Repository URL to install this package:
Version:
0.23.4 ▾
|
# -*- coding: utf-8 -*-
"""
Internal module for formatting output data in csv, html,
and latex files. This module also applies to display formatting.
"""
from __future__ import print_function
# pylint: disable=W0141
from pandas.core.dtypes.missing import isna, notna
from pandas.core.dtypes.common import (
is_categorical_dtype,
is_float_dtype,
is_period_arraylike,
is_integer_dtype,
is_interval_dtype,
is_datetimetz,
is_integer,
is_float,
is_scalar,
is_numeric_dtype,
is_datetime64_dtype,
is_timedelta64_dtype,
is_list_like)
from pandas.core.dtypes.generic import ABCSparseArray
from pandas.core.base import PandasObject
import pandas.core.common as com
from pandas.core.index import Index, MultiIndex, _ensure_index
from pandas import compat
from pandas.compat import (StringIO, lzip, map, zip, u)
from pandas.io.formats.terminal import get_terminal_size
from pandas.core.config import get_option, set_option
from pandas.io.common import (_expand_user, _stringify_path)
from pandas.io.formats.printing import adjoin, justify, pprint_thing
from pandas._libs import lib
from pandas._libs.tslib import (iNaT, Timestamp, Timedelta,
format_array_from_datetime)
from pandas.core.indexes.datetimes import DatetimeIndex
from pandas.core.indexes.period import PeriodIndex
import pandas as pd
import numpy as np
from functools import partial
common_docstring = """
Parameters
----------
buf : StringIO-like, optional
buffer to write to
columns : sequence, optional
the subset of columns to write; default None writes all columns
col_space : int, optional
the minimum width of each column
header : bool, optional
%(header)s
index : bool, optional
whether to print index (row) labels, default True
na_rep : string, optional
string representation of NAN to use, default 'NaN'
formatters : list or dict of one-parameter functions, optional
formatter functions to apply to columns' elements by position or name,
default None. The result of each function must be a unicode string.
List must be of length equal to the number of columns.
float_format : one-parameter function, optional
formatter function to apply to columns' elements if they are floats,
default None. The result of this function must be a unicode string.
sparsify : bool, optional
Set to False for a DataFrame with a hierarchical index to print every
multiindex key at each row, default True
index_names : bool, optional
Prints the names of the indexes, default True
line_width : int, optional
Width to wrap a line in characters, default no wrap
table_id : str, optional
id for the <table> element create by to_html
.. versionadded:: 0.23.0"""
_VALID_JUSTIFY_PARAMETERS = ("left", "right", "center", "justify",
"justify-all", "start", "end", "inherit",
"match-parent", "initial", "unset")
justify_docstring = """
justify : str, default None
How to justify the column labels. If None uses the option from
the print configuration (controlled by set_option), 'right' out
of the box. Valid values are
* left
* right
* center
* justify
* justify-all
* start
* end
* inherit
* match-parent
* initial
* unset
"""
return_docstring = """
Returns
-------
formatted : string (or unicode, depending on data and options)"""
docstring_to_string = common_docstring + justify_docstring + return_docstring
class CategoricalFormatter(object):
def __init__(self, categorical, buf=None, length=True, na_rep='NaN',
footer=True):
self.categorical = categorical
self.buf = buf if buf is not None else StringIO(u(""))
self.na_rep = na_rep
self.length = length
self.footer = footer
def _get_footer(self):
footer = ''
if self.length:
if footer:
footer += ', '
footer += "Length: {length}".format(length=len(self.categorical))
level_info = self.categorical._repr_categories_info()
# Levels are added in a newline
if footer:
footer += '\n'
footer += level_info
return compat.text_type(footer)
def _get_formatted_values(self):
return format_array(self.categorical.get_values(), None,
float_format=None, na_rep=self.na_rep)
def to_string(self):
categorical = self.categorical
if len(categorical) == 0:
if self.footer:
return self._get_footer()
else:
return u('')
fmt_values = self._get_formatted_values()
result = [u('{i}').format(i=i) for i in fmt_values]
result = [i.strip() for i in result]
result = u(', ').join(result)
result = [u('[') + result + u(']')]
if self.footer:
footer = self._get_footer()
if footer:
result.append(footer)
return compat.text_type(u('\n').join(result))
class SeriesFormatter(object):
def __init__(self, series, buf=None, length=True, header=True, index=True,
na_rep='NaN', name=False, float_format=None, dtype=True,
max_rows=None):
self.series = series
self.buf = buf if buf is not None else StringIO()
self.name = name
self.na_rep = na_rep
self.header = header
self.length = length
self.index = index
self.max_rows = max_rows
if float_format is None:
float_format = get_option("display.float_format")
self.float_format = float_format
self.dtype = dtype
self.adj = _get_adjustment()
self._chk_truncate()
def _chk_truncate(self):
from pandas.core.reshape.concat import concat
max_rows = self.max_rows
truncate_v = max_rows and (len(self.series) > max_rows)
series = self.series
if truncate_v:
if max_rows == 1:
row_num = max_rows
series = series.iloc[:max_rows]
else:
row_num = max_rows // 2
series = concat((series.iloc[:row_num],
series.iloc[-row_num:]))
self.tr_row_num = row_num
self.tr_series = series
self.truncate_v = truncate_v
def _get_footer(self):
name = self.series.name
footer = u('')
if getattr(self.series.index, 'freq', None) is not None:
footer += 'Freq: {freq}'.format(freq=self.series.index.freqstr)
