Welcome to my python_projects repository! This repository showcases various projects and exercises completed during different Data Science courses. Each project is organized in its own directory by topic and includes Jupyter Notebooks with all the necessary code and explanations.
This repository contains a collection of Python projects developed during Data Science courses. The projects cover a wide range of topics and complexity levels, from basic scripts to advanced applications, all documented in Jupyter Notebooks.
The repository is organized as follows:
/python_projects
|-- /Pandas
| |-- boxplot.ipynb
| |-- cleaning_duplicate.ipynb
| |-- combining_dataframes.ipynb
| |-- dataframe.ipynb
| |-- groupby.ipynb
| |-- index.ipynb
| |-- limpeza_duplicata.ipynb
| |-- melt.ipynb
| |-- merge_dataframe.ipynb
| |-- missing_values.ipynb
| |-- new_column.ipynb
| |-- open_file.ipynb
| |-- plot_graf.ipynb
| |-- reshaping_data.ipynb
| |-- selection_data.ipynb
| |-- sort_data.ipynb
| |-- sort_data.ipynb
| |-- summarying_data.ipynb
|-- /TensorFlow
| |-- Project1_ Celsius and Fahrenheit.ipynb
| |-- Project2_ Forecasting of revenue (ice creams).ipynb
| |-- Project3_Prediction of rent bike.ipynb
| |-- Project4_ House Sales Prediction.ipynb
| |-- Project5_ Sentiment Analysis.ipynb
| |-- Project6_ Diabetes Classification.ipynb
| |-- Project7_ CNN classifier.ipynb
| |-- Project8_Traffic sign classification.ipynb
| |-- Project9__Object_Classification.ipynb
| |-- Project10_ Transfer learning classifier cat and dogs.ipynb
| |-- Project11__Transfer_Learning_to_object_identification.ipynb
| |-- Project12_Remove_noise_from_images(autoencoders).ipynb
| |-- Project13_ Compress Images.ipynb
| |-- Project14_ Deep_Dream.ipynb
| |-- Project15__Image_Generation_(GAN).ipynb
| |-- Project16__Text_Generation.ipynb
|-- .gitignore
|-- LICENSE
|-- README.md
To run the projects locally, follow these steps:
-
Clone the repository:
git clone https://github.com/eduardoafonso1089/python_projects.git
-
Navigate to the project directory you want to explore:
cd python_projects/Pandas -
(Optional) Create and activate a virtual environment:
python -m venv env source env/bin/activate # On Windows, use `env\Scripts�ctivate`
-
Install the project dependencies (if there is a
requirements.txtfile):pip install -r requirements.txt
To run the Jupyter Notebooks of a project, navigate to the project directory and start Jupyter Notebook. For example:
cd python_projects/Pandas
jupyter notebookOpen the desired .ipynb file in Jupyter Notebook to explore and execute the code.
- boxplot.ipynb: Creating box plots.
- cleaning_duplicate.ipynb: Cleaning duplicates.
- combining_dataframes.ipynb: Combining dataframes.
- dataframe.ipynb: DataFrame basics.
- groupby.ipynb: Using groupby function.
- index.ipynb: Indexing data.
- melt.ipynb: Using melt function.
- merge_dataframe.ipynb: Merging dataframes.
- missing_values.ipynb: Handling missing values.
- multi_index.ipynb: Working with multi-index.
- new_column.ipynb: Adding new columns.
- open_file.ipynb: Opening files.
- plot_graf.ipynb: Plotting graphs.
- reshaping_data.ipynb: Reshaping data.
- selection_data.ipynb: Selecting data.
- sort_data.ipynb: Sorting data.
- stack_unstack.ipynb: Stacking and unstacking data.
- summarying_data.ipynb: Summarizing data.
- Project1_ Celsius and Fahrenheit.ipynb: Converting Celsius to Fahrenheit.
- Project2_ Forecasting of revenue (ice creams).ipynb: Forecasting revenues from an ice Cream store.
Contributions are welcome! Feel free to open issues and submit pull requests. To contribute:
- Fork the repository
- Create a branch for your feature (
git checkout -b feature/MyFeature) - Commit your changes (
git commit -m 'Add MyFeature') - Push to the branch (
git push origin feature/MyFeature) - Open a Pull Request
This project is licensed under the Unlicense License - see the LICENSE file for details.