Overview

Dataset statistics

Number of variables12
Number of observations1232
Missing cells57
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory121.6 KiB
Average record size in memory101.1 B

Variable types

Numeric5
Categorical2
Text5

Dataset

Description충청북도 청주시 관내 산업단지별 입주기업 현황 데이터(2022. 8. 31.기준)로 단지명, 회사명, 지식산업센터명, 공장대표주소, 업종번호, 업종명, 생산품, 용지면적(제곱미터), 제조시설면적(제곱미터), 부대시설면적(제곱미터)을 제공합니다.
Author충청북도 청주시
URLhttps://www.data.go.kr/data/15066601/fileData.do

Alerts

지식산업센터명 is highly overall correlated with 용지면적 and 3 other fieldsHigh correlation
단지명 is highly overall correlated with 지식산업센터명High correlation
용지면적 is highly overall correlated with 제조시설면적 and 2 other fieldsHigh correlation
제조시설면적 is highly overall correlated with 용지면적 and 2 other fieldsHigh correlation
부대시설면적 is highly overall correlated with 용지면적 and 2 other fieldsHigh correlation
공장대표주소(도로명) has 54 (4.4%) missing valuesMissing
제조시설면적 is highly skewed (γ1 = 23.01256774)Skewed
용지면적 has 262 (21.3%) zerosZeros
제조시설면적 has 212 (17.2%) zerosZeros
부대시설면적 has 136 (11.0%) zerosZeros

Reproduction

Analysis started2023-12-12 09:54:08.125499
Analysis finished2023-12-12 09:54:13.582050
Duration5.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

Distinct685
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219.04708
Minimum1
Maximum685
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T18:54:13.667606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q143
median144.5
Q3377.25
95-th percentile623.45
Maximum685
Range684
Interquartile range (IQR)334.25

Descriptive statistics

Standard deviation206.26357
Coefficient of variation (CV)0.94164038
Kurtosis-0.72828933
Mean219.04708
Median Absolute Deviation (MAD)121.5
Skewness0.78429854
Sum269866
Variance42544.662
MonotonicityNot monotonic
2023-12-12T18:54:14.200915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 14
 
1.1%
3 12
 
1.0%
2 12
 
1.0%
4 10
 
0.8%
5 9
 
0.7%
6 9
 
0.7%
7 9
 
0.7%
8 9
 
0.7%
14 8
 
0.6%
19 8
 
0.6%
Other values (675) 1132
91.9%
ValueCountFrequency (%)
1 14
1.1%
2 12
1.0%
3 12
1.0%
4 10
0.8%
5 9
0.7%
6 9
0.7%
7 9
0.7%
8 9
0.7%
9 8
0.6%
10 8
0.6%
ValueCountFrequency (%)
685 1
0.1%
684 1
0.1%
683 1
0.1%
682 1
0.1%
681 1
0.1%
680 1
0.1%
679 1
0.1%
678 1
0.1%
677 1
0.1%
676 1
0.1%

단지명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
청주일반산업단지
685 
청주오창과학일반산업단지
219 
청주오송제2생명과학일반산업단지(충북경제자유구역 오송바이오폴리스지구)
103 
오송생명과학단지
73 
청원옥산일반산업단지
 
57
Other values (9)
95 

Length

Max length37
Median length8
Mean length11.504058
Min length8

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row오송생명과학단지
2nd row오송생명과학단지
3rd row오송생명과학단지
4th row오송생명과학단지
5th row오송생명과학단지

Common Values

ValueCountFrequency (%)
청주일반산업단지 685
55.6%
청주오창과학일반산업단지 219
 
17.8%
청주오송제2생명과학일반산업단지(충북경제자유구역 오송바이오폴리스지구) 103
 
8.4%
오송생명과학단지 73
 
5.9%
청원옥산일반산업단지 57
 
4.6%
청주오창제3일반산업단지 35
 
2.8%
청주테크노폴리스일반산업단지 21
 
1.7%
오창외국인투자지역 19
 
1.5%
청주오창제2일반산업단지 8
 
0.6%
청주현도일반산업단지 4
 
0.3%
Other values (4) 8
 
0.6%

Length

2023-12-12T18:54:14.367643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청주일반산업단지 685
51.3%
청주오창과학일반산업단지 219
 
16.4%
청주오송제2생명과학일반산업단지(충북경제자유구역 103
 
7.7%
오송바이오폴리스지구 103
 
7.7%
오송생명과학단지 73
 
5.5%
청원옥산일반산업단지 57
 
4.3%
청주오창제3일반산업단지 35
 
2.6%
청주테크노폴리스일반산업단지 21
 
1.6%
오창외국인투자지역 19
 
1.4%
청주오창제2일반산업단지 8
 
0.6%
Other values (6) 13
 
1.0%

회사명
Text

Distinct1160
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2023-12-12T18:54:14.661410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length7.9691558
Min length2

Characters and Unicode

Total characters9818
Distinct characters497
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1099 ?
Unique (%)89.2%

