Hello! I am trying to dynamically output x amount of data tables based on a date chosen in a date picker. I have the data printing correctly, but once I put the dash table into the loop I am only getting the first split of the data in a table. For more context, I am working with PayPal payout data where there are multiple payouts a day based on when orders were placed. For example, orders placed on Friday, Saturday, and Sunday are paid out on Monday but in separate deposits.
Based on this, I feel like the problem is with using dash_table.DataTable in a loop. Has anyone done something like this before? TYIA!
@app.callback(
Output('paypal_tables', 'children'),
[Input("date_picker", "date")]
)
def update_paypal_tables(payout_date):
if payout_date is not None:
payout_date = pd.to_datetime(payout_date, format='%Y-%m-%d')
paypal_data = grab_paypal_payout_data()
filtered_data = paypal_data[paypal_data['Payout_Date'] == payout_date]
filtered_data = filtered_data.drop(columns=['Payout_Date'])
payouts_list = [d for _, d in filtered_data.groupby(['order_date'])]
for df in payouts_list:
df = df.sort_values('product_group')
df.loc['total'] = df.select_dtypes(pd.np.number).sum().round(2)
df = df.to_dict('records')
print(df) #this prints the correct data for each table
return dash_table.DataTable(
id= 'paypal_payout_table'+str(df[0]),
data = df,
#extra stuff
persistence=True,
row_deletable=False,
selected_columns=[], # ids of columns that user selects
selected_rows=[], # indices of rows that user selects
page_action="native", # all data is passed to the table up-front or not ('none')
sort_action='native',
fill_width=False,
style_as_list_view=True,
style_cell={'padding': '4px', 'font-family': 'sans-serif'},
style_header={
'backgroundColor': 'white',
'fontWeight': 'bold'
},
style_data={
'whiteSpace': 'normal',
'height': 'auto',
},
css=[{"selector": ".show-hide", "rule": "display: none"}]
)
