Pandas VS Glimpse
Compare Pandas VS Glimpse and see what are their differences
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
featured
Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Glimpse
Exploding Topics
Google Trends
Widgeridoo
Trends.co
Treendly
Trends.vc
Google Trends Visualizer
Use the code saashub for 50% off your first month
Pandas GlimpseGlimpse's answer:
Glimpse leverages a proprietary algorithm that doesn’t have the lag that other search volume data providers have. Other providers have a number of issues, including lag time and bundling similar keywords together, which decrease the accuracy of their estimates. This is especially important for trends - for example, many of the other tools showed “chatgpt” having 0 or minimal search volume in mid-January 2023 when Glimpse showed it having 4M searches. Google Trends data doesn't suffer from these issues, and Glimpse's data is the only source that aligns with Google Trends.
Based on our record, Pandas seems to be a lot more popular than Glimpse. While we know about 219 links to Pandas, we've tracked only 16 mentions of Glimpse. 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.
Libraries for data science and deep learning that are always changing. - Source: dev.to / 17 days 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 / about 1 month 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 / about 1 month 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 / 3 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 / 9 months ago
If you want to build something instead, I suggest taking a look at indie hackers to see what other people are doing or using a tool like glimpse to find trends before they pop-off and build a solution to those things. Source: almost 2 years ago
The most valuable and impressive thing you can do is build a business. Hands down. Especially if it makes money. That will show you're not just a cog in the wheel but able to critically think and have valuable practical skillsets. I would experiment with something that has tailwinds. Like an AI business, or a VR business once the new apple VR app store comes out. you'd be shocked at how much you can make... Source: almost 2 years ago
For example; trends.co is not very good because the people that write for them are journalists, not business owners so although the writing is good, the ideas are poorly researched. On the other hand, meetglimpse.com is pretty good, they have nuanced and unique business ideas that you can take advantage of but the market research behind it is a little lacking, their chrome extension tool is great tho. And then... Source: almost 2 years ago
a lot of things. I've built 3 online businesses that were profitable with under $1000. it's really just a hustle once you get product market fit. Starting something online shouldn't take that much money if you know how to test it. Check out like trends.vc, explodingideas.co, meetglimpse.com etc. They may be able to spark your creativity for ideas that could be good opportunities for the price point. Source: about 2 years ago
Great idea. You should scrape ideas from meetglimpse.com, explodingideas.co, trends.co and the other sites that post ideas. Would be an easy way to bulk up the document. Source: about 2 years ago
NumPy - NumPy is the fundamental package for scientific computing with Python
Exploding Topics - Get inspirations for blog posts, startup projects, cocktail conversations and beyond on Trennd, the one-stop aggregator for emerging search and social trends.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Google Trends - Explore Google trending search topics with Google Trends.
OpenCV - OpenCV is the world's biggest computer vision library
Widgeridoo - Custom and pre-made widgets for iOS and macOS