&edZddlmZddlmZddlmZddlmZddl m Z m Z m Z m Z mZmZmZmZddlZddlmZmZdd lmZddlmcmZdd lmZdd lmZm Z m!Z!m"Z"m#Z#dd l$m%Z%dd l&m'Z'ddl(m)Z)ddl*m+Z+m,Z,ddl-m.Z/ddl0m1Z1e r ddl2Z3ddl4m5Z5GddeZ6e7dddZ8e7dddZ9dZ:dZ;dZe;e=zZ?estr | Sequence[str] | Noner8 str | Color | List[Color] | Noner?intr@rAboolreturnrc t}ttj||||d||\} } t || |d|jd|| S)aDisplay a line chart. This is syntax-sugar around ``st.altair_chart``. The main difference is this command uses the data's own column and indices to figure out the chart's spec. As a result this is easier to use for many "just plot this" scenarios, while being less customizable. If ``st.line_chart`` does not guess the data specification correctly, try specifying your desired chart using ``st.altair_chart``. Parameters ---------- data : pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, pyspark.sql.DataFrame, snowflake.snowpark.dataframe.DataFrame, snowflake.snowpark.table.Table, Iterable, dict or None Data to be plotted. x : str or None Column name to use for the x-axis. If None, uses the data index for the x-axis. y : str, Sequence of str, or None Column name(s) to use for the y-axis. If a Sequence of strings, draws several series on the same chart by melting your wide-format table into a long-format table behind the scenes. If None, draws the data of all remaining columns as data series. color : str, tuple, Sequence of str, Sequence of tuple, or None The color to use for different lines in this chart. For a line chart with just one line, this can be: * None, to use the default color. * A hex string like "#ffaa00" or "#ffaa0088". * An RGB or RGBA tuple with the red, green, blue, and alpha components specified as ints from 0 to 255 or floats from 0.0 to 1.0. For a line chart with multiple lines, where the dataframe is in long format (that is, y is None or just one column), this can be: * None, to use the default colors. * The name of a column in the dataset. Data points will be grouped into lines of the same color based on the value of this column. In addition, if the values in this column match one of the color formats above (hex string or color tuple), then that color will be used. For example: if the dataset has 1000 rows, but this column only contains the values "adult", "child", and "baby", then those 1000 datapoints will be grouped into three lines whose colors will be automatically selected from the default palette. But, if for the same 1000-row dataset, this column contained the values "#ffaa00", "#f0f", "#0000ff", then then those 1000 datapoints would still be grouped into three lines, but their colors would be "#ffaa00", "#f0f", "#0000ff" this time around. For a line chart with multiple lines, where the dataframe is in wide format (that is, y is a Sequence of columns), this can be: * None, to use the default colors. * A list of string colors or color tuples to be used for each of the lines in the chart. This list should have the same length as the number of y values (e.g. ``color=["#fd0", "#f0f", "#04f"]`` for three lines). width : int The chart width in pixels. If 0, selects the width automatically. height : int The chart height in pixels. If 0, selects the height automatically. use_container_width : bool If True, set the chart width to the column width. This takes precedence over the width argument. Examples -------- >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame(np.random.randn(20, 3), columns=["a", "b", "c"]) >>> >>> st.line_chart(chart_data) .. output:: https://doc-line-chart.streamlit.app/ height: 440px You can also choose different columns to use for x and y, as well as set the color dynamically based on a 3rd column (assuming your dataframe is in long format): >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame( ... { ... "col1": np.random.randn(20), ... "col2": np.random.randn(20), ... "col3": np.random.choice(["A", "B", "C"], 