Pandas Alternatives

Pandas reviews and mentions

• Don't Know These 6 Tools? No Wonder Your Python Development Is So Slow
  4 projects | dev.to | 10 Jul 2025

  👉 https://pandas.pydata.org/

• Open Source Can't Coordinate
  6 projects | news.ycombinator.com | 19 Jun 2025
• Top Programming Languages for AI Development in 2025
  9 projects | dev.to | 29 Apr 2025

  Libraries for data science and deep learning that are always changing

• How to import sample data into a Python notebook on watsonx.ai and other questions…
  1 project | dev.to | 13 Apr 2025

  # Read the content of nda.txt try: import os, types import pandas as pd from botocore.client import Config import ibm_boto3 def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. cos_client = ibm_boto3.client(service_name='s3', ibm_api_key_id='api-generated', ibm_auth_endpoint="https://iam.cloud.ibm.com/identity/token", config=Config(signature_version='oauth'), endpoint_url='https://s3.direct.us-south.cloud-object-storage.appdomain.cloud') bucket = 'your-bucket-referenced-here' object_key = 'nda__da__crxq8b2hmy.txt' # load data of type "text/plain" into a botocore.response.StreamingBody object. # Please read the documentation of ibm_boto3 and pandas to learn more about the possibilities to load the data. # ibm_boto3 documentation: https://ibm.github.io/ibm-cos-sdk-python/ # pandas documentation: http://pandas.pydata.org/ streaming_body_1 = cos_client.get_object(Bucket=bucket, Key=object_key)['Body'] with open("nda.txt", "r") as f: nda_content = f.read() print("Content of nda.txt has been read.") except FileNotFoundError: print("Error: nda.txt not found in the current directory.") nda_content = "" # Initialize knowledge source content_source = CrewDoclingSource( file_paths=["..."] )

• How I Hacked Uber’s Hidden API to Download 4379 Rides
  4 projects | dev.to | 9 Apr 2025

  As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here).

• Show HN: Aiopandas – Async .apply() and .map() for Pandas, Faster API/LLMs Calls
  6 projects | news.ycombinator.com | 15 Mar 2025

  Can this be merged into pandas?

  Pandas does not currently install tqdm by default.

  pandas-dev/pandas//pyproject.toml [project.optional-dependencies] https://github.com/pandas-dev/pandas/blob/main/pyproject.tom...

  Dask solves for various adjacent problems; IDK if pandas, dask, or dask-cudf would be faster with async?

  Dask docs > Scheduling > Dask Distributed (local) https://docs.dask.org/en/stable/scheduling.html#dask-distrib... :

  > Asynchronous Futures API

  Dask docs > Deploy Dask Clusters; local multiprocessing poll, k8s (docker desktop, podman-desktop,), public and private clouds, dask-jobqueue (SLURM,), dask-mpi:

• We Are Destroying Software
  4 projects | news.ycombinator.com | 8 Feb 2025

  They are when the only reason they are flagged as security updates is because some a single group deems a very rare, obscure edge case as a HIGH severity vuln when in practice it rarely is => this leads to having to upgrade a minor version of a library that ends up causing breaking changes.

  This is the recent thread I'm down. Pandas 2.2 broke SQLalchemy backwards compatibility: https://stackoverflow.com/questions/38332787/pandas-to-sql-t... + https://github.com/pandas-dev/pandas/issues/57049#issuecomme...

• Must-Know 2025 Developer’s Roadmap and Key Programming Trends
  6 projects | dev.to | 5 Feb 2025

  Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python, try projects that combine data with everyday problems. For example, build a simple recommendation system using Pandas and scikit-learn.

• Sample Super Store Analysis Using Python & Pandas
  3 projects | dev.to | 4 Feb 2025

  This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of capabilities that the Pandas library, written in Python can offer.

• Bullish on AI infrastructure, bearish on AI developer frameworks
  3 projects | dev.to | 31 Jan 2025

  Data preprocessing and manipulation: Libraries like Pandas solve for the messy, real-world challenge of efficiently wrangling and cleaning large datasets. Without it, you'd be reinventing functionality for basic tasks like merging, filtering, or aggregating data.

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  www.influxdata.com | 19 Jul 2025

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