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QuickEcharts

QuickEcharts is a Python package that enables one to plot Echarts quickly. It piggybacks off of the pyecharts package that pipes into Apache Echarts. Pyecharts is a great package for fully customizing plots but is quite a challenge to make use of quickly. QuickEcharts solves this with a simple API for defining plotting elements and data, along with automatic data wrangling operations, using polars, to correctly structure data fast.

For the Code Examples below, there is a dataset in the QuickEcharts/datasets folder named FakeBevData.csv that you can download for replication purposes.

Installation

pip install QuickEcharts

or 

pip install git+https://github.com/AdrianAntico/QuickEcharts.git#egg=quickecharts

Run Shiny App

from QuickEcharts.shiny_app import run_app
run_app(port=8001)

Code Examples


Area

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Area(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = None,
  FacetRows = 2,
  FacetCols = 2,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = "Area Plot",
  Opacity = 0.50,
  GradientColors = ['#e12191', '#0011FF'],
  LineWidth = 1,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Area Plot',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = "Gradient Colors",
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = "Daily Liters",
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '2%',
  LegendBorderSize = 0.25,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Area(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  FacetRows = 1,
  FacetCols = 1,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  Opacity = 0.5,
  GradientColors = ['#c86589', '#06a7ff0d'],
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Line Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

brand = data['Brand'].unique()
brand = [b for b in brand if b != "#N/A"]

plot_list = [None] * len(brand)
for i in range(len(brand)):
  plot_list[i] = Charts.Area(
    dt = data.filter(pl.col('Brand') == brand[i]),
    PreAgg = False,
    YVar = 'Daily Liters',
    XVar = 'Date',
    GroupVar = None,
    FacetRows = 1,
    FacetCols = 1,
    FacetLevels = None,
    TimeLine = False,
    AggMethod = 'sum',
    YVarTrans = "Identity",
    RenderHTML = "Area Plot",
    Opacity = 0.50,
    GradientColors = ['#e12191', '#0011FF'],
    LineWidth = 1,
    Symbol = "emptyCircle",
    SymbolSize = 6,
    ShowLabels = False,
    LabelPosition = "top",
    Theme = 'dark',
    BackgroundColor = None,
    Width = None,
    Height = None,
    ToolBox = True,
    Brush = True,
    DataZoom = True,
    Title = f'{brand[i]}',
    TitleColor = "lightgray",
    TitleFontSize = 20,
    SubTitle = "Gradient Colors",
    SubTitleColor = "#fff",
    SubTitleFontSize = 12,
    AxisPointerType = 'cross',
    YAxisTitle = "Daily Liters",
    YAxisNameLocation = 'middle',
    YAxisNameGap = 70,
    XAxisTitle = None,
    XAxisNameLocation = 'middle',
    XAxisNameGap = 42,
    Legend = 'top',
    LegendPosRight = '0%',
    LegendPosTop = '2%',
    LegendBorderSize = 0.25,
    LegendTextColor = "#fff",
    VerticalLine = None,
    VerticalLineName = 'Line Name',
    HorizontalLine = None,
    HorizontalLineName = 'Line Name',
    AnimationThreshold = 2000,
    AnimationDuration = 1000,
    AnimationEasing = "cubicOut",
    AnimationDelay = 0,
    AnimationDurationUpdate = 300,
    AnimationEasingUpdate = "cubicOut",
    AnimationDelayUpdate = 0)

Charts.display_plots_grid(
  plot_list,
  cols = 3,
  render = "html")


Bar

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Bar(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = None,
  FacetCols = 1,
  FacetRows = 1,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Bar Plot',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = 'Daily Liters',
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = 'Date',
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '2%',
  LegendBorderSize = 1,
  LegendTextColor = "#lightgray",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Bar(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  FacetCols = 1,
  FacetRows = 1,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Bar Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Bar(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  FacetCols = 2,
  FacetRows = 2,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Bar Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Bar3D

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Bar3D(
  dt = data,
  PreAgg = False,
  YVar = 'Brand',
  XVar = 'Category',
  ZVar = 'Daily Liters',
  AggMethod = 'mean',
  ZVarTrans = "logmin",
  RenderHTML = None,
  Theme = 'wonderland',
  BarColors = ["#00b8ff", "#0097e1", "#0876b8", "#004fa7", "#012e6d"],
  BackgroundColor = "#000",
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Bar3D Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Box

