The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: UnicodeDecodeError
Message: 'utf-8' codec can't decode byte 0xa3 in position 805: invalid start byte
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 249, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 196, in _generate_tables
csv_file_reader = pd.read_csv(file, iterator=True, dtype=dtype, **self.config.pd_read_csv_kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/streaming.py", line 73, in wrapper
return function(*args, download_config=download_config, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1279, in xpandas_read_csv
return pd.read_csv(xopen(filepath_or_buffer, "rb", download_config=download_config), **kwargs)
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1026, in read_csv
return _read(filepath_or_buffer, kwds)
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 620, in _read
parser = TextFileReader(filepath_or_buffer, **kwds)
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1620, in __init__
self._engine = self._make_engine(f, self.engine)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1898, in _make_engine
return mapping[engine](f, **self.options)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 93, in __init__
self._reader = parsers.TextReader(src, **kwds)
~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "pandas/_libs/parsers.pyx", line 574, in pandas._libs.parsers.TextReader.__cinit__
File "pandas/_libs/parsers.pyx", line 663, in pandas._libs.parsers.TextReader._get_header
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2053, in pandas._libs.parsers.raise_parser_error
File "<frozen codecs>", line 325, in decode
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xa3 in position 805: invalid start byteNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Techsalerator's Business Funding Data
Techsalerator's Business Funding Data provides a comprehensive and insightful collection of information crucial for businesses, investors, and financial analysts. This dataset offers an in-depth look into the funding activities of companies across various sectors, capturing and categorizing data related to their funding rounds, investment sources, and financial milestones. Coverage is available by country or region on request.
Top 5 Most Utilized Data Fields Company Name: Lists the name of the company receiving funding. Knowing which companies are securing investments helps investors identify potential opportunities and allows analysts to track funding trends within specific industries. Funding Amount: Details the amount of funding received by the company. Understanding the funding amounts provides insights into the financial health and growth potential of businesses, as well as the scale of investment activity. Funding Round: Indicates the stage of funding, such as seed, series A, series B, or later stages. Identifying the funding round helps investors gauge the maturity of the business and its growth trajectory. Investor Name: Provides information on the investors or investment firms involved in the funding round. Knowing the investors helps in understanding the credibility of the funding source and assessing the strategic interests of the investors. Investment Date: Records the date when the funding was officially completed. The timing of investments can indicate market trends, investor confidence, and potential impacts on the company's future development. Accessing Techsalerator's Business Funding Data
If you're interested in obtaining Techsalerator's Business Funding Data, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide a customized quote based on the number of data fields and records you need, and coverage can be scoped to a specific country, industry, or region. Datasets are typically available for delivery within 24 hours, with ongoing access options available on request.
Included Data Fields Company Name Funding Amount Funding Round Investor Name Investment Date Funding Type (Equity, Debt, Grants, etc.) Sector Focus Deal Structure Investment Stage Contact Information
For detailed insights into funding activities and financial trends, Techsalerator's dataset is an invaluable resource for investors, business analysts, and financial professionals aiming to stay informed and make strategic decisions.
FAQ
Q: How much does the Business Funding Data Dataset cost? Cost can vary depending on factors such as the number of data fields, the frequency of updates, and the total number of records required. For precise pricing, consult directly with a Techsalerator data specialist, who can provide a customized quote based on your specific needs.
Q: How complete is the coverage of the Business Funding Data? Techsalerator's Business Funding Data offers extensive coverage of funding activities across entities in the covered market that have raised capital. The dataset aggregates information from a variety of sources, including investment reports, company press releases, funding announcements, and venture capital activities, providing a comprehensive overview of the funding landscape.
Q: How does Techsalerator collect this data? Techsalerator collects Business Funding Data from a diverse array of reliable sources, such as investment reports, company press releases, funding announcements, and venture capital activities. The data is curated to ensure accuracy and comprehensiveness, offering valuable insights into companies' funding activities and capital raised.
Q: Can I select specific industries or focus on particular regions with Techsalerator's Business Funding Data? Yes. Techsalerator offers the flexibility to filter funding data based on specific industries or geographic regions. While the primary dataset provides broad coverage, customization options are available to focus on particular sectors or regions of interest. Discuss your specific requirements with a Techsalerator representative to tailor the dataset to your needs.
Q: How do I pay for this dataset? Techsalerator accepts various payment methods, including credit cards, direct transfers, ACH (Automated Clearing House), and wire transfers. You can choose the payment method that best suits your preferences.
Q: How do I receive the data? Techsalerator provides the Business Funding Data through multiple delivery methods, including FTP, SFTP, S3 bucket, or email. The dataset can be delivered in formats such as JSON, CSV, TXT, or XLS, allowing you to choose the format that best fits your data processing and integration requirements.
Pricing available upon request — Get Custom Quote
Contact: info@techsalerator.com · Contact Provider
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