Overview

Dataset statistics

Number of variables8
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory68.6 B

Variable types

Numeric2
Text5
Categorical1

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

Alerts

단지명 has constant value ""Constant
순번 has unique valuesUnique
회사명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:47:06.185295
Analysis finished2023-12-11 00:47:07.268424
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-11T09:47:07.355370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly increasing
2023-12-11T09:47:07.520098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
2 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%

회사명
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T09:47:07.762274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.1960784
Min length3

Characters and Unicode

Total characters367
Distinct characters113
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row(주)SM TECH
2nd row(주)경민산업
3rd row(주)대경열처리 진주지점
4th row(주)대산금속 사봉공장
5th row(주)메카티엔에스
ValueCountFrequency (%)
사봉공장 4
 
6.8%
주)신흥기업 2
 
3.4%
주)sm 1
 
1.7%
다인테크 1
 
1.7%
대림산업 1
 
1.7%
3공장 1
 
1.7%
대림산업2공장 1
 
1.7%
동일단조 1
 
1.7%
디엠아이(주 1
 
1.7%
삼성개발 1
 
1.7%
Other values (45) 45
76.3%
2023-12-11T09:47:08.172340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 34
 
9.3%
( 31
 
8.4%
) 31
 
8.4%
공 14
 
3.8%
장 11
 
3.0%
이 10
 
2.7%
신 10
 
2.7%
업 9
 
2.5%
산 8
 
2.2%
8
 
2.2%
Other values (103) 201
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 279
76.0%
Open Punctuation 31
 
8.4%
Close Punctuation 31
 
8.4%
Uppercase Letter 12
 
3.3%
Space Separator 8
 
2.2%
Decimal Number 6
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 34
 
12.2%
공 14
 
5.0%
장 11
 
3.9%
이 10
 
3.6%
신 10
 
3.6%
업 9
 
3.2%
산 8
 
2.9%
테 6
 
2.2%
대 6
 
2.2%
크 6
 
2.2%
Other values (89) 165
59.1%
Uppercase Letter
ValueCountFrequency (%)
M 3
25.0%
S 2
16.7%
T 2
16.7%
E 1
 
8.3%
C 1
 
8.3%
H 1
 
8.3%
K 1
 
8.3%
P 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 4
66.7%
3 1
 
16.7%
4 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 279
76.0%
Common 76
 
20.7%
Latin 12
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 34
 
12.2%
공 14
 
5.0%
장 11
 
3.9%
이 10
 
3.6%
신 10
 
3.6%
업 9
 
3.2%
산 8
 
2.9%
테 6
 
2.2%
대 6
 
2.2%
크 6
 
2.2%
Other values (89) 165
59.1%
Latin
ValueCountFrequency (%)
M 3
25.0%
S 2
16.7%
T 2
16.7%
E 1
 
8.3%
C 1
 
8.3%
H 1
 
8.3%
K 1
 
8.3%
P 1
 
8.3%
Common
ValueCountFrequency (%)
( 31
40.8%
) 31
40.8%
8
 
10.5%
2 4
 
5.3%
3 1
 
1.3%
4 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 279
76.0%
ASCII 88
 
24.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 34
 
12.2%
공 14
 
5.0%
장 11
 
3.9%
이 10
 
3.6%
신 10
 
3.6%
업 9
 
3.2%
산 8
 
2.9%
테 6
 
2.2%
대 6
 
2.2%
크 6
 
2.2%
Other values (89) 165
59.1%
ASCII
ValueCountFrequency (%)
( 31
35.2%
) 31
35.2%
8
 
9.1%
2 4
 
4.5%
M 3
 
3.4%
S 2
 
2.3%
T 2
 
2.3%
E 1
 
1.1%
C 1
 
1.1%
H 1
 
1.1%
Other values (4) 4
 
4.5%

단지명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
진주일반산업단지
51 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진주일반산업단지 51
100.0%

Length

2023-12-11T09:47:08.301194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:47:08.408597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진주일반산업단지 51
100.0%

전화번호
Text

Distinct45
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T09:47:08.634519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.019608
Min length12

Characters and Unicode

Total characters613
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

Unique41 ?
Unique (%)80.4%

Sample

1st row055-757-1484
2nd row055-761-0760
3rd row055-752-1746
4th row055-757-0966
5th row055-921-7701
ValueCountFrequency (%)
055-748-8520 3
 
