Investment Trends in Indian Startups
An Exploration of Indian Startup Funding Rounds
By [source]
About this dataset
This project aims to explore the fascinating Indian Startup Funding Landscape. By utilizing two datasets, 'startup_cleaned' and 'startup_funding', each containing different yet complementary features, this study will analyze investment patterns across startups operating in India. With seven columns including details such as date, start-up name, verticals and sub-verticals associated with them, city of their operations and investors involved in the funding round - the ‘startup_cleaned’ dataset offers a broad overview of the Indian startup ecosystem. The ‘startup_funding’ dataset contains 10 columns which provide a more detailed look into the investments made in each startup - from investors name and investment type to amount invested & remarks offering additional insights. This analysis seeks to discover interesting trends & correlations between different industry sectors & cities which have enabled a dynamic entrepreneurship ecosystem in India that continues to attract global investments despite daunting challenges ahead
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How to use the dataset
To use this dataset effectively you need to first become familiar with the data that has been provided. The columns labeled ‘Sr No’ and ‘Date dd/mm/yyyy’ denote the Unique serial number associated with each start-up as well as the date of investment made into it respectively. You can group all investments made around a particular date range or even view individual investments by referring to these two columns.
Research Ideas
- Investigating investor trends - Analyzing what types of startups investors often invest in, where these investments occur, and how much they typically invest can inform entrepreneurial strategy when it comes to finding potential investments.
- Mapping startup ecosystems - Compiling the data into large-scale maps can show hotspots for startup activity and help visualize the diversification of the Indian startup ecosystem.
- Analyzing impact - Examining investment patterns over time as well as in specific cities or industry verticals can provide insight into how government regulation, trade agreements, and other factors affectIndia's economy and business landscape
Acknowledgements
If you use this dataset in your research, please credit the original authors.
Data Source
License
License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
Columns
File: startup_cleaned.csv
| Column name |
Description |
| date |
Date of the investment round. (Date) |
| startup |
Name of the startup. (String) |
| vertical |
Industry sector of the startup. (String) |
| subvertical |
Sub-sector of the startup. (String) |
| city |
Location of the startup. (String) |
| investors |
Name of the investors. (String) |
| amount |
Amount of investment in USD. (Integer) |
File: startup_funding.csv
| Column name |
Description |
| **Sr No** |
A unique identifier for each startup. (Integer) |
| Date dd/mm/yyyy |
The date of the investment. (Date) |
| Startup Name |
The name of the startup. (String) |
| Industry Vertical |
The industry sector the startup operates in. (String) |
| SubVertical |
The sub-sector the startup operates in. (String) |
| City Location |
The city the startup is located in. (String) |
| Investors Name |
The name of the investor. (String) |
| InvestmentnType |
The type of investment made. (String) |
| Amount in USD |
The amount of the investment in US Dollars. (Integer) |
| Remarks |
Any additional remarks related to the investment. (String) |
Acknowledgements
If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .