2b:null 2c:["$","title",null,{"children":"Post-Pandemic Surge in Mortgage Rates | Kasi Viswanath | Observable"}] 31:Te0d,## Intro: The mortgage industry in the USA has undergone significant changes over the past decade. Mortgage rates, which are a crucial factor in determining the affordability of home ownership, have fluctuated during this time. Understanding these fluctuations is important for prospective homeowners as well as industry stakeholders. This article aims to provide an analysis of the evolution of USA mortgage rates from 2013 to 2022. It highlights the trends, fluctuations, and significant changes that have taken place during this period. ## Insights: - After the pandemic, USA saw a steep increase in mortgage rates - During the pandemic the lowest mortgage rates were recorded in USA, regardless of whether they were 15-year fixed rates or 30-year fixed rates, since 2014 - From 2018 to 2022, the least difference between 30-year fixed rates and 15-year fixed rates was noticed ## Data Abstraction(What): - Dataset type: Temporal - Dataset Availability: Static - Attributes: - Mortgage Rate Type - ordinal - This attribute describes where the term is 15-year or 30-year) - Mortgage Rate - Quantitative(sequential orientation) - This attribute contains the interest rate - Date - ordinal - This attribute contains the date recorded for the mortgage interest - Derived Attribute: - Excess of 30-year fixed rate from Mortgage Rate - Quantitative(sequential orientation) ## Tasks Abstraction(Why): - T1 : Compare the USA mortgage rates from 2013 till 2022 [Compare, Extremes] - T2 : Identify the year in which the lowest mortgage was recorded in the USA [Identify, Extremes] - T3 : identify the year in which has least change b/w 30-year fixed rates and 15-year fixed rates[Identify, Trends] ## Marks and Channels (How): - Mark:- Line - Channel - **Length:** Indicates the Mortgage rate in the Stacked Area chart - Attribute: Mortgage Rate - Task: T1,T2,T3 - Expressiveness : The tasks expresses mortgage rate from the dataset - Effectiveness : The length indicates how much the mortgage rate defined for 15-year or 30-year fixed rate - **Color Hue:** To differentiate Mortgage Rate Type either 15 or 30-year fixed rate - Attribute: Mortgage Rate Type - Task: T1,T2 - Expressiveness : The channel expresses the distinct type of mortgage types from the dataset - Effectiveness : The hue indicate what kind of mortgage type ## Target Audience - Prospective homeowners who seek a favorable mortgage interest rate when buying a property - Industry stakeholders who are interested in knowing market trends to invest ## Critique - T1: The Stacked Area chart is very efficient in conveying the trend of mortgage rate in USA over the period of time - T2: The designer clearly pointed out that the lowest mortgage was observed in 2021 - T3: The years in which there is less increase in mortgage rate in visualization could have been highlighted The graph presents the data in a visually appealing manner, making it easy to understand the trend in the mortgage rate. However, to further enhance the usefulness of the graph, it would be ideal if it could show the exact amount of change in the mortgage rate compared to the previous year. This information would provide a deeper level of analysis and allow the user to gain a better understanding of the fluctuations in the mortgage rate over time. Additionally, having this information readily available could also help in making informed decisions related to mortgage rates.32:T463,tableauhtml = html`

`33:[] 2f:{"id":"8eb8599fe4195146","slug":null,"title":"Post-Pandemic Surge in Mortgage Rates","thumbnail":"df80de9073b18641fb4e9591436eec169d1eb443d67e25959a35bfda98e2b68f","access_level":"public","create_time":"$D2023-02-08T05:09:16.190Z","update_time":"$D2023-02-22T06:43:17.876Z","view_time":null,"first_public_time":"$D2023-02-08T05:09:16.190Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"b760ea566a896d7d","login":"kasivisu4","name":"Kasi Viswanath","avatar_url":"https://avatars-next.observableusercontent.com/48e36723913e7e5b18b906e1d7cde12fad4146715e78bbf74d3db7969a248b56","tier":"starter_2024"},"version":164,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"fcd94e1c1ca12ae9","login":"kasivisu4","name":"Kasi Viswanath","avatar_url":"https://avatars-next.observableusercontent.com/48e36723913e7e5b18b906e1d7cde12fad4146715e78bbf74d3db7969a248b56","tier":null}],"members":[{"type":"individual","id":"fcd94e1c1ca12ae9","login":"kasivisu4","name":"Kasi Viswanath","avatar_url":"https://avatars-next.observableusercontent.com/48e36723913e7e5b18b906e1d7cde12fad4146715e78bbf74d3db7969a248b56","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":{"id":"14a0961462b84603","slug":"dataviz","title":"DataViz","owner":{"id":"b760ea566a896d7d","login":"kasivisu4","name":"Kasi Viswanath"}},"type":"notebook","body":{"title":"Post-Pandemic Surge in Mortgage Rates","cells":[{"id":0,"value":"# Post-Pandemic Surge in Mortgage Rates\n\n Homework 3: Visualization Problem Abstraction and Critique\n- Created by [Kasi Viswanath Vandanapu](https://vandanapuk.sites.northeastern.edu/)\n- Class [CS 7295: Special Topics Course / Information Visualization](https://johnguerra.co/classes/data_visualization_spring_2023/)\n- Professor Name : [John Alexis Guerra Gómez](https://johnguerra.co)\n- [Tweet](https://twitter.com/kasi_vandanapu/status/1623226753455120390)\n\nThis is a critique of the visualization [Tableau dashboard](https://public.tableau.com/app/profile/enrique.mendoza3617/viz/MortgageRatesHaveSpikedSince2022/Dashboard1) following Tamara's grammar from the book Visualization Analysis and Design ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":30,"value":"htmlElement = html`

${tableauhtml}

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":146,"value":"## Analysis Video\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":59,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":133,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":7,"value":"$32","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":22,"value":"divElement = {\n return htmlElement.querySelector(\"#viz1675833112912\");\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":27,"value":"{\n \n \n let vizElement = divElement?.getElementsByTagName(\"object\")[0];\n vizElement.style.width = \"1200px\";\n vizElement.style.height = \"827px\";\n let scriptElement = document.createElement(\"script\");\n scriptElement.src = \"https://public.tableau.com/javascripts/api/viz_v1.js\";\n vizElement.parentNode.insertBefore(scriptElement, vizElement);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 30:"$2f:body"