20), ... } ... ) >>> >>> st.line_chart(chart_data, x="col1", y="col2", color="col3") .. output:: https://doc-line-chart1.streamlit.app/ height: 440px Finally, if your dataframe is in wide format, you can group multiple columns under the y argument to show multiple lines with different colors: >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame(np.random.randn(20, 3), columns=["col1", "col2", "col3"]) >>> >>> st.line_chart( ... chart_data, x="col1", y=["col2", "col3"], color=["#FF0000", "#0000FF"] # Optional ... ) .. output:: https://doc-line-chart2.streamlit.app/ height: 440px N chart_typerB x_from_user y_from_usercolor_from_usersize_from_userr?r@ streamlitthemearrow_line_chartadd_rows_metadata)ArrowVegaLiteChartProto_generate_chartr!r,marshalldg_enqueue selfrBr=r>r8r?r@rAprotochartrUs r0r<zArrowAltairMixin.line_chartasZ())#2 ~! $ $ $    2+FFFFw 9J    r/ area_chartc t}ttj||||d||\} } t || |d|jd|| S)aDisplay an area chart. This is syntax-sugar around ``st.altair_chart``. The main difference is this command uses the data's own column and indices to figure out the chart's spec. As a result this is easier to use for many "just plot this" scenarios, while being less customizable. If ``st.area_chart`` does not guess the data specification correctly, try specifying your desired chart using ``st.altair_chart``. Parameters ---------- data : pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, pyspark.sql.DataFrame, snowflake.snowpark.dataframe.DataFrame, snowflake.snowpark.table.Table, Iterable, or dict Data to be plotted. x : str or None Column name to use for the x-axis. If None, uses the data index for the x-axis. y : str, Sequence of str, or None Column name(s) to use for the y-axis. If a Sequence of strings, draws several series on the same chart by melting your wide-format table into a long-format table behind the scenes. If None, draws the data of all remaining columns as data series. color : str, tuple, Sequence of str, Sequence of tuple, or None The color to use for different series in this chart. For an area chart with just 1 series, this can be: * None, to use the default color. * A hex string like "#ffaa00" or "#ffaa0088". * An RGB or RGBA tuple with the red, green, blue, and alpha components specified as ints from 0 to 255 or floats from 0.0 to 1.0. For an area chart with multiple series, where the dataframe is in long format (that is, y is None or just one column), this can be: * None, to use the default colors. * The name of a column in the dataset. Data points will be grouped into series of the same color based on the value of this column. In addition, if the values in this column match one of the color formats above (hex string or color tuple), then that color will be used. For example: if the dataset has 1000 rows, but this column only contains the values "adult", "child", and "baby", then those 1000 datapoints will be grouped into three series whose colors will be automatically selected from the default palette. But, if for the same 1000-row dataset, this column contained the values "#ffaa00", "#f0f", "#0000ff", then then those 1000 datapoints would still be grouped into 3 series, but their colors would be "#ffaa00", "#f0f", "#0000ff" this time around. For an area chart with multiple series, where the dataframe is in wide format (that is, y is a Sequence of columns), this can be: * None, to use the default colors. * A list of string colors or color tuples to be used for each of the series in the chart. This list should have the same length as the number of y values (e.g. ``color=["#fd0", "#f0f", "#04f"]`` for three lines). width : int The chart width in pixels. If 0, selects the width