En este proyecto se verá métodos avanzados para manejar los datos faltantes de manera más eficiente
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Updated
Mar 31, 2024 - Jupyter Notebook
En este proyecto se verá métodos avanzados para manejar los datos faltantes de manera más eficiente
In this project, we created an 'expected goals' metric to help us assess a team's performance rather than the actual number of goals scored. We merged this metric with the calculation of a team's offensive and defensive ratings, which are updated after every game, to create a classification model that predicts the outcome of future matches, as w…
machine learning à partir du dataset titanic
Exploring 118 wells of 1 MM+ rows and 29 columns of wireline petrophysical data using the Pandas library. Analysed & Visualised wireline logs petrophysical dataset using - Pandas, Numpy, Matplotlib, Plotly & seaborn libraries Discovered insights of wireline logs quality & interpretation (missing data and imbalance class
EDA for more than 30K game ratings collected from [IGDB API](https://api-docs.igdb.com/#about) using [igdb-api-v4 for python](https://github.com/twitchtv/igdb-api-python). This notebook explores any common trends for games that have ratings from igdb and external critics.
Exploratory and explanatory analysis of a small, generated dataset. pandas + missingno + seaborn.
Exploratory Data Analysis and Data Cleaning on a Amazon E-Commerce Dataset
Analyzing of local and global temperature data and comparing the temperature trends with a residence to overall global temperature trends.
📈 Data Science Using Python
Este espaço é dedicado para treinar minhas habilidades em ciência de dados, concentrando-se principalmente no aproveitamento da biblioteca Pandas para manipulação e análise de dados.
Capstone _EDA_on Global terrorism data
OpenClassrooms Data Analyst 2022-2023 - Projet 9
Exploratory Data Analysis
OpenClassrooms Data Analyst 2022-2023 - Projet 5
A python script to convert any image to a MissingNo like sprite
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