Time-Series-Forecasting

Time Series Forecasting using ARIMA

Dependencies

• pandas
• matplotlib
• statsmodel
• sklearn.metrics

Dataset

• Dataset was obtained from City of Cape Town's portal.
• It consists of hourly water consumption data over a period of 168 hours.

Usage

Directly run the python script .

About ARIMA

ARIMA stands for Auto Regressive Integrated Moving Average. ARIMA captures standard temporal structures in time series data. ARIMA model takes 3 parameters

• p = No fo lag terms in the observation.
• d = Degree of Differencing.
• q = No of terms included in Moving Average.

Data Distribution

Results

• Blue represents Actual values
• Red represents Predicted values

This project is done in contribution