Q: # unique companies in entire db
A:
84,472 unique companies (totally there are 563,295 company records)
Q: # unique companies per year
A:
|
year |
company_count |
|
1989 |
16985 |
|
1990 |
20936 |
|
1991 |
23554 |
|
1992 |
24331 |
|
1993 |
26938 |
|
1994 |
31144 |
|
1995 |
34477 |
|
1996 |
35992 |
|
1997 |
38228 |
|
1998 |
41692 |
|
1999 |
43663 |
|
2000 |
51321 |
|
2001 |
60294 |
|
2002 |
56944 |
|
2003 |
56796 |
Q: # unique Primary NAICS
A:
498
Q: # unique Primary NAICS per year
A:
|
year |
uniq_naics_count |
|
1989 |
143 |
|
1990 |
145 |
|
1991 |
144 |
|
1992 |
148 |
|
1993 |
148 |
|
1994 |
147 |
|
1995 |
147 |
|
1996 |
148 |
|
1997 |
148 |
|
1998 |
148 |
|
1999 |
149 |
|
2000 |
149 |
|
2001 |
457 |
|
2002 |
466 |
|
2003 |
480 |
Q: # companies that have more than one unique Primary NAICS (over time)
A:
22,288
Here is the distribution regarding "how many companies have how many
different NAICS over the years":
|
diff_naics_count |
company_count |
|
7 |
1 |
|
6 |
10 |
|
5 |
101 |
|
4 |
673 |
|
3 |
3827 |
|
2 |
17676 |
Q: # unique zip codes in zipdata
or # unique places in zip data set
A:
42,193
Q: How many companies change their
zip code and how often - distribution?
A:
"how often" = diff_zip_count -1
"how many" = company_count
|
diff_zip_count |
company_count |
|
7 |
4 |
|
6 |
25 |
|
5 |
165 |
|
4 |
793 |
|
3 |
4220 |
|
2 |
19759 |
Q: the sales in million per employee = $sales / # employees
A:
|
year |
sum_sales |
sum_employ |
sales per employee |
|
1989 |
2074780 |
14275279 |
0.15 |
|
1990 |
2694950 |
17606668 |
0.15 |
|
1991 |
2875140 |
18071001 |
0.16 |
|
1992 |
2952690 |
17938409 |
0.16 |
|
1993 |
3053900 |
17989674 |
0.17 |
|
1994 |
3426370 |
18792961 |
0.18 |
|
1995 |
3789250 |
20320100 |
0.19 |
|
1996 |
4185210 |
21171157 |
0.2 |
|
1997 |
4516210 |
22736662 |
0.2 |
|
1998 |
5167000 |
24915589 |
0.21 |
|
1999 |
5482400 |
25897635 |
0.21 |
|
2000 |
6343680 |
28776028 |
0.22 |
|
2001 |
8376420 |
39317977 |
0.21 |
|
2002 |
8703030 |
40396389 |
0.22 |
|
2003 |
9015400 |
41274313 |
0.22 |