![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F2926708%2F944730e9f4ed58055d3296abae55542a%2FData%20competition%20social%20card%201.png?generation=1605121882815667&alt=media\")
Hi Kagglers!
\nSome big news…We have reached the midpoint of the CDP: Unlocking Climate Solutions analytics competition and it’s time to award the Midpoint Prizes:
\nFavourite public dataset shared prior to 11/4/2020
\nWinner Prize: $3,000
Most engaging data visualization published prior to 11/4/2020
\nWinner Prize: $3,000
We would like to thank all of you who have entered prize submissions. The range of data sets were fantastic and we can’t wait to see how you utilise the data to build further metrics as the competition continues.
\nThe visualisations submitted were also brilliant, investigating CDP’s data in new and innovative ways to highlight the intersection between environmental and social issues.
\nFavourite public dataset shared
\nWinning Dataset Submission: Compiled datasets for CDP Analytics Competition
\nWinning User: @seraphimstreets
This data set was extremely comprehensive, including data from the Organization of Economic Co-Operation and Development (OECD), BP Statistical Review of World Energy, International Renewable Energy Agency (IRENA), World Resource Institute, Berkeley Earth, Institute for Health Metrics and Evaluation (IMHE) and Our World In Data.
It was great to see @seraphimstreets cover data at both national and sub-national levels, covering multiple spatial scales that can allow us to compare Corporate Climate ambitions against national benchmarks.
Documentation for this data was also brilliant, creating a detailed directory of social equity data that covered both social and environmental issues, including a helpful README.
Other Notable Mentions
\nData Submission: Annual Financial Data For Hybrid Metrics
\nUser: @takahirokubo0
Data Submission: Yearly Air Quality Index (AQI) For CDP Cities
\nUser: @reubencpereira
Innovative thinking from @reubencpereira to link disclosing Cities to their closest weather station using data from the U.S Environmental Protection Agency, allowing us to ground truth disclosed city-wide air pollution metrics* with the EPA’s Yearly Air Quality Index (AQI).
Most engaging data visualization published
\nWinning Visualisations Submission: CDP : Impact on social aspects and city services
\nWinning User: @dsnil87
@dsnil87 first visualisation provides a fantastic overview of city participation rates across CDP’s operating regions. The plot presents the % of cities currently disclosing to CDP vs the remaining % of cities (over 100’000 population) not yet disclosing. This is a great visualisation to inform CDP’s outreach activities as we make plans to onboard even more City’s into our global disclosure system.
@dsnil87 also made use of Altair visualisations to build eye-catching interactive visuals, allowing us to cycle through each disclosure year and asses how Cities’ climate risk and vulnerability assessments have evolved over time
@dsnil87 even had time to build geospatial visualisations, analysing the Climate Hazards section of the Cities questionnaire (Section 2.1) highlighting services and assets that are at risk from climate impacts - while also meeting the competitions evaluation criteria to analyse both environmental AND social aspects of the climate crisis, mapping out the social impacts of climate hazards with another Plotly interactive map.
Other Notable Mentions
\nVisualisations Submission: CDP: Introduction to the Dataset
\nUser: @iamleonie
Visualisations Submission: Environmental Justice - A Berlin City Case
\nUser: @jpbremer
Well done to our winners!
\nReviewing all your data sets and notebooks was a lot of fun and we hope you have all enjoyed the competition so far.
\nWe wish you all the luck for the remainder of the competition and hope the notebooks shared above provide inspiration as you build indicators to uncover the intersection between environmental and social challenges.
\n( e.g. https://www.huduser.gov/portal/periodicals/em/summer11/highlight2.html ! )
\nRegards,
\nThe CDP Team
", "messages": [ { "id": "1075504", "postDate": "11/11/2020 18:52:05", "content": "
Hi Kagglers!
\nSome big news…We have reached the midpoint of the CDP: Unlocking Climate Solutions analytics competition and it’s time to award the Midpoint Prizes:
\nFavourite public dataset shared prior to 11/4/2020
\nWinner Prize: $3,000
Most engaging data visualization published prior to 11/4/2020
\nWinner Prize: $3,000
We would like to thank all of you who have entered prize submissions. The range of data sets were fantastic and we can’t wait to see how you utilise the data to build further metrics as the competition continues.
