2b:null 2c:["$","title",null,{"children":"Analyzing suicides in US | Harshit Gajjar | Observable"}] 31:Td89,# Analyzing suicides in US By Harshit Gajjar, Mihir Mesia
[Slides](https://docs.google.com/presentation/d/1cx8qWt1-4k2tMlscGMyvUt9DlDW2fJpAN_xhS-czn6g/edit#slide=id.p) ## Between Hope and Despair: Dissecting the Complex Interplay of Suicide Rates, Methods, and Gun Laws in the USA Suicide is a pressing public health concern that continues to devastate families and communities across the United States. With a rising number of individuals succumbing to this preventable tragedy, understanding the factors contributing to suicide rates becomes critical in designing effective interventions and policies. Our data visualization aims to shed light on the complex interplay between suicide rates, methods, and gun laws across different states, providing a comprehensive and comparative perspective on this crucial issue. This timely analysis will help unravel the impact of suicides across different ethnicity, gender as well as highlight variations in methods used for suicide across states. By examining the correlation between these factors, our visualization seeks to provide an evidence-based foundation for further research, policy discussions, and targeted interventions. Ultimately, our goal is to contribute to the ongoing efforts to better understand and prevent suicide, and to create a safer and more supportive environment for individuals struggling with mental health challenges. By delving into this important topic, we hope to stimulate a constructive dialogue among researchers, policymakers, mental health professionals, and the general public. Together, we can work towards reducing the incidence of suicide and improving the well-being of individuals and communities throughout the United States. ### Contents * [Idea 1: Causes of Death in United States from 2000-2020 (by Mihir Mesia)](https://observablehq.com/d/72142fe4c5aa271d#cell-31) * [Idea 2: Trends in Suicide in US from 1999 - 2020 (by Harshit Gajjar)](https://observablehq.com/d/72142fe4c5aa271d#cell-21) * [Idea 3: Suicide rates of different race/ethnicity in blue/red states of US from 2016-2020 (by Harshit Gajjar)](https://observablehq.com/d/72142fe4c5aa271d#cell-35) * [Idea 4: Trends in suicide rate of different race/ethnicity in US from 2016 to 2020 (by Harshit Gajjar)](https://observablehq.com/d/72142fe4c5aa271d#cell-38) * [Idea 5: Top Method of Committing Suicide in US from 2020 (by Mihir Mesia)](https://observablehq.com/d/72142fe4c5aa271d#cell-28) * [Idea 6: Top Method of Committing Suicide in US among male/female from 2000-2020 (by Mihir Mesia)](https://observablehq.com/d/72142fe4c5aa271d#cell-40) * [Idea 7: Patterns in suicide by a given method across different red/blue states and age groups from 2016-2020 (by Harshit Gajjar)](https://observablehq.com/d/72142fe4c5aa271d#cell-44) * [Idea 8: Determine the top method of suicide and age group with highest suicide rate for all race/ethnicity in US from 2016-2020 (by Harshit Gajjar)](https://observablehq.com/d/72142fe4c5aa271d#cell-49) * [Idea 9: Correlation between gun possession and suicide rate by firearm in blue/red states in US from 2020 (by Mihir Mesia) ](https://observablehq.com/d/72142fe4c5aa271d#cell-47)32:T490,## Data Abstraction (What) **Dataset Type:** Table |Attributes|Type & Direction| |---|---| |Death_rates|quantitative, sequential| |Causes_Deaths|categorical| * **Availability:** Static * **Time frame of Data:** 2020 * **Data Source:** [Suicides in United States](https://vpc.org/revealing-the-impacts-of-gun-violence/suicide/) ## Task Abstraction (Why) - T1: Summarize the leading causes of death in US. **[Summarize, Feature]** - T2: Identify the percentage of deaths by suicide in US. **[Identify, Feature]** - ## Marks and Channels (How) * **Marks:** Lines |Channel|Attribute|Using|Rationale |---|---|---|---| |Horizontal Position|Death_Rates|Express|It