Overview

Dataset statistics

Number of variables9
Number of observations228
Missing cells100
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.4 KiB
Average record size in memory73.6 B

Variable types

Categorical2
Text6
Numeric1

Dataset

Description전라남도 순천시 산업단지 현황 정보입니다. 순천시 관내 산업단지에 대한 구분, 회사명, 공장대표주소, 전화번호, 생산품, 업종명, 공장면적, 종업원수, 기업구분 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/3040993/fileData.do

Alerts

종업원수(명) is highly overall correlated with 기업구분High correlation
기업구분 is highly overall correlated with 종업원수(명)High correlation
전화번호 has 17 (7.5%) missing valuesMissing
업종명 has 27 (11.8%) missing valuesMissing
공장면적 has 28 (12.3%) missing valuesMissing
종업원수(명) has 28 (12.3%) missing valuesMissing
종업원수(명) has 22 (9.6%) zerosZeros

Reproduction

Analysis started2023-12-12 09:35:39.557731
Analysis finished2023-12-12 09:35:40.955845
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct5
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
율촌제1산업단지
84 
해룡일반산업단지
63 
순천일반산업단지
37 
순천주암농공단지
34 
해룡국민임대산업단지
10 

Length

Max length10
Median length8
Mean length8.0877193
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
율촌제1산업단지 84
36.8%
해룡일반산업단지 63
27.6%
순천일반산업단지 37
16.2%
순천주암농공단지 34
14.9%
해룡국민임대산업단지 10
 
4.4%

Length

2023-12-12T18:35:41.053990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:35:41.203743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
율촌제1산업단지 84
36.8%
해룡일반산업단지 63
27.6%
순천일반산업단지 37
16.2%
순천주암농공단지 34
14.9%
해룡국민임대산업단지 10
 
4.4%

회사명
Text

Distinct225
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T18:35:41.501654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length5.9210526
Min length2

Characters and Unicode

Total characters1350
Distinct characters238
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique222 ?
Unique (%)97.4%

Sample

1st row디에스알제강㈜
2nd row매일식품㈜
3rd row한국신광마이크로애랙트로닉스㈜
4th row부국철강㈜
5th row㈜티에이
ValueCountFrequency (%)
디에스알제강㈜ 3
 
1.3%
㈜파루 3
 
1.3%
재)전남테크노파크 2
 
0.9%
㈜키플러스 1
 
0.4%
라인호㈜ 1
 
0.4%
마린블리스 1
 
0.4%
유)유성기업 1
 
0.4%
유)천진기업 1
 
0.4%
주)동화에프엔이 1
 
0.4%
주)명진철강산업 1
 
0.4%
Other values (217) 217
93.5%
2023-12-12T18:35:42.004160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 173
 
12.8%
스 54
 
4.0%
이 53
 
3.9%
에 43
 
3.2%
지 28
 
2.1%
업 27
 
2.0%
엔 26
 
1.9%
크 23
 
1.7%
리 21
 
1.6%
아 21
 
1.6%
Other values (228) 881
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1121
83.0%
Other Symbol 173
 
12.8%
Uppercase Letter 18
 
1.3%
Close Punctuation 16
 
1.2%
Open Punctuation 16
 
1.2%
Space Separator 4
 
0.3%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 54
 
4.8%
이 53
 
4.7%
에 43
 
3.8%
지 28
 
2.5%
업 27
 
2.4%
엔 26
 
2.3%
크 23
 
2.1%
리 21
 
1.9%
아 21
 
1.9%
산 21
 
1.9%
Other values (213) 804
71.7%
Uppercase Letter
ValueCountFrequency (%)
S 7
38.9%
G 2
 
11.1%
T 2
 
11.1%
K 1
 
5.6%
H 1
 
5.6%
P 1
 
5.6%
E 1
 
5.6%
D 1
 
5.6%
N 1
 
5.6%
C 1
 
5.6%
Other Symbol
ValueCountFrequency (%)
㈜ 173
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1294
95.9%
Common 38
 
