eCibSSKJr SSKrSSKrSSKJr SSKJr SSKJrJ r J r SSK J r SSK J r SSKrSSKrSSKrSSKJr SS KJrJr SS KJrJrJrJrJrJr "S S 5r "S S\ 5r!"SS\ 5r""SS\ 5r#"SS5r$"SS\5r%SSjr&SSjr'Sr(Sr)SSjr*g)) annotationsNcopy) UserString)IterableSequenceMapping)Number)datetime)PlotData) QUAL_PALETTES color_palette)_check_argument_version_predates desaturatelocator_to_legend_entriesget_color_cycle remove_nacH\rSrSr%SrSrS\S'SrSrSr Sr Sr S r S r g) SemanticMappingz6Base class for mapping data values to plot attributes.Nz str | Nonemap_typecXlgNplotter)selfrs G/home/james-whalen/.local/lib/python3.13/site-packages/seaborn/_base.py__init__SemanticMapping.__init__+s  cSn[U5[U5:afSRSUS[U5S3S[U5S3S/5n[U[R"U55VVs/sHupVUPM nnnOV[U5[U5:a>SRS US [U5S3S[U5S 3/5nUS [U5nU(a[ R "U[S S9 U$s snnf)z/Input check when values are provided as a list. z The z list has fewer values ()z than needed (z) and will cycle, which mayz produce an uninterpretable plot.The z list has more values (z), which may not be intended.N stacklevel)lenjoinzip itertoolscyclewarningswarn UserWarning)rlevelsvaluesvariablemessage_xs r_check_list_length"SemanticMapping._check_list_length4s v;V $hh ":3v;-qIF },GH2 G %( 0G$HI$HDAa$HFIF [3v; &hhxj 7F }AFF },IJ GLS[)F  MM';1 = Js/C:c URU$)z)Apply the mapping to a single data value. lookup_table)rkeys r_lookup_singleSemanticMapping._lookup_singleLs  %%r!c[U[[R[R 45(a&UVs/sHo@R "U/UQ70UD6PM sn$UR "U/UQ70UD6$s snf)z-Get the attribute(s) values for the data key.) isinstancelistnpndarraypdSeriesr>)rr=argskwargsks r__call__SemanticMapping.__call__Psg cD"**bii8 9 9EHIS'';D;F;SI I&&srJ__static_attributes__r!rrrs3@  HjFL0&=r!rcV^\rSrSrSrSrSrSrS U4SjjrSr Sr Sr Sr S r U=r$) HueMappingXz9Mapping that sets artist colors according to data values.Nc>[T U]U5 URRS[R "[ S95n[U[R5(a'Sn[R"USS9 UR5nUR5R5(aUbSn[R"USS9 ggURX$UR UR"S5nUS:Xa,[R$"U5nUR'XbU5uppKO>US :XaS=pUR)XbU5upO S=pUR)[+U5X#5upXPlXlXlX lXlX@lXlg) zoMap the levels of the `hue` variable to distinct colors. Parameters ---------- # TODO add generic parameters huedtypez|Numpy array is not a supported type for `palette`. Please convert your palette to a list. This will become an error in v0.14r(Nz?Ignoring `palette` because no `hue` variable has been assigned.numeric categorical)superr plot_datagetrErFfloatrArCrDr/r0tolistisnaallinfer_map_type input_format var_types to_numericnumeric_mappingcategorical_mappingrB saturationrr<paletter2normcmap) rrrlorderrmrkdatamsgrr2r<rn __class__s rrHueMapping.__init__css !  $$UBIIE,BC grzz * *5  MM#! ,nn&G 99;??  "W ca0# **w33W5F5Fu5MH9$}}T*373G3G440dD ]*""'+'?'?5($ #"'+'?'