Overview

Dataset statistics

Number of variables7
Number of observations1023
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory57.1 KiB
Average record size in memory57.1 B

Variable types

Text5
Categorical1
Numeric1

Dataset

Description진주시 기업(공장) 현황 정보에 대한 상세 내역입니다. 단지명, 회사명, 공장대표 주소, 전화번호, 업종명 등을 제공
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3068407

Reproduction

Analysis started2023-12-11 00:47:41.955620
Analysis finished2023-12-11 00:47:42.850024
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct999
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2023-12-11T09:47:43.033022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length6.115347
Min length2

Characters and Unicode

Total characters6256
Distinct characters387
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

Unique977 ?
Unique (%)95.5%

Sample

1st row(유)동양프라스틱
2nd row(유)유창ENG
3rd row(주)HK바이오텍
4th row(주)HM금속
5th row(주)거산피앤에프
ValueCountFrequency (%)
주식회사 15
 
1.4%
제2공장 11
 
1.0%
대양산업 4
 
0.4%
주)성광 3
 
0.3%
주)디.에이치.티 3
 
0.3%
하나로테크(주 3
 
0.3%
진주공장 3
 
0.3%
주)화림 2
 
0.2%
주)신성엠텍 2
 
0.2%
주)서경 2
 
0.2%
Other values (1007) 1040
95.6%
2023-12-11T09:47:43.449079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 410
 
6.6%
( 334
 
5.3%
) 334
 
5.3%
업 299
 
4.8%
공 271
 
4.3%
정 180
 
2.9%
사 165
 
2.6%
성 136
 
2.2%
산 126
 
2.0%
기 124
 
2.0%
Other values (377) 3877
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5385
86.1%
Open Punctuation 334
 
5.3%
Close Punctuation 334
 
5.3%
Uppercase Letter 83
 
1.3%
Space Separator 66
 
1.1%
Decimal Number 32
 
0.5%
Other Punctuation 17
 
0.3%
Lowercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 410
 
7.6%
업 299
 
5.6%
공 271
 
5.0%
정 180
 
3.3%
사 165
 
3.1%
성 136
 
2.5%
산 126
 
2.3%
기 124
 
2.3%
대 123
 
2.3%
진 122
 
2.3%
Other values (348) 3429
63.7%
Uppercase Letter
ValueCountFrequency (%)
S 12
14.5%
G 10
12.0%
E 10
12.0%
N 9
10.8%
T 7
8.4%
M 6
7.2%
C 5
 
6.0%
H 4
 
4.8%
K 4
 
4.8%
L 3
 
3.6%
Other values (7) 13
15.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
40.0%
d 1
20.0%
f 1
20.0%
e 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 23
71.9%
3 5
 
15.6%
1 4
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 15
88.2%
& 2
 
11.8%
Open Punctuation
ValueCountFrequency (%)
( 334
100.0%
Close Punctuation
ValueCountFrequency (%)
) 334
100.0%
Space Separator
ValueCountFrequency (%)
66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5385
86.1%
Common 783
 
12.5%
Latin 88
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 410
 
7.6%
업 299
 
5.6%
공 271
 
5.0%
정 180
 
3.3%
사 165
 
3.1%
성 136
 
2.5%
산 126
 
2.3%
기 124
 
2.3%
대 123
 
2.3%
진 122
 
2.3%
Other values (348) 3429
63.7%
Latin
ValueCountFrequency (%)
S 12
13.6%
G 10
11.4%
E 10
11.4%
N 9
10.2%
T 7
 
8.0%
M 6
 
6.8%
C 5
 
5.7%
H 4
 
4.5%
K 4
 
4.5%
L 3
 
3.4%
Other values (11) 18
20.5%
Common
ValueCountFrequency (%)
( 334
42.7%
) 334
42.7%
66
 
8.4%
2 23
 
2.9%
. 15
 
1.9%
3 5
 
0.6%
1 4
 
0.5%
& 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5385
86.1%
ASCII 871
 
13.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 410
 
7.6%
업 299
 
5.6%
공 271
 
5.0%
정 180
 
3.3%
사 165
 
3.1%
성 136
 
2.5%
산 126
 
2.3%
기 124
 
2.3%
대 123
 
2.3%
진 122
 
2.3%
Other values (348) 3429
63.7%
ASCII
ValueCountFrequency (%)
( 334
38.3%
) 334
38.3%
66
 
