nka/videotron-invoice-compilator
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Sebastien Plante
2022-11-01 13:17:12 -04:00
commit 1b0ff29b05
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videotron1.py Normal file
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import pandas as pd
import PySimpleGUI as sg
sg.theme("Brownblue")
layout = [[sg.T("")], [sg.Text("Choisir le fichier CSV: "), sg.Input(key="-IN2-" ,change_submits=True), sg.FileBrowse(key="-IN-")],[sg.Button("Submit")]]
window = sg.Window('VIDEOTRON MOBILE DATA CALCULATOR', layout, size=(600,150))
while True:
event, values = window.read()
if event == sg.WIN_CLOSED or event=="Exit":
break
elif event == "Submit":
pd.set_option('display.max_rows', None)
df = pd.read_csv(values["-IN2-"], sep=";", encoding='unicode_escape', decimal=",", usecols=[9,20,39])
df.replace('UTILISATION POUR LE', '', regex=True, inplace=True)
df = df.set_axis(['USER', 'B', 'DATA'], axis=1)
df = df.replace('é', 'e', regex=True)
df = df.replace('Ã', 'E', regex=True)
df = df.replace('E´', 'o', regex=True)
df = df.replace('E§', 'c', regex=True)
df = df.replace('‰', '', regex=True)
df = df[df['B'].str.contains('DONN')]
df['DATA'] = df['DATA'].apply(lambda x: float(x.split()[0].replace(',', '.')))
datasum = df.groupby('USER')['DATA'].sum(min_count=1).reset_index()
print(datasum)

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videotron2.py Normal file
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import PySimpleGUI as sg
import pandas as pd
file_list_column = [
[sg.Text('Choose CSV File')],
[sg.Text('File Location: '), sg.Input(size=(25, 1), key="-IN2-",
change_submits=True), sg.FileBrowse(key="-IN-")],
[sg.Button('Submit')],
[sg.Output(size=(60, 40))]]
layout = [[(file_list_column)]]
window = sg.Window('VIDEOTRON DATA CALCULATOR', layout)
while True:
event, values = window.read()
if event == sg.WIN_CLOSED or event == "Exit":
break
if event == 'Submit':
pd.set_option('display.max_rows', None)
df = pd.read_csv(
values["-IN2-"], sep=";", encoding='unicode_escape', decimal=",", usecols=[9, 20, 39])
df.replace('UTILISATION POUR LE', '', regex=True, inplace=True)
df = df.set_axis(['NOM', 'B', 'DATA'], axis=1)
df = df[df['B'].str.contains('DONN')]
df = df.replace('é', 'e', regex=True)
df = df.replace('Ã', 'E', regex=True)
df = df.replace('E´', 'o', regex=True)
df = df.replace('E§', 'c', regex=True)
df = df.replace('‰', '', regex=True)
df['DATA'] = df['DATA'].apply(
lambda x: float(x.split()[0].replace(',', '.')))
datasum = df.groupby('NOM')['DATA'].sum(min_count=1).reset_index()
print(datasum)