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Based on my own experience, I think this roadmap will answer all the questions of how to become a data analyst from zero, which technologies and programming languages are better to know, what kind of soft skills do we need, how do I start my professional career in this field.
This is an analysis made on a superstore to understand why they had been making losses over a four year period, yet it had accounts on a substantial amount of sales over the same year period.
The IPL EDA (Exploratory Data Analysis) was conducted, revealing valuable insights. The analysis focused on various aspects such as player performance, team statistics, and match outcomes. Key findings include trends in run-scoring, top performers, and team dynamics. The EDA offers actionable insights for teams and fans to make data-driven decision
Project description. I developed a weekly credit card dashboard for real-time insights using Excel, SQL, and Power BI. The project included data cleaning, database creation, and visualization. Key insights included identifying top-performing cards and analyzing revenue factors. This demonstrates my proficiency in these tools for accurate analysis.
This Repository consist of all the Project Task with total of eight tasks that were assigned to me on a weekly basis as part of Data Analyst Internship at Yoshops.com
create data visualizations using PandasAI within a Google Colab environment. It showcases the power of combining pandas for data manipulation with AI-assisted visualization techniques.
Este repositorio contiene un proyecto de Machine Learning para predecir números de un juego utilizando árboles de decisión. Incluye un script principal (Lottery.py) para cargar datos, entrenar el modelo y hacer predicciones. Se proporciona un archivo de datos (num.csv) como entrada para el modelo.