I am trying to subset rows that occur twice in my df (YearlyDataTMEANPre) dependent on the DATE and UNIQUEID columns. Here is what my df looks like.

```
            ID     DATE TYPE VALUE COL2 NA. NA.1 NA.2 UNIQUEID
6  ASN00015643 20170101 TMAX 81.32             a <NA>      330
7  ASN00015643 20170101 TMIN 71.24             a <NA>      330
9  ASN00085296 20170101 TMAX 71.06             a <NA>      733
10 ASN00085296 20170101 TMIN 54.86             a <NA>      733
13 ASN00085280 20170101 TMIN 60.08             a <NA>      730
15 ASN00040209 20170101 TMAX 84.74             a <NA>      492
16 ASN00040209 20170101 TMIN 77.00             a <NA>      492
40 CA005030984 20170101 TMAX 12.38             C <NA>     1623
41 CA005030984 20170101 TMIN -2.56             C <NA>     1623

```

Note that there is a TMAX and TMIN value on each DATE for each station (ID or UNIQUEID). I am trying to make sure I only get rows where I have both TMAX and TMIN on each date. For example, there may be a day where a station only recorded the TMAX and not the TMIN. I created a numerical UNIQUEID to help with this.

The line of code I tried is,

```
YearlyDataTMEAN <- subset(YearlyDataTMEANPre, UNIQUEID & DATE == 2)

```

however, this seems to get me zero rows. I must be missing something obvious but I am new to R. I would like the output to look like,

```
                ID     DATE TYPE VALUE COL2 NA. NA.1 NA.2 UNIQUEID
6  ASN00015643 20170101 TMAX 81.32             a <NA>      330
7  ASN00015643 20170101 TMIN 71.24             a <NA>      330
9  ASN00085296 20170101 TMAX 71.06             a <NA>      733
10 ASN00085296 20170101 TMIN 54.86             a <NA>      733
15 ASN00040209 20170101 TMAX 84.74             a <NA>      492
16 ASN00040209 20170101 TMIN 77.00             a <NA>      492
40 CA005030984 20170101 TMAX 12.38             C <NA>     1623
41 CA005030984 20170101 TMIN -2.56             C <NA>     1623

```

Note that row 13 in the first table is gone in the output.

Thanks!