o ŀgO@sUdZddlmZddlmZmZmZmZddlm Z ddl m Z ddl m Z ddlmZddlmZdd lZdd lZdd lmZdd lmZmZmZmZmZdd lZdd lmZm Z dd l!m"Z"ddl#m$Z$ddl%m&Z&m'Z'm(Z(ddl)m*Z*ddl+m,Z,m-Z-m.Z.m/Z/m0Z0m1Z1ddl2m3Z3m4Z4m5Z5ddl6m7Z7m8Z8ddl9m:Z:m;Z;mm?Z?ddl@mAZAdd lBmCmDZEddlFmGZGmHZHmIZImJZJddlKmLZLddlMmNZNddlOmPZPddlQmRZRmSZSddlTmUZUer ddlVmWZWmXZXmYZYmZZZm[Z[m\Z\m]Z]m^Z^m_Z_m`Z`maZambZbddlcmdZdmeZedZfd egd!<d"Zhd#Zid egd$<Gd%d&d&Zjdd)d*Zkdd+d,ZlGd-d.d.ZmGd/d0d0Zn ddd7d8Zoe ddd:d;Zp < = > ? dddRdSZqGdTdUdUZrGdVdWdWerZsGdXdYdYerZtGdZd[d[erZuGd\d]d]erZvdd`daZwddddeZxdddjdkZy f dddmdnZz dddrdsZ{GdtdudueuZ|GdvdwdwerZ} f xddd|d}Z~ = ddddZddddZdddZ >ddddZdddZGdddZddddZ ddddZdddZd S)z Internal module for formatting output data in csv, html, xml, and latex files. This module also applies to display formatting. ) annotations) GeneratorHashableMappingSequence)contextmanager) QUOTE_NONE)Decimal)partial)StringION)get_terminal_size) TYPE_CHECKINGAnyCallableFinalcast) get_option set_option)lib)NA)NaT Timedelta Timestamp)NaTType)is_complex_dtypeis_float is_integer is_list_likeis_numeric_dtype is_scalar)CategoricalDtypeDatetimeTZDtypeExtensionDtype)isnanotna) Categorical DatetimeArrayExtensionArrayTimedeltaArray) StringDtype) PandasObject)Index MultiIndex PeriodIndex ensure_index) DatetimeIndex)TimedeltaIndex)concat)check_parent_directorystringify_path)printing) ArrayLikeAxesColspaceArgType ColspaceTypeCompressionOptionsFilePathFloatFormatTypeFormattersType IndexLabelSequenceNotStrStorageOptions WriteBuffer) DataFrameSeriesa Parameters ---------- buf : str, Path or StringIO-like, optional, default None Buffer to write to. If None, the output is returned as a string. columns : array-like, optional, default None The subset of columns to write. Writes all columns by default. col_space : %(col_space_type)s, optional %(col_space)s. header : %(header_type)s, optional %(header)s. index : bool, optional, default True Whether to print index (row) labels. na_rep : str, optional, default 'NaN' String representation of ``NaN`` to use. formatters : list, tuple or dict of one-param. functions, optional Formatter functions to apply to columns' elements by position or name. The result of each function must be a unicode string. List/tuple must be of length equal to the number of columns. float_format : one-parameter function, optional, default None Formatter function to apply to columns' elements if they are floats. This function must return a unicode string and will be applied only to the non-``NaN`` elements, with ``NaN`` being handled by ``na_rep``. sparsify : bool, optional, default True Set to False for a DataFrame with a hierarchical index to print every multiindex key at each row. index_names : bool, optional, default True Prints the names of the indexes. 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. max_rows : int, optional Maximum number of rows to display in the console. max_cols : int, optional Maximum number of columns to display in the console. show_dimensions : bool, default False Display DataFrame dimensions (number of rows by number of columns). decimal : str, default '.' Character recognized as decimal separator, e.g. ',' in Europe. rcommon_docstring) leftrightcenterjustifyz justify-allstartendinheritz match-parentinitialunsetz Returns ------- str or None If buf is None, returns the result as a string. Otherwise returns None. return_docstringc @sXeZdZdZdddddddddd d$ddZd%ddZd&ddZd'd d!Zd&d"d#ZdS)(SeriesFormatterz\ Implement the main logic of Series.to_string, which underlies Series.