7.6%
2 23
 
2.6%
. 15
 
1.7%
S 12
 
1.4%
G 10
 
1.1%
E 10
 
1.1%
N 9
 
1.0%
T 7
 
0.8%
Other values (19) 51
 
5.9%

업종명
Text

Distinct291
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2023-12-11T09:47:43.782872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length14.667644
Min length3

Characters and Unicode

Total characters15005
Distinct characters262
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

Unique160 ?
Unique (%)15.6%

Sample

1st row포장용 플라스틱 성형용기 제조업
2nd row농업 및 임업용 기계 제조업
3rd row건강기능식품 제조업 외 1 종
4th row선철주물 주조업
5th row선박 구성부분품 제조업
ValueCountFrequency (%)
제조업 753
 
16.8%
및 593
 
13.2%
종 181
 
4.0%
외 181
 
4.0%
기타 161
 
3.6%
절삭가공 143
 
3.2%
유사처리업 143
 
3.2%
1 122
 
2.7%
기계 110
 
2.5%
임업용 104
 
2.3%
Other values (373) 1989
44.4%
2023-12-11T09:47:44.196341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3457
23.0%
업 1249
 
8.3%
제 910
 
6.1%
조 905
 
6.0%
및 593
 
4.0%
기 517
 
3.4%
용 288
 
1.9%
사 267
 
1.8%
외 264
 
1.8%
공 246
 
1.6%
Other values (252) 6309
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11261
75.0%
Space Separator 3457
 
23.0%
Decimal Number 192
 
1.3%
Other Punctuation 95
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1249
 
11.1%
제 910
 
8.1%
조 905
 
8.0%
및 593
 
5.3%
기 517
 
4.6%
용 288
 
2.6%
사 267
 
2.4%
외 264
 
2.3%
공 246
 
2.2%
품 242
 
2.1%
Other values (243) 5780
51.3%
Decimal Number
ValueCountFrequency (%)
1 133
69.3%
2 33
 
17.2%
3 16
 
8.3%
6 4
 
2.1%
5 4
 
2.1%
4 2
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 87
91.6%
· 8
 
8.4%
Space Separator
ValueCountFrequency (%)
3457
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11261
75.0%
Common 3744
 
25.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1249
 
11.1%
제 910
 
8.1%
조 905
 
8.0%
및 593
 
5.3%
기 517
 
4.6%
용 288
 
2.6%
사 267
 
2.4%
외 264
 
2.3%
공 246
 
2.2%
품 242
 
2.1%
Other values (243) 5780
51.3%
Common
ValueCountFrequency (%)
3457
92.3%
1 133
 
3.6%
, 87
 
2.3%
2 33
 
0.9%
3 16
 
0.4%
· 8
 
0.2%
6 4
 
0.1%
5 4
 
0.1%
4 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11261
75.0%
ASCII 3736
 
24.9%
None 8
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3457
92.5%
1 133
 
3.6%
, 87
 
2.3%
2 33
 
0.9%
3 16
 
0.4%
6 4
 
0.1%
5 4
 
0.1%
4 2
 
0.1%
Hangul
ValueCountFrequency (%)
업 1249
 
11.1%
제 910
 
8.1%
조 905
 
8.0%
및 593
 
5.3%
기 517
 
4.6%
용 288
 
2.6%
사 267
 
2.4%
외 264
 
2.3%
공 246
 
2.2%
품 242
 
2.1%
Other values (243) 5780
51.3%
None
ValueCountFrequency (%)
· 8
100.0%

소재지
Text

Distinct848
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2023-12-11T09:47:44.416647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length50
Mean length25.530792
Min length18

Characters and Unicode

Total characters26118
Distinct characters187
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

Unique732 ?
Unique (%)71.6%

Sample

1st row경상남도 진주시 동진로264번길 12 (상대동) 외 1개 주소
2nd row경상남도 진주시 돗골로58번길 19 (상평동)
3rd row경상남도 진주시 문산읍 월아산로950번길 6
4th row경상남도 진주시 대곡면 남강로 2294 외 1개 주소
5th row경상남도 진주시 사봉면 사군로303번길 34
ValueCountFrequency (%)
경상남도 1023
18.4%
진주시 1023
18.4%
상평동 449
 
