results.yml

locale: en-US
translations:
  ###########################################################################
  # General
  ###########################################################################

  - key: results.start
    t: Start

  - key: page.previous
    t: "Previous:"
  - key: page.next
    t: "Next:"

  - key: general.state_of_css_link
    t: State of CSS

  - key: general.netlify_link
    t: Hosted on <a href="{link}">Netlify</a>.

  - key: general.completion_percentage
    t: "Completion percentage:"

  - key: sponsors.thanks
    t: Thanks to our partners for supporting us!

  - key: sponsors.learn_more
    t: Learn more.

  - key: tabs.all_respondents
    t: All Respondents
  - key: tabs.main_answers
    t: Main Answers
  - key: tabs.other_answers
    t: Other Answers
  - key: tabs.bracket_wins
    t: Wins
  - key: tabs.bracket_matchups
    t: Matchups
  - key: tabs.chart
    t: Chart
  - key: tabs.data
    t: Data
  - key: tabs.share
    t: Share
  - key: tabs.debug
    t: Debug
  - key: tabs.by_country
    t: By Country
  - key: tabs.by_experience
    t: By Experience
  - key: tabs.by_degree
    t: By Degree
  - key: tabs.by_salary
    t: By Salary
  - key: tabs.by_gender
    t: By Gender

  ###########################################################################
  # Options
  ###########################################################################

  - key: options.experience_ranking.satisfaction
    t: Retention
  - key: options.experience_ranking.interest
    t: Interest
  - key: options.experience_ranking.usage
    t: Usage
  - key: options.experience_ranking.awareness
    t: Awareness

  - key: options.features_mode.grouped
    t: Grouped
  - key: options.features_mode.awareness_rank
    t: By Awareness
  - key: options.features_mode.usage_rank
    t: By Usage
  - key: options.features_mode.usage_ratio_rank
    t: By Ratio

  - key: options.features_simplified.know_it
    t: Know about it
  - key: options.features_simplified.used_it
    t: Have used it
  - key: options.features_simplified.usage_ratio
    t: Ratio

  - key: options.quadrant.assess
    t: ASSESS
  - key: options.quadrant.assess.long
    t: |
      ASSESS: Low usage, high retention. Technologies worth keeping an eye on.
  - key: options.quadrant.adopt
    t: ADOPT
  - key: options.quadrant.adopt.long
    t: |
      ADOPT: High usage, high retention. Safe technologies to adopt.
  - key: options.quadrant.avoid
    t: AVOID
  - key: options.quadrant.avoid.long
    t: |
      AVOID: Low usage, low retention. Technologies probably best avoided currently.
  - key: options.quadrant.analyze
    t: ANALYZE
  - key: options.quadrant.analyze.long
    t: |
      ANALYZE: High usage, low retention. Reassess these technologies if you're currently using them.

  - key: options.quadrant.1
    t: 1
  - key: options.quadrant.1.long
    t: |
      1: Low usage, high retention. Technologies worth keeping an eye on.
  - key: options.quadrant.2
    t: 2
  - key: options.quadrant.2.long
    t: |
      2: High usage, high retention. Safe technologies to adopt.
  - key: options.quadrant.3
    t: 3
  - key: options.quadrant.3.long
    t: |
      3: Low usage, low retention. Technologies that are harder to recommend.
  - key: options.quadrant.4
    t: 4
  - key: options.quadrant.4.long
    t: |
      4: High usage, low retention. Reassess these technologies if you're currently using them.
      
  - key: ranges.selector.years_of_experience
    t: Experience
  - key: ranges.selector.yearly_salary
    t: Salary
  - key: ranges.selector.company_size
    t: Company Size

  # other learning methods
  - key: options.first_steps.blogs
    t: Blogs
  - key: options.first_steps.forums
    t: Forums
  - key: options.first_steps.view_source
    t: View Source
  - key: options.first_steps.copy_paste
    t: Copy/paste
  - key: options.first_steps.trial_and_error
    t: Trial & Error
  - key: options.first_steps.documentation
    t: Documentation

  # other disablities
  - key: options.disability_status_others.adhd
    t: ADHD
  - key: options.disability_status_others.autism
    t: Autism
  - key: options.disability_status_others.glasses
    t: Glasses
  - key: options.disability_status_others.old
    t: Old Age
  - key: options.disability_status_others.back_pain
    t: Back Pain
  - key: options.disability_status_others.epilepsy
    t: Epilepsy
  - key: options.disability_status_others.aspergers
    t: Aspergers
  - key: options.disability_status_others.color_blindness
    t: Color Blindness
  - key: options.disability_status_others.anxiety
    t: Anxiety
  - key: options.disability_status_others.dyslexia
    t: Dyslexia
  - key: options.disability_status_others.diabetes
    t: Diabetes
  - key: options.disability_status_others.carpal_tunnel
    t: Carpal Tunnel
  - key: options.disability_status_others.migraine
    t: Migraine
  - key: options.disability_status_others.speech_impairment
    t: Speech Impairment
  - key: options.disability_status_others.ocd
    t: OCD
  - key: options.disability_status_others.chronic_pain
    t: Chronic Pain
  - key: options.disability_status_others.chronic_fatigue
    t: Chronic Fatigue
  - key: options.disability_status_others.crohn
    t: Crohn's
    
