Pandas VS stats.fm
Compare Pandas VS stats.fm 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
stats.fm
Last.fm
ListenBrainz
BandNext
Music Walker
KOLLEKT.FM
Songstack
Gnoosic
PandasBased on our record, Pandas should be more popular than stats.fm. It has been mentiond 219 times since March 2021. 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 / 25 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 / 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 / 9 months ago
If you're interested in something for consumers, I recommend you try https://stats.fm/. - Source: Hacker News / over 1 year ago
If you cannot find it, you always have the option of paying and importing your stats to stats.fm and it should hopefully be there on the songs you have played! Source: over 1 year ago
Stats.fm is just for spotify right? I use last.fm to track music on almost any interface you can think of:. Source: over 1 year ago
Not sure if the stats.fm 'leader board' for top listeners are correct since there seems to be some users with inflated minutes. Some random dude has 157,274 minutes on 'Fantastic Magic' alone which is unbelievable. Source: over 1 year ago
I tried contacting support about this but they just hit me with a "we think you deserve it so we're not going to do anything" (not literally, but it has those vibes). I do not farm streams or practice fraudulent behavior in any manner, and y'all are free to check this out yourselves. I use Spotify very frequently, whether it be to drown out noise or to distract me from other things. I also have diagnosed ADHD and... Source: over 1 year ago
NumPy - NumPy is the fundamental package for scientific computing with Python
Last.fm - The world's largest online music service. Listen online, find out more about your favourite artists, and get music recommendations, only at Last.fm
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
ListenBrainz - Open source music website that allows users to import their listen history.
OpenCV - OpenCV is the world's biggest computer vision library
BandNext - Discover bands that sound similar to artists you already love with BandNext. A single click saves your results to a Youtube playlist.