The goal of this project is to eliminate the need for paper by digitizing the process of handling client passport information.
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Updated
Sep 3, 2024 - C#
The goal of this project is to eliminate the need for paper by digitizing the process of handling client passport information.
BlockPredict is a project that utilizes historical data from a blockchain network to predict future block rewards. It combines data fetching, preprocessing, machine learning, and visualization techniques to provide insights into the block reward dynamics of a blockchain.
Reference project using AWS Lambda and Scala for CSV processing and loading into DynamoDB
🇺🇸 Solution for importing and analyzing public Brazilian business data (CNPJ). 🇧🇷 Processamento de Dados CNPJ: Uma solução robusta e conteinerizada para importação e análise de dados empresariais brasileiros (CNPJ).
Command-line utility for processing semicolon-separated values (SCSV)
Java-based application for managing and processing climate and economic information for USA communities using a layered linked list structure. Features include CSV data import, efficient data management, and retrieval methods. Ideal for learning and applying OOP and linked lists.
This project is a Python tool for generating Ethereum addresses in batch and saving them as a CSV file.
A Python script for analyzing weather statistics from CSV files. This tool provides functionalities to compute minimum, maximum, and average values for a specified column, generate charts for visual analysis, and list raw data. Explore your weather data effortlessly!
Examines the progression of the gross revenue in the USA and the IMDB user score of movies which have won the Oscar in the category "Best Picture" and were released between 1986 and 2016.
This Python application analytically processes CSV data containing haunted site information, employing heatmap visualization techniques to discern the most paranormally active regions within the USA.
This bot is very useful to search books and download them in Telegram
Data-Splitter is a Python script designed to split a large CSV file containing data into three different formats: JSON, a database table, and another CSV file. The script ensures a random distribution of data across the three output formats based on custom-defined ratios.
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