Pandas Libraries

86 Components & Libraries

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Pandas 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 help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

🧡🧡🧡 HAPPY CODING 🧡🧡🧡 This challenge is designed for beginners and professionals who want to learn python programming language. It may take 30 to 100 days to complete the challenge, people who activel…

Open Machine Learning Course

mlcourse.ai is still in self-paced mode but we offer you Bonus Assignments with solutions for a contribution of $17/month. The idea is that you pay for ~1-5 months while studying the course materials…

Modin: Scale your Pandas workflows by changing a single line of code

By simply replacing the import statement, Modin offers users effortless speed and scale for their pandas workflows: If you want to install Modin with a specific engine, we recommend: Modin automatica…

PandasAI is a Python library that integrates generative artificial intelligence capabilities into pandas, making dataframes conversational

Try out PandasAI in your browser: PandasAI is designed to be used in conjunction with pandas. It makes pandas conversational, allowing you to ask questions to your data in natural language. For examp…

A terminal spreadsheet multitool for discovering and arranging data

A terminal interface for exploring and arranging tabular data. To install the latest release from PyPi: Hundreds of other commands and options are also available; see the documentation.

A python wrapper for Alpha Vantage API for financial data.

To install the package use: Or install with pandas support, simply install pandas too: If you want to install from source, then use: Internally there is a retries counter, that can be used to minimiz…

Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.

To install mimesis, simply use pip: It is divided into several sections: You can improve it by sending pull requests to this repository.

pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON…

Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

IPython Notebook(s) and other programming tools such as Torch/Lua/D lang in demonstrating deep learning functionality. Additional PyRo tutorials: IPython Notebook(s) demonstrating scikit-learn functi…

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling you to thoroughly test your data and models from research to production. Deepchecks includes: For …

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

You can start with this article that I wrote in Heartbeat magazine (on Medium platform): Jupyter notebooks covering a wide range of functions and operations on the topics of NumPy, Pandans, Seaborn, …

Hot Reloading, Profiling and AI debugging for Python

Running python files: Running modules:

Expressive analytics in Python at any scale.

Ibis is a Python library that provides a lightweight, universal interface for data wrangling. It helps Python users explore and transform data of any size, stored anywhere. Ibis has three primary com…

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

This repository contains all the code, notebooks and examples used in this book. We will also be adding bonus content here from time to time. So keep watching this space! Master the essential skills …

Learn Python for the next 30 (or so) Days.

Simple wrapper of tabula-java: extract table from PDF into pandas DataFrame

Ensure you have a Java runtime and set the PATH for it. tabula-py enables you to extract tables from a PDF into a DataFrame, or a JSON. It can also extract tables from a PDF and save the file as a CS…

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

Graphistry gets used on problems like visually mapping the behavior of devices and users, investigating fraud, analyzing machine learning results, and starting in graph AI. It provides point-and-clic…

:zap: Data quality management for SQL, Spark, and Pandas-accessible data

Soda Core is a free, open-source, command-line tool that enables you to use the Soda Checks Language to turn user-defined input into aggregated SQL queries. When it runs a scan on a dataset, Soda Cor…

DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration

Dataframes are used for statistics, machine-learning, and data manipulation/exploration. You can think of a Dataframe as an excel spreadsheet. This package is designed to be light-weight and intuitiv…

Your single tool to express data, ML, and LLM pipelines with simple python functions. Runs anywhere that python runs, E.G. spark, airflow, jupyter, fastapi, etc. Incrementally adoptable. Use Hamilton to build testable, reusable, and self-documenting dataflows with lineage and metadata out of the box.

Hamilton is a novel paradigm for specifying a flow of delayed execution in python. It works on python objects of any type and dataflows of any complexity. Core to the design of Hamilton is a clear ma…

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

You should already have pip, Python, and optionally XGBoost, LightGBM, and CatBoost installed on your system (see below). Run the following command to install AlphaPy: Pyfolio is automatically instal…

A scalable general purpose micro-framework for defining dataflows. You can use it to build dataframes, numpy matrices, python objects, ML models, etc. Embed Hamilton anywhere python runs, e.g. spark, airflow, jupyter, fastapi, python scripts, etc.

The general purpose micro-framework for creating dataflows from python functions! Specifically, Hamilton defines a novel paradigm, that allows you to specify a flow of (delayed) execution, that forms…

do more with dbt. dbt-fal helps you run Python alongside dbt, so you can send Slack alerts, detect anomalies and build machine learning models.

The dbt-fal ecosystem has two main components: The command line and the adapter. With the CLI, you can: With the Python adapter, you can:

Manipulate JSON-like data with NumPy-like idioms.

The result is The equivalent using only Python is The expression using Awkward Arrays is more concise, using idioms familiar from NumPy, and it also has NumPy-like performance. For a similar problem …

General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python

Jupyter Notebooks on the topics of statistical analysis, mathematics, and numerical/sceintific computing (in Python).

do more with dbt. fal helps you run Python alongside dbt, so you can send Slack alerts, detect anomalies and build machine learning models.

Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.

Retentioneering is a Python library that makes analyzing clickstreams, user paths (trajectories), and event logs much easier, and yields much broader and deeper insights than funnel analysis. You can…

Data science, machine learning, and web development project code for https://www.youtube.com/c/Dataquestio .

These walkthroughs help you build complete end-to-end projects that can go into your portfolio. To complete these projects, you'll need to have a good understanding of: Please make sure you've comple…

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