Use np.isclose, which allows you to precisely control the absolute and relative tolerance of the comparison.

I assume that you only want to compare rows with labels that exist in both dataframes. Rows that exist in one but not the other are ignored. Also, since you use a relative criterion for A, C, G, T, compare(df0,df1) is not the same as compare(df1,df0). It assumes the second parameter is the reference value. This is consistent with how np.isclose works.

def compare(dfa, dfb):
    s = pd.Series(['A','C','G','T'])
    tmp = dfa.join(dfb, how='inner', lsuffix='_a', rsuffix='_b')

    # The A, C, G, T columns: within 90% of dfb
    lhs = tmp[s + '_a'].values
    rhs = tmp[s + '_b'].values
    compare1 = np.isclose(lhs, rhs, atol=0, rtol=0.9)

    # The uA, uC, uG, uT columns: within 1e-5
    lhs = tmp['u' + s + '_a'].values
    rhs = tmp['u' + s + '_b'].values
    compare2 = np.isclose(lhs, rhs, atol=1e-5, rtol=0)

    # The cmA, cmC, cmG, cmT columns: within 1e-3
    lhs = tmp['cm' + s + '_a'].values
    rhs = tmp['cm' + s + '_b'].values
    compare3 = np.isclose(lhs, rhs, atol=1e-3, rtol=0)

    # Assemble the result
    data = np.concatenate([compare1, compare2, compare3], axis=1)
    cols = pd.concat([s, 'u'+s, 'cm'+s])    
    result = pd.DataFrame(data, columns=cols, index=tmp.index)

    return result

compare(df0, df2)

For an easy visualization of the result:

def highlight_false(cell):
    return '' if cell else 'background-color: yellow'

result = compare(df0,df2)
result.style.applymap(highlight_false)

Due to imprecise float comparison you can or your comparison with np.isclose, isclose takes a relative and absolute tolerance param so the following should work:

Copydf['result'] = df['actual_credit'].ge(df['min_required_credit']) | np.isclose(df['actual_credit'], df['min_required_credit'])

OK you can use np.isclose for this:

In [250]:
np.isclose(a,b)

Out[250]:
array([[ True],
       [ True]], dtype=bool)

np.isclose takes relative tolerance and absolute tolerance. These have default values: rtol=1e-05, atol=1e-08 respectively