Inspecting data from: https://github.com/gradlab/CtTrajectories.

nba_covid.py

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

csv_url = "https://raw.githubusercontent.com/gradlab/CtTrajectories/main/data/ct_dat_clean.csv"
df = pd.read_csv(csv_url)

person_ids = df["Person.ID"].unique()
(min_x, max_x) = (df["Date.Index"].min(), df["Date.Index"].max())
(min_y, max_y) = (df["CT.Mean"].min(), df["CT.Mean"].max())
(rows, cols) = (8, 9)

(fig, axs) = plt.subplots(rows, cols)
symptom_min_ct = []
asymptom_min_ct = []
for (person_idx, person_id) in enumerate(person_ids):
    (row, col) = (person_idx // cols, person_idx % cols)
    ax = axs[row][col]
    person_data = df[df["Person.ID"] == person_id]
    first_symptoms = person_data[person_data["Symptomatic"] == "Yes"]
    color = "red" if len(first_symptoms) > 0 else "blue"
    sns.lineplot(
        x="Date.Index",
        y="CT.Mean",
        data=person_data,
        # marker=markers[state_idx % len(markers)],
        color=color,
        ax=ax,
    )
    ax.set_xlim(min_x, max_x)
    ax.set_ylim(min_y, max_y)
    axs[row][col].invert_yaxis()
    ax.set_xlabel("")
    ax.set_ylabel("")
    ax.set_title(person_id, fontsize="small")

    if len(first_symptoms) > 0:
        ax.axvline(first_symptoms["Date.Index"].item(), color="black")
        symptom_min_ct.append(person_data["CT.Mean"].min())
    else:
        asymptom_min_ct.append(person_data["CT.Mean"].min())

plt.subplots_adjust(0.021, 0.036, 0.98, 0.967, 0.326, 0.707)
plt.show()

asymptom_min_ct.sort()
symptom_min_ct.sort()

print(np.median(symptom_min_ct))
print(np.median(asymptom_min_ct))
sns.histplot(symptom_min_ct)
plt.show()
sns.histplot(asymptom_min_ct)
plt.show()

symptom_days = df[df["Symptomatic"] == "Yes"]
symptom_and_positive_days = df[(df["Symptomatic"] == "Yes") & (df["CT.Mean"] < 40)]
symptom_and_negative_days = df[(df["Symptomatic"] == "Yes") & (df["CT.Mean"] == 40)]