Overview

Dataset statistics

Number of variables5
Number of observations991
Missing cells114
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.8 KiB
Average record size in memory41.1 B

Variable types

Numeric1
Text4

Dataset

Description대구광역시 서구의 공장등록 현황입니다. 서구 내 공장의 회사명, 공장주소, 전화번호, 생산품 등 데이터를 포함하고 있습니다.
Author대구광역시 서구
URLhttps://www.data.go.kr/data/15092730/fileData.do

Alerts

전화번호 has 111 (11.2%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:46:14.386156
Analysis finished2023-12-12 05:46:15.536614
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct991
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean496
Minimum1
Maximum991
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.8 KiB
2023-12-12T14:46:15.638464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.5
Q1248.5
median496
Q3743.5
95-th percentile941.5
Maximum991
Range990
Interquartile range (IQR)495

Descriptive statistics

Standard deviation286.22136
Coefficient of variation (CV)0.57705919
Kurtosis-1.2
Mean496
Median Absolute Deviation (MAD)248
Skewness0
Sum491536
Variance81922.667
MonotonicityStrictly increasing
2023-12-12T14:46:15.811241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
667 1
 
0.1%
654 1
 
0.1%
655 1
 
0.1%
656 1
 
0.1%
657 1
 
0.1%
658 1
 
0.1%
659 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
Other values (981) 981
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
991 1
0.1%
990 1
0.1%
989 1
0.1%
988 1
0.1%
987 1
0.1%
986 1
0.1%
985 1
0.1%
984 1
0.1%
983 1
0.1%
982 1
0.1%

회사명
Text

Distinct972
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-12-12T14:46:16.372391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length6.4298688
Min length2

Characters and Unicode

Total characters6372
Distinct characters420
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique954 ?
Unique (%)96.3%

Sample

1st row(유)대안에이엔씨
2nd row(자)구진기업
3rd row(주) 이 주
4th row(주) 제이드 청포도
5th row(주)가베
ValueCountFrequency (%)
주식회사 64
 
5.7%
제2공장 9
 
0.8%
서연유니폼 4
 
0.4%
주 3
 
0.3%
비산공장 3
 
0.3%
대구공장 3
 
0.3%
대구지점 3
 
0.3%
주)보광아이엔티 3
 
0.3%
주)희성다이텍 2
 
0.2%
주)미앤부티 2
 
0.2%
Other values (995) 1027
91.5%
2023-12-12T14:46:16.822629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 430
 
6.7%
( 373
 
5.9%
) 373
 
5.9%
이 159
 
2.5%
사 144
 
2.3%
134
 
2.1%
업 131
 
2.1%
스 130
 
2.0%
대 119
 
1.9%
산 105
 
1.6%
Other values (410) 4274
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5269
82.7%
Open Punctuation 373
 
5.9%
Close Punctuation 373
 
5.9%
Uppercase Letter 135
 
2.1%
Space Separator 134
 
2.1%
Decimal Number 42
 
0.7%
Lowercase Letter 25
 
0.4%
Other Punctuation 20
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 430
 
8.2%
이 159
 
3.0%
사 144
 
2.7%
업 131
 
2.5%
스 130
 
2.5%
대 119
 
2.3%
산 105
 
2.0%
성 103
 
2.0%
유 100
 
1.9%
공 86
 
1.6%
Other values (360) 3762
71.4%
Uppercase Letter
ValueCountFrequency (%)
D 14
 
10.4%
T 13
 
9.6%
C 12
 
8.9%
I 12
 
8.9%
E 12
 
8.9%
S 9
 
6.7%
N 6
 
4.4%
O 6
 
4.4%
P 6
 
4.4%
F 5
 
3.7%
Other values (13) 40
29.6%
Lowercase Letter
ValueCountFrequency (%)
e 6
24.0%
i 3
12.0%
h 3
12.0%
n 2
 
