first commit

videotron1.py

@@ -0,0 +1,36 @@
+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)
+        
+

videotron2.py

@@ -0,0 +1,45 @@
+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)