Programme für Diagrammtypen: Säule, gestapelte Säulen
Linien, gestapelte Balken, Torte
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teil23/.gitignore
vendored
1
teil23/.gitignore
vendored
@@ -3,3 +3,4 @@ __pycache__
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bin
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lib
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share
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*.csv
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20
teil23/iospeed_balken.py
Executable file
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teil23/iospeed_balken.py
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#! ./bin/python
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#encoding: utf-8
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import matplotlib.pyplot as plt
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import numpy as np
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labels = [ 'Pineberry Pi pcie1_gen=2','Pineberry Pi pcie1_gen=3', 'MicroSD Raspi 5', 'MicroSD Raspi 4']
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io_read= np.array([148.50,171.99,30.85,10.15])
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io_write = np.array([99.15,114.97,20.45,6.63])
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legend = ['Schreiben','Lesen']
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#Höhe der Balken
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__hoehe__ =0.6
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fig,ax = plt.subplots()
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plt.barh(labels,io_write,__hoehe__)
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plt.barh(labels,io_read,__hoehe__,left=io_write)
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plt.legend(legend)
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plt.show()
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30
teil23/normparabel_graph.py
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teil23/normparabel_graph.py
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#! ./bin/python
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# encoding:utf-8
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import matplotlib.pyplot as plt
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import numpy as np
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def plot_normal_parabel():
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# Erzeuge Datenpunkte für x-Werte von -10 bis 10
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x = np.linspace(-3, 3, 100)
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# Berechne die y-Werte für die Normalparabel
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y = x**2
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# Erstelle das Diagramm
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plt.plot(x, y, label='Normalparabel: $y=x^2$')
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# Beschriftungen und Titel hinzufügen
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plt.xlabel('x-Achse')
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plt.ylabel('y-Achse')
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plt.title('Normalparabel')
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# Legende hinzufügen
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plt.legend()
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# Funktion aufrufen, um die Normalparabel zu zeichnen
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plot_normal_parabel()
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# Diagramm anzeigen
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plt.grid(True)
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plt.show()
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45
teil23/sinus_parabel_graph.py
Executable file
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teil23/sinus_parabel_graph.py
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#! ./bin/python
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# encoding:utf-8
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import matplotlib.pyplot as plt
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import numpy as np
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def plot_normal_parabel():
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# Erzeuge Datenpunkte für x-Werte von -10 bis 10
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x = np.linspace(-3, 3, 100)
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# Berechne die y-Werte für die Normalparabel
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y = x**2
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# Erstelle das Diagramm
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plt.plot(x, y, label='Normalparabel: $y=x^2$')
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# Beschriftungen und Titel hinzufügen
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plt.xlabel('x-Achse')
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plt.ylabel('y-Achse')
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plt.title('Normalparabel')
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# Legende hinzufügen
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plt.legend()
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def plot_sinus_function():
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# Erzeuge Datenpunkte für x-Werte von -2π bis 2π
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x = np.linspace(-2 * np.pi, 2 * np.pi, 100)
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# Berechne die y-Werte für die Sinusfunktion
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y = np.sin(x)
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# Erstelle das Diagramm für die Sinusfunktion
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plt.plot(x, y, label='Sinusfunktion: $y = \sin(x)$', color='blue')
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# Legende hinzufügen
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plt.legend()
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# Funktion aufrufen, um die Normalparabel zu zeichnen
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plot_normal_parabel()
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plot_sinus_function()
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# Diagramm anzeigen
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plt.grid(True)
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plt.show()
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23
teil23/verkauf_stapel.py
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teil23/verkauf_stapel.py
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#! ./bin/python
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#encoding: utf-8
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import matplotlib.pyplot as plt
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import numpy as np
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jahre= np.array(['2018','2019', '2020'])
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aepfel= np.array([1000,1500,2000])
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erdbeeren =np.array([500,950,900])
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bananen=np.array([400,800,750])
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breite = 0.6
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fig,ax = plt.subplots()
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#ax.legend('Verkäufe')
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ax.bar(jahre,bananen,color='yellow')
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ax.bar(jahre,erdbeeren,bottom=bananen,color='red')
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ax.bar(jahre,aepfel,bottom=erdbeeren,color='green')
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plt.legend(['Bananen','Erdbeeren','Äpfel'])
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plt.show()
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47
teil23/vornamen_reader.py
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teil23/vornamen_reader.py
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#encoding: utf-8
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def read_vornamen(filename):
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dict = {}
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# Der Zähler dient nur dazu, die erste Zeile zu überspringen
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count = 0
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dict['mädchen'] = 0
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dict['jungs'] = 0
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dict['divers'] = 0
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with open(filename,'r') as f:
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for zeile in f:
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if count >0:
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# einzelne Zeile in seine Bestandteile zerlegen
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splitted = zeile.strip().split(';')
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anzahl = splitted[0]
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vorname = splitted[1]
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geschlecht= splitted[2]
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position = splitted[3]
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if geschlecht == 'w':
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dict['mädchen'] += 1
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elif geschlecht == 'm':
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dict['jungs'] += 1
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else:
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dict['divers'] += 1
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data = {}
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data['vorname'] = vorname
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data['anzahl'] = int(anzahl)
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data['geschlecht'] = geschlecht
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data['position'] = position
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if vorname not in dict:
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dict[vorname] = data
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else:
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# doppelte Einträge summieren wir auf.