?J($ )O$M , "L KIIr!cURUnURS:a[X R5nU$![a URcgURU5n[RR U5(a[R nURU5nN![a*n[R"U5(aSnSnANUeSnAff=ff=f)z@Get the color for a single value, using colormap to interpolate.N)rrrr) r<KeyErrorrmrCma is_maskednanrn TypeErrorisnanrkr)rr=valuenormederrs rr>HueMapping._lookup_singles *%%c*E. ??Q uoo6E 3 *yy $ *355??6**VVF &) 88C==(EI   *s:8C"B*#AC"* C4CC"CCC"cU[;aSnU$UbSnU$[U[[45(aSnU$US:XaSnU$UnU$)z'Determine how to implement the mapping.r]r\wide)r rAdictrB)rrlrmrfvar_typers rreHueMapping.infer_map_typesk m #$H  H$ . .$H  V #$H Hr!c[X5n[U5n[U[5(aH[ U5[ U5- n[ U5(aSn[ URU55eUnXH4$Uc1U[[55::a [SU5n O@[SU5n O3[U[5(aURXBS5n O [X%5n [[XI55nXH4$)z5Determine colors when the hue mapping is categorical.z*The palette dictionary is missing keys: {}Nhuslrl) categorical_orderr*rArsetany ValueErrorformatrrrBr8r,) rrprlror2n_colorsmissingr~r<colorss rrjHueMapping.categorical_mappings#4/v; gt $ $&kCL0G7||B G!455"L ##s?#455*4:F*68L "'')DKKM":; ?@LT//E;sG)rnr2r<rrmrlrkNNNru)rLrMrNrOrPrlrmrnrr>rerjrirR __classcell__rrs@rrUrUXsBCG D DHIHT@  $D)0)0r!rUcN^\rSrSrSrSrS U4SjjrSrSrSr Sr S r U=r $) SizeMappingi*z8Mapping that sets artist sizes according to data values.Nc>[T U]U5 URRS[R "[ S95nUR5R5(aURXBURS5nUS:XaURXRU5upxpIOSizeMapping._lookup_singlers J%%c*E   JYYs^Fuuv&&OOA&"&&2I)IIE  JsBBBc[X5n[U[5(aJ[U5[U5- n[ U5(aSU3n[ U5eUR 5nXG4$[U[5(a)URXBS5n[[XB55nXG4$[U[5(a[U5S:wa Sn[ U5eO)UbSU3n[ U5eURRn[R"/UQ[U5P76SSS2n[[XB55nXG4$)Nz(Missing sizes for the following levels: r'A `sizes` tuple must have only 2 values"Value for `sizes` not understood: )rrArrrrrrBr8r,rr*r_default_size_rangerClinspace)rrprror2rr~r<s rrjSizeMapping.categorical_mapping}s?"4/ eT " "&kCJ.G7||@ J o% ::rjrirRrrs@rrr*s2B D596-p  8$tM6M6r!rcD^\rSrSrSrSrSU4SjjrS SjrSrSr U=r $) StyleMappingiz8Mapping that sets artist style according to data values.r]c >[TU]U5 URRS[R "[ S95nUR5R5(Ga[U5S:Xa [U5n[XT5nURX&[[U55S5nURX6[[U55S5n0n/nUR!5Hup[#U [$R&R(5(d[$R&R)U 5n U R+5R-U R/55Xy'UR1U R355 M [U5(a[5U5(d Sn [7U 5e0n UH2n 0X'U(aX-XS'X}XS'U(dM)X=XS'M4 X`lXlg g ) zqMap the levels of the `style` variable to distinct values. Parameters ---------- # TODO add generic parameters stylerYr markersdashesz+Filled and line art markers cannot be mixedmarkerpathN)r^rr_r`rErFrarr variable_typerBr_map_attributesunique_markersr* unique_dashesitemsrArr MarkerStyleget_path transformed get_transformappend is_filledrdrr2r<)rrrrrorpr2pathsfilled_markersrImr~r<r=rrs rrStyleMapping.__init__ s !  $$Wbiie.DE ::<    T"j0Dz't3F**F !""3~+>+>C o%L$& !29,L%h/05 L%f-628+L%h/ !K , Y r!cRUcURUnU$URUUnU$)z(Get attribute(s) for a given data point.r;)rr=attrr|s rr>StyleMapping._lookup_singleGs: <%%c*E %%c*40E r!cUSLa[[X#55nU$[U[5(a5[U5[U5- nU(aSUSU3n[ U5eUnU$[U[ 5(a(UR X!U5n[[X!55nU$U(aSUSU3n[ U5e0nU$)z5Handle the specification for a given style attribute.TzThese `z` levels are missing values: zThis `z` argument was not understood: )rr,rArrrr8)rargr2defaultsrr<rr~s rrStyleMapping._map_attributesOs $;F 56L T " "&kCH,Gv%B7)L o%LX & &))&trrRrrs@rrrs"BH8-tr!rc\rSrSrSrSSSSS.rSSS.rSrS 04S jr\ S 5r \ S 5r S 04S jr S"Sjr S#SjrS$SjrS$SjrS"SSSSSS.Sjjr\ S5rSrS%SjrSrS&SjrS$SjrSrSrSrSrS%S jrS!rg )' VectorPlotterihz2Base class for objects underlying *plot functions.@index@values@columns)r7yrXrr7r)rurNc0UlSSS.UlURX5 SHnX2;dM [USU35"5 M g)NFrrXrrmap_) _var_levels _var_orderedassign_variablesgetattr)rrp variablesvars rrVectorPlotter.__init__rsL #(e4 d. ,CSEl+-,r!cH[SS1[UR5-5$)z.Return True at least one of x or y is defined.r7r)boolrr)rs r has_xy_dataVectorPlotter.has_xy_datas!S#JT^^!4455r!cURH2n[USUS3S5=ncMURURU'M4 UR$)aProperty interface to ordered list of variables levels. Each time it's accessed, it updates the var_levels dictionary with the list of levels in the current semantic mappers. But it also allows the dictionary to persist, so it can be used to set levels by a key. This is used to track the list of col/row levels using an attached FacetGrid object, but it's kind of messy and ideally fixed by improving the faceting logic so it interfaces better with the modern approach to tracking plot variables. r6_mapN)rrr2r)rrmap_objs r var_levelsVectorPlotter.var_levelssP>>C"41SE==J(/  %"r!c `URSS5nURSS5nUc UcSUlUR"U40UD6upVO*SUl[X5nURnUR nXPlX`lUVs0sHnU[XXUS;aSOSS 9_M snUl U$s snf) z;Define plot variables, optionally using lookup from `data`.r7Nrrlongxyr\r]) boolean_type) r`rf_assign_variables_wideformr framenamesr_rrrg) rrprr7rrrr_vs rrVectorPlotter.assign_variabless MM#t $ MM#t $ 9 &D ::4M9MLE5 !'D  1IOOEOOE    }*+t)Y     sB+c UR5VVs/sH up4UcM UPM nnn[U5(a?[U5S:aSOSnSUS3nUSRSU55- n[ U5eUSL=(d [U5(+n[ U[ 5(aUR5n O-[R"[R"U[S 95n [S U 55(+n U(a[R"5n 0n X4$U (a[R"U5R5n U R U R"R S .n0n 0n S HGnXR$;dMUR$Un['U USS5X'XR$UX'MI [R"U 5n X4$[ U[(5(a?0n[+U5H,unn['US U5n[R"U5UU'M. Un[ U[,5(a:UR5VVs0sHunnU[R"U5_M nnn[R"USS9nUR5VVs/sHup4[/U5S:XdMUPM nnnUUnSSS.nSUR0R5;nU(aqSUS'UR2R4nUR2R6nUR2R9S5UlSnUR"R=5US'UR>"S0UD6n U(a%W(a[R@"U SWW5U S'UR0R5H unnU UX'M 0n UR0R5H$unn['UUSS5n['US S5X'M& U [CU 5n X4$s snnfs snnfs snnf![:a SnNf=f)aDefine plot variables given wide-form data. Parameters ---------- data : flat vector or collection of vectors Data can be a vector or mapping that is coerceable to a Series or a sequence- or mapping-based collection of such vectors, or a rectangular numpy array, or a Pandas DataFrame. kwargs : variable -> data mappings Behavior with keyword arguments is currently undefined. Returns ------- plot_data : :class:`pandas.DataFrame` Long-form data object mapping seaborn variables (x, y, hue, ...) to data vectors. variables : dict Keys are defined seaborn variables; values are names inferred from the inputs (or None when no name can be determined). Nrusr#zThe following variablez) cannot be assigned with wide-form data: z, c3.# UH nSUS3v M g7f)`NrS.0rs r ;VectorPlotter._assign_variables_wideform..s8x!q1XxsrYc3# UH7n[U[5=(a [U[[45(+v M9 g7fr)rArstrbytesrs rrrs4  q( # GJq3,,G(G Gs?A)rrrnameTrr\rr)var_name value_namerid_varsFrS)"rrr*r+rrArr3rC atleast_1drobjectrE DataFramerFrr indexflat_structurerr enumerater rwide_structurecolumns categoriesorderedadd_categoriesAttributeError to_seriesmelt CategoricalrB)rrprHrIrassignedrr~emptyr3flatr_r flat_datarrr data_dictir=val wide_data numeric_colsmelt_kws use_indexorig_categories orig_orderedcategory_columnsobjs rr(VectorPlotter._assign_variables_wideforms.#),,.B.$!AA.B x==8}q(bA*1#-VWC 4998x88 8CS/ ! -CI  dD ! ![[]F]]2::d&#ABF      IIz##w  $,,.I$>>#//..E II!---..s3D%,YQR%AIN%*+>+>s+C%DIN "  Y/IN##}$)) 'oFAs!#vq1C&(YYs^IcN . !$((<@JJLILSRYYs^+LI  T5I(oo//da=3Cy3P/ ",/I%/iHH D$7$7$>$>$@@I&.#,&/&7&7&B&BO#,#4#4#<#r?r facet_varsrrpr2axis converterrJ grouped_data grouping_keysr= iter_keyspd_key data_subsetsub_varss r iter_dataVectorPlotter.iter_dataQsF  M  s + +*OM  u - - /M J  S03}3EEE  )6O 9N O >>D>>D ;;=D%%' c S%77 OOD166q9 >>$'=8((. (1'>'>v|'L (*wwtz/@/@/B'C ) 7 7 9 C CI#,Y-D-DV\-R#SFL8" <<EEE(LM$jjo$$3;RC@%"))=9I$T)_5  "#h!m0A"g0N0NCFTW/"."8"8"@K$$[M3 78 0 0 222'!.diik/ !GPf / #'((2,K /s>BLK#K#!GL5K(A"L(LLLLc P[US5(d UR$[US5(GdURRSS9RSS/SSS 9nS GHnX R;aM/nURUR UR USS 9nUGH$upVURUR[R[R*/5[R5nUR5nX R;a XfRURU5n[R"UR!U55R#[$5nUR'5R(nUR+[R,"U"U5UR.UR0S 95 GM' U(a[R2"U5n O[R,"[$US 9n UR5SX)5 GM XlUR6$)zFDataframe with numeric x and y, after unit conversion and log scaling.ax _comp_dataF)deepr7rruignore)rRerrorsyxrr )rZr r)hasattrr_rdroprrKrGmaskisinrCinfryrrrErhrIastyperarrJrrFrr concatinsertr^) rrFrpartsgroupedrSorigcomprJcomp_cols rrFVectorPlotter.comp_datastT"" >> !t\**5!sCjq:  nn,..-55dooc6JQV5W'.OI99TYY/@%A266JD;;=Doo- $IIdooc.B$CD==)@)@)FGNNuUD ) 7 7 9 C CILL9T?DJJTYY!WX(/!yy/H!yyu3?H  C2+.