  ###########################################################################
  # Sections
  ###########################################################################

  - key: sections.introduction.title
    t: Introduction

  - key: sections.demographics.title
    t: Demographics

  - key: sections.tshirt.title
    t: T-shirt

  - key: sections.technologies.title
    t: Technologies

  - key: sections.libraries.title
    t: Libraries

  - key: sections.conclusion.title
    t: Conclusion

  - key: sections.about.title
    t: About

  - key: sections.how_to_help.title
    t: How to Help

  - key: sections.support.title
    t: Support Us
  - key: sections.support.description
    t: >
      We run this survey as a side project, but in order to make the
      project sustainable we’re always looking for partners who can help support us,
      either financially or by helping us spread the word.
      If you think you could help in any way, please don’t hesitate to [get in touch](mailto:hello@stateofjs.com)!

  - key: sections.awards.title
    t: Awards
  - key: sections.awards.description
    t: Things that stood out this year.

  ###########################################################################
  # User Info
  ###########################################################################

  - key: user_info.locale
    t: Language
  - key: user_info.locale.description
    t: What language did respondents select to fill out the survey?
  - key: user_info.locale.note
    t: >
      This data is collected automatically based on respondent's settings while taking the survey; 
      Languages with fewer than 20 respondents not shown.

  - key: user_info.source
    t: Source
  - key: user_info.source.description
    t: How did respondents find out about the survey?
  - key: user_info.source.note
    t: Respondent source is computed based on referrer data, URL tracking data, and self-reported answers.

  - key: user_info.gender_by_country
    t: Gender By Country
  - key: user_info.gender_by_country.description
    t: Gender distribution by country with at least 100 respondents, sorted by "mean gender" (each gender key being assigned an integer value in ascending order) descending.

  - key: user_info.years_of_experience_by_salary
    t: Years of Experience by Salary Range
  - key: user_info.years_of_experience_by_salary.description
    t: Years of experience by salary range.

  - key: user_info.yearly_salary_by_country
    t: Salary By Country
  - key: user_info.yearly_salary_by_country.description
    t: Yearly salary distribution by country with at least 100 respondents, sorted by mean salary descending.

  - key: user_info.yearly_salary_by_degree
    t: Salary By Higher Education Degree
  - key: user_info.yearly_salary_by_degree.description
    t: Yearly salary distribution by higher education degree, sorted by mean salary descending.

  - key: user_info.yearly_salary_by_experience
    t: Salary By Experience
  - key: user_info.yearly_salary_by_experience.description
    t: Yearly salary distribution by experience, sorted by mean salary descending.

  - key: user_info.race_ethnicity_by_years_of_experience
    t: Race & Ethnicity by Years of Experience
  - key: user_info.race_ethnicity_by_years_of_experience.description
    t: Race & ethnicity distribution by years of experience, sorted by mean experience ascending.

  - key: user_info.higher_education_degree_by_gender
    t: Higher Education Degree by Gender
  - key: user_info.higher_education_degree_by_gender.description
    t: Higher education degree distribution by gender.

  ###########################################################################
  # Locales
  ###########################################################################

  - key: options.locale.en-US
    t: English
  - key: options.locale.ca-ES
    t: Catalan
  - key: options.locale.es-ES
    t: Spanish
  - key: options.locale.ru-RU
    t: Russian
  - key: options.locale.fr-FR
    t: French
  - key: options.locale.zh-Hant
    t: Chinese (Traditional)
  - key: options.locale.de-DE
    t: German
  - key: options.locale.cs-CZ
    t: Czech
  - key: options.locale.pt-PT
    t: Portuguese
  - key: options.locale.pt-BR
    t: Portuguese (Brazil)
  - key: options.locale.it-IT
    t: Italian
  - key: options.locale.sv-SE
    t: Swedish
  - key: options.locale.tr-TR
    t: Turkish
  - key: options.locale.id-ID
    t: Indonesian
  - key: options.locale.hi-IN
    t: Hindi
  - key: options.locale.zh-Hans
    t: Chinese (Simplified)
  - key: options.locale.ja-JP
    t: Japanese
  - key: options.locale.ua-UA
    t: Ukrainian
  - key: options.locale.pl-PL
    t: Polish
  - key: options.locale.fa-IR
    t: Farsi
  - key: options.locale.nl-NL
    t: Dutch
  - key: options.locale.ko-KR
    t: Korean
  - key: options.locale.ro-RO
    t: Romanian

  ###########################################################################
  # Features
  ###########################################################################

  - key: features.learn_more
    t: Learn More (MDN)
  - key: features.mdn_link
    t: MDN
  - key: features.caniuse_link
    t: Can I use
  - key: features.specification_link
    t: W3C Specification

  # knowledge score
  - key: features.knowledge_score
    t: Knowledge Score
  - key: features.knowledge_score.description
    t: Out of all the features mentioned in the survey, how many did the respondent know about?