\nThe visualisations submitted were also brilliant, investigating CDP’s data in new and innovative ways to highlight the intersection between environmental and social issues.
\nFavourite public dataset shared
\nWinning Dataset Submission: Compiled datasets for CDP Analytics Competition
\nWinning User: @seraphimstreets
This data set was extremely comprehensive, including data from the Organization of Economic Co-Operation and Development (OECD), BP Statistical Review of World Energy, International Renewable Energy Agency (IRENA), World Resource Institute, Berkeley Earth, Institute for Health Metrics and Evaluation (IMHE) and Our World In Data.
It was great to see @seraphimstreets cover data at both national and sub-national levels, covering multiple spatial scales that can allow us to compare Corporate Climate ambitions against national benchmarks.
Documentation for this data was also brilliant, creating a detailed directory of social equity data that covered both social and environmental issues, including a helpful README.
Other Notable Mentions
\nData Submission: Annual Financial Data For Hybrid Metrics
\nUser: @takahirokubo0
Data Submission: Yearly Air Quality Index (AQI) For CDP Cities
\nUser: @reubencpereira
Innovative thinking from @reubencpereira to link disclosing Cities to their closest weather station using data from the U.S Environmental Protection Agency, allowing us to ground truth disclosed city-wide air pollution metrics* with the EPA’s Yearly Air Quality Index (AQI).
Most engaging data visualization published
\nWinning Visualisations Submission: CDP : Impact on social aspects and city services
\nWinning User: @dsnil87
@dsnil87 first visualisation provides a fantastic overview of city participation rates across CDP’s operating regions. The plot presents the % of cities currently disclosing to CDP vs the remaining % of cities (over 100’000 population) not yet disclosing. This is a great visualisation to inform CDP’s outreach activities as we make plans to onboard even more City’s into our global disclosure system.
@dsnil87 also made use of Altair visualisations to build eye-catching interactive visuals, allowing us to cycle through each disclosure year and asses how Cities’ climate risk and vulnerability assessments have evolved over time
@dsnil87 even had time to build geospatial visualisations, analysing the Climate Hazards section of the Cities questionnaire (Section 2.1) highlighting services and assets that are at risk from climate impacts - while also meeting the competitions evaluation criteria to analyse both environmental AND social aspects of the climate crisis, mapping out the social impacts of climate hazards with another Plotly interactive map.
Other Notable Mentions
\nVisualisations Submission: CDP: Introduction to the Dataset
\nUser: @iamleonie
Visualisations Submission: Environmental Justice - A Berlin City Case
\nUser: @jpbremer
Well done to our winners!
\nReviewing all your data sets and notebooks was a lot of fun and we hope you have all enjoyed the competition so far.
\nWe wish you all the luck for the remainder of the competition and hope the notebooks shared above provide inspiration as you build indicators to uncover the intersection between environmental and social challenges.
\n( e.g. https://www.huduser.gov/portal/periodicals/em/summer11/highlight2.html ! )
\nRegards,
\nThe CDP Team
", "rawMarkdown": "\n\n**Hi Kagglers!**\n\nSome big news...We have reached the midpoint of the [CDP: Unlocking Climate Solutions analytics competition](https://www.kaggle.com/c/cdp-unlocking-climate-solutions/overview) and it’s time to award the [Midpoint Prizes](https://www.kaggle.com/c/cdp-unlocking-climate-solutions/overview/prizes):\n \n**Favourite public dataset shared prior to 11/4/2020** \nWinner Prize: $3,000\n \n**Most engaging data visualization published prior to 11/4/2020**\nWinner Prize: $3,000\n \nWe would like to thank all of you who have entered prize submissions. The range of data sets were fantastic and we can’t wait to see how you utilise the data to build further metrics as the competition continues.\n \nThe visualisations submitted were also brilliant, investigating CDP’s data in new and innovative ways to highlight the intersection between environmental and social issues. \n \n**Favourite public dataset shared** \n\n**Winning Dataset Submission:** [Compiled datasets for CDP Analytics Competition](https://www.kaggle.com/seraphimstreets/environmentequity-starterpack)\n**Winning User:** @seraphimstreets \n\n- This data set was extremely comprehensive, including data from the [Organization of Economic Co-Operation and Development (OECD)](https://stats.oecd.org/), [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html), [International Renewable Energy Agency (IRENA)](https://www.irena.org/Statistics/View-Data-by-Topic/Costs/Global-Trends), [World Resource Institute](https://www.wri.org/), [Berkeley Earth](http://berkeleyearth.org/), [Institute for Health Metrics and Evaluation (IMHE)](http://www.healthdata.org/) and [Our World In Data](https://ourworldindata.org/).