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AtmaManirohitgeo
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Guide 09 mapping (#67)
* Fix wrong location in comment * Merge dev branch into master for 0.2 Beta and Holistic Testing (#24) * Updated publishing samples to reflect changes made to source code * Updated Publihing SDs, shp, csv samples to reflect latest API changes * Publisher sample updates - added samples for web maps and web scene (#3) * Updated notebook title to match filename * Added a new sample to showcase publishing web maps and web scenes * Fixed credentials * Updated sample titled "Using and updating GIS content" (#4) * Updated notebook title to match filename * Added a new sample to showcase publishing web maps and web scenes * Fixed credentials * Updated the sample with additional examples * Fixed credentials * Added an example for line featuers. Added some text explaining what smart mapping is * Additional widgets to minimize scrolling. Fixed geocoder usage following API update * Updated geocoder usage to match API updates * Updated the sample to match gp service update. Added a bit more text explaining the usage of gp tools (#12) * Minor - updated sample to search for desired item to add instead of a fixed index (#13) * GIS analysts - sample illustrating spatial analysis using ArcGIS Python API (#14) * Initial commit * Furnished the sample with spatial analysis examples * Fixes for API changes. Added summary text and elaborated a few steps (#15) * new sample to showcase big data anlaysis using NYC taxi example (#16) * Updated hurricane tracks sample to match API changes (#17) * Updated hurricane tracks sample to match API changes and added descriptive text * updated credentials * Updated sample to match API changes, added explanatory text (#19) * clean up sample (#18) * clean up sample (#20) * Remove usage statistics notebook as the API isnt available This requires work on the portal backend as well as it does not yet support ASM. * bug fixes and added descriptive text (#22) * synced raster product sample in 05 Content Publishers folder to match that in 04 GIS Analysts and Data Scientists (#21) Thanks, @AtmaMani * Updated Overview page - updated sample TOC (#23) * doc updates * apidoc update for 0.2 beta release * updated install instructions * Updated samples download link to point to v0.2-beta release (#25) * fixed wrong import * fixed execution count * removed geometry and moved up mapping to 09 * guide - finished 09 mapping module
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guide/10 Mapping and visualization/Smart Mapping.ipynb renamed to guide/09 Mapping and visualization/Smart Mapping.ipynb

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{
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"<div class=\"alert alert-info\">\n",
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"\n",
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"**Note:** Refer here for instructions to <a href=\"https://developers.arcgis.com/python/sample-notebooks/#Download-and-run-the-sample-notebooks\">download and run this sample locally</a> on your computer\n",
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"## Visualizing line features\n",
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"The first sample shows some ideas to visualize linear features using streets data. When you add an item to your map, the map widget visualizes using the default symbology of the item. In this sample, you will see how you can use **smart mapping** to better visualize the same layer.\n",
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"The first example shows some ideas to visualize linear features using streets data. When you add an item to your map, the map widget visualizes using the default symbology of the item. In this sample, you will see how you can use **smart mapping** to better visualize the same layer.\n",
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"\n",
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"You can add the layer back to the map by passing the URL to the layer and specifying how you want the layer rendered. In this sample we will use **ClassSizeRenderer** to emphasize differences in value by varying the thickness of line features."
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"![line features](http://esri.github.io/arcgis-python-api/notebooks/nbimages/02_SmartMapping_01.PNG)"
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"[<Item title:\"USA Freeway System\" type:Feature Service owner:esri>]"
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"map2"
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"![area features](http://esri.github.io/arcgis-python-api/notebooks/nbimages/02_SmartMapping_02.PNG)"
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"## Visualizing location data\n",
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"Point features are the most common type of location data. Smart mapping provides a special visualization technique called **heatmap**. The heatmap renderer is useful when representing the spatial distribution or clustering of points as it represents the relative density of points on a map as smoothly varying sets of colors ranging from cool (low density) to hot (many points).\n",
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"Thus the sample below visualizes earthquake occurrences in Southern California, using the heatmap renderer"
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"Thus, the sample below visualizes earthquake occurrences in Southern California, using the heatmap renderer"
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"![location data](http://esri.github.io/arcgis-python-api/notebooks/nbimages/02_SmartMapping_03.PNG)"
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