2b:null 2c:["$","title",null,{"children":"Visual Landscape of Shark Tank India | Akhila Sulgante | Observable"}] 31:T5a9,## Target Audience 1. People who are interested to learn about Shark Tank India Investments: This audience includes individuals who are interested in the world of entrepreneurship, startups, and venture capital. They may be interested in learning about the investment process of Shark Tank India and the types of businesses that are successful in securing funding. They may also want to gain insights into the strategies of the Sharks and the characteristics they look for in potential investments 2. People who want to analyze Shark Tank India Sharks portfolio: This audience includes individuals who are interested in the investment strategies of the Sharks and want to analyze their portfolio of investments. They may be investors themselves who are looking to learn from the success of the Sharks or entrepreneurs who want to understand what types of businesses the Sharks are interested in 3. Startup founder who is looking to appear on Shark Tank India and seeking Investment: This audience includes entrepreneurs who are looking to secure funding for their startup and see Shark Tank India as a potential avenue for investment. They may be looking to learn about the investment process, what the Sharks look for in a potential investment, and how to make a successful pitch to the Sharks. They may also want to analyze the past investments made by the Sharks to gain insights into what types of businesses are successful in securing funding32:T55c,**Akhila** I focused on understanding the Investment patterns of Shark Tank India by increasing the granularity in each step. The purpose of understanding this is to provide a detailed view of the kinds of deals made on the show. By analyzing this, users can draw their own sights. It might also help a prospective Shark Tank Contestant to understand the potential Shark that might be interested in investing in the startups. Story Plot: 1. Understanding the overview, Summarizing the data to understand how many companies received an offer from the Sharks and how many did not. Amongst the ones that received offers, how many companies accepted the offer and how many companies did not? As the last steps, Industries are also included in this exploration to understand the trends of the above-mentioned bins 2. Summarizing Shark's portfolio by the amount they have invested in each Industry. This will help us identify the Industry choice of each Shark 3. Discovering the companies that each shark has invested in 4. Analyzing the mutual and individual investments of sharks. Here we explore the companies that got joint investments from sharks and the ones that did not 5. Dissecting the investment pattern by the count of companies. This will provide us with the count of companies and the exact pair-up of sharks. It helps is identifying the sharks that invest alike33:T5b1,#### Problem Abstraction **Data Abstraction** **Dataset Availability:** Static
**Dataset Type:** Table
Attribute used:
**Pitcher's state(Categorical):** This attribute projects states that the pitchers belong to
**Industry(Categorical):** This attribute indicates industries that participated in Shark Tank
**Count of Season 1(Quantitative, sequential):** This is a _derived_ attribute that displays the number of companies that participated in Season 1 for each state and for each industry
**Count of Season 2(Quantitative, sequential):** This is a _derived_ attribute that displays the number of companies that participated in Season 2 for each state and for each industry
**Difference(Quantitative, Diverging):** This is a _derived_ attribute that displays the difference in pitches from season 2 to season 1
#### Tasks (why) T1: Identify the change in sports company participation in each state (**Identify / Trends**)
Sub Task1: Compare the change in the sports industry in each state (**Compare / Dependency**)
Sub Task2: Identify if the change is positive or negative (**Compare / Dependency**)
#### How **Marks:** Line
**Channels:**
Position: To indicate the difference from season 1 to season 2
Text: To indicate industry and increase and decrease in the pitch count
Color hue: To differentiate the Industry or state
Expressivity Principle: Express
34:T5c3,#### Problem Abstraction **Data Abstraction** **Dataset Availability:** Static
**Dataset Type:** Table
Attribute used:
