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Historical precipitation measurements every 24 hours from the DMC network

Meteorological Directorate of Chile

datasetViewer.description

In meteorology, precipitation is any form of hydrometeor that falls from the atmosphere and reaches the earth's surface. This phenomenon includes rain, drizzle, snow, sleet, hail, but not virga, mist or dew, which are forms of condensation and not precipitation. This is one of the variables recorded by the meteorological network of the Chilean Meteorological Directorate (DMC). This collection contains the information stored by 524 stations that have recorded, at some point, precipitation since 1922, spaced every 24 hours on those days that some data was recorded. In addition to precipitation, the trace is indicated, corresponding to a binary variable that indicates if there was any precipitation but that could not be recorded, either due to technical or other limitations. It is important to note that not all stations are currently operational. The data is updated directly from the DMC's web services and can be viewed in the Data Series viewer of the Itrend Data Platform. In addition, a historical database is provided in .npz* and .mat** format that is updated every 30 days for those stations that are still valid. *To load the data correctly in Python it is recommended to use the following code: ```python import numpy as np with np.load(filename, allow_pickle = True) as f: data = {} for key, value in f.items(): data[key] = value.item() ``` **Date data is in ```datenum``` format, and to load it correctly in ```datetime``` format, it is recommended to use the following command in MATLAB: ```python datetime(TS.x , 'ConvertFrom' , 'datenum') ```

datasetViewer.preview

datasetViewer.previewCollectionInfo

Código NacionalNombre EstaciónComunaRegiónLatitudLongitudOrganismoDatos DesdeDatos Hasta
170001Visviri TenenciaGeneral LagosArica y Parinacota-17.594999-69.477499Dirección Meteorológica de Chile19612012
170002Villa Industrial reténGeneral LagosArica y Parinacota-17.781388-69.708055Dirección Meteorológica de Chile19611980
170003Alcerreca reténGeneral LagosArica y Parinacota-17.992499-69.660555Dirección Meteorológica de Chile19612010
170004Tacora reténGeneral LagosArica y Parinacota-17.771943-69.724443Dirección Meteorológica de Chile19972012
180001Caquena reténPutreArica y Parinacota-18.054444-69.201388Dirección Meteorológica de Chile19622008
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950001C.M.A. Eduardo Frei Montalva, AntárticaAntárticaMagallanes y de la Antártica Chilena-62.191944-58.979721Dirección Meteorológica de Chile19702019
950002Arturo Prat, Base AntárticaAntárticaMagallanes y de la Antártica Chilena-62.47861-59.664166Armada de Chile19582019
950003Bernardo O`Higgins, Base AntárticaAntárticaMagallanes y de la Antártica Chilena-63.320832-57.899444Dirección Meteorológica de Chile19532019
950006Antártica, Bahía Fildes Gobernación MarítimaAntárticaMagallanes y de la Antártica Chilena-62.201388-58.963611Armada de Chile20172023
950901Antártica, Base Gabriel Gonzalez VidelaAntárticaMagallanes y de la Antártica Chilena-64.824166-62.858055Armada de Chile20172023

datasetViewer.download

datasetViewer.download1 datasetViewer.here. datasetViewer.download3

datasetViewer.programaticAccess

datasetViewer.programaticAccess1 itrend-ds:6d7ba7c949f9ea5d

datasetViewer.programaticAccess2 Código Nacional

datasetViewer.programaticAccess3 datasetViewer.programaticAccess4 datasetViewer.programaticAccess5 datasetViewer.here

```python import pytrend import pandas as pd session = pytrend.itrend_developer_tools() session.set_credentials( access_key_id = '', # Type your access_key_id secret_access_key = '' # Type your secret_access_key ) # Dataset dataset_id = 'itrend-ds:6d7ba7c949f9ea5d' collection_id = 'Código Nacional' # Get available formats dataset_formats = session.get_dataset_formats(dataset_id) fmt = dataset_formats[0] # Choose your preferred format: dataset_formats = [xlsx, csv] # Download file response = session.download_file(dataset_id, fmt) # Download an element filename = response.get('filename') delimiter = response.get('delimiter') df = pd.read_csv(filename, delimiter) element_formats = session.get_element_formats(dataset_id) efmt = element_formats[0] # Choose your preferred format: element_formats = [npz, mat] for r, row in df.iterrows(): element_id = row[collection_id] element_response = session.download_file(dataset_id, efmt, element_id) break ```

datasetViewer.attribution

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datasetViewer.attribution1 Meteorological Directorate of Chile, «Historical precipitation measurements every 24 hours from the DMC network». datasetViewer.attribution2

datasetViewer.attributionMessage2

datasetViewer.attribution3 Meteorological Directorate of Chile («Historical precipitation measurements every 24 hours from the DMC network»), datasetViewer.attribution4

datasetViewer.permanentLink

datasetViewer.permanentLinkDescription

https://www.plataformadedatos.cl/datasets/en/6d7ba7c949f9ea5d

datasetViewer.metadata

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