.iFUdZddlmZddlmZmZmZmZmZddl m Z ddl m Z ddl mZddlmZddlmZdd lZdd lZdd lmZdd lmZmZmZmZdd lZdd lmZm Z dd l!m"Z"ddl#m$Z$ddl%m&Z&m'Z'm(Z(ddl)m*Z*ddl+m,Z,ddl-m.Z.m/Z/m0Z0m1Z1m2Z2m3Z3ddl4m5Z5m6Z6m7Z7ddl8m9Z9m:Z:ddl;mZ>m?Z?ddl@mAZAdd lBmCcmDZEddlFmGZGmHZHmIZImJZJddlKmLZLddlMmNZNddlOmPZPmQZQddlRmSZSer$ddlTmUZUmVZVmWZWmXZXmYZYmZZZm[Z[m\Z\m]Z]m^Z^m_Z_m`Z`ddlambZbmcZcdZddeed <d!Zfd"Zgdeed#<Gd$d%ZhdNd&ZidNd'ZjGd(d)ZkGd*d+Zl dO dPd,Zme dQ dRd-Zn dS dTd.ZoGd/d0ZpGd1d2epZqGd3d4epZrGd5d6epZsGd7d8epZt dUd9ZudVd:ZvdWdXd;Zw dY dZd<Zx dY d[d=ZyGd>d?esZzGd@dAepZ{ d\ d]dBZ| d^ d_dCZ}d`dadDZ~dbdEZ d` dcdFZdddGZGdHdIZe,dJdedfdKZ dg dhdLZdidMZy )jz Internal module for formatting output data in csv, html, xml, and latex files. This module also applies to display formatting. ) annotations)Callable GeneratorHashableMappingSequence)contextmanager) QUOTE_NONE)Decimal)partial)StringION)get_terminal_size) TYPE_CHECKINGAnyFinalcast) get_option set_option)lib)NA)NaT Timedelta Timestamp)NaTType) set_module)is_complex_dtypeis_float is_integer is_list_likeis_numeric_dtype is_scalar)CategoricalDtypeDatetimeTZDtypeExtensionDtype)isnanotna) Categorical DatetimeArrayExtensionArrayTimedeltaArray) PandasObject)Index MultiIndex PeriodIndex ensure_index) DatetimeIndex)TimedeltaIndex)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 '.' 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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 or bool When an integer value is provided, it sets the border attribute in the opening tag, specifying the thickness of the border. If ``False`` or ``0`` is passed, the border attribute will not be present in the ``
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Nzutf-8z1buf is not a file name and encoding is specified.rrrv)rxnewlinez1buf is not a file name and it has no write method) r3r r}rrhasattrr2open TypeError)r]rxfs rbrrs S!j S !LMMsG C s3x( #sXr : a G   KLL  sA=B$?BB$B!B$c tj|jdrt} t t |}nt |jtrt} t t |}ntj|jdrt} t t|}nut |jtrt} nTtj|jdrt} n-tj|jdrt} nt} |d}| t!d}| t!d}| |||||||||| |  } | j#S) a Format an array for printing. Parameters ---------- values : np.ndarray or ExtensionArray formatter float_format na_rep digits space justify decimal leading_space : bool, optional, default True Whether the array should be formatted with a leading space. When an array as a column of a Series or DataFrame, we do want the leading space to pad between columns. 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Parameters ---------- percentiles : list-like, containing floats from interval [0,1] Returns ------- formatted : list of strings Notes ----- Rounding precision is chosen so that: (1) if any two elements of ``percentiles`` differ, they remain different after rounding (2) no entry is *rounded* to 0% or 100%. Any non-integer is always rounded to at least 1 decimal place. Examples -------- Keeps all entries different after rounding: >>> format_percentiles([0.01999, 0.02001, 0.5, 0.666666, 