def calcNumericStats(self, features, feedback, field, count):
total = 100.0 / count if count else 0
stat = QgsStatisticalSummary()
for current, ft in enumerate(features):
if feedback.isCanceled():
break
stat.addVariant(ft[field.name()])
feedback.setProgress(int(current * total))
stat.finalize()
cv = stat.stDev() / stat.mean() if stat.mean() != 0 else 0
results = {
self.COUNT: stat.count(),
self.UNIQUE: stat.variety(),
self.EMPTY: stat.countMissing(),
self.FILLED: count - stat.countMissing(),
self.MIN: stat.min(),
self.MAX: stat.max(),
self.RANGE: stat.range(),
self.SUM: stat.sum(),
self.MEAN: stat.mean(),
self.MEDIAN: stat.median(),
self.STD_DEV: stat.stDev(),
self.CV: cv,
self.MINORITY: stat.minority(),
self.MAJORITY: stat.majority(),
self.FIRSTQUARTILE: stat.firstQuartile(),
self.THIRDQUARTILE: stat.thirdQuartile(),
self.IQR: stat.interQuartileRange()
}
data = []
data.append(self.tr('Count: {}').format(stat.count()))
data.append(self.tr('Unique values: {}').format(stat.variety()))
data.append(
self.tr('NULL (missing) values: {}').format(stat.countMissing()))
data.append(self.tr('Minimum value: {}').format(stat.min()))
data.append(self.tr('Maximum value: {}').format(stat.max()))
data.append(self.tr('Range: {}').format(stat.range()))
data.append(self.tr('Sum: {}').format(stat.sum()))
data.append(self.tr('Mean value: {}').format(stat.mean()))
data.append(self.tr('Median value: {}').format(stat.median()))
data.append(self.tr('Standard deviation: {}').format(stat.stDev()))
data.append(self.tr('Coefficient of Variation: {}').format(cv))
data.append(
self.tr('Minority (rarest occurring value): {}').format(
stat.minority()))
data.append(
self.tr('Majority (most frequently occurring value): {}').format(
stat.majority()))
data.append(self.tr('First quartile: {}').format(stat.firstQuartile()))
data.append(self.tr('Third quartile: {}').format(stat.thirdQuartile()))
data.append(
self.tr('Interquartile Range (IQR): {}').format(
stat.interQuartileRange()))
return data, results
def calcNumericStats(self, features, progress, field):
count = len(features)
total = 100.0 / float(count)
stat = QgsStatisticalSummary()
for current, ft in enumerate(features):
stat.addVariant(ft[field.name()])
progress.setPercentage(int(current * total))
stat.finalize()
cv = stat.stDev() / stat.mean() if stat.mean() != 0 else 0
self.setOutputValue(self.COUNT, stat.count())
self.setOutputValue(self.UNIQUE, stat.variety())
self.setOutputValue(self.EMPTY, stat.countMissing())
self.setOutputValue(self.FILLED, count - stat.countMissing())
self.setOutputValue(self.MIN, stat.min())
self.setOutputValue(self.MAX, stat.max())
self.setOutputValue(self.RANGE, stat.range())
self.setOutputValue(self.SUM, stat.sum())
self.setOutputValue(self.MEAN, stat.mean())
self.setOutputValue(self.MEDIAN, stat.median())
self.setOutputValue(self.STD_DEV, stat.stDev())
self.setOutputValue(self.CV, cv)
self.setOutputValue(self.MINORITY, stat.minority())
self.setOutputValue(self.MAJORITY, stat.majority())
self.setOutputValue(self.FIRSTQUARTILE, stat.firstQuartile())
self.setOutputValue(self.THIRDQUARTILE, stat.thirdQuartile())
self.setOutputValue(self.IQR, stat.interQuartileRange())
data = []
data.append(self.tr('Count: {}').format(stat.count()))
data.append(self.tr('Unique values: {}').format(stat.variety()))
data.append(
self.tr('NULL (missing) values: {}').format(stat.countMissing()))
data.append(self.tr('Minimum value: {}').format(stat.min()))