\n \n- It was great to see @seraphimstreets cover data at both national and sub-national levels, covering multiple spatial scales that can allow us to compare Corporate Climate ambitions against national benchmarks.\n \n- Documentation for this data was also brilliant, creating a detailed directory of social equity data that covered both social and environmental issues, including a helpful README.\n \n**Other Notable Mentions** \n\n**Data Submission:** [Annual Financial Data For Hybrid Metrics](https://www.kaggle.com/takahirokubo0/annual-financial-data-for-hybrid-cdp-kpi)\n**User:** @takahirokubo0 \n\n- A great idea by @takahirokubo0 to join CDP data with financial data from [SimFin](https://simfin.com/), using organisation Ticker data from the [CDP Corporations Disclosing data set](https://www.kaggle.com/c/cdp-unlocking-climate-solutions/data) to augment competition data with financial performance metrics.\n \n**Data Submission:** [Yearly Air Quality Index (AQI) For CDP Cities](https://www.kaggle.com/reubencpereira/yearly-air-quality-index-aqi-for-cdp-cities)\n**User:** @reubencpereira \n\n- Innovative thinking from @reubencpereira to link disclosing Cities to their closest weather station using data from the [U.S Environmental Protection Agency](https://www.epa.gov/), allowing us to ground truth disclosed city-wide air pollution metrics* with the EPA’s Yearly Air Quality Index (AQI).\n \n* ([Question 10.14 within the ‘Full_Cities_Dataset’](https://www.kaggle.com/c/cdp-unlocking-climate-solutions/data)) \n \n**Most engaging data visualization published** \n\n**Winning Visualisations Submission:** [CDP : Impact on social aspects and city services](https://www.kaggle.com/dsnil87/cdp-impact-on-social-aspects-and-city-services)\n**Winning User:** @dsnil87 \n\n- @dsnil87 first visualisation provides a fantastic overview of city participation rates across CDP’s operating regions. The plot presents the % of cities currently disclosing to CDP vs the remaining % of cities (over 100’000 population) not yet disclosing. This is a great visualisation to inform CDP’s outreach activities as we make plans to onboard even more City’s into our global disclosure system.\n \n- @dsnil87 also made use of [Altair ](https://altair-viz.github.io/) visualisations to build eye-catching interactive visuals, allowing us to cycle through each disclosure year and asses how Cities’ climate risk and vulnerability assessments have evolved over time\n \n- @dsnil87 even had time to build geospatial visualisations, analysing the Climate Hazards section of the Cities questionnaire ([Section 2.1](https://guidance.cdp.net/en/guidance?cid=16&ctype=theme&idtype=ThemeID&incchild=1µsite=0&otype=Questionnaire&tags=TAG-637%2CTAG-570%2CTAG-13013%2CTAG-13002%2CTAG-13009%2CTAG-13010)) highlighting services and assets that are at risk from climate impacts - while also meeting the competitions evaluation criteria to analyse both environmental **AND** social aspects of the climate crisis, mapping out the social impacts of climate hazards with another [Plotly ](https://plotly.com/python/maps/) interactive map.\n \n**Other Notable Mentions** \n\n**Visualisations Submission:** [CDP: Introduction to the Dataset](https://www.kaggle.com/iamleonie/cdp-introduction-to-the-dataset)\n**User:** @iamleonie \n\n- Excellent overview of the CDP questionnaire structure and a fantastic analysis of Physical risks. The Likelihood x Impact matrix is an intuitive way to visualise hidden risks structure and sets @iamleonie up nicely for a promising [risk classification analysis](https://towardsdatascience.com/risk-management-with-clustering-fd594e064806)!\n\n**Visualisations Submission:** [Environmental Justice - A Berlin City Case](https://www.kaggle.com/jpbremer/environmental-justice-a-berlin-city-case)\n**User:** @jpbremer \n\n- A nice attempt to bring together environmental and social indicators in a city specific analysis of Environmental Justice. @jpbremer has recognised the overlap between environmental and social issues, aligning to the [competitions problem statement](https://www.kaggle.com/c/cdp-unlocking-climate-solutions/overview) well.\n\n**Well done to our winners!** \n\nReviewing all your data sets and notebooks was a lot of fun and we hope you have all enjoyed the competition so far.\n\nWe wish you all the luck for the remainder of the competition and hope the notebooks shared above provide inspiration as you build indicators to uncover the *intersection between environmental and social challenges.*\n\n( e.g. https://www.huduser.gov/portal/periodicals/em/summer11/highlight2.html ! )\n\n\nRegards,\n\n*The CDP Team*", "votes": null }, { "id": "1075536", "postDate": "11/11/2020 19:10:47", "content": "Congrats to the winners!