__repr__. TNaNFN) lengthheaderindexna_repname float_formatdtypemax_rowsmin_rowsseriesrBrP bool | strrQboolrRrSstrrTrU str | NonerVrW int | NonerXreturnNonec Csj||_t|_||_||_||_||_||_| |_| |_ |dur$t d}||_ ||_ t |_|dS)Ndisplay.float_format)rYr bufrTrSrQrPrRrWrXrrUrVr4get_adjustmentadj _chk_truncate) selfrYrPrQrRrSrTrUrVrWrXrgL/var/www/html/myenv/lib/python3.10/site-packages/pandas/io/formats/format.py__init__s  zSeriesFormatter.__init__cCs||j}|j}|ot|j|k}|j}|rItt|}|r"t||}|dkr0|}|jd|}n|d}t|jd||j| df}||_ nd|_ ||_ ||_ dS)N) rXrWlenrYrintminilocr1 tr_row_num tr_seriesis_truncated_vertically)rfrXrWrrrYrow_numrgrgrhres$  " zSeriesFormatter._chk_truncatecCs0|jj}d}|jj}t|tttfr|jdur|d|j7}|jdur<|dur<|r.|d7}t j |dd}|d|7}|j dusI|j d krY|j rY|rO|d7}|d t |j7}|jdur}|jdur}t|jjd d}|r}|rs|d7}|d t |7}t|jjtr|jj}|r|d 7}||7}t|S)NzFreq: Fz,    ) escape_charszName: TtruncatezLength: rTzdtype: rx)rYrTrR isinstancer/r-r0freqfreqstrr4 pprint_thingrPrrrlrVgetattrrqr _values_get_repr_footerr\)rfrTfooterrR series_name dtype_name level_inforgrgrh _get_footers:   zSeriesFormatter._get_footer list[str]cCst|jjd|j|j|jdS)N)rUrS leading_space) format_arrayrqrrUrSrRrfrgrgrh_get_formatted_values(sz%SeriesFormatter._get_formatted_valuesc Cst|j}|}t|dkrt|jjd|dS|j}t|}t|t r=|j ddd}t }|j dg|Rd}n|jdd}|}|jrd}|j} tt| } |j|| d } | d kred } nd } |jj| g| d dd} || || || d d|jr|jj d g|d d|gR} n|j d |} |jr|r|dd| } |r| d|7} td| S)Nrz([], )T) include_namessparsifyrkrx include_namerj...z..rFmodert)rqrrltyperY__name__rR _has_namesr{r, _format_multir4rcadjoinsplit _format_flatrrrrprrmrdrGinsertrQr\join) rfrYrrR have_header fmt_indexrd fmt_values n_header_rowsrswidthdot_strresultrgrgrh to_string1s>    "  zSeriesFormatter.to_string)rYrBrPrZrQr[rRr[rSr\rTr[rUr]rVr[rWr^rXr^r_r`r_r`r_r\r_r) r __module__ __qualname____doc__rirerrrrgrgrgrhrNs    * rNr_dict[str, Any]cCsLddlm}tdr|\}}nd}tdtdtdtdtd |d S) aGet the parameters used to repr(dataFrame) calls using DataFrame.to_string. Supplying these parameters to DataFrame.to_string is equivalent to calling ``repr(DataFrame)``. This is useful if you want to adjust the repr output. .. versionadded:: 1.4.0 Example ------- >>> import pandas as pd >>> >>> df = pd.DataFrame([[1, 2], [3, 4]]) >>> repr_params = pd.io.formats.format.get_dataframe_repr_params() >>> repr(df) == df.to_string(**repr_params) True r)consolezdisplay.expand_frame_reprNdisplay.max_rowsdisplay.min_rowszdisplay.max_columnsdisplay.max_colwidthdisplay.show_dimensions)rWrXmax_cols max_colwidthshow_dimensions line_width)pandas.io.formatsrrget_console_size)rr_rgrgrhget_dataframe_repr_params_s rcCsJt\}}td}|dkr|n|}|dkr|ntd}dd||tddS)aGet the parameters used to repr(Series) calls using Series.to_string. Supplying these parameters to Series.to_string is equivalent to calling ``repr(series)``. This is useful if you want to adjust the series repr output. .. versionadded:: 1.4.0 Example ------- >>> import pandas as pd >>> >>> ser = pd.Series([1, 2, 3, 4]) >>> repr_params = pd.io.formats.format.get_series_repr_params() >>> repr(ser) == ser.to_string(**repr_params) True rrrTr)rTrVrXrWrP)r r)rheight max_rows_optrWrXrgrgrhget_series_repr_paramss rc@seZdZdZer endZeee7Z                 dtdud(d)Zdvd+d,Zedwd-d.Z edwd/d0Z edwd1d2Z edwd3d4Z edxd5d6Z edwd7d8Zedwd9d:Zedwd;d<Zedwd=d>Zedyd@dAZdzdBdCZd{dEdFZd|dGdHZd}dJdKZd~dMdNZddOdPZddQdRZddSdTZdwdUdVZdwdWdXZdwdYdZZdyd[d\Zdd]d^Zdd_d`Z ddadbZ!dvdcddZ"ddgdhZ#ddkdlZ$ddmdnZ%ddodpZ&ddrdsZ'dS)DataFrameFormatterz Class for processing dataframe formatting options and data. Used by DataFrame.to_string, which backs DataFrame.