The Automated EDA tool within this repository simplifies the exploratory data analysis process:
- Imports libraries and reads data from CSV files into DataFrames.
- Utilizes a
maximize_attractions
function to find the maximum number of attractions visitable within a budget. - Uses a 2D table (
dp
) to store maximum attractions for each state (city and budget combination). - Utilizes backtracking to find selected attractions based on the filled
dp
table. - Provides a
get_recommendations
function for retrieving recommended cities based on user input (name, budget, and number of cities). - Displays recommended cities and a merged DataFrame.
This project was built following a tutorial by FreeCodeCamp.org
.
The mini-projects folder contains four Python mini-projects:
Send emails using Python's built-in smtplib module. Specify the recipient's email address, subject, and message.
Slice an email address into its username and domain name.
Replace specific words in a text file. Specify the input file, output file, and the words you want to replace.
Display random fortunes.
Use the following keys to move the snake:
W - Up
S - Down
A - Left
D - Right
The objective is to eat the food (colored shapes) and grow without colliding with walls or the snake's own body.
- Randomly generated food colors and shapes.
- Score and high score tracking.
- Game resets upon collision.
- Increased snake speed as score increases.
This game requires the Pygame library.
Clone this repository or download the ZIP file and extract the contents to a directory of your choice.
Navigate to the directory containing the game files and run:
python snake.py
The classic Tic Tac Toe game implemented in Python:
- Built as a command-line game.
- Game logic implemented using Python's built-in data structures and control flow.
- Players input moves via the command line.
- Played on a 3x3 grid.
- Features a function to print the current game board, handle player moves, check for a win, and check for a tie.
The Dynamic Programming project imports libraries and reads data from CSV files into DataFrames. It includes a function to find the maximum number of attractions that can be visited within a budget using dynamic programming techniques.
Develop an Automated EDA (Exploratory Data Analysis) tool using Python:
- Simplifies EDA by automating data preprocessing and visualization.
- Supports various data formats: CSV, Excel, and SQL databases.
- Identifies column data types and performs appropriate preprocessing steps.
- Provides options for feature selection and dimensionality reduction.
- Generates comprehensive visualization dashboards for each column type.
- Utilizes Python libraries: Matplotlib, Seaborn, and Plotly for interactive visualizations.
- Offers a user-friendly command-line interface.
- Involves stages of designing, implementing, testing, and debugging.
To use these projects, simply clone the repository to your local machine and run the Python files using your favorite Python IDE or the command line. For the Snake Game, make sure you have the Pygame library installed on your machine.
Feel free to explore each project and provide any feedback or suggestions. Thank you for visiting my repository!