Layout

from lplots.widgets.row import w_row
from lplots.widgets.select import w_select
import plotly.express as px

# Get the iris dataset
df = px.data.iris()

# Get numeric columns for axis selection
numeric_cols = df.select_dtypes(include=['float64', 'int64']).columns.tolist()

# Create a column of select widgets with defaults set to first two columns
x_axis = w_select(
    label="X-axis",
    options=numeric_cols,
    default=numeric_cols[0]
)
y_axis = w_select(
    label="Y-axis",
    options=numeric_cols,
    default=numeric_cols[1]
)

w_row(items=[x_axis, y_axis])

from lplots.widgets.column import w_column
from lplots.widgets.select import w_select
import plotly.express as px

# Get the iris dataset
df = px.data.iris()

# Get numeric columns for axis selection
numeric_cols = df.select_dtypes(include=['float64', 'int64']).columns.tolist()

# Create a column of select widgets with defaults set to first two columns
x_axis = w_select(
    label="X-axis",
    options=numeric_cols,
    default=numeric_cols[0]
)
y_axis = w_select(
    label="Y-axis",
    options=numeric_cols,
    default=numeric_cols[1]
)

w_column(items=[x_axis, y_axis])

from lplots.widgets.grid import w_grid
from lplots.widgets.plot import w_plot
import plotly.express as px

# Create some plots
df = px.data.iris()
fig1 = px.scatter(df, x="sepal_width", y="sepal_length", color="species")
fig2 = px.box(df, x="species", y="petal_length", color="species")
fig3 = px.histogram(df, x="petal_width", color="species")

plot1 = w_plot(source=fig1)
plot2 = w_plot(source=fig2)
plot3 = w_plot(source=fig3)

# Create a grid with 3 columns
with w_grid(columns=3) as g:
    # Add plots to the grid with different spans
    g.add(item=plot1, col_span=2)  # Spans 2 columns
    g.add(item=plot2, col_span=1)  # Spans 1 column
    g.add(item=plot3, col_span=3)  # Spans all columns