Overview

Dataset statistics

Number of variables5
Number of observations856
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.4 KiB
Average record size in memory41.2 B

Variable types

Numeric1
Categorical2
Text2

Dataset

Description2023년 7월 26일 기준 지방출자출연기관 설립 현황에 대한 데이터로 설립 지역, 기관, 운영구분, 유형, 기관 명칭을 제공합니다.
Author행정안전부 지방공기업평가원
URLhttps://www.data.go.kr/data/15048281/fileData.do

Alerts

연번 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 연번High correlation
시도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
기관명 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:05:08.526995
Analysis finished2023-12-13 00:05:08.993076
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct856
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean428.5
Minimum1
Maximum856
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2023-12-13T09:05:09.054016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile43.75
Q1214.75
median428.5
Q3642.25
95-th percentile813.25
Maximum856
Range855
Interquartile range (IQR)427.5

Descriptive statistics

Standard deviation247.25021
Coefficient of variation (CV)0.57701333
Kurtosis-1.2
Mean428.5
Median Absolute Deviation (MAD)214
Skewness0
Sum366796
Variance61132.667
MonotonicityStrictly increasing
2023-12-13T09:05:09.163841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
564 1
 
0.1%
566 1
 
0.1%
567 1
 
0.1%
568 1
 
0.1%
569 1
 
0.1%
570 1
 
0.1%
571 1
 
0.1%
572 1
 
0.1%
573 1
 
0.1%
Other values (846) 846
98.8%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
856 1
0.1%
855 1
0.1%
854 1
0.1%
853 1
0.1%
852 1
0.1%
851 1
0.1%
850 1
0.1%
849 1
0.1%
848 1
0.1%
847 1
0.1%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
출연기관
757 
출자기관
99 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
출연기관 757
88.4%
출자기관 99
 
11.6%

Length

2023-12-13T09:05:09.259253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:05:09.336292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
출연기관 757
88.4%
출자기관 99
 
11.6%

시도
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
경기도
150 
강원도
87 
전라남도
83 
경상북도
73 
경상남도
70 
Other values (12)
393 

Length

Max length7
Median length5
Mean length4.0373832
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 150
17.5%
강원도 87
10.2%
전라남도 83
9.7%
경상북도 73
8.5%
경상남도 70
8.2%
서울특별시 68
7.9%
충청남도 68
7.9%
전라북도 60
 
7.0%
충청북도 40
 
4.7%
부산광역시 32
 
3.7%
Other values (7) 125
14.6%

Length

2023-12-13T09:05:09.425464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 150
17.5%
강원도 87
10.2%
전라남도 83
9.7%
경상북도 73
8.5%
경상남도 70
8.2%
서울특별시 68
7.9%
충청남도 68
7.9%
전라북도 60
 
7.0%
충청북도 40
 
4.7%
부산광역시 32
 
3.7%
Other values (7) 125
14.6%

시군구
Text

Distinct197
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2023-12-13T09:05:09.696907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length2.6705607
Min length2

Characters and Unicode

Total characters2286
Distinct characters127
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)5.6%

Sample

1st row성동구
2nd row노원구
3rd row금천구
4th row동작구
5th row서초구
ValueCountFrequency (%)
본청 285
33.3%
춘천시 10
 
1.2%
목포시 10
 
1.2%
창원시 9
 
1.1%
화성시 8
 
0.9%
용인시 8
 
0.9%
수원시 8
 
0.9%
의정부시 7
 
0.8%
순천시 7
 
0.8%
전주시 7
 
0.8%
Other values (187) 497
58.1%
2023-12-13T09:05:10.093921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 310
 
13.6%
청 298
 
13.0%
본 286
 
12.5%
군 185
 
8.1%
구 105
 
4.6%
천 71
 
3.1%
주 59
 
2.6%
양 48
 
2.1%
산 46
 
2.0%
성 45
 
2.0%
Other values (117) 833
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2282
99.8%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 310
 
13.6%
청 298
 
13.1%
본 286
 
12.5%
군 185
 
8.1%
구 105
 
4.6%
천 71
 
3.1%
주 59
 
2.6%
양 48
 
2.1%
산 46
 
2.0%
성 45
 
2.0%
Other values (116) 829
36.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2282
99.8%
Common 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 310
 
13.6%
청 298
 
13.1%
본 286
 
12.5%
군 185
 
8.1%
구 105
 
4.6%
천 71
 
3.1%
주 59
 
2.6%
양 48
 
2.1%
산 46
 
2.0%
성 45
 
2.0%
Other values (116) 829
36.3%
Common
ValueCountFrequency (%)
, 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2282
99.8%
ASCII 4
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 310
 
13.6%
청 298
 
13.1%
본 286
 
12.5%
군 185
 
8.1%
구 105
 
4.6%
천 71
 
3.1%
주 59
 
2.6%
양 48
 
2.1%
산 46
 
2.0%
성 45
 
2.0%
Other values (116) 829
36.3%
ASCII
ValueCountFrequency (%)
, 4
100.0%

기관명
Text

UNIQUE 

Distinct856
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2023-12-13T09:05:10.341831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length21
Mean length10.628505
Min length3

Characters and Unicode

Total characters9098
Distinct characters362
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique856 ?
Unique (%)100.0%

