Code:
    +----------------------------------------------------------+
     |    A         B           C           D        Q        U |
     |----------------------------------------------------------|
  1. | Name   AB BANK   BANK ASIA   CITY BANK   #ERROR   #ERROR |
     +----------------------------------------------------------+
Q1. How do I delete variables which contain "#ERROR"? In this example, the variables are Q and U. In the actual data set, there are many more. So, I want a general solution.

After deleting the variables, I want to make observation 1 as the variable names using the following code.
Code:
foreach var of varlist * {
    rename `var' `=strtoname(`var'[1])'
}

drop in 1
Q2. After destringing the BANKs and renaming Name as Date, how do I keep only those variables that have values greater than 110 in the last observation? In this example, "AB BANK" and "CITY BANK" have values greater than 110 in the last observation.
Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input str10 A str17(B C D) str38(Q U)
"Name"       "AB BANK"           "BANK ASIA"         "CITY BANK" "#ERROR"                                 "#ERROR"                                
"  1/1/2014" "100"               "100"               "100"       "$$ER: 2380,NO DATA IN REQUESTED PERIOD" "$$ER: 2380,NO DATA IN REQUESTED PERIOD"
"  1/2/2014" "99.23"             "97.73"             "100"       ""                                       ""                                      
"  1/3/2014" "99.23"             "97.73"             "100"       ""                                       ""                                      
"  1/6/2014" "98.84999999999999" "91.36"             "97.47"     ""                                       ""                                      
"  1/7/2014" "98.08"             "94.09"             "96.97"     ""                                       ""                                      
"  1/8/2014" "99.62000000000001" "93.64"             "100.51"    ""                                       ""                                      
"  1/9/2014" "99.23"             "93.64"             "100.51"    ""                                       ""                                      
" 1/10/2014" "99.23"             "90.91"             "99.49"     ""                                       ""                                      
" 1/13/2014" "101.53"            "93.64"             "105.05"    ""                                       ""                                      
" 1/14/2014" "101.53"            "93.64"             "105.05"    ""                                       ""                                      
" 1/15/2014" "102.68"            "95.45"             "105.56"    ""                                       ""                                      
" 1/16/2014" "105.75"            "96.81999999999999" "105.05"    ""                                       ""                                      
" 1/17/2014" "106.9"             "102.27"            "106.57"    ""                                       ""                                      
" 1/20/2014" "104.98"            "98.64"             "102.53"    ""                                       ""                                      
" 1/21/2014" "104.98"            "97.27"             "101.01"    ""                                       ""                                      
" 1/22/2014" "106.51"            "96.81999999999999" "102.02"    ""                                       ""                                      
" 1/23/2014" "110.73"            "99.09"             "102.02"    ""                                       ""                                      
" 1/24/2014" "116.48"            "100.45"            "107.58"    ""                                       ""                                      
" 1/27/2014" "116.48"            "102.73"            "110.1"     ""                                       ""                                      
end