Cron
Cal.com
zcal
Vimcal
Calendly
SavvyCal
TidyCal
Amie
Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
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 Cron. While we know about 219 links to Pandas, we've tracked only 21 mentions of Cron. 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.
To sync with Google Calendar you could use Cron (recently acquired by Notion). Source: almost 2 years ago
I have been using cron for a while and can vouch for it. Source: about 2 years ago
Cron https://cron.com/ best calendar app I can think of. Source: about 2 years ago
No, not yet. We all speculate and hope Cron integration will solve it since acquisition. Source: about 2 years ago
If they’re both using gmail cron is great, but personally I haven’t really found the need with just 2J’s but the meetings are lighter so that probably comes into play. Source: about 2 years ago
Libraries for data science and deep learning that are always changing. - Source: dev.to / 29 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 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 / about 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 / 9 months ago
Cal.com - Cal.com (formerly Calendso) is the open source Calendly alternative.
NumPy - NumPy is the fundamental package for scientific computing with Python
zcal - zcal is the fastest way to schedule every meeting for Free and make it personal.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Vimcal - Vimcal is the world’s fastest calendar, beautifully designed for people who work remotely and live in their calendars.
OpenCV - OpenCV is the world's biggest computer vision library