Overview

Dataset statistics

Number of variables8
Number of observations23
Missing cells24
Missing cells (%)13.0%
Duplicate rows1
Duplicate rows (%)4.3%
Total size in memory1.6 KiB
Average record size in memory70.7 B

Variable types

Categorical2
Text4
DateTime1
Numeric1

Dataset

Description충청남도 산하 공공기관(공사공단, 출자출연, 공직유관단체) 현황으로 기관유형, 기관명, 직위, 대표자, 설립일, 우편번호, 주소, 대포전화번호 정보가 포함되어 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=397&beforeMenuCd=DOM_000000201001001000&publicdatapk=15019761

Alerts

Dataset has 1 (4.3%) duplicate rowsDuplicates
기관유형 is highly overall correlated with 직위High correlation
직위 is highly overall correlated with 기관유형High correlation
기관명 has 4 (17.4%) missing valuesMissing
대표자 has 4 (17.4%) missing valuesMissing
설립일 has 4 (17.4%) missing valuesMissing
우편번호 has 4 (17.4%) missing valuesMissing
주소 has 4 (17.4%) missing valuesMissing
대표전화 has 4 (17.4%) missing valuesMissing

Reproduction

Analysis started2024-01-09 22:43:47.767769
Analysis finished2024-01-09 22:43:48.442511
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size316.0 B
출연기관
15 
<NA>
4 
공직유관단체
3 
공기업
 
1

Length

Max length6
Median length4
Mean length4.2173913
Min length3

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row공기업
2nd row출연기관
3rd row출연기관
4th row출연기관
5th row출연기관

Common Values

ValueCountFrequency (%)
출연기관 15
65.2%
<NA> 4
 
17.4%
공직유관단체 3
 
13.0%
공기업 1
 
4.3%

Length

2024-01-10T07:43:48.523018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:43:48.616471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
출연기관 15
65.2%
na 4
 
17.4%
공직유관단체 3
 
13.0%
공기업 1
 
4.3%

기관명
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing4
Missing (%)17.4%
Memory size316.0 B
2024-01-10T07:43:48.770495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.7368421
Min length5

Characters and Unicode

Total characters128
Distinct characters65
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

Unique19 ?
Unique (%)100.0%

Sample

1st row충남개발공사
2nd row천안의료원
3rd row공주의료원
4th row서산의료원
5th row홍성의료원
ValueCountFrequency (%)
천안의료원 1
 
5.3%
역사문화연구원 1
 
5.3%
장애인체육회 1
 
5.3%
충남체육회 1
 
5.3%
교통연수원 1
 
5.3%
백제문화제재단 1
 
5.3%
한국유교문화진흥원 1
 
5.3%
정보문화산업진흥원 1
 
5.3%
문화관광재단 1
 
5.3%
충남개발공사 1
 
5.3%
Other values (9) 9
47.4%
2024-01-10T07:43:49.097638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 12
 
9.4%
화 5
 
3.9%
문 5
 
3.9%
흥 4
 
3.1%
의 4
 
3.1%
료 4
 
3.1%
진 4
 
3.1%
재 4
 
3.1%
육 4
 
3.1%
연 3
 
2.3%
Other values (55) 79
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 12
 
9.4%
화 5
 
3.9%
문 5
 
3.9%
흥 4
 
3.1%
의 4
 
3.1%
료 4
 
3.1%
진 4
 
3.1%
재 4
 
3.1%
육 4
 
3.1%
연 3
 
2.3%
Other values (55) 79
61.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 128
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 12
 
9.4%
화 5
 
3.9%
문 5
 
3.9%
흥 4
 
3.1%
의 4
 
3.1%
료 4
 
3.1%
진 4
 
3.1%
재 4
 
3.1%
육 4
 
3.1%
연 3
 
2.3%
Other values (55) 79
61.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 128
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 12
 
9.4%
화 5
 
3.9%
문 5
 
3.9%
흥 4
 
3.1%
의 4
 
3.1%
료 4
 
3.1%
진 4
 
3.1%
재 4
 
3.1%
육 4
 
3.1%
연 3
 
2.3%
Other values (55) 79
61.7%

직위
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Memory size316.0 B
원장
13 
<NA>
4 
대표이사
2 
사장
 
