Manuskript
Scrivener
yWriter
bibisco
oStorybook
Novelize
BlankPage
FocusWriter
Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Manuskript PandasPandas 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 Manuskript. While we know about 219 links to Pandas, we've tracked only 1 mention of Manuskript. 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.
Looks like you want something that integrates well with your workflow. The closest to your description seems to be Manuskript although I haven't used it. But your requirement of "keeping notes and frameworks and linking back and forth" should be possible by stitching together existing Linux tools using a syntax like markdown or asciidoc so that you can use any text editor to write your story and use external tools... Source: over 3 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
Scrivener - Scrivener is a content-generation tool for composing and structuring documents.
NumPy - NumPy is the fundamental package for scientific computing with Python
yWriter - Free writing software designed by the author of the Hal Spacejock and Hal Junior series. yWriter6 helps you write a book by organising chapters, scenes, characters and locations in an easy-to-use interface.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
bibisco - bibisco is a novel writing software.
OpenCV - OpenCV is the world's biggest computer vision library