How can I convert a Python dictionary to an HTML table?

Question

I have this Python dictionary as output.

{'Job1': {'2017-01-10': [44, 33, 11, 75, 22]},
'Job 2': {'2017-01-05': [25, 25, 0, 100, 25], '2017-01-10': [50, 50, 0, 100, 25]},
'Job 3': {'2017-01-03': [44, 22, 22, 50, 22], '2017-01-04': [66, 36, 30, 54, 22], '2017-01-06': [88, 52, 36, 59, 22], '2017-01-10': [132, 68, 64, 51, 22], '2017-01-02': [22, 9, 13, 40, 22], '2017-01-08': [110, 52, 58, 47, 22]},
 'Job4': {'2017-01-10': [25, 25, 0, 100, 25]}}

where the date is a dynamic list like.

And I have a static job list.

How could I transform this dict like the below picture?

PS - the captured first element from the date dictionary.

       1/2/2017  1/3/2017  1/4/2017  1/5/2017  1/6/2017  1/7/2017   1/8/2017    1/9/2017  1/10/2017
Job 1                                                                            44
Job 2                       25                                                   50
Job 3   22        44        66        88       110       132
Job 4                                                                                      25

Answer 1

You can do it with pandas like so:

import pandas as pd

a = {'Job1': {'2017-01-10': [44, 33, 11, 75, 22]}, 
'Job2': {'2017-01-05': [25, 25, 0, 100, 25], '2017-01-10': [50, 50, 0, 100, 25]}, 
'Job3': {'2017-01-03': [44, 22, 22, 50, 22], '2017-01-04': [66, 36, 30, 54, 22], '2017-01-06': [88, 52, 36, 59, 22], '2017-01-10': [132, 68, 64, 51, 22], '2017-01-02': [22, 9, 13, 40, 22], '2017-01-08': [110, 52, 58, 47, 22]},
 'Job4': {'2017-01-10': [25, 25, 0, 100, 25]}}
df = pd.DataFrame(data=a)
df = df.fillna(' ').T
df

Output:

If you want just the first element of the list:

df = df.applymap(lambda x: x[0] if type(x)==list else x)
df

If you want to convert it into HTML table you can use .to_html() method like so:

print df.to_html()

Output:

<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>2017-01-02</th>
      <th>2017-01-03</th>
      <th>2017-01-04</th>
      <th>2017-01-05</th>
      <th>2017-01-06</th>
      <th>2017-01-08</th>
      <th>2017-01-10</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>Job1</th>
      <td></td>
      <td></td>
      <td></td>
      <td></td>
      <td></td>
      <td></td>
      <td>44</td>
    </tr>
    <tr>
      <th>Job2</th>
      <td></td>
      <td></td>
      <td></td>
      <td>25</td>
      <td></td>
      <td></td>
      <td>50</td>
    </tr>
    <tr>
      <th>Job3</th>
      <td>22</td>
      <td>44</td>
      <td>66</td>
      <td></td>
      <td>88</td>
      <td>110</td>
      <td>132</td>
    </tr>
    <tr>
      <th>Job4</th>
      <td></td>
      <td></td>
      <td></td>
      <td></td>
      <td></td>
      <td></td>
      <td>25</td>
    </tr>
  </tbody>
</table>