is a quantitative attribute but on the x-axis.The death rates varies for different causes, making it the most effective and expressive |Vertical Position|Death_Causes|Separate, Align| It is a quantitative attribute but on the y-axis. It helps in identifying the death rates for different causes, making it the most effective and expressive |Length|Death_Rates|| It is a quantitative attribute, so bigger the width of the bar higher the number of death rates, making it the most effective and expressive33:T440,## Data Abstraction (What) **Dataset Type:** Table |Attributes|Type & Direction| |---|---| |year|ordinal, sequential| |Derived Attributes|Type & Direction| |---|---| |rate|quantitative, sequential| * **Availability:** Static * **Time frame of Data:** 1999 - 2020 * **Data Source:** [Suicides in United States](https://wonder.cdc.gov/controller/datarequest/D76;jsessionid=C8B84AE25B40557654EAE4E01326) ## Task Abstraction (Why) - T1: Summarize the suicide rate in US. **[Summarize, Trend]** - T2: Identify the extremes in suicide rate. **[Identify, Extreme]** ## Marks and Channels (How) * **Marks:** Point |Channel|Attribute|Using|Rationale |---|---|---|---| |Horizontal Position|rate|Express|It is a quantitative attribute but on the y-axis. Each year can have a different suicide rate, so we use position to display it, making it the most effective and expressive |Vertical Position|year|Separate, Order| It is an ordinal attribute but on the x-axis. There are multiple years which needs to be shown. so we use position to display it, making it the most effective and expressive34:T707,## Data Abstraction (What) * **Dataset Type:** Table (converted to network) |Attributes|Type & Direction| |---|---| |Race|categorical| |State|categorical| |Deaths|quantitative, sequential| |Derived Attributes|Type & Direction| |---|---| |value|quantitative, sequential| * **Availability:** Static * **Time frame of Data:** 2016 - 2020 * **Data Source:** [Suicides in United States](https://wonder.cdc.gov/controller/datarequest/D76;jsessionid=C8B84AE25B40557654EAE4E01326) ## Task Abstraction (Why) - T1: Summarize the state as blue or red. **[Summarize, Feature]** - T2: Summarize the suicide trends in the red and blue states **[Summarize, Feature]** - T3: Identify the race/ethnicity with highest number of suicide cases. **[Identify, Extreme]** ## Marks and Channels (How) * **Marks:** Point, Line |Channel|Attribute|Using|Rationale |---|---|---|---| |Position|State, Race|-|State" and "Race" is a categorical attribute and they are represented by node. The best way to show red and blue states and race/ethnicity is to use the position. The nodes can be aligned as the outcome of the force simulation algorithm and we can place the nodes depending upon forces applied. |Color Hue|State, Race|separate| "State" and "Race" is a categorical attribute so it is represented with color hue. The best way to show red and blue states and race/ethnicity is to use color hue. The colors determines if it is a red/blue state or race/ethnicity. |Area|value|express| "Value" is a quantitative attribute so it is represented with Area. The best way to see determine number of suicide cases across different red and blue states a is to use Area in a Force Simulation (Node-Link). The Node-Link idiom will help us summarize the states as red or blue and show the number of suicide cases for each state.35:T592,## Data Abstraction (What) * **Dataset Type:** Table (converted to network) |Attributes|Type & Direction| |---|---| |Race|categorical| |State|categorical| |Deaths|quantitative, sequential| |Derived Attributes|Type & Direction| |---|---| |value|quantitative, sequential| * **Availability:** Static * **Time frame of Data:** 1999 - 2020 * **Data Source:** [Suicides in United States](https://wonder.cdc.gov/controller/datarequest/D76;jsessionid=C8B84AE25B40557654EAE4E01326) ## Task Abstraction (Why) - T1: Summarize the suicide