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Basketball Analytics using Python

𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐎𝐛𝐣𝐞𝐜𝐭𝐢𝐯𝐞: The aim was to analyze team performance data and recommend which teams Company X should approach for potential deals, given that some of the older teams are already contracted by competitors. 𝐒𝐭𝐞𝐩𝐬 𝐚𝐧𝐝 𝐓𝐚𝐬𝐤𝐬: 1️⃣ Data Cleaning and Preparation 2️⃣ Detailed EDA (Univariate, Bi-variate, Multivariate) to extract meaningful insights 3️⃣ Statistical analysis and performance reporting for optimal team selection 𝐓𝐨𝐨𝐥𝐬 𝐚𝐧𝐝 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐔𝐬𝐞𝐝: • Python • Pandas, Numpy, Matplotlib, Seaborn for data handling and visualization • Jupyter Notebook for an interactive and exploratory approach 𝐊𝐞𝐲 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠𝐬: • Data cleaning & merging • Data visualization using interactive plots • Exploratory Data Analysis (EDA) to uncover hidden insights like the best performing team, oldest team, teams with the highest and lowest scores,