How to create a density plot in matplotlib

Question

In R I can create the desired output by doing    data   c rep 1 5  7   rep 2 5  2   rep 3 5  8            rep 4 5  3   rep 5 5  1   rep 6 5  8   plot density data  bw 0 5       In python  with matplotlib  the closest I got was with a simple histogram   import matplotlib pyplot as plt data    1 5  7    2 5  2    3 5  8    4 5  3    5 5  1    6 5  8 plt hist data  bins 6  plt show       I also tried the normed True parameter but couldn t get anything other than trying to fit a gaussian to the histogram   My latest attempts were around scipy stats and gaussian kde  following examples on the web  but I ve been unsuccessful so far

User · Answer

Option 1   Use pandas dataframe plot  built on top of matplotlib     import pandas as pd data    1 5  7    2 5  2    3 5  8    4 5  3    5 5  1    6 5  8 pd DataFrame data  plot kind  density     or pd Series       Option 2   Use distplot of seaborn   import seaborn as sns data    1 5  7    2 5  2    3 5  8    4 5  3    5 5  1    6 5  8 sns distplot data  hist False

User · Answer

The density plot can also be created by using matplotlib  The function plt hist data  returns the y and x values necessary for the density plot  see the documentation https   matplotlib org 3 1 1 api  as gen matplotlib pyplot hist html   Resultingly  the following code creates a density plot by using the matplotlib library   import matplotlib pyplot as plt dat  -1 2 1 4 -5 3 6 1 2 1 2 5 6 5 6 2 2 2  a plt hist dat density True  plt close   plt figure   plt plot a 1  1   a 0           This code returns the following density plot

User · Answer

Maybe try something like   import matplotlib pyplot as plt import numpy from scipy import stats data    1 5  7    2 5  2    3 5  8    4 5  3    5 5  1    6 5  8 density   stats kde gaussian kde data  x   numpy arange 0   8   1  plt plot x  density x   plt show     You can easily replace gaussian kde   by a different kernel density estimate

User · Answer

Sven has shown how to use the class gaussian kde from Scipy  but you will notice that it doesn t look quite like what you generated with R  This is because gaussian kde tries to infer the bandwidth automatically  You can play with the bandwidth in a way by changing the function covariance factor of the gaussian kde class  First  here is what you get without changing that function     However  if I use the following code   import matplotlib pyplot as plt import numpy as np from scipy stats import gaussian kde data    1 5  7    2 5  2    3 5  8    4 5  3    5 5  1    6 5  8 density   gaussian kde data  xs   np linspace 0 8 200  density covariance factor   lambda    25 density  compute covariance   plt plot xs density xs   plt show     I get    which is pretty close to what you are getting from R  What have I done  gaussian kde uses a changable function  covariance factor to calculate its bandwidth  Before changing the function  the value returned by covariance factor for this data was about  5  Lowering this lowered the bandwidth  I had to call  compute covariance after changing that function so that all of the factors would be calculated correctly  It isn t an exact correspondence with the bw parameter from R  but hopefully it helps you get in the right direction

User · Answer

Five years later  when I Google  how to create a kernel density plot using python   this thread still shows up at the top    Today  a much easier way to do this is to use seaborn  a package that provides many convenient plotting functions and good style management   import numpy as np import seaborn as sns data    1 5  7    2 5  2    3 5  8    4 5  3    5 5  1    6 5  8 sns set style  whitegrid   sns kdeplot np array data   bw 0 5

User · Answer

You can do something like  s   np random normal 2  3  1000  import matplotlib pyplot as plt count  bins  ignored   plt hist s  30  density True  plt plot bins  1  3   np sqrt 2   np pi     np exp  -  bins - 2   2    2   3  2      linewidth 2  color  r   plt show

[python] How to create a density plot in matplotlib?

Examples related to python

Examples related to r

Examples related to numpy

Examples related to matplotlib

Examples related to scipy