automatically. height : int The chart height in pixels. If 0, selects the height automatically. use_container_width : bool If True, set the chart width to the column width. This takes precedence over the width argument. Examples -------- >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame(np.random.randn(20, 3), columns=["a", "b", "c"]) >>> >>> st.area_chart(chart_data) .. output:: https://doc-area-chart.streamlit.app/ height: 440px You can also choose different columns to use for x and y, as well as set the color dynamically based on a 3rd column (assuming your dataframe is in long format): >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame( ... { ... "col1": np.random.randn(20), ... "col2": np.random.randn(20), ... "col3": np.random.choice(["A", "B", "C"], 20), ... } ... ) >>> >>> st.area_chart(chart_data, x="col1", y="col2", color="col3") .. output:: https://doc-area-chart1.streamlit.app/ height: 440px Finally, if your dataframe is in wide format, you can group multiple columns under the y argument to show multiple series with different colors: >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame(np.random.randn(20, 3), columns=["col1", "col2", "col3"]) >>> >>> st.area_chart( ... chart_data, x="col1", y=["col2", "col3"], color=["#FF0000", "#0000FF"] # Optional ... ) .. output:: https://doc-area-chart2.streamlit.app/ height: 440px NrJrPrQarrow_area_chartrT)rVrWr!r*rXrYrZr[s r0r_zArrowAltairMixin.area_charts\())#2 ~! $ $ $    2+FFFFw 9J    r/ bar_chartc t}ttj||||d||\} } t || |d|jd|| S)a!Display a bar chart. This is syntax-sugar around ``st.altair_chart``. The main difference is this command uses the data's own column and indices to figure out the chart's spec. As a result this is easier to use for many "just plot this" scenarios, while being less customizable. If ``st.bar_chart`` does not guess the data specification correctly, try specifying your desired chart using ``st.altair_chart``. Parameters ---------- data : pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, pyspark.sql.DataFrame, snowflake.snowpark.dataframe.DataFrame, snowflake.snowpark.table.Table, Iterable, or dict Data to be plotted. x : str or None Column name to use for the x-axis. If None, uses the data index for the x-axis. y : str, Sequence of str, or None Column name(s) to use for the y-axis. If a Sequence of strings, draws several series on the same chart by melting your wide-format table into a long-format table behind the scenes. If None, draws the data of all remaining columns as data series. color : str, tuple, Sequence of str, Sequence of tuple, or None The color to use for different series in this chart. For a bar chart with just one series, this can be: * None, to use the default color. * A hex string like "#ffaa00" or "#ffaa0088". * An RGB or RGBA tuple with the red, green, blue, and alpha components specified as ints from 0 to 255 or floats from 0.0 to 1.0. For a bar chart with multiple series, where the dataframe is in long format (that is, y is None or just one column), this can be: * None, to use the default colors. * The name of a column in the dataset. Data points will be grouped into series of the same color based on the value of this column. In addition, if the values in this column match one of the color formats above (hex string or color tuple), then that color will be used. For example: if the dataset has 1000 rows, but this column only contains the values "adult", "child", and "baby", then those 1000 datapoints will be grouped into three series whose colors will be automatically selected from the default palette. But, if for the same 1000-row dataset, this column contained the values "#ffaa00", "#f0f", "#0000ff", then then those 1000 datapoints would still be grouped into 3 series, but their