Based on our record, Pandas seems to be a lot more popular than SciPy. While we know about 199 links to Pandas, we've tracked only 16 mentions of SciPy. 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.
It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / 8 days ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 25 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 19 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 3 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
Python has become a popular programming language for different applications, including data science, artificial intelligence, and web development. But, did you know creating and rendering fully customized videos with Python is also possible? At Stack Builders, we have successfully used Python libraries such as MoviePy, SciPy, and ImageMagick to generate videos with animations, text, and images. In this article, we... - Source: dev.to / 2 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
SciPy: a library used for scientific and technical computing. It has a function that can calculate the cosine distance, which equals 1 minus the cosine similarity. - Source: dev.to / 11 months ago
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: about 1 year ago
I mean scientific-grade Python libraries like https://pytorch.org https://numpy.org https://scipy.org etc, which exist for about 10 years (your comment may be ok in 2001, but now it's a bit outdated;). Source: over 1 year ago
NumPy - NumPy is the fundamental package for scientific computing with Python
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Matplotlib - matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
OpenCV - OpenCV is the world's biggest computer vision library
Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.
Exploratory - Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.