(Or!cXURSS5nURSS5nUbUbURRX#4$UbURRU$UbURRU$URcURR$UR$)z>Return an Axes object based on existence of row/col variables.rBNrA)r`facets axes_dictr])rrYrBrAs r _get_axesVectorPlotter._get_axessll5$'ll5$' ?s;;((#4 4 _;;((- - _;;((- - WW_;;>> !77Nr!c$SSKJn [X5(atSUlXlUR R 5nURbURURS'URbURURS'OXlSUlU/n[S5RUR5nUc/SQnO[U[5(aU/nUH.nURUnX;dMSUS US US 3n [U 5e SSS .n 0UlUGHnS SS .Un ["R$"UR&R(U[*S9n [-URSU3S5n U SLdXU :Xa [-USUS35U R.SS&OU SLaQUR15H<upUR3U5n[-UUS35U R.UR('M> O[-URU S35n[5U5HYunnU S:XaUS4OSU4n[-URR UUS35nUU R.UR&U U:H'M[ XR U'UR&UR7UR USS9nUH\un nURUS:Xa2UR8U(aURUnOSn[;UU5nU R=U5 M^ GM UcS=nnOUunn[ASUU45H>unnU(dMUH)n[-USUS35nUSLa U"SSS9 M!U"SUSS9 M+ M@ URR?S S5S:Xa%UHnURBRES5 M gg![aI URR?S5S:XaUOSnURR?S 5S:XaUOSnNf=f)a=Associate the plotter with an Axes manager and initialize its units. Parameters ---------- obj : :class:`matplotlib.axes.Axes` or :class:'FacetGrid` Structural object that we will eventually plot onto. allowed_types : str or list of str If provided, raise when either the x or y variable does not have one of the declared seaborn types. log_scale : bool, number, or pair of bools or numbers If not False, set the axes to use log scaling, with the given base or defaulting to 10. If a tuple, interpreted as separate arguments for the x and y axes. ru) FacetGridNrArBrr\r r]r&z variable is z , but one of z is requiredrrr7)rr rZ_shareTrrRF_namesrcr]r\set_scalelogrg) nonpositive)baser)#axisgridryrAr]rtaxesflatten col_namesr row_namesr intersectionrr rgrzrGrErFr_rrrrOrZrvrrKrr update_unitsr`r,yaxis set_inverted)rr- allowed_types log_scaleryax_listaxis_variablesrrr~ facet_dim other_varrS share_state axes_vars axes_datar]rr$levelidxrRrn seed_dataroscalexscaleyr~ set_scales r_attachVectorPlotter._attachs* ( c % %DGKhh&&(G}}(),&}}(),&GDKeGT//?  BM  s + +*OM!C~~c*H,3%}XJm$o\3 n$" e, !C!,S1I (<(<3fUI!$++u~tDK d"ky5I&I#*71:#d|#D a %'040@, !^^I69@uD\9R ioo61A$DKKK=1GHE$-e$45(3u(>#&-7((- $ 4 $ 1)U CI&&y1)0K"b  # #FV V!* tff%56KD%u!B 'd4&,> ?I}!%V<!%eH "7 >>  c4 (M 9%%d+ : V&*nn&8&8&=&JPU&*nn&8&8&=&JPU Vs!N<Bkk>N>N>S>ST>SvT]3>SIT3<=94nn&9F=6{QV"3''%aL668M$DGGvT];IIKM&& (>(>(@(J(JJJ#U=s C&C+cUR5(dJ[SUR555nURURR SU5US9 UR 5(dK[SUR555nURURR SU5US9 gg)zCAdd axis labels if not present, set visibility to match ticklabels.c3@# UHoR5v M g7fr get_visiblerts rr1VectorPlotter._add_axis_labels..J5IMMOO5Ir7)visiblec3@# UHoR5v M g7frrrs rrrrrrN) get_xlabelrget_xticklabels set_xlabelrr` get_ylabelget_yticklabels set_ylabel)rr] default_x default_y x_visible y_visibles r_add_axis_labelsVectorPlotter._add_axis_labelss }}JR5G5G5IJJI MM$..,,S)Add labeled artists to represent the different plot semantics.)autobrieffullz7`legend` must be 'auto', 'brief', 'full', or a boolean.TrNc3\># UH!nTRRUS5v M# g7fr)rr`)rrrs rr0VectorPlotter.add_legend_data..s' K2JQT^^  4 ( (2Js),rrur#Fwr)rcolorr linewidthrrc>X4nUT;aTUR"S0UD6 gTRU5 [S0UD6TU'g)NrS)updaterr)r val_namekwsr=keys legend_kwss rr-VectorPlotter.add_legend_data..updatesC$Cj 