The best standup bot for keeping your team on track during daily async standup meetings. Sup can facilitate a standup meeting, retrospective meeting, or other meetings asynchronously for your team using either a chat-based interface or a dialogue window.
Conduct standups & follow-ups: Sup provides team standup updates. You can see how everything works with direct questions and answers. Asynchronous standups and multiple follow-ups are a click away.
Vacation Tracker: Request, approve, view, and manage vacations with Sup. Holiday tracking is easy with regular updates and a dashboard of employee holiday analytics.
Create surveys & polls: Remote working can become a lot easier when you can make quick decisions based on surveys and quick polls. Make it simple for your team to voice their opinions.
Track team mood: Sup? Is that what you want to ask your team? Using mood tracking, understand your team's emotions. To gauge team morale, use it with a follow-up like standups. The anonymity of responses allows for honest answers.
Integrations: Sup x GoogleSheets. Sup integrates with Google Sheets to create a new Google Sheet file at the end of every month and sync the follow-up responses. Trusted by small and big-leaguers like Iterable, Adobe, PWC, Stripe, MailChimp, Starbucks, Mixpanel, Dell, Warner Bros, Wise, Perceptyx, Udaan, and more.
We use Sup bot extensively in our team to facilitate standup, End-of-day follow-ups, holiday tracking - all without leaving Slack.
Based on our record, Pandas seems to be more popular. 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 / 20 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
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