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Historical evapotranspiration measurements from the CEAZA network

Centre for Advanced Studies in Arid Zones

datasetViewer.description

Evapotranspiration is defined as the loss of moisture from a surface by direct evaporation together with the loss of water by transpiration from vegetation. This is one of the variables recorded by the meteorological network of the Center for Advanced Studies in Arid Zones (CEAZA). This collection contains the information stored by 35 stations that have recorded, at some point, evapotranspiration since 2009, spaced on a daily basis. On each day, the minimum, maximum and average evapotranspiration is indicated. It is important to note that not all stations are currently operational. The data is updated monthly. For each sensor, the data series are available in *npz* format for Numpy and *mat* for Matlab, in addition to being able to be viewed in the Data Series viewer of the Itrend Data Platform. Last update: Thursday, August 11, 2022

datasetViewer.preview

datasetViewer.previewCollectionInfo

NombreCódigo sensorCanalesPrimer registroÚltimo registro
Andacollo [Collowara]ANDAset0min; prom; max2014-01-142022-01-16
CachiyuyoCACHset0min; prom; max2013-09-172022-01-18
CanelaCANset0min; prom; max2013-07-092022-01-18
Combarbalá [C.del Sur]COMBset0min; prom; max2013-10-172022-01-18
Coquimbo [El Panul]4set0min; prom; max2009-01-012019-05-20
···············
RivadaviaPYRVset0min; prom; max2010-09-232021-01-27
Salamanca [Chillepín]CHILLset0min; prom; max2013-07-10 00:00:002022-01-18
TascaderoTASCset0min; prom; max2020-11-052022-01-18
TilamaTILset0min; prom; max2013-07-252022-01-18
Vicuña6set0min; prom; max2009-04-152022-01-18

datasetViewer.download

datasetViewer.download1 datasetViewer.here. datasetViewer.download3

datasetViewer.programaticAccess

datasetViewer.programaticAccess1 itrend-ds:5c020e2c9e4e78cd

datasetViewer.programaticAccess2 Nombre

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:5c020e2c9e4e78cd' collection_id = 'Nombre' # Get available formats dataset_formats = session.get_dataset_formats(dataset_id) fmt = dataset_formats[0] # Choose your preferred format: dataset_formats = [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

datasetViewer.attributionMessage1

datasetViewer.attribution1 Centre for Advanced Studies in Arid Zones, «Historical evapotranspiration measurements from the CEAZA network». datasetViewer.attribution2

datasetViewer.attributionMessage2

datasetViewer.attribution3 Centre for Advanced Studies in Arid Zones («Historical evapotranspiration measurements from the CEAZA network»), datasetViewer.attribution4

datasetViewer.permanentLink

datasetViewer.permanentLinkDescription

https://www.plataformadedatos.cl/datasets/en/5c020e2c9e4e78cd

datasetViewer.metadata

datasetViewer.noMetadata