Hi,
I am trying to build a dash app, in which i am reading a csv file and filtering it based on user inputs and showing the output in a dash datatable.
As the data in a few columns are very large, I am using tooltip_data to show the complete cell data,
The problem I am facing is to show the tooltip data I need to have to define a dataframe df outside the call back function which would be used by the tooltip_data,
if i am assigning a empty df, tooltips are not populating and if i am reading the complete csv in df then the tooltips that are coming are not correct.
Please help me figure out a way by which i can use update the df outside of the callback itself.
PFB the code snippet.
import dash
from dash import Dash
import dash_table
import pandas as pd
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
import dash_bootstrap_components as dbc
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWlwgP.css']
app = dash.Dash(__name__,external_stylesheets=[dbc.themes.LUX])
# df = pd.read_csv("emails_updated.csv")
# df = df[['Date', 'updated_To', 'updated_From', 'Subject', 'Message_Body', 'sentiment']]
df = pd.DataFrame()
app.layout = html.Div([
html.Label([
"Select the Employee",
dcc.Dropdown(
id='folder_picker',
options=[
{'label': 'lay-k', 'value': 'lay-k'},
{'label': 'giron-d', 'value': 'giron-d'},
{'label': 'nemec-g', 'value': 'nemec-g'}
],
value=['lay-k'],
placeholder="Select an Employee",
style={'height': '34px', 'width': '14rem','font-size': "100%"},
)
]),
dash_table.DataTable(
id='table',
page_size=15,
data=df.to_dict('records'),
columns=[{'id': c, 'name': c} for c in df.columns],
style_cell={
'overflow': 'hidden',
'textOverflow': 'ellipsis',
'maxWidth': 0,
},
tooltip_data=[
{
column: {'value': str(value), 'type': 'markdown'}
for column, value in row.items()
} for row in df.to_dict('rows')
],
tooltip_duration=None
)
])
@app.callback([Output('table', 'data'),
Output('table', 'columns')],
[
Input('folder_picker', 'value')]
)
def update_table(employee):
print('employee')
print(employee)
df = pd.read_csv("emails_updated.csv")
df = df[df['employee']==employee]
df = df[['Date', 'updated_To', 'updated_From', 'Subject', 'Message_Body', 'sentiment']]
return df.to_dict('records') , [{"name": i, "id": i} for i in df.columns]
if __name__ == "__main__":
app.run_server()