8.0%
o 2
 
8.0%
l 2
 
8.0%
c 2
 
8.0%
x 1
 
4.0%
t 1
 
4.0%
a 1
 
4.0%
Other values (2) 2
 
8.0%
Decimal Number
ValueCountFrequency (%)
2 15
35.7%
1 9
21.4%
5 6
 
14.3%
3 3
 
7.1%
4 2
 
4.8%
0 2
 
4.8%
9 2
 
4.8%
6 2
 
4.8%
8 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 13
65.0%
& 7
35.0%
Open Punctuation
ValueCountFrequency (%)
( 373
100.0%
Close Punctuation
ValueCountFrequency (%)
) 373
100.0%
Space Separator
ValueCountFrequency (%)
134
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5269
82.7%
Common 943
 
14.8%
Latin 160
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 430
 
8.2%
이 159
 
3.0%
사 144
 
2.7%
업 131
 
2.5%
스 130
 
2.5%
대 119
 
2.3%
산 105
 
2.0%
성 103
 
2.0%
유 100
 
1.9%
공 86
 
1.6%
Other values (360) 3762
71.4%
Latin
ValueCountFrequency (%)
D 14
 
8.8%
T 13
 
8.1%
C 12
 
7.5%
I 12
 
7.5%
E 12
 
7.5%
S 9
 
5.6%
N 6
 
3.8%
O 6
 
3.8%
P 6
 
3.8%
e 6
 
3.8%
Other values (25) 64
40.0%
Common
ValueCountFrequency (%)
( 373
39.6%
) 373
39.6%
134
 
14.2%
2 15
 
1.6%
. 13
 
1.4%
1 9
 
1.0%
& 7
 
0.7%
5 6
 
0.6%
3 3
 
0.3%
4 2
 
0.2%
Other values (5) 8
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5269
82.7%
ASCII 1103
 
17.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 430
 
8.2%
이 159
 
3.0%
사 144
 
2.7%
업 131
 
2.5%
스 130
 
2.5%
대 119
 
2.3%
산 105
 
2.0%
성 103
 
2.0%
유 100
 
1.9%
공 86
 
1.6%
Other values (360) 3762
71.4%
ASCII
ValueCountFrequency (%)
( 373
33.8%
) 373
33.8%
134
 
12.1%
2 15
 
1.4%
D 14
 
1.3%
T 13
 
1.2%
. 13
 
1.2%
C 12
 
1.1%
I 12
 
1.1%
E 12
 
1.1%
Other values (40) 132
 
12.0%

공장주소
Text

Distinct913
Distinct (%)92.4%
Missing3
Missing (%)0.3%
Memory size7.9 KiB
2023-12-12T14:46:17.185778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length40
Mean length27.283401
Min length19

Characters and Unicode

Total characters26956
Distinct characters255
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique847 ?
Unique (%)85.7%

Sample

1st row대구광역시 서구 염색공단로21길 8, (유)대안에이엔씨 (비산동)
2nd row대구광역시 서구 와룡로87길 8-1 (이현동, 구진기업)
3rd row대구광역시 서구 염색공단중앙로21길 33 (비산동, 이주염공)
4th row대구광역시 서구 서대구로 351(비산동)
5th row대구광역시 서구 장산로 224 (중리동)
ValueCountFrequency (%)
대구광역시 988
18.7%
서구 988
18.7%
이현동 326
 
6.2%
중리동 265
 
5.0%
비산동 231
 
4.4%
와룡로 61
 
1.2%
평리동 45
 
0.9%
와룡로72길 32
 
0.6%
와룡로66길 29
 
0.5%
문화로 28
 
0.5%
Other values (849) 2294
43.4%
2023-12-12T14:46:17.715733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4303
 
16.0%
구 2009
 
7.5%
대 1066
 
4.0%
서 1066
 
4.0%
( 1044
 
3.9%
) 1044
 
3.9%
동 1039
 
3.9%
광 1000
 
3.7%
역 991
 
3.7%
시 990
 
3.7%
Other values (245) 12404
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16074
59.6%
Space Separator 4303
 
