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Error code: FeaturesError Exception: ValueError Message: Failed to convert pandas DataFrame to Arrow Table from file zip://mainboard_needed_jsons/0_RHP.json::hf://datasets/sohomghosh/indian_ipo_rating_prediction@77176f72055305d84fdea0aee1f4f404e75cc927/mainboard_needed_jsons.zip. Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 231, in compute_first_rows_from_streaming_response iterable_dataset = iterable_dataset._resolve_features() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2998, in _resolve_features features = _infer_features_from_batch(self.with_format(None)._head()) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1918, in _head return _examples_to_batch(list(self.take(n))) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__ for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__ for key, pa_table in self.generate_tables_fn(**gen_kwags): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 172, in _generate_tables raise ValueError( ValueError: Failed to convert pandas DataFrame to Arrow Table from file zip://mainboard_needed_jsons/0_RHP.json::hf://datasets/sohomghosh/indian_ipo_rating_prediction@77176f72055305d84fdea0aee1f4f404e75cc927/mainboard_needed_jsons.zip.
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The copyright for this content belongs to its respective owners, and we do not claim any copyright rights over this data. This dataset has been released under the CC-BY-NC-SA-4.0 licence for non-commercial research purposes only. We are not liable for any monetary loss that may arise from the use of these datasets and model artefacts.
Files:
mb_ipo-reviews-final_data.xlsx : This is the main file for Mainboard
sme_ipo-reviews-final_data.xlsx : This is the main file for SME
In some cases, while creating json files, '&' in pdf file names has been replaced by ' '
sme_needed_jsons.zip : JSON files for SME IPOs
mainboard_needed_jsons.zip : JSON files for Main board IPOs
Code: ipo-review-longformerroberta-classify-summarised.ipynb
Column Name | Description |
---|---|
key | Unique identifier of each row |
year | Year of the IPO review |
Review Title | Title of the review |
review_text | Text content of the review |
review_link | Link to the review |
Author | Author of the review |
ipo_link | Link to the IPO information |
most_relevant_link | Link to access the (D)RHP report |
Text_extracted_JSON | name of JSON file with texts extracted from the (D)RHP report |
answer_of_question_0 | Answer of Question 0 |
answer_of_question_1 | Answer of Question 1 |
answer_of_question_2 | Answer of Question 2 |
answer_of_question_3 | Answer of Question 3 |
answer_of_question_4 | Answer of Question 4 |
answer_of_question_5 | Answer of Question 5 |
answer_of_question_6 | Answer of Question 6 |
answer_of_question_7 | Answer of Question 7 |
answer_of_question_8 | Answer of Question 8 |
answer_of_question_9 | Answer of Question 9 |
answer_of_question_10 | Answer of Question 10 |
answer_of_question_11 | Answer of Question 11 |
answer_of_question_12 | Answer of Question 12 |
answer_of_question_13 | Answer of Question 13 |
answer_of_question_14 | Answer of Question 14 |
answer_of_question_15 | Answer of Question 15 |
summary_of_all_answers | Summary of all answers 0 to 15 |
Recommendation | Apply, Neutral, May apply, or Avoid (Target Variable) |
split | train / test split |
List of questions
Question Number | Question |
---|---|
0 | What is the price band and issue price of the IPO? |
1 | What is the issue size and how many shares are being issued as part of the IPO? |
2 | What is the implied market capitalization of the company after the IPO? |
3 | How will the company utilize the funds raised through the IPO, and what is the purpose of the IPO? |
4 | What is the company's revenue growth rate over recent financial years, and how has its financial performance been historically (including revenue, EBITDA, and net profit trends)? |
5 | What are the key financial ratios, such as net profit margin, return on equity (RoE), return on capital employed (RoCE), and total debt? |
6 | What is the shareholding pattern before and after the IPO, and who are the promoters? |
7 | Are there any regulatory issues or conflicts of interest affecting the company? |
8 | What are the company's plans for expansion and future growth, and how does it position itself in terms of competition within its industry? |
9 | Who are the company's major customers, what is the revenue breakdown by sector, and is there a dependency on large institutional customers? |
10 | What are the potential risks associated with increasing raw material costs, and what other risks does the company face? |
11 | How does the company's valuation compare to its peers, and is the issue priced aggressively compared to industry standards? |
12 | What is the competitive landscape of the industry in which the company operates? |
13 | Has the company declared any dividends in the past, and what is its dividend policy? |
14 | Who are the lead managers and registrar for the IPO, and what is their track record in terms of past IPO listings? |
15 | Are there any concerns regarding transparency or missing details in the offer document? |
@misc{ghosh2024indianiporating,
title={Predicting Ratings of Indian IPOs from Red Herring Prospectus},
author={Sohom Ghosh and Sudip Kumar Naskar},
year={2025},
url={https://easychair.org/publications/preprint/G1P2/open},
}
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