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Defaulting to nominal.r stacklevel)r catordered categoriestolistwarningswarnformat)datatyps rinfer_vegalite_typers d  C ~  $("2 48.557788 Q Q Qy   z  %%+VC[[    yr(cfddD} d|d}n#ttf$r|}YnwxYw|S)zc Merge properties with geometry * Overwrites 'type' and 'geometry' entries if existing c"i|] }|| Sr#r#)r$r%feats rr'z$merge_props_geom..s 5 5 51AtAw 5 5 5r(typegeometry properties)updateAttributeErrorKeyError)rgeom props_geoms` rmerge_props_geomrs| 6 5 5 5 4 5 5 5D \!!$''',' H %  s#5A  A c,t|}|D]Y}tt||jdr||||<Ztjtj |}|ddkrC|d}t|dkr't|D]\}}t|||<n!|ddkrt|}nd|d}|S)zSantize a geo_interface to prepare it for serialization. * Make a copy * Convert type array or _Array to list * Convert tuples to lists (using json.loads/dumps) * Merge properties with geometry )_ArrayarrayrFeatureCollectionfeaturesrFeaturer) rkeysstrr__name__ startswithrjsonloadsdumpslen enumerater)geokeyidxrs rsanitize_geo_interfacers  3--Cxxzz)) tCH~~& ' ' 2 23F G G )3x((CH *TZ__ % %C 6{)))*o s88a<<&s^^ 2 2 T+D11C V ! !s## c22 Jr(cT |}t|jtjr$|jt |_|jD]9}t|t s"td|:t|j tj rtdt|jtj rtdd}|j D]\}}t |dkrL||t}||d||<et |dkrL||t}||d||<t |dkr$||t||<t |dkrM||t}||d||<[t |d r5||d d d ||<t |d r$td||t |drt |dvrM||t}||d||<zt'j|t&jr%||t||<t'j|t&jre||}|t'j|z}|t|d||<B|tkrH|||d}||d||<|S)aSanitize a DataFrame to prepare it for serialization. * Make a copy * Convert RangeIndex columns to strings * Raise ValueError if column names are not strings * Raise ValueError if it has a hierarchical index. * Convert categoricals to strings. * Convert np.bool_ dtypes to Python bool objects * Convert np.int dtypes to Python int objects * Convert floats to objects and replace NaNs/infs with None. * Convert DateTime dtypes into appropriate string representations * Convert Nullable integers to objects and replace NaN with None * Convert Nullable boolean to objects and replace NaN with None * convert dedicated string column to objects and replace NaN with None * Raise a ValueError for TimeDelta dtypes zKDataframe contains invalid column name: {0!r}. 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Parameters ---------- shorthand : dict or string The shorthand representation to be parsed data : DataFrame, optional If specified and of type DataFrame, then use these values to infer the column type if not provided by the shorthand. parse_aggregates : boolean If True (default), then parse aggregate functions within the shorthand. parse_window_ops : boolean If True then parse window operations within the shorthand (default:False) parse_timeunits : boolean If True (default), then parse timeUnits from within the shorthand parse_types : boolean If True (default), then parse typecodes within the shorthand Returns ------- attrs : dict a dictionary of attributes extracted from the shorthand Examples -------- >>> data = pd.DataFrame({'foo': ['A', 'B', 'A', 'B'], ... 'bar': [1, 2, 3, 4]}) >>> parse_shorthand('name') == {'field': 'name'} True >>> parse_shorthand('name:Q') == {'field': 'name', 'type': 'quantitative'} True >>> parse_shorthand('average(col)') == {'aggregate': 'average', 'field': 'col'} True >>> parse_shorthand('foo:O') == {'field': 'foo', 'type': 'ordinal'} True >>> parse_shorthand('min(foo):Q') == {'aggregate': 'min', 'field': 'foo', 'type': 'quantitative'} True >>> parse_shorthand('month(col)') == {'field': 'col', 'timeUnit': 'month', 'type': 'temporal'} True >>> parse_shorthand('year(col):O') == {'field': 'col', 'timeUnit': 'year', 'type': 'ordinal'} True >>> parse_shorthand('foo', data) == {'field': 'foo', 'type': 'nominal'} True >>> parse_shorthand('bar', data) == {'field': 'bar', 'type': 'quantitative'} True >>> parse_shorthand('bar:O', data) == {'field': 'bar', 'type': 'ordinal'} True >>> parse_shorthand('sum(bar)', data) == {'aggregate': 'sum', 'field': 'bar', 'type': 'quantitative'} True >>> parse_shorthand('count()', data) == {'aggregate': 'count', 'type': 'quantitative'} True z (?P.