gistfile1.txt

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.read_csv("data.csv")
df.columns = [c.lower() for c in df.columns]
df = df[["period", "result", "starting_point_id", "online_hours", "undersupply_hours_pct", "oversupply_hours_pct",
         "is_late20min", "nd", "num_delivs"]]
df = df.rename(columns={
    "result": "group",
    "starting_point_id": "spid",
    "online_hours": "hours",
    "undersupply_hours_pct": "uh",
    "oversupply_hours_pct": "oh",
    "is_late20min": "late",
})

df["late_count"] = df["late"] * df["num_delivs"]
df["nd_count"] = df["nd"] * df["num_delivs"]

df_exp = df[df.period == "experiment"]

g = sns.histplot(
    data=df_exp[df_exp.uh < 0.8],
    x="uh",
    weights="num_delivs",
    hue="group",
    stat="probability",
    common_norm=False,
    bins=50,
)
g.set_yscale("log")
plt.show()