8.1%
상대동 140
 
2.5%
외 94
 
1.7%
주소 87
 
1.6%
대곡면 64
 
1.2%
문산읍 63
 
1.1%
1개 57
 
1.0%
정촌면 53
 
1.0%
Other values (759) 2511
45.1%
2023-12-11T09:47:44.797744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4582
17.5%
상 1632
 
6.2%
진 1224
 
4.7%
주 1154
 
4.4%
남 1116
 
4.3%
도 1086
 
4.2%
경 1040
 
4.0%
1 1028
 
3.9%
시 1027
 
3.9%
로 958
 
3.7%
Other values (177) 11271
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15576
59.6%
Space Separator 4582
 
17.5%
Decimal Number 4347
 
16.6%
Open Punctuation 659
 
2.5%
Close Punctuation 659
 
2.5%
Dash Punctuation 190
 
0.7%
Other Punctuation 75
 
0.3%
Uppercase Letter 30
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 1632
 
10.5%
진 1224
 
7.9%
주 1154
 
7.4%
남 1116
 
7.2%
도 1086
 
7.0%
경 1040
 
6.7%
시 1027
 
6.6%
로 958
 
6.2%
동 879
 
5.6%
길 563
 
3.6%
Other values (156) 4897
31.4%
Decimal Number
ValueCountFrequency (%)
1 1028
23.6%
2 581
13.4%
3 437
10.1%
5 393
 
9.0%
4 347
 
8.0%
0 332
 
7.6%
9 330
 
7.6%
6 321
 
7.4%
7 297
 
6.8%
8 281
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
B 14
46.7%
L 8
26.7%
C 4
 
13.3%
E 2
 
6.7%
A 1
 
3.3%
K 1
 
3.3%
Space Separator
ValueCountFrequency (%)
4582
100.0%
Open Punctuation
ValueCountFrequency (%)
( 659
100.0%
Close Punctuation
ValueCountFrequency (%)
) 659
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 190
100.0%
Other Punctuation
ValueCountFrequency (%)
, 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15576
59.6%
Common 10512
40.2%
Latin 30
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 1632
 
10.5%
진 1224
 
7.9%
주 1154
 
7.4%
남 1116
 
7.2%
도 1086
 
7.0%
경 1040
 
6.7%
시 1027
 
6.6%
로 958
 
6.2%
동 879
 
5.6%
길 563
 
3.6%
Other values (156) 4897
31.4%
Common
ValueCountFrequency (%)
4582
43.6%
1 1028
 
9.8%
( 659
 
6.3%
) 659
 
6.3%
2 581
 
5.5%
3 437
 
4.2%
5 393
 
3.7%
4 347
 
3.3%
0 332
 
3.2%
9 330
 
3.1%
Other values (5) 1164
 
11.1%
Latin
ValueCountFrequency (%)
B 14
46.7%
L 8
26.7%
C 4
 
13.3%
E 2
 
6.7%
A 1
 
3.3%
K 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15576
59.6%
ASCII 10542
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4582
43.5%
1 1028
 
9.8%
( 659
 
6.3%
) 659
 
6.3%
2 581
 
5.5%
3 437
 
4.1%
5 393
 
3.7%
4 347
 
3.3%
0 332
 
3.1%
9 330
 
3.1%
Other values (11) 1194
 
11.3%
Hangul
ValueCountFrequency (%)
상 1632
 
10.5%
진 1224
 
7.9%
주 1154
 
7.4%
남 1116
 
7.2%
도 1086
 
7.0%
경 1040
 
6.7%
시 1027
 
6.6%
로 958
 
6.2%
동 879
 
5.6%
길 563
 
3.6%
Other values (156) 4897
31.4%

단지명
Categorical

Distinct11
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
진주상평지방산업단지
516 
368 
진주정촌일반산업단지
 
48
진주대곡농공단지
 
20
진주사봉농공단지
 
18
Other values (6)
53 

Length

Max length12
Median length10
Mean length6.6656891
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row진주상평지방산업단지
2nd row진주상평지방산업단지
3rd row진주생물산업전문농공단지
4th row
5th row진주사봉농공단지

