How to save a pandas DataFrame table as a png

Question

I constructed a pandas dataframe of results  This data frame acts as a table  There are MultiIndexed columns and each row represents a name  ie index   name1   name2       when creating the DataFrame  I would like to display this table and save it as a png  or any graphic format really   At the moment  the closest I can get is converting it to html  but I would like a png  It looks like similar questions have been asked such as How to save the Pandas dataframe series data as a figure   However  the marked solution converts the dataframe into a line plot  not a table  and the other solution relies on PySide which I would like to stay away simply because I cannot pip install it on linux  I would like this code to be easily portable  I really was expecting table creation to png to be easy with python  All help is appreciated

User · Accepted Answer

Pandas allows you to plot tables using matplotlib (details here). Usually this plots the table directly onto a plot (with axes and everything) which is not what you want. However, these can be removed first:

import matplotlib.pyplot as plt
import pandas as pd
from pandas.table.plotting import table # EDIT: see deprecation warnings below

ax = plt.subplot(111, frame_on=False) # no visible frame
ax.xaxis.set_visible(False)  # hide the x axis
ax.yaxis.set_visible(False)  # hide the y axis

table(ax, df)  # where df is your data frame

plt.savefig('mytable.png')

The output might not be the prettiest but you can find additional arguments for the table() function here. Also thanks to this post for info on how to remove axes in matplotlib.

EDIT:

Here is a (admittedly quite hacky) way of simulating multi-indexes when plotting using the method above. If you have a multi-index data frame called df that looks like:

first  second
bar    one       1.991802
       two       0.403415
baz    one      -1.024986
       two      -0.522366
foo    one       0.350297
       two      -0.444106
qux    one      -0.472536
       two       0.999393
dtype: float64

First reset the indexes so they become normal columns

df = df.reset_index() 
df
    first second       0
0   bar    one  1.991802
1   bar    two  0.403415
2   baz    one -1.024986
3   baz    two -0.522366
4   foo    one  0.350297
5   foo    two -0.444106
6   qux    one -0.472536
7   qux    two  0.999393

Remove all duplicates from the higher order multi-index columns by setting them to an empty string (in my example I only have duplicate indexes in "first"):

df.ix[df.duplicated('first') , 'first'] = '' # see deprecation warnings below
df
  first second         0
0   bar    one  1.991802
1          two  0.403415
2   baz    one -1.024986
3          two -0.522366
4   foo    one  0.350297
5          two -0.444106
6   qux    one -0.472536
7          two  0.999393

Change the column names over your "indexes" to the empty string

new_cols = df.columns.values
new_cols[:2] = '',''  # since my index columns are the two left-most on the table
df.columns = new_cols

Now call the table function but set all the row labels in the table to the empty string (this makes sure the actual indexes of your plot are not displayed):

table(ax, df, rowLabels=['']*df.shape[0], loc='center')

et voila:

Your not-so-pretty but totally functional multi-indexed table.

EDIT: DEPRECATION WARNINGS

As pointed out in the comments, the import statement for table:

from pandas.tools.plotting import table

is now deprecated in newer versions of pandas in favour of:

from pandas.plotting import table

EDIT: DEPRECATION WARNINGS 2

The ix indexer has now been fully deprecated so we should use the loc indexer instead. Replace:

df.ix[df.duplicated('first') , 'first'] = ''

with

df.loc[df.duplicated('first') , 'first'] = ''

User · Answer

If you re okay with the formatting as it appears when you call the DataFrame in your coding environment  then the absolute easiest way is to just use print screen and crop the image using basic image editing software    Here s how it turned out for me using Jupyter Notebook  and Pinta Image Editor  Ubuntu freeware

User · Answer

Although I am not sure if this is the result you expect  you can save your DataFrame in png by plotting the DataFrame with Seaborn Heatmap with annotations on  like this   http   stanford edu  mwaskom software seaborn generated seaborn heatmap html seaborn heatmap    It works right away with a Pandas Dataframe  You can look at this example  Efficiently ploting a table in csv format using Python  You might want to change the colormap so it displays a white background only   Hope this helps

User · Answer

The solution of  bunji works for me  but default options don t always give a good result  I added some useful parameter to tweak the appearance of the table   import pandas as pd import matplotlib pyplot as plt from pandas tools plotting import table import numpy as np  dates   pd date range  20130101  periods 6  df   pd DataFrame np random randn 6 4  index dates columns list  ABCD     df index    item strftime   Y- m- d   for item in df index    Format date  fig  ax   plt subplots figsize  12  2     set size frame ax xaxis set visible False     hide the x axis ax yaxis set visible False     hide the y axis ax set frame on False     no visible frame  uncomment if size is ok tabla   table ax  df  loc  upper right   colWidths  0 17  len df columns      where df is your data frame tabla auto set font size False    Activate set fontsize manually tabla set fontsize 12    if   fontsize is necessary   colWidths tabla scale 1 2  1 2    change size table plt savefig  table png   transparent True    The result

