depress data frame:
   obs age educ income score isdep
1  181  58    3     15     1     0
2  182  59    3     13    33     1
3  183  26    3      9     8     0
4  184  21    3     19     5     0
5  185  83    2      6     7     0
6  186  34    2      7    16     1
7  187  42    3     23     5     0
8  188  42    3      7    16     1
9  189  24    3     13    39     1
10 190  80    2      5     9     0
11 191  18    2     15     8     0
12 192  58    2      9     3     0
13 193  54    3      2     2     0
14 194  47    4     45     1     0
15 195  61    2      4     3     0
16 196  18    2     24     5     0
17 197  51    5     45     4     0
18 198  28    2      9     0     0
19 199  44    3     26     0     0
20 200  50    3     23     8     0

Call:
glm(formula = isdep ~ obs + age + educ + income + score, family = binomial(link = "logit"), 
    data = depress)

Deviance Residuals: 
       Min          1Q      Median          3Q         Max  
-1.094e-05  -2.110e-08  -2.110e-08  -2.110e-08   1.101e-05  

Coefficients:
              Estimate Std. Error z value Pr(>|z|)
(Intercept) -5.457e+01  6.960e+06       0        1
obs         -1.221e-01  4.016e+04       0        1
age         -6.897e-02  6.447e+03       0        1
educ         1.239e+00  1.000e+05       0        1
income       2.019e-01  3.977e+04       0        1
score        6.203e+00  1.696e+04       0        1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 2.0016e+01  on 19  degrees of freedom
Residual deviance: 5.2158e-10  on 14  degrees of freedom
AIC: 12

Number of Fisher Scoring iterations: 25

Predicted Values:
           1            2            3            4            5            6 
2.220446e-16 1.000000e+00 5.981846e-11 2.220446e-16 2.220446e-16 1.000000e+00 
           7            8            9           10           11           12 
2.220446e-16 1.000000e+00 1.000000e+00 3.922785e-11 3.804939e-11 2.220446e-16 
          13           14           15           16           17           18 
2.220446e-16 2.220446e-16 2.220446e-16 2.220446e-16 2.220446e-16 2.220446e-16 
          19           20 
2.220446e-16 2.422228e-11 
Residuals:
            1             2             3             4             5 
-2.107342e-08  2.107342e-08 -1.093786e-05 -2.107342e-08 -2.107342e-08 
            6             7             8             9            10 
 1.100674e-05 -2.107342e-08  8.819574e-06  2.107342e-08 -8.857534e-06 
           11            12            13            14            15 
-8.723456e-06 -2.107342e-08 -2.107342e-08 -2.107342e-08 -2.107342e-08 
           16            17            18            19            20 
-2.107342e-08 -2.107342e-08 -2.107342e-08 -2.107342e-08 -6.960198e-06 
Warning message:
glm.fit: fitted probabilities numerically 0 or 1 occurred