data.append(self.tr('Maximum value: {}').format(stat.max()))
data.append(self.tr('Range: {}').format(stat.range()))
data.append(self.tr('Sum: {}').format(stat.sum()))
data.append(self.tr('Mean value: {}').format(stat.mean()))
data.append(self.tr('Median value: {}').format(stat.median()))
data.append(self.tr('Standard deviation: {}').format(stat.stDev()))
data.append(self.tr('Coefficient of Variation: {}').format(cv))
data.append(
self.tr('Minority (rarest occurring value): {}').format(
stat.minority()))
data.append(
self.tr('Majority (most frequently occurring value): {}').format(
stat.majority()))
data.append(self.tr('First quartile: {}').format(stat.firstQuartile()))
data.append(self.tr('Third quartile: {}').format(stat.thirdQuartile()))
data.append(
self.tr('Interquartile Range (IQR): {}').format(
stat.interQuartileRange()))
return data
def calcNumericStats(self, features, feedback, field, count):
total = 100.0 / count if count else 0
stat = QgsStatisticalSummary()
for current, ft in enumerate(features):
if feedback.isCanceled():
break
stat.addVariant(ft[field.name()])
feedback.setProgress(int(current * total))
stat.finalize()
cv = stat.stDev() / stat.mean() if stat.mean() != 0 else 0
results = {self.COUNT: stat.count(),
self.UNIQUE: stat.variety(),
self.EMPTY: stat.countMissing(),
self.FILLED: count - stat.countMissing(),
self.MIN: stat.min(),
self.MAX: stat.max(),
self.RANGE: stat.range(),
self.SUM: stat.sum(),
self.MEAN: stat.mean(),
self.MEDIAN: stat.median(),
self.STD_DEV: stat.stDev(),
self.CV: cv,
self.MINORITY: stat.minority(),
self.MAJORITY: stat.majority(),
self.FIRSTQUARTILE: stat.firstQuartile(),
self.THIRDQUARTILE: stat.thirdQuartile(),
self.IQR: stat.interQuartileRange()}
data = []
data.append(self.tr('Count: {}').format(stat.count()))
data.append(self.tr('Unique values: {}').format(stat.variety()))
data.append(self.tr('NULL (missing) values: {}').format(stat.countMissing()))
data.append(self.tr('Minimum value: {}').format(stat.min()))
data.append(self.tr('Maximum value: {}').format(stat.max()))
data.append(self.tr('Range: {}').format(stat.range()))
data.append(self.tr('Sum: {}').format(stat.sum()))
data.append(self.tr('Mean value: {}').format(stat.mean()))
data.append(self.tr('Median value: {}').format(stat.median()))
data.append(self.tr('Standard deviation: {}').format(stat.stDev()))
data.append(self.tr('Coefficient of Variation: {}').format(cv))
data.append(self.tr('Minority (rarest occurring value): {}').format(stat.minority()))
data.append(self.tr('Majority (most frequently occurring value): {}').format(stat.majority()))
data.append(self.tr('First quartile: {}').format(stat.firstQuartile()))
data.append(self.tr('Third quartile: {}').format(stat.thirdQuartile()))
data.append(self.tr('Interquartile Range (IQR): {}').format(stat.interQuartileRange()))
return data, results
def calcNumericStats(self, values, sink, feedback):
stat = QgsStatisticalSummary()
total = 50.0 / len(values) if values else 0
current = 0
for cat, v in values.items():
if feedback.isCanceled():
break
feedback.setProgress(int(current * total) + 50)
stat.calculate(v)
f = QgsFeature()
f.setAttributes(
list(cat) + [
stat.count(),
stat.variety(),
stat.min(),
stat.max(),
stat.range(),
stat.sum(),
stat.mean(),
stat.median(),
stat.stDev(),
stat.minority(),
stat.majority(),
stat.firstQuartile(),
stat.thirdQuartile(),
stat.interQuartileRange()
])
sink.addFeature(f, QgsFeatureSink.FastInsert)
current += 1
def calcNumericStats(self, values, sink, feedback):
stat = QgsStatisticalSummary()
total = 50.0 / len(values) if values else 0
current = 0
for cat, v in values.items():
if feedback.isCanceled():
break
feedback.setProgress(int(current * total) + 50)
stat.calculate(v)
f = QgsFeature()
f.setAttributes(list(cat) + [stat.count(),
stat.variety(),
stat.min(),
stat.max(),
stat.range(),
stat.sum(),
stat.mean(),
stat.median(),
stat.stDev(),
stat.minority(),
stat.majority(),
stat.firstQuartile(),
stat.thirdQuartile(),
stat.interQuartileRange()])
sink.addFeature(f, QgsFeatureSink.FastInsert)
current += 1
def calcNumericStats(self, features, progress, field):
count = len(features)
total = 100.0 / float(count)
stat = QgsStatisticalSummary()
for current, ft in enumerate(features):
stat.addVariant(ft[field.name()])
progress.setPercentage(int(current * total))
stat.finalize()
cv = stat.stDev() / stat.mean() if stat.mean() != 0 else 0
self.setOutputValue(self.COUNT, stat.count())
self.setOutputValue(self.UNIQUE, stat.variety())
self.setOutputValue(self.EMPTY, stat.countMissing())
self.setOutputValue(self.FILLED, count - stat.countMissing())
self.setOutputValue(self.MIN, stat.min())
self.setOutputValue(self.MAX, stat.max())
self.setOutputValue(self.RANGE, stat.range())
self.setOutputValue(self.SUM, stat.sum())
self.setOutputValue(self.MEAN, stat.mean())
self.setOutputValue(self.MEDIAN, stat.median())
self.setOutputValue(self.STD_DEV, stat.stDev())
self.setOutputValue(self.CV, cv)
self.setOutputValue(self.MINORITY, stat.minority())
self.setOutputValue(self.MAJORITY, stat.majority())
self.setOutputValue(self.FIRSTQUARTILE, stat.firstQuartile())
self.setOutputValue(self.THIRDQUARTILE, stat.thirdQuartile())
self.setOutputValue(self.IQR, stat.interQuartileRange())
data = []
data.append(self.tr('Count: {}').format(stat.count()))
data.append(self.tr('Unique values: {}').format(stat.variety()))
data.append(self.tr('NULL (missing) values: {}').format(stat.countMissing()))
data.append(self.tr('Minimum value: {}').format(stat.min()))
data.append(self.tr('Maximum value: {}').format(stat.max()))
data.append(self.tr('Range: {}').format(stat.range()))
data.append(self.tr('Sum: {}').format(stat.sum()))
data.append(self.tr('Mean value: {}').format(stat.mean()))
data.append(self.tr('Median value: {}').format(stat.median()))
data.append(self.tr('Standard deviation: {}').format(stat.stDev()))
data.append(self.tr('Coefficient of Variation: {}').format(cv))
data.append(self.tr('Minority (rarest occurring value): {}').format(stat.minority()))
data.append(self.tr('Majority (most frequently occurring value): {}').format(stat.majority()))
data.append(self.tr('First quartile: {}').format(stat.firstQuartile()))
data.append(self.tr('Third quartile: {}').format(stat.thirdQuartile()))
data.append(self.tr('Interquartile Range (IQR): {}').format(stat.interQuartileRange()))
return data
def processAlgorithm(self, feedback):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.INPUT_LAYER))
fieldName = self.getParameterValue(self.FIELD_NAME)
outputFile = self.getOutputValue(self.OUTPUT_HTML_FILE)
request = QgsFeatureRequest().setFlags(
QgsFeatureRequest.NoGeometry).setSubsetOfAttributes([fieldName],
layer.fields())
stat = QgsStatisticalSummary()
features = vector.features(layer, request)
count = len(features)
total = 100.0 / float(count)
for current, ft in enumerate(features):
