Plotly

import plotly.express as px
import pandas as pd
 
df = pd.read_csv("sales.csv", parse_dates=["ordered_at"])
fig = px.line(df, x="ordered_at", y="revenue", color="region", title="Revenue trend")
fig.update_layout(hovermode="x unified")
fig.write_html("revenue.html", include_plotlyjs="cdn")

import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
import numpy as np
 
rng = np.random.default_rng(42)
df = pd.DataFrame(
    {
        "region": np.repeat(["East", "West"], 100),
        "month": np.tile(np.arange(1, 13).repeat(8)[:100], 2),
        "revenue": rng.integers(80, 200, 200),
        "units": rng.integers(5, 50, 200),
    }
)
 
# Express scatter with custom hover
fig_scatter = px.scatter(
    df,
    x="units",
    y="revenue",
    color="region",
    hover_data=["month"],
    opacity=0.7,
    title="Units vs revenue",
)
fig_scatter.update_traces(marker=dict(size=8))
 
# Graph objects for dual-axis combo
monthly = df.groupby(["month", "region"], observed=True)["revenue"].sum().reset_index()
fig_combo = go.Figure()
for region, sub in monthly.groupby("region"):
    fig_combo.add_trace(
        go.Scatter(x=sub["month"], y=sub["revenue"], mode="lines+markers", name=region)
    )
fig_combo.update_layout(
    xaxis_title="Month",
    yaxis_title="Revenue",
    legend_title="Region",
    template="plotly_white",
)
 
fig_scatter.write_html("scatter.html", include_plotlyjs="cdn")
fig_combo.write_html("combo.html", include_plotlyjs="cdn")

import plotly.io as pio
 
# Static image export needs kaleido
pio.write_image(fig, "chart.png", scale=2)