Pandas: How to reference and print multiple dataframes as HTML tables
<p>I'm trying split out individual dataframes from a <code>groupby</code> to print them as pandas HTML tables. I need to reference and render them individually as tables so I can screenshot them for a presentation.</p>

<p>This is my current code: </p>

<pre><code>import pandas as pd

df = pd.DataFrame(
    {'area': [5, 42, 20, 20, 43, 78, 89, 30, 46, 78],
     'cost': [52300, 52000, 25000, 61600, 43000, 23400, 52300, 62000, 62000, 73000], 
     'grade': [1, 3, 2, 1, 2, 2, 2, 4, 1, 2], 'size': [1045, 957, 1099, 1400, 1592, 1006, 987, 849, 973, 1005], 
     'team': ['man utd', 'chelsea', 'arsenal', 'man utd', 'man utd', 'arsenal', 'man utd', 'chelsea', 'arsenal', 'arsenal']})

result =  df.groupby(['team', 'grade']).agg({'cost':'mean', 'area':'mean', 'size':'sum'}).rename(columns={'cost':'mean_cost', 'area':'mean_area'})

dfs = {team:grp.drop('team', axis=1) 
       for team, grp in result.reset_index().groupby('team')}

for team, grp in dfs.items():
    print('{}:\n{}\n'.format(team, gap))
</code></pre>

<p>Which prints (as non HTML tables):</p>

<pre><code>chelsea:
   grade  mean_cost  mean_area  size
2      3      52000         42   957
3      4      62000         30   849

arsenal:
   grade     mean_cost  mean_area  size
0      1  62000.000000  46.000000   973
1      2  40466.666667  58.666667  3110

man utd:
   grade  mean_cost  mean_area  size
4      1      56950       12.5  2445
5      2      47650       66.0  2579
</code></pre>

<p>Is it possible to get these dataframes one by one as HTML tables? For the avoidance of doubt, I don't need an iterative method to return them all as HTML tables in one go - am happy to reference each one individually. </p>