Latest Contributions by PaulMcCord1

Michael, Unfortunately I never found a better solution than switching to Pro. The script was developed for a suite of desktop-based geoprocessing tools for users interested in resource sustainability. The only "compromise" I came up with was articulating in the user guide for these geoprocessing tools that ArcGIS may need to be restarted after running the tool. Not an ideal solution at all, but it was all I could do. ... View more

Thanks Dan, I appreciate your suggestion. I do have import sys at the beginning of my script (sorry for not initially including my code). The script is fairly long, but I'm including the primary parts of it here: #Import modules import os import pandas as pd import numpy as np import pygal as pg import sys import arcpy arcpy.env.overwriteOutput = True arcpy.env.outputCoordinateSystem = arcpy.SpatialReference(3857) def plotFAO(df, iso_code, fao_indicator, itemCodeFS, countrySelection, outputLocation):      arcpy.AddMessage("IN FAO LOOP")      #Select the appropriate indicator      df_selected = df[df["Item Code"] == itemCodeFS]      #color code for plots      customColorStyle = pg.style.Style(colors = ['#D35400', '#979A9A', '#797D7F', '#5F6A6A', '#515A5A'], title_font_size = 18)      arcpy.AddMessage("added Style")      if itemCodeFS == 21010:           #Creat the line chart plot           line_chart = pg.Line(title = u"Average Dietary Energy Supply Adequacy - \n" + countrySelection, x_title = "End Year of '3-Year Average'", y_title = "% - 3-Year Average", style = customColorStyle, show_dots = False, stroke_style = {'width': 3}, show_minor_y_labels = True)           line_chart.x_labels = map(str, range(2001, 2018))           #Get just the Value column for the country of interest and the country groupings           country_series = df_selected.loc[df_selected["ISO_code"] == iso_code, "Value"]           low_income_series = df_selected.loc[df_selected["ISO_code"] == "lowestIncome", "Value"]           mid_lower_income_series = df_selected.loc[df_selected["ISO_code"] == "midLowerIncome", "Value"]           mid_upper_income_series = df_selected.loc[df_selected["ISO_code"] == "midUpperIncome", "Value"]           high_income_series = df_selected.loc[df_selected["ISO_code"] == "uppermostIncome", "Value"]           #Add Pd Series to the line chart           line_chart.add(countrySelection, country_series)           line_chart.add("Low-Income", low_income_series)           line_chart.add("Lower-Middle-Income", mid_lower_income_series)           line_chart.add("Upper-Middle-Income", mid_upper_income_series)           line_chart.add("High-Income", high_income_series)           #Output the plot           line_chart.render_to_file(os.path.join(outputLocation, 'test_pygal3.svg')) def foodSecurity_v1():      #FAO Data      fao_clean = "C:\\Users\\Paul McCord\\Google Drive\\Toolbox\\Tool_First\\FoodSecurity\\Content_Post052418\\Data_Tabular\\FAOSTAT\\fao_clean.csv"      #Country ISO codes      country_iso_csv = "C:\\Users\\Paul McCord\\Google Drive\\Toolbox\\Tool_First\\FoodSecurity\\Content_Post052418\\Data_Tabular\\country_codes\\FAO_Area_Export.csv"      #Set tool parameters      #Local variables      out_src_FeatureSet = r"in_memory\src_feature_set"      #User specified parameters      src_FeatureSet = arcpy.GetParameterAsText(0)      countrySelection = arcpy.GetParameterAsText(1)      fao_indicator = arcpy.GetParameterAsText(2)      outputLocation = arcpy.GetParameterAsText(3)      try:           #Save the Feature Set to Feature Layer           arcpy.MakeFeatureLayer_management(src_FeatureSet, out_src_FeatureSet)           aoi = arcpy.CopyFeatures_management(out_src_FeatureSet, os.path.join(arcpy.env.scratchFolder, "AOI_layer.shp"))                      #Obtain the country ISO code to avoid formatting problems with country name           df_iso = pd.read_csv(country_iso_csv)           countryDF = df_iso[df_iso["Area"] == countrySelection]           iso_code = countryDF["ISO_code"].iloc[0]           arcpy.AddMessage("country: " + countrySelection + ", code: " + iso_code)           arcpy.AddMessage(iso_code)                      #Obtain the Item Code and Item Description selected by the user           if fao_indicator == "Average dietary energy supply adequacy (%) (3-year average)":                itemCodeFS = 21010           if fao_indicator == "Average value of food production (constant I$ per person) (3-year average)":                itemCodeFS = 21011           if fao_indicator == "Share of dietary energy supply derived from cereals, roots and tubers (%) (3-year average)":                itemCodeFS = 21012           if fao_indicator == "Average protein supply (g/capita/day) (3-year average)":                itemCodeFS = 21013           if fao_indicator == "Average supply of protein of animal origin (g/capita/day) (3-year average)":                itemCodeFS = 21014           if fao_indicator == "Rail-lines density (per 100 square km of land area)":                itemCodeFS = 21016           if fao_indicator == "Gross domestic product per capita, PPP (constant 2011 international $)":                itemCodeFS = 22013           if fao_indicator == "Prevalence of undernourishment (%) (3-year average)":                itemCodeFS = 21004           if fao_indicator == "Depth of the food deficit (kcal/capita/day) (3-year average)":                itemCodeFS = 21023                      #Select FAO Food Security information of interest           df = pd.read_csv(fao_clean, dtype = {"Area": "S100", "Area Code": "f8", "Element": "S25", "Element Code": "f8", "Flag": "S25",                                                        "Flag Description": "S25", "ISO_code": "S25", "Item": "S150", "Item Code": "i4", "Unit": "S25",                                                        "Value": "f8", "Year": "S25", "Year Code": "f8", "YearEnd": "i4"})                      plotFAO(df, iso_code, fao_indicator, itemCodeFS, countrySelection, outputLocation)           #test output layer           arcpy.SetParameter(4, aoi)           #arcpy.SetParameter(4, fig)                      #except Exception:      #     e = sys.exc_info()[1]      #     arcpy.AddError('An error occurred: {}'.format(e.args[0]))                 except Exception:           if exc_info is not None and exec_info is not (None, None, None):                e = sys.exc_info()[1]                arcpy.AddError('An error occurred: {}'.format(e.args[0]))       if __name__ == '__main__':      foodSecurity_v1()‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍ There are actually nine food security indicators that I'm plotting, but I've only included the code for the first indicator in the 'plotFAO' function. The other plotting snippets look nearly identical, just with different food security indicators. I've tried a couple of options in the 'except' statement, but none have been successful. Thanks again for weighing in. ... View more

Thank you Dan, Unfortunately, I need to include this as a script tool belonging to a larger suite of script tools that are shipped in an Arc Toolbox, so the users won't have the option to run as a standalone script.  Since there seems to be this conflict between the applications, I might see if another library is able to plot my data without the conflict.  Thank you, Paul ... View more

Apologies, as you suggested, I've now run the Create Referenced Mosaic Dataset tool using the Kenya polygon to set the Extent from Dataset, and it works perfectly. Thanks for your help! Paul ... View more

Thanks Mody!  I think I'm now on the right track, but I'm getting a strange output when I edit the boundaries.  I took your advice and copy and pasted my mosaic data set to a new mosaic and then edited the boundary of the new mosaic by right clicking on the mosaic data set in the Catalog panel, then choosing Modify, then choosing Import Footprints or Boundary. I filled out the tool as shown below, making sure that the Target Feature Class was set to Boundary: However, my output was the following: It might be hard to see, but there's a Boundary around Kenya as I was hoping to get (in purple just right of center), but as you can see there's nothing to view now.  When I select the value of pixels both within and outside of the Boundary, I get a pixel value of -1.  I imagine there's a simple explanation or a simple step that I'm missing here. Thanks again, Paul ... View more