Styler.format_index(formatter=None, axis=0, level=None, na_rep=None, precision=None, decimal='.', thousands=None, escape=None, hyperlinks=None)[source]#

Format the text display value of index labels or column headers.

New in version 1.4.0.

formatterstr, callable, dict or None

Object to define how values are displayed. See notes.

axis{0, “index”, 1, “columns”}

Whether to apply the formatter to the index or column headers.

levelint, str, list

The level(s) over which to apply the generic formatter.

na_repstr, optional

Representation for missing values. If na_rep is None, no special formatting is applied.

precisionint, optional

Floating point precision to use for display purposes, if not determined by the specified formatter.

decimalstr, default “.”

Character used as decimal separator for floats, complex and integers.

thousandsstr, optional, default None

Character used as thousands separator for floats, complex and integers.

escapestr, optional

Use ‘html’ to replace the characters &, <, >, ', and " in cell display string with HTML-safe sequences. Use ‘latex’ to replace the characters &, %, $, #, _, {, }, ~, ^, and \ in the cell display string with LaTeX-safe sequences. Escaping is done before formatter.

hyperlinks{“html”, “latex”}, optional

Convert string patterns containing https://, http://, ftp:// or www. to HTML <a> tags as clickable URL hyperlinks if “html”, or LaTeX href commands if “latex”.


See also


Format the text display value of data cells.


This method assigns a formatting function, formatter, to each level label in the DataFrame’s index or column headers. If formatter is None, then the default formatter is used. If a callable then that function should take a label value as input and return a displayable representation, such as a string. If formatter is given as a string this is assumed to be a valid Python format specification and is wrapped to a callable as string.format(x). If a dict is given, keys should correspond to MultiIndex level numbers or names, and values should be string or callable, as above.

The default formatter currently expresses floats and complex numbers with the pandas display precision unless using the precision argument here. The default formatter does not adjust the representation of missing values unless the na_rep argument is used.

The level argument defines which levels of a MultiIndex to apply the method to. If the formatter argument is given in dict form but does not include all levels within the level argument then these unspecified levels will have the default formatter applied. Any levels in the formatter dict specifically excluded from the level argument will be ignored.

When using a formatter string the dtypes must be compatible, otherwise a ValueError will be raised.


Styler.format_index is ignored when using the output format Styler.to_excel, since Excel and Python have inherrently different formatting structures. However, it is possible to use the number-format pseudo CSS attribute to force Excel permissible formatting. See documentation for Styler.format.


Using na_rep and precision with the default formatter

>>> df = pd.DataFrame([[1, 2, 3]], columns=[2.0, np.nan, 4.0])
>>>, na_rep='MISS', precision=3)  
    2.000    MISS   4.000
0       1       2       3

Using a formatter specification on consistent dtypes in a level

>>>'{:.2f}', axis=1, na_rep='MISS')  
     2.00   MISS    4.00
0       1      2       3

Using the default formatter for unspecified levels

>>> df = pd.DataFrame([[1, 2, 3]],
...     columns=pd.MultiIndex.from_arrays([["a", "a", "b"],[2, np.nan, 4]]))
>>>{0: lambda v: upper(v)}, axis=1, precision=1)
               A       B
      2.0    nan     4.0
0       1      2       3

Using a callable formatter function.

>>> func = lambda s: 'STRING' if isinstance(s, str) else 'FLOAT'
>>>, axis=1, na_rep='MISS')
          STRING  STRING
0       1      2       3

Using a formatter with HTML escape and na_rep.

>>> df = pd.DataFrame([[1, 2, 3]], columns=['"A"', 'A&B', None])
>>> s ='$ {0}', axis=1, escape="html", na_rep="NA")
<th .. >$ &#34;A&#34;</th>
<th .. >$ A&amp;B</th>
<th .. >NA</td>

Using a formatter with LaTeX escape.

>>> df = pd.DataFrame([[1, 2, 3]], columns=["123", "~", "$%#"])
>>>"\\textbf{{{}}}", escape="latex", axis=1).to_latex()
{} & {\textbf{123}} & {\textbf{\textasciitilde }} & {\textbf{\$\%\#}} \\
0 & 1 & 2 & 3 \\