Bin size in Matplotlib Histogram

Question

I m using matplotlib to make a histogram   Is there any way to manually set the size of the bins as opposed to the number of bins

User · Answer

I use quantiles to do bins uniform and fitted to sample:

bins=df['Generosity'].quantile([0,.05,0.1,0.15,0.20,0.25,0.3,0.35,0.40,0.45,0.5,0.55,0.6,0.65,0.70,0.75,0.80,0.85,0.90,0.95,1]).to_list()

plt.hist(df['Generosity'], bins=bins, normed=True, alpha=0.5, histtype='stepfilled', color='steelblue', edgecolor='none')

User · Answer

For N bins  the bin edges are specified by list of N 1 values where the first N give the lower bin edges and the  1 gives the upper edge of the last bin   Code   from numpy import np  from pylab import    bin size   0 1  min edge   0  max edge   2 5 N    max edge-min edge  bin size  Nplus1   N   1 bin list   np linspace min edge  max edge  Nplus1    Note that linspace produces array from min edge to max edge broken into N 1 values or N bins

User · Answer

I guess the easy way would be to calculate the minimum and maximum of the data you have   then   calculate L   max - min   Then you divide L by the desired bin width  I m assuming this is what you mean by bin size  and use the ceiling of this value as the number of bins

User · Answer

For a histogram with integer x-values I ended up using  plt hist data  np arange min data -0 5  max data  0 5   plt xticks range min data   max data      The offset of 0 5 centers the bins on the x-axis values  The plt xticks call adds a tick for every integer

User · Answer

This answer support the   macrocosme suggestion   I am using heat map as hist2d plot  Additionally I use cmin 0 5 for no count value and cmap for color  r represent the reverse of given color  Describe statistics     np arange data min    data max   binwidth  binwidth  bin x   np arange 0 6  7   0 3  0 3  bin y   np arange 12  58   3  3  plt hist2d data fuel econ  x  displ   y  comb   cmin 0 5  cmap  viridis r   bins  bin x  bin y    plt xlabel  Dispalcement  1     plt ylabel  Combine fuel efficiency  mpg      plt colorbar

User · Answer

I had the same issue as OP  I think    but I couldn t get it to work in the way that Lastalda specified  I don t know if I have interpreted the question properly  but I have found another solution  it probably is a really bad way of doing it though     This was the way that I did it    plt hist  1 11 21 31 41   bins  0 10 20 30 40 50   weights  10 1 40 33 6     Which creates this     So the first parameter basically  initialises  the bin - I m specifically creating a number that is in between the range I set in the bins parameter   To demonstrate this  look at the array in the first parameter   1 11 21 31 41   and the  bins  array in the second parameter   0 10 20 30 40 50      The number 1  from the first array  falls between 0 and 10  in the  bins  array  The number 11  from the first array  falls between 11 and 20  in the  bins  array  The number 21  from the first array  falls between 21 and 30  in the  bins  array   etc    Then I m using the  weights  parameter to define the size of each bin  This is the array used for the weights parameter   10 1 40 33 6    So the 0 to 10 bin is given the value 10  the 11 to 20 bin is given the value of 1  the 21 to 30 bin is given the value of 40  etc

User · Answer

Actually  it s quite easy  instead of the number of bins you can give a list with the bin boundaries  They can be unequally distributed  too   plt hist data  bins  0  10  20  30  40  50  100     If you just want them equally distributed  you can simply use range   plt hist data  bins range min data   max data    binwidth  binwidth       Added to original answer  The above line works for data filled with integers only  As macrocosme points out  for floats you can use   import numpy as np plt hist data  bins np arange min data   max data    binwidth  binwidth

User · Answer

I like things to happen automatically and for bins to fall on  nice  values  The following seems to work quite well   import numpy as np import numpy random as random import matplotlib pyplot as plt def compute histogram bins data  desired bin size       min val   np min data      max val   np max data      min boundary   -1 0    min val   desired bin size - min val      max boundary   max val - max val   desired bin size   desired bin size     n bins   int  max boundary - min boundary    desired bin size    1     bins   np linspace min boundary  max boundary  n bins      return bins  if   name         main         data   np random random sample 100    123 34 - 67 23     bins   compute histogram bins data  10 0      print bins      plt hist data  bins bins      plt xlabel  Value       plt ylabel  Counts       plt title  Compute Bins Example       plt grid True      plt show     The result has bins on nice intervals of bin size    -70  -60  -50  -40  -30  -20  -10    0   10   20   30   40   50   60

[python] Bin size in Matplotlib (Histogram)

Examples related to python

Examples related to matplotlib

Examples related to histogram