\n@seraphimstreets and @dsnil87, the Kaggle Team will reach out to you shortly with instructions on how to claim your prizes.
\nThere were a lot of great submissions, thank you everybody for making submissions and for marking your work as public! Hopefully these notebooks and datasets provide inspiration as you build indicators to uncover the intersection between environmental and social challenges.
", "rawMarkdown": "**Congrats to the winners!**\n\n@seraphimstreets and @dsnil87, the Kaggle Team will reach out to you shortly with instructions on how to claim your prizes.\n\nThere were a lot of great submissions, thank you everybody for making submissions and for marking your work as public! Hopefully these notebooks and datasets provide inspiration as you build indicators to **uncover the intersection between environmental and social challenges**.", "votes": null }, { "id": "1075558", "postDate": "11/11/2020 19:25:56", "content": "Thank you for the mention! I feel honored and appreciate the feedback. Congratulations to @seraphimstreets and @dsnil87! Very well deserved.
", "rawMarkdown": "Thank you for the mention! I feel honored and appreciate the feedback. Congratulations to @seraphimstreets and @dsnil87! Very well deserved.", "votes": null }, { "id": "1075564", "postDate": "11/11/2020 19:28:00", "content": "Brilliant visuals @iamleonie - great representation of the risks corporations and cities face!
", "rawMarkdown": "Brilliant visuals @iamleonie - great representation of the risks corporations and cities face!", "votes": null }, { "id": "1075579", "postDate": "11/11/2020 19:40:28", "content": "Thanks so much for selecting my dataset for the prize! Hope that it will help other Kagglers in producing amazing analytics notebooks for this competition. :)
", "rawMarkdown": "Thanks so much for selecting my dataset for the prize! Hope that it will help other Kagglers in producing amazing analytics notebooks for this competition. :)", "votes": null }, { "id": "1075582", "postDate": "11/11/2020 19:41:50", "content": "Amazing collection of data sets and background research @seraphimstreets - well done!
", "rawMarkdown": "Amazing collection of data sets and background research @seraphimstreets - well done!", "votes": null }, { "id": "1075586", "postDate": "11/11/2020 19:45:01", "content": "@iamleonie Thank you! Your visualization (using the cosine similarity) was really innovative as well!
", "rawMarkdown": "iamleonie Thank you! Your visualization (using the cosine similarity) was really innovative as well!", "votes": null }, { "id": "1075609", "postDate": "11/11/2020 20:12:10", "content": "@seraphimstreets , @jpbremer, @iamleonie congratulations to all of you !!
\nI would also like to thank @paultimothymooney, @callumr22 for considering to create such a track for visualization. Otherwise, I perhaps would have never learnt altair and plotly :) . Hope such sub-tracks also find a place in future competitions.
\nIt's great to get a recognition for work from CDP and Kaggle. But more importantly it made me realise, how much hard work goes in to create a good visualization. All these times, when we all were busy with deep nets and boosting trees, those visualization library-makers have done a tremendous job silently! Kudos to those guys!
Congratulations to the winners
", "rawMarkdown": "Congratulations to the winners", "votes": null }, { "id": "1075643", "postDate": "11/11/2020 20:56:51", "content": "Great work @dsnil87 !
\nAnd good shout out for the visualizers - time for me to go and have my own fun with Altair now!