0.9999]) ['1.999%', '2.001%', '50%', '66.667%', '99.99%'] No element is rounded to 0% or 100% (unless already equal to it). Duplicates are allowed: >>> format_percentiles([0, 0.5, 0.02001, 0.5, 0.666666, 0.9999]) ['0%', '50%', '2.0%', '50%', '66.67%', '99.99%'] rrfz/percentiles should all be in the interval [0,1]dr\r )rhrlrr rr get_precisionroundastyperiiscloserunique empty_liker ) percentilesprecpercentiles_round_typeint_idxoutr; unique_pctss rbformat_percentilesrIsjD ;1 **[)K [ )vvkQ&'vvkQ&'JKK #K  %D(..t4;;C@jj/=G vvg$++C0!$%AC%%))K(K  %D -- 6 2Cw'--/66s;BB3GCL)//5<D t9D HHRXXbffTl+ , 3 3C 8 8D q$.}s4 wK rdct|S)N)r.)rTrSs rbrz'get_format_datetime64..s+Aw?rdr) is_dates_onlyr.rs ``rbget_format_datetime64r]vs   @?rdc eZdZUded<ddZy)rr(rc|jj}|jjt}|jxst ||j }|Dcgc] }|| }}|Scc}w)zwe by definition have a TZ)r)r_is_dates_onlyr?r rEr]r)raidorrEr0rs rbrz&_Datetime64TZFormatter._format_stringssjkk((##F+NN &; T--' -33qil3 34sA2Nrr:rrdrbrrs  rdrcBeZdZUded< d dfd ZddZxZS)rr*rc 4t||fi|||_yr)rrcr.)rarr.rrs rbrcz_Timedelta64Formatter.__init__s *6* rdc|jxs"t|j|jd}|jDcgc] }|| c}Scc}w)NF)r.box)rEget_format_timedelta64rr.)rarEr0s rbrz%_Timedelta64Formatter._format_stringssENN &< KK5' '+kk2 ! 222sAr)rr*r.rrrrr3r$s@rbrrs4    3rdrc@|j}|rdndfd}|S)z Return a formatter function for a range of timedeltas. 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Returns True if all numbers containing decimals (defined by the above regular expression) within the array end in a zero, otherwise returns False. rc3>K|]}|jdyw)rN)rrs rbr1z9_trim_zeros_float..should_trim../s'IA 3'Is)rhr)rr0numbersrs rb should_trimz&_trim_zeros_float..should_trim&sE%B(>q(A1BB7|aIC'I'I$IICs <<NrKrri)rArrayLike | list[str]rr)rzcompiler) str_floatsrr~rr0rrrs @@rbr r sG::!27)7CDL5 J g GNO!3A61Sb6A=OO g   *!,G1DC!KF MPs B'B cvt|trtj|jS|j duSr)r}r-com any_not_nonerZrU)rSs rbrr<s0%$--zz%%rdceZdZdZidddddddd d d d d ddddddddddddddddddd d!d"d#Z d' d(d%Zd)d&Zy$)* EngFormatterzl Formats float values according to engineering format. Based on matplotlib.ticker.EngFormatter iyiziairipiriurrrvrrRrr GrTPEZYNc ||_||_yraccuracyuse_eng_prefix)rarrs rbrczEngFormatter.__init___s! ,rdctt|}tj|rytj|ryd}|dkrd}| }|dk7r>> 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 rPinfrfrrKrzE-02dzE+rz{mant: g}{prefix}z{mant: .rz f}{prefix})mantprefix)r ris_nan is_infiniterimathrOrPrjr: ENG_PREFIXESr rrr^) ranumdnumsignpow10 int_pow10rr format_strrs rb__call__zEngFormatter.__call__es_(s3x  >>$    t $ !8D5D 19C 4::>> 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 r[N)rrrs rbset_eng_float_formatrsD%|Hn'MNrdct|dk(rgSdgt|dz}g}|D]U}d}i}t|D]\}}||r||k(rd||<||z ||<|}!t||z ||<|j|W|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)rhr4r8) levelssentinelcontrolrlevel last_indexlengthsr;keys rbget_level_lengthsrs$ 6{a fs6!9~%G F & FAsqzcXo" &'*n #  "%j:5  g Mrdctd|Dr|Dcgc] }t|}}|jdj|ycc}w)z Appends lines to a buffer. 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