Plotly: Indexing and plotting timestamps-CodePudding

I am creating a plotly graph with a slider. In the 2nd line I want to add a marker My issue is in the 2nd line of the code below:

fig.add_trace(go.Scatter(visible=False, x=time_qin, y=q_in_cum_plot, mode='lines', line=dict(color='red')), row=3, col=1)
fig.add_trace(go.Scatter(visible=False, x=time_qin[row], y=q_in_cum_plot[row],  mode='markers', marker=dict(color='red')), row=3, col=1)

time_qin is an array that contains datetime values. When I'm indexing over time_qin in the 2nd line I obtain the following error:

ValueError: 
Invalid value of type 'datetime.date' received for the 'x' property of scatter
    Received value: datetime.date(2020, 5, 12)

The 'x' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series

So when calling time_qin[row] a datetime.date type is received that plotly can not handle. Is there a work around in order to add the tracer to the plot? Many thanks for the help.

CodePudding user response：

The most likely cause of this error is that if the index is a single value, the resulting value is the value itself and not a list, array, or series, so it is occurring. The solution is to specify it in a list format. My code uses stock price data and the index is a single number. I use line or mar mode because it is indistinguishable in line mode for scatter plots.

import yfinance as yf
data = yf.download("AAPL", start="2022-05-01", end="2022-07-01")

import plotly.graph_objects as go

row = 84
fig = go.Figure()
fig.add_trace(go.Scatter(visible=True, x=data.index, y=data['Close'], mode='lines', line=dict(color='red')))
fig.add_trace(go.Scatter(visible=True,
                         x=[data.index[row]],
                         y=[data['Close'][row]],
                         mode='lines markers',
                         line=dict(
                             color='green',
                             width=2
                         )
                        )
             )
fig.update_layout(template='plotly_white')
fig.show