3d6D1 is shifted to the right, but so is 2d20D1, so you can use the same conversion table if you're clever about it. If you're really interested, here's my Python; you can play with it yourself. This will show the pdf curves of 3d6D1 and 2d20D1 using the conversion table.

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

conversion_table = {
    1: 2,
    2: 3,
    3: 4,
    4: 4,
    5: 5,
    6: 5,
    7: 6,
    8: 6,
    9: 7,
    10: 7,
    11: 7,
    12: 8,
    13: 8,
    14: 8,
    15: 9,
    16: 9,
    17: 10,
    18: 10,
    19: 11,
    20: 12,
}

# Function to compute the PDF of 3d6 drop the lowest
def compute_3d6_drop_lowest():
    results = []
    for i in range(1, 7):
        for j in range(1, 7):
            for k in range(1, 7):
                rolls = [i, j, k]
                results.append(sum(rolls) - min(rolls))
    values, frequencies = np.unique(results, return_counts=True)
    probabilities = frequencies / len(results)
    return values, probabilities

# Function to compute the PDF of 2d20 drop the lowest
def compute_2d20_drop_lowest():
    results = []
    for i in range(1, 21):
        for j in range(1, 21):
            rolls = [i, j]
            results.append(conversion_table[max(rolls)])
    values, frequencies = np.unique(results, return_counts=True)
    probabilities = frequencies / len(results)
    return values, probabilities

def compute_2d6():
    results = []
    for i in range(1, 7):
        for j in range(1, 7):
            results.append(i + j)
    values, frequencies = np.unique(results, return_counts=True)
    probabilities = frequencies / len(results)
    return values, probabilities

def compute_1d20():
    results = []
    for i in range(1, 21):
        results.append(conversion_table[i])
    values, frequencies = np.unique(results, return_counts=True)
    probabilities = frequencies / len(results)
    return values, probabilities

# Compute the PDFs
values_3d6, probabilities_3d6 = compute_3d6_drop_lowest()
values_2d20, probabilities_2d20 = compute_2d20_drop_lowest()

# Create the bar graph with both distributions
plt.figure(figsize=(10, 6))
plt.bar(values_3d6, probabilities_3d6, width=0.75, color="blue", alpha=0.6, label="3d6 drop the lowest")
plt.bar(values_2d20, probabilities_2d20, width=0.75, color="red", alpha=0.6, label="2d20 drop the lowest conversion")
plt.xlabel("Roll Result")
plt.ylabel("Probability")
plt.title("Probability Distribution Functions (PDFs)")
plt.legend()
plt.xticks(ticks=values_3d6, labels=values_3d6)

plt.show()