), daily (ex: weather), hourly (ex: stocks price), minutes (ex: inbound calls in a call canter) and even seconds wise (ex: web traffic).

## Furniture Sales Vs Date

![graph](furniture_vs_date.png)

## Furniture data Decomposition

![graph](furniture_decomposition.png)

## ARIMA Model Daignostics for Furniture Sales

![graph](ARIMA_daignostics.png)

## Observed vs one step ahead Forecast plots

![graph](observed.png)

## Forecast furniture sale using ARIMA

![](future_sales_furniture.png)

## Sales Furniture vs Office Supplies

![graph](sales_furniture_vs_office.png)

## PROPHET Given Furniture Sales

![graph](PROPHET_furniture.png)

## PROPHET Given Office Sales

![graph](PROPHET_office.png)

## Furniture vs. Office Supplies Sales Trend

![graph](trend_in_supplies.png)

## Furniture vs. Office Supplies Estimate

![graph](PROPHET_estimates.png)