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Pandas Alternatives
Similar projects and alternatives to Pandas
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Mergify
Tired of breaking your main and manually rebasing outdated pull requests?. Managing outdated pull requests is time-consuming. Mergify's Merge Queue automates your pull request management & merging. It's fully integrated to GitHub & coordinated with any CI. Start focusing on code. Try Mergify for free.
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Pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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InfluxDB
Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.
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Cubes
[NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
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Airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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Apache Arrow
Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
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pyexcel
Single API for reading, manipulating and writing data in csv, ods, xls, xlsx and xlsm files
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TypeScript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
Pandas reviews and mentions
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Interacting with Amazon S3 using AWS Data Wrangler (awswrangler) SDK for Pandas: A Comprehensive Guide
AWS Data Wrangler is a Python library that simplifies the process of interacting with various AWS services, built on top of some useful data tools and open-source projects such as Pandas, Apache Arrow and Boto3. It offers streamlined functions to connect to, retrieve, transform, and load data from AWS services, with a strong focus on Amazon S3.
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How to Build and Deploy a Machine Learning model using Docker
Pandas
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[Python] A Journey to Python Async - 1. Intro
But whereas I took for granted that async syntax in JS, async in Python was quite unfamiliar to me when I saw it for the first time. I had some experiences of using Python for writing really simple scripts, without ever worrying about those async features. That was probably because many big popular libraries such as numpy, pandas, or even selenium didn’t require any async logics to be considered. And those libraries were(and still are) the main reasons for using Python at all.
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Mastering MultiIndexes in Pandas: A Powerful Tool for Complex Data Analysis
Pandas is a widely used data manipulation library in Python that offers extensive capabilities for handling various types of data. One of its notable features is the ability to work with MultiIndexes, also known as hierarchical indexes. In this blog post, we will delve into the concept of MultiIndexes and explore how they can be leveraged to tackle complex, multidimensional datasets.
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Visualize Real-Time Data With Python, Dash, and RisingWave
To install Dash, you can also refer to Dash installation guide on the website. Basically, we need to install two libraries (Dash itself and Pandas) by running the following pip install command:
- Polars: alternativa ao Pandas
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Fueling Innovation and Collaborative Storytelling
This might not be at the top of your list, but science fiction often presents advanced data analysis and visualization technologies. Open source data analysis tools such as Python's Pandas and R's ggplot2 have revolutionized the field, making complex data manipulation and visualization accessible to all. In the science fiction novel The Martian, astronaut Mark Watney uses a variety of data analysis and visualization tools to survive on Mars. He uses Python's Pandas to clean and organize data, and he uses R's ggplot2 to create visualizations of his data. These tools allow him to make sense of the vast amounts of data and help him to make critical decisions about his survival.
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Beaver: a common lisp library for data analysis and manipulation
Hello there folks! I decided to create a data analysis library modeled after pandas, as all things are, this library isn't perfect. It currently only supports a simple CSV, and serializes it into a 2D matrix. Here is currently how it looks
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How do I get Local LLM to analyze an whole excel or CSV?
I think that the model should be able to understand to use a tool like [pandas](https://pandas.pydata.org/) and not to analyze the data with it's capabilities.
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Why are physics undergrads told to "learn programming" and what does this consist of?
pandas: you mention employability, and this is one of the most powerful ways you can wrangle with data in Python, say as a data analyst. I have used it for some of my research projects because it allows you to collect elements from a data table easily based on shared characteristics or a custom function and plot/perform statistical analysis on them.
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A note from our sponsor - Sonar
www.sonarsource.com | 22 Sep 2023
Stats
pandas-dev/pandas is an open source project licensed under BSD 3-clause "New" or "Revised" License which is an OSI approved license.
The primary programming language of Pandas is Python.