This project aims to analyze comments from an Instagram post exported to a CSV file to determine the winner of a giveaway competition. The primary goal is to identify the comment with the highest count.
result.csv: CSV file containing the exported comments from the Instagram post.psd.ipynb: Jupyter Notebook containing the Python code for analyzing comments.
- Ensure you have Python installed on your system.
- Install the required dependencies
- Run the Jupyter Notebook
psd.ipynbto execute the analysis code.
The analysis will identify the comment with the highest count, which can be considered the winner of the giveaway competition.
This project utilizes datasets containing information on all products sold by Bolapsd, including sizes and quantities sold. The data is cleaned to retain only relevant information. A linear regression model is trained based on this data to predict the sizes and respective quantities of T-shirts to restock.
inventory sales.csv: CSV file containing sales data including product information, sizes, and quantities sold.size model.ipynb: Jupyter Notebook containing the Python code for training the linear regression model and making predictions.
- Ensure you have Python installed on your system.
- Install the required dependencies
- Run the Jupyter Notebook
size model.ipynbto train the model and make predictions.
The trained linear regression model can predict the sizes and quantities of T-shirts to restock based on the desired restocking amount.