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Copy file name to clipboardExpand all lines: guide/01-getting-started/system-requirements.ipynb
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"metadata": {},
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"source": [
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"## Operating System \n",
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"The ArcGIS API for Python 2.2.0 is compatible with 64-bit versions of Windows, macOS, and Linux. Note that, 32-bit versions of Windows and Linux are no longer supported for API versions later than 1.7.1.\n",
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"The ArcGIS API for Python 2.3.0 is compatible with 64-bit versions of Windows, macOS, and Linux. Note that, 32-bit versions of Windows and Linux are no longer supported for API versions later than 1.7.1.\n",
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"\n",
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"## Python Version\n",
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"Python 3.9.x to 3.11.x is required to use the ArcGIS API for Python 2.2.0.\n",
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"\n",
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"> **Note:** The `arcgis.learn` module is **only** supported with Python 3.9.x.\n",
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"Python 3.9.x to 3.11.x is required to use the ArcGIS API for Python 2.3.0.\n",
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"## Dependencies\n",
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"The full power of the ArcGIS API for Python is best experienced when all its dependencies are installed. However, specific tasks such as GIS administration and content management can be accomplished with a subset of dependencies installed. See [Install with minimum Dependencies](../install-and-set-up#install-with-minimum-dependencies) to install the `arcgis` package in this manner.\n",
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"It is recommended to install the `arcgis` package the default way of either `conda install -c esri arcgis` or `pipenv install arcgis`. When version 2.2.0 is installed in this manner, all the below dependencies are automatically installed. \n",
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"It is recommended to install the `arcgis` package the default way of either `conda install -c esri arcgis` or `pipenv install arcgis`. When version 2.3.0 is installed in this manner, all the below dependencies are automatically installed. \n",
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"> __Note__ Most of these packages have dependencies of their own. For a full list of packages installed:\n",
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" > * conda environment, type `conda list -n <environment_name>`. \n",
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" > * pipenv virtual environment: See [`Pipfile` and `Pipfile.lock`](https://pipenv.pypa.io/en/latest/pipfile/) for details. \n",
"> Note: if `arcpy` is found in the current python environment, it may be used in various locations. Otherwise, `pyshp` will be used. See [Spatially Enabled DataFrame](https://developers.arcgis.com/python/api-reference/arcgis.features.toc.html?highlight=geoaccessor#arcgis.features.GeoAccessor) for more information.\n",
snippet: Use big data tools to analye NYC taxi data
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snippet: Use big data tools to analyze NYC taxi data
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description: This sample demonstrates the steps involved in performing an aggregation analysis on New York city taxi point data using ArcGIS API for Python.
snippet: Analyze growth factors of Arbnb properties in New York
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snippet: Analyze growth factors of Airbnb properties in New York
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description: A study is carried out in this sample notebook to understand the factors that are fuelling widespread growth in the number of Airbnb listings
description: This sample showcases not just the analysis and visualization capabilities of your GIS, but also the ability to store illustrative text, graphics and live code in a Jupyter notebook.
# snippet: Determine the occurance of super blooms in the study area for a given year
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# snippet: Determine the occurrence of super blooms in the study area for a given year
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# description: This sample is to study three poppy fields where people often go for watching super blooms, compare the sites with historic scenes, capture the differences in vegetation conditions, and calculate the vegetation density of blooms.
snippet: Use Landsat 8 imagery to detect green cover of New Delhi, India
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description: This sample shows the capabilities of spectral indices such as Normalized Difference Vegetation index (NDVI) for the calculation of green cover in Delhi, India on 15 October 2017 using Landsat 8 imagery.
description: This sample demonstrates the utility of ArcGIS API for Python to identify some great locations for a new retirement community, which will satisfy these needs of senior citizens.
# description: In this notebook you will analyze the aggregated tracks to investigate the communities that are most affected by hurricanes, as well as as answer important questions about the prevalance of hurricanes, their seasonality, their density, and places where they make landfall.
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# description: In this notebook you will analyze the aggregated tracks to investigate the communities that are most affected by hurricanes, as well as as answer important questions about the prevalence of hurricanes, their seasonality, their density, and places where they make landfall.
description: The analysis below uses a geoprocessing tool to deduce the path that the debris of a crashed airplane would take if it went down at different places in the ocean.
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