tools for collecting, compressing, and using a space-efficient columnar data format based on a document model (bson) and designed for timeseries data.

High-level lib for reading and writing physiological data into mef file format using python wrapper pymef for meflib.

Get boundaries between recent timeframes

A backend-for-frontend REST API which gathers and serves prometheus metrics from other services.

The project aims to develop a mobile application using accelerometer data for time series analysis to detect heavy drinking patterns, prioritizing user privacy and data security. The goal is to provide insights into drinking habits, promote responsible consumption, and enable early intervention for alcohol-related harm.

Apply SARIMA model to predict the numbers of tourist visiting Brazil in the future 12 months

An EncoderTransformer Architecture developed from scratch using pytorch's neural network module as the base class. The developed model used for sentiment analysis and time series prediction tasks.

Cut the log file by time quickly by binary search

Import and export data into/from InfluxDB.

Capstone project for Galvanize Data Science Immersive Program

Revision Analysis Tool initiated by Eurostat

Forecasting footsteps in Walmart from previous years available timeseries data and predict on new years data.

example of a take-home data science problem. Covering pandas, time series, handing null values, and building a classification model

EDA performed on timeseries data and different plots to get insights from data visualizations

Exploring stability-drivers relationships with terrestrial and freshwater long-term community timeseries data

A custom CMS, built on CodeIgnitor3, for tracking energy generation and consumption in an off-grid house.

This is a time series project that seeks to predict sales of the Favourita company.

A Jupyter Notebook to demo the openseries package.

This notebook has the pourpose to show an easy approach to fill large gaps in time series, mantainign a certain veridicity and data validity. The approach consist in apply a forecasting in both sides of the gap, and combine the two prediction using interpolation.