trends among different race/ethnicity in US. **[Summarize, Feature]** - T2: Identify the trends in suicide rate among different race/ethnicity. **[Identify, Trend]** ## Marks and Channels (How) * **Marks:** Point |Channel|Attribute|Using|Rationale |---|---|---|---| |Horizontal Position|year|Express|It is a quantitative attribute but on the y-axis. Each year can have a different suicide rate, so we use position to display it, making it the most effective and expressive |Vertical Position|rate|Separate, Order| It is an ordinal attribute but on the x-axis. There are multiple years which needs to be shown. so we use position to display it, making it the most effective and expressive |Color Hue|race|Separate, Order| It is a categorical attribute. There are multiple race/ethnicity which needs to be shown so we use color hue to separate them, making it the most effective and expressive36:T6bc,## Data Abstraction (What) |Attributes|Type & Direction| |---|---| |Suicide_Percentage|quantitative, sequential| |Method_Suicide|categorical| |Derived Attributes|Type & Direction| |---|---| |Suicide_Percentage|quantitative, sequential| * **Availability:** Static * **Time frame of Data:** 2020 * **Data Source:** [Suicides in United States](https://www.cdc.gov/suicide/suicide-data-statistics.html) ## Task Abstraction (Why) - T1: Summarize the state as blue or red. **[Summarize, Feature]** - T2: Summarize the suicide trends in the red and blue states **[Summarize, Feature]** - T3: Identify the race/ethnicity with highest number of suicide cases. **[Identify, Extreme]** ## Marks and Channels (How) * **Marks:** Point, Line |Channel|Attribute|Using|Rationale |---|---|---|---| |Position|State, Race|-|State" and "Race" is a categorical attribute and they are represented by node. The best way to show red and blue states and race/ethnicity is to use the position. The nodes can be aligned as the outcome of the force simulation algorithm and we can place the nodes depending upon forces applied. |Color Hue|State, Race|separate| "State" and "Race" is a categorical attribute so it is represented with color hue. The best way to show red and blue states and race/ethnicity is to use color hue. The colors determines if it is a red/blue state or race/ethnicity. |Area|value|express| "Value" is a quantitative attribute so it is represented with Area. The best way to see determine number of suicide cases across different red and blue states a is to use Area in a Force Simulation (Node-Link). The Node-Link idiom will help us summarize the states as red or blue and show the number of suicide cases for each state.37:T4b5,## Data Abstraction (What) **Dataset Type:** Table |Attributes|Type & Direction| |---|---| |Suicide_Percentage|quantitative, sequential| |Method_Suicide|categorical| |Derived Attributes|Type & Direction| |---|---| |Suicide_Percentage|quantitative, sequential| * **Availability:** Static * **Time frame of Data:** 2020 * **Data Source:** [Suicides in United States](https://www.cdc.gov/suicide/suicide-data-statistics.html) ## Task Abstraction (Why) - T1: Summarize the distribution of most common methods of committing suicide. **[Summarize, Distribution]** - T2: Identify the most common method of committing suicide. **[Identify, Extreme]** ## Marks and Channels (How) * **Marks:** Arcs |Channel|Attribute|Using|Rationale |---|---|---|---| |Angular Position|Suicide_Percentage|Express|It is a quantitative attribute so the start and end angles of each arc represent the respective proportions of the data, so we use angular position to display it, making it the most effective and expressive |Color Hue|method|NA| It is a categorical attribute, and according to the task we need to distinguish the methods of committing suicide. So we use color use, making it the most effective and expressive.38:T5d7,## Data Abstraction (What) **Dataset Type:** Table |Attributes|Type & Direction| |---|---| |Suicide_Rates|quantitative, sequential| |Method_Suicide|categorical| |Gender|categorical| * **Availability:** Static * **Time frame of Data:** 2020 * **Data Source:** [Suicides in United States](https://vpc.org/revealing-the-impacts-of-gun-violence/suicide/) ## Task Abstraction (Why) - T1: Summarize the trends of most common methods of committing suicide for both males and females. **[Summarize, Trends]** - T2: Identify the most common method of committing suicide for both males and females. **[Identify, Extreme]** - T3: Compare the trends of most common methods of committing suicide between males and females. **[Identify, Extreme]** ## Marks and Channels (How) * **Marks:** Point |Channel|Attribute|Using|Rationale |---|---|---|---| |Vertical Position|Suicide_Rates|Express|It is a quantitative attribute but on the y-axis. Each year can have a different suicide rate, so we use position to display it, making it the most effective and expressive |Horizontal Position|year|Separate, Order| It is an ordinal attribute but on the x-axis. There are multiple years which needs to be shown. so we use position to display it, making it the most effective and expressive |Color Hue|Method|Separate, Order| It is a categorical attribute. There are different methods of committing suicides which needs to be shown so we use color hue to separate them, making it the most effective and expressive.39:T7e7,## Data Abstraction (What) * **Dataset Type:** Table |Attributes|Type & Direction| |---|---| |Ten-Year Age Groups|ordinal, sequential| |method|categorical| |state|categorical| |Derived Attributes|Type & Direction| |---|---| |Number of suicide cases|quantitative, sequential| * **Availability:** Static * **Time frame of Data:** 2016 - 2020 * **Data Source:** [Suicides in United States](https://wonder.cdc.gov/controller/datarequest/D76;jsessionid=C8B84AE25B40557654EAE4E01326) ## Task Abstraction (Why) * T1: Compare the suicide cases across red and blue states for different methods of suicide **[Compare, Feature]** * T2: Identify the state with highest cases of suicide due for given method of suicide **[Identify, Outliers]** * T3: Identify the Age Group with highest cases of suicide for given method of suicide **[Identify, Outliers]** ## Marks and Channels (How) * **Marks:** Area |Channel|Attribute|Using|Rationale |---|---|---|---| |Color Saturation|Number of suicide cases|Express|"Number of Suicides" is a quantitative attribute so it is represented with color saturation. The best way to see trends and patterns in number of suicide cases across different states and age group for a given method of suicide is to use color saturation in a Heatmap. The heatmap will help us analyze the patterns in suicide cases. The saturation of color implies higher or smaller count. Darker color here denotes that number of suicide cases are high and light color denotes that number of suicide cases are low. The color saturation at a glance help us see the trends and patterns in suicide cases in US states. |Horizontal Position (x-axis)|Ten-Year Age Groups|Separate, Order, Align| It is an ordinal attribute but on the x-axis. There are multiple age-groups which needs to be shown. so we use position to display it, making it the most effective and expressive. |Vertical Position (y-axis)|state|Separate, Align| There are 50 states, so the position is the most expressive and effective best to distinguish them. 3a:T5bb,## Data Abstraction (What) * **Dataset Type:** Table |Attributes|Type & Direction| |---|---| |Ten-Year Age Groups|ordinal, sequential| |State|categorical| |method|categorical| |deaths|quantitative, sequential| |Race|categorical| |Derived Attributes|Type & Direction| |---|---| |rate|quantitative, sequential| * **Availability:** Static * **Time frame of Data:** 2016 - 2020 * **Data Source:** [Suicides in United States](https://wonder.cdc.gov/controller/datarequest/D76;jsessionid=C8B84AE25B40557654EAE4E01326) ## Task