stat.addVariant(ft[fieldName])
feedback.setProgress(int(current * total))
stat.finalize()
count = stat.count()
uniqueValue = stat.variety()
minValue = stat.min()
maxValue = stat.max()
rValue = stat.range()
sumValue = stat.sum()
meanValue = stat.mean()
medianValue = stat.median()
stdDevValue = stat.stDev()
cvValue = stdDevValue / meanValue if meanValue != 0 else 0
minority = stat.minority()
majority = stat.majority()
firstQuartile = stat.firstQuartile()
thirdQuartile = stat.thirdQuartile()
iqr = stat.interQuartileRange()
nullValues = stat.countMissing()
data = []
data.append(self.tr('Analyzed layer: {}').format(layer.name()))
data.append(self.tr('Analyzed field: {}').format(fieldName))
data.append(self.tr('Count: {}').format(count))
data.append(self.tr('Unique values: {}').format(uniqueValue))
data.append(self.tr('Minimum value: {}').format(minValue))
data.append(self.tr('Maximum value: {}').format(maxValue))
data.append(self.tr('Range: {}').format(rValue))
data.append(self.tr('Sum: {}').format(sumValue))
data.append(self.tr('Mean value: {}').format(meanValue))
data.append(self.tr('Median value: {}').format(medianValue))
data.append(self.tr('Standard deviation: {}').format(stdDevValue))
data.append(self.tr('Coefficient of Variation: {}').format(cvValue))
data.append(
self.tr('Minority (rarest occurring value): {}').format(minority))
data.append(
self.tr('Majority (most frequently occurring value): {}').format(
majority))
data.append(self.tr('First quartile: {}').format(firstQuartile))
data.append(self.tr('Third quartile: {}').format(thirdQuartile))
data.append(self.tr('NULL (missing) values: {}').format(nullValues))
data.append(self.tr('Interquartile Range (IQR): {}').format(iqr))
self.createHTML(outputFile, data)
self.setOutputValue(self.COUNT, count)
self.setOutputValue(self.UNIQUE, uniqueValue)
self.setOutputValue(self.MIN, minValue)
self.setOutputValue(self.MAX, maxValue)
self.setOutputValue(self.RANGE, rValue)
self.setOutputValue(self.SUM, sumValue)
self.setOutputValue(self.MEAN, meanValue)
self.setOutputValue(self.MEDIAN, medianValue)
self.setOutputValue(self.STD_DEV, stdDevValue)
self.setOutputValue(self.MINORITY, minority)
self.setOutputValue(self.MAJORITY, majority)
self.setOutputValue(self.FIRSTQUARTILE, firstQuartile)
self.setOutputValue(self.THIRDQUARTILE, thirdQuartile)
self.setOutputValue(self.NULLVALUES, nullValues)
self.setOutputValue(self.IQR, iqr)
def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.INPUT_LAYER))
fieldName = self.getParameterValue(self.FIELD_NAME)
outputFile = self.getOutputValue(self.OUTPUT_HTML_FILE)
request = QgsFeatureRequest().setFlags(QgsFeatureRequest.NoGeometry).setSubsetOfAttributes([fieldName], layer.fields())
stat = QgsStatisticalSummary()
features = vector.features(layer, request)
count = len(features)
total = 100.0 / float(count)
for current, ft in enumerate(features):
stat.addVariant(ft[fieldName])
progress.setPercentage(int(current * total))
stat.finalize()
count = stat.count()
uniqueValue = stat.variety()
minValue = stat.min()
maxValue = stat.max()
rValue = stat.range()
sumValue = stat.sum()
meanValue = stat.mean()
medianValue = stat.median()
stdDevValue = stat.stDev()
cvValue = stdDevValue / meanValue if meanValue != 0 else 0
minority = stat.minority()
majority = stat.majority()
firstQuartile = stat.firstQuartile()
thirdQuartile = stat.thirdQuartile()
iqr = stat.interQuartileRange()