**Industry(Categorical):** This attribute indicates industries that participated in Shark Tank
**Average Valuation Requested(Quantitative, sequential):** This is a _dervied_ attribute that indicates the average valuation asked by companies in a particular industry
**Average Valuation offered(Quantitative, sequential):** This is a _dervied_ attribute that indicates the average valuation offered by sharks in a particular industry
**Valuation Requested(Quantitative, sequential):** This attribute is used in computing the average valuation asked of an industry **Deal Valuation(Quantitative, sequential):** This attribute is used in computing the average deal amount offered asked of the industry #### Tasks (why)
T1: Derive the average valuation asked by companies in the Entertainment industry[Derive, distribution] Sub Task1: Derive the average offered by sharks in the Entertainment industry[Derive, distribution] Sub Task2: Compare the difference with other industries[Identify, extreme] #### How
Marks: Line, point
Channel
Position: indicating average valuation asked and offered
Color hue: To differentiate valuation asked and offered and positive and negative change in the average
length: Difference in average valuation asked and offered
Expressivity Principle: Express
35:T6c2,#### Problem Abstraction In this section, I have performed problem abstraction on the above zoomable Icicle chart **Data Abstraction**
**Dataset Availability:** Static
**Dataset Type:** Table
Attribute used:
**`Industry`** (_Categorical_): This attribute indicates the industry the startup name belongs to
**` Received Offer`** (_Categorical_): This attribute indicates if the company received an offer
**` Accepted Offer`** (_Categorical_): This attribute indicates if the company accepted the offer
**` Total Received Offer`** (_Quantitative, Sequential_): This is a _derived_ attribute obtained by summing up the count of companies that received an offer
**` Total Accepted Offer`** (Quantitative, Sequential): This is a _derived_ attribute obtained by summing up the count of companies that Accepted the offer
**` Total No offer received`** (_Quantitative, Sequential_): This is a _derived_ attribute obtained by summing up the count of companies that did not receive an offer
#### Tasks (why) Task 1: Identify the industries that received an offer from Sharks by summing the companies in it[Identify, distribution]
Sub Task 1: Identify the industries that accepted the offer[Idetify, distribution]
Sub Task 2: Identify the industries that did not accept the offer[Identify, distribution]
Sub Task 3: Identify the industry that did not reject any offer[Identify, feature]
#### How Marks: Area
Channels:
Position: To identify the levels in the icicle
Size: To indicate the companies in each category
Color hue: To differentiate companies that received offers and the ones that did not
Principle: Separate, order, and align
36:T4b6,#### Problem Abstraction In this section, I have performed problem abstraction on the above cascaded Treemap chart **Data Abstraction**
**Dataset Availability:** Static
**Dataset Type:** Table
Attribute used:
**`Industry`** (_Categorical_): This attribute indicates the industry the startup name belongs to
**`{Shark} Investment Amount`** (_Quantitaive, sequential_): This attribute determines the amount each shark has invested
**` Sharks`** (_Categorical_): This attribute was not directly available and was extracted from the column "{Shark} Investment Equity", by splicing the names of the shark from the column #### Tasks (why) Task 1: Identify the sharks that have their investment in the food industry as the majority[Identify, distribution] sub-task 1: Locate the food industry in each shark's portfolio[Locate, Distribution] Sub-task 2: Identify the sharks that have food as their highest investment[Identity, exterme] #### How
Mark: Area
Channel
Position: Sharks that invested the most to least, industries that got most investment amount from most to least
Color hue: To differentiate levels
Principle: Separate, order, and align
37:T4ea,#### Problem Abstraction In this section, I have performed problem abstraction on the Bar chart **Data Abstraction**
**Dataset Availability:** Static
**Dataset Type:** Table
Attribute used:
**`Industry`** (_Categorical_): This attribute indicates the industry the startup name belongs to
**`Startup Name`** (_Categorical_): These attribute indicates the startup name that got an offer
**Derived Attribute**
**` Sharks`** (_Categorical_): This attribute was not directly available and was extracted from the column "{Shark} Investment Equity", by splicing the names of the shark from the column
**`{Shark} Investment Amount`** (_Quantitaive, sequential_): This attribute determines the amount shark has invested in each company
#### Tasks (why) Task 1: Identify the company Namita has invested the highest amount in[Identify, Extereme]
Sub Task 1: Browse all the companies in which Namita is an investor[Browse, Distribution]
Sub Task 2: Locate the company with the highest amount invested[Identify, extreme]
#### How Marks: Line
Channel:
Position: The amount Shark has invested in a company
Color Hue: To differentiate Industries
Expressivity: Separate, order and align