2.8%
Latin 18
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 173
 
13.4%
스 54
 
4.2%
이 53
 
4.1%
에 43
 
3.3%
지 28
 
2.2%
업 27
 
2.1%
엔 26
 
2.0%
크 23
 
1.8%
리 21
 
1.6%
아 21
 
1.6%
Other values (214) 825
63.8%
Latin
ValueCountFrequency (%)
S 7
38.9%
G 2
 
11.1%
T 2
 
11.1%
K 1
 
5.6%
H 1
 
5.6%
P 1
 
5.6%
E 1
 
5.6%
D 1
 
5.6%
N 1
 
5.6%
C 1
 
5.6%
Common
ValueCountFrequency (%)
) 16
42.1%
( 16
42.1%
4
 
10.5%
2 2
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1121
83.0%
None 173
 
12.8%
ASCII 56
 
4.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 173
100.0%
Hangul
ValueCountFrequency (%)
스 54
 
4.8%
이 53
 
4.7%
에 43
 
3.8%
지 28
 
2.5%
업 27
 
2.4%
엔 26
 
2.3%
크 23
 
2.1%
리 21
 
1.9%
아 21
 
1.9%
산 21
 
1.9%
Other values (213) 804
71.7%
ASCII
ValueCountFrequency (%)
) 16
28.6%
( 16
28.6%
S 7
12.5%
4
 
7.1%
G 2
 
3.6%
T 2
 
3.6%
2 2
 
3.6%
K 1
 
1.8%
H 1
 
1.8%
P 1
 
1.8%
Other values (4) 4
 
7.1%

공장대표주소
Text

Distinct187
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T18:35:42.237007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length54
Mean length24.864035
Min length16

Characters and Unicode

Total characters5669
Distinct characters92
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

Unique168 ?
Unique (%)73.7%

Sample

1st row전라남도 순천시 서면산단1길15
2nd row전라남도 순천시 서면산단1길 16
3rd row전라남도 순천시 서면산단1길 32
4th row전라남도 순천시 서면산단1길 26
5th row전라남도 순천시 서면산단2길 63
ValueCountFrequency (%)
전라남도 229
19.5%
순천시 229
19.5%
해룡면 158
13.5%
율촌산단1로 43
 
3.7%
선월리 36
 
3.1%
주암면 34
 
2.9%
주석로 34
 
2.9%
율촌산단4로 31
 
2.6%
호두리 23
 
2.0%
서면산단4길 21
 
1.8%
Other values (213) 336
28.6%
2023-12-12T18:35:42.666818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
946
 
16.7%
1 251
 
4.4%
전 246
 
4.3%
남 246
 
4.3%
시 231
 
4.1%
도 229
 
4.0%
순 229
 
4.0%
천 229
 
4.0%
라 229
 
4.0%
면 228
 
4.0%
Other values (82) 2605
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3429
60.5%
Decimal Number 1019
 
18.0%
Space Separator 946
 
16.7%
Dash Punctuation 148
 
2.6%
Other Punctuation 41
 
0.7%
Uppercase Letter 34
 
0.6%
Close Punctuation 26
 
0.5%
Open Punctuation 26
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 246
 
7.2%
남 246
 
7.2%
시 231
 
6.7%
도 229
 
6.7%
순 229
 
6.7%
천 229
 
6.7%
라 229
 
6.7%
면 228
 
6.6%
룡 174
 
5.1%
해 174
 
5.1%
Other values (63) 1214
35.4%
Decimal Number
ValueCountFrequency (%)
1 251
24.6%
2 150
14.7%
4 114
11.2%
0 113
11.1%
9 104
10.2%
3 82
 
8.0%
6 56
 
5.5%
7 56
 
5.5%
8 51
 
5.0%
5 42
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
P 14
41.2%
T 13
38.2%
A 7
20.6%
Other Punctuation
ValueCountFrequency (%)
, 28
68.3%
/ 13
31.7%
Space Separator
ValueCountFrequency (%)
946
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 148
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3429
60.5%
Common 2206
38.9%
Latin 34
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 246
 
7.2%
남 246
 
7.2%
시 231
 
6.7%
도 229
 
6.7%
순 229
 
6.7%
천 229
 
6.7%
라 229
 
6.7%
면 228
 
6.6%
룡 174
 
5.1%
해 174
 
5.1%
Other values (63) 1214
35.4%
Common
ValueCountFrequency (%)
946
42.9%
1 251
 
11.4%
2 150
 
6.8%
- 148
 
6.7%
4 114
 
5.2%
0 113
 
5.1%
9 104
 
4.7%
3 82
 
3.7%
6 56
 
2.5%
7 56
 
2.5%
Other values (6) 186
 
8.4%
Latin
ValueCountFrequency (%)
P 14
41.2%
T 13
38.2%
A 7
20.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3429
60.5%
ASCII 2240
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
946
42.2%
1 251
 
11.2%
2 150
 
6.7%
- 148
 
6.6%
4 114
 
5.1%
0 113
 
5.0%
9 104
 
4.6%
3 82
 
3.7%
6 56
 
2.5%
7 56
 
2.5%
Other values (9) 220
 
9.8%
Hangul
ValueCountFrequency (%)
전 246
 
7.2%
남 246
 
7.2%
시 231
 
6.7%
도 229
 
6.7%
순 229
 
6.7%
천 229
 
6.7%
라 229
 
6.7%
면 228
 
6.6%
룡 174
 
5.1%
해 174
 
5.1%
Other values (63) 1214
35.4%

전화번호
Text

MISSING 

Distinct199
Distinct (%)94.3%
Missing17
Missing (%)7.5%
Memory size1.9 KiB
2023-12-12T18:35:43.012915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.895735
Min length2

Characters and Unicode

Total characters2510
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique189 ?
Unique (%)89.6%

Sample

1st row061-729-3500
2nd row061-752-3331
3rd row061-753-8801
4th row061-751-0303
5th row061-755-4806
ValueCountFrequency (%)
061-727-8058 3
 
1.4%
061-729-3500 3
 
1.4%
061-759-5159 2
 
0.9%
2
 
0.9%
061-727-7881 2
 
0.9%
061-744-6266 2
 
0.9%
061-754-8114 2
 
0.9%
061-724-2125 2
 
0.9%
061-723-4994 2
 
0.9%
053-584-6841 2
 
0.9%
Other values (189) 189
89.6%
2023-12-12T18:35:43.487357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 419
16.7%
0 365
14.5%
1 321
12.8%
6 284
11.3%
7 264
10.5%
2 207
8.2%
5 202
8.0%
8 125
 
5.0%
3 114
 
4.5%
4 106
 
4.2%
Other values (2) 103
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2089
83.2%
Dash Punctuation 419
 
16.7%
Space Separator 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 365
17.5%
1 321
15.4%
6 284
13.6%
7 264
12.6%
2 207
9.9%
5 202
9.7%
8 125
 
6.0%
3 114
 
5.5%
4 106
 
5.1%
9 101
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 419
100.0%
Space Separator
ValueCountFrequency (%)
　 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2510
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 419
16.7%
0 365
14.5%
1 321
12.8%
6 284
11.3%
7 264
10.5%
2 207
8.2%
5 202
8.0%
8 125
 
5.0%
3 114
 
4.5%
4 106
 
4.2%
Other values (2) 103
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2508
99.9%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 419
16.7%
0 365
14.6%
1 321
12.8%
6 284
11.3%
7 264
10.5%
2 207
8.3%
5 202
8.1%
8 125
 
5.0%
3 114
 
4.5%
4 106
 
4.2%
None
ValueCountFrequency (%)
　 2
100.0%

생산품
Text

Distinct216
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T18:35:43.852561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length29
Mean length9.0877193
Min length2

Characters and Unicode

Total characters2072
Distinct characters332
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

Unique205 ?
Unique (%)89.9%

Sample

1st row와이어로프
2nd row장류, 식품첨가물, 절임식품 등
3rd row다이오드
4th row냉연강판
5th row텅스텐카바이드 재생분말, 헤비알로이분말, 선재용 가이드쿨러 등
ValueCountFrequency (%)
및 8
 