__repr__. rtNTrOF.framerAcolumns Axes | None col_spaceColspaceArgType | NonerQbool | SequenceNotStr[str]rRr[rSr\ formattersFormattersType | NonerGr]rUFloatFormatType | Noner bool | None index_namesrWr^rXrrrZdecimal bold_rowsescaper_r`cCs||_|||_|||_||_||_||_|||_ | ||_ | |_ | | |_| |_||_||_||_| |_| |_||_||_||_||_|j|_|t|_dSN) r_initialize_columnsr_initialize_colspacerrQrRrS_initialize_formattersr_initialize_justifyrGrU_initialize_sparsifyrshow_index_namesrrrrWrXrr_calc_max_cols_fittedmax_cols_fitted_calc_max_rows_fittedmax_rows_fittedtr_framerzr4rcrd)rfrrrrQrRrSrrGrUrrrWrXrrrrrrgrgrhris.       zDataFrameFormatter.__init__list[list[str]]cCs*|}|jr||j}|d||S)zP Render a DataFrame to a list of columns (as lists of strings). r)_get_strcols_without_indexrR_get_formatted_indexrr)rfstrcols str_indexrgrgrh get_strcolss   zDataFrameFormatter.get_strcolscCs|jdup |jdko |jS)NTrz)r is_truncatedrrgrgrhshould_show_dimensionss z)DataFrameFormatter.should_show_dimensionscCst|jp|jSr)r[is_truncated_horizontallyrrrrgrgrhrszDataFrameFormatter.is_truncatedcCt|jo t|j|jkSr)r[rrlrrrgrgrhrz,DataFrameFormatter.is_truncated_horizontallycCrr)r[rrlrrrgrgrhrrrz*DataFrameFormatter.is_truncated_verticallycCs dt|jdt|jjdS)Nz [z rows x z columns])rlrrrrgrgrhdimensions_infos z"DataFrameFormatter.dimensions_infocC t|jjSr)rrrRrrgrgrhhas_index_names z"DataFrameFormatter.has_index_namescCrr)rrrrrgrgrhhas_column_namesrz#DataFrameFormatter.has_column_namescCt|j|j|jfSr)allrrRrrrgrgrhshow_row_idx_namesz%DataFrameFormatter.show_row_idx_namescCrr)rrrrQrrgrgrhshow_col_idx_namesrz%DataFrameFormatter.show_col_idx_namesrmcCst|jpt|jt|jSr)rnrWrlrrrgrgrhmax_rows_displayed sz%DataFrameFormatter.max_rows_displayedcC|durtdS|S)Nzdisplay.multi_sparser)rfrrgrgrhrsz'DataFrameFormatter._initialize_sparsifyr<cCsP|duriSt|jjt|kst|tr|Stdt|dt|jjd)NzFormatters length(+) should match DataFrame number of columns(r)rlrrr{dict ValueError)rfrrgrgrhrs  z)DataFrameFormatter._initialize_formatterscCr)Nzdisplay.colheader_justifyr)rfrGrgrgrhr sz&DataFrameFormatter._initialize_justifyr+cCs(|durt|}|j||_|S|jjSr)r.rr)rfrcolsrgrgrhr&s  z&DataFrameFormatter._initialize_columnsr8csduri}|Stttfr#di}|fdd|jjD|SttrDD]}||jjvr?|dkr?td|q,}|St |jjt kr_tdt dt |jjdt t |jj}|S)Nrtcsi|]}|qSrgrg).0columnrrgrh 5z;DataFrameFormatter._initialize_colspace..z,Col_space is defined for an unknown column: zCol_space length(rr) r{rmr\updaterrrkeysrrlrzip)rfrrrrgrrhr.s0   z'DataFrameFormatter._initialize_colspacecCs,|s|jSt\}}||r|S|jS)z%Number of columns fitting the screen.)_is_in_terminalrr _is_screen_narrow)rfrrrgrgrhrFs   z(DataFrameFormatter._calc_max_cols_fittedcCsP|r t\}}|jdkr||S||r|}n|j}n|j}||S)z,Number of rows with data fitting the screen.r)rr rW_get_number_of_auxiliary_rows_is_screen_short_adjust_max_rows)rfrrrWrgrgrhrQs     z(DataFrameFormatter._calc_max_rows_fittedcCs(|rt|j|kr|jrt|j|}|S)zAdjust max_rows using display logic. See description here: https://pandas.pydata.org/docs/dev/user_guide/options.html#frequently-used-options GH #37359 )rlrrXrn)rfrWrgrgrhrds z#DataFrameFormatter._adjust_max_rowscCst|jdkp |jdkS)z/Check if the output is to be shown in terminal.r)r[rrWrrgrgrhrrsz"DataFrameFormatter._is_in_terminalcCst|jdko t|jj|kSNr)r[rrlrr)rf max_widthrgrgrhrvsz$DataFrameFormatter._is_screen_narrowcCst|jdko t|j|kSr)r[rWrlr)rf max_heightrgrgrhrysz#DataFrameFormatter._is_screen_shortcCs:d}d}||}|jr|t|j7}|jr|d7}|S)z?Get number of rows occupied by prompt, dots and dimension info.rj)rrlr splitlinesrQ)rfdot_row prompt_rownum_rowsrgrgrhr|sz0DataFrameFormatter._get_number_of_auxiliary_rowscCs$|jr||jr|dSdS)zY Check whether the frame should be truncated. If so, slice the