colors would be "#ffaa00", "#f0f", "#0000ff" this time around. For a bar chart with multiple series, where the dataframe is in wide format (that is, y is a Sequence of columns), this can be: * None, to use the default colors. * A list of string colors or color tuples to be used for each of the series in the chart. This list should have the same length as the number of y values (e.g. ``color=["#fd0", "#f0f", "#04f"]`` for three lines). width : int The chart width in pixels. If 0, selects the width automatically. height : int The chart height in pixels. If 0, selects the height automatically. use_container_width : bool If True, set the chart width to the column width. This takes precedence over the width argument. Examples -------- >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame(np.random.randn(20, 3), columns=["a", "b", "c"]) >>> >>> st.bar_chart(chart_data) .. output:: https://doc-bar-chart.streamlit.app/ height: 440px You can also choose different columns to use for x and y, as well as set the color dynamically based on a 3rd column (assuming your dataframe is in long format): >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame( ... { ... "col1": list(range(20)) * 3, ... "col2": np.random.randn(60), ... "col3": ["A"] * 20 + ["B"] * 20 + ["C"] * 20, ... } ... ) >>> >>> st.bar_chart(chart_data, x="col1", y="col2", color="col3") .. output:: https://doc-bar-chart1.streamlit.app/ height: 440px Finally, if your dataframe is in wide format, you can group multiple columns under the y argument to show multiple series with different colors: >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame( ... {"col1": list(range(20)), "col2": np.random.randn(20), "col3": np.random.randn(20)} ... ) >>> >>> st.bar_chart( ... chart_data, x="col1", y=["col2", "col3"], color=["#FF0000", "#0000FF"] # Optional ... ) .. output:: https://doc-bar-chart2.streamlit.app/ height: 440px NrJrPrQarrow_bar_chartrT)rVrWr!r+rXrYrZr[s r0rbzArrowAltairMixin.bar_charts`())#2 }! $ $ $    2+FFFFw u8I    r/ scatter_chart)r=r>r8sizer?r@rArfstr | float | int | None'DeltaGenerator'c t} ttj|||||||\} } t | | |d|jd| | S)a Display a scatterplot chart. This is syntax-sugar around ``st.altair_chart``. The main difference is this command uses the data's own column and indices to figure out the chart's spec. As a result this is easier to use for many "just plot this" scenarios, while being less customizable. If ``st.scatter_chart`` does not guess the data specification correctly, try specifying your desired chart using ``st.altair_chart``. Parameters ---------- data : pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, pyspark.sql.DataFrame, snowflake.snowpark.dataframe.DataFrame, snowflake.snowpark.table.Table, Iterable, dict or None Data to be plotted. x : str or None Column name to use for the x-axis. If None, uses the data index for the x-axis. y : str, Sequence of str, or None Column name(s) to use for the y-axis. If a Sequence of strings, draws several series on the same chart by melting your wide-format table into a long-format table behind the scenes. If None, draws the data of all remaining columns as data series. color : str, tuple, Sequence of str, Sequence of tuple, or None The color of the circles representing each datapoint. This can be: * None, to use the default color. * A hex string like "#ffaa00" or "#ffaa0088". * An RGB or RGBA tuple with the red, green, blue, and alpha components specified as ints from 0 to 255 or floats from 0.0 to 1.0. * The name of a column in the dataset where the color of that datapoint will come from. If the values in this column are in one of the color formats above (hex string or color tuple), then that color will be used. Otherwise, the color will be automatically picked from the