a0th

powers_10 = [3, 5]


def generate_variance_instance(instances):
    return (
        generate_sales(
            days=60,
            sale_probability_first_half=0.2,
            sale_probability_second_half=0.2,
            visitors_per_day=instances,

a0th

np.random.seed(0)
conversion_rate_second_example = generate_sales(
    days=60, sale_probability_first_half=0.20, sale_probability_second_half=0.22
).loc["1990-01-01":"1990-02-28"]

conversion_rate_first_half = conversion_rate_second_example.conversion_rate.loc[
    "1990-01"
].mean()
conversion_rate_second_half = conversion_rate_second_example.conversion_rate.loc[
    "1990-02"

a0th

from scipy.stats import chi2_contingency


first_week, second_week = (
    conversion_rates.sales.loc["1990-01"],
    conversion_rates.sales.loc["1990-02"],
)
first_week_visitors, first_week_buyers = first_week.size, first_week.sum()
second_week_visitors, second_week_buyers = second_week.size, second_week.sum()

a0th

import numpy as np
import pandas as pd
import plotly.io as pio
import plotly.express as px
pio.templates.default = "plotly_dark"
pio.renderers.default='svg'

np.random.seed(0)