1.8%
등 6
 
1.4%
금속 5
 
1.1%
철구조물 5
 
1.1%
전기 4
 
0.9%
플라스틱 4
 
0.9%
수지 4
 
0.9%
제조 4
 
0.9%
가공 4
 
0.9%
산업용 4
 
0.9%
Other values (344) 395
89.2%
2023-12-12T18:35:44.337836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
215
 
10.4%
, 101
 
4.9%
기 64
 
3.1%
제 55
 
2.7%
조 39
 
1.9%
재 32
 
1.5%
전 31
 
1.5%
장 30
 
1.4%
품 28
 
1.4%
용 26
 
1.3%
Other values (322) 1451
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1656
79.9%
Space Separator 215
 
10.4%
Other Punctuation 103
 
5.0%
Uppercase Letter 74
 
3.6%
Open Punctuation 8
 
0.4%
Lowercase Letter 8
 
0.4%
Close Punctuation 7
 
0.3%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 64
 
3.9%
제 55
 
3.3%
조 39
 
2.4%
재 32
 
1.9%
전 31
 
1.9%
장 30
 
1.8%
품 28
 
1.7%
용 26
 
1.6%
스 26
 
1.6%
트 24
 
1.4%
Other values (290) 1301
78.6%
Uppercase Letter
ValueCountFrequency (%)
E 14
18.9%
P 9
12.2%
D 7
9.5%
L 7
9.5%
C 6
8.1%
T 5
 
6.8%
S 4
 
5.4%
A 4
 
5.4%
N 3
 
4.1%
V 2
 
2.7%
Other values (10) 13
17.6%
Lowercase Letter
ValueCountFrequency (%)
i 2
25.0%
l 2
25.0%
t 1
12.5%
r 1
12.5%
e 1
12.5%
p 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 101
98.1%
/ 2
 
1.9%
Space Separator
ValueCountFrequency (%)
215
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1656
79.9%
Common 334
 
16.1%
Latin 82
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 64
 
3.9%
제 55
 
3.3%
조 39
 
2.4%
재 32
 
1.9%
전 31
 
1.9%
장 30
 
1.8%
품 28
 
1.7%
용 26
 
1.6%
스 26
 
1.6%
트 24
 
1.4%
Other values (290) 1301
78.6%
Latin
ValueCountFrequency (%)
E 14
17.1%
P 9
11.0%
D 7
 
8.5%
L 7
 
8.5%
C 6
 
7.3%
T 5
 
6.1%
S 4
 
4.9%
A 4
 
4.9%
N 3
 
3.7%
i 2
 
2.4%
Other values (16) 21
25.6%
Common
ValueCountFrequency (%)
215
64.4%
, 101
30.2%
( 8
 
2.4%
) 7
 
2.1%
/ 2
 
0.6%
2 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1656
79.9%
ASCII 416
 
20.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
215
51.7%
, 101
24.3%
E 14
 
3.4%
P 9
 
2.2%
( 8
 
1.9%
D 7
 
1.7%
L 7
 
1.7%
) 7
 
1.7%
C 6
 
1.4%
T 5
 
1.2%
Other values (22) 37
 
8.9%
Hangul
ValueCountFrequency (%)
기 64
 
3.9%
제 55
 
3.3%
조 39
 
2.4%
재 32
 
1.9%
전 31
 
1.9%
장 30
 
1.8%
품 28
 
1.7%
용 26
 
1.6%
스 26
 
1.6%
트 24
 
1.4%
Other values (290) 1301
78.6%

업종명
Text

MISSING 

Distinct161
Distinct (%)80.1%
Missing27
Missing (%)11.8%
Memory size1.9 KiB
2023-12-12T18:35:44.619802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length194
Median length87
Mean length41.711443
Min length6

Characters and Unicode

Total characters8384
Distinct characters236
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)70.1%