", "rawMarkdown": "Great work @dsnil87 ! \n\nAnd good shout out for the visualizers - time for me to go and have my own fun with Altair now!", "votes": null }, { "id": "1076047", "postDate": "11/12/2020 08:04:04", "content": "Well done to the winners (and all the participants) !
", "rawMarkdown": "Well done to the winners (and all the participants) !", "votes": null }, { "id": "1086210", "postDate": "11/21/2020 13:31:09", "content": "Thank you for the notable mention!
\nI'll use my dataset to digging into the financial & non-financial combination metrics.
(I already surveyed CDP emission data, the preparation is in progress!)
", "rawMarkdown": "Thank you for the notable mention!\nI'll use my dataset to digging into the financial & non-financial combination metrics.\n\n([I already surveyed CDP emission data](https://www.kaggle.com/takahirokubo0/extract-emissions-from-corporate-responses), the preparation is in progress!)", "votes": null } ], "comments": [ { "id": 1075536, "author_name": "paultimothymooney", "author_url": "", "post_date": "11/11/2020 19:10:47", "content": "Congrats to the winners!
\n@seraphimstreets and @dsnil87, the Kaggle Team will reach out to you shortly with instructions on how to claim your prizes.
\nThere were a lot of great submissions, thank you everybody for making submissions and for marking your work as public! Hopefully these notebooks and datasets provide inspiration as you build indicators to uncover the intersection between environmental and social challenges.
", "votes": null, "replies": [] }, { "id": 1075558, "author_name": "iamleonie", "author_url": "", "post_date": "11/11/2020 19:25:56", "content": "Thank you for the mention! I feel honored and appreciate the feedback. Congratulations to @seraphimstreets and @dsnil87! Very well deserved.
", "votes": null, "replies": [ { "id": 1075564, "author_name": "callumr22", "author_url": "", "post_date": "11/11/2020 19:28:00", "content": "Brilliant visuals @iamleonie - great representation of the risks corporations and cities face!
", "votes": null, "replies": [] }, { "id": 1075586, "author_name": "seraphimstreets", "author_url": "", "post_date": "11/11/2020 19:45:01", "content": "@iamleonie Thank you! Your visualization (using the cosine similarity) was really innovative as well!
", "votes": null, "replies": [] } ] }, { "id": 1075579, "author_name": "seraphimstreets", "author_url": "", "post_date": "11/11/2020 19:40:28", "content": "Thanks so much for selecting my dataset for the prize! Hope that it will help other Kagglers in producing amazing analytics notebooks for this competition. :)
", "votes": null, "replies": [ { "id": 1075582, "author_name": "callumr22", "author_url": "", "post_date": "11/11/2020 19:41:50", "content": "Amazing collection of data sets and background research @seraphimstreets - well done!
", "votes": null, "replies": [] } ] }, { "id": 1075609, "author_name": "dsnil87", "author_url": "", "post_date": "11/11/2020 20:12:10", "content": "@seraphimstreets , @jpbremer, @iamleonie congratulations to all of you !!
\nI would also like to thank @paultimothymooney, @callumr22 for considering to create such a track for visualization. Otherwise, I perhaps would have never learnt altair and plotly :) . Hope such sub-tracks also find a place in future competitions.
\nIt's great to get a recognition for work from CDP and Kaggle. But more importantly it made me realise, how much hard work goes in to create a good visualization. All these times, when we all were busy with deep nets and boosting trees, those visualization library-makers have done a tremendous job silently! Kudos to those guys!
Great work @dsnil87 !
\nAnd good shout out for the visualizers - time for me to go and have my own fun with Altair now!
", "votes": null, "replies": [] } ] }, { "id": 1075618, "author_name": "david289", "author_url": "", "post_date": "11/11/2020 20:20:18", "content": "Congratulations to the winners
", "votes": null, "replies": [] }, { "id": 1076047, "author_name": "boltmaud", "author_url": "", "post_date": "11/12/2020 08:04:04", "content": "Well done to the winners (and all the participants) !
", "votes": null, "replies": [] }, { "id": 1086210, "author_name": "takahirokubo0", "author_url": "", "post_date": "11/21/2020 13:31:09", "content": "Thank you for the notable mention!