nullValues = stat.countMissing()
data = []
data.append(self.tr('Analyzed layer: {}').format(layer.name()))
data.append(self.tr('Analyzed field: {}').format(fieldName))
data.append(self.tr('Count: {}').format(count))
data.append(self.tr('Unique values: {}').format(uniqueValue))
data.append(self.tr('Minimum value: {}').format(minValue))
data.append(self.tr('Maximum value: {}').format(maxValue))
data.append(self.tr('Range: {}').format(rValue))
data.append(self.tr('Sum: {}').format(sumValue))
data.append(self.tr('Mean value: {}').format(meanValue))
data.append(self.tr('Median value: {}').format(medianValue))
data.append(self.tr('Standard deviation: {}').format(stdDevValue))
data.append(self.tr('Coefficient of Variation: {}').format(cvValue))
data.append(self.tr('Minority (rarest occurring value): {}').format(minority))
data.append(self.tr('Majority (most frequently occurring value): {}').format(majority))
data.append(self.tr('First quartile: {}').format(firstQuartile))
data.append(self.tr('Third quartile: {}').format(thirdQuartile))
data.append(self.tr('NULL (missing) values: {}').format(nullValues))
data.append(self.tr('Interquartile Range (IQR): {}').format(iqr))
self.createHTML(outputFile, data)
self.setOutputValue(self.COUNT, count)
self.setOutputValue(self.UNIQUE, uniqueValue)
self.setOutputValue(self.MIN, minValue)
self.setOutputValue(self.MAX, maxValue)
self.setOutputValue(self.RANGE, rValue)
self.setOutputValue(self.SUM, sumValue)
self.setOutputValue(self.MEAN, meanValue)
self.setOutputValue(self.MEDIAN, medianValue)
self.setOutputValue(self.STD_DEV, stdDevValue)
self.setOutputValue(self.MINORITY, minority)
self.setOutputValue(self.MAJORITY, majority)
self.setOutputValue(self.FIRSTQUARTILE, firstQuartile)
self.setOutputValue(self.THIRDQUARTILE, thirdQuartile)
self.setOutputValue(self.NULLVALUES, nullValues)
self.setOutputValue(self.IQR, iqr)
def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.INPUT_LAYER))
fieldName = self.getParameterValue(self.FIELD_NAME)
outputFile = self.getOutputValue(self.OUTPUT_HTML_FILE)
cvValue = 0
minValue = 0
maxValue = 0
sumValue = 0
meanValue = 0
medianValue = 0
stdDevValue = 0
minority = 0
majority = 0
firstQuartile = 0
thirdQuartile = 0
nullValues = 0
iqr = 0
values = []
features = vector.features(layer)
count = len(features)
total = 100.0 / float(count)
for current, ft in enumerate(features):
value = ft[fieldName]
if value or value == 0:
values.append(float(value))
else:
nullValues += 1
progress.setPercentage(int(current * total))
stat = QgsStatisticalSummary()
stat.calculate(values)
count = stat.count()
uniqueValue = stat.variety()
minValue = stat.min()
maxValue = stat.max()
rValue = stat.range()
sumValue = stat.sum()
meanValue = stat.mean()
medianValue = stat.median()
stdDevValue = stat.stDev()
if meanValue != 0.00:
cvValue = stdDevValue / meanValue
minority = stat.minority()
majority = stat.majority()
firstQuartile = stat.firstQuartile()
thirdQuartile = stat.thirdQuartile()
iqr = stat.interQuartileRange()
data = []
data.append(self.tr('Analyzed layer: {}').format(layer.name()))
data.append(self.tr('Analyzed field: {}').format(fieldName))
data.append(self.tr('Count: {}').format(count))
data.append(self.tr('Unique values: {}').format(uniqueValue))
data.append(self.tr('Minimum value: {}').format(minValue))
data.append(self.tr('Maximum value: {}').format(maxValue))
data.append(self.tr('Range: {}').format(rValue))
