format Date in pandas style render

Question

I have a pandas dataframe with three columns of which the first is the Date. To produce a html output I use this:

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

how is it possible to specifiy the format of the Date as well...something like:

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

mechanical_meat · Answer 1 · 2016-07-28T14:33:57.850

3

You can do:

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

edited Jul 28 '16 at 14:33

answered Jul 28 '16 at 13:47

mechanical_meat

163,903
24
228
223

score 2 · Answer 2 · answered Jul 28 '16 at 14:00

2

Actually it takes a string as argument...so this should work:

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

thanks though

answered Jul 28 '16 at 14:00

y4nnick

101
1
4

1

This is exactly my answer... 17 minutes ago – mechanical_meat Jul 28 '16 at 14:04
For me it doesnt work, I use python 3. Maybe try test with sample `df`: `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)` – jezrael Jul 28 '16 at 14:08
@bernie it is almost : {:"%Y.%m"} vs "{:%Y.%m}" for me only the latter is working – y4nnick Jul 28 '16 at 14:29
Ah, I see @y4nnick. Fixed my example. – mechanical_meat Jul 28 '16 at 14:34

jezrael · Answer 3 · 2016-07-28T13:54:08.300

For me works:

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)

Sample:

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>

Unfortunately I think it is not supported yet... But maybe I am wrong, try post question. — jezrael, Oct 05 '17 at 14:12
Alright thanks. I've been trying to figure it out for about a day now... and I can't seem to. Seems like it isn't supported to me too. As of now it looks like if you have a datetime index and you only care about the date part, you're going to be stuck with looking at the time part too. — Alex Luis Arias, Oct 05 '17 at 14:30
Here's the question I posted in case you wanted to follow: https://stackoverflow.com/questions/46588792/formatting-datetime-index-with-pandas-dataframe-style — Alex Luis Arias, Oct 05 '17 at 15:17

format Date in pandas style render

3 Answers3