[FEATURE] Add dataset information retrieval functions in Stock_prediction_Data_Analysis.ipynb

[Maryam0330]

Is this a unique feature?

• [X] I have checked "open" AND "closed" issues and this is not a duplicate

Is your feature request related to a problem/unavailable functionality? Please describe.

The current Stock_prediction_Data_Analysis.ipynb file does not provide detailed insight into the dataset's structure. There are no existing functions that allow users to view metadata such as the columns, data types, size of the DataFrame, or the numeric columns, which are essential for exploratory data analysis.

Proposed Solution

Add a section at the beginning of the notebook that uses Pandas functions like tail(), columns, dtypes, size, and dtypes to retrieve important information about the dataset. This would help users better understand the dataset before performing further analysis.

Screenshots

No response

Do you want to work on this issue?

Yes

If "yes" to above, please explain how you would technically implement this (issue will not be assigned if this is skipped)

To technically implement this, I would first ensure the dataset is loaded into a Pandas DataFrame. Then, I would add a section in the notebook dedicated to retrieving basic information about the dataset. Using Pandas functions, I would include methods to display the last few rows of the DataFrame, the column names, data types of each column, and the total number of elements in the DataFrame. Additionally, I would use a function to specifically extract and display the numeric columns to help with further analysis, ensuring all data types are well understood for future steps. These insights will be printed in a clear format for the user.

[github-actions[bot]]

Ensure the issue is not similar or previously being worked on.Thanks for your time

[Maryam0330]

@rohitinu6 Please assign me this task under the gssoc-ext and level3 labels.