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e = dict[vorname]
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e['anzahl'] = int(anzahl) + (e['anzahl'])
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count +=1
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gesamt = dict['jungs'] + dict['mädchen'] + dict['divers']
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dict['gesamt'] = gesamt
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return dict
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teil23/vornamen_sauelen.py
Executable file
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teil23/vornamen_sauelen.py
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#! ./bin/python
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#encondig: utf-8
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import matplotlib.pyplot as plt
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from vornamen_reader import read_vornamen
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def plot_geschlecht(vornamen):
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bez= ['Mädchen', 'Jungs','divers']
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geburten = [vornamen['mädchen'], vornamen['jungs'],vornamen['divers']]
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print(f'geburten={geburten}')
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farben = ['red','blue','green']
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fig, ax = plt.subplots()
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print(f'fig={fig}')
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print(f'ax={ax}')
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ax.bar(bez,geburten,label=bez, color=farben)
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ax.set_ylabel('Geburten')
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ax.set_title('Geburten nach Geschlecht Wuppertal 2020')
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ax.legend(title='Geburten')
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plt.show()
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if __name__ == '__main__':
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vornamen = read_vornamen('./Vornamen_Wuppertal_2020.csv')
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jungs= vornamen['jungs']
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maedels = vornamen['mädchen']
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divers = vornamen['divers']
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print(f'Jungs: {jungs}')
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print(f'Mädchen: {maedels}')
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print(f'divers: {divers}')
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# print(f'vornamen={vornamen}')
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plot_geschlecht(vornamen)
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43
teil23/vornamen_torte.py
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teil23/vornamen_torte.py
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#! ./bin/python
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#encondig: utf-8
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import matplotlib.pyplot as plt
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import logging
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from vornamen_reader import read_vornamen
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logging.basicConfig( format='%(asctime)-15s [%(levelname)s] %(funcName)s: %(message)s', level=logging.INFO)
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def plot_geschlecht(vornamen):
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bez= ['Mädchen', 'Jungs','divers']
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geburten = [vornamen['mädchen'], vornamen['jungs'],vornamen['divers']]
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logging.info(f'geburten={geburten}')
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proz_maedels = round(vornamen['mädchen'] / vornamen['gesamt'] *100,2)
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proz_jungs = round(vornamen['jungs'] / vornamen['gesamt'] *100,2)
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proz_divers = round(vornamen['divers'] / vornamen['gesamt'] *100,2)
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farben = ['red','blue','green']
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sizes= [proz_maedels,proz_jungs,proz_divers]
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logging.info(f'sizes={sizes}')
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fig, ax = plt.subplots()
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ax.pie(sizes,explode=(0,0,0), labels=bez,autopct='%1.1f%%',shadow=True,startangle=90)
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ax.axis('equal')
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plt.show()
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if __name__ == '__main__':
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vornamen = read_vornamen('./Vornamen_Wuppertal_2020.csv')
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jungs= vornamen['jungs']
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maedels = vornamen['mädchen']
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divers = vornamen['divers']
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plot_geschlecht(vornamen)
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