User · Answer

The best solution to your problem is probably to first export your dataframe to HTML and then convert it using an HTML-to-image tool  The final appearance could be tweaked via CSS   Popular options for HTML-to-image rendering include    WeasyPrint wkhtmltopdf wkhtmltoimage     Let us assume we have a dataframe named df  We can generate one with the following code   import string import numpy as np import pandas as pd   np random seed 0     just to get reproducible results from  np random  rows  cols   5  10 labels   list string ascii uppercase  cols   df   pd DataFrame np random randint 0  100  size  5  10    columns labels  print df        A   B   C   D   E   F   G   H   I   J   0  44  47  64  67  67   9  83  21  36  87   1  70  88  88  12  58  65  39  87  46  88   2  81  37  25  77  72   9  20  80  69  79   3  47  64  82  99  88  49  29  19  19  14   4  39  32  65   9  57  32  31  74  23  35     Using WeasyPrint  This approach uses a pip-installable package  which will allow you to do everything using the Python ecosystem  One shortcoming of weasyprint is that it does not seem to provide a way of adapting the image size to its content  Anyway  removing some background from an image is relatively easy in Python   PIL  and it is implemented in the trim   function below  adapted from here   One also would need to make sure that the image will be large enough  and this can be done with CSS s  page size property   The code follows   import weasyprint as wsp import PIL as pil   def trim source filepath  target filepath None  background None       if not target filepath          target filepath   source filepath     img   pil Image open source filepath      if background is None          background   img getpixel  0  0       border   pil Image new img mode  img size  background      diff   pil ImageChops difference img  border      bbox   diff getbbox       img   img crop bbox  if bbox else img     img save target filepath    img filepath    table1 png  css   wsp CSS string      page   size  2048px 2048px  padding  0px  margin  0px    table  td  tr  th   border  1px solid black    td  th   padding  4px 8px         html   wsp HTML string df to html    html write png img filepath  stylesheets  css   trim img filepath        Using wkhtmltopdf wkhtmltoimage  This approach uses an external open source tool and this needs to be installed prior to the generation of the image  There is also a Python package  pdfkit  that serves as a front-end to it  it does not waive you from installing the core software yourself   but I will not use it   wkhtmltoimage can be simply called using subprocess  or any other similar means of running an external program in Python   One would also need to output to disk the HTML file   The code follows   import subprocess   df to html  table2 html   subprocess call       wkhtmltoimage -f png --width 0 table2 html table2 png   shell True      and its aspect could be further tweaked with CSS similarly to the other approach

User · Answer

There is actually a python library called dataframe image Just do a pip install dataframe image  Do the imports import pandas as pd import numpy as np import dataframe image as dfi df   pd DataFrame np random randn 6  6   columns list  ABCDEF     and style your table if you want by  df styled   df style background gradient    adding a gradient based on values in cell  and finally  dfi export df styled  quot mytable png quot

User · Answer

I had the same requirement for a project I am doing  But none of the answers came elegant to my requirement  Here is something which finally helped me  and might be useful for this case   from bokeh io import export png  export svgs from bokeh models import ColumnDataSource  DataTable  TableColumn  def save df as image df  path       source   ColumnDataSource df      df columns    df index name      df columns extend df columns values      columns for table        for column in df columns          columns for table append TableColumn field column  title column        data table   DataTable source source  columns columns for table height policy  auto  width policy  auto  index position None      export png data table  filename   path

User · Answer

As jcdoming suggested  use Seaborn heatmap     import seaborn as sns import matplotlib pyplot as plt  fig   plt figure facecolor  w   edgecolor  k   sns heatmap df head    annot True  cmap  viridis   cbar False  plt savefig  DataFrame png

User · Answer

The following would need extensive customisation to format the table correctly  but the bones of it works   import numpy as np from PIL import Image  ImageDraw  ImageFont import pandas as pd  df   pd DataFrame    A    1                         B    pd Series 1 index list range 4   dtype  float32                          C    np array  3    4 dtype  int32                          D    pd Categorical   test   train   test   train                           E     foo       class DrawTable        def   init   self  df           self rows self cols    df shape         img size    300 200          self border   50         self bg col    255 255 255          self div w   1         self div col    128 128 128          self head w   2         self head col    0 0 0          self image   Image new  RGBA   img size self bg col          self draw   ImageDraw Draw self image          self draw grid           self populate  df          self image show       def draw grid self           width height   self image size         row step    height-self border 2   self rows          col step    width-self border 2   self cols          for row in range 1 self rows 1               self draw line  self border-row step  2 self border row step row width-self border self border row step row  fill self div col width self div w              for col in range 1 self cols 1                   self draw line  self border col step col self border-col step  2 self border col step col height-self border  fill self div col width self div w          self draw line  self border-row step  2 self border width-self border self border  fill self head col width self head w          self draw line  self border self border-col step  2 self border height-self border  fill self head col width self head w          self row step   row step         self col step   col step     def populate self  df2           font   ImageFont load default   font         for row in range self rows               print  df2 iloc row 0               self draw text  self border-self row step  2 self border self row step row  str  df2 index row   font font fill  0 0 128               for col in range self cols                   text   str  df2 iloc row col                   text w  text h   font getsize text                  x pos   self border self col step  col 1 -text w                 y pos   self border self row step row                 self draw text  x pos y pos  text font font fill  0 0 128           for col in range self cols               text   str  df2 columns col               text w  text h   font getsize text              x pos   self border self col step  col 1 -text w             y pos   self border - self row step  2             self draw text  x pos y pos  text font font fill  0 0 128       def save self filename           try              self image save filename mode  RGBA               print filename   Saved            except              print  Error saving   filename      table1   DrawTable df  table1 save  C  Users user Pictures table1 png     The output looks like this

User · Answer

The easiest and fastest way to convert a Pandas dataframe into a png image using Anaconda Spyder IDE- just double-click on the dataframe in variable explorer  and the IDE table will appear  nicely packaged with automatic formatting and color scheme  Just use a snipping tool to capture the table for use in your reports  saved as a png     This saves me lots of time  and is still elegant and professional

[python] How to save a pandas DataFrame table as a png

EDIT:

EDIT: DEPRECATION WARNINGS

EDIT: DEPRECATION WARNINGS 2

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