if self.name is not False and name is not None:
if footer:
footer += ', '
series_name = pprint_thing(name,
escape_chars=('\t', '\r', '\n'))
footer += ((u"Name: {sname}".format(sname=series_name))
if name is not None else "")
if (self.length is True or
(self.length == 'truncate' and self.truncate_v)):
if footer:
footer += ', '
footer += 'Length: {length}'.format(length=len(self.series))
if self.dtype is not False and self.dtype is not None:
name = getattr(self.tr_series.dtype, 'name', None)
if name:
if footer:
footer += ', '
footer += u'dtype: {typ}'.format(typ=pprint_thing(name))
# level infos are added to the end and in a new line, like it is done
# for Categoricals
if is_categorical_dtype(self.tr_series.dtype):
level_info = self.tr_series._values._repr_categories_info()
if footer:
footer += "\n"
footer += level_info
return compat.text_type(footer)
def _get_formatted_index(self):
index = self.tr_series.index
is_multi = isinstance(index, MultiIndex)
if is_multi:
have_header = any(name for name in index.names)
fmt_index = index.format(names=True)
else:
have_header = index.name is not None
fmt_index = index.format(name=True)
return fmt_index, have_header
def _get_formatted_values(self):
values_to_format = self.tr_series._formatting_values()
return format_array(values_to_format, None,
float_format=self.float_format, na_rep=self.na_rep)
def to_string(self):
series = self.tr_series
footer = self._get_footer()
if len(series) == 0:
return 'Series([], ' + footer + ')'
fmt_index, have_header = self._get_formatted_index()
fmt_values = self._get_formatted_values()
if self.truncate_v:
n_header_rows = 0
row_num = self.tr_row_num
width = self.adj.len(fmt_values[row_num - 1])
if width > 3:
dot_str = '...'
else:
dot_str = '..'
# Series uses mode=center because it has single value columns
# DataFrame uses mode=left
dot_str = self.adj.justify([dot_str], width, mode='center')[0]
fmt_values.insert(row_num + n_header_rows, dot_str)
fmt_index.insert(row_num + 1, '')
if self.index:
result = self.adj.adjoin(3, *[fmt_index[1:], fmt_values])
else:
result = self.adj.adjoin(3, fmt_values).replace('\n ',
'\n').strip()
if self.header and have_header:
result = fmt_index[0] + '\n' + result
if footer:
result += '\n' + footer
return compat.text_type(u('').join(result))
class TextAdjustment(object):
def __init__(self):
self.encoding = get_option("display.encoding")
def len(self, text):
return compat.strlen(text, encoding=self.encoding)
def justify(self, texts, max_len, mode='right'):
return justify(texts, max_len, mode=mode)
def adjoin(self, space, *lists, **kwargs):
return adjoin(space, *lists, strlen=self.len,
justfunc=self.justify, **kwargs)
class EastAsianTextAdjustment(TextAdjustment):
def __init__(self):
super(EastAsianTextAdjustment, self).__init__()
if get_option("display.unicode.ambiguous_as_wide"):
self.ambiguous_width = 2
else:
self.ambiguous_width = 1
def len(self, text):
return compat.east_asian_len(text, encoding=self.encoding,
ambiguous_width=self.ambiguous_width)
def justify(self, texts, max_len, mode='right'):
# re-calculate padding space per str considering East Asian Width
def _get_pad(t):
return max_len - self.len(t) + len(t)
if mode == 'left':
return [x.ljust(_get_pad(x)) for x in texts]
elif mode == 'center':
return [x.center(_get_pad(x)) for x in texts]
else:
return [x.rjust(_get_pad(x)) for x in texts]
def _get_adjustment():
use_east_asian_width = get_option("display.unicode.east_asian_width")
if use_east_asian_width:
return EastAsianTextAdjustment()
else:
return TextAdjustment()
class TableFormatter(object):
is_truncated = False
show_dimensions = None
@property
def should_show_dimensions(self):
return (self.show_dimensions is True or
(self.show_dimensions == 'truncate' and self.is_truncated))
def _get_formatter(self, i):
if isinstance(self.formatters, (list, tuple)):
if is_integer(i):
return self.formatters[i]
else:
return None
else:
if is_integer(i) and i not in self.columns:
i = self.columns[i]
return self.formatters.get(i, None)
class DataFrameFormatter(TableFormatter):
"""
Render a DataFrame
self.to_string() : console-friendly tabular output
self.to_html() : html table
self.to_latex() : LaTeX tabular environment table
"""
__doc__ = __doc__ if __doc__ else ''
__doc__ += common_docstring + justify_docstring + return_docstring
def __init__(self, frame, buf=None, columns=None, col_space=None,
header=True, index=True, na_rep='NaN', formatters=None,
justify=None, float_format=None, sparsify=None,
index_names=True, line_width=None, max_rows=None,
max_cols=None, show_dimensions=False, decimal='.',
table_id=None, **kwds):
self.frame = frame
if buf is not None:
self.buf = _expand_user(_stringify_path(buf))
else:
self.buf = StringIO()
self.show_index_names = index_names
if sparsify is None:
sparsify = get_option("display.multi_sparse")
self.sparsify = sparsify
self.float_format = float_format
self.formatters = formatters if formatters is not None else {}
self.na_rep = na_rep
self.decimal = decimal
self.col_space = col_space
self.header = header
self.index = index
self.line_width = line_width
self.max_rows = max_rows
self.max_cols = max_cols
self.max_rows_displayed = min(max_rows or len(self.frame),
len(self.frame))
self.show_dimensions = show_dimensions
self.table_id = table_id
if justify is None:
self.justify = get_option("display.colheader_justify")
else:
self.justify = justify
self.kwds = kwds
if columns is not None:
self.columns = _ensure_index(columns)
self.frame = self.frame[self.columns]
else:
self.columns = frame.columns
self._chk_truncate()
self.adj = _get_adjustment()
def _chk_truncate(self):
"""
Checks whether the frame should be truncated. If so, slices
the frame up.
