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2 Commits
Author | SHA1 | Date |
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MoritzLutz | cd615c1938 | |
MoritzLutz | ea7143df3f |
15
python.py
15
python.py
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@ -1,15 +0,0 @@
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import numpy as np
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import matplotlib.pyplot as plt
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import seaborn as sns
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plt.title('ChatGpt seine Lernkurve')
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a = np.random.random((100,100))
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plt.imshow(a)
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plt.hot()
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plt.colorbar()
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plt.show()
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import re
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import json
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#this is a test comment
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person_list = []
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with open("Studienleistung2/Personen.txt") as input:
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for lines in input:
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current_line = lines.split(",")
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titel = re.findall(r"([A-Z][a-z]+\.)", current_line[0])
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name = re.findall(r"([A-Z][a-z]+[^\.]*$)", current_line[0])
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name = re.split("\s", name[0])
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# getting the fragments building the whole name
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first_name = name[0]
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# if there are more than one second names
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second_name = ""
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counter = 1
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while counter<len(name)-1:
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second_name = second_name + name[counter] + " "
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counter += 1
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# -1 to get the last elem of the list name
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last_name = name[-1]
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address = re.findall(r"(.+)([1-9]+).([\d]{5})(.+)", current_line[1])
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address = address[0]
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street_name = address[0]
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house_number = address[1]
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plz = address[2]
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city = address[3]
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geb_date = re.findall("([0-9][0-9]\.[0-9][0-9]\.[0-9][0-9][0-9][0-9])", current_line[2])
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tel = re.findall("(\d{12,15})", current_line[3])
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person = {
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"titel": titel[0],
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"Vorname": first_name,
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"Zweitname": second_name,
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"Nachname": last_name,
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"Straße": street_name,
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"Hausnummer": house_number,
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"PLZ": plz,
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"Stadt": city,
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"Geb.Datum": geb_date[0],
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"Tel.": tel[0],
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}
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person_list.append(person)
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with open("Studienleistung2/Person_Neu.json", "w") as outfile:
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json.dump(person_list, outfile, indent=2, ensure_ascii=False)
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