Overview

Dataset statistics

Number of variables6
Number of observations223
Missing cells245
Missing cells (%)18.3%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory10.8 KiB
Average record size in memory49.6 B

Variable types

Categorical2
DateTime1
Text2
Numeric1

Dataset

Description한국남부발전(주)_시설개방정보에 대한 데이터로 시설명, 신청날짜, 주요내용, 신청기관 등의 항목을 제공합니다.
Author한국남부발전(주)
URLhttps://www.data.go.kr/data/15037904/fileData.do

Alerts

Dataset has 1 (0.4%) duplicate rowsDuplicates
비고 is highly overall correlated with 시설명High correlation
시설명 is highly overall correlated with 비고High correlation
주요내용 has 116 (52.0%) missing valuesMissing
신청인원 has 129 (57.8%) missing valuesMissing

Reproduction

Analysis started2024-04-06 08:58:00.240513
Analysis finished2024-04-06 08:58:02.194532
Duration1.95 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
섬진강 문화센터(하동)
177 
본사 대강당(부산)
46 

Length

Max length12
Median length12
Mean length11.587444
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row섬진강 문화센터(하동)
2nd row섬진강 문화센터(하동)
3rd row섬진강 문화센터(하동)
4th row섬진강 문화센터(하동)
5th row섬진강 문화센터(하동)

Common Values

ValueCountFrequency (%)
섬진강 문화센터(하동) 177
79.4%
본사 대강당(부산) 46
 
20.6%

Length

2024-04-06T17:58:02.331761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:58:02.521006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
섬진강 177
39.7%
문화센터(하동 177
39.7%
본사 46
 
10.3%
대강당(부산 46
 
10.3%

신청날짜
Date

Distinct209
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2016-01-26 00:00:00
Maximum2024-03-22 00:00:00
2024-04-06T17:58:02.734263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:58:03.021495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주요내용
Text

MISSING 

Distinct51
Distinct (%)47.7%
Missing116
Missing (%)52.0%
Memory size1.9 KiB
2024-04-06T17:58:03.545116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length8.2897196
Min length2

Characters and Unicode

Total characters887
Distinct characters178
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

Unique37 ?
Unique (%)34.6%

Sample

1st row토익시험
2nd row배드민턴 대회
3rd row토익시험
4th row불공정 예방교육 대관
5th row토익시험
ValueCountFrequency (%)
교육 28
 
13.5%
대관 22
 
10.6%
토익시험 9
 
4.3%
회의 6
 
2.9%
예식서비스 5
 
2.4%
본사 5
 
2.4%
bifc 5
 
2.4%
bifc관리단 4
 
1.9%
체육대회 4
 
1.9%
주택금융공사 4
 
1.9%
Other values (86) 115
55.6%
2024-04-06T17:58:04.707574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
 
11.4%
육 43
 
4.8%
관 41
 
4.6%
교 40
 
4.5%
대 35
 
3.9%
사 28
 
3.2%
회 23
 
2.6%
스 12
 
1.4%
C 12
 
1.4%
험 12
 
1.4%
Other values (168) 540
60.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 697
78.6%
Space Separator 101
 
11.4%
Uppercase Letter 46
 
5.2%
Decimal Number 23
 
2.6%
Close Punctuation 8
 
0.9%
Open Punctuation 8
 
0.9%
Other Punctuation 3
 
0.3%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
육 43
 
6.2%
관 41
 
5.9%
교 40
 
5.7%
대 35
 
5.0%
사 28
 
4.0%
회 23
 
3.3%
스 12
 
1.7%
험 12
 
1.7%
공 10
 
1.4%
단 10
 
1.4%
Other values (148) 443
63.6%
Decimal Number
ValueCountFrequency (%)
0 10
43.5%
1 5
21.7%
2 2
 
8.7%
9 1
 
4.3%
7 1
 
4.3%
8 1
 
4.3%
6 1
 
4.3%
3 1
 
4.3%
5 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
C 12
26.1%
F 11
23.9%
I 11
23.9%
B 11
23.9%
S 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 697
78.6%
Common 144
 
16.2%
Latin 46
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
육 43
 
6.2%
관 41
 
5.9%
교 40
 
5.7%
대 35
 
5.0%
사 28
 
4.0%
회 23
 
3.3%
스 12
 
1.7%
험 12
 
1.7%
공 10
 
1.4%
단 10
 
1.4%
Other values (148) 443
63.6%
Common
ValueCountFrequency (%)
101
70.1%
0 10
 
6.9%
) 8
 
5.6%
( 8
 
5.6%
1 5
 
3.5%
2 2
 
1.4%
/ 2
 
1.4%
9 1
 
0.7%
7 1
 
0.7%
, 1
 
0.7%
Other values (5) 5
 
3.5%
Latin
ValueCountFrequency (%)
C 12
26.1%
F 11
23.9%
I 11
23.9%
B 11
23.9%
S 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 697
78.6%
ASCII 190
 
