https://github.com/suvoooo/cave-analysis

Time Series Analysis of Cave Data
https://github.com/suvoooo/cave-analysis

Last synced: about 1 month ago
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Time Series Analysis of Cave Data

• Host: GitHub
• URL: https://github.com/suvoooo/cave-analysis
• Owner: suvoooo
• Created: 2022-09-21T19:40:30.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-11-24T07:39:41.000Z (about 2 years ago)
• Last Synced: 2024-10-28T15:26:56.281Z (3 months ago)
• Language: Jupyter Notebook
• Size: 16.7 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Cave-Analysis

Time Series Analysis of Cave Data

### Libraries

- Python      `version: 3.7.15`

- Numpy       `version: 1.21.6`

- Scipy       `version: 1.7.3`

- Pandas      `version: 1.3.5`

- Seaborn     `version: 0.11.2`

- Matplotlib  `version: 3.2.2`

- Statsmodels `version: 0.12.2`

### Getting Started

#### Access Data from Data Folder

 - The file is in xlsx format. 

 - For our analysis purpose we have converted this into dataframe format. 

 - The steps are described in Cell 3 and 4 of the [Intro Notebook](https://github.com/suvoooo/Cave-Analysis/blob/main/Cave_Analysis_Intro.ipynb). 

 

#### Plots 

 - All the generalize plots (except core time series analysis) for studying dependencies of various parameters (eg. Dissolved O2 vs Sun Duration) can be easily produced just by following the steps in [Intro Notebook](https://github.com/suvoooo/Cave-Analysis/blob/main/Cave_Analysis_Intro.ipynb). 

 - For time-series analysis, checking data stability, data preparation for analysis and eventually several parameters for finding time series orders are studied. 

 - Use the steps freely for your own data and try various other parameters (usually this is done separately for checking parameter dependecy and reducing residuals from fit).