Abstraction (Why) * T1: Summarize the suicide rate of different race/ethnicity by different methods of suicide **[Summarize, Feature]** * T2: Identify the method with highest suicide rate for all race/ethnicity **[Identify, Extreme]** * T3: Summarize the suicide rate of different race/ethnicity by different age groups **[Summarize, Feature]** * T4: Identify the Age Group with highest suicide rate for all race/ethnicity **[Identify, Extreme]** ## Marks and Channels (How) * **Marks:** Area |Channel|Attribute|Using|Rationale |---|---|---|---| |Color Hue|rate|Express|"rate" is a quantitative attribute so it is represented with color Hue. The best way to differentiate different age groups and methods is to use color hue, making it the most expressive and effective. |Position|method, Ten-Year Age Groups|Separate, Order| Depending upon the average suicide rate, the positions of the rectangles for methods/age-groups are determined.3b:T446,## Data Abstraction (What) **Dataset Type:** Table |Attributes|Type & Direction| |---|---| |Suicide_Percentages|quantitative, sequential| |Gun_Possessing_Household|quantitative, sequential| |States|categorical| * **Availability:** Static * **Time frame of Data:** 2020 * **Data Source:** [Suicides in United States](https://vpc.org/revealing-the-impacts-of-gun-violence/suicide/) ## Task Abstraction (Why) - T1: Identify the correlation between percentage of households possessing guns vs suicide rates for different states. **[Identify, Correlation]** ## Marks and Channels (How) * **Marks:** Point |Channel|Attribute|Using|Rationale |---|---|---|---| |Vertical Position|Suicide_Rates|Express|It is a quantitative attribute but on the y-axis.The suicide rates varies with the percentage of guns possessing household, making it the most effective and expressive |Horizontal Position|Guns_Possessing_Household|Express| It is a quantitative attribute but on the x-axis. The suicide rates varies with the percentage of guns possessing household, making it the most effective and expressive3c:T852,## Testing Plan We will be considering our first 6 idioms for usability testing * [Idea 1: Causes of Death in United States from 2000-2020 (by Mihir Mesia)](https://observablehq.com/d/72142fe4c5aa271d#cell-31) * Tasks * Can you point to the bar representing suicide death rates * Can you tell the percentage of people who died from suicides * [Idea 2: Trends in Suicide in US from 1999 - 2020 (by Harshit Gajjar)](https://observablehq.com/d/72142fe4c5aa271d#cell-21) * Tasks * Can you identify the year having peak suicide rate per 100k? * What are you able to interpret from the visualization (the trends)? * [Idea 3: Suicide rates of different race/ethnicity in blue/red states of US from 2016-2020 (by Harshit Gajjar)](https://observablehq.com/d/72142fe4c5aa271d#cell-35) * Tasks * Mention some of the red and blue states in US based on the visualization * Which is the democratic state with highest suicide rates for white * What is the race with highest suicide rate? * [Idea 4: Trends in suicide rate of different race/ethnicity in US from 2016 to 2020 (by Harshit Gajjar)](https://observablehq.com/d/72142fe4c5aa271d#cell-38) * Tasks * What is the line representing the white race? * Which year had the suicide rates for American Indian or Alaska Native? * [Idea 5: Top Method of Committing Suicide in US from 2020 (by Mihir Mesia)](https://observablehq.com/d/72142fe4c5aa271d#cell-28) * Tasks * Which is the most common method of committing suicides in usa * Can you order the method of committing suicide from most common to least common * [Idea 6: Top Method of Committing Suicide in US among male/female from 2000-2020 (by Mihir Mesia)](https://observablehq.com/d/72142fe4c5aa271d#cell-40) * Tasks * What are the methods of committing suicide among males and females. * What is the most common method of committing suicides for males and females. 