Pandas Activity - Iris Base

Report Bug · Request Feature

Table of Contents

1. About The Project
   • Built With
2. Usage
3. Getting Started
   • Prerequisites
   • Installation
4. Contributing
5. Collaborators
6. License
7. Contact

About The Project

Statistics activity passed in the classroom using pandas with the iris database.

1 - download the iris base: csv_url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data ' col_names = ['Sepal_Length','Sepal_Width','Petal_Length','Petal_Width','Class'] iris = pd.read_csv(csv_url, names = col_names)

2 - Identify and Classify the Variables. 3 - Calculate the following measurements on the size of the sepals ( Sepal_Length) the average

• b) median
• c) fashion
• d) standard deviation
• e) overall amplitude
• f) coefficient of variation

4 - Separate the data by 'Class' and check:

• a) Which class has the largest petal size on average?
• b) which class has the smallest sepal width on average?
• c) rank each class in order of homogeneity

(back to top)

Built With

• 

(back to top)

Prerequisites

• Python
• Scipy
• Pandas

Getting Started

Installation

1. Clone the repo

   git clone https://github.com/HeitorLouzeiro/pandas-activity-iris-base.git

2. Access the project folder in terminal/cmd

   cd pandas-activity-iris-base

3. Create a virtualenv with Python 3.9.0.

   python -m venv venv

4. Activate virtualenv.

   • Ubunto

   source venv/bin/activate

   • MacOs

   source venv/bin/activate

   • Windows

    venv\scripts\activate

5. Install as dependencies.

    pip install -r requirements.txt

   • OBS. If you get an error installing a package, follow the instructions.

   • Install scipy

       pip install scipy

   • install pandas.

       pip install pandas

6. Run one of the questions below in the terminal.

     python main.py

(back to top)

See the open issues for a full list of proposed features (and known issues).

(back to top)

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/Improvements)
3. Commit your Changes (git commit -m 'Add my new Enhancements')
4. Push to the Branch (git push origin feature/Improvements)
5. Open a Pull Request

(back to top)

Collaborators

We thank the following people who contributed to this project:

Heitor Louzeiro

(back to top)

License

Distributed under the MIT License. See LICENSE for more information.

(back to top)

Contact

Project Link: https://github.com/HeitorLouzeiro/pandas-activity-iris-base

(back to top)