Explore projects
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Исследовательский анализ данных. Project for E-commerce. Product analysis, cohort analysis, RFM analysis in Python.
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Various examples of some data analysis exercises.
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Calculation of covariance of cosmological maps in the BINGO radio telescope pipeline.
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Tracks and heatmaps using the GPS tracks.
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Data analysis:
🍔 Foods &🌍 Ecological ImpactUpdated -
Analysis of a spotify user's musical tastes using Spotify's API
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Study of the connections between DNA expression of Covid patients and the development of Acute Encephalopathy. Project carried out by the Neurology Department of UC San Francisco in collaboration with the Data Science department of UC Berkeley (2022).
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Prediction of Nobel Prize outcomes based on country data. Project done for an Applications in Data Analysis course (INDENG-242) for UC Berkeley (2022).
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This project contains the source files I used in a free-lance project for a book reseller.
Python environment setup SQL (mariadb) database configuration setup of a Python-mariadb connector Data enrichment with the seller's local currency value in time. Data analysis with Python [pandas, scikit-learn, matplotlib, seaborn] Brief interpretation of the data is present in the notebook.Updated -
Simulation set-ups and analysis scripts for the BINGO experiment
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Patrick Tapping / TRSpectrometer
GNU General Public License v3.0 or laterSoftware for running time-resolved spectrometers, plus viewing and analysis of time-resolved spectroscopy data.
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This jupyter notebook goes through how to use python in you data analysis. Mainly analysis of experiments, such as peak analysis and curve fitting.
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Humanities Data Analysis Book / HDA website
BSD Zero Clause LicenseRepository for the public website of the book Humanities Data Analysis: Case Studies with Python.
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Personal Jupyter Notebooks with Open Data.
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This work is focused on the prediction of customer departures in telecommunications through data analysis. Departures in telecommunications are a relatively common issue, and if potential customers were detected much earlier, their departure could be prevented in many cases. Our work's mission was to predict such customers' departures by using data analysis and by creating decision models. The eventual model will determine which customers are potentially risky and how big the risk is.
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Analisi di un dataset contenenti informazioni su diverse tipologie di vetro.
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