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    <title>topic Re: problem of using arcpy.polyline creat line in Python Questions</title>
    <link>https://community.esri.com/t5/python-questions/problem-of-using-arcpy-polyline-creat-line/m-p/151900#M11731</link>
    <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;You appear to be using the original ArcPy cursors, as opposed to the ArcPy Data Access cursors that were introduced in 10.1.&amp;nbsp; I recommend switching to the DA cursors and then re-post your question if you are still having issues:&amp;nbsp; &lt;A class="link-titled" href="http://desktop.arcgis.com/en/arcmap/latest/analyze/python/data-access-using-cursors.htm" title="http://desktop.arcgis.com/en/arcmap/latest/analyze/python/data-access-using-cursors.htm"&gt;Accessing data using cursors—Help | ArcGIS Desktop&lt;/A&gt;&amp;nbsp;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
    <pubDate>Sat, 29 Jun 2019 14:23:17 GMT</pubDate>
    <dc:creator>JoshuaBixby</dc:creator>
    <dc:date>2019-06-29T14:23:17Z</dc:date>
    <item>
      <title>problem of using arcpy.polyline creat line</title>
      <link>https://community.esri.com/t5/python-questions/problem-of-using-arcpy-polyline-creat-line/m-p/151899#M11730</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;PRE&gt;&lt;SPAN style="display: inline !important; float: none; background-color: #ffffff; color: #3d3d3d; font-family: inherit; font-size: 100%; font-style: inherit; font-variant: normal; font-weight: inherit; letter-spacing: normal; orphans: 2; overflow-wrap: break-word; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px;"&gt;I&amp;nbsp; have a python script that was get coordinate points (&lt;SPAN style="display: inline !important; float: none; background-color: #ffffff; color: #333333; font-family: arial; font-size: 18px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; line-height: 24px; list-style-image: none; list-style-position: outside; list-style-type: none; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px;"&gt;Longitudinal and latitudinal coordinat&lt;/SPAN&gt;e ) from excel and writing them to an arcpy.Array and then writing the array to an already existing feature class as a polyline.&amp;nbsp; but line created&amp;nbsp; finished offset the point ,and vertices of&amp;nbsp; creating line&amp;nbsp; less than numbers of points.&amp;nbsp;&lt;/SPAN&gt;&lt;/PRE&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;IMG class="j-img-centered" 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" style="margin-right: auto; margin-left: auto; display: block;" /&gt;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Sat, 29 Jun 2019 03:21:00 GMT</pubDate>
      <guid>https://community.esri.com/t5/python-questions/problem-of-using-arcpy-polyline-creat-line/m-p/151899#M11730</guid>
      <dc:creator>lmzh</dc:creator>
      <dc:date>2019-06-29T03:21:00Z</dc:date>
    </item>
    <item>
      <title>Re: problem of using arcpy.polyline creat line</title>
      <link>https://community.esri.com/t5/python-questions/problem-of-using-arcpy-polyline-creat-line/m-p/151900#M11731</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;You appear to be using the original ArcPy cursors, as opposed to the ArcPy Data Access cursors that were introduced in 10.1.&amp;nbsp; I recommend switching to the DA cursors and then re-post your question if you are still having issues:&amp;nbsp; &lt;A class="link-titled" href="http://desktop.arcgis.com/en/arcmap/latest/analyze/python/data-access-using-cursors.htm" title="http://desktop.arcgis.com/en/arcmap/latest/analyze/python/data-access-using-cursors.htm"&gt;Accessing data using cursors—Help | ArcGIS Desktop&lt;/A&gt;&amp;nbsp;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Sat, 29 Jun 2019 14:23:17 GMT</pubDate>
      <guid>https://community.esri.com/t5/python-questions/problem-of-using-arcpy-polyline-creat-line/m-p/151900#M11731</guid>
      <dc:creator>JoshuaBixby</dc:creator>
      <dc:date>2019-06-29T14:23:17Z</dc:date>
    </item>
    <item>
      <title>Re: problem of using arcpy.polyline creat line</title>
