python - 在熊猫样式渲染中格式化日期

Question

我有一个包含三列的熊猫数据框，其中第一列是日期。要生成 html 输出，我使用以下命令：

html_string = df.style.format({'second': "{:0,.0f}",third: "{:0,.0f}"}).set_table_styles(styles).render()

怎么可能指定日期的格式......就像：

html_string = df.style.format({'Date': "%Y.%m",'second': "{:0,.0f}",third: "{:0,.0f}"}).set_table_styles(styles).render()

Answer 1

你可以做：

html_string = df.style.format({'Date': "{:%Y.%m}",
                               'second': "{:0,.0f}",
                               'third': "{:0,.0f}"}).set_table_styles(styles).render()

Answer 2

实际上它需要一个字符串作为参数......所以这应该工作：

html_string = df.style.format({'Date': "{:%Y.%m}",'second': "{:0,.0f}",'third': "{:0,.0f}"}).set_table_styles(styles).render()

不过谢谢

Answer 3

对我来说工作：

html_string = df.style.format({'first': lambda x: "{}".format(x.strftime('%Y.%m')) , 
                               'second': "{:0,.0f}",
                               'third': "{:0,.0f}"}).set_table_styles('styles').render()
print (html_string)

样本：

df = pd.DataFrame({ 'first':['2015-01-05','2015-01-06','2015-01-07'],
                    'second':[4,2.1,5.9],
                   'third':[8,5.1,7.7]})
df['first'] = pd.to_datetime(df['first'] )
print (df)
       first  second  third
0 2015-01-05     4.0    8.0
1 2015-01-06     2.1    5.1
2 2015-01-07     5.9    7.7

<table id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4f" None>


  <thead>

    <tr>

      <th class="blank">

        <th class="col_heading level0 col0">first

          <th class="col_heading level0 col1">second

            <th class="col_heading level0 col2">third

    </tr>

  </thead>
  <tbody>

    <tr>

      <th id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4f" class="row_heading level2 row0">
        0

        <td id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4frow0_col0" class="data row0 col0">
          2015.01

          <td id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4frow0_col1" class="data row0 col1">
            4

            <td id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4frow0_col2" class="data row0 col2">
              8

    </tr>

    <tr>

      <th id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4f" class="row_heading level2 row1">
        1

        <td id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4frow1_col0" class="data row1 col0">
          2015.01

          <td id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4frow1_col1" class="data row1 col1">
            2

            <td id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4frow1_col2" class="data row1 col2">
              5

    </tr>

    <tr>

      <th id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4f" class="row_heading level2 row2">
        2

        <td id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4frow2_col0" class="data row2 col0">
          2015.01

          <td id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4frow2_col1" class="data row2 col1">
            6

            <td id="T_a301a12e_54ca_11e6_9a6f_acb57da49b4frow2_col2" class="data row2 col2">
              8

    </tr>

  </tbody>
</table>