python plot normal distribution

Question

Given a mean and a variance is there a simple function call which will plot a normal distribution

User · Answer

I have just come back to this and I had to install scipy as matplotlib mlab gave me the error message MatplotlibDeprecationWarning  scipy stats norm pdf when trying example above   So the sample is now    matplotlib inline import math import matplotlib pyplot as plt import numpy as np import scipy stats   mu   0 variance   1 sigma   math sqrt variance  x   np linspace mu - 3 sigma  mu   3 sigma  100  plt plot x  scipy stats norm pdf x  mu  sigma    plt show

User · Answer

you can get cdf easily  so pdf via cdf      import numpy as np     import matplotlib pyplot as plt     import scipy interpolate     import scipy stats      def setGridLine ax            http   jonathansoma com lede data-studio matplotlib adding-grid-lines-to-a-matplotlib-chart          ax set axisbelow True          ax minorticks on           ax grid which  major   linestyle  -   linewidth 0 5  color  grey           ax grid which  minor   linestyle      linewidth 0 5  color   a6a6a6           ax tick params which  both     Options for both major and minor ticks                         top False    turn off top ticks                         left False    turn off left ticks                         right False     turn off right ticks                         bottom False    turn off bottom ticks      data1   np random normal 0 1 1000000      x np sort data1      y np arange x shape 0    x shape 0  1       f2   scipy interpolate interp1d x  y kind  linear       x2   np linspace x 0  x -1  1001      y2   f2 x2       y2b   np diff y2  np diff x2      x2b  x2 1   x2  -1   2       f3   scipy interpolate interp1d x  y kind  cubic       x3   np linspace x 0  x -1  1001      y3   f3 x3       y3b   np diff y3  np diff x3      x3b  x3 1   x3  -1   2       bins np arange -4 4 0 1      bins centers 0 5  bins 1   bins  -1       cdf   scipy stats norm cdf bins centers      pdf   scipy stats norm pdf bins centers       plt rcParams  font size     18     fig  ax   plt subplots 3 1 figsize  10 16       ax 0  set title  cdf       ax 0  plot x y label  data       ax 0  plot x2 y2 label  linear       ax 0  plot x3 y3 label  cubic       ax 0  plot bins centers cdf label  ans        ax 1  set title  pdf linear       ax 1  plot x2b y2b label  linear       ax 1  plot bins centers pdf label  ans        ax 2  set title  pdf cubic       ax 2  plot x3b y3b label  cubic       ax 2  plot bins centers pdf label  ans        for idx in range 3           ax idx  legend           setGridLine ax idx        plt show       plt clf       plt close

User · Answer

Unutbu answer is correct  But because our mean can be more or less than zero I would still like to change this    x   np linspace -3   sigma  3   sigma  100    to this    x   np linspace -3   sigma   mean  3   sigma   mean  100

User · Answer

I don t think there is a function that does all that in a single call  However you can find the Gaussian probability density function in scipy stats   So the simplest way I could come up with is   import numpy as np import matplotlib pyplot as plt from scipy stats import norm    Plot between -10 and 10 with  001 steps  x axis   np arange -10  10  0 001    Mean   0  SD   2  plt plot x axis  norm pdf x axis 0 2   plt show     Sources    http   www johndcook com distributions scipy html http   docs scipy org doc scipy reference stats html http   telliott99 blogspot com 2010 02 plotting-normal-distribution-with html

User · Answer

import matplotlib pyplot as plt import numpy as np import scipy stats as stats import math  mu   0 variance   1 sigma   math sqrt variance  x   np linspace mu - 3 sigma  mu   3 sigma  100  plt plot x  stats norm pdf x  mu  sigma   plt show

User · Answer

If you prefer to use a step by step approach you could consider a solution like follows  import numpy as np import matplotlib pyplot as plt  mean   0  std   1  variance   np square std  x   np arange -5 5  01  f   np exp -np square x-mean  2 variance   np sqrt 2 np pi variance    plt plot x f  plt ylabel  gaussian distribution   plt show

User · Answer

I believe that is important to set the height  so created this function   def my gauss x  sigma 1  h 1  mid 0       from math import exp  pow     variance   pow sdev  2      return h   exp -pow x-mid  2   2 variance     Where sigma is the standard deviation  h is the height and mid is the mean   Here is the result using different heights and deviations

User · Answer

Use seaborn instead  i am using distplot of seaborn with mean 5 std 3 of 1000 values  value   np random normal loc 5 scale 3 size 1000  sns distplot value    You will get a normal distribution curve

User · Answer

import math   import matplotlib pyplot as plt import numpy import pandas as pd   def normal pdf x  mu 0  sigma 1       sqrt two pi   math sqrt math pi   2      return math exp - x - mu     2   2   sigma    2     sqrt two pi   sigma    df   pd DataFrame   x1   numpy arange -10  10  0 1    y1   map normal pdf  numpy arange -10  10  0 1      plt plot  x1    y1   data df  marker  o   markerfacecolor  blue   markersize 5  color  skyblue   linewidth 1  plt show

[python] python plot normal distribution

Examples related to python

Examples related to matplotlib