5.9%
055-758-1546 3
 
5.9%
055-758-8030 2
 
3.9%
055-763-7842 2
 
3.9%
055-256-7622 1
 
2.0%
055-854-8490 1
 
2.0%
055-757-1484 1
 
2.0%
055-757-9827 1
 
2.0%
055-760-5583 1
 
2.0%
055-761-9936 1
 
2.0%
Other values (35) 35
68.6%
2023-12-11T09:47:09.365195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 145
23.7%
- 102
16.6%
0 83
13.5%
7 78
12.7%
6 41
 
6.7%
1 34
 
5.5%
8 33
 
5.4%
4 30
 
4.9%
2 27
 
4.4%
3 24
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 511
83.4%
Dash Punctuation 102
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 145
28.4%
0 83
16.2%
7 78
15.3%
6 41
 
8.0%
1 34
 
6.7%
8 33
 
6.5%
4 30
 
5.9%
2 27
 
5.3%
3 24
 
4.7%
9 16
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 613
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 145
23.7%
- 102
16.6%
0 83
13.5%
7 78
12.7%
6 41
 
6.7%
1 34
 
5.5%
8 33
 
5.4%
4 30
 
4.9%
2 27
 
4.4%
3 24
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 613
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 145
23.7%
- 102
16.6%
0 83
13.5%
7 78
12.7%
6 41
 
6.7%
1 34
 
5.5%
8 33
 
5.4%
4 30
 
4.9%
2 27
 
4.4%
3 24
 
3.9%

종업원수
Real number (ℝ)

Distinct27
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.568627
Minimum2
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-11T09:47:09.513602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.5
Q17
median11
Q320.5
95-th percentile38
Maximum49
Range47
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation11.727327
Coefficient of variation (CV)0.75326659
Kurtosis0.37836066
Mean15.568627
Median Absolute Deviation (MAD)6
Skewness1.0898096
Sum794
Variance137.5302
MonotonicityNot monotonic
2023-12-11T09:47:09.634960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
7 6
 
11.8%
10 5
 
9.8%
20 3
 
5.9%
2 3
 
5.9%
4 2
 
3.9%
8 2
 
3.9%
5 2
 
3.9%
15 2
 
3.9%
9 2
 
3.9%
6 2
 
3.9%
Other values (17) 22
43.1%
ValueCountFrequency (%)
2 3
5.9%
3 1
 
2.0%
4 2
 
3.9%
5 2
 
3.9%
6 2
 
3.9%
7 6
11.8%
8 2
 
3.9%
9 2
 
3.9%
10 5
9.8%
11 1
 
2.0%
ValueCountFrequency (%)
49 1
2.0%
41 1
2.0%
40 1
2.0%
36 2
3.9%
35 1
2.0%
33 2
3.9%
28 1
2.0%
25 1
2.0%
24 1
2.0%
21 2
3.9%

생산품
Text

Distinct50
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T09:47:09.893927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length14
Mean length9.7058824
Min length2

Characters and Unicode

Total characters495
Distinct characters153
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)96.1%

Sample

1st row자동차중장비부품(금형)
2nd row철구조물,흙막이용 주열벽구조체
3rd row열처리품
4th row허브베어링,디퍼케이스
5th row산업용로봇, 공장자동화시스템
ValueCountFrequency (%)
및 5
 
5.4%
자동차 3
 
3.3%
등 3
 
3.3%
금속구조물 2
 
2.2%
밸브 2
 
2.2%
베어링 2
 
2.2%
부품 2
 
2.2%
중장비,유압,구조금속제품 1
 
1.1%
구조물 1
 
1.1%
조명기구 1
 
1.1%
Other values (70) 70
76.1%
2023-12-11T09:47:10.371315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41
 
8.3%
, 29
 
5.9%
품 23
 
4.6%
부 18
 
3.6%
기 15
 
3.0%
동 12
 
2.4%
차 11
 
2.2%
조 11
 
2.2%
자 11
 
2.2%
스 11
 
2.2%
Other values (143) 313
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 403
81.4%
Space Separator 41
 
8.3%
Other Punctuation 29
 
5.9%
Uppercase Letter 10
 
2.0%
Open Punctuation 6
 
1.2%
Close Punctuation 6
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 23
 
5.7%
부 18
 
4.5%
기 15
 
3.7%
동 12
 
3.0%
차 11
 
2.7%
조 11
 
2.7%
자 11
 
2.7%
스 11
 
2.7%
장 9
 
2.2%
이 9
 
2.2%
Other values (130) 273
67.7%
Uppercase Letter
ValueCountFrequency (%)
S 2
20.0%
P 1
10.0%
C 1
10.0%
B 1
10.0%
L 1
10.0%
E 1
10.0%
D 1
10.0%
A 1
10.0%
Y 1
10.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 403
81.4%
Common 82
 
