Heatmap in matplotlib with pcolor

Question

I d like to make a heatmap like this  shown on FlowingData     The source data is here  but random data and labels would be fine to use  i e   import numpy column labels   list  ABCD   row labels   list  WXYZ   data   numpy random rand 4 4    Making the heatmap is easy enough in matplotlib   from matplotlib import pyplot as plt heatmap   plt pcolor data    And I even found a colormap arguments that look about right  heatmap   plt pcolor data  cmap matplotlib cm Blues   But beyond that  I can t figure out how to display labels for the columns and rows and display the data in the proper orientation  origin at the top left instead of bottom left    Attempts to manipulate heatmap axes  e g  heatmap axes set xticklabels   column labels  have all failed  What am I missing here

User · Answer

Main issue is that you first need to set the location of your x and y ticks. Also, it helps to use the more object-oriented interface to matplotlib. Namely, interact with the axes object directly.

import matplotlib.pyplot as plt
import numpy as np
column_labels = list('ABCD')
row_labels = list('WXYZ')
data = np.random.rand(4,4)
fig, ax = plt.subplots()
heatmap = ax.pcolor(data)

# put the major ticks at the middle of each cell, notice "reverse" use of dimension
ax.set_yticks(np.arange(data.shape[0])+0.5, minor=False)
ax.set_xticks(np.arange(data.shape[1])+0.5, minor=False)


ax.set_xticklabels(row_labels, minor=False)
ax.set_yticklabels(column_labels, minor=False)
plt.show()

Hope that helps.

User · Answer

The python seaborn module is based on matplotlib  and produces a very nice heatmap   Below is an implementation with seaborn  designed for the ipython jupyter notebook   import pandas as pd import matplotlib pyplot as plt import seaborn as sns  matplotlib inline   import the data directly into a pandas dataframe nba   pd read csv  http   datasets flowingdata com ppg2008 csv   index col  Name       remove index title nba index name        normalize data columns nba norm    nba - nba mean       nba max   - nba min      relabel columns labels     Games    Minutes    Points    Field goals made    Field goal attempts    Field goal percentage    Free throws made               Free throws attempts    Free throws percentage   Three-pointers made    Three-point attempt    Three-point percentage               Offensive rebounds    Defensive rebounds    Total rebounds    Assists    Steals    Blocks    Turnover    Personal foul   nba norm columns   labels   set appropriate font and dpi sns set font scale 1 2  sns set style   savefig dpi   100     plot it out ax   sns heatmap nba norm  cmap plt cm Blues  linewidths  1    set the x-axis labels on the top ax xaxis tick top     rotate the x-axis labels plt xticks rotation 90    get figure  usually obtained via  fig ax plt subplots    with matplotlib  fig   ax get figure     specify dimensions and save fig set size inches 15  20  fig savefig  nba png     The output looks like this   I used the matplotlib Blues color map  but personally find the default colors quite beautiful  I used matplotlib to rotate the x-axis labels  as I couldn t find the seaborn syntax  As noted by grexor  it was necessary to specify the dimensions  fig set size inches  by trial and error  which I found a bit frustrating   As noted by Paul H  you can easily add the values to heat maps  annot True   but in this case I didn t think it improved the figure  Several code snippets were taken from the excellent answer by joelotz

User · Answer

Someone edited this question to remove the code I used  so I was forced to add it as an answer  Thanks to all who participated in answering this question  I think most of the other answers are better than this code  I m just leaving this here for reference purposes   With thanks to Paul H  and unutbu  who answered this question   I have some pretty nice-looking output   import matplotlib pyplot as plt import numpy as np column labels   list  ABCD   row labels   list  WXYZ   data   np random rand 4 4  fig  ax   plt subplots   heatmap   ax pcolor data  cmap plt cm Blues     put the major ticks at the middle of each cell ax set xticks np arange data shape 0   0 5  minor False  ax set yticks np arange data shape 1   0 5  minor False     want a more natural  table-like display ax invert yaxis   ax xaxis tick top    ax set xticklabels row labels  minor False  ax set yticklabels column labels  minor False  plt show     And here s the output

User · Answer

This is late  but here is my python implementation of the flowingdata NBA heatmap   updated 1 4 2014  thanks everyone    - - coding  utf-8 - -    lt nbformat gt 3 0 lt  nbformat gt     ------------------------------------------------------------------------   Filename     heatmap py   Date         2013-04-19   Updated      2014-01-04   Author        LotzJoe  gt  gt  Joe Lotz   Description  My attempt at reproducing the FlowingData graphic in Python   Source       http   flowingdata com 2010 01 21 how-to-make-a-heatmap-a-quick-and-easy-solution      Other Links        http   stackoverflow com questions 14391959 heatmap-in-matplotlib-with-pcolor     ------------------------------------------------------------------------  import matplotlib pyplot as plt import pandas as pd from urllib2 import urlopen import numpy as np  pylab inline  page   urlopen  http   datasets flowingdata com ppg2008 csv   nba   pd read csv page  index col 0     Normalize data columns nba norm    nba - nba mean       nba max   - nba min       Sort data according to Points  lowest to highest   This was just a design choice made by Yau   inplace False  default  - gt thanks SO user d1337 nba sort   nba norm sort  PTS   ascending True   nba sort  PTS   head 10     Plot it out fig  ax   plt subplots   heatmap   ax pcolor nba sort  cmap plt cm Blues  alpha 0 8     Format fig   plt gcf   fig set size inches 8  11     turn off the frame ax set frame on False     put the major ticks at the middle of each cell ax set yticks np arange nba sort shape 0     0 5  minor False  ax set xticks np arange nba sort shape 1     0 5  minor False     want a more natural  table-like display ax invert yaxis   ax xaxis tick top      Set the labels    label source https   en wikipedia org wiki Basketball statistics labels          Games    Minutes    Points    Field goals made    Field goal attempts    Field goal percentage    Free throws made    Free throws attempts    Free throws percentage        Three-pointers made    Three-point attempt    Three-point percentage    Offensive rebounds    Defensive rebounds    Total rebounds    Assists    Steals    Blocks    Turnover    Personal foul      note I could have used nba sort columns but made  labels  instead ax set xticklabels labels  minor False  ax set yticklabels nba sort index  minor False     rotate the plt xticks rotation 90   ax grid False     Turn off all the ticks ax   plt gca    for t in ax xaxis get major ticks        t tick1On   False     t tick2On   False for t in ax yaxis get major ticks        t tick1On   False     t tick2On   False   The output looks like this    There s an ipython notebook with all this code here  I ve learned a lot from  overflow so hopefully someone will find this useful

[python] Heatmap in matplotlib with pcolor?

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