How to overplot a line on a scatter plot in python

Question

I have two vectors of data and I ve put them into matplotlib scatter    Now I d like to over plot a linear fit to these data  How would I do this  I ve tried using scikitlearn and np scatter

User · Answer

plt plot X plot  X plot results params 0    results params 1     versus  plt plot X plot  X plot results params 1    results params 0

User · Answer

I m partial to scikits statsmodels   Here an example   import statsmodels api as sm import numpy as np import matplotlib pyplot as plt  X   np random rand 100  Y   X   np random rand 100  0 1  results   sm OLS Y sm add constant X   fit    print results summary    plt scatter X Y   X plot   np linspace 0 1 100  plt plot X plot  X plot results params 0    results params 1    plt show     The only tricky part is sm add constant X  which adds a columns of ones to X in order to get an intercept term        Summary of Regression Results                                           Dependent Variable               y      Model                            OLS    Method                 Least Squares    Date                Sat  28 Sep 2013    Time                        09 22 59      obs                          100 0    Df residuals                    98 0    Df model                         1 0                                                                                                     coefficient     std  error    t-statistic          prob    ------------------------------------------------------------------------------   x1                      1 007       0 008466       118 9032         0 0000     const                 0 05165       0 005138        10 0515         0 0000                                                                                                             Models stats                      Residual stats    ------------------------------------------------------------------------------   R-squared                      0 9931   Durbin-Watson               1 484      Adjusted R-squared             0 9930   Omnibus                     12 16      F-statistic                 1 414e 04   Prob Omnibus             0 002294      Prob  F-statistic          9 137e-108   JB                         0 6818      Log likelihood                  223 8   Prob JB                    0 7111      AIC criterion                  -443 7   Skew                      -0 2064      BIC criterion                  -438 5   Kurtosis                    2 048    ------------------------------------------------------------------------------

User · Answer

Another way to do it  using axes get xlim     import matplotlib pyplot as plt import numpy as np  def scatter plot with correlation line x  y  graph filepath               http   stackoverflow com a 34571821 395857     x does not have to be ordered                Create scatter plot     plt scatter x  y         Add correlation line     axes   plt gca       m  b   np polyfit x  y  1      X plot   np linspace axes get xlim   0  axes get xlim   1  100      plt plot X plot  m X plot   b   -          Save figure     plt savefig graph filepath  dpi 300  format  png   bbox inches  tight    def main          Data     x   np random rand 100      y   x   np random rand 100  0 1        Plot     scatter plot with correlation line x  y   scatter plot png    if   name         main         main        cProfile run  main       if you want to do some profiling

User · Answer

I like Seaborn s regplot or lmplot for this

User · Answer

You can use this tutorial by Adarsh Menon https   towardsdatascience com linear-regression-in-6-lines-of-python-5e1d0cd05b8d   This way is the easiest I found and it basically looks like   import numpy as np import matplotlib pyplot as plt    To visualize import pandas as pd    To read data from sklearn linear model import LinearRegression data   pd read csv  data csv      load data set X   data iloc    0  values reshape -1  1     values converts it into a numpy array Y   data iloc    1  values reshape -1  1     -1 means that calculate the dimension of rows  but have 1 column linear regressor   LinearRegression      create object for the class linear regressor fit X  Y     perform linear regression Y pred   linear regressor predict X     make predictions plt scatter X  Y  plt plot X  Y pred  color  red   plt show

User · Answer

A one-line version of this excellent answer to plot the line of best fit is   plt plot np unique x   np poly1d np polyfit x  y  1   np unique x      Using np unique x  instead of x handles the case where x isn t sorted or has duplicate values   The call to poly1d is an alternative to writing out m x   b like in this other excellent answer

User · Answer

import numpy as np from numpy polynomial polynomial import polyfit import matplotlib pyplot as plt    Sample data x   np arange 10  y   5   x   10    Fit with polyfit b  m   polyfit x  y  1   plt plot x  y       plt plot x  b   m   x   -   plt show

[python] How to overplot a line on a scatter plot in python?

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