default palette. For example: if the dataset has 1000 rows, but this column only contains the values "adult", "child", and "baby", then those 1000 datapoints be shown using three colors from the default palette. But if this column only contains floats or ints, then those 1000 datapoints will be shown using a colors from a continuous color gradient. Finally, if this column only contains the values "#ffaa00", "#f0f", "#0000ff", then then each of those 1000 datapoints will be assigned "#ffaa00", "#f0f", or "#0000ff" as appropriate. If the dataframe is in wide format (that is, y is a Sequence of columns), this can also be: * A list of string colors or color tuples to be used for each of the series in the chart. This list should have the same length as the number of y values (e.g. ``color=["#fd0", "#f0f", "#04f"]`` for three series). size : str, float, int, or None The size of the circles representing each point. This can be: * A number like 100, to specify a single size to use for all datapoints. * The name of the column to use for the size. This allows each datapoint to be represented by a circle of a different size. width : int The chart width in pixels. If 0, selects the width automatically. height : int The chart height in pixels. If 0, selects the height automatically. use_container_width : bool If True, set the chart width to the column width. This takes precedence over the width argument. Examples -------- >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame(np.random.randn(20, 3), columns=["a", "b", "c"]) >>> >>> st.scatter_chart(chart_data) .. output:: https://doc-scatter-chart.streamlit.app/ height: 440px You can also choose different columns to use for x and y, as well as set the color dynamically based on a 3rd column (assuming your dataframe is in long format): >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame(np.random.randn(20, 3), columns=["col1", "col2", "col3"]) >>> chart_data['col4'] = np.random.choice(['A','B','C'], 20) >>> >>> st.scatter_chart( ... chart_data, ... x='col1', ... y='col2', ... color='col4', ... size='col3', ... ) .. output:: https://doc-scatter-chart1.streamlit.app/ height: 440px Finally, if your dataframe is in wide format, you can group multiple columns under the y argument to show multiple series with different colors: >>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> >>> chart_data = pd.DataFrame(np.random.randn(20, 4), columns=["col1", "col2", "col3", "col4"]) >>> >>> st.scatter_chart( ... chart_data, ... x='col1', ... y=['col2', 'col3'], ... size='col4', ... color=['#FF0000', '#0000FF'], # Optional ... ) .. output:: https://doc-scatter-chart2.streamlit.app/ height: 440px rJrPrQarrow_scatter_chartrT)rVrWr!r-rXrYrZ) r\rBr=r>r8rfr?r@rAr]r^rUs r0rezArrowAltairMixin.scatter_chart?sx())#2 (! $ $ $    2+FFFFw !5>> import streamlit as st >>> import pandas as pd >>> import numpy as np >>> import altair as alt >>> >>> chart_data = pd.DataFrame(np.random.randn(20, 3), columns=["a", "b", "c"]) >>> >>> c = ( ... alt.Chart(chart_data) ... .mark_circle() ... .encode(x="a", y="b", size="c", color="c", tooltip=["a", "b", "c"]) ... ) >>> >>> st.altair_chart(c, use_container_width=True) .. output:: https://doc-vega-lite-chart.streamlit.app/ height: 300px Examples of Altair charts can be found at https://altair-viz.github.io/gallery/. rPNzYou set theme="us" while Streamlit charts only support theme=”streamlit” or theme=None to fallback to the default library theme.rArRarrow_vega_lite_chart)rrVrXrYrZ)r\rkrArRr]s r0rkzArrowAltairMixin.altair_charts` K  ETMM']%]]] ())   3     w 7???r/c"td|S)zGet our DeltaGenerator.r)r)r\s r0rYzArrowAltairMixin.dg*s$d+++r/N)rBrr=rCr>rDr8rEr?rFr@rFrArGrHr)rBrr=rCr>rDr8rErfrgr?rFr@rFrArGrHrhFrP)rkrlrArGrRrmrHr)rHr) r'r(r)rr<r_rbrerkpropertyrYr.r/r0r;r;`s^L!![ (,26$([ [ [ [ [ "![ z^L!!