-
-
Notifications
You must be signed in to change notification settings - Fork 18.1k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
ENH: Add built-in function for Styler to format the text displayed for missing values #29118
Merged
TomAugspurger
merged 14 commits into
pandas-dev:master
from
immaxchen:styler-builtin-shortcut-for-missing-values-formatting-gh28358
Nov 25, 2019
Merged
Changes from all commits
Commits
Show all changes
14 commits
Select commit
Hold shift + click to select a range
c42de40
Add built-in funcion for Styler to format the text displayed for miss…
immaxchen 01632ce
Add Styler.format_null into user_guide and reference Doc
immaxchen 53b0843
Revised to change implementation to integrate with the original Style…
immaxchen 7a5dd65
resolve merge conflicts
immaxchen da3cb43
add more tests for styling with NA values
immaxchen bdfff98
Merge remote-tracking branch 'upstream/master' into styler-builtin-sh…
immaxchen b86bdc6
revision based on the requested changes
immaxchen a1e9a9e
add tests, enhance doc string and formatter wrapping
immaxchen def71c9
Merge remote-tracking branch 'upstream/master' into styler-builtin-sh…
immaxchen af396b1
resolve merge conflict
immaxchen 3d4cfd0
add type-hint and xfail test
immaxchen bd99db9
revise test using pytest.raises
immaxchen 346eee6
Merge remote-tracking branch 'upstream/master' into styler-builtin-sh…
immaxchen 7935359
using py36 syntax for annotations
immaxchen File filter
Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
|
@@ -8,7 +8,7 @@ | |
import copy | ||
from functools import partial | ||
from itertools import product | ||
from typing import Optional | ||
from typing import Any, Callable, DefaultDict, Dict, List, Optional, Sequence, Tuple | ||
from uuid import uuid1 | ||
|
||
import numpy as np | ||
|
@@ -71,6 +71,11 @@ class Styler: | |
The ``id`` takes the form ``T_<uuid>_row<num_row>_col<num_col>`` | ||
where ``<uuid>`` is the unique identifier, ``<num_row>`` is the row | ||
number and ``<num_col>`` is the column number. | ||
na_rep : str, optional | ||
Representation for missing values. | ||
If ``na_rep`` is None, no special formatting is applied | ||
|
||
.. versionadded:: 1.0.0 | ||
|
||
Attributes | ||
---------- | ||
|
@@ -126,9 +131,10 @@ def __init__( | |
caption=None, | ||
table_attributes=None, | ||
cell_ids=True, | ||
na_rep: Optional[str] = None, | ||
): | ||
self.ctx = defaultdict(list) | ||
self._todo = [] | ||
self.ctx: DefaultDict[Tuple[int, int], List[str]] = defaultdict(list) | ||
self._todo: List[Tuple[Callable, Tuple, Dict]] = [] | ||
|
||
if not isinstance(data, (pd.Series, pd.DataFrame)): | ||
raise TypeError("``data`` must be a Series or DataFrame") | ||
|
@@ -149,19 +155,24 @@ def __init__( | |
self.precision = precision | ||
self.table_attributes = table_attributes | ||
self.hidden_index = False | ||
self.hidden_columns = [] | ||
self.hidden_columns: Sequence[int] = [] | ||
self.cell_ids = cell_ids | ||
self.na_rep = na_rep | ||
|
||
# display_funcs maps (row, col) -> formatting function | ||
|
||
def default_display_func(x): | ||
if is_float(x): | ||
if self.na_rep is not None and pd.isna(x): | ||
return self.na_rep | ||
elif is_float(x): | ||
display_format = "{0:.{precision}f}".format(x, precision=self.precision) | ||
return display_format | ||
else: | ||
return x | ||
|
||
self._display_funcs = defaultdict(lambda: default_display_func) | ||
self._display_funcs: DefaultDict[ | ||
Tuple[int, int], Callable[[Any], str] | ||
] = defaultdict(lambda: default_display_func) | ||
|
||
def _repr_html_(self): | ||
""" | ||
|
@@ -416,16 +427,22 @@ def format_attr(pair): | |
table_attributes=table_attr, | ||
) | ||
|
||
def format(self, formatter, subset=None): | ||
