Plot rows of df on Plotly - dataframe

Question

The df is like this:
X Y Label
0 [16, 37, 38] [7968, 4650, 3615] 0.7
1 [29, 37, 12] [4321, 4650, 1223] 0.8
2 [12, 2, 445] [1264, 3456, 2112] 0.9
This should plot three lines on the same plot with labels as continuous variables. What is the fastest & simplest way to plot it using plotly?

Answer 1

Taking This should plot three lines on the same plot as the requirement. (Which is inconsistent with where I want subplots from each row of the df)
Simple case of create a trace for each row, using https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.explode.html to prepare x and y
import pandas as pd
import plotly.graph_objects as go
df = pd.DataFrame(
{
"X": [[16, 37, 38], [29, 37, 12], [12, 2, 445]],
"Y": [[7968, 4650, 3615], [4321, 4650, 1223], [1264, 3456, 2112]],
"Label": [0.7, 0.8, 0.9],
}
)
go.Figure(
[
go.Scatter(
x=r["X"].explode(), y=r["Y"].explode(), name=str(r["Label"].values[0])
)
for _, r in df.groupby(df.index)
]
)
with continuous color defined by label
import pandas as pd
import plotly.graph_objects as go
from plotly.colors import sample_colorscale
import plotly.express as px
df = pd.DataFrame(
{
"X": [[16, 37, 38], [29, 37, 12], [12, 2, 445]],
"Y": [[7968, 4650, 3615], [4321, 4650, 1223], [1264, 3456, 2112]],
"Label": [0.1, 0.5, 0.9],
}
)
fig = px.scatter(x=[0], y=[0], color=[.5], color_continuous_scale="YlGnBu")
fig = fig.add_traces(
[
go.Scatter(
x=r["X"].explode(),
y=r["Y"].explode(),
name=str(r["Label"].values[0]),
line_color=sample_colorscale("YlGnBu", r["Label"].values[0])[0],
showlegend=False
)
for _, r in df.groupby(df.index)
]
)
fig