def testchart(self):
obs = r'c:\temp\chart.jpg'
t_fc = self.t_fc
est = ap.chart(t_fc, obs, texts = {'txt': 'Element txt'}, openit=False)
self.assertEqual(est, obs)
pass
def testchart(self):
obs = r'c:\temp\chart.jpg'
t_fc = self.t_fc
est = ap.chart(t_fc, obs, texts = {'txt': 'Element txt'}, openit=False)
self.assertEqual(str(est).lower(), str(obs).lower())
pass
# now print 5 rows as a formatted table, print '-' for geometries tmp = ap.head(fc, 5, False, '|', '-') # Print some basic statistics for each column. tmp = ap.summary(fc) # Force lime, soil, and ffreq to be treated as categorical variables. tmp = ap.summary(fc, ['lime', 'soil', 'ffreq'], ['CAT', 'CAT', 'CAT']) # Make a quick map # If you are in ArcMap's Python window, add fc as a feature layer. # This will add the layer if your ArcMap's Geoprocessing options # allow to 'Add results of geoprocessing operations to the display'. ap.flyr(fc) # If you are not in ArcMap, you can still plot the feature class: ap.chart(fc) # You can plot values in a column once you read its values into Python. # Let's first find out what unique landuse categories there are in fc: ap.distinct(fc, 'landuse') # How many records of each species are there? x = ap.values(fc, 'landuse') ap.frequency(x) # Now plot zinc concentration for landuse 'W' z = ap.values(fc, 'zinc', '"landuse" = \'W\'', '"OBJECTID" ASC') ap.plot(z) # Arcapi now plots histograms too! ap.hist(z) # Show scatter plot of zinc against distance from the river
tmp = ap.head(fc) # now print 5 rows as a formatted table, print '-' for geometries tmp = ap.head(fc, 5, False, '|', '-') # Print some basic statistics for each column. tmp = ap.summary(fc) # Force lime, soil, and ffreq to be treated as categorical variables. tmp = ap.summary(fc, ['lime', 'soil', 'ffreq'], ['CAT', 'CAT', 'CAT']) # Make a quick map # If you are in ArcMap's Python window, add fc as a feature layer. # This will add the layer if your ArcMap's Geoprocessing options # allow to 'Add results of geoprocessing operations to the display'. ap.flyr(fc) # If you are not in ArcMap, you can still plot the feature class: ap.chart(fc) # You can plot values in a column once you read its values into Python. # Let's first find out what unique landuse categories there are in fc: ap.distinct(fc, 'landuse') # How many records of each species are there? x = ap.values(fc, 'landuse') ap.frequency(x) # Now plot zinc concentration for landuse 'W' z = ap.values(fc, 'zinc', '"landuse" = \'W\'', '"OBJECTID" ASC') ap.plot(z) # Show scatter plot of zinc against distance from the river # The 'order by' clause ensures values come in the same order d = ap.values(fc, 'dist_m', '"landuse" = \'W\'', '"OBJECTID" ASC') ap.plot(d, z, main='Zinc', xlab='Ditance', ylab='Zn', pch='o', color='k')