38:T908,#### Problem Abstraction In this section, I have performed problem abstraction on the Force-directed network chart **Data Abstraction**
**Dataset Availability:** Static
**Dataset Type:** Table
Attribute used: **`Industry`** (_Categorical_): This attribute indicates the industry the startup name belongs to **`Startup Name`** (_Categorical_): These attribute indicates the startup name **`{Shark} Investment Equity`** (_Quantitative, Sequential_): This attribute is used to link startups with sharks if they have made an investment **Derived Attribute** **` Sharks`** (_Categorical_): This attribute was not directly available and was extracted from the column "{Shark} Investment Equity", by splicing the names of the shark from the column #### Tasks (why) Compare the number of companies that got individual investment and mutual from Sharks
Sub-task 1: (_Explore_) the companies that got individual investment from sharks(_paths_)
Sub-task 2: (_Explore_) the companies that got mutual investment from sharks(_paths_)
Sub-task 3: (_Compare_) the number of companies that got joint and individual investment #### How * **Marks:** Point, Line * **Channel:** * Color Hue: To identify different industries that the nodes are associated to * Attribute: Startup Name * Task: T1, T2 * Using **seperate** * **Expressiveness principle** - Since Startups are associated with a particular industry making easier to differentiate when identified by colors * **Effectiveness principle** - The different colors of the nodes indicate different industries * Size: To differentiate shark nodes from start-up nodes * Attribute: Sharks(dervied) * Task: T1, T2 * Using **seperate** * **Expressiveness principle** - Since the sharks are displayed with the bigger circle and the startup with the smaller one, it shows all the data very efficiently * **Effectiveness principle** - Since the size is reasonably different, it is easier to differentiate between Sharks and Startup nodes * Position: To draw the nodes on the screen * Attribute: Sharks(dervied) and start up name * Task: T1, T2 * Using **Express** * Although the position is not going to directly express an attribute, it is directed by the forces on the graph 39:T4ee,#### Problem Abstraction In this section, I have performed problem abstraction on the upset chart **Data Abstraction**
**Dataset Availability:** Static
**Dataset Type:** Table
Attribute used:
**Sharks(Categorical):** This attribute indicates the sharks in Shark Tank India
**Degree(Quantitative, sequential):** This is a _derived_ attribute that indicates number of sharks involvement in deals
**Prevalence(Quantitative, sequential):** This is a _derived_ attribute that count of the companies in different combinations of sharks involvement
**Seasons(Categorical):** This indicates the seasons of Shark Tank India
**Count(Quantitative, sequential):** This indicates the Count of companies sharks have invested in together or individually
#### Tasks (why) T1: Identify the pair that have invested the most together[Identify, Extreme]
Sub Task1: Locate all pairs that have invested together[Locate, Distribution]
Sub Task 2: Identify the pair that has the most investment[Identify, extreme]
#### How
Marks: Line, point
Channels:
Position: To indicate the count and degree
Color hue(Images): To differentiate the sharks
Expressivity Principle: Separate, order, and align
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\nVideo showing Problem Abstraction: [Akhila](https://youtu.be/jc7Rulg6bwQ)
\n\nTweet Link: [Akhila](https://twitter.com/akhila_sulgante/status/1651303489723863041?t=h1uYNP-yuZEEojnb9mxg8g&s=08), [Kasi](https://twitter.com/kasi_vandanapu/status/1651307972327542784)
\nSlides: [Akhila](https://docs.google.com/presentation/d/15cr6D1-7xmXGjOsldyaz6e6145V-y5b7CEhxNEP-FVM/edit#slide=id.p),[Kasi](https://docs.google.com/presentation/d/1PevNDLcyN2kdiz2EyhU2oqpLWh7s8Qc4THSvgkGgZWI/edit#slide=id.g21ea3c364aa_1_308)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":7,"value":"This notebook is created by [Akhila Sulgante](https://akhilasulgante.github.io/portfolio) and [Kasi Viswanath Vandanapu](https://kasivisu4.github.io/) as a part of the final Project submission for the [CS 7295 class](https://johnguerra.co/classes/data_visualization_spring_2023/) at Northeastern under the guidance of [prof. John Alexis Guerra Gómez](https://johnguerra.co/)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":36,"value":"#### Note: This notebook refers to startup companies and the ecosystem of Shark Tank India. It in no way refers to the entire Startup Culture of India","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":9,"value":"## Introduction\n\nShark Tank India is an Indian Hindi-language business reality television series that airs on Sony Entertainment Television. The show is the Indian franchise of the American show Shark Tank. It shows entrepreneurs making business presentations to a panel of investors or sharks, who decide whether to invest in their company.