AabidMK/CricketIQ_Infosys_Internship_Feb2025
Apr 2025 – Apr 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data AnalysisExploratory Data AnalysisJupyter NotebookPandas
arpitha-gaddam
PROFILE
Arpitha-gaddam
Arpitha Reddy developed a data exploration and cleaning setup for cricket datasets in the CricketIQ_Infosys_Internship_Feb2025 repository. She created an exploratory data analysis notebook using Jupyter Notebook and Python, focusing on deliveries.csv and matches.csv files. Her approach included loading data, generating descriptive statistics, and implementing null value checks to identify and address missing values. Arpitha added data cleaning steps and introduced a placeholder matches.csv file to support pipeline prototyping. By leveraging Pandas for data manipulation, she established a reproducible baseline that enables reliable analytics and faster iteration, laying the groundwork for future cricket data insights and decision support.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
2,207
Activity Months1
Your Network
5 peopleShared Repositories
5
Work History
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 focused on making CricketIQ analytics-ready by delivering a data exploration and cleaning setup for cricket datasets. Implemented an exploratory data analysis notebook (EDA.ipynb), data loading, descriptive statistics, and null value checks for deliveries.csv and matches.csv. Added data cleaning steps to address missing values and included a placeholder matches.csv to enable pipeline prototyping. All changes were committed to the CricketIQ_Infosys_Internship_Feb2025 repository (Add files via upload). This work establishes a solid foundation for reliable analytics, faster iteration, and better decision support for cricket data insights.
1 Commits • 1 Features
Apr 1, 2025April 2025 focused on making CricketIQ analytics-ready by delivering a data exploration and cleaning setup for cricket datasets. Implemented an exploratory data analysis notebook (EDA.ipynb), data loading, descriptive statistics, and null value checks for deliveries.csv and matches.csv. Added data cleaning steps to address missing values and included a placeholder matches.csv to enable pipeline prototyping. All changes were committed to the CricketIQ_Infosys_Internship_Feb2025 repository (Add files via upload). This work establishes a solid foundation for reliable analytics, faster iteration, and better decision support for cricket data insights.
April 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture60.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data AnalysisExploratory Data AnalysisJupyter NotebookPandas
Repositories Contributed To
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