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import plotly.offline as pyo | |
def plot_predictions(df_result, df_baseline): | |
data = [] | |
value = go.Scatter( | |
x=df_result.index, | |
y=df_result.value, | |
mode="lines", | |
name="values", | |
marker=dict(), | |
text=df_result.index, | |
line=dict(color="rgba(0,0,0, 0.3)"), | |
) | |
data.append(value) | |
baseline = go.Scatter( | |
x=df_baseline.index, | |
y=df_baseline.prediction, | |
mode="lines", | |
line={"dash": "dot"}, | |
name='linear regression', | |
marker=dict(), | |
text=df_baseline.index, | |
opacity=0.8, | |
) | |
data.append(baseline) | |
prediction = go.Scatter( | |
x=df_result.index, | |
y=df_result.prediction, | |
mode="lines", | |
line={"dash": "dot"}, | |
name='predictions', | |
marker=dict(), | |
text=df_result.index, | |
opacity=0.8, | |
) | |
data.append(prediction) | |
layout = dict( | |
title="Predictions vs Actual Values for the dataset", | |
xaxis=dict(title="Time", ticklen=5, zeroline=False), | |
yaxis=dict(title="Value", ticklen=5, zeroline=False), | |
) | |
fig = dict(data=data, layout=layout) | |
iplot(fig) | |
# Set notebook mode to work in offline | |
pyo.init_notebook_mode() | |
plot_predictions(df_result, df_baseline) |
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