Sample

1st row금속 단조제품 제조업, 도금업, 철강선 제조업
2nd row천연 및 혼합조제 조미료 제조업, 장류 제조업, 식초, 발효 및 화학 조미료 제조업
3rd row도금업, 기타 반도체소자 제조업, 발광 다이오드 제조업
4th row강관 제조업, 강관 가공품 및 관 연결구류 제조업
5th row그 외 기타 1차 철강 제조업,기타 1차 비철금속 제조업
ValueCountFrequency (%)
및 233
 
11.2%
제조업 180
 
8.6%
기타 107
 
5.1%
금속 95
 
4.6%
외 66
 
3.2%
골조 37
 
1.8%
구조재 37
 
1.8%
그 33
 
1.6%
제조업,기타 32
 
1.5%
제조업,그 29
 
1.4%
Other values (386) 1235
59.3%
2023-12-12T18:35:45.455387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1883
22.5%
제 627
 
7.5%
조 611
 
7.3%
업 561
 
6.7%
, 382
 
4.6%
기 344
 
4.1%
및 233
 
2.8%
금 184
 
2.2%
속 177
 
2.1%
타 150
 
1.8%
Other values (226) 3232
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6107
72.8%
Space Separator 1883
 
22.5%
Other Punctuation 387
 
4.6%
Decimal Number 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 627
 
10.3%
조 611
 
10.0%
업 561
 
9.2%
기 344
 
5.6%
및 233
 
3.8%
금 184
 
3.0%
속 177
 
2.9%
타 150
 
2.5%
품 144
 
2.4%
용 132
 
2.2%
Other values (222) 2944
48.2%
Other Punctuation
ValueCountFrequency (%)
, 382
98.7%
. 5
 
1.3%
Space Separator
ValueCountFrequency (%)
1883
100.0%
Decimal Number
ValueCountFrequency (%)
1 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6107
72.8%
Common 2277
 
27.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 627
 
10.3%
조 611
 
10.0%
업 561
 
9.2%
기 344
 
5.6%
및 233
 
3.8%
금 184
 
3.0%
속 177
 
2.9%
타 150
 
2.5%
품 144
 
2.4%
용 132
 
2.2%
Other values (222) 2944
48.2%
Common
ValueCountFrequency (%)
1883
82.7%
, 382
 
16.8%
1 7
 
0.3%
. 5
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6106
72.8%
ASCII 2277
 
27.2%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1883
82.7%
, 382
 
16.8%
1 7
 
0.3%
. 5
 
0.2%
Hangul
ValueCountFrequency (%)
제 627
 
10.3%
조 611
 
10.0%
업 561
 
9.2%
기 344
 
5.6%
및 233
 
3.8%
금 184
 
3.0%
속 177
 
2.9%
타 150
 
2.5%
품 144
 
2.4%
용 132
 
2.2%
Other values (221) 2943
48.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

공장면적
Text

MISSING 

Distinct168
Distinct (%)84.0%
Missing28
Missing (%)12.3%
Memory size1.9 KiB
2023-12-12T18:35:45.880766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.715
Min length1

Characters and Unicode

Total characters943
Distinct characters12
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

Unique157 ?
Unique (%)78.5%

Sample

1st row33058
2nd row12316
3rd row23887
4th row13223
5th row3445
ValueCountFrequency (%)
0 23
 
11.5%
7113.3 2
 
1.0%
163.7 2
 
1.0%
150 2
 
1.0%
7639.2 2
 
1.0%
4961.1 2
 
1.0%
4857.6 2
 
1.0%
33058 2
 
1.0%
158.25 2
 
1.0%
2500 2
 
1.0%
Other values (158) 159
79.5%
2023-12-12T18:35:46.559677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 108
11.5%
3 98
10.4%
. 97
10.3%
2 97
10.3%
4 91
9.7%
0 88
9.3%
9 79
8.4%
5 77
8.2%
6 77
8.2%
8 69
7.3%
Other values (2) 62
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 845
89.6%
Other Punctuation 98
 
