I know there are Plotly.jl and PlotlyJS.jl. But, it would be nice to provide a Pythonista-friendly Julia interface for plotly since there are lots of examples on the internet regarding plotly written in Python.
$ pip3 install numpy pandas plotly
$ git clone https://github.com/AtelierArith/PyPlotly.jl.git
$ cd PyPlotly
$ julia --project=@. -e 'using Pkg; Pkg.isinstance()'Let's assume you've written a Python script something like:
import plotly.graph_objects as go
# Create random data with numpy
import numpy as np
np.random.seed(1)
N = 100
random_x = np.linspace(0, 1, N)
random_y0 = np.random.randn(N) + 5
random_y1 = np.random.randn(N)
random_y2 = np.random.randn(N) - 5
fig = go.Figure()
# Add traces
fig.add_trace(go.Scatter(x=random_x, y=random_y0,
mode='markers',
name='markers'))
fig.add_trace(go.Scatter(x=random_x, y=random_y1,
mode='lines+markers',
name='lines+markers'))
fig.add_trace(go.Scatter(x=random_x, y=random_y2,
mode='lines',
name='lines'))
fig.show()The example above is taken from Line and Scatter Plots. You can translate the python code into Julia code as below:
using PyPlotly # this exports `go` and `px`
using Random
Random.seed!(1)
N = 100
random_x = range(0, 1, length=N)
random_y0 = randn(N) .+ 5
random_y1 = randn(N)
random_y2 = randn(N) .- 5
fig = go.Figure()
# Add traces
fig.add_trace(go.Scatter(x=random_x, y=random_y0,
mode="markers",
name="markers"))
fig.add_trace(go.Scatter(x=random_x, y=random_y1,
mode="lines+markers",
name="lines+markers"))
fig.add_trace(go.Scatter(x=random_x, y=random_y2,
mode="lines",
name="lines"))
figTry running the following example in your notebook
using PyPlotly
df = px.data.iris()
fig = px.scatter(
df,
x="sepal_width",
y="sepal_length",
color="species",
size="petal_length",
hover_data=["petal_width"],
)
fig
Code is available from here.