"""
from pandas.core.reshape.concat import concat
# Column of which first element is used to determine width of a dot col
self.tr_size_col = -1
# Cut the data to the information actually printed
max_cols = self.max_cols
max_rows = self.max_rows
if max_cols == 0 or max_rows == 0: # assume we are in the terminal
# (why else = 0)
(w, h) = get_terminal_size()
self.w = w
self.h = h
if self.max_rows == 0:
dot_row = 1
prompt_row = 1
if self.show_dimensions:
show_dimension_rows = 3
n_add_rows = (self.header + dot_row + show_dimension_rows +
prompt_row)
# rows available to fill with actual data
max_rows_adj = self.h - n_add_rows
self.max_rows_adj = max_rows_adj
# Format only rows and columns that could potentially fit the
# screen
if max_cols == 0 and len(self.frame.columns) > w:
max_cols = w
if max_rows == 0 and len(self.frame) > h:
max_rows = h
if not hasattr(self, 'max_rows_adj'):
self.max_rows_adj = max_rows
if not hasattr(self, 'max_cols_adj'):
self.max_cols_adj = max_cols
max_cols_adj = self.max_cols_adj
max_rows_adj = self.max_rows_adj
truncate_h = max_cols_adj and (len(self.columns) > max_cols_adj)
truncate_v = max_rows_adj and (len(self.frame) > max_rows_adj)
frame = self.frame
if truncate_h:
if max_cols_adj == 0:
col_num = len(frame.columns)
elif max_cols_adj == 1:
frame = frame.iloc[:, :max_cols]
col_num = max_cols
else:
col_num = (max_cols_adj // 2)
frame = concat((frame.iloc[:, :col_num],
frame.iloc[:, -col_num:]), axis=1)
self.tr_col_num = col_num
if truncate_v:
if max_rows_adj == 0:
row_num = len(frame)
if max_rows_adj == 1:
row_num = max_rows
frame = frame.iloc[:max_rows, :]
else:
row_num = max_rows_adj // 2
frame = concat((frame.iloc[:row_num, :],
frame.iloc[-row_num:, :]))
self.tr_row_num = row_num
self.tr_frame = frame
self.truncate_h = truncate_h
self.truncate_v = truncate_v
self.is_truncated = self.truncate_h or self.truncate_v
def _to_str_columns(self):
"""
Render a DataFrame to a list of columns (as lists of strings).
"""
frame = self.tr_frame
# may include levels names also
str_index = self._get_formatted_index(frame)
if not is_list_like(self.header) and not self.header:
stringified = []
for i, c in enumerate(frame):
fmt_values = self._format_col(i)
fmt_values = _make_fixed_width(fmt_values, self.justify,
minimum=(self.col_space or 0),
adj=self.adj)
stringified.append(fmt_values)
else:
if is_list_like(self.header):
if len(self.header) != len(self.columns):
raise ValueError(('Writing {ncols} cols but got {nalias} '
'aliases'
.format(ncols=len(self.columns),
nalias=len(self.header))))
str_columns = [[label] for label in self.header]
else:
str_columns = self._get_formatted_column_labels(frame)
stringified = []
for i, c in enumerate(frame):
cheader = str_columns[i]
header_colwidth = max(self.col_space or 0,
*(self.adj.len(x) for x in cheader))
fmt_values = self._format_col(i)
fmt_values = _make_fixed_width(fmt_values, self.justify,
minimum=header_colwidth,
adj=self.adj)
max_len = max(max(self.adj.len(x) for x in fmt_values),
header_colwidth)
cheader = self.adj.justify(cheader, max_len, mode=self.justify)
stringified.append(cheader + fmt_values)
strcols = stringified
if self.index:
strcols.insert(0, str_index)
# Add ... to signal truncated
truncate_h = self.truncate_h
truncate_v = self.truncate_v
if truncate_h:
col_num = self.tr_col_num
# infer from column header
col_width = self.adj.len(strcols[self.tr_size_col][0])
strcols.insert(self.tr_col_num + 1, ['...'.center(col_width)] *
(len(str_index)))
if truncate_v:
n_header_rows = len(str_index) - len(frame)
row_num = self.tr_row_num
for ix, col in enumerate(strcols):
# infer from above row
cwidth = self.adj.len(strcols[ix][row_num])
is_dot_col = False
if truncate_h:
is_dot_col = ix == col_num + 1
if cwidth > 3 or is_dot_col:
my_str = '...'
else:
my_str = '..'
if ix == 0:
dot_mode = 'left'
elif is_dot_col:
cwidth = self.adj.len(strcols[self.tr_size_col][0])
dot_mode = 'center'
else:
dot_mode = 'right'
dot_str = self.adj.justify([my_str], cwidth, mode=dot_mode)[0]
strcols[ix].insert(row_num + n_header_rows, dot_str)
return strcols
def to_string(self):
"""
Render a DataFrame to a console-friendly tabular output.
