scapy
seaborn
scapy | seaborn | |
---|---|---|
26 | 77 | |
10,061 | 11,958 | |
0.9% | - | |
9.3 | 8.4 | |
6 days ago | 9 days ago | |
Python | Python | |
GNU General Public License v3.0 only | BSD 3-clause "New" or "Revised" License |
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scapy
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Seven Python Projects to Elevate Your Coding Skills
Example Network Scanner Scapy
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Python Networking: TCP and UDP
In the last installment we looked at IP headers. One thing you might have seen missing is the port numbers. That's pretty important for making an internet connection. Well it turns out that IP tends to encapsulate other protocols (which is why it has protocol as part of the header). In this article we'll be looking at two popular protocols for internet traffic: TCP and UDP. Before we begin though install scapy which we'll be using to make things easier, and dnslib that will be used during the UDP section:
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🛜 What is ARP Spoofing?
I've coded my small ARP spoofer in Go because I love the language, though it can very well be coded in other languages, for example Python with Scapy.
- What are the most underrated python libraries?
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Is it possible to send raw data over an IP network, not encapsulated in TCP or UDP?
Scapy: https://github.com/secdev/scapy
- packet-rs - A Scapy like rust packet interface
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tshark live statistics (-z) display?
Tshark can't do that. The Wireshark app does update its Conversations window pretty frequently when doing a live capture, so that might be a reasonable alternative. Otherwise you could probably also cobble something together yourself with a tool like scapy or some other Python library, but that would clearly be more work.
- Is there a script/program to find similarities among multiple pcap files?
- Scapy - Packet Crafting
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Extract data from a pcap file
I don't know if you can do it within the gui, I don't see anything but perhaps a bit of Python code would do it. There is a python library called Scapy that may have functions to help you along the way.
seaborn
- "No" is not an actionable error message
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Apache Superset
If you are doing data analysis I don't think any of the 3 pieces of software you mentioned are going to be that helpful.
I see these products as tools for data visualization and reporting i.e. presenting prepared datasets to users in a visually appealing way. They aren't as well suited for serious analytics.
I can't comment on Superset or Tableau but I am familiar with Power BI (it has been rolled out across my org), the type of statistics you can do with it are fairly rudimentary. If you need to do any thing beyond summarizing (counts, averages, min, max etc). It is not particularly easy.
For data analysis I use SAS or R. This software allows you do things like multivariate regression, timeseries forecasting, PCA, Cluster analysis etc. There is also plotting capability.
Both these products are kind of old school, I've been using them since early 2000's, the "new school" seems to be Python. Pretty much all the recent data science people in my organization use Python. Particularly Pandas and libraries like Seaborn (https://seaborn.pydata.org/).
The "power" users of Power BI in my organization tend to be finance/HR people for use cases like drill down into cost figures or Interactively presenting KPI's and other headline figures to management things like that.
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Seaborn bug responsible for finding of declining disruptiveness in science
It's referring to the seaborn library (https://seaborn.pydata.org/), a Python library for data visualization (built on top of matplotlib).
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Why Pandas feels clunky when coming from R
While it’s not perfect and it’s not ggplot2, Seaborn is definitely a big improvement over bare matplotlib. You can still use matplotlib to modify the plots it spits out if you want to but the defaults are pretty good most of the time.
https://seaborn.pydata.org/
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Releasing The Force Of Machine Learning: A Novice’s Guide 😃
Seaborn: A statistical data visualization library based on Matplotlib, enhancing the aesthetics and visual appeal of statistical graphics.
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Seven Python Projects to Elevate Your Coding Skills
Matplotlib Seaborn Example data sets
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Seaborn - Statistical data visualization using Matplotlib.
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/mwaskom/seaborn
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Best Portfolio Projects for Data Science
Seaborn Documentation
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[OC] Nationwide Public Transit Ridership is down 30% from pre-lockdown levels; San Francisco's BART ridership is down almost 70%
You've done a great job presenting this. Maybe you already know, but seaborne is an extension of matplotlib that makes it pretty easy to "beautify" matplotlib charts
What are some alternatives?
pyshark - Python wrapper for tshark, allowing python packet parsing using wireshark dissectors
bokeh - Interactive Data Visualization in the browser, from Python
pySerial - Python serial port access library
Altair - Declarative statistical visualization library for Python
impacket - Impacket is a collection of Python classes for working with network protocols. [Moved to: https://github.com/SecureAuthCorp/impacket]
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
keyboard - Hook and simulate global keyboard events on Windows and Linux.
ggplot - ggplot port for python
RustScan - 🤖 The Modern Port Scanner 🤖
plotnine - A Grammar of Graphics for Python
elmocut - Eye candy ARP spoofer for Windows
matplotlib - matplotlib: plotting with Python