Sample

1st row(사)대한결핵협회
2nd row(주)그린광학
3rd row(주)그린광학
4th row(주)기린화장품
5th row(주)네오비젼 오송지점
ValueCountFrequency (%)
주식회사 57
 
4.1%
2공장 19
 
1.4%
농업회사법인 8
 
0.6%
주)그린광학 5
 
0.4%
주)심텍 4
 
0.3%
청주지점 4
 
0.3%
3공장 4
 
0.3%
주)에코프로비엠 4
 
0.3%
충청에너지서비스(주 4
 
0.3%
주)제트바이오텍 4
 
0.3%
Other values (1165) 1265
91.8%
2023-12-12T18:54:15.207398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 936
 
9.5%
( 893
 
9.1%
) 893
 
9.1%
이 411
 
4.2%
스 351
 
3.6%
255
 
2.6%
에 239
 
2.4%
아 113
 
1.2%
지 111
 
1.1%
사 110
 
1.1%
Other values (487) 5506
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7460
76.0%
Open Punctuation 893
 
9.1%
Close Punctuation 893
 
9.1%
Space Separator 255
 
2.6%
Uppercase Letter 164
 
1.7%
Lowercase Letter 71
 
0.7%
Decimal Number 60
 
0.6%
Other Punctuation 17
 
0.2%
Dash Punctuation 4
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 936
 
12.5%
이 411
 
5.5%
스 351
 
4.7%
에 239
 
3.2%
아 113
 
1.5%
지 111
 
1.5%
사 110
 
1.5%
텍 103
 
1.4%
오 97
 
1.3%
엔 96
 
1.3%
Other values (433) 4893
65.6%
Uppercase Letter
ValueCountFrequency (%)
E 19
 
11.6%
S 18
 
11.0%
M 15
 
9.1%
T 11
 
6.7%
N 9
 
5.5%
A 9
 
5.5%
K 8
 
4.9%
R 8
 
4.9%
C 8
 
4.9%
H 7
 
4.3%
Other values (15) 52
31.7%
Lowercase Letter
ValueCountFrequency (%)
i 12
16.9%
e 11
15.5%
n 11
15.5%
h 7
9.9%
g 6
8.5%
a 5
7.0%
o 4
 
5.6%
c 4
 
5.6%
r 3
 
4.2%
s 2
 
2.8%
Other values (5) 6
8.5%
Decimal Number
ValueCountFrequency (%)
2 33
55.0%
1 11
 
18.3%
3 11
 
18.3%
4 2
 
3.3%
5 1
 
1.7%
9 1
 
1.7%
7 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 14
82.4%
& 3
 
17.6%
Open Punctuation
ValueCountFrequency (%)
( 893
100.0%
Close Punctuation
ValueCountFrequency (%)
) 893
100.0%
Space Separator
ValueCountFrequency (%)
255
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7461
76.0%
Common 2122
 
21.6%
Latin 235
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 936
 
12.5%
이 411
 
5.5%
스 351
 
4.7%
에 239
 
3.2%
아 113
 
1.5%
지 111
 
1.5%
사 110
 
1.5%
텍 103
 
1.4%
오 97
 
1.3%
엔 96
 
1.3%
Other values (434) 4894
65.6%
Latin
ValueCountFrequency (%)
E 19
 
8.1%
S 18
 
7.7%
M 15
 
6.4%
i 12
 
5.1%
e 11
 
4.7%
n 11
 
4.7%
T 11
 
4.7%
N 9
 
3.8%
A 9
 
3.8%
K 8
 
3.4%
Other values (30) 112
47.7%
Common
ValueCountFrequency (%)
( 893
42.1%
) 893
42.1%
255
 
12.0%
2 33
 
1.6%
. 14
 
0.7%
1 11
 
0.5%
3 11
 
0.5%
- 4
 
0.2%
& 3
 
0.1%
4 2
 
0.1%
Other values (3) 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7460
76.0%
ASCII 2357
 
24.0%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 936
 
12.5%
이 411
 
5.5%
스 351
 
4.7%
에 239
 
3.2%
아 113
 
1.5%
지 111
 
1.5%
사 110
 
1.5%
텍 103
 
1.4%
오 97
 
1.3%
엔 96
 
1.3%
Other values (433) 4893
65.6%
ASCII
ValueCountFrequency (%)
( 893
37.9%
) 893
37.9%
255
 
10.8%
2 33
 
1.4%
E 19
 
0.8%
S 18
 
0.8%
M 15
 
0.6%
. 14
 
0.6%
i 12
 
0.5%
e 11
 
0.5%
Other values (43) 194
 
8.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%

지식산업센터명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
<NA>
786 
직지스타
136 
세중테크노밸리
130 
티원타워
96 
청주테크노S타워
 
66
Other values (2)
 
18

Length

Max length8
Median length4
Mean length4.6525974
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 786
63.8%
직지스타 136
 
11.0%
세중테크노밸리 130
 
10.6%
티원타워 96
 
7.8%
청주테크노S타워 66
 
5.4%
청주미래누리터 12
 
1.0%
HS비즈타워 6
 
0.5%

Length

2023-12-12T18:54:15.390413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:15.534253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 786
63.8%
직지스타 136
 
