Synchronize Pandas Dataframe With Pyqt5 Qtableview

I have an editable QTableView which reads the values from a pandas DataFrame. What I'm looking for is that when I change the value of one cell, the pandas DataFrame synchronizes a

Solution 1:

The solution is so simple that I don't understand it. If someone could just explain to me what's going on.

I point out the changes I've made in run.py:

run.py edited

classMainWindow(QMainWindow):

    def__init__(self, parent=None):

        QMainWindow.__init__(self, parent)
        uic.loadUi('table.ui', self)  # --- Loading from Qt Designer. ---# Packages.# ---------
        self.pd = pd
        
        # Instancies of class.# --------------------
        self.cnt_init_val = CntInitialValues(self)
                    
        # Attributes of the instance.# ---------------------------
        self.df_table = pd.DataFrame()
        self.model = ''# --- Instance variable for model. ---# PyQt5 objects.# --------------
        self.tableview = self.tableView
        self.btn_print_df = self.pushButtonPrintDataFrame  # --- pushButton to print DataFrame. ---# Add initial values to QTableView and show them.# -----------------------------------------------
        self.df_table = self.cnt_init_val.dataframe_initial()
        self.cnt_init_val.initial_values(self.df_table)
        
        # Events.# -------
        self.btn_print_df.clicked.connect(self.dataframe_output) # --- pushButton prints DataFrame. ---# PyQt5 outputs.# ==============deftable_output(self, df):
        
        print('\nInitial DataFrame:')
        print(self.df_table)
        
        self.model = PandasModel(df)
        self.tableview.setModel(self.model)
        self.tableview.show()
    
    # Terminal outputs.  # --- DaraFrame output. ---# =================defdataframe_output(self):
        
        print('\nUpdated DataFrame:')
        print(self.df_table)

Firstly, when the app is executed:

Initial DataFrame:
     x    x²     x³
0  0.0   0.0    0.0
1  1.0   1.0    1.0
2  2.0   4.0    8.0
3  3.0   9.0   27.0
4  4.0  16.0   64.0
5  5.0  25.0  125.0

After changing some values in the table:

Updated DataFrame:xx²x³0999.00.00.011.01.01.022.04.08.033.09.027.044.016.064.055.025.01111.0

Now I have to work with the DataFrame to make the values of the rows consistent, but that's another question.