16.0%
Decimal Number 3854
 
14.3%
Open Punctuation 1044
 
3.9%
Close Punctuation 1044
 
3.9%
Other Punctuation 372
 
1.4%
Dash Punctuation 239
 
0.9%
Uppercase Letter 26
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2009
 
12.5%
대 1066
 
6.6%
서 1066
 
6.6%
동 1039
 
6.5%
광 1000
 
6.2%
역 991
 
6.2%
시 990
 
6.2%
로 978
 
6.1%
길 715
 
4.4%
리 442
 
2.7%
Other values (213) 5778
35.9%
Uppercase Letter
ValueCountFrequency (%)
A 4
15.4%
D 3
11.5%
S 3
11.5%
P 2
 
7.7%
C 2
 
7.7%
O 2
 
7.7%
N 2
 
7.7%
E 1
 
3.8%
W 1
 
3.8%
F 1
 
3.8%
Other values (5) 5
19.2%
Decimal Number
ValueCountFrequency (%)
1 774
20.1%
2 581
15.1%
3 493
12.8%
7 355
9.2%
6 343
8.9%
4 277
 
7.2%
0 274
 
7.1%
5 266
 
6.9%
9 259
 
6.7%
8 232
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 366
98.4%
. 3
 
0.8%
& 3
 
0.8%
Space Separator
ValueCountFrequency (%)
4303
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1044
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1044
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 239
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16074
59.6%
Common 10856
40.3%
Latin 26
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2009
 
12.5%
대 1066
 
6.6%
서 1066
 
6.6%
동 1039
 
6.5%
광 1000
 
6.2%
역 991
 
6.2%
시 990
 
6.2%
로 978
 
6.1%
길 715
 
4.4%
리 442
 
2.7%
Other values (213) 5778
35.9%
Common
ValueCountFrequency (%)
4303
39.6%
( 1044
 
9.6%
) 1044
 
9.6%
1 774
 
7.1%
2 581
 
5.4%
3 493
 
4.5%
, 366
 
3.4%
7 355
 
3.3%
6 343
 
3.2%
4 277
 
2.6%
Other values (7) 1276
 
11.8%
Latin
ValueCountFrequency (%)
A 4
15.4%
D 3
11.5%
S 3
11.5%
P 2
 
7.7%
C 2
 
7.7%
O 2
 
7.7%
N 2
 
7.7%
E 1
 
3.8%
W 1
 
3.8%
F 1
 
3.8%
Other values (5) 5
19.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16074
59.6%
ASCII 10882
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4303
39.5%
( 1044
 
9.6%
) 1044
 
9.6%
1 774
 
7.1%
2 581
 
5.3%
3 493
 
4.5%
, 366
 
3.4%
7 355
 
3.3%
6 343
 
3.2%
4 277
 
2.5%
Other values (22) 1302
 
12.0%
Hangul
ValueCountFrequency (%)
구 2009
 
12.5%
대 1066
 
6.6%
서 1066
 
6.6%
동 1039
 
6.5%
광 1000
 
6.2%
역 991
 
6.2%
시 990
 
6.2%
로 978
 
6.1%
길 715
 
4.4%
리 442
 
2.7%
Other values (213) 5778
35.9%

전화번호
Text

MISSING 

Distinct832
Distinct (%)94.5%
Missing111
Missing (%)11.2%
Memory size7.9 KiB
2023-12-12T14:46:17.968736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.993182
Min length9

Characters and Unicode

Total characters10554
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique786 ?
Unique (%)89.3%

Sample

1st row053-524-3984
2nd row053-357-5210
3rd row053-357-0987
4th row053-358-6638
5th row053-351-5240
ValueCountFrequency (%)
053-566-1200 3
 
0.3%
053-551-9901 3
 
0.3%
053-563-1320 2
 
0.2%
053-571-4711 2
 
0.2%
053-585-9393 2
 
0.2%
053-561-8197 2
 
0.2%
053-557-3008 2
 
0.2%
053-358-7521 2
 
0.2%
053-761-5363 2
 
0.2%
053-295-1065 2
 
0.2%
Other values (822) 858
97.5%
2023-12-12T14:46:18.354165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2294
21.7%
- 1757
16.6%
3 1586
15.0%
0 1375
13.0%
2 658
 
