The objective of this project is to embark on a journey through the Indian startup environment. Our mission? To recommend the optimal course of action for venturing into this dynamic space. 🌟
Below is a preview showcasing the app's appearance.
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The project spans the years 2018 to 2021, and it's designed to accomplish two main objectives: data handling and in-depth analysis. Our journey unfolds as a thrilling expedition through these milestones:
🧐 Questions:
- Do companies in specific sectors receive more funding than others?
- Is there a correlation between a company's development stage and the funding it receives?
- Does the number of founders impact funding?
- What's the connection between a company's location and its funding?
- Does the number of investors influence funding?
🧪 Hypotheses:
- E-commerce and fintech startups receive more funding than the technology sector.
- A positive correlation exists between the development stage and funding.
- Companies with more founders receive higher funding.
- Major metropolitan areas attract more significant funding.
- The number of investors correlates with funding.
Our toolkit includes powerful Python libraries:
- Pandas 🐼
- Scipy 📈
- Seaborn 📊
- Matplotlib 📉
- Scikit-learn 🧠
We kick things off by giving our data a good scrub:
- Replacing missing values
- Dropping duplicates
- Restructuring columns
Our journey continues with deep dives into the data:
- Univariate Analysis
- Bivariate Analysis
- Multivariate Analysis
We employ various statistical tests such as T-tests and Pearson correlation to validate our hypotheses.
Our insights come to life through captivating visuals:
- Violin plots 🎻
- Box plots 📦
- Bar charts 📊
- Scatter plots 🌐
We take our analysis to the next level with Power BI's Python scripting tool:
For a deeper dive into our findings, check out my article covering the topic Unveiling the Indian Startup Ecosystem: A Deep Dive into Funding Trends, A Data Analyst Perspective.
To get started with this project, follow these simple steps:
1. **Python Installation**: Ensure you have Python 3.8 or higher installed on your system. You can download Python from the official website [here](https://www.python.org/downloads/).
2. **Install Dependencies**: You'll need to install the required Python libraries for this project. Open your command line or terminal and run the following command within the project directory:
```bash
pip install -r requirements.txtThis will install all the necessary libraries and packages.
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Run in Jupyter Notebook: To explore the project interactively, start Jupyter Notebook. Run the following command:
jupyter notebook
It will open Jupyter Notebook in your web browser. Navigate to the project directory, and you'll find Jupyter notebooks to run and explore.
That's it! You're all set to dive into the project and start your data science journey. 🌐💼📈