11.0%
세중테크노밸리 130
 
10.6%
티원타워 96
 
7.8%
청주테크노s타워 66
 
5.4%
청주미래누리터 12
 
1.0%
hs비즈타워 6
 
0.5%

공장대표주소(도로명)
Text

MISSING 

Distinct1034
Distinct (%)87.8%
Missing54
Missing (%)4.4%
Memory size9.8 KiB
2023-12-12T18:54:15.883230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length66
Mean length38.283531
Min length8

Characters and Unicode

Total characters45098
Distinct characters247
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique952 ?
Unique (%)80.8%

Sample

1st row충청북도 청주시 흥덕구 오송읍 오송생명4로 168-5 결핵연구원 ()
2nd row충청북도 청원군 오송읍 만수리 485번지
3rd row충청북도 청원군 오송읍 만수리 486번지
4th row충청북도 청원군 오송읍 연제리 684번지
5th row충청북도 청주시 흥덕구 오송읍 정중연제로 787
ValueCountFrequency (%)
충청북도 1178
 
12.5%
청주시 1154
 
12.3%
흥덕구 931
 
9.9%
송정동 388
 
4.1%
1동 325
 
3.5%
오창읍 233
 
2.5%
청원구 221
 
2.4%
76 150
 
1.6%
외 145
 
1.5%
오송읍 141
 
1.5%
Other values (1225) 4529
48.2%
2023-12-12T18:54:16.428886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8221
 
18.2%
청 2668
 
5.9%
1 2176
 
4.8%
주 1295
 
2.9%
북 1208
 
2.7%
도 1206
 
2.7%
충 1203
 
2.7%
구 1200
 
2.7%
시 1159
 
2.6%
3 1104
 
2.4%
Other values (237) 23658
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25792
57.2%
Space Separator 8221
 
18.2%
Decimal Number 8167
 
18.1%
Close Punctuation 873
 
1.9%
Open Punctuation 873
 
1.9%
Other Punctuation 853
 
1.9%
Uppercase Letter 177
 
0.4%
Dash Punctuation 123
 
0.3%
Math Symbol 12
 
< 0.1%
Other Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 2668
 
10.3%
주 1295
 
5.0%
북 1208
 
4.7%
도 1206
 
4.7%
충 1203
 
4.7%
구 1200
 
4.7%
시 1159
 
4.5%
동 1051
 
4.1%
로 1016
 
3.9%
덕 938
 
3.6%
Other values (207) 12848
49.8%
Decimal Number
ValueCountFrequency (%)
1 2176
26.6%
3 1104
13.5%
0 890
10.9%
4 880
10.8%
2 751
 
9.2%
6 652
 
8.0%
5 609
 
7.5%
7 542
 
6.6%
8 291
 
3.6%
9 272
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
B 70
39.5%
F 40
22.6%
L 25
 
14.1%
T 21
 
11.9%
S 9
 
5.1%
I 4
 
2.3%
G 4
 
2.3%
K 2
 
1.1%
A 1
 
0.6%
M 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 852
99.9%
& 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
i 1
50.0%
Space Separator
ValueCountFrequency (%)
8221
100.0%
Close Punctuation
ValueCountFrequency (%)
) 873
100.0%
Open Punctuation
ValueCountFrequency (%)
( 873
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 123
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25795
57.2%
Common 19122
42.4%
Latin 179
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 2668
 
10.3%
주 1295
 
5.0%
북 1208
 
4.7%
도 1206
 
4.7%
충 1203
 
4.7%
구 1200
 
4.7%
시 1159
 
4.5%
동 1051
 
4.1%
로 1016
 
3.9%
덕 938
 
3.6%
Other values (207) 12851
49.8%
Common
ValueCountFrequency (%)
8221
43.0%
1 2176
 
11.4%
3 1104
 
5.8%
0 890
 
4.7%
4 880
 
4.6%
) 873
 
4.6%
( 873
 
4.6%
, 852
 
4.5%
2 751
 
3.9%
6 652
 
3.4%
Other values (7) 1850
 
9.7%
Latin
ValueCountFrequency (%)
B 70
39.1%
F 40
22.3%
L 25
 
14.0%
T 21
 
11.7%
S 9
 
5.0%
I 4
 
2.2%
G 4
 
2.2%
K 2
 
1.1%
A 1
 
0.6%
t 1
 
0.6%
Other values (2) 2
 
1.1%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25790
57.2%
ASCII 19301
42.8%
None 5
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8221
42.6%
1 2176
 
11.3%
3 1104
 
5.7%
0 890
 
4.6%
4 880
 
4.6%
) 873
 
4.5%
( 873
 
4.5%
, 852
 
4.4%
2 751
 
3.9%
6 652
 
3.4%
Other values (19) 2029
 
10.5%
Hangul
ValueCountFrequency (%)
청 2668
 
10.3%
주 1295
 
5.0%
북 1208
 
4.7%
도 1206
 
4.7%
충 1203
 
4.7%
구 1200
 
4.7%
시 1159
 
4.5%
동 1051
 
4.1%
로 1016
 
3.9%
덕 938
 
3.6%
Other values (206) 12846
49.8%
None
ValueCountFrequency (%)
㈜ 5
100.0%
CJK
ValueCountFrequency (%)
內 2
100.0%

