pandas DataFrame中的粗体to_html [英] Bold column in pandas DataFrame to_html

问题描述

我正在尝试使用一个粗体列返回df.to_html().我只尝试过

I am trying to return df.to_html() with one bold column. I have only tried

df = pd.DataFrame({'important_column': [1,2,3,4], 
                   'dummy_column': [5,6,7,8]})

def some_function()
      df.apply(lambda x: '<b>' + str(df['important_column']) + '</b>', axis=1)
      return [df.to_html()]

但是它似乎不起作用.有谁知道一种可行的解决方案?

But it doesn't seem to work. Does any one know a practical solution?

推荐答案

您忘了分配输出，但是更快的矢量化解决方案是将列转换为字符串，并使用f字符串添加不带apply的字符串:

You forget assign output, but faster vectorized solution is convert column to string and add strings with no apply with f strings:

def some_function():

    df['important_column'] = [f'<b>{x}</b>' for x in df['important_column']]
    #alternative1 
    df['important_column'] =  '<b>' + df['important_column'].astype(str) + '</b>'
    #alternative2
    #df['important_column'] = df['important_column'].apply(lambda x: '<b>' + str(x) + '</b>')
    #alternative3, thanks @Jon Clements
    #df['important_column'] = df['important_column'].apply('<b>{}</b>?'.format)
    return df.to_html()

df['important_column'] = [f'<b>{x}</b>' for x in df['important_column']]
print (df.to_html(escape=False))
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>important_column</th>
      <th>dummy_column</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td><b>1</b></td>
      <td>5</td>
    </tr>
    <tr>
      <th>1</th>
      <td><b>2</b></td>
      <td>6</td>
    </tr>
    <tr>
      <th>2</th>
      <td><b>3</b></td>
      <td>7</td>
    </tr>
    <tr>
      <th>3</th>
      <td><b>4</b></td>
      <td>8</td>
    </tr>
  </tbody>
</table>

时间:

df = pd.DataFrame({'important_column': [1,2,3,4], 
                   'dummy_column': [5,6,7,8]})

df = pd.concat([df] * 10000, ignore_index=True)

In [213]: %timeit df['important_column'] = [f'<b>{x}</b>' for x in df['important_column']]
74 ms ± 22.2 ms per loop (mean ± std. dev. of 7 runs, 100 loops each)

In [214]: %timeit df['important_column'] = df['important_column'].apply(lambda x: '<b>' + str(x) + '</b>')
150 ms ± 7.75 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

In [216]: %timeit df['important_column'].apply('<b>{}</b>?'.format)
133 ms ± 238 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

In [217]: %timeit '<b>' + df['important_column'].astype(str) + '</b>'
266 ms ± 1.21 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

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