play_arrowdatasetViewer.description
A hazard or threat map identifies areas exposed to the direct and indirect effect of possible volcanic eruptions, through different forms and scales of representation, which distinguishes each of the possible processes during an eruption, and proposes a simpler and more integrated zoning. A map is a contribution to the management of eventual 'crises'. That is, events where there is high uncertainty about the eruptive scenarios and their impacts; and high pressure on the authorities in charge of making decisions.
play_arrowdatasetViewer.preview
datasetViewer.previewCollectionInfo
| Nombre | Territorio | Peligrosidad |
|---|
| Taapaca | Arica y Parinacota | Alta |
| Parinacota | Arica y Parinacota | Alta |
| Güallatiri | Arica y Parinacota | Alta |
| Isluga | Tarapacá | Baja |
| Irruputuncu | Tarapacá | Moderada |
| ··· | ··· | ··· |
| Corcovado | Los Lagos | Alta |
| Melimoyu | Aysén | Moderada |
| Mentolat | Aysén | Baja |
| Macá | Aysén | Alta |
| Hudson | Aysén | Alta |
play_arrowdatasetViewer.download
datasetViewer.download1 datasetViewer.here. datasetViewer.download3
play_arrowdatasetViewer.programaticAccess
datasetViewer.programaticAccess1 itrend-ds:TBRT56GD2I9BW7CP
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:TBRT56GD2I9BW7CP'
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, xlsx]
# 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 = [pdf, geojson, shp]
for r, row in df.iterrows():
element_id = row[collection_id]
element_response = session.download_file(dataset_id, efmt, element_id)
break
```
play_arrowdatasetViewer.attribution
datasetViewer.attributionMessage1
datasetViewer.attribution1 National Geology and Mining Service, «Volcanic hazard maps». datasetViewer.attribution2
file_copy
datasetViewer.attributionMessage2
datasetViewer.attribution3 National Geology and Mining Service («Volcanic hazard maps»), datasetViewer.attribution4
file_copy
play_arrowdatasetViewer.permanentLink
datasetViewer.permanentLinkDescription
https://www.plataformadedatos.cl/datasets/en/TBRT56GD2I9BW7CP
file_copy
play_arrowdatasetViewer.metadata
datasetViewer.noMetadata