16.6%
Latin 10
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 23
 
5.7%
부 18
 
4.5%
기 15
 
3.7%
동 12
 
3.0%
차 11
 
2.7%
조 11
 
2.7%
자 11
 
2.7%
스 11
 
2.7%
장 9
 
2.2%
이 9
 
2.2%
Other values (130) 273
67.7%
Latin
ValueCountFrequency (%)
S 2
20.0%
P 1
10.0%
C 1
10.0%
B 1
10.0%
L 1
10.0%
E 1
10.0%
D 1
10.0%
A 1
10.0%
Y 1
10.0%
Common
ValueCountFrequency (%)
41
50.0%
, 29
35.4%
( 6
 
7.3%
) 6
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 403
81.4%
ASCII 92
 
18.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41
44.6%
, 29
31.5%
( 6
 
6.5%
) 6
 
6.5%
S 2
 
2.2%
P 1
 
1.1%
C 1
 
1.1%
B 1
 
1.1%
L 1
 
1.1%
E 1
 
1.1%
Other values (3) 3
 
3.3%
Hangul
ValueCountFrequency (%)
품 23
 
5.7%
부 18
 
4.5%
기 15
 
3.7%
동 12
 
3.0%
차 11
 
2.7%
조 11
 
2.7%
자 11
 
2.7%
스 11
 
2.7%
장 9
 
2.2%
이 9
 
2.2%
Other values (130) 273
67.7%

공장대표주소
Text

Distinct50
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T09:47:10.578091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length59
Mean length31.843137
Min length21

Characters and Unicode

Total characters1624
Distinct characters66
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)96.1%

Sample

1st row경상남도 진주시 사봉면 산업단지로44번길 22
2nd row경상남도 진주시 사봉면 산업단지로43번길 39 (총 2 필지)
3rd row경상남도 진주시 사봉면 산업단지로44번길 50
4th row경상남도 진주시 사봉면 사곡리 1850-4번지
5th row경상남도 진주시 사봉면 산업단지로44번길 41-76
ValueCountFrequency (%)
사봉면 58
17.5%
경상남도 51
15.4%
진주시 51
15.4%
산업단지로44번길 28
 
8.4%
사곡리 17
 
5.1%
총 12
 
3.6%
필지 12
 
3.6%
2 8
 
2.4%
산업단지로 8
 
2.4%
공장 7
 
2.1%
Other values (71) 80
24.1%
2023-12-11T09:47:10.913304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
281
 
17.3%
4 83
 
5.1%
사 76
 
4.7%
지 65
 
4.0%
1 62
 
3.8%
면 58
 
3.6%
봉 58
 
3.6%
주 56
 
3.4%
경 52
 
3.2%
시 51
 
3.1%
Other values (56) 782
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 970
59.7%
Space Separator 281
 
17.3%
Decimal Number 281
 
17.3%
Dash Punctuation 33
 
2.0%
Open Punctuation 32
 
2.0%
Close Punctuation 27
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 76
 
7.8%
지 65
 
6.7%
면 58
 
6.0%
봉 58
 
6.0%
주 56
 
5.8%
경 52
 
5.4%
시 51
 
5.3%
도 51
 
5.3%
상 51
 
5.3%
진 51
 
5.3%
Other values (42) 401
41.3%
Decimal Number
ValueCountFrequency (%)
4 83
29.5%
1 62
22.1%
2 27
 
9.6%
8 23
 
8.2%
5 20
 
7.1%
0 19
 
6.8%
6 16
 
5.7%
3 14
 
5.0%
7 10
 
3.6%
9 7
 
2.5%
Space Separator
ValueCountFrequency (%)
281
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 970
59.7%
Common 654
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 76
 
7.8%
지 65
 
6.7%
면 58
 
6.0%
봉 58
 
6.0%
주 56
 
5.8%
경 52
 
5.4%
시 51
 
5.3%
도 51
 
5.3%
상 51
 
5.3%
진 51
 
5.3%
Other values (42) 401
41.3%
Common
ValueCountFrequency (%)
281
43.0%
4 83
 
12.7%
1 62
 
9.5%
- 33
 
5.0%
( 32
 
4.9%
2 27
 
4.1%
) 27
 
4.1%
8 23
 
3.5%
5 20
 
3.1%
0 19
 
2.9%
Other values (4) 47
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 970
59.7%
ASCII 654
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
281
43.0%
4 83
 
