fst_column = data["FSIQ"].values
snd_column = data["MRI_Count"].values
res_table = []
for i in range(len(fst_column)):
    new_row = []
    new_row.append(fst_column[i])
    new_row.append(snd_column[i])
    res_table.append(new_row)
avg1 = data["FSIQ"].values.mean()
avg2 = data["MRI_Count"].values.mean()
quarter1 = 0
quarter2 = 0
quarter3 = 0
quarter4 = 0
for el in res_table:
    if el[0] > avg1:
        if el[1] > avg2:
            quarter1 += 1
        else:
            quarter2 += 1
    else:
        if el[1] > avg2:
            quarter3 += 1
        else:
            quarter4 += 1
ready_table = []
row = []
row.append(quarter1)
row.append(quarter2)
ready_table.append(row)
row2 = []
row2.append(quarter3)
row2.append(quarter4)
ready_table.append(row2)
chi2, prob, df, expected = chi2_contingency(ready_table)
output = "test Statistics: {}\ndegrees of freedom: {}\np-value: {}\n"

print(output.format( chi2, df, prob))

print(expected)

alpha = 0.05
if prob < 0.05:
    print("Отвергаем нулевую гипотезу, то есть есть зависимость")
else:
    print("Нет оснований отклонить нулевую гипотезу")