Conditional formatting of plotly scatterplot markers

Question

Problem:
I have a data set with x and y value pairs, plus lower_limit and upper_limit values for y .

I want to plot x vs. y in a plot.ly scatter plot, and colour the marker in green if lower_limit ≤ y ≤ upper_limit , else in red .

I know that I could use 2 traces, or add a color column in the DataFrame. However, I'd like to generate these colour on the fly and use one trace only.

Example:
Consider this data set:

   x   y  lower_limit  upper_limit
0  1  13           10           15
1  2  13           15           20
2  3  17           15           20

The first marker ( x =1, y =13) should be green, because lower_limit ≤ y ≤ upper_limit (10 ≤ 13 ≤ 15), just like the third one.
However the second should be red, because y < lower_limit .

I then want to produce this graph:

---

MWE:

import pandas as pd
import plotly.graph_objs as go
import plotly.plotly as py
import plotly.offline as po

data = [
    [1, 13, 10, 15],
    [2, 13, 15, 20],
    [3, 17, 15, 20]
]

df = pd.DataFrame(
    data,
    columns=['x', 'y', 'lower_limit', 'upper_limit']
)

trace = go.Scatter(
    x=df['x'],
    y=df['y'],
    mode='markers',
    marker=dict(
        size=42,
        # I want the color to be green if 
        # lower_limit ≤ y ≤ upper_limit
        # else red
        color='green',
    )
)

po.plot([trace])

Answer 1

I would suggest creating a new array which will store the color values, please find below the example which uses, np.where and np.logical_and to form your conditional comparison.

import plotly.offline as py
import plotly.graph_objs as go
from plotly.offline import init_notebook_mode, iplot, plot
from plotly import tools
import pandas as pd
import numpy
init_notebook_mode(connected=True)
data = [
    [1, 13, 10, 15],
    [2, 13, 15, 20],
    [3, 17, 15, 20]
]

df = pd.DataFrame(
    data,
    columns=['x', 'y', 'lower_limit', 'upper_limit']
)

#df['color'] = np.where(np.logical_and(df['lower_limit'] >= df['y'], df['y']  <= df['upper_limit']), 'green', 'red')

trace = go.Scatter(
    x=df['x'],
    y=df['y'],
    mode='markers',
    marker=dict(
        size=42,
        # I want the color to be green if lower_limit ≤ y ≤ upper_limit
        # else red
        color=np.where(np.logical_and(df['lower_limit'] <= df['y'], df['y']  <= df['upper_limit']), 'green', 'red'),
    )
)

iplot([trace])

References:

1. Pandas: np.where with multiple conditions on dataframes

2. Pandas: Ternary conditional operator for setting a value in a DataFrame