I looking for a dataset that contains desease information and its respective drugs as well as advice given by doctors for home rest.
submitted by /u/Low_Relationship6157
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Here you can observe the biggest nerds in the world in their natural habitat, longing for data sets. Not that it isn’t interesting, i’m interested. Maybe they know where the chix are. But what do they need it for? World domination?
I looking for a dataset that contains desease information and its respective drugs as well as advice given by doctors for home rest.
submitted by /u/Low_Relationship6157
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Hi all,
Just something I figured worth sharing. UK power networks have started publishing aggregated smart meter data on their open data portal. This dataset currently has 40,000 smart meters aggregated within it, with all that their region covers expected to be in the dataset by the end of the month. (Need to log in to download/get API details)
The rest of the distribution networks in the UK need to publish the same data for their region by the end of the month too. Expect it’ll be a real treasure trove for those of you wanting to do stuff with energy data.
Enjoy!
https://ukpowernetworks.opendatasoft.com/pages/smart-meters/
submitted by /u/BackpackingScot
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Hi there! I have recently started a pet-sitting and pet-care business that provides high-end services. As our target audience is high-income earners, I am wondering if there is a way to access income data by zip code or even by specific neighborhoods. Additionally, I would like to know if there is a way to find out which areas or neighborhoods have a higher number of pets or dogs. This information would be very helpful for me to conduct further research. Thank you!
submitted by /u/MannyOchoaVC
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Hello. Nonprofit here with public and private datasets. We’d love to host a portal to make them available based on user permissions. Looking at CKAN, Taylor, Datahub… what’s available at a lower cost for our small org that is somewhat plug and play? Am I asking for too much?
submitted by /u/rudeamy
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Hi all, I am trying to get the county-by-year values for selected variables for all the counties in the U.S. from the Land Use and Cover Inventory Database (LUCID).
It only allows me to download one county at a time. If I select multiple counties, they sum up the value instead of showing the value by each county.
Can anyone give me a clue on how I can scrape the data?
Thanks so much!
submitted by /u/pakheyyy
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Github: https://github.com/codeplot-co/codeplot App: https://codeplot.co Discord: https://codeplot.co/discord
Hey Datasets community,
I’m excited to introduce codeplot, a tool I’ve been working on that’s designed to revolutionize the way we interact with data visualizations in Python.
What is codeplot?
codeplot is an interactive spatial canvas that allows for dynamic data exploration. It’s built to move beyond static images and fixed layouts, giving your data the interactive, engaging platform it deserves. With codeplot, you can easily integrate live data visualizations directly from your Python code or REPL into a flexible, interactive canvas hosted at codeplot.co.
Key Features:
Dynamic Visualization: Say goodbye to static charts. Visualize your data in real-time on an interactive canvas. Easy Integration: Seamlessly plot from Python with just a few lines of code. Varied Visualizations: Support for a wide range of data representations, from basic charts to complex widgets. Flexible Layouts: Customize your data exploration space with draggable and resizable plots. Open Community: Whether you’re a data scientist or a hobbyist, codeplot is designed for anyone passionate about data. Getting Started is Simple:
Install codeplot with pip, connect to a room, and start plotting right away. We even support usage in Jupyter Notebooks for an integrated development experience.
Docker Support:
For those who prefer self-hosting, codeplot is Docker-ready, allowing you to run your own server and client locally with ease.
Join Our Community:
We’re building a community of data enthusiasts and professionals on Discord. It’s a place to share insights, ask questions, and collaborate on data visualization projects.
I’d love to get your feedback, suggestions, and hear about the visualizations you create with codeplot. Let’s make data exploration more interactive and engaging together!
Thanks for checking out codeplot!
– @antl3x (Creator of codeplot)
submitted by /u/nthypes
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Don’t care whether return rate is monthly or daily, as long as I can calculate performance over past 10 years. I’m talking about every publicly available asset, from cryptocurrencies, to stocks, to commodities.
submitted by /u/crustyrusty7
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I remember I browsed it a year ago quite extensively, but used a different source for my project in the end. Now I don’t remember what it was called and can’t find it anywhere now – can anyone help?
The site had different datasets uploaded by random users, some of them were just, for example, bulks of documents about a particular issue for the last 10 years. No clean data. Maybe it was a bit sketchy, I don’t know. I think it had a red icon/layout and a short name… pretty sure something with a letter “A”
submitted by /u/merlarchenemy
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I am looking for historical data on social connectedness but only found one that appears to cover only the most recent data. Any suggestions?
submitted by /u/BOBOLIU
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I am studying data science and looking for a dataset that lists food and drink products and their associated carbon footprint. For my project the carbon figures do not need to be super accurate.