Common Values

ValueCountFrequency (%)
진주상평지방산업단지 516
50.4%
368
36.0%
진주정촌일반산업단지 48
 
4.7%
진주대곡농공단지 20
 
2.0%
진주사봉농공단지 18
 
1.8%
진주진성농공단지 17
 
1.7%
진주생물산업전문농공단지 14
 
1.4%
진주이반성농공단지 9
 
0.9%
진주실크전문농공단지 7
 
0.7%
진주일반산업단지 4
 
0.4%

Length

2023-12-11T09:47:44.930239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진주상평지방산업단지 516
78.8%
진주정촌일반산업단지 48
 
7.3%
진주대곡농공단지 20
 
3.1%
진주사봉농공단지 18
 
2.7%
진주진성농공단지 17
 
2.6%
진주생물산업전문농공단지 14
 
2.1%
진주이반성농공단지 9
 
1.4%
진주실크전문농공단지 7
 
1.1%
진주일반산업단지 4
 
0.6%
진주지수일반산업단지 2
 
0.3%

종업원수
Real number (ℝ)

Distinct75
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.158358
Minimum1
Maximum444
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2023-12-11T09:47:45.036545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median7
Q315
95-th percentile43.9
Maximum444
Range443
Interquartile range (IQR)11

Descriptive statistics

Standard deviation27.337714
Coefficient of variation (CV)1.9308535
Kurtosis116.49513
Mean14.158358
Median Absolute Deviation (MAD)4
Skewness9.1465391
Sum14484
Variance747.35063
MonotonicityNot monotonic
2023-12-11T09:47:45.158446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 103
 
10.1%
3 99
 
9.7%
5 97
 
9.5%
2 78
 
7.6%
10 66
 
6.5%
6 57
 
5.6%
8 53
 
5.2%
7 53
 
5.2%
9 44
 
4.3%
1 37
 
3.6%
Other values (65) 336
32.8%
ValueCountFrequency (%)
1 37
 
3.6%
2 78
7.6%
3 99
9.7%
4 103
10.1%
5 97
9.5%
6 57
5.6%
7 53
5.2%
8 53
5.2%
9 44
4.3%
10 66
6.5%
ValueCountFrequency (%)
444 1
0.1%
404 1
0.1%
290 1
0.1%
230 1
0.1%
195 1
0.1%
166 1
0.1%
151 1
0.1%
111 1
0.1%
110 1
0.1%
105 1
0.1%

주요생산품
Text

Distinct775
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2023-12-11T09:47:45.358740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length25
Mean length8.3284457
Min length1

Characters and Unicode

Total characters8520
Distinct characters497
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

Unique706 ?
Unique (%)69.0%

Sample

1st row육묘상자
2nd row농기계부품
3rd row버섯균사체,공액리놀레산
4th row자동차부품
5th row조선기자재배관 SPOOL
ValueCountFrequency (%)
자동차부품 65
 
4.2%
농기계부품 64
 
4.1%
및 43
 
2.8%
부품 32
 
2.1%
등 28
 
1.8%
자동차 26
 
1.7%
중장비부품 24
 
1.5%
기어 18
 
1.2%
농기구부품 17
 
1.1%
중장비 16
 
1.0%
Other values (983) 1221
78.6%
2023-12-11T09:47:45.685709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
533
 
6.3%
품 429
 
5.0%
부 412
 
4.8%
기 412
 
4.8%
, 407
 
4.8%
자 208
 
2.4%
동 208
 
2.4%
차 188
 
2.2%
농 173
 
2.0%
계 163
 
1.9%
Other values (487) 5387
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7045
82.7%
Space Separator 533
 
6.3%
Other Punctuation 427
 
5.0%
Uppercase Letter 181
 
2.1%
Open Punctuation 146
 
1.7%
Close Punctuation 144
 
1.7%
Lowercase Letter 35
 
0.4%
Decimal Number 8
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 429
 
6.1%
부 412
 
5.8%
기 412
 
5.8%
자 208
 
3.0%
동 208
 
3.0%
차 188
 
2.7%
농 173
 
2.5%
계 163
 
2.3%
장 144
 
2.0%
비 118
 
1.7%
Other values (442) 4590
65.2%
Uppercase Letter
ValueCountFrequency (%)
P 26
14.4%
E 20
11.0%
C 18
9.9%
L 13
 