"""
from pandas import Series
frame = self.frame
if len(frame.columns) == 0 or len(frame.index) == 0:
info_line = (u('Empty {name}\nColumns: {col}\nIndex: {idx}')
.format(name=type(self.frame).__name__,
col=pprint_thing(frame.columns),
idx=pprint_thing(frame.index)))
text = info_line
else:
strcols = self._to_str_columns()
if self.line_width is None: # no need to wrap around just print
# the whole frame
text = self.adj.adjoin(1, *strcols)
elif (not isinstance(self.max_cols, int) or
self.max_cols > 0): # need to wrap around
text = self._join_multiline(*strcols)
else: # max_cols == 0. Try to fit frame to terminal
text = self.adj.adjoin(1, *strcols).split('\n')
max_len = Series(text).str.len().max()
headers = [ele[0] for ele in strcols]
# Size of last col determines dot col size. See
# `self._to_str_columns
size_tr_col = len(headers[self.tr_size_col])
max_len += size_tr_col # Need to make space for largest row
# plus truncate dot col
dif = max_len - self.w
# '+ 1' to avoid too wide repr (GH PR #17023)
adj_dif = dif + 1
col_lens = Series([Series(ele).apply(len).max()
for ele in strcols])
n_cols = len(col_lens)
counter = 0
while adj_dif > 0 and n_cols > 1:
counter += 1
mid = int(round(n_cols / 2.))
mid_ix = col_lens.index[mid]
col_len = col_lens[mid_ix]
# adjoin adds one
adj_dif -= (col_len + 1)
col_lens = col_lens.drop(mid_ix)
n_cols = len(col_lens)
# subtract index column
max_cols_adj = n_cols - self.index
# GH-21180. Ensure that we print at least two.
max_cols_adj = max(max_cols_adj, 2)
self.max_cols_adj = max_cols_adj
# Call again _chk_truncate to cut frame appropriately
# and then generate string representation
self._chk_truncate()
strcols = self._to_str_columns()
text = self.adj.adjoin(1, *strcols)
if not self.index:
text = text.replace('\n ', '\n').strip()
self.buf.writelines(text)
if self.should_show_dimensions:
self.buf.write("\n\n[{nrows} rows x {ncols} columns]"
.format(nrows=len(frame), ncols=len(frame.columns)))
def _join_multiline(self, *strcols):
lwidth = self.line_width
adjoin_width = 1
strcols = list(strcols)
if self.index:
idx = strcols.pop(0)
lwidth -= np.array([self.adj.len(x)
for x in idx]).max() + adjoin_width
col_widths = [np.array([self.adj.len(x) for x in col]).max() if
len(col) > 0 else 0 for col in strcols]
col_bins = _binify(col_widths, lwidth)
nbins = len(col_bins)
if self.truncate_v:
nrows = self.max_rows_adj + 1
else:
nrows = len(self.frame)
str_lst = []
st = 0
for i, ed in enumerate(col_bins):
row = strcols[st:ed]
if self.index:
row.insert(0, idx)
if nbins > 1:
if ed <= len(strcols) and i < nbins - 1:
row.append([' \\'] + [' '] * (nrows - 1))
else:
row.append([' '] * nrows)
str_lst.append(self.adj.adjoin(adjoin_width, *row))
st = ed
return '\n\n'.join(str_lst)
def to_latex(self, column_format=None, longtable=False, encoding=None,
multicolumn=False, multicolumn_format=None, multirow=False):
"""
Render a DataFrame to a LaTeX tabular/longtable environment output.
"""
from pandas.io.formats.latex import LatexFormatter
latex_renderer = LatexFormatter(self, column_format=column_format,
longtable=longtable,
multicolumn=multicolumn,
multicolumn_format=multicolumn_format,
multirow=multirow)
if encoding is None:
encoding = 'ascii' if compat.PY2 else 'utf-8'
if hasattr(self.buf, 'write'):
latex_renderer.write_result(self.buf)
elif isinstance(self.buf, compat.string_types):
import codecs
with codecs.open(self.buf, 'w', encoding=encoding) as f:
latex_renderer.write_result(f)
else:
raise TypeError('buf is not a file name and it has no write '
'method')
def _format_col(self, i):
frame = self.tr_frame
formatter = self._get_formatter(i)
values_to_format = frame.iloc[:, i]._formatting_values()
return format_array(values_to_format, formatter,
float_format=self.float_format, na_rep=self.na_rep,
space=self.col_space, decimal=self.decimal)
def to_html(self, classes=None, notebook=False, border=None):
"""
Render a DataFrame to a html table.
Parameters
----------
classes : str or list-like
classes to include in the `class` attribute of the opening
``<table>`` tag, in addition to the default "dataframe".
notebook : {True, False}, optional, default False
Whether the generated HTML is for IPython Notebook.
border : int
A ``border=border`` attribute is included in the opening
``<table>`` tag. Default ``pd.options.html.border``.