1
이사장
 
1
Other values (2)
2 

Length

Max length4
Median length2
Mean length2.6521739
Min length2

Unique

Unique4 ?
Unique (%)17.4%

Sample

1st row사장
2nd row원장
3rd row원장
4th row원장
5th row원장

Common Values

ValueCountFrequency (%)
원장 13
56.5%
<NA> 4
 
17.4%
대표이사 2
 
8.7%
사장 1
 
4.3%
이사장 1
 
4.3%
회장 1
 
4.3%
사무처장 1
 
4.3%

Length

2024-01-10T07:43:49.233647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:43:49.354988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원장 13
56.5%
na 4
 
17.4%
대표이사 2
 
8.7%
사장 1
 
4.3%
이사장 1
 
4.3%
회장 1
 
4.3%
사무처장 1
 
4.3%

대표자
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing4
Missing (%)17.4%
Memory size316.0 B
2024-01-10T07:43:49.512249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters57
Distinct characters37
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

Unique19 ?
Unique (%)100.0%

Sample

1st row정석완
2nd row이경석
3rd row임수흠
4th row김영완
5th row김건식
ValueCountFrequency (%)
이경석 1
 
5.3%
김낙중 1
 
5.3%
변현수 1
 
5.3%
김영범 1
 
5.3%
홍완선 1
 
5.3%
신광섭 1
 
5.3%
정재근 1
 
5.3%
김창수 1
 
5.3%
서흥식 1
 
5.3%
정석완 1
 
5.3%
Other values (9) 9
47.4%
2024-01-10T07:43:49.784943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 7
 
12.3%
석 3
 
5.3%
수 3
 
5.3%
완 3
 
5.3%
식 3
 
5.3%
서 2
 
3.5%
정 2
 
3.5%
중 2
 
3.5%
영 2
 
3.5%
경 2
 
3.5%
Other values (27) 28
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 7
 
12.3%
석 3
 
5.3%
수 3
 
5.3%
완 3
 
5.3%
식 3
 
5.3%
서 2
 
3.5%
정 2
 
3.5%
중 2
 
3.5%
영 2
 
3.5%
경 2
 
3.5%
Other values (27) 28
49.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 7
 
12.3%
석 3
 
5.3%
수 3
 
5.3%
완 3
 
5.3%
식 3
 
5.3%
서 2
 
3.5%
정 2
 
3.5%
중 2
 
3.5%
영 2
 
3.5%
경 2
 
3.5%
Other values (27) 28
49.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 7
 
12.3%
석 3
 
5.3%
수 3
 
5.3%
완 3
 
5.3%
식 3
 
5.3%
서 2
 
3.5%
정 2
 
3.5%
중 2
 
3.5%
영 2
 
3.5%
경 2
 
3.5%
Other values (27) 28
49.1%

설립일
Date

MISSING 

Distinct17
Distinct (%)89.5%
Missing4
Missing (%)17.4%
Memory size316.0 B
Minimum1927-03-05 00:00:00
Maximum2022-09-27 00:00:00
2024-01-10T07:43:49.885960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:43:50.234794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

우편번호
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)68.4%
Missing4
Missing (%)17.4%
Infinite0
Infinite (%)0.0%
Mean32185.421
Minimum31035
Maximum33115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-10T07:43:50.329901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31035
5-th percentile31067.4
Q132116.5
median32263
Q332562
95-th percentile32923.3
Maximum33115
Range2080
Interquartile range (IQR)445.5

Descriptive statistics

Standard deviation597.60581
Coefficient of variation (CV)0.018567593
Kurtosis0.045189845
Mean32185.421
Median Absolute Deviation (MAD)272
Skewness-0.88440924
Sum611523
Variance357132.7
MonotonicityNot monotonic
2024-01-10T07:43:50.431988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
32589 3
13.0%
32416 3
13.0%
32263 2
8.7%
32256 2
8.7%
31071 1
 
4.3%
32535 1
 
4.3%
32001 1
 
4.3%
32232 1
 
4.3%
31035 1
 
4.3%
31450 1
 
4.3%
Other values (3) 3
13.0%
(Missing) 4
17.4%
ValueCountFrequency (%)
31035 1
 
4.3%
31071 1
 
4.3%
31129 1
 
4.3%
31450 1
 
4.3%
32001 1
 
4.3%
32232 1
 
4.3%
32256 2
8.7%
32263 2
8.7%
32416 3
13.0%
32535 1
 
4.3%
ValueCountFrequency (%)
33115 1
 
4.3%
32902 1
 
4.3%
32589 3
13.0%
32535 1
 
4.3%
32416 3
13.0%
32263 2
8.7%
32256 2
8.7%
32232 1
 
4.3%
32001 1
 
4.3%
31450 1
 
4.3%

주소
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing4
Missing (%)17.4%
Memory size316.0 B
2024-01-10T07:43:50.614932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length24
Mean length22.684211
Min length15