3&&-- C "&++ 3r!rrrlabelz.2z3.5.0rS)legendrAr rrr*poprr_update_legend_datar`_legend_attributesr3rrlinesLine2Dadd_linepatchesPatch add_patch collections Collectionadd_collection add_artistr legend_title legend_data legend_order)rr]func common_kwsattrs semantic_kws verbosityr~titletitles title_kwsrrrrrr=r6rr level_kws var_attrsr use_attrsartistrrs` @@radd_legend_dataVectorPlotter.add_legend_datasKK i % %);T*TKCS/ ! $ I %-R:??3D )1r|7H7H7J  L2J K K  K  &kQ&FJJLQr"  . =#k3-?$OE++-JC  $ $YyAQAQRUAV (    >>'5 ) 1 NN7 #CHAuS/CI(()5(;(;(=T(=9)$$)$(=TI "3;&)$iIdO"TT'4)S:)S)STF g..fcii&6&677KK' (9(9::LL((B(BCC%%f- f%%K     $14"&({ RUs;J3J3'J8 c Sn[USUS3S5n U cgU RS:H=(a0 US:H=(d$ US:H=(a [U R5U:n U (a[ U R [ RR5(a[ RRUS9n O[ RRUS 9n [U R5[U R54n [XURUR!5R"5upOU Rc/=pO U R=pU(dCUR$R'US5b&U"UR$US 4UR$U40UD6 Uc0OUn[)X5HunnUcM U "U5n[ U[*5(aUVs0sHnUU_M nnOUbUU0nUR-UR/5VVs0sHunnUU;dMUUU_M snn5 U"UR$UU40UD6 M gs snfs snnf) z1Generate legend tick values and formatted labels.r'r6rNr\rr)numticks)nbinsr)rrr*r2rArmrrLogNormticker LogLocator MaxNLocatorrrrr_ infer_objectsrZrr`r,rBrr)rrrrrr attr_names other_props brief_ticksmapperrlocatorlimitsr2formatted_levelsrformatted_levelrr rIrs rr!VectorPlotter._update_legend_datas$ 3%t}d3 > 9,   JV#HFMM(:[(H  &++szz'9'9::**///E**00{0C'V]]);;F'@!4!B!B!D!J!J( $F$]] "(* *F%(. 5F++C6B DNN3'14>>#3F T) T'/b[ &)&&C "E? e}j$//3=>:4D$J:D>D+&-D [5F5F5HW5HTQEUVJ[Q%[5HWXt~~c*ODtD'D?Xs I  I  I c[erNotImplementedErrorrrRrGrHs r scale_nativeVectorPlotter.scale_native:s "!r!c[errrs r scale_numericVectorPlotter.scale_numeric@ "!r!c[errrs rscale_datetimeVectorPlotter.scale_datetimeGrr!c[SSS/U5 XR;a-SURU'SURU'SURU'URUS:XaURR USS 9UlURUR 5nUSL=(d UR RS :HURU'[R"[XB5US 9nUb#URU5nURU5nO*UR[5nUR[5nX RU'SURU'X@RU'U$) a2 Enforce categorical (fixed-scale) rules for the data on given axis. Parameters ---------- axis : "x" or "y" Axis of the plot to operate on. order : list Order that unique values should appear in. formatter : callable Function mapping values to a string representation. Returns ------- self rRr7rNr]r#r\ mergesort)kindcategoryrd)rrrgr_ sort_valuesrrZr rrEIndexrmaprjr r)rrRro formattercat_datas rscale_categoricalVectorPlotter.scale_categoricalNsDT c D1 ~~ %#'DNN4 #0DNN4 #%DNN4  >>$ 9 ,!^^77;7ODN>>$'..0 #(t"3"Xx~~7J7Jj7X$*8;$G  ||I.HIIi(Es+HLL%E!& -t (t r!)r^r0r5r9rrr]rGrtrfrrrr_rgrrrr)NN)r#r#)rLrMrNrOrPrrrrpropertyrrrrr2r6r:rZrFrvrrrrrrrrrrRrSr!rrrhs<Ij:N$)4N B."66  "%)B:L$\ !" !u"e5u"n**X $ G,VK, QCGP)d/El" ""[r!rc6^\rSrSrSrSrU4SjrSrSrU=r $) VariableTypeiz Prevent comparisons elsewhere in the library from using the wrong name. Errors are simple assertions because users should not be able to trigger them. If that changes, they should be more verbose. rzcP>XR;dU5e[TU] U5 gr)allowedr^r)rrprrs rrVariableType.