Iterate and modify series in pandas, warning still exists after using loc

Question

Code:

import pandas as pd


def map_val(df, rules):
    for column_name in rules.keys():
        column = df[column_name]
        rule_for_this_column = rules.get(column_name)
        column[:] = [rule_for_this_column(value) for value in column]


def a_rule(value):
    digit = float(value)
    if digit > 1:
        return 1
    else:
        return 0


def b_rule(value):
    if value > 8:
        return 1
    else:
        return 0


table = {
    'a': ['1', '2', '3', '4', '5'],
    'b': [6, 7, 8, 9, 10],
    'c': [11, 12, 13, 14, 15],
}

df = pd.DataFrame(table)
print(df)
rules = {
    'a': a_rule,
    'b': b_rule
}
map_val(df, rules)
print(df)

Output:

   a   b   c
0  1   6  11
1  2   7  12
2  3   8  13
3  4   9  14
4  5  10  15
my/source/path/test.py:8: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  column[:] = [rule_for_this_column(value) for value in column]
   a  b   c
0  0  0  11
1  1  0  12
2  1  0  13
3  1  1  14
4  1  1  15

I want to modify each series that has label of keys in dictionary rules, by applying corresponding mapper function(the value of rules) to every single value in that series. I've read the link provided in warning message and changed my code as below:

# column[:] = [rule_for_this_column(value) for value in column]
for idx, value in column.items():
    column.loc[idx] = rule_for_this_column(value)

While the warning still exists.