Characters and Unicode

Total characters431
Distinct characters79
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

Unique19 ?
Unique (%)100.0%

Sample

1st row충청남도 홍성군 홍북읍 상하천로 58, 5층
2nd row충청남도 천안시 동남구 충절로 537
3rd row충청남도 공주시 무령로 77
4th row충청남도 서산시 중앙로 149
5th row충청남도 홍성군 홍성읍 조양로 224
ValueCountFrequency (%)
충청남도 19
 
19.2%
홍성군 5
 
5.1%
공주시 4
 
4.0%
홍북읍 4
 
4.0%
5층 3
 
3.0%
예산군 3
 
3.0%
천안시 3
 
3.0%
삽교읍 3
 
3.0%
예학로 2
 
2.0%
10-22 2
 
2.0%
Other values (45) 51
51.5%
2024-01-10T07:43:50.927976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
80
 
18.6%
청 21
 
4.9%
남 21
 
4.9%
충 20
 
4.6%
도 19
 
4.4%
로 13
 
3.0%
1 11
 
2.6%
2 11
 
2.6%
시 10
 
2.3%
읍 10
 
2.3%
Other values (69) 215
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 270
62.6%
Space Separator 80
 
18.6%
Decimal Number 66
 
15.3%
Other Punctuation 8
 
1.9%
Dash Punctuation 5
 
1.2%
Uppercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 21
 
7.8%
남 21
 
7.8%
충 20
 
7.4%
도 19
 
7.0%
로 13
 
4.8%
시 10
 
3.7%
읍 10
 
3.7%
홍 10
 
3.7%
군 9
 
3.3%
산 8
 
3.0%
Other values (55) 129
47.8%
Decimal Number
ValueCountFrequency (%)
1 11
16.7%
2 11
16.7%
5 8
12.1%
3 8
12.1%
6 6
9.1%
4 6
9.1%
8 5
7.6%
0 5
7.6%
7 5
7.6%
9 1
 
1.5%
Space Separator
ValueCountFrequency (%)
80
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 270
62.6%
Common 159
36.9%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 21
 
7.8%
남 21
 
7.8%
충 20
 
7.4%
도 19
 
7.0%
로 13
 
4.8%
시 10
 
3.7%
읍 10
 
3.7%
홍 10
 
3.7%
군 9
 
3.3%
산 8
 
3.0%
Other values (55) 129
47.8%
Common
ValueCountFrequency (%)
80
50.3%
1 11
 
6.9%
2 11
 
6.9%
5 8
 
5.0%
3 8
 
5.0%
, 8
 
5.0%
6 6
 
3.8%
4 6
 
3.8%
- 5
 
3.1%
8 5
 
3.1%
Other values (3) 11
 
6.9%
Latin
ValueCountFrequency (%)
S 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 270
62.6%
ASCII 161
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
80
49.7%
1 11
 
6.8%
2 11
 
6.8%
5 8
 
5.0%
3 8
 
5.0%
, 8
 
5.0%
6 6
 
3.7%
4 6
 
3.7%
- 5
 
3.1%
8 5
 
3.1%
Other values (4) 13
 
8.1%
Hangul
ValueCountFrequency (%)
청 21
 
7.8%
남 21
 
7.8%
충 20
 
7.4%
도 19
 
7.0%
로 13
 
4.8%
시 10
 
3.7%
읍 10
 
3.7%
홍 10
 
3.7%
군 9
 
3.3%
산 8
 
3.0%
Other values (55) 129
47.8%

대표전화
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing4
Missing (%)17.4%
Memory size316.0 B
2024-01-10T07:43:51.118040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters228
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

Unique19 ?
Unique (%)100.0%

Sample

1st row041-630-7800
2nd row041-570-7114
3rd row041-962-1111
4th row041-689-7000
5th row041-630-6114
ValueCountFrequency (%)
041-570-7114 1
 
5.3%
041-856-8662 1
 
5.3%
041-338-7601 1
 
5.3%
041-635-0100 1
 
5.3%
041-854-2101 1
 
5.3%
041-635-6980 1
 
5.3%
041-980-3500 1
 
5.3%
041-620-6400 1
 
5.3%
041-630-2900 1
 
5.3%
041-630-7800 1
 
5.3%
Other values (9) 9
47.4%
2024-01-10T07:43:51.449548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 54
23.7%
- 38
16.7%
1 35
15.4%
4 27
11.8%
6 17
 
