Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Qlik
Tableau
Looker
Sisense
Domo
Microsoft Power BI
QlikSense
MicroStrategy
MatplotlibQlik's associative data model makes data analytics seamless.
Highly Recomend using this to anyone.
Based on our record, Matplotlib seems to be a lot more popular than Qlik. While we know about 114 links to Matplotlib, we've tracked only 1 mention of Qlik. 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.
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 7 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 8 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
All files was pulled into a program called : QLIK, qlik.com is the company and my company uses it for our reporting and our customer's reporting needs. Source: over 5 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
NumPy - NumPy is the fundamental package for scientific computing with Python
Looker - Looker makes it easy for analysts to create and curate custom data experiencesโso everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
Sisense - The BI & Dashboard Software to handle multiple, large data sets.