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.BoxPlot(
  dt = data,
  SampleSize = 100000,
  YVar = 'Daily Liters',
  GroupVar = 'Brand',
  YVarTrans = "logmin",
  RenderHTML = None,
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Box Plot',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 42,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '2%',
  LegendBorderSize = 1,
  LegendTextColor = "lightgray",
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Copula

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Copula(
  dt = data,
  SampleSize = 15000,
  YVar = 'Daily Liters',
  XVar = 'Daily Units',
  GroupVar = None,
  FacetRows = 2,
  FacetCols = 2,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'mean',
  RenderHTML = None,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Copula Plot',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = 'Daily Liters',
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = 'Daily Units',
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '2%',
  LegendBorderSize = 1,
  LegendTextColor = "lightgray",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Copula(
  dt = data,
  SampleSize = 15000,
  YVar = 'Daily Liters',
  XVar = 'Daily Units',
  GroupVar = 'Brand',
  FacetRows = 1,
  FacetCols = 1,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'mean',
  RenderHTML = None,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Copula Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Copula(
  dt = data,
  SampleSize = 15000,
  YVar = 'Daily Liters',
  XVar = 'Daily Units',
  GroupVar = 'Brand',
  FacetRows = 2,
  FacetCols = 2,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'mean',
  RenderHTML = None,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Copula Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Copula3D

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Copula3D(
  dt = data,
  SampleSize = 15000,
  YVar = 'Daily Liters',
  XVar = 'Daily Units',
  ZVar = 'Daily Margin',
  ColorMapVar = "ZVar",
  AggMethod = 'mean',
  RenderHTML = None,
  RangeColor = ["red", "white", "blue"],
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Density

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Density(
  dt = data,
  SampleSize = 500000,
  YVar = "Daily Liters",
  GroupVar = None,
  FacetRows = 2,
  FacetCols = 2,
  FacetLevels = None,
  TimeLine = False,
  YVarTrans = "sqrt",
  RenderHTML = None,
  LineWidth = 2,
  FillOpacity = 0.5,
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Density Plot',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  XAxisTitle = 'Daily Liters',
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '2%',
  LegendBorderSize = 0.25,
  LegendTextColor = "lightgray",
  VerticalLine = 5,
  VerticalLineName = 'Line Name',
  HorizontalLine = 225000,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Density(
  dt = data,
  SampleSize = 100000,
  YVar = "Daily Liters",
  GroupVar = 'Brand',
  FacetRows = 2,
  FacetCols = 2,
  FacetLevels = None,
  TimeLine = False,
  YVarTrans = "sqrt",
  RenderHTML = None,
  LineWidth = 2,
  FillOpacity = 0.5,
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Density Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Donut

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Donut(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  GroupVar = 'Brand',
  AggMethod = 'count',
  YVarTrans = "Identity",
  RenderHTML = None,
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  Title = 'Donut Chart',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  Legend = 'right',
  LegendPosRight = '5%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "lightgray",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Funnel

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Funnel(
  dt = data,
  CategoryVar = ['Daily Units', 'Daily Revenue', 'Daily Margin', 'Daily Liters'],
  ValuesVar = [100, 80, 60, 40],
  RenderHTML = None,
  SeriesLabel = "Funnel Data",
  SortStyle = 'descending',
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  Title = "Funnel",
  TitleColor = "lightgray",
  TitleFontSize = 20,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '2%',
  LegendBorderSize = 0.25,
  LegendTextColor = "lightgray",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Funnel(
  dt = data,
  CategoryVar = ['Daily Units', 'Daily Revenue', 'Daily Margin', 'Daily Liters'],
  ValuesVar = [100, 80, 60, 40],
  RenderHTML = None,
  SeriesLabel = "Funnel Data",
  SortStyle = 'ascending',
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  Title = "Funnel",
  TitleColor = "lightgray",
  TitleFontSize = 20,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '2%',
  LegendBorderSize = 0.25,
  LegendTextColor = "lightgray",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Heatmap