\n\nShark Tank India (season 1) aired from 20th December 2021 to 4th February 2022. Shark Tank India (season 2) aired on 2nd Jan 2023. \n\nIn this notebook, we explore the Participation and Investment patterns of Shark Tank India. Our objective is to present the data from Shark Tank India in a clear and concise way, allowing users to derive insights and draw their own conclusions. Through our visualizations, we aim to provide a better understanding of the trends and patterns in the show, helping entrepreneurs, investors, and fans alike to stay up-to-date with the latest happenings in the Indian startup world(Companies that appeared on the show). ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":51,"value":"## Data source\n\nData used for this visualization :[Data link](https://www.kaggle.com/datasets/thirumani/shark-tank-india)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":17,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":19,"value":"## Main Insights\n\n**Kasi**\n\n_Exploring the participation_\n1. Maharashtra sees a decrease in pitches by almost 50% in Season 2 as compared to Season 1\n2. Entertainment is the only industry where Sharks offered a higher valuation than the original ask from the contestants","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":22,"value":"**Akhila**\n\n_Exploring the Investment Patterns_\n1. From analyzing previous investments, it is seen that the startups on Shark Tank India have a high chance of getting an offer from the Sharks\n2. Sharks like to diversify their portfolio, and an interesting find is that Sharks Amit and Anupam have their highest investment amount in Beauty/Fashion, which is an industry that is not linked to the domain they have expertise in\n3. Peyush has a significant amount invested in the service industry, but the count of service-based startups he has invested in is just 4\n4. Pyeush and Namita are the only two sharks that have invested in Agriculture companies on Shark Tank\n5. Amit Jain prefers investing solo in the startups than teaming up with other sharks ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":32,"value":"## Story line\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":34,"value":"**Kasi**\n\nI focused on exploring the participation trends in Shark Tank India. I compared states on their participation count based on Season 1 and Season 2. I also focused on exploring the industry-wise change in each state. In this exploration, the user also has the ability to see industry-wise change and it is reflected from the state's point of view. I have also analyzed the valuation difference that was offered on the Shark Tank and the original ask from the companies.\n\nStory Plot:\n1. Explore the States and/or Industries that saw an increase and decrease in pitches in season 2 as compared to Season 1\n2. Assess the valuation difference that was offered on the show for each Industry\n\n**Note: Rest of my three charts are from my research [here](https://observablehq.com/@kasivisu4/research-notebook-for-grading)**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":41,"value":"$32","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":46,"value":"## Participation on Shark Tank India (kasi)\n[Usabiltiy study report](https://docs.google.com/document/d/1siXqg_9mnEovVYrGR5YmbPX7e6GDG0IoNgbuU3i8bBI/edit?usp=sharing)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":53,"value":"### Exploring the Participation of Industries and States on Shark Tank India","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":57,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":61,"value":"$33","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":66,"value":"### Accurately Assessing Industry Valuations","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":70,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":73,"value":"$34","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":77,"value":"## Understanding the investment patterns on Shark Tank India\n_By Akhila_\n\n\n[Slides](https://docs.google.com/presentation/d/15cr6D1-7xmXGjOsldyaz6e6145V-y5b7CEhxNEP-FVM/edit#slide=id.g21d948be3a6_0_57)
\n[Usability study report](https://docs.google.com/document/d/1GEAVRsfscFDTJP4PyOHF_exoeeN8dw2hVPrLDsYSpro/edit)\n\nHighlights:\n\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":130,"value":"screenshot20230426At032629 = FileAttachment(\"Screenshot 2023-04-26 at 03.26.29.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":132,"value":"screenshot20230426At032644 = FileAttachment(\"Screenshot 2023-04-26 at 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