.. versionadded:: 0.19.0
"""
from pandas.io.formats.html import HTMLFormatter
html_renderer = HTMLFormatter(self, classes=classes,
max_rows=self.max_rows,
max_cols=self.max_cols,
notebook=notebook,
border=border,
table_id=self.table_id)
if hasattr(self.buf, 'write'):
html_renderer.write_result(self.buf)
elif isinstance(self.buf, compat.string_types):
with open(self.buf, 'w') as f:
html_renderer.write_result(f)
else:
raise TypeError('buf is not a file name and it has no write '
' method')
def _get_formatted_column_labels(self, frame):
from pandas.core.index import _sparsify
columns = frame.columns
if isinstance(columns, MultiIndex):
fmt_columns = columns.format(sparsify=False, adjoin=False)
fmt_columns = lzip(*fmt_columns)
dtypes = self.frame.dtypes._values
# if we have a Float level, they don't use leading space at all
restrict_formatting = any(l.is_floating for l in columns.levels)
need_leadsp = dict(zip(fmt_columns, map(is_numeric_dtype, dtypes)))
def space_format(x, y):
if (y not in self.formatters and
need_leadsp[x] and not restrict_formatting):
return ' ' + y
return y
str_columns = list(zip(*[[space_format(x, y) for y in x]
for x in fmt_columns]))
if self.sparsify and len(str_columns):
str_columns = _sparsify(str_columns)
str_columns = [list(x) for x in zip(*str_columns)]
else:
fmt_columns = columns.format()
dtypes = self.frame.dtypes
need_leadsp = dict(zip(fmt_columns, map(is_numeric_dtype, dtypes)))
str_columns = [[' ' + x if not self._get_formatter(i) and
need_leadsp[x] else x]
for i, (col, x) in enumerate(zip(columns,
fmt_columns))]
if self.show_index_names and self.has_index_names:
for x in str_columns:
x.append('')
# self.str_columns = str_columns
return str_columns
@property
def has_index_names(self):
return _has_names(self.frame.index)
@property
def has_column_names(self):
return _has_names(self.frame.columns)
def _get_formatted_index(self, frame):
# Note: this is only used by to_string() and to_latex(), not by
# to_html().
index = frame.index
columns = frame.columns
show_index_names = self.show_index_names and self.has_index_names
show_col_names = (self.show_index_names and self.has_column_names)
fmt = self._get_formatter('__index__')
if isinstance(index, MultiIndex):
fmt_index = index.format(sparsify=self.sparsify, adjoin=False,
names=show_index_names, formatter=fmt)
else:
fmt_index = [index.format(name=show_index_names, formatter=fmt)]
fmt_index = [tuple(_make_fixed_width(list(x), justify='left',
minimum=(self.col_space or 0),
adj=self.adj)) for x in fmt_index]
adjoined = self.adj.adjoin(1, *fmt_index).split('\n')
# empty space for columns
if show_col_names:
col_header = ['{x}'.format(x=x)
for x in self._get_column_name_list()]
else:
col_header = [''] * columns.nlevels
if self.header:
return col_header + adjoined
else:
return adjoined
def _get_column_name_list(self):
names = []
columns = self.frame.columns
if isinstance(columns, MultiIndex):
names.extend('' if name is None else name
for name in columns.names)
else:
names.append('' if columns.name is None else columns.name)
return names
# ----------------------------------------------------------------------
# Array formatters
def format_array(values, formatter, float_format=None, na_rep='NaN',
digits=None, space=None, justify='right', decimal='.'):
if is_categorical_dtype(values):
fmt_klass = CategoricalArrayFormatter
elif is_interval_dtype(values):
fmt_klass = IntervalArrayFormatter
elif is_float_dtype(values.dtype):
fmt_klass = FloatArrayFormatter
elif is_period_arraylike(values):
fmt_klass = PeriodArrayFormatter
elif is_integer_dtype(values.dtype):
fmt_klass = IntArrayFormatter
elif is_datetimetz(values):
fmt_klass = Datetime64TZFormatter
elif is_datetime64_dtype(values.dtype):
fmt_klass = Datetime64Formatter
elif is_timedelta64_dtype(values.dtype):
fmt_klass = Timedelta64Formatter
else:
fmt_klass = GenericArrayFormatter
if space is None:
space = get_option("display.column_space")
if float_format is None:
float_format = get_option("display.float_format")
if digits is None:
digits = get_option("display.precision")
fmt_obj = fmt_klass(values, digits=digits, na_rep=na_rep,
float_format=float_format, formatter=formatter,
space=space, justify=justify, decimal=decimal)
return fmt_obj.get_result()
class GenericArrayFormatter(object):
def __init__(self, values, digits=7, formatter=None, na_rep='NaN',
space=12, float_format=None, justify='right', decimal='.',
quoting=None, fixed_width=True):
self.values = values
self.digits = digits
self.na_rep = na_rep
self.space = space
self.formatter = formatter
self.float_format = float_format
self.justify = justify
self.decimal = decimal
self.quoting = quoting
self.fixed_width = fixed_width
def get_result(self):
fmt_values = self._format_strings()
return _make_fixed_width(fmt_values, self.justify)
def _format_strings(self):
if self.float_format is None:
float_format = get_option("display.float_format")
if float_format is None:
fmt_str = ('{{x: .{prec:d}g}}'
.format(prec=get_option("display.precision")))
float_format = lambda x: fmt_str.format(x=x)
else:
float_format = self.float_format
formatter = (
self.formatter if self.formatter is not None else
(lambda x: pprint_thing(x, escape_chars=('\t', '\r', '\n'))))
def _format(x):
if self.na_rep is not None and is_scalar(x) and isna(x):
if x is None:
return 'None'
elif x is pd.NaT:
return 'NaT'
return self.na_rep
elif isinstance(x, PandasObject):
return u'{x}'.format(x=x)
else:
# object dtype
return u'{x}'.format(x=formatter(x))
vals = self.values
if isinstance(vals, Index):
vals = vals._values
elif isinstance(vals, ABCSparseArray):
vals = vals.values
is_float_type = lib.map_infer(vals, is_float) & notna(vals)
leading_space = is_float_type.any()
fmt_values = []
for i, v in enumerate(vals):
if not is_float_type[i] and leading_space:
fmt_values.append(u' {v}'.format(v=_format(v)))
elif is_float_type[i]:
fmt_values.append(float_format(v))
else:
fmt_values.append(u' {v}'.format(v=_format(v)))