__init__s%||#)T)# r!cLXR;dU5eURU:H$r)rrp)rothers r__eq__VariableType.__eq__s& $+e+$yyE!!r!rS) rLrMrNrOrPrrrrRrrs@rrrs3G""r!rc[R"U5n[UR[R5(a [ S5$[R "U5R5(a [ S5$UR5n[R"5 [R"S[[4S9 [R"USS/5R5(a[ U5sSSS5 $SSS5 [R"R$R'U5(a [ S5$[R"R$R)U5(a [ S5$S nU"U5(a [ S5$S nU"U5(a [ S5$[ S5$![ a Nf=f!,(df  N=f) a Determine whether a vector contains numeric, categorical, or datetime data. This function differs from the pandas typing API in two ways: - Python sequences or object-typed PyData objects are considered numeric if all of their entries are numeric. - String or mixed-type data are considered categorical even if not explicitly represented as a :class:`pandas.api.types.CategoricalDtype`. Parameters ---------- vector : :func:`pandas.Series`, :func:`numpy.ndarray`, or Python sequence Input data to test. boolean_type : 'numeric' or 'categorical' Type to use for vectors containing only 0s and 1s (and NAs). Returns ------- var_type : 'numeric', 'categorical', or 'datetime' Name identifying the type of data in the vector. r]r\r`)actionr rruNr cDUHn[U[5(aM g gNFT)rAr r7x_is r all_numeric"variable_type..all_numerics!Cc6**r!cdUH*n[U[[R45(aM* g gr")rAr rC datetime64r#s r all_datetime#variable_type..all_datetimes*CcHbmm#<==r!)rErFrArZCategoricalDtyperrcrdrr/catch_warnings simplefilter FutureWarningDeprecationWarningrCrhrzapitypesis_numeric_dtypeis_datetime64_dtype)vectorrr%r)s rrrs|.YYv F&,, 3 344M** wwvI&&]]_F  "}6H&I  wwv1v&**,,#L1 # " - # vv||$$V,,I&& vv||''//J''  6I&& FJ''  &&M    # "s0$ G6GG G G GG GcUcSO [U5nUcSO [U5nSnSnUcn[U5RS5(a&[R"UR SS55 U(a!US:wa[ UR SS55eg Ucn[U5RS 5(a&[R"UR SS 55 U(a!US:wa[ UR SS 55eg[U5RS 5(dUS :Xa)U(a!US:wa[ UR SS55eg [U5RS5(dUS:Xa)U(a!US:wa[ UR SS 55egUbS [U5S 3n[U5eUS :waUS :XagUS:waUS:Xag US:XaUS:wagU(aSXE4;a Sn[ U5eg )a Determine how the plot should be oriented based on the data. For historical reasons, the convention is to call a plot "horizontally" or "vertically" oriented based on the axis representing its dependent variable. Practically, this is used when determining the axis for numerical aggregation. Parameters ---------- x, y : Vector data or None Positional data vectors for the plot. orient : string or None Specified orientation. If not None, can be "x" or "y", or otherwise must start with "v" or "h". require_numeric : bool If set, raise when the implied dependent variable is not numeric. Returns ------- orient : "x" or "y" Raises ------ ValueError: When `orient` is an unknown string. TypeError: When dependent variable is not numeric, with `require_numeric` Nz.