Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Airbyte
Fivetran
QuickBI
Meltano
Supermetrics
Hevo Data
Zapier
Segment
Pandas AirbytePandas 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.
Airbyte is recommended for organizations and developers who prefer an open-source tool for data integration, specifically those who want to create custom connectors or have unique data integration requirements. It's particularly suitable for technology-savvy teams who are comfortable working with a modular system and can contribute or adapt to the evolving ecosystem.
Based on our record, Pandas should be more popular than Airbyte. 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 / 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 / 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 / 10 months ago
Airbyte is an open-source data integration platform that supports log-based CDC from databases like Postgres, MySQL, and SQL Server. To assist log-based CDC, Airbyte uses Debezium to capture various operations like INSERT and UPDATE. - Source: dev.to / about 2 months ago
Whenever we discuss event streaming, Kafka inevitably enters the conversation. As the de facto standard for event streaming, Kafka is widely used as a data pipeline to move data between systems. However, Kafka is not the only tool capable of facilitating data movement. Products like Fivetran, Airbyte, and other SaaS offerings provide user-friendly tools for data ingestion, expanding the options available to... - Source: dev.to / 4 months ago
Let’s say I’m using Cursor to build a bunch of data apps and using Airbyte as the data movement platform and Streamlit for the frontend. I’m writing in Python and using the Airbyte API libraries. This is my basic ‘tech stack’. - Source: dev.to / 6 months ago
Some popular tools for data extraction are Airbyte, Fivetran, Hevo Data, and many more. - Source: dev.to / 6 months ago
Open source tools like Apache Superset, Airbyte, and DuckDB are providing cost-effective and customizable solutions for data professionals. Becoming adept at these tools not only reduces dependency on proprietary software but also fosters community engagement. - Source: dev.to / 6 months ago
NumPy - NumPy is the fundamental package for scientific computing with Python
Fivetran - Fivetran offers companies a data connector for extracting data from many different cloud and database sources.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
QuickBI - Export data from over 300 sources to a data warehouse and analyze it with a reporting tool of your choice. Quick and easy setup.
OpenCV - OpenCV is the world's biggest computer vision library
Meltano - Open source data dashboarding
