Context

Stack Overflow is the largest online community for programmers to learn, share their knowledge, and advance their careers.

Content

Updated on a quarterly basis, this BigQuery dataset includes an archive of Stack Overflow content, including posts, votes, tags, and badges. This dataset is updated to mirror the Stack Overflow content on the Internet Archive, and is also available through the Stack Exchange Data Explorer.

Fork this kernel to get started with this dataset.

Acknowledgements

Dataset Source: https://archive.org/download/stackexchange

https://bigquery.cloud.google.com/dataset/bigquery-public-data:stackoverflow

https://cloud.google.com/bigquery/public-data/stackoverflow

Banner Photo by Caspar Rubin from Unplash.

Inspiration

What is the percentage of questions that have been answered over the years?

What is the reputation and badge count of users across different tenures on StackOverflow?

What are 10 of the “easier” gold badges to earn?

Which day of the week has most questions answered within an hour?

StackOverflow Posts Markdown

  Dataset Summary

This dataset contains all posts submitted to StackOverflow before the 14th of June 2023 formatted as Markdown text. The dataset contains ~60 Million posts, totaling ~35GB in size and ~65 billion characters of text. The data is sourced from Internet Archive StackExchange Data Dump.

  Dataset Structure

Each record corresponds to one post of a particular type. Original ordering from the data dump is not exactly preserved… See the full description on the dataset page: https://huggingface.co/datasets/mikex86/stackoverflow-posts.

In May 2024 over 65,000 developers responded to Stack Overflow's annual survey about coding, working, AI and how they feel about all of those topics and more.

There were seven sections in this survey. The 2nd, 3rd, 4th, and 5th sections will appear in a random order.

1. Basic Information
2. Education, Work, and Career
3. Technology and Tech Culture
4. Stack Overflow Usage + Community
5. Artificial Intelligence
6. Professional Developer Series (Optional)
7. Final Questions

c17hawke/stackoverflow-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

In May 2023 over 90,000 developers responded to the Stack Overflow annual survey about how they learn and level up, which tools they're using, and which ones they want.

The dataset is a collection of two CSV files and the original survey questionnaire as described below: - survey_results_schema.csv - contains 78 rows and 6 columns covering the basic schema of the survey.

• survey_results_public.csv- contains 89184 rows and 84 columns covering different questions related to users and tools they want to explore.

This dataset is good enough for exploration, and basic data analysis purposes. Alongside, Kagglers can try hands-on to solve some NLP problems as well.

Stack Overflow Dataset

This dataset contains badge awards earned by users on Stack Overflow between January 1, 2022, and December 31, 2023. It includes 3,336 sequences with 187,836 events and 25 badge types, derived from the Stack Exchange Data Dump under the CC BY-SA 4.0 license. The detailed data preprocessing steps used to create this dataset can be found in the TPP-LLM paper and TPP-Embedding paper. Update (2025-10-28): Added three timestamp fields (timestamp_event… See the full description on the dataset page: https://huggingface.co/datasets/tppllm/stack-overflow.

Dataset Card for Stack Overflow Chat Dutch

  Dataset Summary

This dataset contains 56,964 conversations between een AI assistant and a (fake) "Human" (generated) in Dutch, specifically in the domain of programming (Stack Overflow). They are translations of Baize's machine-generated answers to the Stack Overflow dataset. ☕ Want to help me out? Translating the data with the OpenAI API, and prompt testing, cost me 💸$133.60💸. If you like this dataset, please consider buying… See the full description on the dataset page: https://huggingface.co/datasets/BramVanroy/stackoverflow-chat-dutch.

RP-commenting-practices-multiple-sources

Replication package for the paper "What do Developers Discuss about Code Comments?"

Structure

Appendix.pdf
Tags-topics.md
Stack-exchange-query.md

RQ1/
  LDA_input/
    combined-so-quora-mallet-metadata.csv
    topic-input.mallet

  LDA_output/
    Mallet/
      output_csv/
        docs-in-topics.csv
        topic-words.csv
        topics-in-docs.csv
        topics-metadata.csv
      output_html/
        all_topics.html
        Docs/
        Topics/

RQ2/
  datasource_rawdata/
    quora.csv
    stackoverflow.csv
  manual_analysis_output/
    stackoverflow_quora_taxonomy.xlsx

Contents of the Replication Package

• Appendix.pdf- Appendix of the paper containing supplement tables

• Tags-topics.md tags selected from Stack overflow and topics selected from Quora for the study (RQ1 & RQ2)

• Stack-exchange-query.md the query interface used to extract the posts from stack exchnage explorer.