3d:[{"id":"5a79b8e8cf5d6bbbc1c1c709acc1bdf189ae11ea79d612e653a314918901dd8904166f73fa7a882f8b9e3239211a5d7c532fcced724d08a0575a14d47dcff53c","href":"https://static.observableusercontent.com/files/5a79b8e8cf5d6bbbc1c1c709acc1bdf189ae11ea79d612e653a314918901dd8904166f73fa7a882f8b9e3239211a5d7c532fcced724d08a0575a14d47dcff53c","name":"Screen Shot 2023-04-04 at 7.22.29 PM.png","type":"image/png","lastModified":1680711162306.147,"size":824805},{"id":"bcfa28dc2662473f1fadb4c5928c3cc705a719bb149377208d052e718091e4c9c85f55386046dc1184ec6b2947e5d8e1e0fa3169e418c9a06800bb71e4514d00","href":"https://static.observableusercontent.com/files/bcfa28dc2662473f1fadb4c5928c3cc705a719bb149377208d052e718091e4c9c85f55386046dc1184ec6b2947e5d8e1e0fa3169e418c9a06800bb71e4514d00","name":"Screen Shot 2023-04-04 at 7.22.35 PM.png","type":"image/png","lastModified":1680711211367.529,"size":38007},{"id":"7497e7eaf5b9fdeed6b4588a558883fb0fc1119af068ee4a3001726e9b36529483226dffcef13b12ab56767413d3b09e0c045b684532cf553766e4e10e01f678","href":"https://static.observableusercontent.com/files/7497e7eaf5b9fdeed6b4588a558883fb0fc1119af068ee4a3001726e9b36529483226dffcef13b12ab56767413d3b09e0c045b684532cf553766e4e10e01f678","name":"Screen Shot 2023-04-04 at 7.23.15 PM.png","type":"image/png","lastModified":1680711380310.304,"size":1021596},{"id":"8baef4204fcff5d7e4a43dba9855ae6c890ec3bf8751ddf5ff2b7619a161bedc2bf68dfb4c7c5cc49ce0707656d4c775e2a87bb9329fe255163242341cfe56eb","href":"https://static.observableusercontent.com/files/8baef4204fcff5d7e4a43dba9855ae6c890ec3bf8751ddf5ff2b7619a161bedc2bf68dfb4c7c5cc49ce0707656d4c775e2a87bb9329fe255163242341cfe56eb","name":"Screen Shot 2023-04-04 at 7.24.18 PM.png","type":"image/png","lastModified":1680711380249.008,"size":1004386},{"id":"04f60476d582a57e41b2e15fe55f05c9261469e933d7063fbf840ad6e6c44675b0e111c3f83804751399be2e58b95279365bf40382d9ac098ebae83147028033","href":"https://static.observableusercontent.com/files/04f60476d582a57e41b2e15fe55f05c9261469e933d7063fbf840ad6e6c44675b0e111c3f83804751399be2e58b95279365bf40382d9ac098ebae83147028033","name":"xxDqNL1xLxC67dymMyXbUV0afNTVRZ8_XxvEeWhMX5X-Zg4lDVZzEi-FK58OBt6nxzi56OkhrMGBTf72zYERdE5o10Iy7LT4yN8RaB5FofZTLglj96BbQ85-j7ab.png","type":"image/png","lastModified":1680888105966.613,"size":39837},{"id":"4d6914d80c7d4803c5baf65521f480a48e96a34cec440ad345efeec7ed68e5fa0096af55c714185f14c4cb356a0cb045aa6ff987770a8d8ded6c336b53d888d8","href":"https://static.observableusercontent.com/files/4d6914d80c7d4803c5baf65521f480a48e96a34cec440ad345efeec7ed68e5fa0096af55c714185f14c4cb356a0cb045aa6ff987770a8d8ded6c336b53d888d8","name":"Screen Shot 2023-04-04 at 10.25.44 PM.png","type":"image/png","lastModified":1680710874014.579,"size":1903333},{"id":"ff9d599d0c1ac5203e47388c85470a1aa27b7b6bf3390e25579941f2b9a4f8888a23d17e645ed9bd0be5dbf19f941bd7b7e412a221369a12e3e635619c123bf3","href":"https://static.observableusercontent.com/files/ff9d599d0c1ac5203e47388c85470a1aa27b7b6bf3390e25579941f2b9a4f8888a23d17e645ed9bd0be5dbf19f941bd7b7e412a221369a12e3e635619c123bf3","name":"i15eYvDHku_W2y1UcR4_diVZ9wY-IF_xSjWBfOYlKvBB5HcUVL0gM0-Zs6yE1qRCcGOmJ1TI1ZaQhCgc0pap_Li8DA2opMyQN-9CsTyYCYF0tK7GEjmfuZpGEa4X.png","type":"image/png","lastModified":1680888415422.035,"size":55011},{"id":"ff9d599d0c1ac5203e47388c85470a1aa27b7b6bf3390e25579941f2b9a4f8888a23d17e645ed9bd0be5dbf19f941bd7b7e412a221369a12e3e635619c123bf3","href":"https://static.observableusercontent.com/files/ff9d599d0c1ac5203e47388c85470a1aa27b7b6bf3390e25579941f2b9a4f8888a23d17e645ed9bd0be5dbf19f941bd7b7e412a221369a12e3e635619c123bf3","name":"i15eYvDHku_W2y1UcR4_diVZ9wY-IF_xSjWBfOYlKvBB5HcUVL0gM0-Zs6yE1qRCcGOmJ1TI1ZaQhCgc0pap_Li8DA2opMyQN-9CsTyYCYF0tK7GEjmfuZpGEa4X@1.png","type":"image/png","lastModified":1680888517335.089,"size":55011},{"id":"7622074beb70be6cd27e709c18e9f0a52198ef19559fec827f506ab116d8f3e1bbbadd371c12cecb41d757ffe24899123706dca128b8bffd9bc7a521f6a12630","href":"https://static.observableusercontent.com/files/7622074beb70be6cd27e709c18e9f0a52198ef19559fec827f506ab116d8f3e1bbbadd371c12cecb41d757ffe24899123706dca128b8bffd9bc7a521f6a12630","name":"5pVu43OdRDNYgod1TwVpreIsYR7wxqu1-MRCKkG7rqmXE5OdwVI66qdQhzOZBGqfv3J-4wmWa8ZYMKpdBrfR-qMZqymOyZeqQTJi99_D16F1xKvr6q7IRLJpvq45.png","type":"image/png","lastModified":1680888517364.599,"size":65617}] 