return fmt_values
class FloatArrayFormatter(GenericArrayFormatter):
"""
"""
def __init__(self, *args, **kwargs):
GenericArrayFormatter.__init__(self, *args, **kwargs)
# float_format is expected to be a string
# formatter should be used to pass a function
if self.float_format is not None and self.formatter is None:
if callable(self.float_format):
self.formatter = self.float_format
self.float_format = None
def _value_formatter(self, float_format=None, threshold=None):
"""Returns a function to be applied on each value to format it
"""
# the float_format parameter supersedes self.float_format
if float_format is None:
float_format = self.float_format
# we are going to compose different functions, to first convert to
# a string, then replace the decimal symbol, and finally chop according
# to the threshold
# when there is no float_format, we use str instead of '%g'
# because str(0.0) = '0.0' while '%g' % 0.0 = '0'
if float_format:
def base_formatter(v):
return float_format(value=v) if notna(v) else self.na_rep
else:
def base_formatter(v):
return str(v) if notna(v) else self.na_rep
if self.decimal != '.':
def decimal_formatter(v):
return base_formatter(v).replace('.', self.decimal, 1)
else:
decimal_formatter = base_formatter
if threshold is None:
return decimal_formatter
def formatter(value):
if notna(value):
if abs(value) > threshold:
return decimal_formatter(value)
else:
return decimal_formatter(0.0)
else:
return self.na_rep
return formatter
def get_result_as_array(self):
"""
Returns the float values converted into strings using
the parameters given at initialisation, as a numpy array
"""
if self.formatter is not None:
return np.array([self.formatter(x) for x in self.values])
if self.fixed_width:
threshold = get_option("display.chop_threshold")
else:
threshold = None
# if we have a fixed_width, we'll need to try different float_format
def format_values_with(float_format):
formatter = self._value_formatter(float_format, threshold)
# separate the wheat from the chaff
values = self.values
mask = isna(values)
if hasattr(values, 'to_dense'): # sparse numpy ndarray
values = values.to_dense()
values = np.array(values, dtype='object')
values[mask] = self.na_rep
imask = (~mask).ravel()
values.flat[imask] = np.array([formatter(val)
for val in values.ravel()[imask]])
if self.fixed_width:
return _trim_zeros(values, self.na_rep)
return values
# There is a special default string when we are fixed-width
# The default is otherwise to use str instead of a formatting string
if self.float_format is None:
if self.fixed_width:
float_format = partial('{value: .{digits:d}f}'.format,
digits=self.digits)
else:
float_format = self.float_format
else:
float_format = lambda value: self.float_format % value
formatted_values = format_values_with(float_format)
if not self.fixed_width:
return formatted_values
# we need do convert to engineering format if some values are too small
# and would appear as 0, or if some values are too big and take too
# much space
if len(formatted_values) > 0:
maxlen = max(len(x) for x in formatted_values)
too_long = maxlen > self.digits + 6
else:
too_long = False
with np.errstate(invalid='ignore'):
abs_vals = np.abs(self.values)
# this is pretty arbitrary for now
# large values: more that 8 characters including decimal symbol
# and first digit, hence > 1e6
has_large_values = (abs_vals > 1e6).any()
has_small_values = ((abs_vals < 10**(-self.digits)) &
(abs_vals > 0)).any()
if has_small_values or (too_long and has_large_values):
float_format = partial('{value: .{digits:d}e}'.format,
digits=self.digits)
formatted_values = format_values_with(float_format)
return formatted_values
def _format_strings(self):
# shortcut
if self.formatter is not None:
return [self.formatter(x) for x in self.values]
return list(self.get_result_as_array())
class IntArrayFormatter(GenericArrayFormatter):
def _format_strings(self):
formatter = self.formatter or (lambda x: '{x: d}'.format(x=x))
fmt_values = [formatter(x) for x in self.values]
return fmt_values
class Datetime64Formatter(GenericArrayFormatter):
def __init__(self, values, nat_rep='NaT', date_format=None, **kwargs):
super(Datetime64Formatter, self).__init__(values, **kwargs)
self.nat_rep = nat_rep
self.date_format = date_format
def _format_strings(self):
""" we by definition have DO NOT have a TZ """
values = self.values
if not isinstance(values, DatetimeIndex):
values = DatetimeIndex(values)
if self.formatter is not None and callable(self.formatter):
return [self.formatter(x) for x in values]
fmt_values = format_array_from_datetime(
values.asi8.ravel(),
format=_get_format_datetime64_from_values(values,
self.date_format),
na_rep=self.nat_rep).reshape(values.shape)
return fmt_values.tolist()
class IntervalArrayFormatter(GenericArrayFormatter):
def __init__(self, values, *args, **kwargs):
GenericArrayFormatter.__init__(self, values, *args, **kwargs)
def _format_strings(self):
formatter = self.formatter or str
fmt_values = np.array([formatter(x) for x in self.values])
return fmt_values
class PeriodArrayFormatter(IntArrayFormatter):
def _format_strings(self):
from pandas.core.indexes.period import IncompatibleFrequency
try:
values = PeriodIndex(self.values).to_native_types()
except IncompatibleFrequency:
# periods may contains different freq
values = Index(self.values, dtype='object').to_native_types()
formatter = self.formatter or (lambda x: '{x}'.format(x=x))
fmt_values = [formatter(x) for x in values]
return fmt_values
class CategoricalArrayFormatter(GenericArrayFormatter):
def __init__(self, values, *args, **kwargs):
GenericArrayFormatter.__init__(self, values, *args, **kwargs)
def _format_strings(self):
fmt_values = format_array(self.values.get_values(), self.formatter,
float_format=self.float_format,
na_rep=self.na_rep, digits=self.digits,
space=self.space, justify=self.justify)
return fmt_values
def format_percentiles(percentiles):
"""
Outputs rounded and formatted percentiles.