6.2%
6 637
 
6.0%
1 612
 
5.8%
7 458
 
4.3%
4 427
 
4.0%
8 403
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8797
83.4%
Dash Punctuation 1757
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2294
26.1%
3 1586
18.0%
0 1375
15.6%
2 658
 
7.5%
6 637
 
7.2%
1 612
 
7.0%
7 458
 
5.2%
4 427
 
4.9%
8 403
 
4.6%
9 347
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 1757
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10554
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2294
21.7%
- 1757
16.6%
3 1586
15.0%
0 1375
13.0%
2 658
 
6.2%
6 637
 
6.0%
1 612
 
5.8%
7 458
 
4.3%
4 427
 
4.0%
8 403
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10554
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2294
21.7%
- 1757
16.6%
3 1586
15.0%
0 1375
13.0%
2 658
 
6.2%
6 637
 
6.0%
1 612
 
5.8%
7 458
 
4.3%
4 427
 
4.0%
8 403
 
3.8%

업종명
Text

Distinct362
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-12-12T14:46:18.702403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length16.340061
Min length3

Characters and Unicode

Total characters16193
Distinct characters274
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique223 ?
Unique (%)22.5%

Sample

1st row날염 가공업
2nd row도금업
3rd row직물, 편조원단 및 의복류 염색 가공업
4th row근무복, 작업복 및 유사의복 제조업 외 13종
5th row제책업 외 3종
ValueCountFrequency (%)
제조업 622
 
12.4%
및 596
 
11.9%
외 419
 
8.3%
가공업 198
 
3.9%
기타 195
 
3.9%
1종 176
 
3.5%
직물 156
 
3.1%
편조원단 135
 
2.7%
염색 134
 
2.7%
의복류 130
 
2.6%
Other values (404) 2267
45.1%
2023-12-12T14:46:19.189770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4037
24.9%
업 1045
 
6.5%
제 891
 
5.5%
조 837
 
5.2%
및 596
 
3.7%
외 426
 
2.6%
기 391
 
2.4%
종 337
 
2.1%
가 320
 
2.0%
공 312
 
1.9%
Other values (264) 7001
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11566
71.4%
Space Separator 4037
 
24.9%
Decimal Number 350
 
2.2%
Other Punctuation 228
 
1.4%
Close Punctuation 6
 
< 0.1%
Open Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1045
 
9.0%
제 891
 
7.7%
조 837
 
7.2%
및 596
 
5.2%
외 426
 
3.7%
기 391
 
3.4%
종 337
 
2.9%
가 320
 
2.8%
공 312
 
2.7%
품 283
 
2.4%
Other values (249) 6128
53.0%
Decimal Number
ValueCountFrequency (%)
1 199
56.9%
2 68
 
19.4%
3 42
 
12.0%
4 12
 
3.4%
6 9
 
2.6%
5 8
 
2.3%
7 5
 
1.4%
0 4
 
1.1%
8 2
 
0.6%
9 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 226
99.1%
. 2
 
0.9%
Space Separator
ValueCountFrequency (%)
4037
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11566
71.4%
Common 4627
28.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1045
 
9.0%
제 891
 
7.7%
조 837
 
7.2%
및 596
 
5.2%
외 426
 
3.7%
기 391
 
3.4%
종 337
 
2.9%
가 320
 
2.8%
공 312
 
2.7%
품 283
 
2.4%
Other values (249) 6128
53.0%
Common
ValueCountFrequency (%)
4037
87.2%
, 226
 
4.9%
1 199
 
4.3%
2 68
 
1.5%
3 42
 
0.9%
4 12
 
0.3%
6 9
 
0.2%
5 8
 
0.2%
) 6
 
0.1%
( 6
 
0.1%
Other values (5) 14
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11559
71.4%
ASCII 4627
28.6%
Compat Jamo 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4037
87.2%
, 226
 
