I have a pandas data frame ***df*** that looks like this:

```
    Timestamp           ProductID.       OrderCount

  6/29/21 10:00       50100100200100       8
  6/29/21 10:00       50100100200101       7
  6/29/21 11:00       50100100200102       5
  6/29/21 11:00       50100100200105       8
  6/29/21 11:00       50100100200101      12
  6/29/21 12:00       50100100200109       4
  6/29/21 12:00       50100100200111       5

```

The timestamp data type is datetime64[ns], ProductID and OrderCount are float64 and int64 respectively.

I want to plot a bar chart where in the X-axis the ***ProductIDs*** will be grouped by the ***Timestamp*** and the height of the bars will be the ***OrderCount*** value.

So far I tried this:

```
  import pandas as pd
  from datetime import datetime
  import plotly.express as px
  import plotly.graph_objects as go
  import plotly.io as pio

  barchart = px.bar( 
       data_frame = df,
       x = "Timestamp",
       y = "OrderCount",
       orientation = "v",
       barmode = 'group',
  )  

  pio.show(barchart)

```

but this stacks up the OrderCount values and would print 15 for Timestamp==6/29/21 10:00 instead of plotting 8 and 7 as individual bars. A pandas newbie here, so help is much appreciated.