Download code/train/Python/0023545_BasicStatisticsStrings.py from Variable-role/sajaniemi_variable_dataset_large: direct link, hf CLI and curl.
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https://huggingface.co/datasets/Variable-role/sajaniemi_variable_dataset_large/resolve/main/code/train/Python/0023545_BasicStatisticsStrings.py
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hf download hf://datasets/Variable-role/sajaniemi_variable_dataset_large/code/train/Python/0023545_BasicStatisticsStrings.py
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curl -L -o 0023545_BasicStatisticsStrings.py https://huggingface.co/datasets/Variable-role/sajaniemi_variable_dataset_large/resolve/main/code/train/Python/0023545_BasicStatisticsStrings.py
5.58 kB
| # -*- coding: utf-8 -*- | |
| """ | |
| *************************************************************************** | |
| BasicStatisticsStrings.py | |
| --------------------- | |
| Date : September 2012 | |
| Copyright : (C) 2012 by Victor Olaya | |
| Email : volayaf at gmail dot com | |
| *************************************************************************** | |
| * * | |
| * This program is free software; you can redistribute it and/or modify * | |
| * it under the terms of the GNU General Public License as published by * | |
| * the Free Software Foundation; either version 2 of the License, or * | |
| * (at your option) any later version. * | |
| * * | |
| *************************************************************************** | |
| """ | |
| __author__ = 'Victor Olaya' | |
| __date__ = 'September 2012' | |
| __copyright__ = '(C) 2012, Victor Olaya' | |
| # This will get replaced with a git SHA1 when you do a git archive | |
| __revision__ = '$Format:%H$' | |
| import codecs | |
| from PyQt4.QtCore import * | |
| from qgis.core import * | |
| from processing.core.GeoAlgorithm import GeoAlgorithm | |
| from processing.core.parameters import ParameterVector | |
| from processing.core.parameters import ParameterTableField | |
| from processing.core.outputs import OutputHTML | |
| from processing.core.outputs import OutputNumber | |
| from processing.tools import dataobjects, vector | |
| class BasicStatisticsStrings(GeoAlgorithm): | |
| INPUT_LAYER = 'INPUT_LAYER' | |
| FIELD_NAME = 'FIELD_NAME' | |
| OUTPUT_HTML_FILE = 'OUTPUT_HTML_FILE' | |
| MIN_LEN = 'MIN_LEN' | |
| MAX_LEN = 'MAX_LEN' | |
| MEAN_LEN = 'MEAN_LEN' | |
| COUNT = 'COUNT' | |
| EMPTY = 'EMPTY' | |
| FILLED = 'FILLED' | |
| UNIQUE = 'UNIQUE' | |
| def defineCharacteristics(self): | |
| self.name = 'Basic statistics for text fields' | |
| self.group = 'Vector table tools' | |
| self.addParameter(ParameterVector(self.INPUT_LAYER, | |
| 'Input vector layer', | |
| ParameterVector.VECTOR_TYPE_ANY, False)) | |
| self.addParameter(ParameterTableField(self.FIELD_NAME, | |
| 'Field to calculate statistics on', | |
| self.INPUT_LAYER, | |
| ParameterTableField.DATA_TYPE_STRING)) | |
| self.addOutput(OutputHTML(self.OUTPUT_HTML_FILE, | |
| 'Statistics for text field')) | |
| self.addOutput(OutputNumber(self.MIN_LEN, 'Minimum length')) | |
| self.addOutput(OutputNumber(self.MAX_LEN, 'Maximum length')) | |
| self.addOutput(OutputNumber(self.MEAN_LEN, 'Mean length')) | |
| self.addOutput(OutputNumber(self.COUNT, 'Count')) | |
| self.addOutput(OutputNumber(self.EMPTY, 'Number of empty values')) | |
| self.addOutput(OutputNumber(self.FILLED, 'Number of non-empty values')) | |
| self.addOutput(OutputNumber(self.UNIQUE, 'Number of unique values')) | |
| 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) | |
| sumValue = 0 | |
| minValue = 0 | |
| maxValue = 0 | |
| meanValue = 0 | |
| countEmpty = 0 | |
| countFilled = 0 | |
| isFirst = True | |
| values = [] | |
| features = vector.features(layer) | |
| count = len(features) | |
| total = 100.0 / float(count) | |
| current = 0 | |
| for ft in features: | |
| length = float(len(ft.attributes()[index])) | |
| if isFirst: | |
| minValue = length | |
| maxValue = length | |
| isFirst = False | |
| else: | |
| if length < minValue: | |
| minValue = length | |
| if length > maxValue: | |
| maxValue = length | |
| if length != 0.00: | |
| countFilled += 1 | |
| else: | |
| countEmpty += 1 | |
| values.append(length) | |
| sumValue += length | |
| current += 1 | |
| progress.setPercentage(int(current * total)) | |
| n = float(len(values)) | |
| if n > 0: | |
| meanValue = sumValue / n | |
| uniqueValues = vector.getUniqueValuesCount(layer, index) | |
| data = [] | |
| data.append('Minimum length: ' + unicode(minValue)) | |
| data.append('Maximum length: ' + unicode(maxValue)) | |
| data.append('Mean length: ' + unicode(meanValue)) | |
| data.append('Filled: ' + unicode(countFilled)) | |
| data.append('Empty: ' + unicode(countEmpty)) | |
| data.append('Count: ' + unicode(count)) | |
| data.append('Unique: ' + unicode(uniqueValues)) | |
| self.createHTML(outputFile, data) | |
| self.setOutputValue(self.MIN_LEN, minValue) | |
| self.setOutputValue(self.MAX_LEN, maxValue) | |
| self.setOutputValue(self.MEAN_LEN, meanValue) | |
| self.setOutputValue(self.FILLED, countFilled) | |
| self.setOutputValue(self.EMPTY, countEmpty) | |
| self.setOutputValue(self.COUNT, count) | |
| self.setOutputValue(self.UNIQUE, uniqueValues) | |
| def createHTML(self, outputFile, algData): | |
| f = codecs.open(outputFile, 'w', encoding='utf-8') | |
| f.write('<html><head>') | |
| f.write('<meta http-equiv="Content-Type" content="text/html; \ | |
| charset=utf-8" /></head><body>') | |
| for s in algData: | |
| f.write('<p>' + str(s) + '</p>') | |
| f.write('</body></html>') | |
| f.close() | |