\nI'll use my dataset to digging into the financial & non-financial combination metrics.
(I already surveyed CDP emission data, the preparation is in progress!)
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1075504": "\n\n**Hi Kagglers!**\n\nSome big news...We have reached the midpoint of the [CDP: Unlocking Climate Solutions analytics competition](https://www.kaggle.com/c/cdp-unlocking-climate-solutions/overview) and it’s time to award the [Midpoint Prizes](https://www.kaggle.com/c/cdp-unlocking-climate-solutions/overview/prizes):\n \n**Favourite public dataset shared prior to 11/4/2020** \nWinner Prize: $3,000\n \n**Most engaging data visualization published prior to 11/4/2020**\nWinner Prize: $3,000\n \nWe would like to thank all of you who have entered prize submissions. The range of data sets were fantastic and we can’t wait to see how you utilise the data to build further metrics as the competition continues.\n \nThe visualisations submitted were also brilliant, investigating CDP’s data in new and innovative ways to highlight the intersection between environmental and social issues. \n \n**Favourite public dataset shared** \n\n**Winning Dataset Submission:** [Compiled datasets for CDP Analytics Competition](https://www.kaggle.com/seraphimstreets/environmentequity-starterpack)\n**Winning User:** @seraphimstreets \n\n- This data set was extremely comprehensive, including data from the [Organization of Economic Co-Operation and Development (OECD)](https://stats.oecd.org/), [BP Statistical Review of World Energy](https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html), [International Renewable Energy Agency (IRENA)](https://www.irena.org/Statistics/View-Data-by-Topic/Costs/Global-Trends), [World Resource Institute](https://www.wri.org/), [Berkeley Earth](http://berkeleyearth.org/), [Institute for Health Metrics and Evaluation (IMHE)](http://www.healthdata.org/) and [Our World In Data](https://ourworldindata.org/).\n \n- It was great to see @seraphimstreets cover data at both national and sub-national levels, covering multiple spatial scales that can allow us to compare Corporate Climate ambitions against national benchmarks.\n \n- Documentation for this data was also brilliant, creating a detailed directory of social equity data that covered both social and environmental issues, including a helpful README.\n \n**Other Notable Mentions** \n\n**Data Submission:** [Annual Financial Data For Hybrid Metrics](https://www.kaggle.com/takahirokubo0/annual-financial-data-for-hybrid-cdp-kpi)\n**User:** @takahirokubo0 \n\n- A great idea by @takahirokubo0 to join CDP data with financial data from [SimFin](https://simfin.com/), using organisation Ticker data from the [CDP Corporations Disclosing data set](https://www.kaggle.com/c/cdp-unlocking-climate-solutions/data) to augment competition data with financial performance metrics.\n \n**Data Submission:** [Yearly Air Quality Index (AQI) For CDP Cities](https://www.kaggle.com/reubencpereira/yearly-air-quality-index-aqi-for-cdp-cities)\n**User:** @reubencpereira \n\n- Innovative thinking from @reubencpereira to link disclosing Cities to their closest weather station using data from the [U.S Environmental Protection Agency](https://www.epa.gov/), allowing us to ground truth disclosed city-wide air pollution metrics* with the EPA’s Yearly Air Quality Index (AQI).\n \n* ([Question 10.14 within the ‘Full_Cities_Dataset’](https://www.kaggle.com/c/cdp-unlocking-climate-solutions/data)) \n \n**Most engaging data visualization published** \n\n**Winning Visualisations Submission:** [CDP : Impact on social aspects and city services](https://www.kaggle.com/dsnil87/cdp-impact-on-social-aspects-and-city-services)\n**Winning User:** @dsnil87 \n\n- @dsnil87 first visualisation provides a fantastic overview of city participation rates across CDP’s operating regions. The plot presents the % of cities currently disclosing to CDP vs the remaining % of cities (over 100’000 population) not yet disclosing. This is a great visualisation to inform CDP’s outreach activities as we make plans to onboard even more City’s into our global disclosure system.