\ (,26$(\ \ \ \ \ "!\ |^K  ^ (,26$(^ ^ ^ ^ ^ ! ^ @^O$$j (,26)-$(j j j j j %$j X^N##%*-8 ;@;@;@;@$#;@z,,,X,,,r/r;df pd.DataFramenamerCrHrGct|dS||}|jdkrdSt|jdtS)aYTrue if the column with the given name stores datetime.date values. This function just checks the first value in the given column, so it's meaningful only for columns whose values all share the same type. Parameters ---------- df : pd.DataFrame name : str The column name Returns ------- bool NFr)rf isinstanceilocr)rurwcolumns r0_is_date_columnr|0s?" |u XF {au fk!nd + ++r/columns_to_leave_alone List[str]columns_to_meltList[str] | Nonenew_y_column_namestrnew_color_column_namec tj|||||}||}|jdkrEdt|vr4t |dkrt dtj|g|||}|S)z)opacity)r8)rf)tooltip)altairrconvert_anything_to_df_parse_x_column_parse_y_columns_parse_generic_columnrrdictrChartr7encode_get_x_encoding_get_y_encoding_get_opacity_encoding_get_color_encoding_get_size_encoding_get_tooltip_encoding interactive)rKrBrLrMrNrOr?r@altrurrr color_valuer size_valuerUrr^ opacity_enc color_encsize_encs r0rWrWs+  )$D A A AB r;//H$Rh??M 5b/ J JL+3BGGK(3B77'%#      9B Hm\;995B(L+ CI   k *      f "h Z @ @ "h 4 4   ( LAAK [ 11$ K}oI 9 --"*k:FFH ( ++ 4 )         1 11r/c|Ut|dkrB|jjt}n |jj}||j_|d|S)NrT)inplace)rr6rwSEPARATED_INDEX_COLUMN_NAME reset_index)rurrs r0rrsZC ..22 8= 2HHx}H   t$$$ Or/ column_namesct}g}|D]4}|||vr ||||5||S)zEReturns a subset of df, selecting only column_names that aren't None.)setaddappend)rurseenkeepr=s r0rrs^ 55D D  9  99    A d8Or/c|t||dkrdS||d}t|rdSt|r%||t||<dSdS)z=If needed, convert color column to a format Vega understands.Nr)rrrmapr)rurfirst_color_datums r0rr#ss2l#34499<(+*++    . / / l+// ==< r/4Tuple[str | None, List[str], str | None, str | None]ct|j}d|D}tj||_|dnt |d|D|dnt ||dnt |fS)zLConverts column names to strings, since Vega-Lite does not accept ints, etc.c,g|]}t|Sr.r.0cs r0 z6_convert_col_names_to_str_in_place..?s5551A555r/Nc,g|]}t|Sr.rrs r0rz6_convert_col_names_to_str_in_place..Ds'''AQ'''r/)listrrIndexr)rurrrrrstr_column_namess r0rr6s ##L55 555*++BJ c(mm'''''$#l*;*;#[)9)9  r/column_or_valuerTuple[str | None, Any]cXt|tr||jvr|}d}nd}|}||fSrr)ryrr)rur column_namer7s r0rrJsC/3'' Orz,I,I%    r/c|dSt|tr||jvrt|||St d|dt |d)Nz^x parameter should be a column name (str) or None to use the dataframe's index. Value given:  (type ))ryrrStreamlitColumnNotFoundErrorrtype)rurLs r0rrWst K % %  bj ( (.r;?? ?$ *0; * *+&& * * *   r/cg}|t|j}njt|tr|g}nQt j|rtd|D}n#t d|dt|d|D]}||jvrt||||vr|r||vr| ||S)Nc34K|]}t|VdSrrr)rcols r0 z#_parse_y_columns..ws(==#SXX======r/zHy parameter should be a column name (str) or list thereof. Value given: rr) rrryrr is_sequencerrrremove)rurMrrrs r0rris "MRZ(( K % %  $  { + + ======= $ E' E E04[0A0A E E E   88 bj .r377 7 !=  + 9T9TX&&& r/alt.OpacityValue | NonecRddl}|r |tjkr|jdSdS)Nrgffffff?)rr!r* OpacityValue)rKrrs r0rrs<% in44s$$$ 4r/r alt.Scalecjddl}t||r|jdS|jS)Nrutc)r)rr|Scale)rurrs r0 _get_scalersEr;''%sye$$$$ 39;;r/gridalt.Axisc~ddl}|'t||r|jd|S|j|S)Nr) tickMinSteprr)rrAxis)rurrrs r0_get_axis_configrsT#3B{O#D#DsxAD1111 38   r/+Tuple[pd.DataFrame, str | None, str | None]ct|dkrd}nZt|dkr |d}n>|d ||D} |j | | d <d| d <n | SdS) Nrrc,g|]}t|Sr.rrs r0rz'_get_color_encoding..@s*Q*Q*Qq<??*Q*Q*Qr/)rangenominal )rrlegendrr)rrrrc,g|]}t|Sr.rrs r0rz'_get_color_encoding..]sNNNq<??NNNr/rr)rtuplerrrrStreamlitColorLengthError ColorValuerryrr rrCOLOR_LEGEND_SETTINGSStreamlitInvalidColorErrorrrinfer_vegalite_typer) rurrrrNrhas_color_value color_values column_typer color_ranges r0rrsw!$EGG)< c;// 0 0 =!!Q&&/ }MMM!3>,tC/E/E"F"FGG G dE] 3 3  5 1;??L<  C $6$666/ mLLL;1$$%s~l4[^3L3L&M&MNNN sy&##)*Q*QL*Q*Q*QRRR0" )_===  ! 3 3 3#KK#7<8HIIKCI'<;   3 3 3"%Ig  L! " " }R 5Ea5H'I'I NNB|4D4K4K4M4MNNNK!*!=!=!