대표업종번호
Real number (ℝ)

Distinct282
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32120.702
Minimum10122
Maximum94120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T18:54:16.581041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10122
5-th percentile10801
Q121210
median26429
Q329299
95-th percentile72111
Maximum94120
Range83998
Interquartile range (IQR)8089

Descriptive statistics

Standard deviation17852.456
Coefficient of variation (CV)0.55579282
Kurtosis0.71379541
Mean32120.702
Median Absolute Deviation (MAD)5129
Skewness1.4084144
Sum39572705
Variance3.1871017 × 108
MonotonicityNot monotonic
2023-12-12T18:54:16.711315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20423 51
 
4.1%
29271 38
 
3.1%
26299 35
 
2.8%
28123 30
 
2.4%
20499 30
 
2.4%
21210 28
 
2.3%
27199 26
 
2.1%
26221 25
 
2.0%
58222 21
 
1.7%
25924 20
 
1.6%
Other values (272) 928
75.3%
ValueCountFrequency (%)
10122 1
 
0.1%
10129 4
0.3%
10219 1
 
0.1%
10220 1
 
0.1%
10301 1
 
0.1%
10309 2
 
0.2%
10402 3
0.2%
10619 2
 
0.2%
10620 1
 
0.1%
10713 5
0.4%
ValueCountFrequency (%)
94120 1
 
0.1%
84229 1
 
0.1%
84213 1
 
0.1%
76400 1
 
0.1%
75994 1
 
0.1%
75992 2
0.2%
75320 1
 
0.1%
74100 3
0.2%
73902 2
0.2%
73203 3
0.2%

업종번호
Text

Distinct553
Distinct (%)44.9%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2023-12-12T18:54:17.029341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length145
Median length5
Mean length9.7954545
Min length5

Characters and Unicode

Total characters12068
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique392 ?
Unique (%)31.8%

Sample

1st row70113
2nd row27199
3rd row70113
4th row20423, 70111
5th row27199, 27301
ValueCountFrequency (%)
20423 60
 
2.9%
26299 47
 
2.3%
20499 45
 
2.2%
29271 40
 
1.9%
28123 37
 
1.8%
27199 37
 
1.8%
21210 35
 
1.7%
21300 33
 
1.6%
58222 28
 
1.3%
26221 27
 
1.3%
Other values (366) 1687
81.3%
2023-12-12T18:54:17.522153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3223
26.7%
1 2119
17.6%
9 1234
 
10.2%
0 1071
 
8.9%
, 844
 
7.0%
844
 
7.0%
3 741
 
6.1%
7 606
 
5.0%
6 420
 
3.5%
4 396
 
3.3%
Other values (2) 570
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10380
86.0%
Other Punctuation 844
 
7.0%
Space Separator 844
 
7.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3223
31.1%
1 2119
20.4%
9 1234
 
11.9%
0 1071
 
10.3%
3 741
 
7.1%
7 606
 
5.8%
6 420
 
4.0%
4 396
 
3.8%
8 305
 
2.9%
5 265
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 844
100.0%
Space Separator
ValueCountFrequency (%)
844
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12068
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3223
26.7%
1 2119
17.6%
9 1234
 
10.2%
0 1071
 
8.9%
, 844
 
7.0%
844
 
7.0%
3 741
 
6.1%
7 606
 
5.0%
6 420
 
3.5%
4 396
 
3.3%
Other values (2) 570
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12068
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3223
26.7%
1 2119
17.6%
9 1234
 
10.2%
0 1071
 
8.9%
, 844
 
7.0%
844
 
7.0%
3 741
 
6.1%
7 606
 
5.0%
6 420
 
3.5%
4 396
 
3.3%
Other values (2) 570
 
4.7%

업종명
Text

Distinct468
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2023-12-12T18:54:17.806350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length16.076299
Min length3

Characters and Unicode

Total characters19806
Distinct characters299
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

Unique282 ?
Unique (%)22.9%

Sample

1st row의학 및 약학 연구개발업
2nd row그 외 기타 의료용 기기 제조업
3rd row의학 및 약학 연구개발업
4th row화장품 제조업 외 1 종
5th row그 외 기타 의료용 기기 제조업 외 1 종
ValueCountFrequency (%)
제조업 926
 
14.9%
외 586
 
9.4%
및 433
 
7.0%
종 430
 
6.9%
기타 340
 
5.5%
1 256
 
4.1%
그 155
 
2.5%
2 87
 
1.4%
기계 71
 
1.1%
서비스업 63
 
1.0%
Other values (503) 2878
46.2%
2023-12-12T18:54:18.364915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4993
25.2%
업 1282
 
