Centralise logs, metrics and traces into a single platform for observability with Logit.io. The Logit.io platform provides complete data reporting, monitoring and alerting by harnessing the best open source tools including ELK, OpenSearch, Prometheus & Grafana.
As the Logit.io platform operates in compliance with GDPR, HIPAA, SOC 2 and is ISO 27001 & PCI Service Provider certified, you can rest assured that we uphold the best security standards possible to protect our user’s data and information security interests. The platform can also be used to meet compliance with the Cybersecurity Maturity Model certification for the following ID numbers AU.2.041, AU.2.042, AU.2.044, AU.3.045, AU.3.046, AU.3.048, AU.3.049, AU.3.050, AU.3.051 and AU.3.052.
In addition to this, our platform can also be used to detect and mitigate issues such as Log4Shell CVE-2021-44228.
Whether you need to conduct application performance monitoring, log management, infrastructure monitoring, SIEM, or data visualisation, the Logit.io platform is here to provide a complete platform for data management and analysis.
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Based on our record, Matplotlib seems to be more popular. It has been mentiond 98 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.
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 / 10 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
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GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.
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Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
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