假设/理解：

• 某些输入字段可能会用双引号括起来;这些双引号 * 不 * 被删除（不像OP所需的输出）
• 由于逗号同时显示为分隔符和数据，我们将临时将数据示例转换为另一个在数据中不显示的字符;在本练习中，我们将使用竖线字符（|），否则我们将需要选择另一个替换字符
• 所有name字段都由两个空格分隔的字符串组成（即，不必担心Bob B Burns III或Lastname, Firstname之类的名称）
• name字段中的两个空格分隔字符串都只需要将首字母大写（例如，我们不必担心名称混合大小写，如dePalma或McDonald）
• 如果我们以重复的电子邮件帐户结束，则location_id保证是唯一的
• 输入文件可以放入内存（如awk数组）

一旦awk被拉入混合，就很少需要sed或额外的awk脚本，也就是说，我们应该能够使用单个awk脚本执行整个操作。
一个awk创意：

awk '
BEGIN { FS="\""; OFS="," }                              # input is delimited by double qutoes
NR==1 { print; next }
      { line=""
        for (i=1;i<NF;i+=2) {                           # loop through odd numbered fields
            gsub(/,/,"|",$(i+1))                        # in even numbered double-quote-delimited fields replace commas with pipes
            line=line $i FS $(i+1) FS                   # rebuild the current line
        }
        line=line $NF                                   # add last field to new line

        split(line,a,",")                               # split new line on commas
        split(tolower(a[3]),b,/[[:space:]]+/)           # split tolower(name field) on white space

        # rebuild name with first characters of first/last names uppercased

        name=toupper(substr(b[1],1,1)) substr(b[1],2) " " toupper(substr(b[2],1,1)) substr(b[2],2)

        acct=substr(b[1],1,1) b[2]                      # build email acct name

        lines[NR]=a[1] OFS a[2] OFS name OFS a[4]       # rebuild current line based on first 4 fields
        locid[NR]=a[2]                                  # make note of location_id for current line
        email[NR]=acct                                  # make note of email acct for current line
        count[acct]++                                   # keep count of number of times we see this email acct
      }

END   { for (i=2;i<=NR;i++) {                           # loop through our lines of output
            gsub(/\|/,",",lines[i])                     # replace pipes with original commas

            # print final line of output; if email acct has been seen more than once then append the location_id to the email acct; add the "@abc.com" domain and the trailing comma

            print lines[i] OFS email[i] (count[email[i]] > 1 ? locid[i] : "") "@abc.com" OFS
        }
      }
' accounts.csv

这将产生：

id,location_id,name,title,email,department
1,1,Susan Houston,Director of Services,shouston@abc.com,
2,1,Christina Gonzalez,Director,cgonzalez@abc.com,
3,2,Brenda Brown,"Director, Second Career Services",bbrown@abc.com,
4,3,Howard Lader,"Manager, Senior Counseling",hlader@abc.com,
5,4,Kimberly Pesavento,Commercial director,kpesavento@abc.com,
6,5,Joe Bloom,Financial Empowerment Programs Program Director,jbloom@abc.com,
7,6,Peter Olson,Director,polson@abc.com,
8,6,Bart Charlow,Executive Director,bcharlow6@abc.com,
9,7,Bart Charlow,Executive Director,bcharlow7@abc.com,

使用任何awk的2遍方法：

$ cat tst.awk
BEGIN { FS=OFS="," }
NR == 1 { print }
FNR == 1 { next }
{ lc_name = tolower($3) }
NR == FNR {
    cnt[lc_name]++
    next
}
{
    n = split(lc_name,parts," ")
    for ( i=1; i<=n; i++ ) {
        name = ( i>1 ? name " " : "" ) toupper(substr(parts[i],1,1)) substr(parts[i],2)
        email = ( i>1 ? email parts[i] : substr(parts[i],1,1) )
    }

    $3 = name
    $(NF-1) = email ( cnt[lc_name] > 1 ? $2 : "" ) "@example.com"
    print
}

$ awk -f tst.awk accounts.csv accounts.csv
id,location_id,name,title,email,department
1,1,Susan Houston,Director of Services,shouston@example.com,
2,1,Christina Gonzalez,Director,cgonzalez@example.com,
3,2,Brenda Brown,"Director, Second Career Services",bbrown@example.com,
4,3,Howard Lader,"Manager, Senior Counseling",hlader@example.com,
5,4,Kimberly Pesavento,Commercial director,kpesavento@example.com,
6,5,Joe Bloom,Financial Empowerment Programs Program Director,jbloom@example.com,
7,6,Peter Olson,Director,polson@example.com,
8,6,Bart Charlow,Executive Director,bcharlow6@example.com,
9,7,Bart Charlow,Executive Director,bcharlow7@example.com,

在上面的例子中，我假设一个包含两个以上部分的名字，比如Billy Jean King，应该会得到一个类似bjeanking@example.com的电子邮件地址，如果你想要其他的，这是一个很小的调整。
我也没有删除字段中的引号，因为这会破坏数据，但如果您真的想要这样做，那么，再一次，这是一个微不足道的调整。