使用 pandas.DataFrame.to_html 时如何设置列宽？

Question

I have read this , but I am still confused about how I set the column width when using pandas.DataFrame.to_html .

import datetime
import pandas

data = {'Los Angles': {datetime.date(2018, 9, 24): 20.5, datetime.date(2018, 9, 25): 1517.1},
        'London': {datetime.date(2018, 9, 24): 0, datetime.date(2018, 9, 25): 1767.4},
        'Kansas City': {datetime.date(2018, 9, 24): 10, datetime.date(2018, 9, 25): 1.4}}

df = pandas.DataFrame(data=data)

html = df.to_html()

The above code results in :

How do I go about forcing the column width so that they are the same?

Answer 1

Try this:

import datetime
import pandas

data = {'Los Angles': {datetime.date(2018, 9, 24): 20.5, datetime.date(2018, 9, 25): 1517.1},
        'London': {datetime.date(2018, 9, 24): 0, datetime.date(2018, 9, 25): 1767.4},
        'Kansas City': {datetime.date(2018, 9, 24): 10, datetime.date(2018, 9, 25): 1.4}}

df = pandas.DataFrame(data=data)
pandas.set_option('display.max_colwidth', 40)

html = df.to_html()

Answer 2

I find it better to use the set_table_attributes function. You are then able to set eg a CSS-class to the table. In case you have many tables on your output it is much better readable.

import datetime
import pandas

data = {'Los Angles': {datetime.date(2018, 9, 24): 20.5, datetime.date(2018, 9, 25): 1517.1},
        'London': {datetime.date(2018, 9, 24): 0, datetime.date(2018, 9, 25): 1767.4},
        'Kansas City': {datetime.date(2018, 9, 24): 10, datetime.date(2018, 9, 25): 1.4}}

df = pandas.DataFrame(data=data)

html = df.set_table_attributes('class="table-style"').to_html()

Your CSS could look something like that:

    .table-style {
                  width: 100%;
}

    .table-style td {
                  width: 100px;
}

Answer 3

You can now set the col_space argument of to_html . col_space specifies the min width of all the columns.

df.to_html(col_space='75px')

Answer 4

另一种选择是

df.style.set_table_styles([dict(selector='th', props='min-width: 60px;'),])