Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Matplotlib
GnuPlot
Plotly
D3.js
Seaborn
NumPy
SciDaVis
GeoGebra
Pandas MatplotlibBased on our record, Pandas should be more popular than Matplotlib. It has been mentiond 199 times since March 2021. 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 / 3 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 / 21 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 / 15 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 / 2 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
Matplotlib: for displaying our image result. - Source: dev.to / about 1 month ago
Matplotlib: Acomprehensive library for creating static, animated, and interactive visualizations in Python. - Source: dev.to / 3 months ago
Data visualization: utilizing Python's Matplotlib for visualizing order book information. - Source: dev.to / 6 months ago
For random, quick and dirty, ad-hoc plotting tasks my default is GNUPlot[1]. Otherwise I tend to use either Python with matplotlib, or R with ggplot2. I keep saying I'm going to invest the time to properly learn D3[4] or something similar for doing web-based plotting, but somehow never quite seem to find time to do it. sigh [1]: http://www.gnuplot.info/ [2]: https://matplotlib.org/ [3]:... - Source: Hacker News / 9 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
NumPy - NumPy is the fundamental package for scientific computing with Python
GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Plotly - Low-Code Data Apps
OpenCV - OpenCV is the world's biggest computer vision library
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.