Fitting a Normal distribution to 1D data

Question

I have a 1 dimensional array  I can compute the  mean  and  standard deviation  of this sample and plot the  Normal distribution  but I have a problem   I want to plot the data and Normal distribution in the same figure   I dont know how to plot both the data and the normal distribution   Any Idea about  Gaussian probability density function in scipy stats    s   np std array  m   np mean array  plt plot norm pdf array m s

User · Answer

To see both the normal distribution and your actual data you should plot your data as a histogram  then draw the probability density function over this  See the example on https   docs scipy org doc numpy-1 15 0 reference generated numpy random normal html for exactly how to do this

User · Answer

There is a much simpler way to do it using seaborn   import seaborn as sns from scipy stats import norm  data   norm rvs 5 0 4 size 1000    you can use a pandas series or a list if you want  sns distplot data  plt show     output     for more information seaborn distplot

User · Answer

You can use matplotlib to plot the histogram and the PDF  as in the link in  MrE s answer    For fitting and for computing the PDF  you can use scipy stats norm  as follows   import numpy as np from scipy stats import norm import matplotlib pyplot as plt     Generate some data for this demonstration  data   norm rvs 10 0  2 5  size 500     Fit a normal distribution to the data  mu  std   norm fit data     Plot the histogram  plt hist data  bins 25  density True  alpha 0 6  color  g      Plot the PDF  xmin  xmax   plt xlim   x   np linspace xmin  xmax  100  p   norm pdf x  mu  std  plt plot x  p   k   linewidth 2  title    Fit results  mu     2f   std     2f     mu  std  plt title title   plt show     Here s the plot generated by the script

User · Answer

Here you are not fitting a normal distribution  Replacing sns distplot data  by sns distplot data  fit norm  kde False  should do the trick

[python] Fitting a Normal distribution to 1D data

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