Pandas 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 Appian. While we know about 219 links to Pandas, we've tracked only 5 mentions of Appian. 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.
Does any of you use a low-code tool like Retool or Appian? If so, what is the most common use case? Source: over 2 years ago
Look for use case inspiration in the Solutions area of appian.com and within the AppMarket. See if you can build proof of concepts of some of these. Source: over 2 years ago
There are low code database driven website creation systems out there at the moment e.g. OutSystems and Appian however they have very limited free trials (e.g. auto-disable after a few days of no use), and then the paid options are again too expensive. Although I will note that they seem to be great in terms of their usability and would be perfect for creating a simple interface without too much diving into code. Source: almost 3 years ago
My concern however is - the working software isn't a generic language such as Java, C#/C++, Python etc. - it is with Appian (Business Process Management), which is a rather specific low-code platform for developing workflow and automation solutions. The role does have other elements potentially too such as getting hands on cloud and API dev etc. The pay for Appian Developers currently is GREAT due to high demand -... Source: about 3 years ago
Platforms like UiPath, Workato, and Appian provide ways to integrate apps and automate the processes that connect and flow between them. - Source: dev.to / almost 4 years ago
Libraries for data science and deep learning that are always changing. - Source: dev.to / about 1 month 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
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