https://github.com/yrohitha/eda-bio-diversity
Use Descriptive statistics and statistical inference to help ensure the survival of at-risk species
https://github.com/yrohitha/eda-bio-diversity
data-visualisation descriptive-statistics statistical-inference storyboarding
Last synced: 3 months ago
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Use Descriptive statistics and statistical inference to help ensure the survival of at-risk species
- Host: GitHub
- URL: https://github.com/yrohitha/eda-bio-diversity
- Owner: YRohitha
- Created: 2022-08-12T09:44:05.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-08-12T12:00:31.000Z (almost 3 years ago)
- Last Synced: 2023-09-10T12:21:09.399Z (almost 2 years ago)
- Topics: data-visualisation, descriptive-statistics, statistical-inference, storyboarding
- Language: Jupyter Notebook
- Homepage:
- Size: 444 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
## EDA-Bio-Diversity
**Ensure the survival of at-risk species, to maintain the level of biodiversity within their park**
* Understand characteristics about the species and their conservations status using Descriptive statistics
* Explore relationship between species and their relationship to the national parks via Statistical Inference
### Description
1. Project goals: Define the high-level objectives and set the intentions for this project.
2. Data: Luckily in this project, data is already provided but still needs to be checked if project goals can be met with the available data.
3. Analysis: Will have to be thought through, which include the methods and questions that are aligned with the project goals.
4. Evaluation: To build conclusions and findings from our analysis.
### Install Setup
This project requires **Python 2.7** and the following Python libraries installed:
- [numpy](http://www.numpy.org/)
- [pandas](http://pandas.pydata.org)
- [matplotlib](http://matplotlib.org/)
- [scikit-learn](http://scikit-learn.org/stable/)
- [datetime](https://docs.python.org/3/library/datetime.html)
- [seaborn](https://seaborn.pydata.org)
You will also need to have software installed to run and execute a [Jupyter Notebook](http://ipython.org/notebook.html)
If you do not have Python installed yet, it is highly recommended that you install the [Anaconda](http://continuum.io/downloads) distribution of Python, which already has the above packages and more included. Make sure that you select the Python 2.7 installer and not the Python 3.x installer.
### Code
Template code is provided in the notebook `eda-bio-diversity.ipynb`
[Jupyter Notebook](https://github.com/YRohitha/EDA-BioDiversity/tree/main/scripts/eda-bio-diversity.ipynb) file.
### Run
In a terminal or command window, navigate to the top-level project directory (that contains this README) and run one of the following commands:
```bash
jupyter notebook eda-bio-diversity.ipynb
```
or
```bash
ipython notebook eda-bio-diversity.ipynb
```
This will open the Jupyter Notebook software and project file in your web browser.
### Data
**Features**
#### species
The `species_info.csv` contains information on the different species in the National Parks. The columns in the data set include:
- **category** - The category of taxonomy for each species
- **scientific_name** - The scientific name of each species
- **common_names** - The common names of each species
- **conservation_status** - The species conservation status
#### observations
The `Observations.csv` contains information from recorded sightings of different species throughout the national parks in the past 7 days. The columns included are:
- **scientific_name** - The scientific name of each species
- **park_name** - The name of the national park
- **observations** - The number of observations in the past 7 days