{} orientation requires numeric `{}` variable.z0{} orientation ignored with only `{}` specified.h Horizontalrr\Verticalr7rz5`orient` must start with 'v' or 'h' or be None, but `z ` was passed.r]z7Neither the `x` nor `y` variable appears to be numeric.) rr  startswithr/r0rrzreprr) r7rorientrequire_numericx_typey_typenonnumeric_dv_errorsingle_var_warningr~s r infer_orientrAs:YTM!$4FYTM!$4FJKy v; ! !# & & MM,33L#F G v2/66z3GH H  v; ! !# & & MM,33JD E v2/66|SIJ J V   $ $# v2/66z3GH H V   $ $# v2/66|SIJ J   L> 0 o = V}%< 9 9!4 9 9!4 Yv.>>Gnr!c^/SQnSn[U5U:a[R"SS/U5n[R"SS/U5n[R"[ [ U5SSSSS2[ U5SS56nUHEn[ U5m[[R"U4SjU565nURU5 MG US- n[U5U:aMUSU$) aBuild an arbitrarily long list of unique dash styles for lines. Parameters ---------- n : int Number of unique dash specs to generate. Returns ------- dashes : list of strings or tuples Valid arguments for the ``dashes`` parameter on :class:`matplotlib.lines.Line2D`. The first spec is a solid line (``""``), the remainder are sequences of long and short dashes. )r#)r[?)ruru)?rCrE)rurururDrEr[rurNc3*># UHoT4v M g7frrS)rseggaps rr unique_dashes..s*J#:s) r*r-combinations_with_replacementchainr,rBrrr) nrpab segment_listsegmentsspecrIs @rrros$F A f+/  3 3QIq A  3 3QFA >! GAbM$B$  GAbM)  %Hh-C*J*JKLD MM$ % Q% f+/( "1:r!c/SQnSn[U5U:aHSUS-- S- nURUS-SU4US-SU4USS4USS4/5 US- n[U5U:aMHUSU$)a/Build an arbitrarily long list of unique marker styles for points. Parameters ---------- n : int Number of unique marker specs to generate. Returns ------- markers : list of string or tuples Values for defining :class:`matplotlib.markers.MarkerStyle` objects. All markers will be filled. ) oX)r[r-P)r[rr)r[rur^)r[rurWrrFihrurrN)r*rE)rMrrrOs rrrs G A g,  1q5MA  UAqM UAqM 1I 1I   Q g,  2A;r!czUcO[US5(a URnOURRn[[ RU5n[U5$![[4aL [ R "U5R5n[U5S:Xa[R"U5nNf=f)aReturn a list of unique data values. Determine an ordered list of levels in ``values``. Parameters ---------- vector : list, array, Categorical, or Series Vector of "categorical" values order : list-like, optional Desired order of category levels to override the order determined from the ``values`` object. Returns ------- order : list Ordered list of category levels not including null values. rr\)rercatrzrrErFrrrCrfilternotnullrB)r4ros rrrs& } 6< ( (%%E + --rzz5) ;~. + &)002 (I5GGENE  +sAAB:9B:)r\)NNNTr)+ __future__rr/r-rrrcollections.abcrrr numbersr r numpyrCpandasrE matplotlibrseaborn._core.datar seaborn.palettesr r seaborn.utilsrrrrrrrrUrrrrrrArrrrSr!rrgs""77'8=8=vO0O0dZ6/Z6z[?[BA A H":"(Y'xPf0f+\!r!