      <link>https://community.esri.com/t5/python-questions/problem-of-using-arcpy-polyline-creat-line/m-p/151901#M11732</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;I always make my polylines like this, so no idea if this will help:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;CODE style="background-color: #eff0f1; border: 0px; font-weight: inherit;"&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;polyline&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;=&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;arcpy&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;.&lt;/SPAN&gt;&lt;SPAN class="" style="color: #2b91af; border: 0px; font-weight: inherit; font-size: 13px;"&gt;Polyline&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;(array&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;)&lt;/SPAN&gt;&lt;/CODE&gt;&lt;/P&gt;&lt;P&gt;&lt;CODE style="background-color: #eff0f1; border: 0px; font-weight: inherit;"&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;row.setValue(shapename, polyline)&lt;/SPAN&gt;&lt;/CODE&gt;&lt;/P&gt;&lt;P&gt;&lt;CODE style="background-color: #eff0f1; border: 0px; font-weight: inherit;"&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;&lt;/SPAN&gt;&lt;/CODE&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN style="color: #3d3d3d;"&gt;For the offset, you probably need to include a spatial reference:&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN style="background-color: #eff0f1; color: #303336; font-size: 13px; "&gt;spatref_epsg =&amp;nbsp;&lt;/SPAN&gt;4326&amp;nbsp; &amp;nbsp;#&lt;A href="https://spatialreference.org/ref/epsg/wgs-84/"&gt;https://spatialreference.org/ref/epsg/wgs-84/&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;CODE style="background-color: #eff0f1; border: 0px; font-weight: inherit;"&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;arcpy&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;.&lt;/SPAN&gt;&lt;SPAN class="" style="color: #2b91af; border: 0px; font-weight: inherit; font-size: 13px;"&gt;CreateFeatureclass_management&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;(&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;out_path&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;=&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;folder&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;,&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt; out_name&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;=&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;shapename&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;,&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;geometry_type&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;=&lt;/SPAN&gt;&lt;SPAN class="" style="color: #7d2727; border: 0px; font-weight: inherit; font-size: 13px;"&gt;'POLYLINE'&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;,&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt; spatial_reference&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;=&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;arcpy&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;.&lt;/SPAN&gt;&lt;SPAN class="" style="color: #2b91af; border: 0px; font-weight: inherit; font-size: 13px;"&gt;SpatialReference&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;(&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;spatref_epsg&lt;/SPAN&gt;&lt;SPAN class="" style="color: #303336; border: 0px; font-weight: inherit; font-size: 13px;"&gt;))&lt;/SPAN&gt;&lt;/CODE&gt;&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Mon, 01 Jul 2019 09:14:20 GMT</pubDate>
      <guid>https://community.esri.com/t5/python-questions/problem-of-using-arcpy-polyline-creat-line/m-p/151901#M11732</guid>
      <dc:creator>LukeWebb</dc:creator>
      <dc:date>2019-07-01T09:14:20Z</dc:date>
    </item>
    <item>
      <title>Re: problem of using arcpy.polyline creat line</title>
      <link>https://community.esri.com/t5/python-questions/problem-of-using-arcpy-polyline-creat-line/m-p/151902#M11733</link>
      <description>&lt;HTML&gt;&lt;HEAD&gt;&lt;/HEAD&gt;&lt;BODY&gt;&lt;P&gt;thanks, offset reason is lack of spatial reference indeed.&lt;/P&gt;&lt;/BODY&gt;&lt;/HTML&gt;</description>
      <pubDate>Tue, 02 Jul 2019 09:06:23 GMT</pubDate>
      <guid>https://community.esri.com/t5/python-questions/problem-of-using-arcpy-polyline-creat-line/m-p/151902#M11733</guid>
      <dc:creator>lmzh</dc:creator>
      <dc:date>2019-07-02T09:06:23Z</dc:date>
    </item>
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