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Heatmap(
  dt = data,
  PreAgg = False,
  YVar = 'Brand',
  XVar = 'Category',
  MeasureVar = 'Daily Liters',
  AggMethod = 'mean',
  MeasureVarTrans = "Identity",
  RenderHTML = None,
  ShowLabels = False,
  LabelPosition = "top",
  LabelColor = "#fff",
  Theme = 'dark',
  RangeColor = ["#5b5b5b5d", "#00c4ff", "#9cff00"],
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Heatmap',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '2%',
  LegendBorderSize = 0.25,
  LegendTextColor = "lightgray",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Histogram

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Histogram(
  dt = data,
  SampleSize = 100000,
  YVar = "Daily Liters",
  GroupVar = None,
  FacetRows = 2,
  FacetCols = 2,
  FacetLevels = None,
  TimeLine = False,
  YVarTrans = "logmin",
  RenderHTML = True,
  Theme = 'dark',
  CategoryGap = "0%",
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Histogram',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  XAxisTitle = "Horray",
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = 'right',
  LegendPosRight = '0%',
  LegendPosTop = '15%',
  LegendBorderSize = 0.25,
  LegendTextColor = "lightgray",
  VerticalLine = 10,
  VerticalLineName = 'Line Name',
  HorizontalLine = 40000,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "elasticOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Histogram(
  dt = data,
  SampleSize = 500000,
  YVar = 'Daily Liters',
  GroupVar = 'Brand',
  FacetRows = 2,
  FacetCols = 2,
  FacetLevels = None,
  TimeLine = False,
  YVarTrans = None,
  RenderHTML = False
  NumberBins = 20,
  CategoryGap = "10%",
  Theme = 'wonderland',
  BackgroundColor = "#000",
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Histogram',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Line

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Line(
  dt = data,
  PreAgg = False,
  YVar = ['Daily Liters', 'Daily Margin', 'Daily Revenue', 'Daily Units'],
  XVar = 'Date',
  GroupVar = None,
  FacetRows = 1,
  FacetCols = 1,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  SmoothLine = True,
  LineWidth = 2,
  Symbol = None,
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Line Plot',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = 'Date',
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = 'right',
  LegendPosRight = '5%',
  LegendPosTop = '15%',
  LegendBorderSize = 1,
  LegendTextColor = "lightgray",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Line(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  FacetRows = 1,
  FacetCols = 1,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  SmoothLine = True,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Line Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Line(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  FacetRows = 2,
  FacetCols = 2,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  SmoothLine = True,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Line Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Parallel

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Parallel(
  dt = data,
  SampleSize = 15000,
  Vars = ['Daily Liters', 'Daily Units', 'Daily Revenue', 'Daily Margin'],
  VarsTrans = ['logmin'] * 4,
  RenderHTML = None,
  SymbolSize = 6,
  Opacity = 0.05,
  LineWidth = 0.20,
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  Title = 'Parallel Plot',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Pie

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Pie(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  GroupVar = 'Brand',
  AggMethod = 'count',
  YVarTrans = None,
  RenderHTML = None,
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  Title = 'Pie Chart',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  Legend = "right",
  LegendPosRight = '5%',
  LegendPosTop = '5%',
  LegendBorderSize = 0.25,
  LegendTextColor = "#fff",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Radar

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Radar(
  dt = data,
  YVar = ['Daily Liters', 'Daily Margin'],
  GroupVar = 'Brand',
  AggMethod = 'mean',
  YVarTrans = None,
  RenderHTML = None,
  LabelColor = '#fff',
  LineColors = ["#ed1690", "#8e5fa8", "#00a6fb", "#213f7f", "#22c0df"],
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  Title = 'Radar Chart',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  Legend = 'right',
  LegendPosRight = '2%',
  LegendPosTop = '5%',
  LegendBorderSize = 0.25,
  LegendTextColor = "#fff",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