21.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
101
53.2%
C 12
 
6.3%
F 11
 
5.8%
I 11
 
5.8%
B 11
 
5.8%
0 10
 
5.3%
) 8
 
4.2%
( 8
 
4.2%
1 5
 
2.6%
2 2
 
1.1%
Other values (10) 11
 
5.8%
Hangul
ValueCountFrequency (%)
육 43
 
6.2%
관 41
 
5.9%
교 40
 
5.7%
대 35
 
5.0%
사 28
 
4.0%
회 23
 
3.3%
스 12
 
1.7%
험 12
 
1.7%
공 10
 
1.4%
단 10
 
1.4%
Other values (148) 443
63.6%

신청기관
Text

Distinct92
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-06T17:58:05.221639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length9.0627803
Min length2

Characters and Unicode

Total characters2021
Distinct characters149
Distinct categories4 ?
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 (%)22.0%

Sample

1st row남전발전본부
2nd row기획관리팀
3rd row남전본사
4th row노경협력팀
5th row노경협력팀
ValueCountFrequency (%)
하동발전본부 110
29.7%
안전재난부 16
 
4.3%
지역협력과 14
 
3.8%
ksr인증원 12
 
3.2%
총무부 9
 
2.4%
bifc 9
 
2.4%
기획관리부 8
 
2.2%
노경협력팀 7
 
1.9%
노조 7
 
1.9%
노사협력부 7
 
1.9%
Other values (81) 171
46.2%
2024-04-06T17:58:06.082796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 186
 
9.2%
158
 
7.8%
전 145
 
7.2%
발 128
 
6.3%
동 127
 
6.3%
하 123
 
6.1%
본 112
 
5.5%
리 36
 
1.8%
협 34
 
1.7%
관 33
 
1.6%
Other values (139) 939
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1741
86.1%
Space Separator 158
 
7.8%
Uppercase Letter 114
 
5.6%
Decimal Number 8
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 186
 
10.7%
전 145
 
8.3%
발 128
 
7.4%
동 127
 
7.3%
하 123
 
7.1%
본 112
 
6.4%
리 36
 
2.1%
협 34
 
2.0%
관 33
 
1.9%
사 30
 
1.7%
Other values (127) 787
45.2%
Uppercase Letter
ValueCountFrequency (%)
S 18
15.8%
F 15
13.2%
I 15
13.2%
B 15
13.2%
C 15
13.2%
K 12
10.5%
R 12
10.5%
H 6
 
5.3%
P 6
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 6
75.0%
2 2
 
25.0%
Space Separator
ValueCountFrequency (%)
158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1741
86.1%
Common 166
 
8.2%
Latin 114
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 186
 
10.7%
전 145
 
8.3%
발 128
 
7.4%
동 127
 
7.3%
하 123
 
7.1%
본 112
 
6.4%
리 36
 
2.1%
협 34
 
2.0%
관 33
 
1.9%
사 30
 
1.7%
Other values (127) 787
45.2%
Latin
ValueCountFrequency (%)
S 18
15.8%
F 15
13.2%
I 15
13.2%
B 15
13.2%
C 15
13.2%
K 12
10.5%
R 12
10.5%
H 6
 
5.3%
P 6
 
5.3%
Common
ValueCountFrequency (%)
158
95.2%
1 6
 
3.6%
2 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1741
86.1%
ASCII 280
 
13.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 186
 
10.7%
전 145
 
8.3%
발 128
 
7.4%
동 127
 
7.3%
하 123
 
7.1%
본 112
 
6.4%
리 36
 
2.1%
협 34
 
2.0%
관 33
 
1.9%
사 30
 
1.7%
Other values (127) 787
45.2%
ASCII
ValueCountFrequency (%)
158
56.4%
S 18
 
6.4%
F 15
 
5.4%
I 15
 
5.4%
B 15
 
5.4%
C 15
 
5.4%
K 12
 
4.3%
R 12
 
4.3%
H 6
 
2.1%
P 6
 
2.1%
Other values (2) 8
 
2.9%

신청인원
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)23.4%
Missing129
Missing (%)57.8%
Infinite0
Infinite (%)0.0%
Mean37.574468
Minimum3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-06T17:58:06.328736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile7.65
Q120
median37.5
Q350
95-th percentile80.5
Maximum100
Range97
Interquartile range (IQR)30

Descriptive statistics

Standard deviation21.998773
Coefficient of variation (CV)0.58547131
Kurtosis1.3053488
Mean37.574468
Median Absolute Deviation (MAD)12.5
Skewness0.94849768
Sum3532
Variance483.94601
MonotonicityNot monotonic
2024-04-06T17:58:06.533016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
50 28
 