frame up. N)r_truncate_horizontallyrr_truncate_verticallyrrgrgrhrzs  zDataFrameFormatter.truncatecCs|jdusJ|jd}|dkrM|jjddd|f}|jjdd| df}t||fdd|_t|jttfrLg|jd||j| d|_ntt |j }|jjddd|f|_||_ dS)zRemove columns, which are not to be displayed and adjust formatters. Attributes affected: - tr_frame - formatters - tr_col_num Nrkrjaxis) rrror1r{rlisttuplerrmr tr_col_num)rfcol_numrDrErgrgrhr s     z)DataFrameFormatter._truncate_horizontallycCs|jdusJ|jd}|dkr-t|j}tt|t|||g}|jj||_ntt|j }|jjd|ddf|_||_ dS)zRemove rows, which are not to be displayed. Attributes affected: - tr_frame - tr_row_num Nrkrj) rrlrnphstackarangerorrmrWrp)rfrs_len_slicergrgrhr s     z'DataFrameFormatter._truncate_verticallyc sg}tjs1js1tjD]\}}|}t|jtj |dj d}| |q|Stjrct t tj_tjtjkrZtdtjdtjdddjD}nj}jrv|D]}| dqntjD]N\}}||}ttj |dgfd d |DR}|}t|j|j d }tgfd d |D|R} j j|| jd }| ||q{|S)Nr)stringsrGminimumrdzWriting z cols but got z aliasescSsg|]}|gqSrgrg)rlabelrgrgrh rzADataFrameFormatter._get_strcols_without_index..rtc3|] }j|VqdSrrdrlrxrrgrh z@DataFrameFormatter._get_strcols_without_index..)rrdc3rrrrrrgrhrrr)rrQ enumerater format_col_make_fixed_widthrGrmrgetrdappendrr r\rlrr_get_formatted_column_labelsrmax) rfricr str_columnsrcheaderheader_colwidthmax_lenrgrrhrsP        z-DataFrameFormatter._get_strcols_without_indexr'rc CsL|j}||}t|jdd|fj||j|j|j|j ||j |j dS)N)rUrSspacerr) r_get_formatterrrorrUrSrr#rrrR)rfr'r formatterrgrgrhr!s zDataFrameFormatter.format_col str | intCallable | NonecCsZt|jttfrt|rtt|}|j|SdSt|r&||jvr&|j|}|j|dSr) r{rr rrrrmrr#)rfr'rgrgrhr.s   z!DataFrameFormatter._get_formattercsddlm}|j}t|tr_|jddd}tt|}jj j }t dd|j Dt t|tt|fddttfd d|D}jrTt|rT||}d d t|D}|S|jdd }jj }t t|tt|fd d t|D}|S)Nr)sparsify_labelsF)rrcss|]}|jVqdSr) is_floating)rlevelrgrgrhrszBDataFrameFormatter._get_formatted_column_labels..cs"|jvr|rsd|S|S)N )r)ry) need_leadsprestrict_formattingrfrgrh space_formats zEDataFrameFormatter._get_formatted_column_labels..space_formatc3s$|] fddDVqdS)csg|]}|qSrgrg)rr6)r9rrgrhr zMDataFrameFormatter._get_formatted_column_labels...Nrg)r)r9rrhr s"cSg|]}t|qSrg)r rrgrgrhr%zCDataFrameFormatter._get_formatted_column_labels..rcs0g|]\}}|s|rd|n|gqS)r5)r.)rr'r)r7rfrgrhr*s)pandas.core.indexes.multir2rr{r,rr rrdtypesranylevelsrmaprrrlrr )rfrr2r fmt_columnsr?str_columns_tupler)rg)r7r8rfr9rhr%s.       z/DataFrameFormatter._get_formatted_column_labelscsddjD|j}|j}d}t|tr%|jjj |d}n |j j |dg}fdd|D}j j dg|R d }jrRd dD}nd g|j}jr_||S|S) NcSsi|] \}}|tt|qSrg)rrm)rkvrgrgrhr4sz;DataFrameFormatter._get_formatted_index.. __index__)rrr/)rr/c s.g|]}ttt|dddjdqS)rDrtr)rGrrd)rr"r r#rdrrrfrgrhrDsz;DataFrameFormatter._get_formatted_index..rjrxcSr<rgr\rrgrgrhrQr=rt)ritemsrRrr.r{r,rrrrrdrrr_get_column_name_listnlevelsrQ)rfrrRrfmtradjoined col_headerrgrHrhr1s,     z'DataFrameFormatter._get_formatted_indexlist[Hashable]cCsNg}|jj}t|tr|dd|jD|S||jdur!dn|j|S)Ncss |] }|dur dn|VqdS)Nrtrg)rrTrgrgrhr^sz;DataFrameFormatter._get_column_name_list..rt)rrr{r,extendnamesr$rT)rfrRrrgrgrhrKZs z(DataFrameFormatter._get_column_name_list)NNTTrONNNNTNNNFrFT)&rrArrrrrQrrRr[rSr\rrrGr]rUrrrrr[rWr^rXr^rr^rrZrr\rr[rr[r_r`)r_rr_r[r)r_rm)rrr_r[)rrr_r<)rGr]r_r\)rrr_r+)rrr_r8)r_r^)rWr^r_r^r)r'rmr_r)r'r0r_r1)rrAr_r)rrAr_r)r_rP)(rrrrrCrMrirpropertyrrrrrrrrrrrrrrrrrrrrrrrrzr r rr!r.r%rrKrgrgrgrhrs   /                        / ))rc@sreZdZdZd9ddZ      d:d;ddZ   dd?d7d8ZdS)@DataFrameRendereraJClass for creating dataframe output in multiple formats. Called in pandas.core.generic.NDFrame: - to_csv - to_latex Called in pandas.core.frame.DataFrame: - to_html - to_string Parameters ---------- fmt : DataFrameFormatter Formatter with the formatting options. rMrr_r`cCs ||_dSr)rM)rfrMrgrgrhrius zDataFrameRenderer.