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app.py
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app.py
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from flask import Flask, render_template, redirect, url_for
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import pandas as pd
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from charts.charts import bar_chart, bar_chart_with_special_legend, point_chart, pie_chart
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app = Flask(__name__)
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# Read the CSV file
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def translate_csv(file, translation_dict):
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with open(file, 'r') as f:
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text = f.read()
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for key, value in translation_dict.items():
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text = text.replace(key, value)
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with open('data/umfrage2survey.csv', 'w') as f:
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f.write(text)
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translation_dict = {
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'Wie sind Sie auf WissKI aufmerksam geworden?': 'How did you hear about WissKI?',
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'In welchem Bereich verwenden Sie WissKI?': 'In which area do you use WissKI?',
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'Wie lange arbeiten Sie mit WissKI?': 'How long do you work with WissKI?',
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'Bedeutung von Softwarefeatures und Eigenschaften': 'Importance of software features and properties',
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'In welcher Rolle benutzen Sie WissKI?': 'In which role do you use WissKI?',
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'Haben Sie Erfahrung mit anderen Forschungsdaten-Management-Systemen?': 'Do you have experience with other research data management systems?',
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'Haben Sie Zugriff auf kompetenten IT- und Systemadministrationssupport innerhalb Ihres Projektes bzw. Institution?': 'Do you have access to competent IT and system administration support within your project or institution?',
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'Arbeitet Ihre Institution/ Unternehmen das erste Mal mit WissKI?': 'Is this the first time your institution/company has worked with WissKI?',
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'Wie viele Stunden stehen Ihnen für die Arbeit mit WissKI wöchentlich zur Verfügung?': 'How many hours a week do you have available for working with WissKI?',
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'Welchen Community-Angeboten haben Sie mindestens einmal wahrgenommen?': 'Which community offers have you used at least once?',
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'Im Verhältnis zu anderen Forschungsdaten-Management-Systemen verorte ich die Qualität von WissKI als...': 'In relation to other research data management systems, I classify the quality of WissKI as...',
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'Wie wahrscheinlich ist es, dass Sie WissKI als Forschungsdaten-Management-System weiterempfehlen?':'How likely is it that you would recommend WissKI as a research data management system?'
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}
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translate_csv('data/Community-Umfrage.csv', translation_dict)
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df = pd.read_csv('data/umfrage2survey.csv', encoding='utf8')
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#df = pd.read_csv('data/Community-Umfrage.csv', encoding='utf8')
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plots = {}
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# Normal bar charts
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# 1 Wie sind Sie auf WissKI aufmerksam geworden?
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# 2 In welchem Bereich verwenden Sie WissKI?
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# 25 Haben Sie Zugriff auf kompetenten IT- und Systemadministrationssupport innerhalb Ihres Projektes bzw. Institution?
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# 26 Arbeitet Ihre Institution/ Unternehmen das erste Mal mit WissKI?
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bar_charts = [1,2,25,26]
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for chart in bar_charts:
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question_data = df.iloc[:, chart]
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question_plot = bar_chart(question_data, question_data.name)
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plots[chart] = (question_data.name, question_plot)
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# Cleaned pie charts
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# 23 In welcher Rolle benutzen Sie WissKI?
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question_data = df.iloc[:, 23]
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for index, value in question_data.items():
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new_value = value.split(' (')[0]
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question_data[index] = new_value
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question_plot = pie_chart(question_data, question_data.name)
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plots[3] = (question_data.name, question_plot)
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# Normal Pie charts
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# 3 Wie lange arbeiten Sie mit WissKI?
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# 24 Haben Sie Erfahrung mit anderen Forschungsdaten-Management-Systemen?
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# 27 Wie viele Stunden stehen Ihnen für die Arbeit mit WissKI wöchentlich zur Verfügung?
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# 28 Welchen Community-Angeboten haben Sie mindestens einmal wahrgenommen?
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pie_charts = [3,24,27,28]
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for chart in pie_charts:
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question_data = df.iloc[:, chart]
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question_plot = pie_chart(question_data, question_data.name)
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plots[chart] = (question_data.name, question_plot)
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# Point charts
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# 9-22 Software Features
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median_values = df.iloc[:, 9:23].median()
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median_values_cleaned = pd.Series(name='Software Features')
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for index, value in median_values.items():
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new_index = index.split(' [')[1].split(']')[0]
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median_values_cleaned[new_index] = value
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point_plot = point_chart(median_values_cleaned, 'Software Features')
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plots[9] = ('Software Features', point_plot)
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# Bar charts with median
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# 29 Im Verhältnis zu anderen Forschungsdaten-Management-Systemen verorte ich die Qualität von WissKI als...
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bar_charts_with_median = [29]
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for chart in bar_charts_with_median:
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question_data = df.iloc[:, chart]
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question_plot = bar_chart_with_special_legend(question_data, question_data.name, 'quality')
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plots[chart] = (question_data.name, question_plot)
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bar_charts_with_median = [31]
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for chart in bar_charts_with_median:
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question_data = df.iloc[:, chart]
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question_plot = bar_chart_with_special_legend(question_data, question_data.name, 'recommendation')
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plots[chart] = (question_data.name, question_plot)
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plots = dict(sorted(plots.items(), key=lambda x: x[0]))
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# Generate list of charts
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charts = [{'id': i+1, 'title': plots[col][0], 'data': plots[col][1]} for i, col in enumerate(plots.keys())]
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@app.route('/')
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def index():
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return redirect(url_for('show_chart', chart_id=1))
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@app.route('/chart/<int:chart_id>')
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def show_chart(chart_id):
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chart = next((c for c in charts if c['id'] == chart_id), None)
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if not chart:
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return redirect(url_for('index'))
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plot_url = chart['data']
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prev_id = chart_id - 1 if chart_id > 1 else len(charts)
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next_id = chart_id + 1 if chart_id < len(charts) else 1
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return render_template('chart.html', plot_url=plot_url, prev_id=prev_id, next_id=next_id, title=chart['title'])
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if __name__ == '__main__':
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app.run(debug=True)
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