River

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.River(
  dt = data,
  PreAgg = False,
  YVars = ['Daily Liters', 'Daily Units', 'Daily Revenue', 'Daily Margin'],
  DateVar = 'Date',
  GroupVar = None,
  AggMethod = "sum",
  YVarTrans = None,
  RenderHTML = None,
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  AxisPointerType = "cross",
  Title = "River Plot",
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  Legend = 'right',
  LegendPosRight = '5%',
  LegendPosTop = '15%',
  LegendBorderSize = 0.25,
  LegendTextColor = "lightgray",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.River(
  dt = data,
  PreAgg = False,
  YVars = 'Daily Liters',
  DateVar = 'Date',
  GroupVar = 'Brand',
  AggMethod = "sum",
  YVarTrans = None,
  RenderHTML = None,
  Theme = 'wonderland',
  BackgroundColor = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Width = None,
  Height = None,
  AxisPointerType = "cross",
  Title = "River Plot",
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Rosetype

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Rosetype(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  GroupVar = 'Brand',
  AggMethod = 'count',
  YVarTrans = "Identity",
  RenderHTML = None,
  Type = "radius",
  Radius = "55%",
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  Title = 'Rosetype Chart',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  Legend = 'right',
  LegendPosRight = '5%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "lightgray",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Scatter

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Scatter(
  dt = data,
  SampleSize = 15000,
  YVar = 'Daily Liters',
  XVar = 'Daily Units',
  GroupVar = None,
  FacetRows = 1,
  FacetCols = 1,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'mean',
  YVarTrans = "logmin",
  XVarTrans = "logmin",
  RenderHTML = None,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Scatter Plot',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = 'Daily Liters',
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = 'Daily Units',
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = 'top',
  LegendPosRight = '0%',
  LegendPosTop = '2%',
  LegendBorderSize = 1,
  LegendTextColor = "lightgray",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Scatter(
  dt = data,
  SampleSize = 15000,
  YVar = 'Daily Liters',
  XVar = 'Daily Units',
  GroupVar = 'Brand',
  FacetRows = 1,
  FacetCols = 1,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'mean',
  YVarTrans = "Identity",
  XVarTrans = "Identity",
  RenderHTML = None,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Scatter Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Scatter(
  dt = data,
  SampleSize = 15000,
  YVar = 'Daily Liters',
  XVar = 'Daily Units',
  GroupVar = 'Brand',
  FacetRows = 2,
  FacetCols = 2,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'mean',
  YVarTrans = "Identity",
  XVarTrans = "Identity",
  RenderHTML = None,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Scatter Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Scatter3D

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Scatter3D(
  dt = data,
  SampleSize = 15000,
  YVar = 'Daily Liters',
  XVar = 'Daily Units',
  ZVar = 'Daily Margin',
  ColorMapVar = "ZVar",
  AggMethod = 'mean',
  YVarTrans = "logmin",
  XVarTrans = "logmin",
  ZVarTrans = "logmin",
  RenderHTML = None,
  SymbolSize = 6,
  Theme = 'dark',
  RangeColor = ["red", "white", "blue"],
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Stacked Area

Click for code example 
# Environment
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.StackedArea(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  Opacity = 0.5,
  LineWidth = 2,
  Symbol = None,
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'dark',
  BackgroundColor = None,
  Width = "1200px",
  Height = "750px",
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Stacked Area',
  TitleColor = "lightgray",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = "right",
  LegendPosRight = '2%',
  LegendPosTop = '10%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Stacked Bar

Click for code example 
# Environment
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.StackedBar(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Stacked Bar',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Stacked Line

Click for code example 
# Environment
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.StackedLine(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  SmoothLine = True,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Stacked Line',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Stacked Step

Click for code example 
# Environment
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.StackedStep(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Width = None,
  Height = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Area Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Step

