2

how can I disable pandas dataframe in flet datatable and be able to edit and delete each row.

Column A Column B
Cell 1 Cell 2
Cell 3 Cell 4

I tried setting the column headers by calling

df.column

but I don't know how to go about populating the row

Oxtux
  • 23
  • 3

2 Answers2

1

I've taken the code from another answer and reworked it quite a bit. I'm not sure if I'm unpacking the pandas dataframe in the most efficient way. Maybe someone with more experience can add to this.

import flet as ft
import pandas as pd

df = pd.DataFrame({
        "test" : ['1', "20", "40"],
        "test1" : ['2', "21", "41"],
        "test2" : ['3', "22", "43"],
    })


def headers(df : pd.DataFrame) -> list:
    return [ft.DataColumn(ft.Text(header)) for header in df.columns]

def rows(df : pd.DataFrame) -> list:
    rows = []
    for index, row in df.iterrows():
        rows.append(ft.DataRow(cells = [ft.DataCell(ft.Text(row[header])) for header in df.columns]))
    return rows

            
def main(page ft.Page):
    datatable = ft.DataTable(
        columns=headers(df),
        rows=rows(df))
    
    page.add(datatable)

ft.app(target=main)
Martin Cronje
  • 175
  • 1
  • 6
0

like this build DataTable from DataFrame

datatable = ft.DataTable()

for i in range(len(df.columns)):
     datatable.columns.append(ft.DataColumn(ft.Text(df.columns[i])))
     for x in range(len(df['name'])):
           datatable.rows.append(
                ft.DataRow(
                 cells=[
                 ft.DataCell(ft.Text(df["name"][x])), 
                 ft.DataCell(ft.Text(df["age"][x])),
                 ]
                 ) 
           )
almosy
  • 1
  • Your answer could be improved with additional supporting information. Please [edit] to add further details, such as citations or documentation, so that others can confirm that your answer is correct. You can find more information on how to write good answers [in the help center](/help/how-to-answer). – Blue Robin Mar 02 '23 at 14:34