• RQ1/ - contains the data used to answer RQ1

  • LDA_input/ - input data used for LDA analysis
  • combined-so-quora-mallet-metadata.csv - Stack overflow and Quora questions used to perform LDA analysis
  • topic-input.mallet - input file to the mallet tool
  • LDA_output/
  • Mallet/ - contains the LDA output generated by MALLET tool
    • output_csv/
      • docs-in-topics.csv - documents per topic
      • topic-words.csv - most relevant topic words
      • topics-in-docs.csv - topic probability per document
      • topics-metadata.csv - metadata per document and topic probability
    • output_html/ - Browsable results of mallet output
      • all_topics.html
      • Docs/
      • Topics/

• RQ2/ - contains the data used to answer RQ2

  • datasource_rawdata/ - contains the raw data for each source
  • quora.csv - contains the processed dataset (like removing html tags). To know more about the preprocessing steps, please refer to the reproducibility section in the paper. The data is preprocessed using Makar tool.
  • stackoverflow.csv - contains the processed stackoverflow dataset. To know more about the preprocessing steps, please refer to the reproducibility section in the paper. The data is preprocessed using Makar tool.
  • manual_analysis_output/
  • stackoverflow_quora_taxonomy.xlsx - contains the classified dataset of stackoverflow and quora and description of taxonomy.
    • Taxonomy - contains the description of the first dimension and second dimension categories. Second dimension categories are further divided into levels, separated by | symbol.
    • stackoverflow-posts - the questions are labelled relevant or irrelevant and categorized into the first dimension and second dimension categories.

      - quota-posts - the questions are labelled relevant or irrelevant and categorized into the first dimension and second dimension categories.

Overview The Stack Overflow Developer Survey Dataset represents one of the most trusted and comprehensive sources of information about the global developer community. Collected by Stack Overflow through its annual survey, the dataset provides insights into the demographics, preferences, habits, and career paths of developers.

This dataset is frequently used for: - Analyzing trends in programming languages, tools, and technologies. - Understanding developer job satisfaction, compensation, and work environments. - Studying global and regional differences in developer demographics and experience.

The data has of two CSV files, "survey_results_public" that consist of data and "survey_results_schema" that describes each column in detail.

Data Dictionary: All the details are in "survey_results_schema.csv"

Features of the Stack Overflow Developer Survey Dataset

Demographic & Background Information - Respondent: A unique identifier for each survey participant. - MainBranch: Describes whether the respondent is a professional developer, student, hobbyist, etc. - Country: The country where the respondent lives. - Age: The respondent's age. - Gender: The gender identity of the respondent. - Ethnicity: Ethnic background (when available). - EdLevel: The highest level of formal education completed. - UndergradMajor: The respondent's undergraduate major. - Hobbyist: Indicates whether the person codes as a hobby (Yes/No).

Employment & Professional Experience - Employment: Employment status (full-time, part-time, unemployed, student, etc.). - DevType: Types of developer roles the respondent identifies with (e.g., Web Developer, Data Scientist). - YearsCode: Number of years the respondent has been coding. - YearsCodePro: Number of years coding professionally. - JobSat: Job satisfaction level. - CareerSat: Career satisfaction level. - WorkWeekHrs: Approximate hours worked per week. - RemoteWork: Whether the respondent works remotely and how frequently.

Compensation - CompTotal: Total compensation in USD (including salary, bonuses, etc.). - CompFreq: Frequency of compensation (e.g., yearly, monthly).

Learning & Education - LearnCode: How the respondent first learned to code (e.g., online courses, university). - LearnCodeOnline: Online resources used (e.g., YouTube, freeCodeCamp). - LearnCodeCoursesCert: Whether the respondent has taken online courses or earned certifications.

Technology & Tools - LanguageHaveWorkedWith: Programming languages the respondent has used. - LanguageWantToWorkWith: Languages the respondent is interested in learning or using more. - DatabaseHaveWorkedWith: Databases the respondent has experience with. - PlatformHaveWorkedWith: Platforms used (e.g., Linux, AWS, Android). - OpSys: The operating system used most often. - NEWCollabToolsHaveWorkedWith: Collaboration tools used (e.g., Slack, Teams, Zoom). - NEWStuck: How often the respondent feels stuck when coding. - ToolsTechHaveWorkedWith: Frameworks and technologies respondents have worked with.

Online Presence & Community - SOAccount: Whether the respondent has a Stack Overflow account. - SOPartFreq: How often the respondent participates on Stack Overflow. - SOVisitFreq: Frequency of visiting Stack Overflow. - SOComm: Whether the respondent feels welcome in the Stack Overflow community. - OpenSourcer: Level of involvement in open-source contributions.

