title: How to apend a row in a pandas dataframe containing column's sum
body: <p>Here is how my dataframe looks like</p>
  <pre><code>0   M   M   W   B   k   a   D   G   247.719248  39.935064   12.983612   177.537373  214.337385  70.248041   78.162404   215.383443
  1   n   a   Y   j   A   N   Q   m   39.014265   64.053771   13.677425   169.164911  153.225780  31.095511   198.805600  179.653853
  2   j   z   v   I   n   N   I   X   152.177940  50.524997   79.063318   181.993409  51.367824   19.294708   217.844628  166.896151
  3   n   w   a   Y   G   B   y   O   243.468930  92.694170   200.305038  249.760627  156.588164  200.031428  146.933709  202.202242
  4   R   i   h   L   J   a   q   S   122.006004  34.979958   151.963992  116.795194  74.713682   252.979874  34.272430   45.334396
  5   m   Y   n   r   u   t   t   b   86.097651   229.911157  75.242197   214.069558  246.390175  235.507510  125.431980  90.467756
  6   d   i   u   d   f   Q   a   q   135.740363  13.388095   107.297373  10.520204   118.578496  101.770257  177.253815  78.800327
  7   n   F   A   x   H   u   b   y   55.497867   210.402998  191.356683  6.438180    85.967328   64.461602   157.265270  213.673103
  8   q   h   w   i   S   B   h   i   253.696469  168.964278  31.592088   160.404929  241.434909  232.280512  116.353252  11.540209
  9   a   z   s   d   Y   z   l   B   50.440346   80.492069   64.991017   88.663195   155.993675  85.967207   120.467390  71.219658
  10  A   U   W   m   y   R   k   K   156.153985  15.862058   95.013242   48.339397   235.440190  160.565380  236.421396  59.981690
  11  z   K   K   w   o   c   n   l   56.310181   210.101571  173.887020  181.040997  193.653296  250.875304  81.096499   234.868844
  </code></pre>
  <p>I want to append a row which will contain the sum of the column but it also contain string values.</p>
  <p>I have tried this solution</p>
  <pre><code>df.loc['Total'] = df.select_dtypes(include=['float64', 'int64']).sum(axis=0)
  </code></pre>
  <p>But I am getting the sum in the string column as well like this</p>
  <pre><code>0   M   M   W   B   k   a   D   G   247.719248  39.935064   12.983612   177.537373  214.337385  70.248041   78.162404   215.383443
  1   n   a   Y   j   A   N   Q   m   39.014265   64.053771   13.677425   169.164911  153.225780  31.095511   198.805600  179.653853
  2   j   z   v   I   n   N   I   X   152.177940  50.524997   79.063318   181.993409  51.367824   19.294708   217.844628  166.896151
  3   n   w   a   Y   G   B   y   O   243.468930  92.694170   200.305038  249.760627  156.588164  200.031428  146.933709  202.202242
  4   R   i   h   L   J   a   q   S   122.006004  34.979958   151.963992  116.795194  74.713682   252.979874  34.272430   45.334396
  5   m   Y   n   r   u   t   t   b   86.097651   229.911157  75.242197   214.069558  246.390175  235.507510  125.431980  90.467756
  6   d   i   u   d   f   Q   a   q   135.740363  13.388095   107.297373  10.520204   118.578496  101.770257  177.253815  78.800327
  7   n   F   A   x   H   u   b   y   55.497867   210.402998  191.356683  6.438180    85.967328   64.461602   157.265270  213.673103
  8   q   h   w   i   S   B   h   i   253.696469  168.964278  31.592088   160.404929  241.434909  232.280512  116.353252  11.540209
  9   a   z   s   d   Y   z   l   B   50.440346   80.492069   64.991017   88.663195   155.993675  85.967207   120.467390  71.219658
  10  A   U   W   m   y   R   k   K   156.153985  15.862058   95.013242   48.339397   235.440190  160.565380  236.421396  59.981690
  11  z   K   K   w   o   c   n   l   56.310181   210.101571  173.887020  181.040997  193.653296  250.875304  81.096499   234.868844
  Total   1598.32 1211.31 1197.37 1604.73 1927.69 1705.08 1690.31 1570.02 1598.323248 1211.310187 1197.373003 1604.727974 1927.690905 1705.077334 1690.308374 1570.021673
  </code></pre>
  <p>Can i keep some value for the string sum? How it should be done?</p>
  <p>Any help would be appreciated. I am newbie to pandas</p>