Getting error ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

Question

I have 2 dataframes from a dash datatable, first is the original from the database, second is from the edited datatable.

In this case I have a column which product_date_up means the last edited timestamp.

I already generate the function to add timestamp every time the user click the save button and the timestamp automatically inserted to the row that was edited.

To do that I am using this code

import sqlalchemy as alch
from datetime import datetime

@app.callback(
    Output('table-container-edit','a'),
    [Input('edit-button','n_clicks')],
    [State('data-table-edit','data'),State('edit-button','click')]
)
def edit_db(n_clicks, dataset, click):
    df_table = pd.DataFrame(dataset)
    df_original = pd.read_sql(query2,engine)
    for row in df_table['product_id']:
        if df_table.loc[df_table['product_id']==row, 'product_name'] != df_original.loc[df_original['product_id']==row, 'product_name']: 
            df_table.loc[df_table['product_id']==row, 'product_date_up'] = datetime.now() 
    #if name from the edited table is different from database, do insert the timestamp

    table_name = 'producttype'
    df_table.to_sql(table_name,con=engine, index=False, if_exists='replace', 
        dtype={
            'product_id': alch.CHAR(36),
            'product_name': alch.VARCHAR(100),
            'product_type': alch.VARCHAR(50),
            'product_description': alch.VARCHAR(300),
            'product_date_cr': alch.DateTime(),
            'product_date_up': alch.DateTime(),
            'product_by_cr': alch.VARCHAR(50),
            'product_by_up': alch.VARCHAR(50)
        })

Seems I can not compare the pandas.Series with != and got this error

Traceback (most recent call last):
  File "D:\Software\Python 3.6.8\lib\site-packages\flask\app.py", line 2447, in wsgi_app
    response = self.full_dispatch_request()
  File "D:\Software\Python 3.6.8\lib\site-packages\flask\app.py", line 1952, in full_dispatch_request
    rv = self.handle_user_exception(e)
  File "D:\Software\Python 3.6.8\lib\site-packages\flask\app.py", line 1821, in handle_user_exception
    reraise(exc_type, exc_value, tb)
  File "D:\Software\Python 3.6.8\lib\site-packages\flask\_compat.py", line 39, in reraise
    raise value
  File "D:\Software\Python 3.6.8\lib\site-packages\flask\app.py", line 1950, in full_dispatch_request
    rv = self.dispatch_request()
  File "D:\Software\Python 3.6.8\lib\site-packages\flask\app.py", line 1936, in dispatch_request
    return self.view_functions[rule.endpoint](**req.view_args)
  File "D:\Software\Python 3.6.8\lib\site-packages\dash\dash.py", line 1031, in dispatch
    response.set_data(func(*args, outputs_list=outputs_list))
  File "D:\Software\Python 3.6.8\lib\site-packages\dash\dash.py", line 966, in add_context
    output_value = func(*args, **kwargs)  # %% callback invoked %%
  File "c:\Users\Kenny\Desktop\producttype.py", line 171, in edit_db
    if df_table.loc[df_table['product_id']==row, 'product_name'] != df_original.loc[df_original['product_id']==row, 'product_name']:
  File "D:\Software\Python 3.6.8\lib\site-packages\pandas\core\generic.py", line 1555, in __nonzero__
    self.__class__.__name__
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

I have try is not but it is updating the entire row instead. What can I use?

EDIT

based from the answer from Gingerhaze and little edit, this code works like magic

df_table.loc[(df_original["product_name"] != df_table["product_name"]),"product_date_up"]=datetime.now()

Gingerhaze Gingerhaze · Accepted Answer · 2020-09-03T13:04:04

If I understand correctly you want to find the rows where the product names are not equal and replace the product_date_up value for those rows? You should just be able to use this then and don't need the for loop

original.loc[(original["Product name"]!=new["Product name"]),"Product_date_up"]=datetime.now()

Getting error ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

1 Answers