def format(self, formatter, subset=None, na_rep: Optional[str] = None): | ||
""" | ||
Format the text display value of cells. | ||
|
||
Parameters | ||
---------- | ||
formatter : str, callable, or dict | ||
formatter : str, callable, dict or None | ||
If ``formatter`` is None, the default formatter is used | ||
subset : IndexSlice | ||
An argument to ``DataFrame.loc`` that restricts which elements | ||
``formatter`` is applied to. | ||
na_rep : str, optional | ||
Representation for missing values. | ||
If ``na_rep`` is None, no special formatting is applied | ||
|
||
.. versionadded:: 1.0.0 | ||
|
||
Returns | ||
------- | ||
|
@@ -451,6 +468,10 @@ def format(self, formatter, subset=None): | |
>>> df['c'] = ['a', 'b', 'c', 'd'] | ||
>>> df.style.format({'c': str.upper}) | ||
""" | ||
if formatter is None: | ||
assert self._display_funcs.default_factory is not None | ||
formatter = self._display_funcs.default_factory() | ||
|
||
if subset is None: | ||
row_locs = range(len(self.data)) | ||
col_locs = range(len(self.data.columns)) | ||
|
@@ -466,16 +487,16 @@ def format(self, formatter, subset=None): | |
if is_dict_like(formatter): | ||
for col, col_formatter in formatter.items(): | ||
# formatter must be callable, so '{}' are converted to lambdas | ||
col_formatter = _maybe_wrap_formatter(col_formatter) | ||
col_formatter = _maybe_wrap_formatter(col_formatter, na_rep) | ||
col_num = self.data.columns.get_indexer_for([col])[0] | ||
|
||
for row_num in row_locs: | ||
self._display_funcs[(row_num, col_num)] = col_formatter | ||
else: | ||
# single scalar to format all cells with | ||
formatter = _maybe_wrap_formatter(formatter, na_rep) | ||
locs = product(*(row_locs, col_locs)) | ||
for i, j in locs: | ||
formatter = _maybe_wrap_formatter(formatter) | ||
self._display_funcs[(i, j)] = formatter | ||
return self | ||
|
||
|
@@ -553,6 +574,7 @@ def _copy(self, deepcopy=False): | |
caption=self.caption, | ||
uuid=self.uuid, | ||
table_styles=self.table_styles, | ||
na_rep=self.na_rep, | ||
) | ||
if deepcopy: | ||
styler.ctx = copy.deepcopy(self.ctx) | ||
|
@@ -896,6 +918,23 @@ def set_table_styles(self, table_styles): | |
self.table_styles = table_styles | ||
return self | ||
|
||
def set_na_rep(self, na_rep: str) -> "Styler": | ||
""" | ||
Set the missing data representation on a Styler. | ||
|
||
.. versionadded:: 1.0.0 | ||
|
||
Parameters | ||
---------- | ||
na_rep : str | ||
|
||
Returns | ||
------- | ||
self : Styler | ||
""" | ||
self.na_rep = na_rep | ||
return self | ||
|
||
def hide_index(self): | ||
""" | ||
Hide any indices from rendering. | ||
|
@@ -1487,14 +1526,22 @@ def _get_level_lengths(index, hidden_elements=None): | |
return non_zero_lengths | ||
|
||
|
||
def _maybe_wrap_formatter(formatter): | ||
def _maybe_wrap_formatter(formatter, na_rep: Optional[str]): | ||
if isinstance(formatter, str): | ||
return lambda x: formatter.format(x) | ||
formatter_func = lambda x: formatter.format(x) | ||
elif callable(formatter): | ||
return formatter | ||
formatter_func = formatter | ||
else: | ||
msg = ( | ||
"Expected a template string or callable, got {formatter} " | ||
"instead".format(formatter=formatter) | ||
) | ||
raise TypeError(msg) | ||
|
||
if na_rep is None: | ||
return formatter_func | ||
elif isinstance(na_rep, str): | ||
return lambda x: na_rep if pd.isna(x) else formatter_func(x) | ||
else: | ||
msg = "Expected a string, got {na_rep} instead".format(na_rep=na_rep) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Can you add a test case that hits this? |
||
raise TypeError(msg) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Not required here but if you wanted to in a follow up annotate other arguments would be super helpful