nka/videotron-invoice-compilator
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Sebastien Plante
2022-11-01 13:19:21 -04:00
parent 1b0ff29b05
commit ce06903ec9
1 changed files with 20 additions and 19 deletions
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videotron1.py
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@@ -1,36 +1,37 @@
import pandas as pd import pandas as pd
import PySimpleGUI as sg import PySimpleGUI as sg
sg.theme("Brownblue") 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")]] layout = [[sg.T("")], [sg.Text("Choisir le fichier CSV: "), sg.Input(key="-IN2-", change_submits=True),
sg.FileBrowse(key="-IN-", file_types=(("Text Files", "*.csv")))], [sg.Button("Submit")]]
window = sg.Window('VIDEOTRON MOBILE DATA CALCULATOR', layout, size=(600,150)) window = sg.Window('VIDEOTRON MOBILE DATA CALCULATOR', layout, size=(600, 150))
while True: while True:
event, values = window.read() event, values = window.read()
if event == sg.WIN_CLOSED or event=="Exit": if event == sg.WIN_CLOSED or event == "Exit":
break break
elif event == "Submit": elif event == "Submit":
pd.set_option('display.max_rows', None) pd.set_option('display.max_rows', None)
df = pd.read_csv(values["-IN2-"], sep=";", encoding='unicode_escape', decimal=",", usecols=[9,20,39]) 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.replace('UTILISATION POUR LE', '', regex=True, inplace=True)
df = df.set_axis(['USER', 'B', 'DATA'], axis=1) df = df.set_axis(['USER', 'B', 'DATA'], axis=1)
df = df.replace('é', 'e', regex=True) df = df.replace('é', 'e', regex=True)
df = df.replace('Ã', 'E', regex=True) df = df.replace('Ã', 'E', regex=True)
df = df.replace('E´', 'o', regex=True) df = df.replace('E´', 'o', regex=True)
df = df.replace('E§', 'c', regex=True) df = df.replace('E§', 'c', regex=True)
df = df.replace('‰', '', regex=True) df = df.replace('‰', '', regex=True)
df = df[df['B'].str.contains('DONN')] df = df[df['B'].str.contains('DONN')]
df['DATA'] = df['DATA'].apply(lambda x: float(x.split()[0].replace(',', '.'))) df['DATA'] = df['DATA'].apply(
lambda x: float(x.split()[0].replace(',', '.')))
datasum = df.groupby('USER')['DATA'].sum(min_count=1).reset_index() datasum = df.groupby('USER')['DATA'].sum(min_count=1).reset_index()
print(datasum)
print(datasum)