Overview

Dataset statistics

Number of variables5
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory46.3 B

Variable types

Numeric1
Text4

Dataset

Description경상남도내 고용우수기업 현황에 대한 데이터입니다. 기업체명, 기업의 소재지, 기업의 주생산품 데이터를 포함하고 있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15015560

Alerts

연번 has unique valuesUnique
기업체명 has unique valuesUnique
대표자 has unique valuesUnique
주생산품 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:27:53.242521
Analysis finished2023-12-11 00:27:53.694731
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T09:27:53.748747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2023-12-11T09:27:53.854040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 1
 
4.0%
2 1
 
4.0%
25 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 1
4.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
25 1
4.0%
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%

기업체명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T09:27:54.031926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.44
Min length3

Characters and Unicode

Total characters136
Distinct characters77
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row㈜성우하이텍
2nd row㈜화승알앤에이
3rd row주식회사 칸
4th row쿠쿠전자㈜
5th row㈜디티알
ValueCountFrequency (%)
㈜성우하이텍 1
 
3.8%
㈜화승알앤에이 1
 
3.8%
삼양화학산업㈜ 1
 
3.8%
㈜에이피씨 1
 
3.8%
상우정공㈜ 1
 
3.8%
㈜한진산업 1
 
3.8%
태영산업㈜ 1
 
3.8%
동이공업㈜ 1
 
3.8%
원창포장공업㈜ 1
 
3.8%
㈜이래cs 1
 
3.8%
Other values (16) 16
61.5%
2023-12-11T09:27:54.340776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
 
16.2%
7
 
5.1%
6
 
4.4%
5
 
3.7%
3
 
2.2%
3
 
2.2%
3
 
2.2%
2
 
1.5%
2
 
1.5%
2
 
1.5%
Other values (67) 81
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107
78.7%
Other Symbol 22
 
16.2%
Uppercase Letter 4
 
2.9%
Open Punctuation 1
 
0.7%
Close Punctuation 1
 
0.7%
Space Separator 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7
 
6.5%
6
 
5.6%
5
 
4.7%
3
 
2.8%
3
 
2.8%
3
 
2.8%
2
 
1.9%
2
 
1.9%
2
 
1.9%
2
 
1.9%
Other values (60) 72
67.3%
Uppercase Letter
ValueCountFrequency (%)
S 2
50.0%
C 1
25.0%
G 1
25.0%
Other Symbol
ValueCountFrequency (%)
22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129
94.9%
Latin 4
 
2.9%
Common 3
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
22
 
17.1%
7
 
5.4%
6
 
4.7%
5
 
3.9%
3
 
2.3%
3
 
2.3%
3
 
2.3%
2
 
1.6%
2
 
1.6%
2
 
1.6%
Other values (61) 74
57.4%
Latin
ValueCountFrequency (%)
S 2
50.0%
C 1
25.0%
G 1
25.0%
Common
ValueCountFrequency (%)
( 1
33.3%
) 1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107
78.7%
None 22
 
16.2%
ASCII 7
 
5.1%

Most frequent character per block

None
ValueCountFrequency (%)
22
100.0%
Hangul
ValueCountFrequency (%)
7
 
6.5%
6
 
5.6%
5
 
4.7%
3
 
2.8%
3
 
2.8%
3
 
2.8%
2
 
1.9%
2
 
1.9%
2
 
1.9%
2
 
1.9%
Other values (60) 72
67.3%
ASCII
ValueCountFrequency (%)
S 2
28.6%
C 1
14.3%
( 1
14.3%
) 1
14.3%
1
14.3%
G 1
14.3%

대표자
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T09:27:54.517396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters75
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row김태일
2nd row백대현
3rd row현장환
4th row구본학
5th row김만수
ValueCountFrequency (%)
김태일 1
 
4.0%
박지삼 1
 
4.0%
박상준 1
 
4.0%
이상국 1
 
4.0%
정혜련 1
 
4.0%
윤영술 1
 
4.0%
진윤숙 1
 
4.0%
김종균 1
 
4.0%
성영화 1
 
4.0%
김용중 1
 
4.0%
Other values (15) 15
60.0%
2023-12-11T09:27:54.808464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
8.0%
3
 
4.0%
3
 
4.0%
3
 
4.0%
3
 
4.0%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
Other values (44) 47
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
8.0%
3
 
4.0%
3
 
4.0%
3
 
4.0%
3
 
4.0%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
Other values (44) 47
62.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
 
8.0%
3
 
4.0%
3
 
4.0%
3
 
4.0%
3
 
4.0%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
Other values (44) 47
62.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6
 
8.0%
3
 
4.0%
3
 
4.0%
3
 
4.0%
3
 
4.0%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
Other values (44) 47
62.7%
Distinct16
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T09:27:54.977108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length7.08
Min length6

Characters and Unicode

Total characters177
Distinct characters42
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)48.0%

