[Python] plot time for scatter chart in log scale - plotly

I've got a wide range of values in seconds that I want to display in log scale. It works fine if i plot the raw data in seconds. But I'm trying to convert the y-axis to timestamps and keep the log scale.

df = pd.DataFrame({
'Position'1,2,3,4,5,6,7,8,9),
'Value'1,20,821,2300,4500,30000,405600,1023764,11256400),
})

# works
fig = px.scatter(x=df['Position'], y=df['Value'], log_y="True")


When trying to change the y-axis to datetime, the values aren't correct. When trying to insert the log scale, the values don;t appear at all.

fig = px.scatter(x=df['Position'], y=pd.to_datetime(df['Value'], unit = 's'))
fig = px.scatter(x=df['Position'], y=pd.to_datetime(df['Value'], unit = 's'), log_y="True")


The output y-axis should range from 0 to 130 days, 6 hours, 46 mins, 40 secs. I'm not fussed about being specific here, the broad range is fine.

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