Branded (e.g. Nutella®, Coca‑Cola) or unbranded (e.g. banana, litre of milk), either would be useful.
submitted by /u/AchillesFirstStand
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I need a dataset with images of food ingredients, from vegetables to fruit, meat and whatnot. It can be multiple datasets specializing in different kinds of ingredients. I’m making a program to identify ingredients from a picture and suggest a recipe that uses the available food, but can’t find a dataset with what I’m looking for, as most only have already prepared meals.
submitted by /u/Accomplished-Level-1
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i am trying to download the IAM Handwriting database from https://fki.tic.heia-fr.ch/databases/iam-handwriting-database/download-the-iam-handwriting-database
whenever i try to open the website, it never opens. Can any one give me a different way to download it through drive or Mega or anything
submitted by /u/VictoryForeign8953
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Looking for statistics on mens pant sizes.
Waist and Inseam.
Looking for a discrete table
submitted by /u/Many-Wasabi9141
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Hey everyone,
I want to build an open source dataset in the clinical trial space. I’m looking for some tech/tools recommendations that make building an open source dataset easy.
I guess the easiest would just be to set up a Google Sheet and Google Form to get new data submissions. I also came across: https://github.com/dolthub/dolt, but this seems to be quite expensive.
Some requirements that need to be fulfilled:
– The core dataset should be public, but we want to restrict access to contact information such as email or phone numbers to avoid that people get spammed
– People should be able to submit new data or submit updates to existing data points, but this data should be verified before it’s written to the public dataset – The final dataset could become quite large (10-20GB). Google Sheet won’t work with this – Users and contributors are non-technical. So it needs to be easy for them to user
Would be curious to learn more about how other people have built their datasets.
Thanks a lot!
submitted by /u/Affenbob123
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I want a dataset where the “Voltage at maximum power point(Vmp)” of a solar cell is measured for different ”irradiance” and ”temperature” values. Thanks a lot in advance. 🙏
submitted by /u/faruquei
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All, looking a dataset that has monthly consumer spend volumes. If availability is a problem, something about the consumer and their opinion about the economy. Can be hard data or a survey. Appreciate the help.
submitted by /u/HangryChef
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Does anyone have access to a dataset containing UK suburbs by their city across the whole uk. I have found one dataset however it is massive and is of poor quality.
submitted by /u/R4eWclan
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I need three pieces of information: 1. Country of origin of the survey participants, 2. When did they move to their current country and 3. An opinion, belief, attitude, behavior… about a topic; it would be ideal to measure their level of openmindedness or trust.
I couldn’t find a specific survey oriented exclusively to measure immigrants’ opinions, so I’m now looking for surveys oriented to the general public (immigrants and natives) and then I would just filter for immigrant cases. Unfortunately, I have been successful in finding a survey that has the three points mentioned above.
Currently, I’m fully focused on the US. The General Social Survey (GSS) has very interesting questions on attitudes but I couldn’t find variables indicating the country of origin or the moving year. Data from IPUMS, census.gov and American Community Surveys (ACS) include information on the country of origin and moving year, but no interesting data about attitudes/opinions, the data from these sources is pretty much technical.
Does anyone know where could I find a survey that fulfills the three requirements?
submitted by /u/Puzzleheaded_Steak54
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Can anyone please suggest some websites to get healthcare data with a 10k records and 20 indipendente variables.
submitted by /u/anil_6
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Greetings everyone! I am looking for a Body dataset which contains images and their measurements. Please do let me know if you do find one.
P.S: I have already know about Kaggle and Hugging face body measurement dataset. I am looking for a bigger dataset not just 20 rows.
Thank you!
submitted by /u/Neither-Bag-696
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Hi everyone, I appreciate any help you can give here. If you think there’s a better place to post this, that would be incredibly helpful, as well. Thanks in advance!
The Ask
Now, here’s the situation: I’m working on an analysis of the workloads of some real estate-specific “groups” in NYC. I’m trying to find datasets that might help me better understand and quantify the time and effort put into menial and repetitive tasks that could be automated.
I’m particularly interested in the apartment rental market, but sales data would also be helpful here.
The Problem
Here are some of the questions I’m trying to answer:
How many inquiries does a typical listing receive across all channels (phone, email, text, listing site — e.g. StreetEasy, Zillow — etc.) from listing to close? (An “inquiry” being defined as a potential lead doing something to initiate communication with an agent or the property like asking a question, requesting a tour, etc.) How many back-and-forths does each channel receive — i.e. how many messages or phone calls, on average, does each inquiry (lead) yield? (This is essentially a follow up to the first question. For example, how many emails are sent by both parties before a showing schedule is confirmed?) How much time is spent on non-transaction related communications like answering basic questions, coordinating with owners to set up a showing (scheduling), sending requests for information or follow up, etc.? (This is essentially just the former questions represented in a different dimension: time instead of volume.)