12.7%
1 62
 
9.5%
- 33
 
5.0%
( 32
 
4.9%
2 27
 
4.1%
) 27
 
4.1%
8 23
 
3.5%
5 20
 
3.1%
0 19
 
2.9%
Other values (4) 47
 
7.2%
Hangul
ValueCountFrequency (%)
사 76
 
7.8%
지 65
 
6.7%
면 58
 
6.0%
봉 58
 
6.0%
주 56
 
5.8%
경 52
 
5.4%
시 51
 
5.3%
도 51
 
5.3%
상 51
 
5.3%
진 51
 
5.3%
Other values (42) 401
41.3%

업종명
Text

Distinct35
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T09:47:11.200755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length16.862745
Min length6

Characters and Unicode

Total characters860
Distinct characters113
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)49.0%

Sample

1st row주형 및 금형 제조업
2nd row육상 금속 골조 구조재 제조업 외 1 종
3rd row금속 열처리업
4th row자동차용 신품 동력전달장치 제조업 외 1 종
5th row산업용 로봇 제조업
ValueCountFrequency (%)
제조업 43
 
15.9%
및 24
 
8.9%
외 23
 
8.5%
종 20
 
7.4%
1 16
 
5.9%
금속 11
 
4.1%
신품 7
 
2.6%
절삭가공 5
 
1.8%
유사처리업 5
 
1.8%
자동차용 5
 
1.8%
Other values (73) 112
41.3%
2023-12-11T09:47:11.653109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
220
25.6%
업 55
 
6.4%
조 54
 
6.3%
제 54
 
6.3%
및 24
 
2.8%
외 23
 
2.7%
품 23
 
2.7%
종 20
 
2.3%
용 19
 
2.2%
기 17
 
2.0%
Other values (103) 351
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 615
71.5%
Space Separator 220
 
25.6%
Decimal Number 21
 
2.4%
Other Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 55
 
8.9%
조 54
 
8.8%
제 54
 
8.8%
및 24
 
3.9%
외 23
 
3.7%
품 23
 
3.7%
종 20
 
3.3%
용 19
 
3.1%
기 17
 
2.8%
금 17
 
2.8%
Other values (97) 309
50.2%
Decimal Number
ValueCountFrequency (%)
1 17
81.0%
5 2
 
9.5%
3 1
 
4.8%
4 1
 
4.8%
Space Separator
ValueCountFrequency (%)
220
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 615
71.5%
Common 245
 
28.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 55
 
8.9%
조 54
 
8.8%
제 54
 
8.8%
및 24
 
3.9%
외 23
 
3.7%
품 23
 
3.7%
종 20
 
3.3%
용 19
 
3.1%
기 17
 
2.8%
금 17
 
2.8%
Other values (97) 309
50.2%
Common
ValueCountFrequency (%)
220
89.8%
1 17
 
6.9%
, 4
 
1.6%
5 2
 
0.8%
3 1
 
0.4%
4 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 615
71.5%
ASCII 245
 
28.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
220
89.8%
1 17
 
6.9%
, 4
 
1.6%
5 2
 
0.8%
3 1
 
0.4%
4 1
 
0.4%
Hangul
ValueCountFrequency (%)
업 55
 
8.9%
조 54
 
8.8%
제 54
 
8.8%
및 24
 
3.9%
외 23
 
3.7%
품 23
 
3.7%
종 20
 
3.3%
용 19
 
3.1%
기 17
 
2.8%
금 17
 
2.8%
Other values (97) 309
50.2%

Interactions

2023-12-11T09:47:06.834111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:47:06.680333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:47:06.916478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:47:06.755994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:47:11.781191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번회사명전화번호종업원수생산품공장대표주소업종명
순번1.0001.0000.9400.0000.9450.9450.671
회사명1.0001.0001.0001.0001.0001.0001.000
전화번호0.9401.0001.0000.9511.0001.0000.972
종업원수0.0001.0000.9511.0000.9930.9930.000
생산품0.9451.0001.0000.9931.0001.0001.000
공장대표주소0.9451.0001.0000.9931.0001.0001.000
업종명0.6711.0000.9720.0001.0001.0001.000
2023-12-11T09:47:11.901288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종업원수
순번1.0000.063
종업원수0.0631.000