7.2%
T 12
 
6.6%
D 10
 
5.5%
V 10
 
5.5%
A 10
 
5.5%
O 9
 
5.0%
S 9
 
5.0%
Other values (12) 44
24.3%
Lowercase Letter
ValueCountFrequency (%)
e 6
17.1%
s 4
11.4%
i 4
11.4%
c 3
8.6%
n 3
8.6%
p 3
8.6%
l 3
8.6%
a 3
8.6%
t 2
 
5.7%
o 1
 
2.9%
Other values (3) 3
8.6%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 2
25.0%
4 1
 
12.5%
3 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 407
95.3%
. 20
 
4.7%
Space Separator
ValueCountFrequency (%)
533
100.0%
Open Punctuation
ValueCountFrequency (%)
( 146
100.0%
Close Punctuation
ValueCountFrequency (%)
) 144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7045
82.7%
Common 1259
 
14.8%
Latin 216
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 429
 
6.1%
부 412
 
5.8%
기 412
 
5.8%
자 208
 
3.0%
동 208
 
3.0%
차 188
 
2.7%
농 173
 
2.5%
계 163
 
2.3%
장 144
 
2.0%
비 118
 
1.7%
Other values (442) 4590
65.2%
Latin
ValueCountFrequency (%)
P 26
 
12.0%
E 20
 
9.3%
C 18
 
8.3%
L 13
 
6.0%
T 12
 
5.6%
D 10
 
4.6%
V 10
 
4.6%
A 10
 
4.6%
O 9
 
4.2%
S 9
 
4.2%
Other values (25) 79
36.6%
Common
ValueCountFrequency (%)
533
42.3%
, 407
32.3%
( 146
 
11.6%
) 144
 
11.4%
. 20
 
1.6%
2 4
 
0.3%
1 2
 
0.2%
4 1
 
0.1%
- 1
 
0.1%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7045
82.7%
ASCII 1475
 
17.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
533
36.1%
, 407
27.6%
( 146
 
9.9%
) 144
 
9.8%
P 26
 
1.8%
E 20
 
1.4%
. 20
 
1.4%
C 18
 
1.2%
L 13
 
0.9%
T 12
 
0.8%
Other values (35) 136
 
9.2%
Hangul
ValueCountFrequency (%)
품 429
 
6.1%
부 412
 
5.8%
기 412
 
5.8%
자 208
 
3.0%
동 208
 
3.0%
차 188
 
2.7%
농 173
 
2.5%
계 163
 
2.3%
장 144
 
2.0%
비 118
 
1.7%
Other values (442) 4590
65.2%

전화번호
Text

Distinct956
Distinct (%)93.7%
Missing3
Missing (%)0.3%
Memory size8.1 KiB
2023-12-11T09:47:45.970551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.011765
Min length12

Characters and Unicode

Total characters12252
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

Unique899 ?
Unique (%)88.1%

Sample

1st row055-762-4588
2nd row055-753-9396
3rd row055-762-9307
4th row055-746-0040
5th row055-759-7080
ValueCountFrequency (%)
055-758-6391 3
 
0.3%
055-794-1001 3
 
0.3%
055-759-5836 3
 
0.3%
055-762-5200 3
 
0.3%
055-749-3200 3
 
0.3%
055-758-1970 3
 
0.3%
055-754-8090 3
 
0.3%
055-742-5205 2
 
0.2%
055-758-6720 2
 
0.2%
055-757-3827 2
 
0.2%
Other values (946) 993
97.4%
2023-12-11T09:47:46.436949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3221
26.3%
- 2040
16.7%
0 1621
13.2%
7 1511
12.3%
6 629
 
5.1%
2 623
 
5.1%
1 591
 
4.8%
4 553
 
4.5%
8 535
 
4.4%
3 508
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10212
83.3%
Dash Punctuation 2040
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3221
31.5%
0 1621
15.9%
7 1511
14.8%
6 629
 
6.2%
2 623
 
6.1%
1 591
 
5.8%
4 553
 
5.4%
8 535
 
5.2%
3 508
 
5.0%
9 420
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 2040
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3221
26.3%
- 2040
16.7%
0 1621
13.2%
7 1511
12.3%
6 629
 
