Display specified data in new column when the row appear certain data in dashtable

Dash Python
1

Hi,

How to display specified data in new column when the row appear certain data in dashtable.

Ex:

Merchant ID Title Information
Acc01 Product Clothes
Acc01 Customer Customer12
Acc01 Sale date 01/10/2022

Need to add a new column to tag the sale reference number.

Expected output:

Merchant ID Title Information New column
Acc01 Product Clothes
Acc01 Customer Customer12
Acc01 Sale date 01/10/2022 sale no 12345
2

Hello @beginof,

In order to add both a column and row information for that column, your callback would have to output both columns and data.

3

Hi @jinnyzor,

Actually, my original data is as per below:

Merchant ID Product Customer Sale date Sale no
Acc01 Clothes Customer12 01/10/2022 sale no 12345




The data as I shown previously which is already transpose.

Merchant ID Title Information
Acc01 Product Clothes
Acc01 Customer Customer12
Acc01 Sale date 01/10/2022




Code: 

transpose = dff.melt(id_vars = ['Merchant ID']
              ,var_name = ['Title']
              ,value_name = 'Information')

So, based on the code, how can I add the sale no 12345 into the New column and only for the ow of Sale sate?

4

When is the sale no supposed to be added, before or after it is displayed to the user?

I was assuming you were adding the column through interaction with the datatable, is that correct?

5

Sorry, I can’t get what you means.

Require to let the system auto-detect the Title column when the row data is Sale date and there is no empty in the Information, so it will add the sale no 12345 into the Sale no column for the Sale date row.

Other than that will be blank.

Currently, I’m using the merge function to get the data. However, it look like if I has more than one condition for the Sale no column, this method look like not working. For example, I want to add-in a new data called refer to profile in the Sale no column when the row Title = Customer

transpose = dff.melt(id_vars = ['Merchant ID']
              ,var_name = ['Title']
              ,value_name = 'Information')

tr = transpose[transpose['header'] == 'Sale date' ]
tr['Sale no'] = transpose['Sale no']

final_df1 = pd.merge(left = transpose,right = tr, how="left", left_on=['Merchant ID', 'header', 'info'], right_on=['Merchant ID', 'header', 'info'])
6

How to insert the data into the field like the logic below:

if
columnA = ‘abc’, then columnB = ‘123’

elif
columnA = ‘cde’, then columnB = ‘567’

else
columnB = ‘’

This is what I need in my new table.