2f:{"id":"72142fe4c5aa271d","slug":null,"title":"Analyzing suicides in US","thumbnail":"716cfff367bbd531604ef031d173be7a46536b053d96b03fa97ecab501bffb8a","access_level":"public","create_time":"$D2023-04-04T14:54:00.304Z","update_time":"$D2023-04-07T17:29:26.057Z","view_time":null,"first_public_time":"$D2023-04-04T14:54:00.304Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"666e343e9fc70af6","login":"hg24","name":"Harshit Gajjar","avatar_url":"https://avatars-next.observableusercontent.com/6f17a096ab3d83e4a953387b0069b305478a67613578aa9ebebb8eaa88a66abb","tier":"starter_2024","bio":""},"version":386,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"5e2ba07857faed1b","login":"hg24","name":"Harshit Gajjar","avatar_url":"https://avatars-next.observableusercontent.com/6f17a096ab3d83e4a953387b0069b305478a67613578aa9ebebb8eaa88a66abb","tier":null,"bio":""},{"type":"individual","id":"32dbd113dcc8c335","login":"mihir22","name":"Mihir Mesia","avatar_url":"https://avatars-next.observableusercontent.com/3d8d930a2f3e4639902c550efcac7f7fba4dda4fdab2f6f72d6e03db2b3bb3be","tier":null,"bio":""}],"members":[{"type":"individual","id":"5e2ba07857faed1b","login":"hg24","name":"Harshit Gajjar","avatar_url":"https://avatars-next.observableusercontent.com/6f17a096ab3d83e4a953387b0069b305478a67613578aa9ebebb8eaa88a66abb","tier":null,"role":"editor"},{"type":"individual","id":"32dbd113dcc8c335","login":"mihir22","name":"Mihir Mesia","avatar_url":"https://avatars-next.observableusercontent.com/3d8d930a2f3e4639902c550efcac7f7fba4dda4fdab2f6f72d6e03db2b3bb3be","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Analyzing suicides in US","cells":[{"id":0,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":177,"value":"## Suicide Accounts for 8% of Total Deaths in the US Over the Past Two Decades","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":31,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":209,"value":"$32","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":142,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":146,"value":"## Insight 3: White populations have higher suicide rates in red states compared to blue states in US from 2016-2020 (by Harshit Gajjar)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":35,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":232,"value":"$34","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":334,"value":"## Iterations","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":339,"value":"### Iteration 1","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":344,"value":"key = FileAttachment(\"Screen Shot 2023-04-04 at 7.22.35 PM.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":341,"value":"nl1 = FileAttachment(\"Screen Shot 2023-04-04 at 7.22.29 PM.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":347,"value":"- Made a node-link visualization, to show suicide cases among different race and ethnicity across blue/red states.\n- Problem: The viz is very crowded and states are not clearly visible.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":350,"value":"### Iteration 2","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":352,"value":"FileAttachment(\"Screen Shot 2023-04-04 at 7.22.35 PM.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":355,"value":"FileAttachment(\"Screen Shot 2023-04-04 at 7.23.15 PM.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":364,"value":"- In the version 2, modified the viz and separated the red and blue states and kept the race/ethnicity in center.\n- Problem: The insight might not be accurate since, data is not normalized.