Incorrect results from json2html module

Question

I've seen multiple of examples of this online, but I've not found anything that helps me solve the problem I'm faced with. I'm trying to convert a JSON object into an HTML table, but I'm faced with a couple of issues.

Suppose I have the following object, call it tableJson, which is essentially representative of a table with only column headers:

[
  {
    "firstColumn": []
  },
  {
    "secondColumn": []
  },
  {
    "thirdColumn": []
  }
]

In trying to convert this into an HTML table, I have done the following:

jsonDumps = json.dumps(jsonTable)
htmlTable = json2html.convert(json = jsonDumps)

Seems pretty simply. However, the result of htmlTable gives me two issues:

1. The output is in a bullet point list format
2. Each column header is treated as a separate table

For example, the result of htmlTable above is:

<ul>
  <li>
    <table border="1">
      <tr><th>firstColumn</th><td></td></tr>
    </table>
  </li>
  <li>
    <table border="1">
      <tr><th>secondColumn</th><td></td></tr>
    </table>
  </li>
  <li>
    <table border="1">
      <tr><th>thirdColumn</th><td></td></tr>
    </table>
  </li>
</ul>

What is the simply way of creating a table (correctly) so that I don't have it in a bullet point list and so that each column is treated as a correct column rather than a table?

Is there a problem with the way the JSON object is represented? If so, what is the correct syntax so that json2html converts it correctly into a table?

Answer 1

There's some issue with the original structure if your table, which is clearer when you attempt to create a DataFrame from it; if you restructure it as a single dict first, you may find it much easier to work with and can directly use Pandas to render your table

Starting Values

>>> import pandas as pd
>>> src_table = [
...   {
...     "firstColumn": []
...   },
...   {
...     "secondColumn": []
...   },
...   {
...     "thirdColumn": []
...   }
... ]

Demo of issue

(each column is unique, rather than being in the same collection)

>>> pd.DataFrame(src_table)
  firstColumn secondColumn thirdColumn
0          []          NaN         NaN
1         NaN           []         NaN
2         NaN          NaN          []

Flatten list of dicts and Display

See How do I merge a list of dicts into a single dict?

>>> src_flattened = dict(pair for d in src_table for pair in d.items())
>>> src_flattened
{'firstColumn': [], 'secondColumn': [], 'thirdColumn': []}
>>> df = pd.DataFrame(src_flattened)
>>> df
Empty DataFrame
Columns: [firstColumn, secondColumn, thirdColumn]
Index: []
>>> print(df.to_html())
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>firstColumn</th>
      <th>secondColumn</th>
      <th>thirdColumn</th>
    </tr>
  </thead>
  <tbody>
  </tbody>
</table>

Rendered

With a few values inserted

>>> pd.DataFrame({"col1": [1,2,3], "col2": [4,5,6], "col3": ['a', None, False]}).to_html()
'<table border="1" class="dataframe">\n  <thead>\n    <tr style="text-align: right;">\n      <th></th>\n      <th>col1</th>\n      <th>col2</th>\n      <th>col3</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>4</td>\n      <td>a</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>5</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>6</td>\n      <td>False</td>\n    </tr>\n  </tbody>\n</table>'

Rendered

You can use different arguments to the .to_html() method to omit major table features like the index and do the rest in CSS