6.5%
제 1245
 
6.3%
조 1010
 
5.1%
기 829
 
4.2%
외 596
 
3.0%
종 442
 
2.2%
및 433
 
2.2%
타 340
 
1.7%
용 326
 
1.6%
Other values (289) 8310
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14255
72.0%
Space Separator 4993
 
25.2%
Decimal Number 435
 
2.2%
Other Punctuation 113
 
0.6%
Close Punctuation 5
 
< 0.1%
Open Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1282
 
9.0%
제 1245
 
8.7%
조 1010
 
7.1%
기 829
 
5.8%
외 596
 
4.2%
종 442
 
3.1%
및 433
 
3.0%
타 340
 
2.4%
용 326
 
2.3%
품 316
 
2.2%
Other values (274) 7436
52.2%
Decimal Number
ValueCountFrequency (%)
1 262
60.2%
2 88
 
20.2%
3 42
 
9.7%
4 15
 
3.4%
5 8
 
1.8%
7 7
 
1.6%
6 6
 
1.4%
8 3
 
0.7%
9 3
 
0.7%
0 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 97
85.8%
. 16
 
14.2%
Space Separator
ValueCountFrequency (%)
4993
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14255
72.0%
Common 5551
 
28.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1282
 
9.0%
제 1245
 
8.7%
조 1010
 
7.1%
기 829
 
5.8%
외 596
 
4.2%
종 442
 
3.1%
및 433
 
3.0%
타 340
 
2.4%
용 326
 
2.3%
품 316
 
2.2%
Other values (274) 7436
52.2%
Common
ValueCountFrequency (%)
4993
89.9%
1 262
 
4.7%
, 97
 
1.7%
2 88
 
1.6%
3 42
 
0.8%
. 16
 
0.3%
4 15
 
0.3%
5 8
 
0.1%
7 7
 
0.1%
6 6
 
0.1%
Other values (5) 17
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14243
71.9%
ASCII 5551
 
28.0%
Compat Jamo 12
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4993
89.9%
1 262
 
4.7%
, 97
 
1.7%
2 88
 
1.6%
3 42
 
0.8%
. 16
 
0.3%
4 15
 
0.3%
5 8
 
0.1%
7 7
 
0.1%
6 6
 
0.1%
Other values (5) 17
 
0.3%
Hangul
ValueCountFrequency (%)
업 1282
 
9.0%
제 1245
 
8.7%
조 1010
 
7.1%
기 829
 
5.8%
외 596
 
4.2%
종 442
 
3.1%
및 433
 
3.0%
타 340
 
2.4%
용 326
 
2.3%
품 316
 
2.2%
Other values (273) 7424
52.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 12
100.0%

생산품
Text

Distinct1091
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2023-12-12T18:54:18.714700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length89
Median length42
Mean length11.263799
Min length2

Characters and Unicode

Total characters13877
Distinct characters567
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1027 ?
Unique (%)83.4%

Sample

1st row연구소
2nd row의료용(외과수술용) 현미경
3rd row인간보건연구개발
4th row의약외품 두발화장품
5th row시력보정용 콘택트렌즈
ValueCountFrequency (%)
등 119
 
4.2%
및 116
 
4.1%
부품 43
 
1.5%
화장품 35
 
1.2%
반도체 35
 
1.2%
pcb 25
 
0.9%
관련 21
 
0.7%
기계 20
 
0.7%
소프트웨어 20
 
0.7%
외 17
 
0.6%
Other values (1631) 2388
84.1%
2023-12-12T18:54:19.231895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1730
 
12.5%
, 662
 
4.8%
기 432
 
3.1%
품 277
 
2.0%
용 256
 
1.8%
제 255
 
1.8%
장 252
 
1.8%
전 214
 
1.5%
스 167
 
1.2%
자 166
 
1.2%
Other values (557) 9466
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10418
75.1%
Space Separator 1730
 
12.5%
Other Punctuation 697
 
5.0%
Uppercase Letter 589
 
4.2%
Lowercase Letter 229
 
1.7%
Open Punctuation 93
 
0.7%
Close Punctuation 93
 
0.7%
Decimal Number 24
 
0.2%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 432
 
4.1%
품 277
 
2.7%
용 256
 
2.5%
제 255
 
2.4%
장 252
 
2.4%
전 214
 
2.1%
스 167
 
1.6%
자 166
 
1.6%
비 146
 
1.4%
부 138
 
1.3%
Other values (493) 8115
77.9%
Uppercase Letter
ValueCountFrequency (%)
C 92
15.6%
P 73
12.4%
D 46
 
7.8%
B 43
 
7.3%
L 41
 
7.0%
S 39
 
6.6%
E 33
 
5.6%
T 28
 
4.8%
O 26
 
4.4%
R 23
 
3.9%
Other values (15) 145
24.6%
Lowercase Letter
ValueCountFrequency (%)
a 26
11.4%
i 25
10.9%
e 25
10.9%
r 18
 
