# Can't edit DataTable

**URL:** <https://community.plotly.com/t/cant-edit-datatable/62653>\
**Category:** Dash Python\
**Created:** [April 3, 2022, 4:36pm UTC](https://community.plotly.com/t/cant-edit-datatable/62653 "2022-04-03T16:36:46Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![shane](https://avatars.discourse-cdn.com/v4/letter/s/dbc845/32.png) [@shane](https://community.plotly.com/u/shane)\
**Post date:** [April 3, 2022, 4:36pm UTC](https://community.plotly.com/t/cant-edit-datatable/62653/1 "2022-04-03T16:36:46Z")

</div>

I don’t seem to be able to edit data in my DataTable. Dash version 2.2.0. Any ideas what I’m doing wrong?

```python
dataTable = dash_table.DataTable(id="dataTable1", data=df.to_dict('records'), page_size=10, editable=True)

```

Here’s the full code:

```python
# Import libraries
from dash import Dash, dash_table
from dash.dependencies import Input, Output, State
import dash_core_components as dcc
import dash_bootstrap_components as dbc
import pandas as pd
import plotly.express as px
from dash.exceptions import PreventUpdate

# Import data into Pandas dataframe
df = px.data.gapminder()

# Filter data with a list of countries we're interested in exploring
country_list = ['Canada', 'Brazil', 'Norway', 'Germany']
df = df[df['country'].isin(country_list)]

# Create a Dash DataTable, limit the page size to 10 because this data set is huge
dataTable = dash_table.DataTable(id="dataTable1", data=df.to_dict('records'), page_size=10, editable=True)

# Create a line graph of life expectancy over time
fig = px.line(df, x= 'year', y = 'lifeExp', color = 'country', markers=True)
graph1 = dcc.Graph(id='figure1', figure=fig)

# Create the Dash application with Bootstrap CSS stylesheet
app = Dash( __name__ , external_stylesheets=[dbc.themes.BOOTSTRAP])

# Create the app layout
app.layout = dbc.Container(
    dbc.Row([
        dbc.Col([
            graph1,
            dataTable
        ])
    ])
)

@app.callback(
    Output('figure1', 'figure'),
    Input('dataTable1', 'data')
)
def display_output(data):
    print("data changed")
    raise PreventUpdate
    # print(str(data))
    # df = pd.DataFrame(rows, columns=[c['name'] for c in columns])
    # return {
    # 'data': [{
    # 'dimensions': [{
    # 'label': col['name'],
    # 'values': df[col['id']]
    # } for col in columns]
    # }]
    # }

# Launch the app server
if __name__ == ' __main__':
    app.run_server()

```