cell_categories = to_categorical(dataset['cell'])
dataset = dataset.join(pd.DataFrame(cell_categories))
dataset = dataset.drop(columns=['cell'])
print(pd.DataFrame(cell_categories).describe())
print(dataset.describe())

                 0            1            2            3            4            5            6            7            8
count  4572.000000  4572.000000  4572.000000  4572.000000  4572.000000  4572.000000  4572.000000  4572.000000  4572.000000
mean      0.111111     0.111111     0.111111     0.111111     0.111111     0.111111     0.111111     0.111111     0.111111
std       0.314304     0.314304     0.314304     0.314304     0.314304     0.314304     0.314304     0.314304     0.314304
min       0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
25%       0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
50%       0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
75%       0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000     0.000000
max       1.000000     1.000000     1.000000     1.000000     1.000000     1.000000     1.000000     1.000000     1.000000
            Rownum    avg_users            x       0       1       2       3       4       5       6       7       8
count  4572.000000  4572.000000  4572.000000  4572.0  4572.0  4572.0  4572.0  4572.0  4572.0  4572.0  4572.0  4572.0
mean    254.500000     4.771667    18.956255     0.0     0.0     0.0     0.0     0.0     0.0     1.0     0.0     0.0
std     146.662724     6.912038     5.553094     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0
min       1.000000     0.000000    10.000000     0.0     0.0     0.0     0.0     0.0     0.0     1.0     0.0     0.0
25%     127.750000     0.107500    20.000000     0.0     0.0     0.0     0.0     0.0     0.0     1.0     0.0     0.0
50%     254.500000     2.245000    20.000000     0.0     0.0     0.0     0.0     0.0     0.0     1.0     0.0     0.0
75%     381.250000     6.030000    20.000000     0.0     0.0     0.0     0.0     0.0     0.0     1.0     0.0     0.0
max     508.000000    43.390000    62.000000     0.0     0.0     0.0     0.0     0.0     0.0     1.0     0.0     0.0