7.9%
l 15
 
6.6%
s 14
 
6.1%
n 13
 
5.7%
t 12
 
5.2%
c 12
 
5.2%
o 11
 
4.8%
Other values (14) 58
25.3%
Decimal Number
ValueCountFrequency (%)
2 14
58.3%
3 3
 
12.5%
4 3
 
12.5%
1 2
 
8.3%
8 1
 
4.2%
0 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 662
95.0%
/ 22
 
3.2%
. 11
 
1.6%
& 1
 
0.1%
· 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1730
100.0%
Open Punctuation
ValueCountFrequency (%)
( 93
100.0%
Close Punctuation
ValueCountFrequency (%)
) 93
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10418
75.1%
Common 2641
 
19.0%
Latin 818
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 432
 
4.1%
품 277
 
2.7%
용 256
 
2.5%
제 255
 
2.4%
장 252
 
2.4%
전 214
 
2.1%
스 167
 
1.6%
자 166
 
1.6%
비 146
 
1.4%
부 138
 
1.3%
Other values (493) 8115
77.9%
Latin
ValueCountFrequency (%)
C 92
 
11.2%
P 73
 
8.9%
D 46
 
5.6%
B 43
 
5.3%
L 41
 
5.0%
S 39
 
4.8%
E 33
 
4.0%
T 28
 
3.4%
O 26
 
3.2%
a 26
 
3.2%
Other values (39) 371
45.4%
Common
ValueCountFrequency (%)
1730
65.5%
, 662
 
25.1%
( 93
 
3.5%
) 93
 
3.5%
/ 22
 
0.8%
2 14
 
0.5%
. 11
 
0.4%
- 4
 
0.2%
3 3
 
0.1%
4 3
 
0.1%
Other values (5) 6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10418
75.1%
ASCII 3458
 
24.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1730
50.0%
, 662
 
19.1%
( 93
 
2.7%
) 93
 
2.7%
C 92
 
2.7%
P 73
 
2.1%
D 46
 
1.3%
B 43
 
1.2%
L 41
 
1.2%
S 39
 
1.1%
Other values (53) 546
 
15.8%
Hangul
ValueCountFrequency (%)
기 432
 
4.1%
품 277
 
2.7%
용 256
 
2.5%
제 255
 
2.4%
장 252
 
2.4%
전 214
 
2.1%
스 167
 
1.6%
자 166
 
1.6%
비 146
 
1.4%
부 138
 
1.3%
Other values (493) 8115
77.9%
None
ValueCountFrequency (%)
· 1
100.0%

용지면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct673
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10102.182
Minimum0
Maximum852762
Zeros262
Zeros (%)21.3%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T18:54:19.391648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120.605
median61.335
Q37000
95-th percentile39694.06
Maximum852762
Range852762
Interquartile range (IQR)6979.395

Descriptive statistics

Standard deviation37606.475
Coefficient of variation (CV)3.7226091
Kurtosis225.99969
Mean10102.182
Median Absolute Deviation (MAD)61.335
Skewness12.349943
Sum12445888
Variance1.4142469 × 109
MonotonicityNot monotonic
2023-12-12T18:54:19.542513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 262
 
21.3%
29.84 56
 
4.5%
25.184 37
 
3.0%
59.68 21
 
1.7%
26.711 13
 
1.1%
44.37 12
 
1.0%
53.422 10
 
0.8%
89.52 10
 
0.8%
46.13 10
 
0.8%
46.79 10
 
0.8%
Other values (663) 791
64.2%
ValueCountFrequency (%)
0.0 262
21.3%
9.583 1
 
0.1%
11.26 3
 
0.2%
11.28 5
 
0.4%
11.98 2
 
0.2%
12.97 1
 
0.1%
13.55 1
 
0.1%
13.63 5
 
0.4%
13.66 4
 
0.3%
14.27 3
 
0.2%
ValueCountFrequency (%)
852762.0 1
0.1%
351465.2 1
0.1%
350781.0 1
0.1%
329095.6 1
0.1%
303938.0 1
0.1%
224254.2 1
0.1%
218073.9 1
0.1%
212258.1 1
0.1%
204980.9 1
0.1%
188117.2 1
0.1%

제조시설면적
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct825
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4432.518
Minimum0
Maximum817440
Zeros212
Zeros (%)17.2%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T18:54:19.672126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q174.475
median274.435
Q32215.98
95-th percentile14782.915
Maximum817440
Range817440
Interquartile range (IQR)2141.505

Descriptive statistics

Standard deviation27358.776
Coefficient of variation (CV)6.1722877
Kurtosis647.71355
Mean4432.518
Median Absolute Deviation (MAD)274.435
Skewness23.012568
Sum5460862.1
Variance7.4850262 × 108
MonotonicityNot monotonic
2023-12-12T18:54:19.832496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 212
 