__init__NFrb"FilePath | WriteBuffer[str] | Noneencodingr]classesstr | list | tuple | Nonenotebookr[borderint | bool | Nonetable_id render_linksc CsFddlm}m} |r | n|} | |j||||d} | } t| ||dS)uJ Render a DataFrame to a html table. Parameters ---------- buf : str, path object, file-like object, or None, default None String, path object (implementing ``os.PathLike[str]``), or file-like object implementing a string ``write()`` function. If None, the result is returned as a string. encoding : str, default “utf-8” Set character encoding. classes : str or list-like classes to include in the `class` attribute of the opening ```` 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 ``
`` tag. Default ``pd.options.display.html.border``. table_id : str, optional A css id is included in the opening `
` tag if specified. render_links : bool, default False Convert URLs to HTML links. r) HTMLFormatterNotebookFormatter)rXr[r]r^rbrW)pandas.io.formats.htmlr_r`rMrsave_to_buffer) rfrbrWrXrZr[r]r^r_r`Klasshtml_formatterstringrgrgrhto_htmlxs" zDataFrameRenderer.to_htmlrr^cCs0ddlm}||j|d}|}t|||dS)u% Render a DataFrame to a console-friendly tabular output. Parameters ---------- buf : str, path object, file-like object, or None, default None String, path object (implementing ``os.PathLike[str]``), or file-like object implementing a string ``write()`` function. If None, the result is returned as a string. encoding: str, default “utf-8” Set character encoding. line_width : int, optional Width to wrap a line in characters. r)StringFormatter)rra)pandas.io.formats.stringrhrMrrc)rfrbrWrrhstring_formatterrfrgrgrhrs zDataFrameRenderer.to_string,winfer"Tstrict path_or_buf7FilePath | WriteBuffer[bytes] | WriteBuffer[str] | Nonesepr\rSequence[Hashable] | None index_labelIndexLabel | Noner compressionr9quoting quotecharlineterminator chunksize date_format doublequote escapecharerrorsstorage_optionsStorageOptions | NonecCsddlm}|durd}t}nd}|did|d| d|d |d |d |d |d |d|d|d| d| d| d| d|d|d|j}||rbt|tsXJ|}||SdS)z; Render dataframe as comma-separated file. r) CSVFormatterNTFrpryrrrWr~rvrwrrtrrzrxr{r|r}rr/rg)pandas.io.formats.csvsrr rMsaver{getvalueclose)rfrprWrrrrtrrvrwrxryrzr{r|r}r~rrcreated_buffer csv_formattercontentrgrgrhto_csvs^      zDataFrameRenderer.to_csv)rMrr_r`)NNNFNNF)rbrVrWr]rXrYrZr[r[r\r]r]r^r[r_r])NNN)rbrVrWr]rr^r_r])NNrkNNrlrmNrnNNNTNroN)"rprqrWr]rrr\rrsrtrurr\rvr9rwr^rxr\ryr]rzr^r{r]r|r[r}r]r~r\rrr_r])rrrrrirgrrrgrgrgrhrUds@  5 rUrfr\rbrVrWr]cCs\t||d}|||dur|WdS WddS1s'wYdS)zQ Perform serialization. Write to buf or return as string if buf is None. )rWN) _get_bufferwriter)rfrbrWfdrgrgrhrcs $rcIGenerator[WriteBuffer[str], None, None] | Generator[StringIO, None, None]ccs|dur t|}nt}|durd}n t|tstdt|dr'|VdSt|trPtt|t|d|dd }|VWddS1sIwYdStd) z Context manager to open, yield and close buffer for filenames or Path-like objects, otherwise yield buf unchanged. Nzutf-8z1buf is not a file name and encoding is specified.rrlrt)rWnewlinez1buf is not a file name and it has no write method) r3r r{r\rhasattrr2open TypeError)rbrWfrgrgrhrs       "rrOrErTvaluesr5r/r1rUrrSdigitsr^r-str | int | NonerGrrrrwfallback_formatterrc Cst|jdrt} tt|}nsz8_GenericArrayFormatter._format_strings..ru)ry quote_stringscsjdur;t|r;t|r;|durdS|turttSt|r)t|r)t|S|t us6t |tj tj fr8dSjSt |t rDt|St |trMt|St|S)Nr`r)rSrr#rr\rrrisinfrr{ datetime64 timedelta64r*r)reprr;)r/rfrgrh_formats   z7_GenericArrayFormatter._format_strings.._formatz=ExtensionArray formatting should use _ExtensionArrayFormatterrjr r5Fz{v}z {v}rF)rUrr/rrwrr r4r~rr{rndarrayrr map_inferrrr$rrangerlshaperr@r r$format) rfrUrrvalsinferred is_float_typerrr'rFtplrg)r/rrfrhrsT       z&_GenericArrayFormatter._format_strings) rNrOrNrErNTTN)rr5rrmr/r1rSr\r-r0rUrrGr\rr\rwr^rr[rrrr1r_r`r)rrrrirrrgrgrgrhrs rcsBeZdZdfdd Z  ddd d ZdddZdddZZS)rr_r`csTtj|i||jdur$|jdur&d|_t|jr(|j|_d|_dSdSdSdSNF)superrirUr/rcallable)rfargskwargs __class__rgrhris  zFloatArrayFormatter.