Missing values

2023-12-11T09:47:07.052518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:47:07.216558image/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

순번회사명단지명전화번호종업원수생산품공장대표주소업종명
01(주)SM TECH진주일반산업단지055-757-14846자동차중장비부품(금형)경상남도 진주시 사봉면 산업단지로44번길 22주형 및 금형 제조업
12(주)경민산업진주일반산업단지055-761-07607철구조물,흙막이용 주열벽구조체경상남도 진주시 사봉면 산업단지로43번길 39 (총 2 필지)육상 금속 골조 구조재 제조업 외 1 종
23(주)대경열처리 진주지점진주일반산업단지055-752-174612열처리품경상남도 진주시 사봉면 산업단지로44번길 50금속 열처리업
34(주)대산금속 사봉공장진주일반산업단지055-757-096628허브베어링,디퍼케이스경상남도 진주시 사봉면 사곡리 1850-4번지자동차용 신품 동력전달장치 제조업 외 1 종
45(주)메카티엔에스진주일반산업단지055-921-770110산업용로봇, 공장자동화시스템경상남도 진주시 사봉면 산업단지로44번길 41-76산업용 로봇 제조업
56(주)부광플랜진주일반산업단지055-748-85202금속구조물경상남도 진주시 사봉면 산업단지로44번길 41-80구조용 금속 판제품 및 공작물 제조업 외 1 종
67(주)신화진주일반산업단지055-761-865517열간단조품경상남도 진주시 사봉면 사곡리 1821-1번지금속 단조제품 제조업
78(주)신화정공진주일반산업단지055-758-156521농기구,자동차,항공기부품경상남도 진주시 사봉면 산업단지로44번길 51-11 (총 2 필지)절삭가공 및 유사처리업
89(주)신흥 사봉공장진주일반산업단지055-752-651141고무경상남도 진주시 사봉면 산업단지로44번길 66 (총 2 필지)합성고무 제조업
910(주)신흥기업진주일반산업단지055-758-154620유압탱크 및 파이프경상남도 진주시 사봉면 산업단지로27번길 21 (사봉면 사곡리 1801-3 공장 ((주)신흥기업)) (총 3 필지)금속탱크 및 저장용기 제조업 외 1 종
순번회사명단지명전화번호종업원수생산품공장대표주소업종명
4142엠테크진주일반산업단지055-761-71427밸브, 링크경상남도 진주시 사봉면 산업단지로44번길 51-3탭, 밸브 및 유사장치 제조업
4243윈테크진주일반산업단지055-762-67264밸브, 역화방지기경상남도 진주시 사봉면 산업단지로44번길 41-72탭, 밸브 및 유사장치 제조업
4344일광금속제2공장 사봉공장진주일반산업단지055-744-215549자동차 부품경상남도 진주시 사봉면 사곡리 1845-7번지 외 5필지자동차 엔진용 신품 부품 제조업 외 1 종
4445일신정밀진주일반산업단지055-762-481733변속기축경상남도 진주시 사봉면 산업단지로44번길 9자동차용 신품 동력전달장치 제조업 외 1 종
4546하이파워유압(주)진주일반산업단지055-334-361119유압시린다,밸브,펌프경상남도 진주시 사봉면 산업단지로 36유압기기 제조업 외 1 종
4647한경티이씨(주)진주일반산업단지055-311-641036지르코니아화합물(제지첨가제)경상남도 진주시 사봉면 산업단지로44번길 60 (한경티이씨주식회사)무기안료용 금속 산화물 및 관련 제품 제조업
4748한국마그넷(주) 사봉공장진주일반산업단지055-752-139636리어카바, 디프케이스경상남도 진주시 사봉면 산업단지로 85 (사봉면 사곡리 1806-4 공장 (한국마그넷(주) (총 2 필지)자동차 엔진용 신품 부품 제조업 외 1 종
4849한두철강(주)진주공장진주일반산업단지055-761-780125인발강관, 강관열처리제품경상남도 진주시 사봉면 산업단지로44번길 42 (총 3 필지)냉간 압연 및 압출 제품 제조업 외 1 종
4950한성엔지니어링진주일반산업단지055-854-84904플라스크 및 대차경상남도 진주시 사봉면 사곡리 1848번지절삭가공 및 유사처리업
5051호성하이텍진주일반산업단지055-757-747020자동차 부속 부품경상남도 진주시 사봉면 사곡리 1815-1번지 외 1필지그 외 자동차용 신품 부품 제조업 외 4 종