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":358,"value":"### Iteration 3","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":360,"value":"FileAttachment(\"Screen Shot 2023-04-04 at 7.22.35 PM.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":362,"value":"FileAttachment(\"Screen Shot 2023-04-04 at 7.24.18 PM.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":366,"value":"- In the version 3, modified the viz and normalized the data to find interesting insights.\n- Insight 1: White population have higher suicide rate in red states.\n- Insight 2: Red states recorded higher rates compared to blue states.\n- Insight 3: American Indian or Alaska Native race have suicides in red states and only 1 blue state of new mexico.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":171,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":183,"value":"## Firearms Dominate Male Suicides, While Poisoning Prevails Among Females","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":40,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":378,"value":"## Iteration 1\n![xxDqNL1xLxC67dymMyXbUV0afNTVRZ8_XxvEeWhMX5X-Zg4lDVZzEi-FK58OBt6nxzi56OkhrMGBTf72zYERdE5o10Iy7LT4yN8RaB5FofZTLglj96BbQ85-j7ab.png](${await FileAttachment(\"xxDqNL1xLxC67dymMyXbUV0afNTVRZ8_XxvEeWhMX5X-Zg4lDVZzEi-FK58OBt6nxzi56OkhrMGBTf72zYERdE5o10Iy7LT4yN8RaB5FofZTLglj96BbQ85-j7ab.png\").url()})\n\nI wanted to analyse the trends in suicides rates for past two decades for different methods. I tried the stacked bar chart, and due to the align problem it became difficult to compare the trends among different methods.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":381,"value":"## Iteration 2\n\n![i15eYvDHku_W2y1UcR4_diVZ9wY-IF_xSjWBfOYlKvBB5HcUVL0gM0-Zs6yE1qRCcGOmJ1TI1ZaQhCgc0pap_Li8DA2opMyQN-9CsTyYCYF0tK7GEjmfuZpGEa4X.png](${await FileAttachment(\"i15eYvDHku_W2y1UcR4_diVZ9wY-IF_xSjWBfOYlKvBB5HcUVL0gM0-Zs6yE1qRCcGOmJ1TI1ZaQhCgc0pap_Li8DA2opMyQN-9CsTyYCYF0tK7GEjmfuZpGEa4X.png\").url()})\n\nTo solve the problem faced in the previous iteration, I tried the line chart. Though I was able to see the trends clearly, but the visualization was for the combined value of both the genders.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":383,"value":"## Iteration 3(Selected)\n\n![5pVu43OdRDNYgod1TwVpreIsYR7wxqu1-MRCKkG7rqmXE5OdwVI66qdQhzOZBGqfv3J-4wmWa8ZYMKpdBrfR-qMZqymOyZeqQTJi99_D16F1xKvr6q7IRLJpvq45.png](${await FileAttachment(\"5pVu43OdRDNYgod1TwVpreIsYR7wxqu1-MRCKkG7rqmXE5OdwVI66qdQhzOZBGqfv3J-4wmWa8ZYMKpdBrfR-qMZqymOyZeqQTJi99_D16F1xKvr6q7IRLJpvq45.png\").url()}), ![i15eYvDHku_W2y1UcR4_diVZ9wY-IF_xSjWBfOYlKvBB5HcUVL0gM0-Zs6yE1qRCcGOmJ1TI1ZaQhCgc0pap_Li8DA2opMyQN-9CsTyYCYF0tK7GEjmfuZpGEa4X@1.png](${await FileAttachment(\"i15eYvDHku_W2y1UcR4_diVZ9wY-IF_xSjWBfOYlKvBB5HcUVL0gM0-Zs6yE1qRCcGOmJ1TI1ZaQhCgc0pap_Li8DA2opMyQN-9CsTyYCYF0tK7GEjmfuZpGEa4X@1.png\").url()})\n\nI realised that the two different line charts for both the genders would be more insightful, so I did two line charts showing trends in suicide per 100k for various method for both the gender.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":385,"value":"## Insights\n\n- Firearm was the most common method of committing suicide in males and the trends for it has been increasing while for suffocation and posinoing there has been slight decline after 2017. While in females poisoning was the most common method till 2015 , after which the firearm became the top method. There has been significant increase in suicides by suffocation among females\n\n- Among males the firearm was the most common and it’s trend has been increasing over the years, while in case of females poisoning was the most common method till 2015, after which it showed and decline and it was overtaken by firearms.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":288,"value":"$38","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":165,"value":"