__init__NrUr threshold float | Nonercsldurjrfddnfddjdkr$fddndur,Sfdd }|S) z;Returns a function to be applied on each value to format itNcs$dusJt|r|dSjS)Nvalue)r$rSr)rUrfrgrhbase_formatters  z.base_formattercst|rt|SjSr)r$r\rSrrrgrhr&srcs|djdS)Nrrj)replacerr)rrfrgrhdecimal_formatter+sz?FloatArrayFormatter._value_formatter..decimal_formattercs*t|rt|kr|SdSjS)Ng)r$absrSr)rrfrrgrhr/4s  z7FloatArrayFormatter._value_formatter..formatter)rUr)rfrUrr/rg)rrrUrfrrh_value_formatters  z$FloatArrayFormatter._value_formatter np.ndarrayc sTddddd d jd urjjjSjr td nd fd d}jd urJjrFjdur;d}nd}t|jj d}n j}nfdd}||}jsY|St |dkrpt dd|D}|j dk}nd}t j}|dk}|dj k|dk@} | s|r|rjdurd}nd}t|jj d}||}|S)z Returns the float values converted into strings using the parameters given at initialisation, as a numpy array rr5r/rrSr\cs<t|}tfddt||D|j}|S)Ncs g|] \}}|s |nqSrgrg)rvalrr/rSrgrhrHszWFloatArrayFormatter.get_result_as_array..format_with_na_rep..)r#rarrayrravelreshaper)rr/rSmask formattedrgrrhformat_with_na_repEs zCFloatArrayFormatter.get_result_as_array..format_with_na_repcSst|}t|}t|t|}}g}t|||||D]R\}} } } } | s6| s6|||q#| sF||| d|dq#| sj|| } | dr^||| dq#||d| dq#||d|dq#t | |j S)N+j-) rrealrimagr#rr$strip startswithrrr)rr/rS real_values imag_values real_mask imag_mask formatted_lstrreal_valimag_valre_isnaim_isnaimag_formattedrgrgrhformat_complex_with_na_repOs,  zKFloatArrayFormatter.get_result_as_array..format_complex_with_na_repNzdisplay.chop_thresholdcs|}jdkrdjnj}j}t|}|r#|||}n|||}jrB|r5t|j}nt|j}t j |ddS|S)NrDr5objectrV) rrGrSrrr_trim_zeros_complexr_trim_zeros_floatrasarray)rUr/rSr is_complexrrrrfrrgrhformat_values_withus   zCFloatArrayFormatter.get_result_as_array..format_values_withTz{value: .{digits:d}f}z{value:.{digits:d}f})rcs j|Sr)rUrrrgrhrs z9FloatArrayFormatter.get_result_as_array..rcs|]}t|VqdSrrlrrgrgrhrz:FloatArrayFormatter.get_result_as_array..Fg.A z{value: .{digits:d}e}z{value:.{digits:d}e})rr5r/rrSr\)r/rrSrrrUrr rrrlr&rrr@) rfrfmt_strrUformatted_valuesmaxlentoo_longabs_valshas_large_valueshas_small_valuesrgrrhget_result_as_array?sB           z'FloatArrayFormatter.get_result_as_arrayrcCs t|Sr)r rrrgrgrhrs z#FloatArrayFormatter._format_stringsrNN)rUrrrr_r)r_rr)rrrrirrr __classcell__rgrgrrhrs 8rc@seZdZdddZdS)rr_rcs>|jdur dd}ndd}|jp|fdd|jD}|S)NFcS|dj|dS)Nrr;rr;rgrgrhrz4_IntArrayFormatter._format_strings..cSr)Nz dr;rr;rgrgrhrrcg|]}|qSrgrgrr/rgrhrr=z6_IntArrayFormatter._format_strings..)rr/r)rf formatter_strrrgrrhrs   z"_IntArrayFormatter._format_stringsNr)rrrrrgrgrgrhrsrcs8eZdZUded<  ddfd d Zdd dZZS)rr&rrNnat_repr\r{r`r_c s$tj|fi|||_||_dSr)rrirr{)rfrrr{rrrgrhris z_Datetime64Formatter.