4.9%
1 199
 
4.3%
2 68
 
1.5%
3 42
 
0.9%
4 12
 
0.3%
6 9
 
0.2%
5 8
 
0.2%
) 6
 
0.1%
( 6
 
0.1%
Other values (5) 14
 
0.3%
Hangul
ValueCountFrequency (%)
업 1045
 
9.0%
제 891
 
7.7%
조 837
 
7.2%
및 596
 
5.2%
외 426
 
3.7%
기 391
 
3.4%
종 337
 
2.9%
가 320
 
2.8%
공 312
 
2.7%
품 283
 
2.4%
Other values (248) 6121
53.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 7
100.0%

Interactions

2023-12-12T14:46:15.031151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T14:46:15.214927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:46:15.370575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T14:46:15.478107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순번회사명공장주소전화번호업종명
01(유)대안에이엔씨대구광역시 서구 염색공단로21길 8, (유)대안에이엔씨 (비산동)<NA>날염 가공업
12(자)구진기업대구광역시 서구 와룡로87길 8-1 (이현동, 구진기업)053-524-3984도금업
23(주) 이 주대구광역시 서구 염색공단중앙로21길 33 (비산동, 이주염공)053-357-5210직물, 편조원단 및 의복류 염색 가공업
34(주) 제이드 청포도대구광역시 서구 서대구로 351(비산동)053-357-0987근무복, 작업복 및 유사의복 제조업 외 13종
45(주)가베대구광역시 서구 장산로 224 (중리동)<NA>제책업 외 3종
56(주)가베 제2공장대구광역시 서구 와룡로73길 33 (중리동)<NA>제책업 외 4종
67(주)가온텍대구광역시 서구 문화로3길 8 (이현동)053-358-6638그 외 자동차용 신품 부품 제조업 외 3종
78(주)거목텍스대구광역시 서구 염색공단천로23길 29 (비산동)053-351-5240직물, 편조원단 및 의복류 염색 가공업
89(주)건강나눔대구광역시 서구 와룡로 307, 7층 723호(중리동)053-257-9599그 외 기타 일반목적용 기계 제조업 외 2종
910(주)경동세라텍대구광역시 서구 국채보상로14길 32 (중리동)053-557-6100위생용 및 산업용 도자기 제조업
순번회사명공장주소전화번호업종명
981982화남공업대구광역시 서구 와룡로97길 5 (이현동)053-559-2900기타 섬유, 의복 및 가죽 가공 기계 제조업
982983화성금속대구광역시 서구 와룡로70길 31 (중리동, 화성금속)053-561-4948그 외 자동차용 신품 부품 제조업 외 3종
983984화성금속대구광역시 서구 와룡로99길 21 (이현동)053-571-1162도금업
984985화성밸브(주)대구광역시 서구 팔달로2길 29 (비산동, 화성)053-353-5789탭, 밸브 및 유사장치 제조업
985986화성산업사대구광역시 서구 가르뱅이로6길 47 (이현동, 화성산업사)053-526-6701폴리스티렌 발포 성형제품 제조업 외 3종
986987화성정밀기계대구광역시 서구 국채보상로 90 (중리동, 화성정밀) (총 2 필지)053-553-0657디지털 적층 성형기계 제조업 외 1종
987988화신섬유(주)대구광역시 서구 달구벌대로377안길 17-7 (내당동)053-556-7449스타킹 및 기타 양말 제조업
988989효성염직대구광역시 서구 문화로 38-10 (이현동)053-562-5141섬유제품 기타 정리 및 마무리 가공업 외 1종
989990휴먼에이코리아대구광역시 서구 와룡로87길 12-7 (이현동)053-721-6312그 외 기타 특수목적용 기계 제조업
990991흥림아이앤씨대구광역시 서구 와룡로99길 17, 18동 (이현동)053-553-4094날염 가공업 외 2종