data.append(self.tr('Sum: {}').format(sumValue))
data.append(self.tr('Mean value: {}').format(meanValue))
data.append(self.tr('Median value: {}').format(medianValue))
data.append(self.tr('Standard deviation: {}').format(stdDevValue))
data.append(self.tr('Coefficient of Variation: {}').format(cvValue))
data.append(
self.tr('Minority (rarest occurring value): {}').format(minority))
data.append(
self.tr('Majority (most frequently occurring value): {}').format(
majority))
data.append(self.tr('First quartile: {}').format(firstQuartile))
data.append(self.tr('Third quartile: {}').format(thirdQuartile))
data.append(self.tr('NULL (missing) values: {}').format(nullValues))
data.append(self.tr('Interquartile Range (IQR): {}').format(iqr))
self.createHTML(outputFile, data)
self.setOutputValue(self.COUNT, count)
self.setOutputValue(self.UNIQUE, uniqueValue)
self.setOutputValue(self.MIN, minValue)
self.setOutputValue(self.MAX, maxValue)
self.setOutputValue(self.RANGE, rValue)
self.setOutputValue(self.SUM, sumValue)
self.setOutputValue(self.MEAN, meanValue)
self.setOutputValue(self.MEDIAN, medianValue)
self.setOutputValue(self.STD_DEV, stdDevValue)
self.setOutputValue(self.MINORITY, minority)
self.setOutputValue(self.MAJORITY, majority)
self.setOutputValue(self.FIRSTQUARTILE, firstQuartile)
self.setOutputValue(self.THIRDQUARTILE, thirdQuartile)
self.setOutputValue(self.NULLVALUES, nullValues)
self.setOutputValue(self.IQR, iqr)
def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.INPUT_LAYER))
fieldName = self.getParameterValue(self.FIELD_NAME)
outputFile = self.getOutputValue(self.OUTPUT_HTML_FILE)
index = layer.fieldNameIndex(fieldName)
cvValue = 0
minValue = 0
maxValue = 0
sumValue = 0
meanValue = 0
medianValue = 0
stdDevValue = 0
minority = 0
majority = 0
firstQuartile = 0
thirdQuartile = 0
iqr = 0
isFirst = True
values = []
features = vector.features(layer)
count = len(features)
total = 100.0 / float(count)
current = 0
for ft in features:
if ft.attributes()[index]:
values.append(float(ft.attributes()[index]))
current += 1
progress.setPercentage(int(current * total))
stat = QgsStatisticalSummary()
stat.calculate(values)
count = stat.count()
uniqueValue = stat.variety()
minValue = stat.min()
maxValue = stat.max()
rValue = stat.range()
sumValue = stat.sum()
meanValue = stat.mean()
medianValue = stat.median()
stdDevValue = stat.stDev()
if meanValue != 0.00:
cvValue = stdDevValue / meanValue
minority = stat.minority()
majority = stat.majority()
firstQuartile = stat.firstQuartile()
thirdQuartile = stat.thirdQuartile()
iqr = stat.interQuartileRange()
data = []
data.append('Count: ' + unicode(count))
data.append('Unique values: ' + unicode(uniqueValue))
data.append('Minimum value: ' + unicode(minValue))
data.append('Maximum value: ' + unicode(maxValue))
data.append('Range: ' + unicode(rValue))
data.append('Sum: ' + unicode(sumValue))
data.append('Mean value: ' + unicode(meanValue))
data.append('Median value: ' + unicode(medianValue))
data.append('Standard deviation: ' + unicode(stdDevValue))
data.append('Coefficient of Variation: ' + unicode(cvValue))
data.append('Minority (rarest occurring value): ' + unicode(minority))
data.append('Majority (most frequently occurring value): ' + unicode(majority))
data.append('First quartile: ' + unicode(firstQuartile))
data.append('Third quartile: ' + unicode(thirdQuartile))
data.append('Interquartile Range (IQR): ' + unicode(iqr))