__init__rcs<j}jdurfdd|DS|jjjd}|S)z&we by definition have DO NOT have a TZNcsg|]}|qSrgrrrrgrhrr:z8_Datetime64Formatter._format_strings..)rSr{)rr/_format_native_typesrr{tolist)rfrrrgrrhrs z$_Datetime64Formatter._format_stringsrN)rr&rr\r{r`r_r`rrrr__annotations__rirrrgrgrrhrs  rc@ eZdZUded<dddZdS) rr'rr_rc Csx|j}|j}d}|dur|jdd}t|tr|}ntj|td}t |||j |j |j |j |j|j|j|j|d }|S)NT)boxedr) rUrSrr-rGrrrwr)rr/ _formatterr{r%_internal_get_valuesrrrrrUrSrr-rGrrrw)rfrr/rrrrgrgrhrs,    z(_ExtensionArrayFormatter._format_stringsNrrrrr rrgrgrgrhr r percentilesnp.ndarray | Sequence[float]cCst|}t|rt|dkrt|dkstdd|}t|}||t}t ||}t|rB|t }dd|DSt |}t|}tj |t d}||tt ||<|||t ||<dd|DS) a 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%'] rrjz/percentiles should all be in the interval [0,1]dcSg|]}|dqS%rgrr'rgrgrhr>r=z&format_percentiles..rcSrrrgrrgrgrhrFr=)rrrrr get_precisionroundastypermiscloser\unique empty_liker)rprecpercentiles_round_typeint_idxout unique_pctsrgrgrhformat_percentiles s* "      r%rrmcCsx|ddkr |dnd}|ddkrd|dnd}tj|||d}t|}ttt|t }td|}|S)Nrr)to_beginto_endrj) rediff1drfloorlog10rnrrmr&)rr'r(diffr rgrgrhrIs rrrNaTType | TimestamprcCs|tur|St|Sr)rr\)rrrgrgrh_format_datetime64Ssr.r{cCs"t|tr|S|r||S|jSr)r{rstrftime _date_repr)rrr{rgrgrh_format_datetime64_dateonly\s  r1 is_dates_onlyr[rcs|r fddSfddS)z]Return a formatter callable taking a datetime64 as input and providing a string as outputcst|dS)N)rr{)r1r;r{rrgrhrrsz'get_format_datetime64..cs t|dS)Nr)r.r;r4rgrhrvs rg)r2rr{rgr3rhget_format_datetime64ks r5c@r ) rr&rr_rcs>|jj}|jt}|jpt||jdfdd|D}|S)zwe by definition have a TZ)r{crrgrgrrrgrhrr=z:_Datetime64TZFormatter._format_strings..)r_is_dates_onlyrrr/r5r{)rfidorrrgrrhr|s z&_Datetime64TZFormatter._format_stringsNrrrgrgrgrhryrrcs6eZdZUded< d dfdd Zdd d ZZS)rr(rrrr\r_r`c stj|fi|||_dSr)rrir)rfrrrrrgrhris z_Timedelta64Formatter.__init__rcs,|jp t|j|jddfdd|jDS)NF)rboxcrrgrgrrrgrhrr=z9_Timedelta64Formatter._format_strings..)r/get_format_timedelta64rrrrgrrhrs z%_Timedelta64Formatter._format_stringsr)rr(rr\r_r`rr rgrgrrhrs  rFr( str | floatr8cs(|j}|rdndfdd}|S)z 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 NlongcsN|dus t|rt|rSt|tst|}|jd}r%d|d}|S)Nr')rr#r{r _repr_base)rrr8rrrgrhrs   z*get_format_timedelta64.._formatter)r6)rrr8 even_daysrrgr?rhr9s   r9rrrdprinting._TextAdjustment | Nonecst|dks |dkr |S|durtn|tfdd|D|dur+t|tddur9kr9dfd d fd d |D}j||d }|S)Nrrc3s|]}|VqdSrrr) adjustmentrgrhrz$_make_fixed_width..rrr\r_cs6durdk|k@r|ddd}|S)Nrrrr;)rBconf_maxr,rgrhjustsz_make_fixed_width..justcrrgrgr)rErgrhrr=z%_make_fixed_width..r)rr\r_r\)rlr4rcr&rrG)rrGrrdrrg)rBrDrEr,rhr"s  r" str_complexesc sgg}}|D] }td|}|d|dd|d|ddqt|}t|||}t|dkr;gStdd|Dd fd d t|d|||dD}|S) z Separates the real and imaginary parts from the complex number, and executes the _trim_zeros_float method on each of those. z([j+-])rtNrcsrrr)rpartrgrgrhrrz&_trim_zeros_complex..rjcs6g|]\}}||d|ddddqS)rrjN>rrg)rreal_ptimag_pt padded_lengthrgrhrsz'_trim_zeros_complex..)rerr$rrlrr&r) rFr real_part imag_partrtrimmedn padded_partspaddedrgrMrhrs    r str_floatcCs |d}|dr|d7}|S)zX Trims trailing zeros after a decimal point, leaving just one if necessary. 0r)rstripendswith)rVrgrgrhrs  r str_floatsArrayLike | list[str]csl|}tdddfdd dfd d }||r*fd d |D}||sfd d |D}|S)z Trims the maximum number of trailing zeros equally from all numbers containing decimals, leaving just one if necessary. z^\s*[\+-]?[0-9]+\z[0-9]*$r_r[cst|duSr)rOmatchr;) number_regexrgrhis_number_with_decimalsz1_trim_zeros_float..is_number_with_decimalrr[cs0fdd|D}t|dkotdd|DS)z Determine if an array of strings should be trimmed. Returns True if all numbers containing decimals (defined by the above regular expression) within the array end in a zero, otherwise returns False. csg|]}|r|qSrgrgrr^rgrhr#sz:_trim_zeros_float..should_trim..rcss|]}|dVqdS)rWNrYrrgrgrhr$rCz9_trim_zeros_float..should_trim..)rlr)rnumbersr_rgrh should_trimsz&_trim_zeros_float..should_trimcs$g|]}|r|ddn|qS)Nr&rgrr_rgrhr's$z%_trim_zeros_float..cs*g|]}|r|r|dn|qS)rWr`r)rr^rgrhr*sNrS)rr[r_r[)rOcompile)rZrrRrbrrg)rr^r]rhr s  rrRr+cCs t|tr tj|jS|jduSr)r{r,com any_not_nonerRrT)rRrgrgrhr1s   rc@seZdZdZidddddddd d d d d ddddddddddddddddddd d!d"d#Z %d3d4d,d-Zd5d1d2Zd$S)6 EngFormatterzl Formats float values according to engineering format. Based on matplotlib.ticker.EngFormatter ir6iziairipirSiurrrtrrErr GrTPEZYNFaccuracyr^use_eng_prefixr[r_r`cCs||_||_dSrrwrx)rfrwrxrgrgrhriTs zEngFormatter.