#exploratorydataanalysis

🧠 QUIZ TIME 

 What is a main goal of EDA ?

A. Model Training B. Data Encryption C. Deployment D. Data Visualization

EDA helps us understand the structure of data, identify patterns, and make informed decisions before model building.

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Exploratory data analysis uses various data visualization techniques, such as Matplotlib, Seaborn, Pandas, etc., to compare multiple sets and highlight their key aspects.

In the previous months, Shark Tank India has captured all of our interests. While my LinkedIn feed was loaded with influencers debating which shark is the greatest, I was busy studying the season. Kaggle Dataset is what was used.

Problem Statements

If you enjoy Shark Tank India, you may be interested in

Maximum number of sharks in a deal

Startups that declined sharks' offer

Total amount borrowed or invested by all sharks

Collections of various sharks

Businesses that received the same valuation as was sought

Which businesses (as of pitching day) have no revenue or pre-revenue?

The project's step-by-step outline is shown below:

Putting in the Required Libraries and Importing.

Data set being downloaded.

Getting Understanding from a Dataset.

Visualization of data.

Setting Up the Necessary Libraries

Installing necessary libraries like Pandas, NumPy, Matplotlib, and Seaborn comes first.

We have completed this stage after importing the necessary library, and are now prepared to continue on to the following section of downloading the dataset. Save the data set. The next step is to get the Kaggle dataset.

Searching for Insights Regarding the Data

Season 1- Shark Tank India

The same technology is utilized and the same kind of visualization has been developed to determine the industry-wise allocation for various shark species.

Galaxies

Universe

Star Clusters

If these words make your eyes twinkle & if you want to dig more about the universe integrate #AI to your research.