self.createHTML(outputFile, data)
self.setOutputValue(self.COUNT, count)
self.setOutputValue(self.UNIQUE, uniqueValue)
self.setOutputValue(self.MIN, minValue)
self.setOutputValue(self.MAX, maxValue)
self.setOutputValue(self.RANGE, rValue)
self.setOutputValue(self.SUM, sumValue)
self.setOutputValue(self.MEAN, meanValue)
self.setOutputValue(self.MEDIAN, medianValue)
self.setOutputValue(self.STD_DEV, stdDevValue)
self.setOutputValue(self.MINORITY, minority)
self.setOutputValue(self.MAJORITY, majority)
self.setOutputValue(self.FIRSTQUARTILE, firstQuartile)
self.setOutputValue(self.THIRDQUARTILE, thirdQuartile)
self.setOutputValue(self.IQR, iqr)
def processAlgorithm(self, progress):
layer = dataobjects.getObjectFromUri(
self.getParameterValue(self.INPUT_LAYER))
fieldName = self.getParameterValue(self.FIELD_NAME)
outputFile = self.getOutputValue(self.OUTPUT_HTML_FILE)
index = layer.fieldNameIndex(fieldName)
cvValue = 0
minValue = 0
maxValue = 0
sumValue = 0
meanValue = 0
medianValue = 0
stdDevValue = 0
minority = 0
majority = 0
firstQuartile = 0
thirdQuartile = 0
iqr = 0
isFirst = True
values = []
features = vector.features(layer)
count = len(features)
total = 100.0 / float(count)
current = 0
for ft in features:
if ft.attributes()[index]:
values.append(float(ft.attributes()[index]))
current += 1
progress.setPercentage(int(current * total))
stat = QgsStatisticalSummary()
stat.calculate(values)
count = stat.count()
uniqueValue = stat.variety()
minValue = stat.min()
maxValue = stat.max()
rValue = stat.range()
sumValue = stat.sum()
meanValue = stat.mean()
medianValue = stat.median()
stdDevValue = stat.stDev()
if meanValue != 0.00:
cvValue = stdDevValue / meanValue
minority = stat.minority()
majority = stat.majority()
firstQuartile = stat.firstQuartile()
thirdQuartile = stat.thirdQuartile()
iqr = stat.interQuartileRange()
data = []
data.append('Analyzed layer: ' + layer.name())
data.append('Analyzed field: ' + fieldName)
data.append('Count: ' + unicode(count))
data.append('Unique values: ' + unicode(uniqueValue))
data.append('Minimum value: ' + unicode(minValue))
data.append('Maximum value: ' + unicode(maxValue))
data.append('Range: ' + unicode(rValue))
data.append('Sum: ' + unicode(sumValue))
data.append('Mean value: ' + unicode(meanValue))
data.append('Median value: ' + unicode(medianValue))
data.append('Standard deviation: ' + unicode(stdDevValue))
data.append('Coefficient of Variation: ' + unicode(cvValue))
data.append('Minority (rarest occurring value): ' + unicode(minority))
data.append('Majority (most frequently occurring value): ' + unicode(majority))
data.append('First quartile: ' + unicode(firstQuartile))
data.append('Third quartile: ' + unicode(thirdQuartile))
data.append('Interquartile Range (IQR): ' + unicode(iqr))
self.createHTML(outputFile, data)
self.setOutputValue(self.COUNT, count)
self.setOutputValue(self.UNIQUE, uniqueValue)
self.setOutputValue(self.MIN, minValue)
self.setOutputValue(self.MAX, maxValue)
self.setOutputValue(self.RANGE, rValue)
self.setOutputValue(self.SUM, sumValue)
self.setOutputValue(self.MEAN, meanValue)
self.setOutputValue(self.MEDIAN, medianValue)
self.setOutputValue(self.STD_DEV, stdDevValue)
self.setOutputValue(self.MINORITY, minority)
self.setOutputValue(self.MAJORITY, majority)
self.setOutputValue(self.FIRSTQUARTILE, firstQuartile)
self.setOutputValue(self.THIRDQUARTILE, thirdQuartile)
self.setOutputValue(self.IQR, iqr)