5.1%
2 623
 
5.1%
1 591
 
4.8%
4 553
 
4.5%
8 535
 
4.4%
3 508
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3221
26.3%
- 2040
16.7%
0 1621
13.2%
7 1511
12.3%
6 629
 
5.1%
2 623
 
5.1%
1 591
 
4.8%
4 553
 
4.5%
8 535
 
4.4%
3 508
 
4.1%

Interactions

2023-12-11T09:47:42.599131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:47:46.544492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단지명종업원수
단지명1.0000.230
종업원수0.2301.000
2023-12-11T09:47:46.620711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종업원수단지명
종업원수1.0000.110
단지명0.1101.000

Missing values

2023-12-11T09:47:42.702267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:47:42.806758image/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.

Sample

업체명업종명소재지단지명종업원수주요생산품전화번호
0(유)동양프라스틱포장용 플라스틱 성형용기 제조업경상남도 진주시 동진로264번길 12 (상대동) 외 1개 주소진주상평지방산업단지29육묘상자055-762-4588
1(유)유창ENG농업 및 임업용 기계 제조업경상남도 진주시 돗골로58번길 19 (상평동)진주상평지방산업단지20농기계부품055-753-9396
2(주)HK바이오텍건강기능식품 제조업 외 1 종경상남도 진주시 문산읍 월아산로950번길 6진주생물산업전문농공단지9버섯균사체,공액리놀레산055-762-9307
3(주)HM금속선철주물 주조업경상남도 진주시 대곡면 남강로 2294 외 1개 주소66자동차부품055-746-0040
4(주)거산피앤에프선박 구성부분품 제조업경상남도 진주시 사봉면 사군로303번길 34진주사봉농공단지7조선기자재배관 SPOOL055-759-7080
5(주)경남일보신문 발행업경상남도 진주시 남강로 1065 (상평동, 경남일보)65일간신문055-751-1000
6(주)경남철공구조용 금속판제품 및 금속공작물 제조업경상남도 진주시 공단로 80 (상평동)진주상평지방산업단지8금속문055-752-3205
7(주)경신석면, 암면 및 유사제품 제조업경상남도 진주시 명석면 남성리 689번지24모래(골재)055-746-6886
8(주)경원1급정비자동차 종합 수리업경상남도 진주시 공단로 174 (상평동)진주상평지방산업단지26자동차정비055-752-6029
9(주)경주빵빵류 제조업경상남도 진주시 평거로258번길 21 (이현동)35빵류(경주빵)055-745-8424
업체명업종명소재지단지명종업원수주요생산품전화번호
1013화진철강공업사구조용 금속판제품 및 금속공작물 제조업경상남도 진주시 큰들로 149 (상평동)진주상평지방산업단지1건축잡자재,통신기기부품055-755-2220
1014환덕견직견직물 직조업경상남도 진주시 대곡면 남강로 23023한복지(한복안지)055-745-6640
1015회성정공절삭가공 및 유사처리업경상남도 진주시 큰들로 78 (상평동)2농기계부품(차축)055-753-6788
1016효성산업도장 및 기타 피막처리업경상남도 진주시 대신로147번길 18 (상평동)진주상평지방산업단지22도장055-755-3661
1017효창유리판유리 가공품 제조업경상남도 진주시 솔밭로 28 (상평동)진주상평지방산업단지4거울055-753-1840
1018휴먼바이오텍(주)생물학적 제제 제조업경상남도 진주시 문산읍 월아산로 999-43, 바이오21센터 생산동 201호, 202호2줄기세포 및 배양물055-763-6127
1019흥성공업(주)기어 및 동력전달장치 제조업경상남도 진주시 남강로1367번길 5 (상대동)진주상평지방산업단지14중장비부품055-762-0674
1020흥일기계기어 및 동력전달장치 제조업경상남도 진주시 동진로311번길 12 (상대동)진주상평지방산업단지5기어055-753-3506
1021흥진ENG주형 및 금형 제조업경상남도 진주시 남강로1179번길 10-4 (상평동)4주형(금형)055-752-8614
1022흥한산업(주)토목공사 및 유사용 기계장비 제조업경상남도 진주시 도동로 134 (상대동)진주상평지방산업단지7중장비부품(토목공사및 유사품제조)055-752-7100