LanguageTool
Grammarly
Ginger
ProWritingAid
Outwrite.com
Wordtune
Editsaurus
QuillBot
Pandas
NumPy
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
LanguageTool PandasBased on our record, Pandas seems to be a lot more popular than LanguageTool. While we know about 201 links to Pandas, we've tracked only 5 mentions of LanguageTool. 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.
You could check for spelling mistakes first with something like https://languagetool.org/de. Source: over 1 year ago
I prefer https://www.deepl.com/ and https://languagetool.org/de might be also helpful. Source: over 1 year ago
I was already used to wiggly lines in my favorite IDE IntelliJ and really missed the spell and grammar check capabilities in other editors especially when writing something in the browser. A colleague told me that IntelliJ is using LanguageTool since I'm pretty satisfied with the analysis inside it. Therefore, I looked around on GitHub for a way of hosting my own LanguageTool server. I came across this... - Source: dev.to / about 2 years ago
Hi. Maybe before posting on r/WriteStreakGerman and getting a proper correction you could check the writing on these sites (LanguageTool, Duden-Mentor), to catch some of the possible errors. Regarding shyness, put anonymity to good use. Source: over 2 years ago
The LanguageTool extension is decent and picks up on a lot of mistakes, but nowhere close to all of them. For example, it will identify if you wrote an article that can never go with a given noun (like "der Auto"), but will not recognize a case error (like using "das Auto" in Dativ). It will also often pick up on things like comma mistakes. Source: almost 3 years ago
How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class... - Source: dev.to / 18 days ago
Pandas - A powerful data analysis and manipulation library for Python. Pandas Documentation - Official documentation. - Source: dev.to / 24 days ago
It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / about 2 months ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 2 months ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 2 months ago
Grammarly - Clear, effective, mistake-free writing everywhere you type.
NumPy - NumPy is the fundamental package for scientific computing with Python
Ginger - Powerful and effortless desktop & mobile solutions for improving your writing and productivity. Ginger Software is your personalized editor - everywhere you go.
OpenCV - OpenCV is the world's biggest computer vision library
ProWritingAid - For the smarter writer. A grammar checker, style editor, and writing mentor in one package.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.