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Datasets:
brandonhxrr
/
mexico_city_weather

Tasks:
Time Series Forecasting
Languages:
Spanish
Size:
1M<n<10M
Tags:
weather
climate
Mexico City
historical data
License:
Dataset card Files Community
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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ParserError
Message:      Error tokenizing data. C error: Expected 1 fields in line 8, saw 6

Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 322, in compute
                  compute_first_rows_from_parquet_response(
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response
                  rows_index = indexer.get_rows_index(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 640, in get_rows_index
                  return RowsIndex(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 521, in __init__
                  self.parquet_index = self._init_parquet_index(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 538, in _init_parquet_index
                  response = get_previous_step_or_raise(
                File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 567, in get_previous_step_or_raise
                  raise CachedArtifactError(
              libcommon.simple_cache.CachedArtifactError: The previous step failed.
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 240, 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 2216, 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 1239, 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 1389, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1044, in __iter__
                  yield from islice(self.ex_iterable, self.n)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__
                  for key, pa_table in self.generate_tables_fn(**self.kwargs):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/csv/csv.py", line 195, in _generate_tables
                  for batch_idx, df in enumerate(csv_file_reader):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
                  return self.get_chunk()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
                  return self.read(nrows=size)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1923, in read
                  ) = self._engine.read(  # type: ignore[attr-defined]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
                  chunks = self._reader.read_low_memory(nrows)
                File "parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
                File "parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
                File "parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
                File "parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
                File "parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
              pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 8, saw 6

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Weather Data for Mexico City by SIH CONAGUA

Overview

This dataset contains weather data for Mexico City collected by the Sistema de Información Hidrológica (SIH) of the Comisión Nacional del Agua (CONAGUA). The dataset includes historical weather records from multiple meteorological stations in Mexico City.

File Structure

  • weather_mexico_city_by_sih_conagua.csv: This file contains aggregated weather data for Mexico City.
  • raw_data: This folder includes individual CSV files with weather data from each meteorological station in Mexico City.

Data Description

  • Source: Comisión Nacional del Agua (CONAGUA), Sistema de Información Hidrológica (SIH)
  • Coverage: Mexico City, Mexico
  • Time Period: The dataset spans several years of historical weather data. Specific time frames can be found in the individual CSV files.
  • Variables: The dataset includes key weather variables such as maximum temperature, minimum temperatura and rainfall.

Dataset Usage

The dataset is valuable for researchers, data scientists, and developers interested in studying weather patterns, forecasting, and climate change analysis in urban areas. It can also be used for machine learning projects related to weather prediction and environmental studies.

Dataset Details

weather_mexico_city_by_sih_conagua.csv

  • Columns:
    • locality: Name of the locality where the data was recorded.
    • year: Year of the recorded data.
    • month: Month of the recorded data.
    • day: Day of the recorded data.
    • maxt: Maximum temperature recorded for the day.
    • mint: Minimum temperature recorded for the day.
    • rainfall: Total precipitation recorded for the day.

raw_data Folder

  • File Structure: Each file is named with the station code and contains weather data specific to that station.
  • File Format: CSV
  • Columns:
    • Similar to those in weather_mexico_city_by_sih_conagua.csv, with detailed data specific to each station.

Data Source and Licensing

  • Source: The data is obtained from the Sistema de Información Hidrológica (SIH) of the Comisión Nacional del Agua (CONAGUA).
  • Access Link: https://sih.conagua.gob.mx/basedatos/Climas/{station}.csv
  • License: This dataset is shared under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Users must provide proper attribution to CONAGUA and cannot use the data for commercial purposes. For more details, visit CONAGUA's data usage policies.

Dataset Curator

  • Name: Brandon Jesús Hernández Herrera
  • Affiliation: Escuela Superior de Cómputo (ESCOM), Instituto Politécnico Nacional (IPN)

Contributions and Acknowledgements

This dataset was made possible through the efforts of CONAGUA and the Sistema de Información Hidrológica.

license: cc-by-nc-4.0

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