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    <title>topic Quantile statistics of z values in a shapefile in ArcGIS Spatial Analyst Questions</title>
    <link>https://community.esri.com/t5/arcgis-spatial-analyst-questions/quantile-statistics-of-z-values-in-a-shapefile/m-p/696008#M10130</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I have a raster dataset containing z values. Besides this i have a shapefile with +/- 50.000 records. Each record represents an area of 400m2. For each record i would like to get the maximum height within the record. Using zonal statistics&amp;nbsp; gives me the MAX z value of the raster within each record of the shapefile. To rule out outlyers in the rasterdataset instead of the maximum value of a cell within each record i would like the quantile 99% value. I reckon this should be possible&amp;nbsp;but I cant seem to figure out how. Im guessing pythons numpy.quantile&amp;nbsp;will be needed.&lt;/P&gt;&lt;P&gt;&lt;IMG class="image-1 jive-image" src="https://community.esri.com/legacyfs/online/450795_pastedImage_1.png" /&gt;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Wed, 19 Jun 2019 14:09:51 GMT</pubDate>
    <dc:creator>TimDubbeldam</dc:creator>
    <dc:date>2019-06-19T14:09:51Z</dc:date>
    <item>
      <title>Quantile statistics of z values in a shapefile</title>
      <link>https://community.esri.com/t5/arcgis-spatial-analyst-questions/quantile-statistics-of-z-values-in-a-shapefile/m-p/696008#M10130</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I have a raster dataset containing z values. Besides this i have a shapefile with +/- 50.000 records. Each record represents an area of 400m2. For each record i would like to get the maximum height within the record. Using zonal statistics&amp;nbsp; gives me the MAX z value of the raster within each record of the shapefile. To rule out outlyers in the rasterdataset instead of the maximum value of a cell within each record i would like the quantile 99% value. I reckon this should be possible&amp;nbsp;but I cant seem to figure out how. Im guessing pythons numpy.quantile&amp;nbsp;will be needed.&lt;/P&gt;&lt;P&gt;&lt;IMG class="image-1 jive-image" src="https://community.esri.com/legacyfs/online/450795_pastedImage_1.png" /&gt;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Wed, 19 Jun 2019 14:09:51 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-spatial-analyst-questions/quantile-statistics-of-z-values-in-a-shapefile/m-p/696008#M10130</guid>
      <dc:creator>TimDubbeldam</dc:creator>
      <dc:date>2019-06-19T14:09:51Z</dc:date>
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    <item>
      <title>Re: Quantile statistics of z values in a shapefile</title>
      <link>https://community.esri.com/t5/arcgis-spatial-analyst-questions/quantile-statistics-of-z-values-in-a-shapefile/m-p/696009#M10131</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;You have to convert the raster to a numpy array (arcpy.da.RasterToNumPyArray(….)&lt;/P&gt;&lt;P&gt;and if you have nodata values, then you should be using the 'nan' versions of either the percentile or quantile&lt;/P&gt;&lt;P&gt;&lt;A class="link-titled" href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.nanpercentile.html" title="https://docs.scipy.org/doc/numpy/reference/generated/numpy.nanpercentile.html"&gt;numpy.nanpercentile — NumPy v1.16 Manual&lt;/A&gt; &amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;A class="link-titled" href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.nanquantile.html" title="https://docs.scipy.org/doc/numpy/reference/generated/numpy.nanquantile.html"&gt;numpy.nanquantile — NumPy v1.16 Manual&lt;/A&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;otherwise, their non-nan versions are fine.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 25 Jun 2019 03:36:25 GMT</pubDate>
      <guid>https://community.esri.com/t5/arcgis-spatial-analyst-questions/quantile-statistics-of-z-values-in-a-shapefile/m-p/696009#M10131</guid>
      <dc:creator>DanPatterson_Retired</dc:creator>
      <dc:date>2019-06-25T03:36:25Z</dc:date>
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