I have a huge dataframe (>1,000,000 rows) like this.

```
term    estimate    st.error    statistic    p.value    SNP
(Intercept)    7.68    0.17    44.64    0    rs1406947
GT    0.01    0.01    0.07    0.19    rs1406947     
SEX    1.52    0.14    10.87    0.1    rs1406947 
M    0.12    0.29    0.41    0.67    rs1406947   
N    -0.06    0.12    -0.48    0.63    rs1406947
GT:SEX    -0.03    0.08    -0.44    0.65    rs1406947
GT:N    -0.00    0.06    -0.08    0.93    rs1406947   
(Intercept)    9.23    0.20    34.64    0    rs25904
GT    0.05    0.04    0.12    0.22    rs25904    
SEX    1.67    0.76    10.34    0.1    rs25904 
M    0.14    0.39    0.51    0.55    rs25904   
N    -0.08    0.05    -0.46    0.55    rs25904
GT:SEX    -0.19    0.11    -0.34    0.44    rs25904
GT:N    -0.22    0.33    -0.44    0.55    rs25904           
(Intercept)    7.99    0.66    44.44    0    rs7133579
GT    0.01    0.3    0.04    0.33    rs7133579    
SEX    1.22    0.22    10.44    0.15    rs7133579 
M    0.88    0.22    0.33    0.44    rs7133579   
N    -0.5    0.5    -0.5    0.6    rs7133579
GT:N    -0.00    0.03    -0.04    0.78    rs7133579 

```

It is composed by blocks of 7 observations: (Intercept), GT, SEX, M, N, GT:SEX and GT:N. However, a few blocks lack one or more of the observations (e.g. the third block lacks GT:SEX). Using R, I want to remove these blocks. In this toy example I would get:

```
term    estimate    st.error    statistic    p.value    SNP
(Intercept)    7.68    0.17    44.64    0    rs1406947
GT    0.01    0.01    0.07    0.19    rs1406947     
SEX    1.52    0.14    10.87    0.1    rs1406947 
M    0.12    0.29    0.41    0.67    rs1406947   
N    -0.06    0.12    -0.48    0.63    rs1406947
GT:SEX    -0.03    0.08    -0.44    0.65    rs1406947
GT:N    -0.00    0.06    -0.08    0.93    rs1406947   
(Intercept)    9.23    0.20    34.64    0    rs25904
GT    0.05    0.04    0.12    0.22    rs25904    
SEX    1.67    0.76    10.34    0.1    rs25904 
M    0.14    0.39    0.51    0.55    rs25904   
N    -0.08    0.05    -0.46    0.55    rs25904
GT:SEX    -0.19    0.11    -0.34    0.44    rs25904
GT:N    -0.22    0.33    -0.44    0.55    rs25904           

```