Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
SpeedCrunch
Qalculate!
Numi App
Soulver
WolframAlpha
Event Viewer
fxSolver
Mathway
Pandas SpeedCrunchPandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.
Based on our record, Pandas seems to be a lot more popular than SpeedCrunch. While we know about 219 links to Pandas, we've tracked only 6 mentions of SpeedCrunch. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Libraries for data science and deep learning that are always changing. - Source: dev.to / 28 days ago
# 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', ... - Source: dev.to / about 1 month ago
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). - Source: dev.to / about 2 months ago
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,... - Source: dev.to / 4 months ago
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... - Source: dev.to / 9 months ago
As well as of https://speedcrunch.org/. Source: about 3 years ago
I would love to see Speedcrunch to become KDE's first choice as a calculator app:. Source: over 3 years ago
Hello, if you are looking for a good scientific calculator you could give a chance to speedcrunch. Source: over 3 years ago
SpeedCrunch - The best and only calculator you'll need, completely stripped down of unnecessary UI clutter. - Source: dev.to / about 4 years ago
I personally really like using speedcrunch[1] as a desktop calculator, and it’s cross platform. It’s not doing pretty print though. Otherwise it’s wolfram alpha[2], but that needs internet. I never type calculations in any search engines, but that’s way too slow compared to speedcrunch. Maybe I feel similarly to chalk using a web view compared to how electron apps are seen by some. Displaying inaccuracies is neat!... - Source: Hacker News / about 4 years ago
NumPy - NumPy is the fundamental package for scientific computing with Python
Qalculate! - Qalculate! is a multiplatform multi-purpose desktop calculator.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Numi App - Numi is a beautiful text calculator for Mac.
OpenCV - OpenCV is the world's biggest computer vision library
Soulver - Soulver is a software application that functions as a calculator that allows you type a continuous stream of information rather than having to input data into multiple cells.