=Ig #'Ih    4r/ralt.Size | alt.SizeValue | NonecRddl}|tjkrv||j|tSt |t tfr|j|S||jdStdt|||td|j ddS)Nr)rrz&This does not look like a valid size: z Chart type z: does not support size argument. This should never happen!) rr!r-SizeSIZE_LEGEND_SETTINGSryfloatrF SizeValuerreprrrw)rKrrrs r0rros Y&&&  "38+   UCL 1 1  3=,, ,   3=%% %'Kj9I9IKK   J$: (*/ ( ( (   4r/rlist[alt.Tooltip]cddl}g}|tkr+||j|tn#||j||t kr,||j|t dn#||j||rkt|ddZ|tkr,||j|tdn#||j||r#||j||S)Nr)r quantitative)rrrTr) rrrTooltipSEPARATED_INDEX_COLUMN_TITLErMELTED_Y_COLUMN_TITLEgetattrrMELTED_COLOR_COLUMN_TITLE)rrrrrrrs r0rrs|G...{s{83OPPPQQQQ{s{8,,---''' CK+#        {s{8,,---  6 8T::F 3 3 3 NN  3"     NN;3;|44 5 5 51{s{;//000 Nr/type_util.VegaLiteTypec|dS|tjkrt||sdStj||S)Nr1ordinal)r!r+r|rr#)rurKrs r0r r sG~Y]""?2x+H+H"y  (H 6 66r/c>|rtj||SdS)Nr1)rr#)rurs r0rrs&;,R\::: >r/FrPvega_lite_chartrVrkrlrArRNone | Literal['streamlit']kwargsNonec ddl}id fd }|jd||jjdkr|jdn t 5|jd5|}|d <tj ||f||d |dddn #1swxYwYddddS#1swxYwYdS) z!Marshall chart's data into proto.rNrHDict[str, str]cNtt|}||<d|iS)z^Altair data transformer that returns a fake named dataset with the object id. rw)rid)rBrwdatasetss r0 id_transformzmarshall..id_transforms)2d88}}~r/rBdefaultnonerCro)rHr@) rdata_transformersregisterthemesactiveenablerto_dictarrow_vega_literX) r;rkrArRr=rrD chart_dictrCs @r0rXrXsH""4666 '*j&79&D&D  6 " " "+--  " ) )$ / /  %--//J&.Jz "  $ %8                       s6!C<0B8, C8B< <C?B< CCCceZdZfdZxZS)rcddt|jD}d|d|d}tj|g|RdS)N, c34K|]}t|VdSrrrrs r0rz8StreamlitColumnNotFoundError.__init__.. s(%G%Gc!ff%G%G%G%G%G%Gr/z$Data does not have a column named `"z"`. Available columns are ``joinrrsuper__init__)r\rucol_nameargsavailable_columnsmessage __class__s r0rWz%StreamlitColumnNotFoundError.__init__ s} II%G%Gd2:6F6F%G%G%GGG ;8 ; ;&7 ; ; ;  (4((((((r/r'r(r)rW __classcell__r\s@r0rr 8)))))))))r/rceZdZfdZxZS)r"cddt|jDd|d}tj|g|RdS)NrQc34K|]}t|VdSrrrrs r0rz6StreamlitInvalidColorError.__init__..s(33Q#a&&333333r/z2 This does not look like a valid color argument: `a5`. The color argument can be: * A hex string like "#ffaa00" or "#ffaa0088". * An RGB or RGBA tuple with the red, green, blue, and alpha components specified as ints from 0 to 255 or floats from 0.0 to 1.0. * The name of a column. * Or a list of colors, matching the number of y columns to draw. rT)r\rurNrYr[r\s r0rWz#StreamlitInvalidColorError.__init__sn 33$rz"2"2333333  2A     (4((((((r/r]r_s@r0r"r"s8)))))))))r/r"ceZdZfdZxZS)rcNd|d|d}tj|g|RdS)NzThe list of colors `zB` must have the same length as the list of columns to be colored `z`.)rVrW)r\r%rrYr[r\s r0rWz"StreamlitColorLengthError.__init__'sR "< " " " " "  (4((((((r/r]r_s@r0rr&r`r/r)rurvrwrCrHrG) rurvr}r~rrrrrrrHrv) rurvrrCrr~rrCrrCrHr)NNNNrr)rKr!rBrrLrCrMrDrNrErOrr?rFr@rFrHr)rurvrrCrr~rHrC)rurvrrCrHrv)rurvrrC) rurvrrCrr~rrCrrCrHr)rurvrrrHr)rurvrLrCrHrC)rurvrMrDrrCrHr~)rKr!rrCrHr)rurvrrCrHr)rurvrrCrrGrHr) rurvrrCrr~rrCrrCrHr) rurvrrCrLrCrKr!rHr)rurvrrCrMrDrHr ) rurvrrrrCrr~rNrErHr)rKr!rrCrrrHr() rrrrrrCrrCrrrHr/)rurvrKr!rrCrHr7)rurvrrCrHr7rs) r;rVrkrlrArGrRr<r=rrHr>)]__doc__ __future__r contextlibrdatetimerenumrtypingrrr r r r r rpandasrpandas.api.typesrrtyping_extensionsr"streamlit.elements.arrow_vega_liteelementsrMrPrstreamlit.color_utilrrrrrstreamlit.elements.altair_utilsrstreamlit.elements.arrowrstreamlit.elements.utilsrstreamlit.errorsrr&streamlit.proto.ArrowVegaLiteChart_pb2rrVstreamlit.runtime.metrics_utilrrrstreamlit.delta_generatorrr!rr!r+r3r4r6PROTECTION_SUFFIXrrrrr;r|rrrWrrrrrrrrrrrrrrrrr rrXrr"rr.r/r0rzsT#"""""""""""TTTTTTTTTTTTTTTTTTTT::::::::%%%%%%<<<<<<<<<<;;;;;))))))EEEEEE99999999:999999888888&&&&&&&&&!AhGGGtQxHHH '#-:=NN,/@@47HH,.??M ,M ,M ,M ,M ,M ,M ,M ,`,,,,6&&&&R)F)F)F)F^#.28<)-Z2Z2Z2Z2Z2z"*    &(        $B    &&&&D%%%%P$$$$NMMMM`@2222j 7 7 7 7!&)4 ,,,,,^)))))#8))))))))!6)))$))))) 5)))))r/