fe_cyclical_cosine_and_plot.py

# We normalize x values to match with the 0-2π cycle
df["x_norm"] = 2 * math.pi * df["x"] / df["x"].max()

df["cos_x"] = np.cos(df["x_norm"])

display(df)

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(x=df.x_norm, y=df.cos_x))

fig.update_layout(yaxis=dict(scaleanchor="x", scaleratio=1))

fig.show()