LINE
The LINE node creates a Plotly Line visualization for a given input DataContainer.Params:default : OrderedPair|DataFrame|Matrix|Vectorthe DataContainer to be visualizedReturns:out : Plotlythe DataContainer containing the Plotly Line visualization of the input data
Python Code
import plotly.graph_objects as go
from flojoy import DataFrame, Matrix, OrderedPair, Plotly, Vector, flojoy
from blocks.DATA.VISUALIZATION.template import plot_layout
from numpy import arange
from pandas.api.types import is_datetime64_any_dtype
@flojoy
def LINE(default: OrderedPair | DataFrame | Matrix | Vector) -> Plotly:
"""The LINE node creates a Plotly Line visualization for a given input DataContainer.
Parameters
----------
default : OrderedPair|DataFrame|Matrix|Vector
the DataContainer to be visualized
Returns
-------
Plotly
the DataContainer containing the Plotly Line visualization of the input data
"""
layout = plot_layout(title="LINE")
fig = go.Figure(layout=layout)
match default:
case OrderedPair():
x = default.x
if isinstance(default.x, dict):
dict_keys = list(default.x.keys())
x = default.x[dict_keys[0]]
y = default.y
fig.add_trace(go.Scatter(x=x, y=y, mode="lines"))
case DataFrame():
df = default.m
first_col = df.iloc[:, 0]
is_timeseries = False
if is_datetime64_any_dtype(first_col):
is_timeseries = True
if is_timeseries:
for col in df.columns:
if col != df.columns[0]:
fig.add_trace(
go.Scatter(
y=df[col].values,
x=first_col,
mode="lines",
name=col,
)
)
else:
for col in df.columns:
fig.add_trace(
go.Scatter(
y=df[col].values,
x=df.index,
mode="lines",
name=col,
)
)
case Matrix():
m = default.m
num_rows, num_cols = m.shape
x_ticks = arange(num_cols)
for i in range(num_rows):
fig.add_trace(
go.Scatter(x=x_ticks, y=m[i, :], name=f"Row {i+1}", mode="lines")
)
fig.update_layout(xaxis_title="Column", yaxis_title="Value")
case Vector():
y = default.v
x = arange(len(y))
fig.add_trace(go.Scatter(x=x, y=y, mode="lines"))
return Plotly(fig=fig)
Example
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In this example we’re simulating data from LINSPACE
, TIMESERIES
, MATRIX
and R_DATASET
and visualizing them with LINE
node which creates a Plotly Line visualization for each of the input node.