17.2%
98.4 55
 
4.5%
77.22 22
 
1.8%
196.8 12
 
1.0%
137.7 11
 
0.9%
143.65 10
 
0.8%
81.9 9
 
0.7%
65.22 6
 
0.5%
163.8 6
 
0.5%
145.9 6
 
0.5%
Other values (815) 883
71.7%
ValueCountFrequency (%)
0.0 212
17.2%
16.0 1
 
0.1%
17.1 1
 
0.1%
18.0 1
 
0.1%
20.0 2
 
0.2%
20.8 1
 
0.1%
20.92 1
 
0.1%
21.0 1
 
0.1%
24.6 1
 
0.1%
25.0 1
 
0.1%
ValueCountFrequency (%)
817440.0 1
0.1%
295837.71 1
0.1%
205093.33 1
0.1%
149596.07 1
0.1%
107887.97 1
0.1%
86771.48 1
0.1%
86301.133 1
0.1%
85720.66 1
0.1%
79702.55 1
0.1%
79005.02 1
0.1%

부대시설면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct848
Distinct (%)69.0%
Missing3
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean2604.342
Minimum0
Maximum222064.76
Zeros136
Zeros (%)11.0%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2023-12-12T18:54:19.987686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q172.09
median240
Q31676.67
95-th percentile9682.834
Maximum222064.76
Range222064.76
Interquartile range (IQR)1604.58

Descriptive statistics

Standard deviation10205.429
Coefficient of variation (CV)3.9186208
Kurtosis214.83763
Mean2604.342
Median Absolute Deviation (MAD)240
Skewness12.45547
Sum3200736.3
Variance1.0415077 × 108
MonotonicityNot monotonic
2023-12-12T18:54:20.176616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 136
 
11.0%
72.09 49
 
4.0%
63.988 21
 
1.7%
170.49 20
 
1.6%
141.208 16
 
1.3%
67.866 10
 
0.8%
144.18 9
 
0.7%
242.58 6
 
0.5%
139.66 6
 
0.5%
135.732 6
 
0.5%
Other values (838) 950
77.1%
ValueCountFrequency (%)
0.0 136
11.0%
5.19 1
 
0.1%
15.0 1
 
0.1%
16.0 1
 
0.1%
16.64 1
 
0.1%
17.71 1
 
0.1%
24.0 1
 
0.1%
25.0 1
 
0.1%
25.36 1
 
0.1%
26.3 1
 
0.1%
ValueCountFrequency (%)
222064.76 1
0.1%
140168.88 1
0.1%
98888.69 1
0.1%
78508.0 1
0.1%
70872.07 1
0.1%
66143.73 1
0.1%
62995.82 1
0.1%
58008.84 1
0.1%
56732.0 1
0.1%
50381.71 1
0.1%

Interactions

2023-12-12T18:54:12.409058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:09.639755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:10.455922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:11.118698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:11.765001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:12.532782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:09.781807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:10.605260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:11.251531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:11.883948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:12.674174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:09.913676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:10.728458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:11.371665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:12.010997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:12.793675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:10.099489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:10.847967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:11.486699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:12.144989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:12.918637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:10.307805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:10.991201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:11.645043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:54:12.287218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:54:20.317716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번단지명지식산업센터명대표업종번호용지면적제조시설면적부대시설면적
순번1.0000.5880.1840.2380.0000.0000.099
단지명0.5881.0001.0000.3950.3570.2360.000
지식산업센터명0.1841.0001.0000.353NaNNaNNaN
대표업종번호0.2380.3950.3531.0000.0000.0000.155
용지면적0.0000.357NaN0.0001.0000.8300.703
제조시설면적0.0000.236NaN0.0000.8301.0000.650
부대시설면적0.0990.000NaN0.1550.7030.6501.000
2023-12-12T18:54:20.459299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지식산업센터명단지명
지식산업센터명1.0000.995
단지명0.9951.000
2023-12-12T18:54:20.575642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번대표업종번호용지면적제조시설면적부대시설면적단지명지식산업센터명
순번1.0000.177-0.364-0.369-0.3740.2830.097
대표업종번호0.1771.000-0.201-0.494-0.1790.1700.136
용지면적-0.364-0.2011.0000.6270.7840.1831.000
제조시설면적-0.369-0.4940.6271.0000.5940.1251.000
부대시설면적-0.374-0.1790.7840.5941.0000.0001.000
단지명0.2830.1700.1830.1250.0001.0000.995
지식산업센터명0.0970.1361.0001.0001.0000.9951.000

Missing values

2023-12-12T18:54:13.062045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:54:13.329307image/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.
2023-12-12T18:54:13.489426image/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