10.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 108
12.8%
3 98
11.6%
2 97
11.5%
4 91
10.8%
0 88
10.4%
9 79
9.3%
5 77
9.1%
6 77
9.1%
8 69
8.2%
7 61
7.2%
Other Punctuation
ValueCountFrequency (%)
. 97
99.0%
, 1
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 943
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 108
11.5%
3 98
10.4%
. 97
10.3%
2 97
10.3%
4 91
9.7%
0 88
9.3%
9 79
8.4%
5 77
8.2%
6 77
8.2%
8 69
7.3%
Other values (2) 62
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 943
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 108
11.5%
3 98
10.4%
. 97
10.3%
2 97
10.3%
4 91
9.7%
0 88
9.3%
9 79
8.4%
5 77
8.2%
6 77
8.2%
8 69
7.3%
Other values (2) 62
6.6%

종업원수(명)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct46
Distinct (%)23.0%
Missing28
Missing (%)12.3%
Infinite0
Infinite (%)0.0%
Mean16.205
Minimum0
Maximum196
Zeros22
Zeros (%)9.6%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T18:35:46.780319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median8
Q315
95-th percentile67.2
Maximum196
Range196
Interquartile range (IQR)12

Descriptive statistics

Standard deviation26.155564
Coefficient of variation (CV)1.6140428
Kurtosis16.90685
Mean16.205
Median Absolute Deviation (MAD)5
Skewness3.6817729
Sum3241
Variance684.11354
MonotonicityNot monotonic
2023-12-12T18:35:46.960227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 22
 
9.6%
3 17
 
7.5%
4 13
 
5.7%
7 13
 
5.7%
12 11
 
4.8%
8 11
 
4.8%
6 11
 
4.8%
10 10
 
4.4%
2 10
 
4.4%
5 9
 
3.9%
Other values (36) 73
32.0%
(Missing) 28
 
12.3%
ValueCountFrequency (%)
0 22
9.6%
1 2
 
0.9%
2 10
4.4%
3 17
7.5%
4 13
5.7%
5 9
3.9%
6 11
4.8%
7 13
5.7%
8 11
4.8%
9 5
 
2.2%
ValueCountFrequency (%)
196 1
0.4%
150 1
0.4%
130 1
0.4%
123 1
0.4%
87 2
0.9%
84 1
0.4%
81 1
0.4%
75 1
0.4%
71 1
0.4%
67 1
0.4%

기업구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
소기업
178 
<NA>
28 
중기업
21 
대기업
 
1

Length

Max length4
Median length3
Mean length3.122807
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row중기업
2nd row중기업
3rd row중기업
4th row소기업
5th row소기업

Common Values

ValueCountFrequency (%)
소기업 178
78.1%
<NA> 28
 
12.3%
중기업 21
 
9.2%
대기업 1
 
0.4%

Length

2023-12-12T18:35:47.153506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:35:47.271538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소기업 178
78.1%
na 28
 
12.3%
중기업 21
 
9.2%
대기업 1
 
0.4%

Interactions

2023-12-12T18:35:40.309397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:35:47.353278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분종업원수(명)기업구분
구분1.0000.2680.165
종업원수(명)0.2681.0000.656
기업구분0.1650.6561.000
2023-12-12T18:35:47.470937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업구분구분
기업구분1.0000.124
구분0.1241.000
2023-12-12T18:35:47.558732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종업원수(명)구분기업구분
종업원수(명)1.0000.1660.525
구분0.1661.0000.124
기업구분0.5250.1241.000

Missing values

2023-12-12T18:35:40.520670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:35:40.711604image/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.
2023-12-12T18:35:40.869293image/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

