df.txt

y a	b	c	d	e
0	6	62.1	no	male	A
1	18	74.7	yes	female	B
1	16	69.7	no	female	A
0	14	71	no	male	C
1	5	56.9	no	male	B
0	11	58.7	no	female	B
0	8	63.3	no	male	B
1	11	70.4	no	male	A
1	15	70.5	no	male	C
0	11	59.2	no	male	B
0	19	76.4	yes	male	A
0	17	71.7	no	male	B
1	12	57.5	yes	male	C
1	10	61.1	no	female	B

script.R

> data = read.table('df.txt', header=T)
> model = glm(y ~ c:d, data=data, family='binomial')
> summary(model)

Call:
glm(formula = y ~ c:d, family = "binomial", data = data)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.4823  -0.9695  -0.4847   1.1082   1.4006  

Coefficients: (1 not defined because of singularities)
               Estimate Std. Error z value Pr(>|z|)
(Intercept)  -9.549e-17  1.414e+00   0.000    1.000
cno:dfemale   6.931e-01  1.871e+00   0.371    0.711
cyes:dfemale  1.757e+01  3.956e+03   0.004    0.996
cno:dmale    -5.108e-01  1.592e+00  -0.321    0.748
cyes:dmale           NA         NA      NA       NA

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 19.408  on 13  degrees of freedom
Residual deviance: 17.177  on 10  degrees of freedom
AIC: 25.177

Number of Fisher Scoring iterations: 16