순번단지명회사명지식산업센터명공장대표주소(도로명)대표업종번호업종번호업종명생산품용지면적제조시설면적부대시설면적
01오송생명과학단지(사)대한결핵협회<NA>충청북도 청주시 흥덕구 오송읍 오송생명4로 168-5 결핵연구원 ()7011370113의학 및 약학 연구개발업연구소9913.60.04372.04
12오송생명과학단지(주)그린광학<NA>충청북도 청원군 오송읍 만수리 485번지2719927199그 외 기타 의료용 기기 제조업의료용(외과수술용) 현미경4492.51241.0616.0
23오송생명과학단지(주)그린광학<NA>충청북도 청원군 오송읍 만수리 486번지7011370113의학 및 약학 연구개발업인간보건연구개발5698.41159.01953.18
34오송생명과학단지(주)기린화장품<NA>충청북도 청원군 오송읍 연제리 684번지2042320423, 70111화장품 제조업 외 1 종의약외품 두발화장품7358.91033.133130.78
45오송생명과학단지(주)네오비젼 오송지점<NA>충청북도 청주시 흥덕구 오송읍 정중연제로 7872719927199, 27301그 외 기타 의료용 기기 제조업 외 1 종시력보정용 콘택트렌즈5488.41880.311265.46
56오송생명과학단지(주)넥스팜코리아<NA>충청북도 청주시 흥덕구 오송읍 오송생명4로 168-41 ()2121021210완제 의약품 제조업혈압강하제외10057.63469.984996.85
67오송생명과학단지(주)다이아덴트<NA>충청북도 청주시 흥덕구 오송읍 오송생명4로 162719127191, 21300치과용 기기 제조업 외 1 종근관충전기외,치과재료10631.1910.02577.28
78오송생명과학단지(주)대웅제약<NA>충청북도 청주시 흥덕구 오송읍 연제리 689번지2121021210완제 의약품 제조업순환계, 신경계질환 치료제66111.411403.1525936.72
89오송생명과학단지(주)동헌기업<NA>충청북도 청주시 흥덕구 오송읍 정중연제로 721-14, 연제리 6102719927199그 외 기타 의료용 기기 제조업의료용 멸균장치3317.7563.2296.67
910오송생명과학단지(주)디에이치바이오<NA>충청북도 청주시 흥덕구 오송읍 정중연제로 721-14, 2동 1층7011370113의학 및 약학 연구개발업의약 및 약학 연구개발업0.00.0208.6
순번단지명회사명지식산업센터명공장대표주소(도로명)대표업종번호업종번호업종명생산품용지면적제조시설면적부대시설면적
1222102청주오송제2생명과학일반산업단지(충북경제자유구역 오송바이오폴리스지구)한양사료 주식회사<NA><NA>7011170111물리, 화학 및 생물학 연구개발업식품연구4950.00.02592.0
1223103청주오송제2생명과학일반산업단지(충북경제자유구역 오송바이오폴리스지구)화학물질안전원<NA>충청북도 청주시 흥덕구 오송읍 오송생명11로 270 화학물질안전원8421384213, 85640환경 행정 외 1 종교육서비스업(화학사고테러 교육 등)36096.00.014500.0
12241청주 강내일반산업단지깨끗한나라(주)<NA><NA>1790217902, 17123, 17125, 17129, 75994위생용 종이제품 제조업 외 4 종미용티슈, 핸드타올, 두루마리화장지, 점보롤화장지, 포장지, 컵원지 등22159.94335.09505.5
12251청주도시첨단문화산업단지(주)케이아이에스<NA>충청북도 청주시 청원구 상당로 314, 356 (내덕동, 청주첨단문화산업단지)2631026310, 26323, 26329, 26421, 26519, 58221, 58222, 62010컴퓨터 제조업 외 7 종av스위처, 수업자동녹화시스템, 멀티미디어 학습시스템, 교육용소프트웨어, 통신소프트웨어34752.0237.60.0
12262청주도시첨단문화산업단지(주)한우리<NA>충청북도 청주시 청원구 내덕동 201-31번지 청주첨단문화산업단지 223~225호2632926329, 26295, 26299, 26410, 26421, 26429, 26519, 28422, 28423, 28903기타 주변기기 제조업 외 9 종통신장비 제조34752.0119.00.0
12273청주도시첨단문화산업단지임원경제사회적협동조합<NA>충청북도 청주시 청원구 상당로 314, 367호 (내덕동, 청주첨단문화산업단지)2632926329기타 주변기기 제조업토양상태분석용 센서 패키81.031.540.5
12281청원내수농공단지(주)대농<NA>충청북도 청원군 내수읍 도원세교로 59-361310113101면 방적업면사86938.023995.8713517.95
12292청원내수농공단지(주)에스엔피시스템<NA>충청북도 청주시 청원구 내수읍 도원세교로 59-352921029210농업 및 임업용 기계 제조업농산물선별기6829.02373.3936.84
12303청원내수농공단지신대한판지(주) 청주공장<NA>충청북도 청주시 청원구 내수읍 도원세교로 59-311721117211, 17212골판지 제조업 외 1 종판지상자7410.03123.041452.5
12311청원현도농공단지(주)광림<NA>충청북도 청주시 서원구 현도면 청남로 484 ((주)광림) 외 8필지2913129131, 25113, 25114, 28111, 28123, 28512, 28909, 29161, 29169, 29172, 29173, 29241, 30121, 30122, 30201, 30202, 30203, 30332, 30400, 31113, 31201액체 펌프 제조업 외 20 종크레인, 노면청소차,소방차, 크루즈스텝카외 특장차유압카고크레인,청소차,고소작업차, 청소차 외60349.017764.874398.52