# Plot the Data itself.plt.plot(x,y)# Calculate the Trendlinez=numpy.polyfit(x,y,1)p=numpy.poly1d(z)# Display the Trendlineplt.plot(x,p(x)) Output: Complete Code importnumpyfrommatplotlibimportpyplotasplt x=[xforxinrange(0,10)]y=numpy.random.rand(10)# Plot the Data itself.plt....
fig = px.scatter(df, x="num_chickens", y="num_rabbits", trendline="ols") fig.add_trace(go.Scatter(x=num_chickens, y=y_hat, name = 'Predicted', line=dict(color='red', width=1))) st.plotly_chart(fig) 77 changes: 77 additions & 0 deletions 77 Book3_Ch25_Python_Codes...
fig = px.scatter(df, x="num_chickens", y="num_rabbits", trendline="ols") fig.add_trace(go.Scatter(x=num_chickens, y=y_hat, name = 'Predicted', line=dict(color='red', width=1))) st.plotly_chart(fig) 77 changes: 77 additions & 0 deletions 77 Book3_Ch25_Python_Codes/...
fig = px.scatter(df, x="num_chickens", y="num_rabbits", trendline="ols") fig.add_trace(go.Scatter(x=num_chickens, y=y_hat, name = 'Predicted', line=dict(color='red', width=1))) st.plotly_chart(fig) 77 changes: 77 additions & 0 deletions 77 Book3_Ch25_Python_Codes/Streamli...