Opinions & Preferences - WorkChallenge: Challenges faced at work (e.g., unclear requirements, unrealistic expectations). - JobFactors: Important job factors (e.g., salary, work-life balance, technologies used). - MentalHealth: Questions on how mental health affects or is affected by their job.

BigQuery dataset includes an archive of Stack Overflow content, including posts, votes, tags, and badges.

mteb/stackoverflow-qa dataset hosted on Hugging Face and contributed by the HF Datasets community

mlfoundations-dev/stackoverflow dataset hosted on Hugging Face and contributed by the HF Datasets community

Stack Overflow is the largest online community for programmers to learn, share their knowledge, and advance their careers. Updated on a quarterly basis, this BigQuery dataset includes an archive of Stack Overflow content, including posts, votes, tags, and badges. This dataset is updated to mirror the Stack Overflow content on the Internet Archive, and is also available through the Stack Exchange Data Explorer. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

--Collective intelligence constitutes a foundational element within online community question-and-answering (CQA) platforms, such as Stack Overflow, being the source of most programming-related issues. Despite this relevance, concerns remain regarding issues surrounding user participation. Precedent research tends to focus on simple numerical measurements to analyse participation, which may sideline the inherent, subtler aspects.

The proposed study aims to bridge this gap by operationalising 11 distinct metrics to represent user participation, behaviour, and community value across different regions of the USA. The study also conducts inductive content analysis to understand the impact of regional contextual factors on users' knowledge sharing patterns.

This replication package is provided for those interested in further examining our research methodology.

About this Dataset

Every year, Stack Overflow conducts a massive survey of people on the site, covering all sorts of information like programming languages, salary, code style and various other information. This year, they amassed more than 64,000 responses fielded from 213 countries. Data The data is made up of two files: 1. survey_results_public.csv - CSV file with main survey results, one respondent per row and one column per answer 2. survey_results_schema.csv - CSV file with survey schema, i.e., the questions that correspond to each column name m Acknowledgements Data is directly taken from StackOverflow and licensed under the ODbL license.

Category

Surveys

Keywords

internet,Information Technology,coding

Row Count

51248

Price

Free

This data set is from Stack Overflow from a Survey held in May 2024. Over 65000 responded to this survey and answered questions , about the work, AI, coding, program language, experiences, etc.

Image used from - https://www.passionateinmarketing.com/fastest-growing-programming-languages/

CSV- Downloaded from - https://survey.stackoverflow.co/ (copy and paste in new tab, seems otherwise not to open the correct page.

There are 114 Columns with lots of Data, useful and maybe less. I have done the Notebook 1st and is now published, and make this database public as part of my learning Process to see if this works as should.

Finished 3 different note books and this database. But I am sure you will be able to get more out of it, But please review mine and share feedback.

This dataset contains valid pylint results for all Stack Overflow code snippets from SOTorrent that meet the following criteria

Tagged with 'python'

6 lines and above

Contains basic python syntax (i.e. 'print', 'import', '(', '=')

Produces a result when processed by Pylint

Stack Overflow, often recognized as the go-to resource for software practitioners, has seen a growing trend of discussions around academic research. Yet, little is known about these academic references and how they intersect developers’ needs and interests. To bridge this gap, we presented a novel approach for identifying academic reference links and curated the first comprehensive dataset of academic references on Stack Overflow.This dataset contains 19,582 academic references mined from Stack Overflow posts, answers, comments, etc. as of October 7, 2024.

This data set contains anonymized data collected from Reddit (via the Pushshift API) and StackOverflow (from Kaggle's dataset).

Each folder includes the data split by trimester. The schema of StackOverflow and Reddit-related files follows:

• Fields from StackOverflow
  • question_id
  • answer_id
  • creation_date - answer creation_date
  • score - score of the question/answer
  • tags - all tags flagged for a question
  • answer_count - number of answers for a question
  • start_question - question's time of creation
  • last_activity_date - last update on the question
  • new_id - hashed id of the answerer
  • q_new_id - hashed id of the questioner
• Fields from Reddit
  • comment_id
  • submission_id
  • score - score of the question/submission
  • subreddit
  • created_utc - time of creation (unrelated to last modified comments)
  • new_id - hashed id

The .txt files represent the structure of the corresponding hypergraphs.

The purpose of this dataset is to provide the opportunity to perform any training, fine-tuning, etc. for any Language Model. In the 'data' folder, you will find the dataset in Parquet format, which is one of the formats used for these processes. In case it may be useful for other purposes, I have also included the dataset in CSV format. All data in this dataset were retrieved from the Stack Exchange network using the Stack Exchange Data explorer tool… See the full description on the dataset page: https://huggingface.co/datasets/mcipriano/stackoverflow-kubernetes-questions.