Parameters
----------
percentiles : list-like, containing floats from interval [0,1]
Returns
-------
formatted : list of strings
Notes
-----
Rounding precision is chosen so that: (1) if any two elements of
``percentiles`` differ, they remain different after rounding
(2) no entry is *rounded* to 0% or 100%.
Any non-integer is always rounded to at least 1 decimal place.
Examples
--------
Keeps all entries different after rounding:
>>> format_percentiles([0.01999, 0.02001, 0.5, 0.666666, 0.9999])
['1.999%', '2.001%', '50%', '66.667%', '99.99%']
No element is rounded to 0% or 100% (unless already equal to it).
Duplicates are allowed:
>>> format_percentiles([0, 0.5, 0.02001, 0.5, 0.666666, 0.9999])
['0%', '50%', '2.0%', '50%', '66.67%', '99.99%']
"""
percentiles = np.asarray(percentiles)
# It checks for np.NaN as well
with np.errstate(invalid='ignore'):
if not is_numeric_dtype(percentiles) or not np.all(percentiles >= 0) \
or not np.all(percentiles <= 1):
raise ValueError("percentiles should all be in the interval [0,1]")
percentiles = 100 * percentiles
int_idx = (percentiles.astype(int) == percentiles)
if np.all(int_idx):
out = percentiles.astype(int).astype(str)
return [i + '%' for i in out]
unique_pcts = np.unique(percentiles)
to_begin = unique_pcts[0] if unique_pcts[0] > 0 else None
to_end = 100 - unique_pcts[-1] if unique_pcts[-1] < 100 else None
# Least precision that keeps percentiles unique after rounding
prec = -np.floor(np.log10(np.min(
np.ediff1d(unique_pcts, to_begin=to_begin, to_end=to_end)
))).astype(int)
prec = max(1, prec)
out = np.empty_like(percentiles, dtype=object)
out[int_idx] = percentiles[int_idx].astype(int).astype(str)
out[~int_idx] = percentiles[~int_idx].round(prec).astype(str)
return [i + '%' for i in out]
def _is_dates_only(values):
# return a boolean if we are only dates (and don't have a timezone)
values = DatetimeIndex(values)
if values.tz is not None:
return False
values_int = values.asi8
consider_values = values_int != iNaT
one_day_nanos = (86400 * 1e9)
even_days = np.logical_and(consider_values,
values_int % int(one_day_nanos) != 0).sum() == 0
if even_days:
return True
return False
def _format_datetime64(x, tz=None, nat_rep='NaT'):
if x is None or (is_scalar(x) and isna(x)):
return nat_rep
if tz is not None or not isinstance(x, Timestamp):
x = Timestamp(x, tz=tz)
return str(x)
def _format_datetime64_dateonly(x, nat_rep='NaT', date_format=None):
if x is None or (is_scalar(x) and isna(x)):
return nat_rep
if not isinstance(x, Timestamp):
x = Timestamp(x)
if date_format:
return x.strftime(date_format)
else:
return x._date_repr
def _get_format_datetime64(is_dates_only, nat_rep='NaT', date_format=None):
if is_dates_only:
return lambda x, tz=None: _format_datetime64_dateonly(
x, nat_rep=nat_rep, date_format=date_format)
else:
return lambda x, tz=None: _format_datetime64(x, tz=tz, nat_rep=nat_rep)
def _get_format_datetime64_from_values(values, date_format):
""" given values and a date_format, return a string format """
is_dates_only = _is_dates_only(values)
if is_dates_only:
return date_format or "%Y-%m-%d"
return date_format
class Datetime64TZFormatter(Datetime64Formatter):
def _format_strings(self):
""" we by definition have a TZ """
values = self.values.astype(object)
is_dates_only = _is_dates_only(values)
formatter = (self.formatter or
_get_format_datetime64(is_dates_only,
date_format=self.date_format))
fmt_values = [formatter(x) for x in values]
return fmt_values
class Timedelta64Formatter(GenericArrayFormatter):
def __init__(self, values, nat_rep='NaT', box=False, **kwargs):
super(Timedelta64Formatter, self).__init__(values, **kwargs)
self.nat_rep = nat_rep
self.box = box
def _format_strings(self):
formatter = (self.formatter or
_get_format_timedelta64(self.values, nat_rep=self.nat_rep,
box=self.box))
fmt_values = np.array([formatter(x) for x in self.values])
return fmt_values
def _get_format_timedelta64(values, nat_rep='NaT', box=False):
"""
Return a formatter function for a range of timedeltas.
These will all have the same format argument
If box, then show the return in quotes
"""
values_int = values.astype(np.int64)
consider_values = values_int != iNaT
one_day_nanos = (86400 * 1e9)
even_days = np.logical_and(consider_values,
values_int % one_day_nanos != 0).sum() == 0
all_sub_day = np.logical_and(
consider_values, np.abs(values_int) >= one_day_nanos).sum() == 0
if even_days:
format = None
elif all_sub_day:
format = 'sub_day'
else:
format = 'long'
def _formatter(x):
if x is None or (is_scalar(x) and isna(x)):
return nat_rep
if not isinstance(x, Timedelta):
x = Timedelta(x)
result = x._repr_base(format=format)
if box:
result = "'{res}'".format(res=result)
return result
return _formatter
def _make_fixed_width(strings, justify='right', minimum=None, adj=None):
if len(strings) == 0 or justify == 'all':
return strings
if adj is None:
adj = _get_adjustment()
max_len = max(adj.len(x) for x in strings)
if minimum is not None:
max_len = max(minimum, max_len)
conf_max = get_option("display.max_colwidth")
if conf_max is not None and max_len > conf_max:
max_len = conf_max
def just(x):
if conf_max is not None:
if (conf_max > 3) & (adj.len(x) > max_len):
x = x[:max_len - 3] + '...'
return x
strings = [just(x) for x in strings]
result = adj.justify(strings, max_len, mode=justify)
return result
def _trim_zeros(str_floats, na_rep='NaN'):
"""
Trims zeros, leaving just one before the decimal points if need be.