Sample

1st row성동미래일자리㈜
2nd row노원어르신행복주식회사
3rd row금천일자리 주식회사
4th row대한민국동작 주식회사
5th row서초여성일자리주식회사
ValueCountFrequency (%)
재단법인 215
 
18.8%
주식회사 26
 
2.3%
사회서비스원 9
 
0.8%
경상남도 4
 
0.3%
광주광역시 3
 
0.3%
충청북도 2
 
0.2%
울산광역시 2
 
0.2%
농업회사법인 2
 
0.2%
조직위원회 2
 
0.2%
관광재단 2
 
0.2%
Other values (873) 877
76.7%
2023-12-13T09:05:10.688565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
876
 
9.6%
재 672
 
7.4%
단 631
 
6.9%
인 318
 
3.5%
원 275
 
3.0%
법 229
 
2.5%
화 201
 
2.2%
시 172
 
1.9%
회 169
 
1.9%
문 165
 
1.8%
Other values (352) 5390
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8085
88.9%
Space Separator 876
 
9.6%
Close Punctuation 35
 
0.4%
Other Symbol 35
 
0.4%
Open Punctuation 35
 
0.4%
Decimal Number 21
 
0.2%
Uppercase Letter 10
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
재 672
 
8.3%
단 631
 
7.8%
인 318
 
3.9%
원 275
 
3.4%
법 229
 
2.8%
화 201
 
2.5%
시 172
 
2.1%
회 169
 
2.1%
문 165
 
2.0%
산 160
 
2.0%
Other values (332) 5093
63.0%
Decimal Number
ValueCountFrequency (%)
2 6
28.6%
0 6
28.6%
1 3
14.3%
4 2
 
9.5%
8 1
 
4.8%
6 1
 
4.8%
5 1
 
4.8%
3 1
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
C 4
40.0%
I 1
 
10.0%
T 1
 
10.0%
F 1
 
10.0%
G 1
 
10.0%
L 1
 
10.0%
U 1
 
10.0%
Space Separator
ValueCountFrequency (%)
876
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8120
89.3%
Common 968
 
10.6%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
재 672
 
8.3%
단 631
 
7.8%
인 318
 
3.9%
원 275
 
3.4%
법 229
 
2.8%
화 201
 
2.5%
시 172
 
2.1%
회 169
 
2.1%
문 165
 
2.0%
산 160
 
2.0%
Other values (333) 5128
63.2%
Common
ValueCountFrequency (%)
876
90.5%
) 35
 
3.6%
( 35
 
3.6%
2 6
 
0.6%
0 6
 
0.6%
1 3
 
0.3%
4 2
 
0.2%
· 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
Other values (2) 2
 
0.2%
Latin
ValueCountFrequency (%)
C 4
40.0%
I 1
 
10.0%
T 1
 
10.0%
F 1
 
10.0%
G 1
 
10.0%
L 1
 
10.0%
U 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8085
88.9%
ASCII 977
 
10.7%
None 36
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
876
89.7%
) 35
 
3.6%
( 35
 
3.6%
2 6
 
0.6%
0 6
 
0.6%
C 4
 
0.4%
1 3
 
0.3%
4 2
 
0.2%
I 1
 
0.1%
T 1
 
0.1%
Other values (8) 8
 
0.8%
Hangul
ValueCountFrequency (%)
재 672
 
8.3%
단 631
 
7.8%
인 318
 
3.9%
원 275
 
3.4%
법 229
 
2.8%
화 201
 
2.5%
시 172
 
2.1%
회 169
 
2.1%
문 165
 
2.0%
산 160
 
2.0%
Other values (332) 5093
63.0%
None
ValueCountFrequency (%)
㈜ 35
97.2%
· 1
 
2.8%

Interactions

2023-12-13T09:05:08.799383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:05:10.774215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분시도
연번1.0000.9940.945
구분0.9941.0000.138
시도0.9450.1381.000
2023-12-13T09:05:10.847432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시도
구분1.0000.123
시도0.1231.000
2023-12-13T09:05:10.917542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분시도
연번1.0000.9300.764
구분0.9301.0000.123
시도0.7640.1231.000

Missing values

2023-12-13T09:05:08.887195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:05:08.960196image/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

연번구분시도시군구기관명
01출자기관서울특별시성동구성동미래일자리㈜
12출자기관서울특별시노원구노원어르신행복주식회사
23출자기관서울특별시금천구금천일자리 주식회사
34출자기관서울특별시동작구대한민국동작 주식회사
45출자기관서울특별시서초구서초여성일자리주식회사
56출자기관부산광역시본청㈜벡스코
67출자기관부산광역시본청아시아드CC㈜
78출자기관대구광역시본청㈜엑스코
89출자기관인천광역시본청인천스마트시티㈜
910출자기관인천광역시본청인천투자펀드
연번구분시도시군구기관명
846847출연기관제주특별자치도본청제주문화예술재단
847848출연기관제주특별자치도본청제주연구원
848849출연기관제주특별자치도본청제주신용보증재단
849850출연기관제주특별자치도본청제주테크노파크
850851출연기관제주특별자치도본청제주특별자치도경제통상진흥원
851852출연기관제주특별자치도본청제주여성가족연구원
852853출연기관제주특별자치도본청제주43평화재단
853854출연기관제주특별자치도본청제주한의약연구원
854855출연기관제주특별자치도본청제주영상·문화산업진흥원
855856출연기관제주특별자치도본청재단법인 제주특별자치도 사회서비스원