Target Cohorts and Parameters
As I mentioned, I’m looking for data specific to New York City and the rental market; however, data from other markets could be helpful so I’m open to other markets if there’s a change I might be able to infer data about NYC from it. For example, national data could be helpful in at least setting some anchors/context.
The data I’m seeking should be specific to:
Real estate agents (brokerage-level stats could be subbed in potentially) Buildings/Property Groups (loosely, could be property managers or management companies)
What I’ve tried
This is an opaque industry, at best. While I’ve found some indirect data from sources like the NAR and StreetEasy (see below), I really haven’t had any luck finding anything.
Here are some of the closest examples I’ve found (with some notes roughly outlining relevant data I could try to use):
2022 Home Buyers and Sellers Generational Trends Report (NAR; industry report) Exhibit 4-8 (contact methods and response rate for home buyers) maybe. It’s somewhat unclear how to read, but there might be value in this 2023 Home Buyers and Sellers Generational Trends Report (NAR; industry report) Same as for the 2022 report
Most of the other sources I’d have thought would have something (StreetEasy, REBNY) have turned up woefully inadequate. It just doesn’t seem to be something they track (or at least release publicly).
Asks (summary)
Recommendations on datasets that might be helpful to me. Ideas about how I might reframe this and find data indirectly — e.g. number of inquiries an average renter sends before finding an apartment.
Thanks again for any help here! Really appreciate it.
submitted by /u/humanatwork
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I’ve been looking for a while in the internet and only got 150 plus for both of the class, so I am trying my luck here to find more information if anyone has a link that I can download. It is for thesis purposes not commercial.
submitted by /u/leanzky
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As I said at title I need a dataset about cargo logistic processes. I want to examine cargo’s delivery performance in term of delivery time, right location etc. I looked for dataset at Kaggle, Github etc. but could not find yet.
Thank you in advice.
submitted by /u/data_sapien
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Hi! Does anyone know of a publicly available dataset that includes a debt collection variable?
submitted by /u/MomentsOfHope
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Anyone know where to find property level data at the county/zip code level? Hoping for sale price, # of beds/baths, sqft, etc.. Any help is greatly appreciated!
submitted by /u/88dontrape
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In today’s AI-driven world, data reigns supreme, fueling innovation and propelling technological advancements. However, a pressing challenge persists: the fragmented nature of data sources. Despite the abundance of data generated daily, accessing high-quality and diverse datasets remains a daunting task, impeding progress in AI/ML training and development.
The current situation of data sources is characterized by siloed datasets, proprietary restrictions, and limited accessibility. While large corporations and tech giants may have access to extensive datasets, smaller organizations and researchers often struggle to find relevant and comprehensive data for their projects. This scarcity of data not only impedes innovation but also exacerbates inequalities in the AI landscape, favoring those with access to privileged data sources.
Compounding this issue is the lack of compensation for data contributors, creating a lose-lose situation for all parties involved. However, platforms like Ocean, Streamr, and the emerging Nuklai are changing the game by offering compensation for data contributors and providing decentralized marketplaces for data enthusiasts.
Ocean Protocol leads the charge with its decentralized data exchange protocol, enabling secure and privacy-preserving data sharing. Through Ocean Market, users can discover, publish, and consume data assets transparently and in a decentralized manner, addressing the challenge of fragmented data by facilitating seamless data exchange across ecosystems.
On the other hand, Nuklai emerges as a disruptive force, leveraging blockchain technology to create a transparent and inclusive ecosystem for data storage, sharing, and monetization. By empowering data contributors to retain control over their data and receive fair compensation, Nuklai fosters more interaction and metadata availability, especially within data consortiums.
Meanwhile, Streamr stands out for its emphasis on real-time data monetization, providing a decentralized marketplace where users can stream and sell their data streams. With a focus on IoT (Internet of Things) data, Streamr enables devices to securely share data and receive instant compensation. Its data marketplace fosters innovation by providing a platform for buyers and sellers to engage in data transactions, thereby addressing the growing demand for timely and actionable data insights.
While all of these platforms offer unique features and strengths, they collectively contribute to the broader goal of democratizing data access and driving innovation in the AI/ML space. By fostering collaboration, transparency, and fair compensation, these decentralized data protocols are reshaping the data landscape and paving the way for a more inclusive and equitable data economy.
submitted by /u/kuonanaxu
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