Data sources

Data-sources

Data sources are essential components in the fields of data science, artificial intelligence, and analytics. They provide the raw information needed to derive insights, make decisions, and develop models. Data can be sourced from various platforms, including public repositories, APIs, and government databases. Commonly used data sources include Kaggle, UCI Machine Learning Repository, and Data.gov, among others. Understanding the types of data available and their respective formats is crucial for effective analysis. By leveraging diverse data sources, researchers and practitioners can enhance their projects and ensure they are grounded in real-world scenarios.

Simply Statistics

Here are places you can get data sets to analyze (for class projects, fun and profit!) Data Market Infochimps Data.gov Factual.com I’m sure there are a ton more…would love to hear from people.

Discover public data with the Data Source Handbook

Pete Warden's blog

I’m pleased to announce that the Data Source Handbook is now available from O’Reilly. It’s a compact ebook guide to the most useful APIs and bulk data sets I’ve found, packed with examples and advice....

Various data sources in Data Science — Overview and Usage

Analytics Vidhya

The core of data science is data. All decision making is data-driven in the present world which makes data and its usage an important element in organizations. From Analysing the health data in…

What’s in the data?

Towards AI

Unpacking the most popular open-source dataset used in LDM safety Text-to-image (T2I) generative AI models have revolutionized content creation by transforming text into photorealistic and imaginativ...

The Best Data is Free Data, Of Course

Towards Data Science

Commonly used data repositories for data science projects are Kaggle and the UCI Machine Learning Repository. However, many of the datasets available there are synthetic and not representative of the…...

Stacked Pandas Bar Chart from US COVID-19 API Data

Analytics Vidhya

In the data science world, you often deal with many different types of data sources. These range from structured data sources like a comma separated file or a database to unstructured data sources…

The source of the cake dataset

R-bloggers

In statistics, there are a number of classic datasets that pop up in examples, tutorials, etc. There’s the infamous iris dataset (just type iris in your nearest R prompt), the Palmer penguins (the mod...

Joining Data Sources

Towards Data Science

Most “data science” in the real world involves creating a data set, a visualization, an application that requires pulling and joining data from very different sources to tell a cohesive story. Moving…...

The ideal data source and activities for developing data skills: Yourself

Towards Data Science

The ideal data source for developing data skills: Yourself An introduction to self-tracking and personal science Image by the author. I teach introductory data courses in a graduate program where stu...

Data Ingestion from 5 Major Data Sources using Python

Towards AI

Learn how to ingest data from 5 Major data sources using python. These data sources are RDBMS database, CSV, Parquet, XML, and CSV.

Top five(ish) sources of ecological data

R-bloggers

As you’re learning R, it can be hard to come up with data sets that you can practice with. Though many of us have our own data, those might not always be in the best format to do what we want. Our own...

Where is the data?

Towards Data Science

One of the hardest things, when you are working with a new dataset, is to discover the most important features for predicting your target, and also, where you can find new sources of information that…...