12.6%
20 14
 
6.3%
15 6
 
2.7%
100 5
 
2.2%
35 5
 
2.2%
25 5
 
2.2%
40 5
 
2.2%
60 4
 
1.8%
45 4
 
1.8%
30 3
 
1.3%
Other values (12) 15
 
6.7%
(Missing) 129
57.8%
ValueCountFrequency (%)
3 1
 
0.4%
5 1
 
0.4%
6 1
 
0.4%
7 2
 
0.9%
8 1
 
0.4%
11 2
 
0.9%
12 2
 
0.9%
15 6
2.7%
16 1
 
0.4%
20 14
6.3%
ValueCountFrequency (%)
100 5
 
2.2%
70 1
 
0.4%
60 4
 
1.8%
50 28
12.6%
45 4
 
1.8%
40 5
 
2.2%
35 5
 
2.2%
33 1
 
0.4%
30 3
 
1.3%
28 1
 
0.4%

비고
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
시청각실
126 
대강당
41 
실내체육관
36 
요가실
 
5
다용도실
 
3
Other values (7)
 
12

Length

Max length23
Median length4
Mean length4.1659193
Min length3

Unique

Unique4 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
시청각실 126
56.5%
대강당 41
 
18.4%
실내체육관 36
 
16.1%
요가실 5
 
2.2%
다용도실 3
 
1.3%
시청각실,요가실 3
 
1.3%
알리오플러스 3
 
1.3%
<NA> 2
 
0.9%
체육관 1
 
0.4%
실내체육관, 시청각실 1
 
0.4%
Other values (2) 2
 
0.9%

Length

2024-04-06T17:58:06.793976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
시청각실 127
56.2%
대강당 41
 
18.1%
실내체육관 37
 
16.4%
요가실 5
 
2.2%
다용도실 3
 
1.3%
시청각실,요가실 3
 
1.3%
알리오플러스 3
 
1.3%
na 2
 
0.9%
체육관 1
 
0.4%
20-08-21 1
 
0.4%
Other values (3) 3
 
1.3%

Interactions

2024-04-06T17:58:01.574817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:58:06.949003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명주요내용신청기관신청인원비고
시설명1.0001.0001.0000.4701.000
주요내용1.0001.0000.9900.9750.774
신청기관1.0000.9901.0000.9390.000
신청인원0.4700.9750.9391.0000.624
비고1.0000.7740.0000.6241.000
2024-04-06T17:58:07.242334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고시설명
비고1.0000.979
시설명0.9791.000
2024-04-06T17:58:07.542198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신청인원시설명비고
신청인원1.0000.3410.250
시설명0.3411.0000.979
비고0.2500.9791.000

Missing values

2024-04-06T17:58:01.775390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:58:01.935374image/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.
2024-04-06T17:58:02.102671image/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

시설명신청날짜주요내용신청기관신청인원비고
0섬진강 문화센터(하동)2016-01-26<NA>남전발전본부12시청각실
1섬진강 문화센터(하동)2016-02-23<NA>기획관리팀30시청각실
2섬진강 문화센터(하동)2016-03-15<NA>남전본사<NA>시청각실
3섬진강 문화센터(하동)2016-04-19<NA>노경협력팀<NA>시청각실
4섬진강 문화센터(하동)2016-04-20<NA>노경협력팀<NA>시청각실
5섬진강 문화센터(하동)2016-04-21<NA>노경협력팀<NA>시청각실
6섬진강 문화센터(하동)2016-04-28<NA>하동화력 노동조합<NA>시청각실
7섬진강 문화센터(하동)2016-05-21토익시험하동발전본부 총무과7시청각실
8섬진강 문화센터(하동)2016-05-28배드민턴 대회노량 배드민턴 동호회60실내체육관
9섬진강 문화센터(하동)2016-06-01<NA>하동발전본부 기획관리팀<NA>시청각실
시설명신청날짜주요내용신청기관신청인원비고
213섬진강 문화센터(하동)2020-11-16교육하동발전본부 발전1부<NA>시청각실
214섬진강 문화센터(하동)2020-11-17교육하동발전본부 발전1부<NA>시청각실
215섬진강 문화센터(하동)2020-11-18교육하동발전본부 발전1부<NA>시청각실
216본사 대강당(부산)2021-03-15BIFC관리단 회의BIFC관리단15대강당
217본사 대강당(부산)2021-03-24BIFC관리단 회의BIFC관리단20대강당
218본사 대강당(부산)2022-10-14사회복지사역량강화교육부산광역시사회복지사협회100대강당
219본사 대강당(부산)2024-02-16BIFC근무자서비스교육BIFC관리단60알리오플러스
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Duplicate rows

Most frequently occurring

시설명신청날짜주요내용신청기관신청인원비고# duplicates
0섬진강 문화센터(하동)2016-08-19<NA>하동발전본부 기획관리팀<NA>시청각실2