Sample

1st row양산시 소주동
2nd row양산시 교동
3rd row거제시 아주동
4th row양산시 교동
5th row진주시 이반성면
ValueCountFrequency (%)
창원시 7
14.0%
양산시 6
12.0%
김해시 5
 
10.0%
주촌면 4
 
8.0%
교동 3
 
6.0%
의창구 3
 
6.0%
성산구 3
 
6.0%
진주시 3
 
6.0%
창녕군 2
 
4.0%
진영읍 1
 
2.0%
Other values (13) 13
26.0%
2023-12-11T09:27:55.259146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
14.1%
23
 
13.0%
12
 
6.8%
11
 
6.2%
9
 
5.1%
8
 
4.5%
8
 
4.5%
7
 
4.0%
7
 
4.0%
7
 
4.0%
Other values (32) 60
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151
85.3%
Space Separator 25
 
14.1%
Decimal Number 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
23
15.2%
12
 
7.9%
11
 
7.3%
9
 
6.0%
8
 
5.3%
8
 
5.3%
7
 
4.6%
7
 
4.6%
7
 
4.6%
6
 
4.0%
Other values (30) 53
35.1%
Space Separator
ValueCountFrequency (%)
25
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151
85.3%
Common 26
 
14.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
23
15.2%
12
 
7.9%
11
 
7.3%
9
 
6.0%
8
 
5.3%
8
 
5.3%
7
 
4.6%
7
 
4.6%
7
 
4.6%
6
 
4.0%
Other values (30) 53
35.1%
Common
ValueCountFrequency (%)
25
96.2%
2 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151
85.3%
ASCII 26
 
14.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
96.2%
2 1
 
3.8%
Hangul
ValueCountFrequency (%)
23
15.2%
12
 
7.9%
11
 
7.3%
9
 
6.0%
8
 
5.3%
8
 
5.3%
7
 
4.6%
7
 
4.6%
7
 
4.6%
6
 
4.0%
Other values (30) 53
35.1%

주생산품
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T09:27:55.458732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8
Min length4

Characters and Unicode

Total characters200
Distinct characters93
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

Unique25 ?
Unique (%)100.0%

Sample

1st row자동차차체부품
2nd row자동차 브레이크호스
3rd row해양플랜트관련 엔지니어링
4th row전기압력밥솥
5th row자동차부품(방진고무)
ValueCountFrequency (%)
자동차 3
 
6.8%
3
 
6.8%
부품 2
 
4.5%
중장비 2
 
4.5%
조선기자재 2
 
4.5%
자동차차체부품 1
 
2.3%
선박용 1
 
2.3%
차체 1
 
2.3%
골판지 1
 
2.3%
제조 1
 
2.3%
Other values (27) 27
61.4%
2023-12-11T09:27:55.761387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
9.5%
10
 
5.0%
9
 
4.5%
8
 
4.0%
8
 
4.0%
7
 
3.5%
7
 
3.5%
5
 
2.5%
4
 
2.0%
4
 
2.0%
Other values (83) 119
59.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167
83.5%
Space Separator 19
 
9.5%
Other Punctuation 5
 
2.5%
Uppercase Letter 5
 
2.5%
Close Punctuation 2
 
1.0%
Open Punctuation 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10
 
6.0%
9
 
5.4%
8
 
4.8%
8
 
4.8%
7
 
4.2%
7
 
4.2%
5
 
3.0%
4
 
2.4%
4
 
2.4%
4
 
2.4%
Other values (73) 101
60.5%
Uppercase Letter
ValueCountFrequency (%)
N 1
20.0%
F 1
20.0%
A 1
20.0%
C 1
20.0%
R 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
/ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 167
83.5%
Common 28
 
14.0%
Latin 5
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10
 
6.0%
9
 
5.4%
8
 
4.8%
8
 
4.8%
7
 
4.2%
7
 
4.2%
5
 
3.0%
4
 
2.4%
4
 
2.4%
4
 
2.4%
Other values (73) 101
60.5%
Common
ValueCountFrequency (%)
19
67.9%
, 4
 
14.3%
) 2
 
7.1%
( 2
 
7.1%
/ 1
 
3.6%
Latin
ValueCountFrequency (%)
N 1
20.0%
F 1
20.0%
A 1
20.0%
C 1
20.0%
R 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 167
83.5%
ASCII 33
 
16.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
57.6%
, 4
 
12.1%
) 2
 
6.1%
( 2
 
6.1%
N 1
 
3.0%
F 1
 
3.0%
A 1
 
3.0%
C 1
 
3.0%
/ 1
 
3.0%
R 1
 
3.0%
Hangul
ValueCountFrequency (%)
10
 
6.0%
9
 
5.4%
8
 
4.8%
8
 
4.8%
7
 
4.2%
7
 
4.2%
5
 
3.0%
4
 
2.4%
4
 
2.4%
4
 
2.4%
Other values (73) 101
60.5%

Interactions