  ###########################################################################
  # Tools & Methodologies
  ###########################################################################

  # general
  - key: tools.links
    t: Links
  - key: tools.github_link
    t: GitHub
  - key: tools.github_stars
    t: stars
  - key: tools.homepage_link
    t: Homepage
  - key: tools.npm_link
    t: NPM
  - key: tools.technology
    t: Technology

  ###########################################################################
  # Blocks
  ###########################################################################

  # heatmaps
  - key: blocks.tools_company_size_heatmap
    t: Usage by Company Size
  - key: blocks.tools_company_size_heatmap.description
    t: |
      For each technology, how usage is spread among respondents
      who picked different company size ranges.

  - key: blocks.tools_yearly_salary_heatmap
    t: Usage by Salary Range
  - key: blocks.tools_yearly_salary_heatmap.description
    t: |
      For each technology, how usage is spread among respondents
      who picked different salary ranges.

  - key: blocks.tools_years_of_experience_heatmap
    t: Usage by Years Of Experience
  - key: blocks.tools_years_of_experience_heatmap.description
    t: |
      For each technology, how usage is spread among respondents who picked different experience ranges.
      Note that the experience in question here is general experience, not experience with a specific technology.

  # tool
  - key: blocks.entity.homepage_link
    t: Homepage
  - key: blocks.entity.github_link
    t: GitHub

  # cardinality
  - key: blocks.all_sections_tools_cardinality_by_user
    t: Technology Usage Cardinality
  - key: blocks.all_sections_tools_cardinality_by_user.description
    t: >
        For each section, which percentage of respondents **use** 
        (defined as having answered “would use again”) one, two, three, etc. technologies.
        The bottom-most bar represents the sum of all other bars.  

  - key: blocks.cardinality.max
    t: Most common answer

  # tools arrows
  - key: blocks.tools_arrows
    t: Changes Over Time
  - key: blocks.tools_arrows.description
    t: |
      Each line goes from 2016 to 2020. A higher point means a technology has been used by more people,
      and a point further to the right means more users want to learn it; or have used it and would use it again.
  - key: blocks.tools_arrows.note
    t: |
      - Some lines skip years.
      - Technologies with only one year of data are not shown. 
      - Velocity formula = (most recent opinion - oldest opinion) + (most recent usage) - (oldest usage)
      - A positive velocity means the usage and/or positive opinions have increased over time.

  # tools quadrant
  - key: blocks.tools_quadrant
    t: Retention vs Usage
  - key: blocks.tools_quadrant.description
    t: |
      This chart shows each technology's **retention ratio** over its total **user count**.
      It can be divided into four quadrants:

        - **ASSESS**: Low usage, high retention. Technologies worth keeping an eye on.

        - **ADOPT**: High usage, high retention. Safe technologies to adopt.

        - **AVOID**: Low usage, low retention. Technologies probably best avoided currently.

        - **ANALYZE**: High usage, low retention. Reassess these technologies if you're currently using them.

  # category other tools
  - key: blocks.category_other_tools
    t: Other Tools
  - key: blocks.category_other_tools.description
    t: Other tools in this category (freeform answers).

  # tool experience
  - key: blocks.tool_experience
    t: "{name} Experience"
  - key: blocks.tool_experience.description
    t: Respondent's experience with {name}.

  # tool positive/negative split ("marimekko" chart)
  - key: blocks.tools_experience_marimekko
    t: Sentiment Split
  - key: blocks.tools_experience_marimekko.description
    t: |
      This chart splits positive (“want to learn”, “would use again”) vs
      negative (“not interested”, “would not use again”) experiences on
      both sides of the central axis.
      
      Bar thickness represents the number of respondents aware of a technology.
      Click on the individual label to see more details.

  # tool tier list
  - key: blocks.tools_tier_list
    t: Library Tier List
  - key: blocks.tools_tier_list.description
    t: |
      This chart ranks libraries based on their retention ratio (percentage of users
      who would use a library again). Note that libraries used by less than 10% of survey 
      respondents are not included.
  - key: blocks.tools_tier_list.bounds
    t: >
      {lowerBound}% - {upperBound}%

  # tools section streams
  - key: blocks.tools_section_streams
    t: Experience Over Time
  - key: blocks.tools_section_streams.description
    t: |
      Overview of opinions on the technologies surveyed over time.
  - key: blocks.tools_section_streams.note
    t: |
      Technologies with only one year of data are not included.

  # tools section overview
  - key: blocks.tools_section_overview
    t: Category Overview
  - key: blocks.tools_section_overview.description
    t: |
      Overview of opinions on the technologies surveyed. Darker segments represent positive opinions,
      while lighter segments correspond to negative sentiment.

  # tools experience ranking
  - key: blocks.tools_experience_ranking
    t: Ranking
  - key: blocks.tools_experience_ranking.percentages
    t: Percentages
  - key: blocks.tools_experience_ranking.rankings
    t: Rankings
  - key: blocks.tools_experience_ranking.description
    t: Retention, interest, usage, and awareness ratio rankings.
  - key: blocks.tools_experience_ranking.note
    t: |
      Technologies with less than 10% awareness not included. <br/> Each ratio is defined as follows:
      - <span class='formula'> Retention = &nbsp;<div class='fraction'><div class='num'>would use again</div><div class='denom'>( would use again + would not use again )</div></div></span>
      - <span class='formula'> Interest = &nbsp;<div class='fraction'><div class='num'>want to learn</div><div class='denom'>( want to learn + not interested )</div></div></span>
      - <span class='formula'> Usage = &nbsp;<div class='fraction'><div class='num'>( would use again + would not use again )</div><div class='denom'>total</div></div></span>
      - <span class='formula'> Awareness = &nbsp;<div class='fraction'><div class='num'>( total - never heard )</div><div class='denom'>total</div></div></span>

  # tools experience linechart
  - key: blocks.tools_experience_linechart
    t: Experience Over Time
  - key: blocks.tools_experience_linechart.description
    t: Retention, interest, usage, and awareness ratio over time.
  - key: blocks.tools_experience_linechart.note
    aliasFor: blocks.tools_experience_ranking.note
  - key: blocks.animations_other
    t: Other graphics and animations solutions

  # happiness
  - key: blocks.happiness
    t: Overall Happiness
  - key: blocks.happiness.description
    t: |
      On a scale of one (very unhappy) to five (very happy), how happy are developers
      with the current overall state of this category?

  # newsletter
  - key: blocks.newsletter.title
    t: Stay Tuned
  - key: blocks.newsletter.description
    t: |
      If you'd like to know when we release additional results or announce next year's edition,
      just leave us your email below:
  - key: blocks.newsletter.email
    t: Your Email
  - key: blocks.newsletter.submit
    t: Notify Me

  # features_overview
  - key: blocks.features_overview
    t: Features Overview
  - key: blocks.features_overview.description
    t: |
      The size of the **outer circle** corresponds to the total number of users who know about a feature (*know about it* + *have used it* respondents), while
      the **inner circle** represents those who have actually used it (*have used it* respondents).

      Hover on each circle to see detailed stats, including the ratio between both values. 

  # export
  - key: export.export
    t: Export
  - key: export.title
    t: Export data for {title}
  - key: export.nocsv
    t: Sorry, CSV export is not available for this dataset.
  - key: export.graphql
    t: >
      You can copy paste this query into our <a target="_blank" rel="nofollow" href="https://graphiql.devographics.com/">public GraphQL API</a>.
  - key: export.export_json
    t: Get JSON Data
  - key: export.export_graphql
    t: Get GraphQL Query

  - key: custom_data.heading
    t: Custom Chart
  - key: custom_data.custom_data
    t: Custom Data
  - key: custom_data.graphql_query
    t: GraphQL Query
  - key: custom_data.chart_title
    t: Custom Chart
  - key: custom_data.submit
    t: Submit
  - key: custom_data.empty_contents
    t: Please enter some data in the "Custom Data" field.
  - key: custom_data.edit_title
    t: Edit Chart Title
  - key: custom_data.customize
    t: Customize Data
  - key: custom_data.details
    t: >

        1. Copy the contents of the "GraphQL Query" textfield and paste them into the middle panel of the [GraphQL API explorer](https://graphiql.stateofjs.com/).

        2. Modify the query by adding one or more **filters** using the left-hand explorer sidebar. Make sure to keep the overall structure of the data the same.

        3. In the explorer window, click the Play ("Execute Query") button.

        4. Copy the results of the modified query (`{ data: … }` ) into the "Custom Data" textfield above and submit.

  # Tools usage variations
  - key: blocks.tools_usage_variations
    t: Usage Variations
  - key: blocks.tools_usage_variations.description
    t: |
      How different factors such as salary range, years of experience
      or company size influence usage (participants who answered either
      “would use again” or “would not use again”).

      The baseline represents the base usage for each tool and the offsets
      correspond to the delta from this baseline in each range. Let's say
      tool X has an overall usage of 10% across all respondents (the baseline),
      then if the percentage of users having from 1 to 2 years of experience
      using this tool is 13% (compared to all users having from 1 to 2 years
      of experience), then we have a positive delta of +3%.
  - key: blocks.tools_usage_variations.note
    t: |
      Please keep in mind that tools having a lower overall usage tends to vary more.

  # Recommended Resources
  - key: blocks.recommended_resources
    t: Recommended Resources
  - key: blocks.recommended_events
    t: Recommended Events

  # Brackets
  - key: tool_evaluation.tool_evaluation_wins
    t: Library Evaluation Rankings
  - key: tool_evaluation.tool_evaluation_wins.description
    t: Which factors do you prioritize when evaluating a new library? Results are ranked by number of tournament rounds won.

  - key: tool_evaluation.tool_evaluation_matchups
    t: Library Evaluation Rankings (Matchups)
  - key: tool_evaluation.tool_evaluation_matchups.description
    t: Which factors do you prioritize when evaluating a new library? Percentage of rounds won by left-hand item against top-side item.

  # other
  - key: blocks.freeform
    t: (freeform question)

  ###########################################################################
  # Charts
  ###########################################################################

  - key: chart_units.respondents
    t: "{count} question respondents ({percentage}% completion percentage)"
  - key: chart_units.percentage
    t: Percents
  - key: chart_units.count
    t: Count
  - key: chart_units.percentage_question
    t: "% of question respondents"
  - key: chart_units.percentage_survey
    t: "% of survey respondents"

  - key: charts.average
    t: Average
  - key: charts.mean
    t: Mean
  - key: charts.overall
    t: Overall
  - key: charts.all_respondents
    t: All Respondents
  - key: charts.facet_responses
    t: '{count} responses'

  - key: charts.axis_legends.years_of_experience
    t: Years of Experience
  - key: charts.axis_legends.yearly_salary
    t: Salary Range (USD)
  - key: charts.axis_legends.company_size
    t: Number of Employees
  - key: charts.axis_legends.backend_proficiency
    t: Back-end Proficiency
  - key: charts.axis_legends.css_proficiency
    t: CSS Proficiency
  - key: charts.axis_legends.javascript_proficiency
    t: JavaScript Proficiency
  - key: charts.axis_legends.users_percentage
    t: Percentage of Users
  - key: charts.axis_legends.users_count
    t: User Count
  - key: charts.axis_legends.interest_percentage
    t: Interest %
  - key: charts.axis_legends.satisfaction_percentage
    t: Retention %
  - key: charts.axis_legends.usage_percentage
    t: Usage %
  - key: charts.axis_legends.awareness_percentage
    t: Awareness %

  - key: chart_units.interest_percentage
    aliasFor: charts.axis_legends.interest_percentage
  - key: chart_units.satisfaction_percentage
    aliasFor: charts.axis_legends.satisfaction_percentage
  - key: chart_units.usage_percentage
    aliasFor: charts.axis_legends.usage_percentage
  - key: chart_units.awareness_percentage
    aliasFor: charts.axis_legends.awareness_percentage
    
  - key: charts.axis_legends.happiness
    t: Happiness
  - key: charts.axis_legends.knowledge_score
    t: Known Features
  - key: charts.axis_legends.frequency
    t: Frequency
  - key: charts.axis_legends.age
    t: Age
  - key: charts.axis_legends.users_percentage_survey
    t: "% of survey respondents"
  - key: charts.axis_legends.users_percentage_question
    t: "% of question respondents"

  - key: charts.ranges_multiple_diverging_lines.baseline
    t: baseline
  - key: charts.ranges_multiple_diverging_lines.positive_offset
    t: positive offset
  - key: charts.ranges_multiple_diverging_lines.negative_offset
    t: negative offset

  - key: charts.tools_arrows.negative_opinion
    t: Negative opinions
  - key: charts.tools_arrows.positive_opinion
    t: Positive opinions
  - key: charts.tools_arrows.have_not_used
    t: Have not used
  - key: charts.tools_arrows.have_used
    t: Have used
  - key: charts.tools_arrows.x_axis
    t: X-axis range
  - key: charts.tools_arrows.y_axis
    t: Y-axis range
  - key: charts.tools_arrows.legend
    t: Legend
  - key: charts.tools_arrows.velocity
    t: Velocity
  - key: charts.tools_arrows.velocity_positive
    t: Overall more positive opinions and/or usage over time
  - key: charts.tools_arrows.velocity_negative
    t: Overall more negative opinions and/or less usage over time
  - key: charts.tools_arrows.opinions_positive
    t: Mostly positive opinions
  - key: charts.tools_arrows.opinions_negative
    t: Mostly negative opinions
  - key: charts.tools_arrows.low_usage
    t: Low usage
  - key: charts.tools_arrows.high_usage
    t: High usage
  - key: charts.tools_arrows.popularity_positive
    t: Rising popularity
  - key: charts.tools_arrows.popularity_negative
    t: Falling popularity

  - key: charts.no_answer
    t: No Answer

  ###########################################################################
  # Comments
  ###########################################################################

  - key: comments.comments
    t: Comments
  - key: comments.comments_for
    t: Comments for “{name}”
  - key: comments.description
    t: |
      These comments were submitted as part of the survey 
      through an optional freeform text field next to the main question. 
  - key: comments.report_abuse
    t: Report this comment
  - key: comments.share
    t: Share Comment

  ###########################################################################
  # Sharing
  ###########################################################################

  - key: share.share
    t: Share
  - key: share.options
    t: Share Options
  - key: share.preview
    t: Social media preview
  - key: share.site.title
    t: Discover the {siteTitle} results
  - key: share.site.twitter_text
    t: "Discover the {siteTitle} results {link} {hashtag}"
  - key: share.site.subject
    t: "{siteTitle} Survey Results"
  - key: share.site.body
    t: "Here are some interesting survey results: {link}"
  - key: share.block.twitter_text
    t: "{hashtag} {year}: {title} {link}"
  - key: share.block.subject
    t: "{siteTitle} Survey Results"
  - key: share.block.body
    t: "Here are some interesting survey results ({title}): {link}"
  - key: share.twitter
    t: Share on Twitter
  - key: share.facebook
    t: Share on Facebook
  - key: share.linkedin
    t: Share on LinkedIn
  - key: share.email
    t: Share by email
  - key: share.image
    t: Get image
  - key: share.link
    t: Link to section
  - key: share.url
    t: Get link
  - key: share.close
    t: Close

  ###########################################################################
  # Views
  ###########################################################################
  - key: views.viz
    t: Graph
  - key: views.table
    t: Table

  ###########################################################################
  # Tables
  ###########################################################################
  - key: table.label
    t: Label
  - key: table.item
    t: Item
  - key: table.percentage_survey
    t: "% of survey respondents"
  - key: table.percentage_question
    t: "% of question respondents"
  - key: table.percentage_facet
    t: "% of facet respondents"
  - key: table.count
    t: Count
  - key: table.year
    t: Year
  - key: table.mean
    t: Mean
  - key: table.usage
    aliasFor: options.features_simplified.used_it
  - key: table.awareness
    aliasFor: options.features_simplified.know_it
  - key: table.usage_ratio
    aliasFor: options.features_simplified.usage_ratio

  - key: table.usage_count
    aliasFor: charts.axis_legends.users_count
  - key: table.satisfaction_percentage
    aliasFor: charts.axis_legends.satisfaction_percentage
  - key: table.interest_percentage
    aliasFor: charts.axis_legends.interest_percentage
  - key: table.usage_percentage
    aliasFor: charts.axis_legends.usage_percentage
  - key: table.awareness_percentage
    aliasFor: charts.axis_legends.awareness_percentage


  - key: table.percentages_table
    t: Percentages
  - key: table.rankings_table
    t: Rankings

  - key: table.satisfaction_rank
    t: Retention Rank
  - key: table.interest_rank
    t: Interest Rank
  - key: table.usage_rank
    t: Usage Rank
  - key: table.awareness_rank
    t: Awareness Rank

  - key: table.would_not_use_percentage
    t: Would not use %
  - key: table.not_interested_percentage
    t: Not interested %
  - key: table.would_use_percentage
    t: Would use again %
  - key: table.interested_percentage
    t: Interested %

  ###########################################################################
  # Awards
  ###########################################################################

  - key: awards.runner_ups
    t: Runner Ups

  - key: award.feature_adoption_award.title
    t: Most Used Feature
  - key: award.feature_adoption_award.description
    t: Awarded to the most adopted feature.

  - key: award.feature_adoption_delta_award.title
    t: Most Adopted Feature
  - key: award.feature_adoption_delta_award.description
    t: Awarded to the feature with the largest year-over-year ”have used” progression.

  - key: award.tool_usage_award.title
    t: Most Used Technology
  - key: award.tool_usage_award.description
    t: Awarded to the technology with the largest user base.

  - key: award.tool_usage_delta_award.title
    t: Most Adopted Technology
  - key: award.tool_usage_delta_award.description
    t: Awarded to the technology with the largest year-over-year “would use again” progression.

  - key: award.tool_satisfaction_award.title
    t: Highest Retention
  - key: award.tool_satisfaction_award.description
    t: Awarded to the technology with the highest percentage of returning users.

  - key: award.tool_interest_award.title
    t: Highest Interest
  - key: award.tool_interest_award.description
    t: Awarded to the technology developers are most interested in learning once they are aware of it.

  - key: award.resource_usage_award.title
    t: Most Used Resource
  - key: award.resource_usage_award.description
    t: Awarded to the resource with the largest user base.

  - key: award.prediction_award.title
    t: Prediction Award
  - key: award.prediction_award.description
    t: Awarded to an up-and-coming technology that might take over… or not?

  - key: award.most_write_ins_award.title
    t: Most Write-Ins
  - key: award.most_write_ins_award.description
    t: Awarded to the item with the most write-in answers

  - key: award.most_commented_featured_award.title
    t: Most Commented
  - key: award.most_commented_featured_award.description
    t: Awarded to the feature with the most comments.

  ###########################################################################
  # Hints
  ###########################################################################

  - key: hints.hint_hint
    t: >
      You'll find little hints like this one throughout the survey results
      that will point out extra features and details.

  - key: hints.units_switcher_hint
    t: >
      You can use the segmented control at the bottom of each block to switch 
      between different units to get an alternate view of the same data.

  - key: hints.export_hint
    t: >
      The <span class="hint-icon hint-export-button">Data</span> tab lets you view the raw 
      data for any chart, view it as JSON, or get a GraphQL query you can 
      run against our public API.

  - key: hints.completion_hint
    t: >
      Since all questions are optional, some of them got fewer responses than others. 
      The completion indicator (<span class="hint-completion-indicator">◕</span>) tells you exactly how many people answered any given question.

  - key: hints.tool_modal_hint
    t: >
      You can click on any technology name to get extra details and 
      a more in-depth look at its related data.

  - key: hints.rankings_modes_hint
    t: >
      The Experience Over Time chart can be toggled between retention, interest, usage, and awareness
      to give you a fuller picture of a category.

  - key: hints.sharing_hint
    t: >
      Sharing this survey on Twitter, Facebook, or by email is scientifically proven to 
      improve your coding performance by up to 15%.

  - key: hints.tshirt_hint
    t: >
      Another guaranteed scientific finding: buying our t-shirt will 
      increase your programming skills by over 9000!

  - key: hints.variants_hint
    t: >
      Some charts feature additional tabs that offer complementary breakdowns of the same data,
      or related data. Make sure to check them out!

  - key: hints.share_hint
    t: >
      The <span class="hint-icon hint-share-button">Share</span> tab makes it easy to share any chart, 
      or even download it as an image. 

  - key: hints.bracket_hint
    t: >
      <span class="hint-bracket"><span class="hint-text">The following chart provides the results of a tournament-style 8-player bracket in which
      respondents were tasked with picking the winner of each match-up until a single winner remained.</span><span class="hint-diagram"/></span>

  - key: hints.comments_hint
    t: >
      The <span class="hint-icon hint-comment-button">Comment</span> tab lets you view comments left by survey respondents as they were filling out the survey. 

  ###########################################################################
  # Sponsor Chart
  ###########################################################################

  - key: sections.sponsor_finish.title
    t: Thanks

  - key: sponsor.sponsor_finish
    t: >
      Thanks for supporting the survey. Your avatar should appear next to the chart you picked
      within the next hour or so. If it doesn't, please [get in touch](mailto:chartsponsor@stateofjs.com).
    

  - key: sponsor.sponsored_by
    t: >
        **{name}** donated **${amount}** to sponsor this chart

  - key: sponsor.sponsor_button
    t: Sponsor This Chart

  - key: sponsor.sponsor_chart.title
    t: Sponsor Chart "{title}"

  - key: sponsor.sponsor_chart.description
    t: >
        Support this survey financially by donating $10 or more, and get your
        Twitter avatar featured next to a chart!

  - key: sponsor.chart_id
    t: 'Chart ID: '

  - key: sponsor.sponsor_this_chart
    t: Sponsor This Chart (${baseAmount}+) 

  - key: sponsor.how_it_works.title
    t: How It Works

  - key: sponsor.how_it_works.description
    t: >
      1. When you **click the "Sponsor This Chart" button**, you will be redirected to our partner [SendOwl](https://www.sendowl.com/)'s checkout page. 
      
      
      2. You can then **adjust the amount** you'd like to sponsor the survey for, starting at USD10.  
      
      
      3. Once you checkout, you will be able to **provide your Twitter username**. 
      
      
      4. You will see a **File Download** page, but you can safely ignore it. 
      
      
      5. The site will rebuild in the background and your username and donation will **appear next to the chart within the next hour**. 


  - key: sponsor.faq.title
    t: F.A.Q.

  - key: sponsor.faq.usage.title
    t: What will my donation be used for?

  - key: sponsor.faq.usage.description
    t: Your donation will help support survey maintainers, as well as help hire more contributors (illustrators, accessibilty and diversity experts, etc.).

  - key: sponsor.faq.public.title
    t: Will my donation be public?

  - key: sponsor.faq.public.description
    t: Yes. Your **Twitter username** as well as the **amount you donated** will be displayed publicly next to the chart.

  # - key: sponsor.faq.donation_public.title
  #   t: Can I donate on somebody else's behalf?

  # - key: sponsor.faq.donation_public.description
  #   t: You can enter a Twitter username other than your own, but that person will have the right to remove the donation if they request it. 

  - key: sponsor.faq.refund.title
    t: What's your refund policy?

  - key: sponsor.faq.refund.description
    t: All donations are refundable within a 1-week period, minus transaction fees. 

  - key: sponsor.faq.influence.title
    t: Do donations influence the survey contents?

  - key: sponsor.faq.influence.description
    t: Donations take place once the survey is already published, and donors to not have any influence on the contents of the survey. 

  - key: sponsor.faq.feedback.title
    t: Where can I leave feedback/ask questions?

  - key: sponsor.faq.feedback.description
    t: You can do so [on GitHub](https://github.com/StateOfJS/Monorepo/issues/69) or [in our Discord](https://discord.gg/tuWRUWVyJs).


  ###########################################################################
  # Data Explorer
  ###########################################################################

  - key: sections.data_explorer.title
    t: Data Explorer
  - key: sections.data_explorer.description
    t: |
      Dynamically explore the survey's audience by picking two questions, and seeing how
      respondents are distributed between them. 

  - key: hints.data_explorer
    t: |
      This is a preview version of our new Data Explorer. If you find any issues or data inconsistencies please [let us know]({issueLink}).

  # heading

  - key: explorer.main_heading
    t: “{xAxisLabel}” vs “{yAxisLabel}”

  - key: explorer.total_respondents
    t: |
      (**{totalCount}** total respondents)

  - key: explorer.count_per_dot
    t: |
      {respondentsPerDot} Respondents
  - key: explorer.percentage_per_dot
    t: |
      {percentsPerDot}%
  - key: explorer.extra_respondents
    t: Extra Respondents
  - key: explorer.missing_respondents
    t: Missing Respondents

  - key: explorer.count_per_dot.tooltip
    t: |
      1 dot represents {respondentsPerDot} respondents
  - key: explorer.percentage_per_dot.tooltip
    t: |
      1 dot represents {percentsPerDot}% of respondents
  - key: explorer.extra_respondents.tooltip
    t: Highlighted dots indicate higher-than-expected results.
  - key: explorer.missing_respondents.tooltip
    t: Empty dots indicate lower-than-expected results. 

  - key: explorer.units_count
    t: Count
  - key: explorer.units_percentage
    t: "% of Row"

  - key: explorer.edit
    t: Edit Parameters…

  - key: explorer.get_data
    t: Get Data…

  # loading

  - key: explorer.loading.1
    t: Querying API…
  - key: explorer.loading.2
    t: Waiting for a response…
  - key: explorer.loading.3
    t: Still working…
  - key: explorer.loading.4
    t: Hang on just a little bit longer…
  - key: explorer.loading.5
    t: Sorry, this is taking a while. You can try waiting a little longer, or [report an issue]({issueLink}).
  - key: explorer.timeout
    t: Timeout
  - key: explorer.timeout.description
    t: The API didn't respond in time. Please try again later, or [report an issue]({issueLink}).

