Pandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.
Based on our record, Pandas seems to be a lot more popular than LucidChart. While we know about 219 links to Pandas, we've tracked only 5 mentions of LucidChart. 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.
I'm thinking something like a lucidchart.com set up, but also wondering since one project is complete if there is anything that can just analyze an existing codebase and automatically do the work for me. Source: over 3 years ago
Oh! excalidraw.com is great for quick paper style diagrams. I have used it a fair bit. The roam integration is good. But I always revert back to draw.io because it's open sourced, simple to use and just works :D If you are looking for more, a paid option would be lucidchart.com. Source: over 3 years ago
You could try lucidchart.com or draw.io. I have used both. Source: about 4 years ago
Otherwise, you may be thinking about a "mind-map" of sorts... Simply to show relationships? Diagrams.net, lucidchart.com. Source: about 4 years ago
What is difference between Yours tool and others like arcentry.com lucidchart.com cloudcraft.co hava.io ? Would be nice to support diagrams as code ( generated from kubernetes states, terraform, pulumi, etc..) Personally I dont think that another diagram tool can beat ^ platforms. Source: about 4 years ago
Libraries for data science and deep learning that are always changing. - Source: dev.to / about 2 months ago
# Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / 2 months ago
As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / 2 months ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 10 months ago
draw.io - Online diagramming application
NumPy - NumPy is the fundamental package for scientific computing with Python
yEd - yEd is a free desktop application to quickly create, import, edit, and automatically arrange diagrams. It runs on Windows, Mac OS X, and Unix/Linux.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
OmniGraffle - OmniGraffle is for creating precise graphics like website wireframes, an electrical system designs, or mapping out software class.
OpenCV - OpenCV is the world's biggest computer vision library