\n \n- @dsnil87 also made use of [Altair ](https://altair-viz.github.io/) visualisations to build eye-catching interactive visuals, allowing us to cycle through each disclosure year and asses how Cities’ climate risk and vulnerability assessments have evolved over time\n \n- @dsnil87 even had time to build geospatial visualisations, analysing the Climate Hazards section of the Cities questionnaire ([Section 2.1](https://guidance.cdp.net/en/guidance?cid=16&ctype=theme&idtype=ThemeID&incchild=1µsite=0&otype=Questionnaire&tags=TAG-637%2CTAG-570%2CTAG-13013%2CTAG-13002%2CTAG-13009%2CTAG-13010)) highlighting services and assets that are at risk from climate impacts - while also meeting the competitions evaluation criteria to analyse both environmental **AND** social aspects of the climate crisis, mapping out the social impacts of climate hazards with another [Plotly ](https://plotly.com/python/maps/) interactive map.\n \n**Other Notable Mentions** \n\n**Visualisations Submission:** [CDP: Introduction to the Dataset](https://www.kaggle.com/iamleonie/cdp-introduction-to-the-dataset)\n**User:** @iamleonie \n\n- Excellent overview of the CDP questionnaire structure and a fantastic analysis of Physical risks. The Likelihood x Impact matrix is an intuitive way to visualise hidden risks structure and sets @iamleonie up nicely for a promising [risk classification analysis](https://towardsdatascience.com/risk-management-with-clustering-fd594e064806)!\n\n**Visualisations Submission:** [Environmental Justice - A Berlin City Case](https://www.kaggle.com/jpbremer/environmental-justice-a-berlin-city-case)\n**User:** @jpbremer \n\n- A nice attempt to bring together environmental and social indicators in a city specific analysis of Environmental Justice. @jpbremer has recognised the overlap between environmental and social issues, aligning to the [competitions problem statement](https://www.kaggle.com/c/cdp-unlocking-climate-solutions/overview) well.\n\n**Well done to our winners!** \n\nReviewing all your data sets and notebooks was a lot of fun and we hope you have all enjoyed the competition so far.\n\nWe wish you all the luck for the remainder of the competition and hope the notebooks shared above provide inspiration as you build indicators to uncover the *intersection between environmental and social challenges.*\n\n( e.g. https://www.huduser.gov/portal/periodicals/em/summer11/highlight2.html ! )\n\n\nRegards,\n\n*The CDP Team*", "1075536": "**Congrats to the winners!**\n\n@seraphimstreets and @dsnil87, the Kaggle Team will reach out to you shortly with instructions on how to claim your prizes.\n\nThere were a lot of great submissions, thank you everybody for making submissions and for marking your work as public! Hopefully these notebooks and datasets provide inspiration as you build indicators to **uncover the intersection between environmental and social challenges**.", "1075558": "Thank you for the mention! I feel honored and appreciate the feedback. Congratulations to @seraphimstreets and @dsnil87! Very well deserved.", "1075564": "Brilliant visuals @iamleonie - great representation of the risks corporations and cities face!", "1075579": "Thanks so much for selecting my dataset for the prize! Hope that it will help other Kagglers in producing amazing analytics notebooks for this competition. :)", "1075582": "Amazing collection of data sets and background research @seraphimstreets - well done!", "1075586": "iamleonie Thank you! Your visualization (using the cosine similarity) was really innovative as well!", "1075609": "seraphimstreets , @jpbremer, @iamleonie congratulations to all of you !! \n\nI would also like to thank @paultimothymooney, @callumr22 for considering to create such a track for visualization. Otherwise, I perhaps would have never learnt altair and plotly :) . Hope such sub-tracks also find a place in future competitions. \nIt's great to get a recognition for work from CDP and Kaggle. But more importantly it made me realise, how much hard work goes in to create a good visualization. All these times, when we all were busy with deep nets and boosting trees, those visualization library-makers have done a tremendous job silently! Kudos to those guys!", "1075618": "Congratulations to the winners", "1075643": "Great work @dsnil87 ! \n\nAnd good shout out for the visualizers - time for me to go and have my own fun with Altair now!", "1076047": "Well done to the winners (and all the participants) !", "1086210": "Thank you for the notable mention!\nI'll use my dataset to digging into the financial & non-financial combination metrics.\n\n([I already surveyed CDP emission data](https://www.kaggle.com/takahirokubo0/extract-emissions-from-corporate-responses), the preparation is in progress!)" }, "source": "meta" }