__init__numfloatr\c Cstt|}t|r dSt|rdSd}|dkrd}| }|dkr3ttt|dd}ntd}|t |j }| t|j }t|}|j rX|j |}n|dkrdd| d}nd |d}||d |}|j d urzd }nd |j dd}|j||d} | S)a Formats a number in engineering notation, appending a letter representing the power of 1000 of the original number. Some examples: >>> format_eng = EngFormatter(accuracy=0, use_eng_prefix=True) >>> format_eng(0) ' 0' >>> format_eng = EngFormatter(accuracy=1, use_eng_prefix=True) >>> format_eng(1_000_000) ' 1.0M' >>> format_eng = EngFormatter(accuracy=2, use_eng_prefix=False) >>> format_eng("-1e-6") '-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 rOinfrjrr&rzE-02dzE+rNz{mant: g}{prefix}z{mant: .rz f}{prefix})mantprefix)r r\is_nan is_infinitermmathr*r+rnr& ENG_PREFIXESrrxrwr) rfrzdnumsignpow10 int_pow10rr~ format_strrrgrgrh__call__Zs4       zEngFormatter.__call__r)rwr^rxr[r_r`)rzr{r_r\)rrrrrrirrgrgrgrhrf8sP      rfrrwrxr`cCstdt||dS)a Format float representation in DataFrame with SI notation. Parameters ---------- accuracy : int, default 3 Number of decimal digits after the floating point. use_eng_prefix : bool, default False Whether to represent a value with SI prefixes. Returns ------- None Examples -------- >>> df = pd.DataFrame([1e-9, 1e-3, 1, 1e3, 1e6]) >>> df 0 0 1.000000e-09 1 1.000000e-03 2 1.000000e+00 3 1.000000e+03 4 1.000000e+06 >>> pd.set_eng_float_format(accuracy=1) >>> df 0 0 1.0E-09 1 1.0E-03 2 1.0E+00 3 1.0E+03 4 1.0E+06 >>> pd.set_eng_float_format(use_eng_prefix=True) >>> df 0 0 1.000n 1 1.000m 2 1.000 3 1.000k 4 1.000M >>> pd.set_eng_float_format(accuracy=1, use_eng_prefix=True) >>> df 0 0 1.0n 1 1.0m 2 1.0 3 1.0k 4 1.0M >>> pd.set_option("display.float_format", None) # unset option raN)rrfryrgrgrhset_eng_float_formats7rrtrArsentinelbool | object | strlist[dict[int, int]]c Cst|dkrgSdgt|d}g}|D]1}d}i}t|D]\}}||r,||kr,qd||<||||<|}qt||||<||q|S)a 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). rTF)rlr r$) rArcontrolrr4 last_indexlengthsr'keyrgrgrhget_level_lengthss   rWriteBuffer[str]linescCs4tdd|Drdd|D}|d|dS)z Appends lines to a buffer. Parameters ---------- buf The buffer to write to lines The lines to append. css|]}t|tVqdSr)r{r\rrgrgrhrrCz#buffer_put_lines..cSr<rgrIrrgrgrhr r=z$buffer_put_lines..rxN)r@rr)rbrrgrgrhbuffer_put_liness r)r_rr)rfr\rbrVrWr]r_r]r)rbrVrWr]r_r) NrONNrErTNN)rr5r/r1rUrrSr\rr^r-rrGr\rr\rrrwr^rr1r_r)rrr_r)rrr_rmr:)rr-rr\r_r\r )rr-rr\r{r]r_r\)r2r[rr\r{r]r_r)rF)rr(rr;r8r[r_r)rENN) rrrGr\rr^rdrAr_r)r)rFr5rr\r_r)rVr\r_r\)rZr[rr\r_r)rRr+r_r[)rF)rwrmrxr[r_r`)rt)rArrrr_r)rbrrrr_r`)r __future__rcollections.abcrrrr contextlibrcsvrrr functoolsr ior rrOshutilr typingr rrrrnumpyrpandas._config.configrr pandas._libsrpandas._libs.missingrpandas._libs.tslibsrrrpandas._libs.tslibs.nattyperpandas.core.dtypes.commonrrrrrrpandas.core.dtypes.dtypesr r!r"pandas.core.dtypes.missingr#r$pandas.core.arraysr%r&r'r(pandas.core.arrays.string_r)pandas.core.baser*pandas.core.commoncorecommonrdpandas.core.indexes.apir+r,r-r.pandas.core.indexes.datetimesr/pandas.core.indexes.timedeltasr0pandas.core.reshape.concatr1pandas.io.commonr2r3rr4pandas._typingr5r6r7r8r9r:r;r<r=r>r?r@pandasrArBrCr VALID_JUSTIFY_PARAMETERSrMrNrrrrUrcrrrrrrrr%rr.r1r5rrr9r"rrrrrfrrrrgrgrgrhs                 8 8   # !H  ( UnJ  ! ?     $ " ! $ `; +