Changing the tick frequency on x or y axis in matplotlib

Question

I am trying to fix how python plots my data   Say   x    0 5 9 10 15    and   y    0 1 2 3 4    Then I would do   matplotlib pyplot plot x y  matplotlib pyplot show     and the x axis  ticks are plotted in intervals of 5  Is there a way to make it show intervals of 1

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I like this solution  from the Matplotlib Plotting Cookbook    import matplotlib pyplot as plt import matplotlib ticker as ticker  x    0 5 9 10 15  y    0 1 2 3 4   tick spacing   1  fig  ax   plt subplots 1 1  ax plot x y  ax xaxis set major locator ticker MultipleLocator tick spacing   plt show     This solution give you explicit control of the tick spacing via the number given to ticker MultipleLocater    allows automatic limit determination  and is easy to read later

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Since None of the above solutions worked for my usecase  here I provide a solution using None  pun   which can be adapted to a wide variety of scenarios  Here is a sample piece of code that produces cluttered ticks on both X and Y axes    Note the super cluttered ticks on both X and Y axis     inputs x   np arange 1  101  y   x   np log x    fig   plt figure         create figure ax   fig add subplot 111  ax plot x  y  ax set xticks x           set xtick values ax set yticks y           set ytick values  plt show    Now  we clean up the clutter with a new plot that shows only a sparse set of values on both x and y axes as ticks    inputs x   np arange 1  101  y   x   np log x   fig   plt figure           create figure ax   fig add subplot 111  ax plot x  y   ax set xticks x  ax set yticks y     which values need to be shown    here  we show every third value from  x  and  y  show every   3  sparse xticks    None    x shape 0  sparse xticks   show every    x   show every   sparse yticks    None    y shape 0  sparse yticks   show every    y   show every   ax set xticklabels sparse xticks  fontsize 6      set sparse xtick values ax set yticklabels sparse yticks  fontsize 6      set sparse ytick values  plt show    Depending on the usecase  one can adapt the above code simply by changing show every and using that for sampling tick values for X or Y or both the axes  If this stepsize based solution doesn t fit  then one can also populate the values of sparse xticks or sparse yticks at irregular intervals  if that is what is desired

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This is an old topic  but I stumble over this every now and then and made this function  It s very convenient   import matplotlib pyplot as pp import numpy as np  def resadjust ax  xres None  yres None               Send in an axis and I fix the resolution as desired               if xres          start  stop   ax get xlim           ticks   np arange start  stop   xres  xres          ax set xticks ticks      if yres          start  stop   ax get ylim           ticks   np arange start  stop   yres  yres          ax set yticks ticks    One caveat of controlling the ticks like this is that one does no longer enjoy the interactive automagic updating of max scale after an added line  Then do  gca   set ylim top new top    for example   and run the resadjust function again

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In case anyone is interested in a general one-liner  simply get the current ticks and use it to set the new ticks by sampling every other tick   ax set xticks ax get xticks     2

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I developed an inelegant solution  Consider that we have the X axis and also a list of labels for each point in X   Example   import matplotlib pyplot as plt  x    0 1 2 3 4 5  y    10 20 15 18 7 19  xlabels     jan   feb   mar   apr   may   jun     Let s say that I want to show ticks labels only for  feb  and  jun   xlabelsnew      for i in xlabels      if i not in   feb   jun            i               xlabelsnew append i      else          xlabelsnew append i    Good  now we have a fake list of labels  First  we plotted the original version   plt plot x y  plt xticks range 0 len x   xlabels rotation 45  plt show     Now  the modified version   plt plot x y  plt xticks range 0 len x   xlabelsnew rotation 45  plt show

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This is a bit hacky  but by far the cleanest easiest to understand example that I ve found to do this  It s from an answer on SO here   Cleanest way to hide every nth tick label in matplotlib colorbar   for label in ax get xticklabels     2       label set visible False    Then you can loop over the labels setting them to visible or not depending on the density you want   edit  note that sometimes matplotlib sets labels        so it might look like a label is not present  when in fact it is and just isn t displaying anything  To make sure you re looping through actual visible labels  you could try   visible labels    lab for lab in ax get xticklabels   if lab get visible   is True and lab get text          plt setp visible labels   2   visible False