7.5%
3 16
 
7.0%
8 12
 
5.3%
5 9
 
3.9%
9 8
 
3.5%
2 7
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190
83.3%
Dash Punctuation 38
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 54
28.4%
1 35
18.4%
4 27
14.2%
6 17
 
8.9%
3 16
 
8.4%
8 12
 
6.3%
5 9
 
4.7%
9 8
 
4.2%
2 7
 
3.7%
7 5
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 228
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 54
23.7%
- 38
16.7%
1 35
15.4%
4 27
11.8%
6 17
 
7.5%
3 16
 
7.0%
8 12
 
5.3%
5 9
 
3.9%
9 8
 
3.5%
2 7
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 228
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 54
23.7%
- 38
16.7%
1 35
15.4%
4 27
11.8%
6 17
 
7.5%
3 16
 
7.0%
8 12
 
5.3%
5 9
 
3.9%
9 8
 
3.5%
2 7
 
3.1%

Interactions

2024-01-10T07:43:48.056546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:43:51.550859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관유형기관명직위대표자설립일우편번호주소대표전화
기관유형1.0001.0000.9881.0001.0000.0001.0001.000
기관명1.0001.0001.0001.0001.0001.0001.0001.000
직위0.9881.0001.0001.0001.0000.0001.0001.000
대표자1.0001.0001.0001.0001.0001.0001.0001.000
설립일1.0001.0001.0001.0001.0000.4411.0001.000
우편번호0.0001.0000.0001.0000.4411.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.000
대표전화1.0001.0001.0001.0001.0001.0001.0001.000
2024-01-10T07:43:51.654266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관유형직위
기관유형1.0000.778
직위0.7781.000
2024-01-10T07:43:51.729800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호기관유형직위
우편번호1.0000.0000.000
기관유형0.0001.0000.778
직위0.0000.7781.000

Missing values

2024-01-10T07:43:48.150180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:43:48.257702image/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.
2024-01-10T07:43:48.363381image/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

기관유형기관명직위대표자설립일우편번호주소대표전화
0공기업충남개발공사사장정석완2006-12-2732263충청남도 홍성군 홍북읍 상하천로 58, 5층041-630-7800
1출연기관천안의료원원장이경석1983-07-0131071충청남도 천안시 동남구 충절로 537041-570-7114
2출연기관공주의료원원장임수흠1982-07-0132535충청남도 공주시 무령로 77041-962-1111
3출연기관서산의료원원장김영완1983-07-0132001충청남도 서산시 중앙로 149041-689-7000
4출연기관홍성의료원원장김건식1983-07-0132232충청남도 홍성군 홍성읍 조양로 224041-630-6114
5출연기관충남연구원원장유동훈1995-05-0432589충청남도 공주시 연수원길73-26041-840-1114
6출연기관평생교육인재육성진흥원원장박하식2000-02-1032263충청남도 홍성군 홍북읍 상하천로 58, 3층041-635-9800
7출연기관테크노파크원장서규석1998-12-0731035충청남도 천안시 서북구 직산읍 직산로 136041-589-0602
8출연기관일자리경제진흥원원장김찬배1998-12-0231450충청남도 아산시 염치읍 은행나무길 223041-330-4913
9출연기관신용보증재단이사장김두중1998-10-0132256충청남도 홍성군 홍북읍 청사로150번길 24, 4층041-530-3800
기관유형기관명직위대표자설립일우편번호주소대표전화
13출연기관정보문화산업진흥원원장김창수2005-07-2231129충청남도 천안시 동남구 은행길 15-1, 6층041-620-6400
14출연기관한국유교문화진흥원원장정재근2022-09-2732902충청남도 논산시 노성면 종학길 10041-980-3500
15출연기관백제문화제재단대표이사신광섭2007-03-2633115충청남도 부여군 규암면 백제문로 386-64041-635-6980
16공직유관단체교통연수원원장홍완선1987-05-1332589충청남도 공주시 연수원길 83041-854-2101
17공직유관단체충남체육회회장김영범1927-03-0532256충청남도 홍성군 홍북읍 청사로174번길, 5층041-635-0100
18공직유관단체장애인체육회사무처장변현수2007-04-0532416충청남도 예산군 삽교읍 예학로81, SS프라자 6층041-338-7601
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Duplicate rows

Most frequently occurring

기관유형기관명직위대표자설립일우편번호주소대표전화# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA>4