Trending repositories for topic pandas
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may ...
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Python Data Science Handbook: full text in Jupyter Notebooks
人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-in...
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AW...
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
TuShare is a utility for crawling historical data of China stocks
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Download historical 13F filing data directly from the United States (U.S.) Securities Exchange Commission (SEC).
Open Source LeetCode for PySpark, Spark, Pandas and DBT/Snowflake
Más de 50 ejemplos de visualizaciones y análisis de datos en Matplotlib, Pandas, Seaborn, Plotly, Bokeh y Networkx
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
Lightweight and extensible compatibility layer between dataframe libraries!
🐍 Hand-picked awesome Python libraries and frameworks, organised by category
Buckaroo - the data wrangling assistant for pandas. Quickly explore dataframes, and run pandas commands via a GUI. Works inside the jupyter notebook.
ArcticDB is a high performance, serverless DataFrame database built for the Python Data Science ecosystem.
I am sharing my Journey of 66DaysofData into Data Analytics by participating in Ken Jee's #66daysofdata challenge
Exchange calendars to use with pandas for trading applications
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may ...
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-in...
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Python Data Science Handbook: full text in Jupyter Notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AW...
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
TuShare is a utility for crawling historical data of China stocks
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
🐍 Data Analysis with the Pandas Library & Notes 📊📈
Técnicas e recursos para estudar ciência de dados.
Download historical 13F filing data directly from the United States (U.S.) Securities Exchange Commission (SEC).
Nvidia DLI workshop on AI-based predictive maintenance techniques to identify anomalies and failures in time-series data, estimate the remaining useful life of the corresponding parts, and map anomali...
A series of notebooks that introduce Machine Learning concepts with hands-on practice and its mathematics in brief.
Open Source LeetCode for PySpark, Spark, Pandas and DBT/Snowflake
Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!
Lightweight and extensible compatibility layer between dataframe libraries!
Practices on data analysis including: cleaning, visualization and EDA on different datasets using Python, SQL, Power BI, etc.
Here I go through the processing of prototyping a mean reversion trading strategy using statistical concepts, then test it in backtrader.
Más de 50 ejemplos de visualizaciones y análisis de datos en Matplotlib, Pandas, Seaborn, Plotly, Bokeh y Networkx
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
A comprehensive collection of practical machine learning examples using popular frameworks and libraries.
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may ...
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Python Data Science Handbook: full text in Jupyter Notebooks
人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-in...
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AW...
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
ArcticDB is a high performance, serverless DataFrame database built for the Python Data Science ecosystem.
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data
TuShare is a utility for crawling historical data of China stocks
A comprehensive collection of practical machine learning examples using popular frameworks and libraries.
🐍 Data Analysis with the Pandas Library & Notes 📊📈
Practices on data analysis including: cleaning, visualization and EDA on different datasets using Python, SQL, Power BI, etc.
Técnicas e recursos para estudar ciência de dados.
Open Source LeetCode for PySpark, Spark, Pandas and DBT/Snowflake
Nvidia DLI workshop on AI-based predictive maintenance techniques to identify anomalies and failures in time-series data, estimate the remaining useful life of the corresponding parts, and map anomali...
Start developing and backtesting your own automated trading strategies
A beginner's roadmap to self studying Machine Learning and Artificial Intelligence
A series of notebooks that introduce Machine Learning concepts with hands-on practice and its mathematics in brief.
动手实战人工智能系列教程，希望从监督学习开始，带你入门机器学习和深度学习。我尝试剖析和推导每一个基础算法的原理，将数学过程写出来，同时基于 Python 代码对公式进行实现，做到公式和代码的一一对应。与此同时，我也会利用主流的开源框架重复同样的过程，帮助读者看出手动实现和主流框架实现之间的区别。
This project is about predicting stock prices with more accuracy using LSTM algorithm. For this project we have fetched real-time data from yfinance library.
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
Gone are the days of black-box dataframes in otherwise type-safe code! Pandantic builds off the Pydantic API to enable validation and filtering of the usual dataframe types (i.e., pandas, etc.)
Lightweight and extensible compatibility layer between dataframe libraries!
Download historical 13F filing data directly from the United States (U.S.) Securities Exchange Commission (SEC).
Lightweight and extensible compatibility layer between dataframe libraries!
Open Source LeetCode for PySpark, Spark, Pandas and DBT/Snowflake
A comprehensive collection of practical machine learning examples using popular frameworks and libraries.
Start developing and backtesting your own automated trading strategies
ML-algorithms from scratch using Python. Classic Machine Learning course.
A Python script that anonymizes an Excel file and synthesizes new data in its place.
A YouTube analytics tool for trend, sentiment, and suitability insights.
🤖 This repository houses a collection of image classification models for various purposes, including vehicle, object, animal, and flower classification. Each classifier is built using deep learning t...
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may ...
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
10 Weeks, 20 Lessons, Data Science for All!
Python Data Science Handbook: full text in Jupyter Notebooks
人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-in...
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AW...
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
A series of notebooks that introduce Machine Learning concepts with hands-on practice and its mathematics in brief.
A Python script that anonymizes an Excel file and synthesizes new data in its place.
This project is about predicting stock prices with more accuracy using LSTM algorithm. For this project we have fetched real-time data from yfinance library.
scores: Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
A Full Stack ML (Machine Learning) Roadmap involves learning the necessary skills and technologies to become proficient in all aspects of machine learning, including data collection and preprocessing,...
A beginner's roadmap to self studying Machine Learning and Artificial Intelligence
动手实战人工智能系列教程，希望从监督学习开始，带你入门机器学习和深度学习。我尝试剖析和推导每一个基础算法的原理，将数学过程写出来，同时基于 Python 代码对公式进行实现，做到公式和代码的一一对应。与此同时，我也会利用主流的开源框架重复同样的过程，帮助读者看出手动实现和主流框架实现之间的区别。
This repository is to show my Data Analytics & Engineering skills, share projects, and track my progress.
This repository was created to showcase my analytical and technical skills (Excel, Python, SQL, Power BI, PowerPoint, and others).
🤖 This repository houses a collection of image classification models for various purposes, including vehicle, object, animal, and flower classification. Each classifier is built using deep learning t...
Entity Matching Model solves the problem of matching company names between two possibly very large datasets.
Compare DuckDB, Polars and Pandas for generating an artificial dataset of persons and companies
Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare ...