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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: Sponsored content from our partners.
- key: sponsors.learn_more
t: Learn more.
- key: general.disclaimer.representation
t: >
This survey was distributed primarily through online platforms, each of which carry their own inherent demographic biases. As such, it is representative of the makeup of these specific communities, and may not be representative of the developer community at large.
- key: results.ongoing_survey
t: Open Now
###########################################################################
# Tabs
###########################################################################
- 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 Income
- key: tabs.by_gender
t: By Gender
- key: tabs.by_race_ethnicity
t: By Race & Ethnicity
- key: tabs.low_vs_high_income
t: Low vs High Income
- key: tabs.usa_vs_the_world
t: U.S.A. vs World
- key: tabs.spanish
t: Spanish-Language
- key: tabs.outreach
t: Outreach
###########################################################################
# 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: ratios.interest
aliasFor: options.experience_ranking.interest
- key: ratios.usage
aliasFor: options.experience_ranking.usage
- key: ratios.awareness
aliasFor: options.experience_ranking.awareness
- key: ratios.retention
t: Retention
- key: ratios.positivity
t: Positivity
- key: ratios.positivityRelative
t: Positivity
- key: ratios.interest.description
t: >
Proportion of **positive sentiment** among respondents having **heard about** an item
- key: ratios.usage.description
t: >
Proportion of respondents **having used** an item
- key: ratios.awareness.description
t: >
Proportion of respondents **having heard about or used** an item
- key: ratios.retention.description
t: >
Proportion of **positive sentiment** among respondents having **used** an item
- key: ratios.positivity.description
t: >
Proportion of **positive sentiment** among all respondents
- key: ratios.positivityRelative.description
t: >
Proportion of **positive sentiment** among respondents who expressed a sentiment.
- key: modes.rank
t: Rank
- key: modes.value
t: Value
- key: modes.rank.description
t: Place according to rank
- key: modes.value.description
t: Place according to value
- 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: Income
- 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 Disease
- key: options.disability_status_others.depression
t: Depression
###########################################################################
# 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: >
In order to make running the survey 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:[email protected])!
- key: sections.awards.title
t: Awards
- key: sections.awards.description
t: Things that stood out this year.
- key: sections.user_metadata.title
t: Metadata
aliases:
- sections._user_metadata.title
- key: sections.user_metadata.description
t: Additional metadata collected about respondents.
aliases:
- sections._user_metadata.description
###########################################################################
# User Info
###########################################################################
- key: user_info.locale
t: Language
aliases:
- user_metadata.locale
- key: user_info.locale.description
t: The language respondents selected to fill out the survey.
aliases:
- user_metadata.locale.description
- key: user_info.source
t: Source
aliases:
- user_metadata.source
- _user_metadata.source
- key: user_info.source.description
t: How respondents found out about the survey
aliases:
- user_metadata.source.description
- _user_metadata.source.description
- key: user_info.source.note
t: Respondent source is computed based on referrer data, URL tracking data, and self-reported answers.
aliases:
- user_metadata.source.note
- _user_metadata.source.note
- key: options.source.other_answers
t: Other sources
- key: user_info.source_by_gender
t: Source by Gender
- key: user_info.source_by_race_ethnicity
t: Source by Race & Ethnicity
- 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.average_income_by_years_of_experience
t: Average Income by Years of Experience
- key: user_info.average_income_by_years_of_experience.description
t: Average income by years of experience.
- key: user_info.average_income_by_company_size
t: Average Income by Company Size
- key: user_info.average_income_by_company_size.description
t: Average income by company size.
- 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.yearly_salary_usa_vs_the_world
t: >
Yearly Income: U.S vs World
- 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.
- key: user_metadata.past_surveys
t: Previous Surveys
- key: user_metadata.past_surveys.description
t: Previous Devographics surveys taken by respondents.
# - key: user_metadata.past_surveys.note
# t: Please note that this data does not include respondents taking the survey as guests.
- key: user_metadata.past_same_survey_count
t: Participation Count
- key: user_metadata.past_same_survey_count.description
t: How many times respondents have taken part in previous editions of this survey.
# - key: user_metadata.past_same_survey_count.note
# aliasFor: user_metadata.past_surveys.note
- key: user_metadata.created_at_date
t: Responses Over Time
- key: user_metadata.created_at_date.description
t: Chronological breakdown of when responses were collected.
- key: user_metadata.authmode
t: Authentication
- key: user_metadata.authmode.description
t: Whether respondents signed in or filled out the survey as guests.
- key: options.authmode.anonymous
t: Guest Account
- key: options.authmode.passwordless
t: Logged-in Account
- key: user_metadata.device
t: Device
- key: user_metadata.device.description
t: What device was used to take the survey.
- key: user_metadata.browser
t: Browser
- key: user_metadata.browser.description
t: What browser was used to take the survey.
- key: user_metadata.version
t: Browser Version
- key: user_metadata.version.description
t: What browser version was used to take the survey.
- key: user_metadata.os
t: OS
- key: user_metadata.os.description
t: What OS version was used to take the survey.
###########################################################################
# 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
- key: options.locale.am-ET
t: Amharic
- key: options.locale.ar-EG
t: Arabic
- key: options.locale.el-GR
t: Greek
- key: options.locale.gl-ES
t: Galician
- key: options.locale.hr-HR
t: Croatian
- key: options.locale.hu-HU
t: Hungarian
- key: options.locale.sk-SK
t: Slovak
- key: options.locale.vi-VN
t: Vietnamese
###########################################################################
# 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
###########################################################################
- key: tools.all_items.experience
t: Libraries Experience & Sentiment
- key: tools.all_items.experience.short
aliasFor: tools.experience
# 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
- key: blocks.entity.twitter_link
t: Twitter
- key: blocks.entity.mastodon_link
t: Mastodon
- key: blocks.entity.blog_link
t: Blog
- key: blocks.entity.rss_link
t: RSS
- key: blocks.entity.twitch_link
t: Twitch
- key: blocks.entity.npm_link
t: npm
- key: blocks.entity.youtube_link
t: YouTube
- key: blocks.entity.mdn_link
t: MDN
- key: blocks.entity.caniuse_link
t: CanIUse
- key: blocks.entity.threads_link
t: Threads
- key: blocks.entity.bluesky_link
t: Bluesky
# people
- key: blocks.people.name
t: Name
- key: blocks.people.social_links
t: Links
- key: blocks.people.responses
t: Responses
# 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 the earliest to the latest available year of data. 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: tools.scatterplot_overview
aliasFor: blocks.tools_quadrant
- 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:
- **1**: Low usage, high retention. Technologies worth keeping an eye on.
- **2**: High usage, high retention. Safe technologies to adopt.
- **3**: Low usage, low retention. Technologies that are harder to recommend currently.
- **4**: 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: Positive/Negative 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 a central axis.
Bar thickness represents the number of respondents aware of a technology.
# tool tier list
- key: blocks.tools_tier_list
t: Library Tier List
- key: blocks.tools_tier_list.note
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: Rankings Over Time
- 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. Each ratio is defined as follows:
- Retention: **would use again** / (**would use again** + **would not use again**)
- Interest: **want to learn** / (**want to learn** + **not interested**)
- Usage: (**would use again** + **would not use again**) / **total**
- Awareness: (**total** - **never heard**) / **total**
# tools experience linechart
- key: blocks.tools_experience_linechart
t: Ratios 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
# 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.
# features_experience_linechart
- key: blocks.features_experience_linechart
t: Ratios Over Time
- key: blocks.features_experience_linechart.description
t: Usage and awareness ratios over time for the highest-rating features.
- key: blocks.features_experience_linechart.note
t: |
Each ratio is defined as follows:
- Usage: (**have used it**) / **total**
- Awareness: (**have used it** + **know about it **) / **total**
- key: blocks.features_experience_ranking
t: Rankings Over Time
- key: blocks.features_experience_ranking.description
t: Usage and awareness rankings over time.
- key: blocks.features_experience_ranking.note
aliasFor: blocks.features_experience_linechart.note
# 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: JSON Data
- key: export.export_graphql
t: GraphQL Query
- key: export.export_filters
t: Filters Code
- 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
# Reading List
- key: features.reading_list
t: Reading List
- key: features.reading_list.note
t: >
How many time each item was added to respondent's Reading List, a feature that lets people
learn more about specific topics as they take the survey.
###########################################################################
# Charts
###########################################################################
- key: chart_units.respondents
t: "**{count}** question respondents out of **{total}** survey participants (**{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.percentageQuestion
aliasFor: chart_units.percentage_question
- key: chart_units.percentage_survey
t: "% of survey respondents"
- key: chart_units.percentageSurvey
aliasFor: chart_units.percentage_survey
- key: chart_units.percentage_bucket
t: Percentages
- key: chart_units.percentageBucket
aliasFor: chart_units.percentage_bucket
- key: chart_units.average
t: Average
- key: chart_units.averageByFacet
aliasFor: chart_units.average
- key: chart_units.facetCounts
t: Counts
- key: chart_units.percentilesByFacet
t: Percentiles
- key: charts.average
t: Average {axis}
- key: charts.average_value
t: "Average value: {value}"
- key: charts.mean
t: Mean
- key: charts.all_respondents
t: All Respondents
- key: charts.overall
aliasFor: charts.all_respondents
- key: charts.facet_responses
t: "{count} responses"
- key: charts.facet_respondents
t: "({count} respondents)"
- key: charts.average.used
t: “Used” average
- key: charts.average.positive
t: “Positive” average
- key: charts.average.negative
t: “Negative” average
- key: charts.nth_percentile
t: "{percentile}th percentile"
- key: charts.nth_percentile_value
t: "{percentile}th percentile: {value}"
- key: charts.freeform_data_indicator
t: (freeform answers)
- key: charts.insufficient_data
t: Insufficient Data
- key: charts.insufficient_data.description
t: Segments with fewer than {value} respondents are not included in the results.
- 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: Organization Size
- 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.users_average
t: Average {axis}
- key: charts.axis_legends.interest_percentage
t: Interest %
- key: charts.axis_legends.satisfaction_percentage
t: Retention %
- key: charts.axis_legends.retention_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_percentageSurvey
aliasFor: charts.axis_legends.users_percentage_survey
- key: charts.axis_legends.users_percentage_question
t: "% of question respondents"
- key: charts.axis_legends.users_percentageQuestion
aliasFor: charts.axis_legends.users_percentage_question
- key: charts.axis_legends.users_percentage_bucket
t: "% of bucket respondents"
- key: charts.axis_legends.users_percentageBucket
aliasFor: charts.axis_legends.users_percentage_bucket