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Another approach is to set the axis locator   import matplotlib ticker as plticker  loc   plticker MultipleLocator base 1 0    this locator puts ticks at regular intervals ax xaxis set major locator loc    There are several different types of locator depending upon your needs   Here is a full example   import matplotlib pyplot as plt import matplotlib ticker as plticker  x    0 5 9 10 15  y    0 1 2 3 4  fig  ax   plt subplots   ax plot x y  loc   plticker MultipleLocator base 1 0    this locator puts ticks at regular intervals ax xaxis set major locator loc  plt show

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Pure Python Implementation  Below s a pure python implementation of the desired functionality that handles any numeric series  int or float  with positive  negative  or mixed values and allows for the user to specify the desired step size   import math  def computeTicks  x  step   5               Computes domain with given step encompassing series x       params     x    - Required - A list-like object of integers or floats     step - Optional - Tick frequency             xMax  xMin   math ceil max x    math floor min x       dMax  dMin   xMax   abs  xMax   step  - step     step if  xMax   step    0  else 0   xMin - abs  xMin   step       return range dMin  dMax  step    Sample Output    Negative to Positive series    -2  18  24  29  43  print list computeTicks series      -5  0  5  10  15  20  25  30  35  40  45     Negative to 0 series    -30  -14  -10  -9  -3  0  print list computeTicks series      -30  -25  -20  -15  -10  -5  0     0 to Positive series    19  23  24  27  print list computeTicks series      15  20  25  30     Floats series    1 8  12 0  21 2  print list computeTicks series      0  5  10  15  20  25     Step     100 series    118 3  293 2  768 1  print list computeTicks series  step   100      100  200  300  400  500  600  700  800    Sample Usage  import matplotlib pyplot as plt  x    0 5 9 10 15  y    0 1 2 3 4  plt plot x y  plt xticks computeTicks x   plt show       Notice the x-axis has integer values all evenly spaced by 5  whereas the y-axis has a different interval  the matplotlib default behavior  because the ticks weren t specified

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if you just want to set the spacing a simple one liner with minimal boilerplate   plt gca   xaxis set major locator plt MultipleLocator 1     also works easily for minor ticks   plt gca   xaxis set minor locator plt MultipleLocator 1     a bit of a mouthfull  but pretty compact

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You could explicitly set where you want to tick marks with plt xticks   plt xticks np arange min x   max x  1  1 0       For example   import numpy as np import matplotlib pyplot as plt  x    0 5 9 10 15  y    0 1 2 3 4  plt plot x y  plt xticks np arange min x   max x  1  1 0   plt show        np arange was used rather than Python s range function just in case min x  and max x  are floats instead of ints       The plt plot  or ax plot  function will automatically set default x and y limits  If you wish to keep those limits  and just change the stepsize of the tick marks  then you could use ax get xlim   to discover what limits Matplotlib has already set    start  end   ax get xlim   ax xaxis set ticks np arange start  end  stepsize     The default tick formatter should do a decent job rounding the tick values to a sensible number of significant digits  However  if you wish to have more control over the format  you can define your own formatter  For example   ax xaxis set major formatter ticker FormatStrFormatter   0 1f      Here s a runnable example   import numpy as np import matplotlib pyplot as plt import matplotlib ticker as ticker  x    0 5 9 10 15  y    0 1 2 3 4  fig  ax   plt subplots   ax plot x y  start  end   ax get xlim   ax xaxis set ticks np arange start  end  0 712123   ax xaxis set major formatter ticker FormatStrFormatter   0 1f    plt show

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xmarks  i for i in range 1 length 1 1    plt xticks xmarks    This worked for me  if you want ticks between  1 5   1 and 5 inclusive  then replace   length   5

[python] Changing the "tick frequency" on x or y axis in matplotlib?

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