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convert2geojson-0.0.2
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مشاهده بیشترتوضیحات
Tools for converting dataframes to GeoJSON format.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | convert2geojson-0.0.2 |
| نام | convert2geojson |
| نسخه کتابخانه | 0.0.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Malte Vogl |
| ایمیل نویسنده | mvogl@mpiwg-berlin.mpg.de |
| آدرس صفحه اصلی | https://github.com/computational-antiquity/convert2geojson/ |
| آدرس اینترنتی | https://pypi.org/project/convert2geojson/ |
| مجوز | GPLv3 |
convert2geojson
===============
Convert databases to geojson, useful for displaying datasets on maps.
A FeatureCollection is generated from those dataframe rows containing
values for latitude and longitude.
*Note:* To limit the size of the GeoJSON file, lookup tables are
generated automatically for fields with a limited number of values (<20)
and saved as a top-level 'properties' key in the JSON file. This is not
part of the GeoJSON standard and can lead to problems with linters, e.g.
`GeoJSONLint <http://geojsonlint.com/>`__.
Content
-------
1. `Installation <#installation>`__
2. `Basics <#basic-usage>`__
- `Loading data <#loading-data>`__
- `Generating geojson <#generating-geojson>`__
- `Plotting <#plotting>`__
3. `Examples <#examples>`__
Installation
------------
The package can be installed by
::
pip install convert2geojson
The latest development version of the package can be installed from
GitHub by running
::
pip install git+https://github.com/computational-antiquity/convert2geojson.git
This installs the most recent version of the master branch.
If the plotting on maps in JupyterLab is not yielding results, there
might be problems with your `ipyleaflet
installtion <https://github.com/jupyter-widgets/ipyleaflet#installation>`__
or `ipywidgets
installtion <https://ipywidgets.readthedocs.io/en/stable/user_install.html#installing-the-jupyterlab-extension>`__.
Basic usage
-----------
Import the package with
.. code:: python
from convert2geojson import Convert2GeoJson
Loading data
~~~~~~~~~~~~
The package is instantiated by providing a dataframe containing the
geodata ,e.g. ``dataframe=df``, a list of columns of the dataframe,
which should be shown as information for every geo feature, e.g.
``properties=df.columns`` to show everything, and the column titles for
longitudal and latitudal data (standard parameter names are
``lat='latitude'`` and ``lon='longitude'``).
.. code:: python
data = Convert2GeoJson(
df,
df.columns,
lat='latitude',
lon='longitude'
)
The geo data is expected to be gievn as float numbers. Rows with empty
longitudal or latitudel data, or marked as ``NaN`` are droped from the
supplied dataframe.
The original dataframe can however still be accessed as ``data.rawDF``.
Generate geoJson
~~~~~~~~~~~~~~~~
To generate the geoJSON simple run
.. code:: python
data.convert()
This generates a geoJSON formated dictionary which is available at
.. code:: python
data.geojson()
To save the geoJSON to a file, run
.. code:: python
data.save()
You can provide parameters for the name and path, standards are
``name='data.geojson'`` and ``path='.'``.
Plotting
~~~~~~~~
For plotting the package is leveraging the `ipyleaflet
package <https://github.com/jupyter-widgets/ipyleaflet>`__ which is also
available as a JupyterLab extension.
For a first overview use
.. code:: python
data.display()
This plots the geoJSON features as a layer on a basemap.
The basic plotting can be changed by parameters for the map layout
(``mapLayout=dict()``), and the basemap data (``basemap=dict()``).
To use a custom basemap, you can provide a dictionary of the format
.. code:: python
customBasemap = {
'url': 'https://{s}.URL_to_mapdata/{z}/{x}/{y}.png',
'max_zoom': 'max available zoom level',
'attribution': 'Attribution',
'name': 'Name for layer control'
}
Screenshot
''''''''''
.. figure:: example/mapExample.png
:alt: Screenshot of generated map
Screenshot of generated map
Grouped Plotting
^^^^^^^^^^^^^^^^
For densely distributed geographical data, to styling options are
available.
By choosing ``style='grouped'`` ipyleaflets MarkerCluster is used to
show groups of markers depending on the zoom level. By clicking on a
cluster, the map zooms to the level, which contains the selected markers
in the cluster .
Additionally, since markers are now single entities, by clicking on any
marker a popup shows the information of the dataframe belonging to the
geographical point.
Screenshot
''''''''''
.. figure:: example/clusterMap.png
:alt: Screenshot of generated cluster map
Screenshot of generated cluster map
Categorical plotting as pie chart distribution
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
By choosing ``style='pie'`` and providing a category found in the
dataframe columns, by setting ``groupBy='Category'``, the package
generates a standalone map showing the clustered markers as pie charts
separated into sub-groups by the chosen category.
Screenshot
''''''''''
.. figure:: example/pieChartMap.png
:alt: Screenshot of generated pie chart map
Screenshot of generated pie charts map
Examples
--------
Have a look at the `Loading datasets </example/Loading_dataset.ipynb>`__
or the `Advanced Plotting </example/Advanced_plotting.ipynb>`__
notebooks in the ``/example`` folder
نیازمندی
| مقدار | نام |
|---|---|
| - | pandas |
| - | xlrd |
| - | citableclass |
| - | ipyleaflet |
| - | ipywidgets |
| - | jinja2 |
| - | ipython |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3 | Python |
نحوه نصب
نصب پکیج whl convert2geojson-0.0.2:
pip install convert2geojson-0.0.2.whl
نصب پکیج tar.gz convert2geojson-0.0.2:
pip install convert2geojson-0.0.2.tar.gz