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Describe your context
Please provide us your environment, so we can easily reproduce the issue.
- replace the result of
pip list | grep dashbelow
dash 2.3.1
dash-auth 1.4.1
dash-bootstrap-components 1.0.2
dash-core-components 2.0.0
dash-html-components 2.0.0
dash-table 5.0.0
-
if frontend related, tell us your Browser, Version and OS
- OS: macOS Version 12.2.1 (21D62)
- Browser: Chrome
- Version: 100.0.4896.88 (Official Build) (x86_64)
Describe the bug
"ols" (original least squares) function to add a linear trend line is not producing a regression line. It is instead something closer to polynomial.
The code I'm using to create the graph is as follows:
elif beh_gph == 'ols':
dfg[date_frmt] = pd.to_datetime(dfg[date_frmt])
print(dfg)
fig = px.scatter(dfg, x=date_frmt, y="Episode_Count", color="Target",
labels={"Episode_Count": tally + " per Shift",
"Target": "Target",
"Yr_Mnth": "Date"},
trendline="ols", title="Aggregate Behavior Data: " + patient + " - " + today)
fig.update_xaxes(tickangle=45,)
fig.update_layout(template='plotly_white', hovermode="x unified")
Instead of a logistic regression line per the example here - https://plotly.com/python/linear-fits/
I'm getting this:
The x and y values are just floating point numbers and date values respectively.
The Plotly version is 5.7.0
Expected behavior
Linear regression line.
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