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Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Home Page: https://pandas.pydata.org

License: BSD 3-Clause "New" or "Revised" License

Shell 0.07% Python 90.19% C 1.77% XSLT 0.01% CSS 0.01% HTML 2.18% Smarty 0.04% Batchfile 0.01% Cython 5.72% Dockerfile 0.03%

pandas's Introduction

Header

A Data Scientist and I love to be

data

srikanthdongalajsr

Bio:

Fuelled by an unwavering passion for innovation armed with a Masters in Data Science. I am passionately dedicated to advancing the frontiers of Data Science through groundbreaking solutions

  • 😄 Pronouns He/Him

  • 🔭 I’m currently working on Satellite Image Processing, Object Detection, Segmentation, Spatial LLM, RAG

  • 🌱 I’m currently learning Advanced AI

  • 💬 Ask me about Python, Data Analysis, Machine Learning, CV, Deep Learning and Generative Artificial Intelligence

  • 📫 How to reach me [email protected]

  • 📑 To read my blogs Hashnode, Medium

  • 📄 To know about my experiences Check my Resume

Connect with me:

https://www.linkedin.com/in/srikanth-dongala/ https://www.kaggle.com/srikanthdongala

Languages and Tools:

mysql opencv pandas python scikit_learn seaborn tensorflow

srikanthdongalajsr

 srikanthdongalajsr

pandas's People

Contributors

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