  # share

  - key: explorer.share
    t: Share…
  - key: explorer.share.title
    t: Share “{xAxisLabel}” vs “{yAxisLabel}”
  - key: explorer.share.tweet
    t: “{xAxisLabel}” vs “{yAxisLabel}” from the {surveyName} {year} survey

  # axis

  - key: explorer.axis_total
    t: "{totalCount} respondents"
  - key: explorer.axis_percent
    t: "{percentCount}% of respondents"

  - key: explorer.x_axis_details
    t: |
      Out of all respondents who completed question “{yAxisLabel}”, **{totalCount}** survey respondents picked “{xQuestionLabel}” for “{xAxisLabel}”
  - key: explorer.y_axis_details
    t: |
      **{totalCount}** survey respondents picked “{yQuestionLabel}”
  - key: explorer.main_legend_count
    t: |
      **{totalCount}** respondents, **1** dot = **{respondentsPerDot}** respondents, **{dotsPerLine}** dots per line

  # controls
  - key: explorer.dots_per_line
    t: Dots per line
  - key: explorer.respondents_per_dot
    t: Respondents per dot
  - key: explorer.show_cell_counts
    t: Show cell counts

  - key: explorer.sections.demographics
    t: Demographics
  - key: explorer.sections.features
    t: Features
  - key: explorer.sections.tools
    t: Libraries

  - key: explorer.all_fields
    t: All fields
  - key: explorer.select_item
    t: Select item

  # details views

  - key: explorer.count_details.1
    t: |
      **{xAxisTotal}** “{xAxisLabel}” respondents selected “{xAnswerLabel}”.
  
  - key: explorer.count_details.2
    t: |
        **{yAxisPercentage}%** of “{yAxisLabel}” respondents selected “{yAnswerLabel}”. 
  
  - key: explorer.count_details.3
    t: |
        Applying that percentage to the previous **{xAxisTotal}** respondents figure 
        gives us an expected baseline of **{normalizedCount}** respondents in this intersection. 
  
  - key: explorer.count_details.4_extra
    t: |
        The actual count is **{bucketCount}**, and those extra **{normalizedCountDelta}** respondents are *highlighted*. 
 
  - key: explorer.count_details.4_missing
    t: |
        The actual count is **{bucketCount}**, and those missing **{normalizedCountDelta}** respondents appear as empty dots. 

  - key: explorer.percentage_details.1_extra
    t: |
      Overall, **{xAxisPercentage}%** of “{xAxisLabel}” respondents selected “{xAnswerLabel}”, but
      within “{yAxisLabel}” respondents who selected “{yAnswerLabel}” that percentage climbs to  **{bucketPercentage}%**.
  
  - key: explorer.percentage_details.1_missing
    t: |
      Overall, **{xAxisPercentage}%** of “{xAxisLabel}” respondents selected “{xAnswerLabel}”, but
      within “{yAxisLabel}” respondents who selected “{yAnswerLabel}” that percentage climbs to  **{bucketPercentage}%**.

  - key: explorer.percentage_details.2_extra
    t: |
        Those extra **{normalizedPercentageDelta}%** respondents are *highlighted*. 
  
  - key: explorer.percentage_details.2_missing
    t: |
        Those missing **{normalizedPercentageDelta}%** respondents appear as empty dots. 

  # - key: explorer.percentage_details.1
  #   t: |
  #     **{xAxisPercentage}%** of **{xAxisTotal}** “{xAxisLabel}” respondents selected “{xAnswerLabel}”.
  
  # - key: explorer.percentage_details.2
  #   t: |
  #       **{yAxisPercentage}%** of “{yAxisLabel}” respondents selected “{yAnswerLabel}”. 
  
  # - key: explorer.percentage_details.3
  #   t: |
  #       Applying that percentage to the previous **{xAxisTotal}** respondents figure 
  #       gives us an expected baseline of **{normalizedPercentage}%** of respondents in this intersection. 
  
  # - key: explorer.percentage_details.4_extra
  #   t: |
  #       The actual percentage is **{bucketPercentage}%**, and those extra **{normalizedPercentageDelta}%** respondents are *highlighted*. 
  
  # - key: explorer.percentage_details.4_missing
  #   t: |
  #       The actual count is **{bucketPercentage}%**, and those missing **{normalizedPercentageDelta}%** respondents appear as empty dots. 

  - key: opinions.opinions_right_direction
    t: "React Native is moving in the right direction"

  - key: opinions.opinions_complex
    t: "Building React Native apps is overly complex right now"

  - key: opinions.opinions_changing_too_fast
    t: "The React Native ecosystem is changing too fast"

  - key: explorer.extra_missing_respondents
    t: |
      ### Extra & Missing Respondents

      The chart above aims to identify areas showing higher-than-expected 
      or lower-than-expected values compared to a calculated baseline. 
      
      For example, assuming there are 1000 CSS Grid users, and that 50% of survey respondents work in a large company, 
      you'd expect to find 500 CSS Grid users working in large companies. 

      Any deviation above or below that expected total could potentially indicate an interesting
      correlation between both variables, and is highlighted on the chart with either colored 
      dots (for extra respondents above the baseline) or empty dots (for missing respondents).