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Step(
  dt = data,
  PreAgg = False,
  YVar = ['Daily Liters', 'Daily Margin', 'Daily Revenue', 'Daily Units'],
  XVar = 'Date',
  GroupVar = None,
  FacetRows = 1,
  FacetCols = 1,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Height = None,
  Width = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Line Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Step(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  FacetRows = 1,
  FacetCols = 1,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Height = None,
  Width = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Line Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.Step(
  dt = data,
  PreAgg = False,
  YVar = 'Daily Liters',
  XVar = 'Date',
  GroupVar = 'Brand',
  FacetRows = 2,
  FacetCols = 2,
  FacetLevels = None,
  TimeLine = False,
  AggMethod = 'sum',
  YVarTrans = "Identity",
  RenderHTML = None,
  LineWidth = 2,
  Symbol = "emptyCircle",
  SymbolSize = 6,
  ShowLabels = False,
  LabelPosition = "top",
  Theme = 'wonderland',
  BackgroundColor = None,
  Height = None,
  Width = None,
  ToolBox = True,
  Brush = True,
  DataZoom = True,
  Title = 'Line Plot',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  AxisPointerType = 'cross',
  YAxisTitle = None,
  YAxisNameLocation = 'middle',
  YAxisNameGap = 70,
  XAxisTitle = None,
  XAxisNameLocation = 'middle',
  XAxisNameGap = 42,
  Legend = None,
  LegendPosRight = '0%',
  LegendPosTop = '5%',
  LegendBorderSize = 1,
  LegendTextColor = "#fff",
  VerticalLine = None,
  VerticalLineName = 'Line Name',
  HorizontalLine = None,
  HorizontalLineName = 'Line Name',
  AnimationThreshold = 2000,
  AnimationDuration = 1000,
  AnimationEasing = "cubicOut",
  AnimationDelay = 0,
  AnimationDurationUpdate = 300,
  AnimationEasingUpdate = "cubicOut",
  AnimationDelayUpdate = 0)

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()


Word Cloud

Click for code example 
# Environment
import pkg_resources
import polars as pl
from QuickEcharts import Charts
from pyecharts.globals import CurrentConfig, NotebookType 
CurrentConfig.NOTEBOOK_TYPE = 'jupyter_lab'

# Pull Data from Package
FilePath = "..FakeBevData.csv"
data = pl.read_csv(FilePath)

# Create Plot in Jupyter Lab
p1 = Charts.WordCloud(
  dt = data,
  SampleSize = 100000,
  YVar = 'Brand',
  RenderHTML = None,
  SymbolType = 'diamond',
  Title = 'Word Cloud',
  TitleColor = "#fff",
  TitleFontSize = 20,
  SubTitle = None,
  SubTitleColor = "#fff",
  SubTitleFontSize = 12,
  Theme = 'wonderland')

# Needed to display
p1.load_javascript()

# In new cell
p1.render_notebook()

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for AdrianAntico from gravatar.com AdrianAntico

Credits

Data verified by PyPI on Dec 14, 2025
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI. Confirms that the provided email matches a verified, public email address on a PyPI user account associated with the project.

Author: Adrian Antico

License

MIT License (MIT)

Requires

Python >=3.10

Classifiers

Report project as malware

Metadata

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for AdrianAntico from gravatar.com AdrianAntico

Credits

Data verified by PyPI on Dec 14, 2025
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI. Confirms that the provided email matches a verified, public email address on a PyPI user account associated with the project.

Author: Adrian Antico

License

MIT License (MIT)

Requires

Python >=3.10

Classifiers

Report project as malware

Release files for QuickEcharts 2.1.8

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for QuickEcharts 2.1.8
File Size Uploaded
quickecharts-2.1.8.tar.gz 47.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for QuickEcharts 2.1.8
File Interpreter ABI Platform
quickecharts-2.1.8-py3-none-any.whl 40.8 kB Python 3 none any Details

Total release size: 88.0 kB

Release files / quickecharts-2.1.8.tar.gz

Download URL quickecharts-2.1.8.tar.gz
Size 47.1 kB
Tags Source
SHA-256 checksum
How to use checksums 		64c80f479a8567ba4708658f738ed9a1f2159b3e862e7267656eba277996882f
BLAKE2b-256 checksum
How to use checksums 		6e7b16d2cd4c8680d3606142d51bcbdbbdfb1f51d9b0da9617ca7c554e5e1079
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Uploaded using Trusted Publishing?
What is trusted publishing? 		No
Uploaded via twine/6.2.0 CPython/3.11.11

Release files / quickecharts-2.1.8-py3-none-any.whl

Download URL quickecharts-2.1.8-py3-none-any.whl
Size 40.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums 		d2891a80dec43fcdc8700f2233786043f05335e72628c0e6efc373f783a5187b
BLAKE2b-256 checksum
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What is trusted publishing? 		No
Uploaded via twine/6.2.0 CPython/3.11.11

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2.1.8 This release

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2 release files

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2 release files

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