"""
trimmed = str_floats
def _cond(values):
non_na = [x for x in values if x != na_rep]
return (len(non_na) > 0 and all(x.endswith('0') for x in non_na) and
not (any(('e' in x) or ('E' in x) for x in non_na)))
while _cond(trimmed):
trimmed = [x[:-1] if x != na_rep else x for x in trimmed]
# leave one 0 after the decimal points if need be.
return [x + "0" if x.endswith('.') and x != na_rep else x for x in trimmed]
def _has_names(index):
if isinstance(index, MultiIndex):
return com._any_not_none(*index.names)
else:
return index.name is not None
class EngFormatter(object):
"""
Formats float values according to engineering format.
Based on matplotlib.ticker.EngFormatter
"""
# The SI engineering prefixes
ENG_PREFIXES = {
-24: "y",
-21: "z",
-18: "a",
-15: "f",
-12: "p",
-9: "n",
-6: "u",
-3: "m",
0: "",
3: "k",
6: "M",
9: "G",
12: "T",
15: "P",
18: "E",
21: "Z",
24: "Y"
}
def __init__(self, accuracy=None, use_eng_prefix=False):
self.accuracy = accuracy
self.use_eng_prefix = use_eng_prefix
def __call__(self, num):
""" Formats a number in engineering notation, appending a letter
representing the power of 1000 of the original number. Some examples:
>>> format_eng(0) # for self.accuracy = 0
' 0'
>>> format_eng(1000000) # for self.accuracy = 1,
# self.use_eng_prefix = True
' 1.0M'
>>> format_eng("-1e-6") # for self.accuracy = 2
# self.use_eng_prefix = False
'-1.00E-06'
@param num: the value to represent
@type num: either a numeric value or a string that can be converted to
a numeric value (as per decimal.Decimal constructor)
@return: engineering formatted string
"""
import decimal
import math
dnum = decimal.Decimal(str(num))
if decimal.Decimal.is_nan(dnum):
return 'NaN'
if decimal.Decimal.is_infinite(dnum):
return 'inf'
sign = 1
if dnum < 0: # pragma: no cover
sign = -1
dnum = -dnum
if dnum != 0:
pow10 = decimal.Decimal(int(math.floor(dnum.log10() / 3) * 3))
else:
pow10 = decimal.Decimal(0)
pow10 = pow10.min(max(self.ENG_PREFIXES.keys()))
pow10 = pow10.max(min(self.ENG_PREFIXES.keys()))
int_pow10 = int(pow10)
if self.use_eng_prefix:
prefix = self.ENG_PREFIXES[int_pow10]
else:
if int_pow10 < 0:
prefix = 'E-{pow10:02d}'.format(pow10=-int_pow10)
else:
prefix = 'E+{pow10:02d}'.format(pow10=int_pow10)
mant = sign * dnum / (10**pow10)
if self.accuracy is None: # pragma: no cover
format_str = u("{mant: g}{prefix}")
else:
format_str = (u("{{mant: .{acc:d}f}}{{prefix}}")
.format(acc=self.accuracy))
formatted = format_str.format(mant=mant, prefix=prefix)
return formatted # .strip()
def set_eng_float_format(accuracy=3, use_eng_prefix=False):
"""
Alter default behavior on how float is formatted in DataFrame.
Format float in engineering format. By accuracy, we mean the number of
decimal digits after the floating point.
See also EngFormatter.
"""
set_option("display.float_format", EngFormatter(accuracy, use_eng_prefix))
set_option("display.column_space", max(12, accuracy + 9))
def _binify(cols, line_width):
adjoin_width = 1
bins = []
curr_width = 0
i_last_column = len(cols) - 1
for i, w in enumerate(cols):
w_adjoined = w + adjoin_width
curr_width += w_adjoined
if i_last_column == i:
wrap = curr_width + 1 > line_width and i > 0
else:
wrap = curr_width + 2 > line_width and i > 0
if wrap:
bins.append(i)
curr_width = w_adjoined
bins.append(len(cols))
return bins
def get_level_lengths(levels, sentinel=''):
"""For each index in each level the function returns lengths of indexes.
Parameters
----------
levels : list of lists
List of values on for level.
sentinel : string, optional
Value which states that no new index starts on there.
Returns
----------
Returns list of maps. For each level returns map of indexes (key is index
in row and value is length of index).
"""
if len(levels) == 0:
return []
control = [True for x in levels[0]]
result = []
for level in levels:
last_index = 0
lengths = {}
for i, key in enumerate(level):
if control[i] and key == sentinel:
pass
else:
control[i] = False
lengths[last_index] = i - last_index
last_index = i
lengths[last_index] = len(level) - last_index
result.append(lengths)
return result
def buffer_put_lines(buf, lines):
"""
Appends lines to a buffer.
Parameters
----------
buf
The buffer to write to
lines
The lines to append.
"""
if any(isinstance(x, compat.text_type) for x in lines):
lines = [compat.text_type(x) for x in lines]
buf.write('\n'.join(lines))