구분회사명공장대표주소전화번호생산품업종명공장면적종업원수(명)기업구분
0순천일반산업단지디에스알제강㈜전라남도 순천시 서면산단1길15061-729-3500와이어로프금속 단조제품 제조업, 도금업, 철강선 제조업3305887중기업
1순천일반산업단지매일식품㈜전라남도 순천시 서면산단1길 16061-752-3331장류, 식품첨가물, 절임식품 등천연 및 혼합조제 조미료 제조업, 장류 제조업, 식초, 발효 및 화학 조미료 제조업1231662중기업
2순천일반산업단지한국신광마이크로애랙트로닉스㈜전라남도 순천시 서면산단1길 32061-753-8801다이오드도금업, 기타 반도체소자 제조업, 발광 다이오드 제조업23887130중기업
3순천일반산업단지부국철강㈜전라남도 순천시 서면산단1길 26061-751-0303냉연강판강관 제조업, 강관 가공품 및 관 연결구류 제조업132236소기업
4순천일반산업단지㈜티에이전라남도 순천시 서면산단2길 63061-755-4806텅스텐카바이드 재생분말, 헤비알로이분말, 선재용 가이드쿨러 등그 외 기타 1차 철강 제조업,기타 1차 비철금속 제조업344510소기업
5순천일반산업단지㈜영토산업개발전라남도 순천시 서면산단2길 63061-722-1209흙콘트리트그 외 기타 분류 안된 비금속 광물제품 제조업,비내화 모르타르 제조업13326소기업
6순천일반산업단지㈜동방이엔지전라남도 순천시 서면산단2길 67061-745-3486전기 박소 외도장 및 기타 피막처리업,배전반 및 전기 자동제어반 제조업12419소기업
7순천일반산업단지세신산업전라남도 순천시 서면산단2길 71061-751-2022분체도장도장 및 기타 피막처리업,금속 문, 창, 셔터 및 관련제품 제조업10394소기업
8순천일반산업단지해원엠에스씨㈜전라남도 순천시 서면산단3길 12061-759-2523아연도금강판, 접합강판, 컬러강판금속 열처리업,도금업,도장 및 기타 피막처리업,도금, 착색 및 기타 표면처리강재 제조업4315675중기업
9순천일반산업단지㈜신성메이저글러브전라남도 순천시 서면산단4길 30061-752-1027산업용 안전장갑기타 편조의복 액세서리 제조업12561196중기업
구분회사명공장대표주소전화번호생산품업종명공장면적종업원수(명)기업구분
218율촌제1산업단지㈜테크빌전라남도 순천시 해룡면 율촌산단1로 50, 신소재센터 제2공장동 203호 (전라남도 순천시 해룡면)061-722-8336치과재료, 자동제어시스템기타 비철금속 주조업,기기용 자동측정 및 제어장치 제조업1502소기업
219율촌제1산업단지현대아이에프씨(주)전라남도 순천시 해룡면 율촌산단5로 46061-760-7332금속 단조제품제강업,금속 단조제품 제조업283258.471중기업
220율촌제1산업단지네모플랜전라남도 순천시 해룡면 율촌산단1로 50061-741-2073트랙체어그 외 기타 특수목적용 기계 제조업,산업용 섬유 세척, 염색, 정리 및 가공 기계 제조업1002소기업
221율촌제1산업단지에스지전라남도 순천시 해룡면 율촌산단1로 50061-686-5203농업 및 임업용 기계농업 및 임업용 기계 제조업1797소기업
222율촌제1산업단지대한한옥개발(주)전라남도 순천시 해룡면 율촌산단4로 13061-383-0227혼성 및 재생플라스틱 소재물질혼성 및 재생 플라스틱 소재 물질 제조업00소기업
223율촌제1산업단지㈜오든전라남도 순천시 해룡면 율촌산단4로 13 지식산업센터동 218호<NA>전기회로 접속장치, 기타선박건조전기회로 접속장치 제조업,기타 선박 건조업73.20소기업
224율촌제1산업단지(유)대광기업전라남도 순천시 해룡면 율촌산단4로 68-7061-727-7881금속탱크 및 저장용기, 공기조하장치, 금속 절삭기계금속탱크 및 저장용기 제조업,금속 절삭기계 제조업,공기 조화장치 제조업4179.2611소기업
225율촌제1산업단지㈜키플러스전라남도 순천시 해룡면 율촌산단4로 13 지식산업센터동 104호041-544-8589산업용 로봇산업용 로봇 제조업633소기업
226율촌제1산업단지㈜에스앤엠전라남도 순천시 해룡면 율촌산단4로 13, 지식산업센터동 205호(전남테크노파크)061-722-7637CO2포집기기체 여과기 제조업,액체 여과기 제조업,증류기, 열교환기 및 가스발생기 제조업876소기업
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