*)z (?P{})|z(?Pcount)z (?Pcount)z(?P{})z (?P{})z(?P{}))fieldr agg_countop_count aggregate window_optimeUnitz{agg_count}\(\)z{aggregate}\({field}\)z{op_count}\(\)z{window_op}\({field}\)z{timeUnit}\({field}\)z{field}c3$K|] }|dz|fV dS)z:{type}Nr#)r$ps r z"parse_shorthand..s+)O)O1y=!*<)O)O)O)O)O)Or(c 3xK|]4}tjd|jdizdztjV5dS)z\Az\ZNr#)recompilerDOTALL)r$runitss rrz"parse_shorthand..s^EF 5818,,e,,,u4bi@@r(c3K|]@}||VAdSr)match groupdict)r$exp shorthands rrz"parse_shorthand.. s`  14399YCWCW IIi * * , ,      r(rrr,rrr r \rrsortr:z"{}" z0is not one of the valid encoding data types: {}.z, zi For more details, see https://altair-viz.github.io/user_guide/encodings/index.html#encoding-data-types. z>If you are trying to use a column name that contains a colon, zPprefix it with a backslash; for example "column\:name" instead of "column:name".)list TYPECODE_MAPINV_TYPECODE_MAPrjoin AGGREGATESWINDOW_AGGREGATES TIMEUNITSextend itertoolschainrdictnextgetr DataFramerrrtuplerfindrsplitr=) rrparse_aggregatesparse_window_opsparse_timeunits parse_typesvalid_typecodespatternsregexpsattrsrs ` @rparse_shorthandr<sd  <((40@+A+AAO!%%chh&?&?@@+#(//0D0DEE!((*?P2P)Q)QRR&--chhy.A.ABB  EH5+,---234445*+,,,23444412333 OOZL!!!R )O)Oh)O)O)OPQQJRG )T""     8?      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Returns ------- kwargs : dict All args and kwargs in a single dict, with keys and types based on the channels mapping. c38K|]}t|VdSr)getattr)r$namechannelss rrz'infer_encoding_types..s-FFGHd++FFFFFFr(c3nK|]0}t|tt|t,|V1dSr)rr issubclassrr$cs rrz'infer_encoding_types..sW:a#6#6;Ea;T;T r(ci|] }||j Sr#)_encoding_namercs rr'z(infer_encoding_types..sAAAqq!*AAAr(DatumdatumValuerr rNzpositional of type {}zencoding {} specified twice.ct|tr|St|trd|i}t|ttfrfd|DSvr+t jdd|S}d|vr|dn|d} ||d S#tj $r|cYSwxYw) Nrc(g|]}|Sr#r#)r$subobj_wrap_in_channel_classencodings r zHinfer_encoding_types.._wrap_in_channel_class..s'OOO**68<<OOOr(z"Unrecognized encoding channel '{}'rrrr F)validate) rrrr#r1rrr from_dict jsonschemaValidationError)objrnclassesclsrmname_to_channels ` rrmz4infer_encoding_types.._wrap_in_channel_classs c: & & J c3   %$C cD%= ) ) POOOOO3OOO O ? * * M4;;HEERS    J!(+")S..gggg6F ==u=55 5)   JJJ s*CCCc0i|]\}}|||Sr#r#)r$rnrtrms rr'z(infer_encoding_types..s=    Hc ((h77   r()dirr setdefaultrendswithrr#r1rrr/NotImplementedErrorrr)argskwargsr` channel_objschannel_to_namechanr_chansrargtype_rnrmrws ` @@rinfer_encoding_typesrs(GFFFH FFFLLBALAAAOO%++-- d**444 = ! !' * * CC ] # #G , , CCCc    cD%= ) ) c#hhllQLLEEIIE"&&ud33  %&@&G&G&N&NOO O v  ;BB8LLMM Mx6    #\\^^   r()NTFTT)F)T)/rGcollections.abcrrrrr+rrSrWrtypingrrrrrpandasrnumpyraltair.utils.schemapir version_infor typing_extensionspandas.api.typesr r ImportError pandas.libr rr$rr%r'r(r)rrrr r<rLrNr[rr#r(rrs$#####  )))))))))),,,,,,w       ++++++7<<<<<<<777666666667 WT]]Yt__###*  ;:\%7%7%9%9::: 6   Q Q Q  h(((V$Bnnnf  ccccLxC(>%%%%P - - - - PPPPPsA## A10A1