Overview

Dataset statistics

Number of variables17
Number of observations489
Missing cells1506
Missing cells (%)18.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory66.0 KiB
Average record size in memory138.3 B

Variable types

Numeric2
Categorical7
Text4
DateTime4

Dataset

Description인천도시경관아카이브 시스템 내 데이터로 위원회 명단에 대한 내용이 담겨져 있으며, 목록으로 위원회명단일련번호, 소속 위원회, 전문 분야, 이름, 성별, 생년월일, 멤버 소속, 직책, 직위, 임기, 연임 여부, 비고, 등록 일자, 수정 일자, 삭제 여부로 구성되어 있습니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15122338&srcSe=7661IVAWM27C61E190

Alerts

비고 has constant value ""Constant
임기 is highly overall correlated with 위원회명단일련번호(SEQ) and 2 other fieldsHigh correlation
소속위원회 is highly overall correlated with 위원회명단일련번호(SEQ) and 3 other fieldsHigh correlation
위원회명단일련번호(SEQ) is highly overall correlated with 소속위원회 and 2 other fieldsHigh correlation
전문분야 is highly overall correlated with 소속위원회High correlation
연임여부 is highly overall correlated with 위원회명단일련번호(SEQ) and 2 other fieldsHigh correlation
직위 is highly imbalanced (82.6%)Imbalance
삭제여부 is highly imbalanced (96.2%)Imbalance
생년월일 has 70 (14.3%) missing valuesMissing
비고 has 488 (99.8%) missing valuesMissing
수정일자 has 474 (96.9%) missing valuesMissing
수정시간 has 474 (96.9%) missing valuesMissing
위원회명단일련번호(SEQ) has unique valuesUnique

Reproduction

Analysis started2024-01-28 05:57:19.867101
Analysis finished2024-01-28 05:57:21.439623
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

위원회명단일련번호(SEQ)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct489
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean245.01431
Minimum1
Maximum493
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-01-28T14:57:21.501515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.4
Q1123
median245
Q3367
95-th percentile464.6
Maximum493
Range492
Interquartile range (IQR)244

Descriptive statistics

Standard deviation141.33131
Coefficient of variation (CV)0.57682878
Kurtosis-1.1991312
Mean245.01431
Median Absolute Deviation (MAD)122
Skewness0.00061634667
Sum119812
Variance19974.539
MonotonicityNot monotonic
2024-01-28T14:57:21.612885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
301 1
 
0.2%
299 1
 
0.2%
298 1
 
0.2%
297 1
 
0.2%
296 1
 
0.2%
295 1
 
0.2%
294 1
 
0.2%
293 1
 
0.2%
292 1
 
0.2%
Other values (479) 479
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
493 1
0.2%
491 1
0.2%
487 1
0.2%
486 1
0.2%
485 1
0.2%
484 1
0.2%
483 1
0.2%
482 1
0.2%
481 1
0.2%
480 1
0.2%

소속위원회
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
경관위원회
296 
공공디자인위원회
193 

Length

Max length8
Median length5
Mean length6.1840491
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경관위원회 296
60.5%
공공디자인위원회 193
39.5%

Length

2024-01-28T14:57:21.718091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:57:21.796295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경관위원회 296
60.5%
공공디자인위원회 193
39.5%

전문분야
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
디자인
99 
건축
66 
도시
62 
경관
36 
조명
35 
Other values (42)
191 

Length

Max length12
Median length2
Mean length2.5296524
Min length2

Unique

Unique14 ?
Unique (%)2.9%

Sample

1st row당연직
2nd row임명직
3rd row도시
4th row도시
5th row디자인

Common Values

ValueCountFrequency (%)
디자인 99
20.2%
건축 66
13.5%
도시 62
12.7%
경관 36
 
7.4%
조명 35
 
7.2%
조경 33
 
6.7%
색채 22
 
4.5%
공무원 17
 
3.5%
교통 15
 
3.1%
범죄예방 12
 
2.5%
Other values (37) 92
18.8%

Length

2024-01-28T14:57:21.895913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
디자인 99
20.2%
건축 66
13.5%
도시 62
12.7%
경관 36
 
7.3%
조명 35
 
7.1%
조경 33
 
6.7%
색채 22
 
4.5%
공무원 17
 
3.5%
교통 15
 
3.1%
범죄예방 12
 
2.4%
Other values (37) 93
19.0%

이름
Text

Distinct265
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-01-28T14:57:22.158389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.99182
Min length2

Characters and Unicode

Total characters1463
Distinct characters137
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

Unique142 ?
Unique (%)29.0%

Sample

1st row전성수
2nd row이종호
3rd row김경배
4th row이인재
5th row곽동하
ValueCountFrequency (%)
민범기 6
 
1.2%
김대성 6
 
1.2%
김용하 6
 
1.2%
김선영 5
 
1.0%
석종수 5
 
1.0%
권윤구 5
 
1.0%
신지훈 5
 
1.0%
손동필 5
 
1.0%
안창환 5
 
1.0%
이금진 4
 
0.8%
Other values (257) 440
89.4%
2024-01-28T14:57:22.526253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 112
 
7.7%
이 96
 
6.6%
영 58
 
4.0%
정 47
 
3.2%
희 40
 
2.7%
민 32
 
2.2%
성 29
 
2.0%
윤 29
 
2.0%
박 28
 
1.9%
진 27
 
1.8%
Other values (127) 965
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1460
99.8%
Space Separator 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 112
 
7.7%
이 96
 
6.6%
영 58
 
4.0%
정 47
 
3.2%
희 40
 
2.7%
민 32
 
2.2%
성 29
 
2.0%
윤 29
 
2.0%
박 28
 
1.9%
진 27
 
1.8%
Other values (126) 962
65.9%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1460
99.8%
Common 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 112
 
7.7%
이 96
 
6.6%
영 58
 
4.0%
정 47
 
3.2%
희 40
 
2.7%
민 32
 
2.2%
성 29
 
2.0%
윤 29
 
2.0%
박 28
 
1.9%
진 27
 
1.8%
Other values (126) 962
65.9%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1460
99.8%
ASCII 3
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 112
 
7.7%
이 96
 
6.6%
영 58
 
4.0%
정 47
 
3.2%
희 40
 
2.7%
민 32
 
2.2%
성 29
 
2.0%
윤 29
 
2.0%
박 28
 
1.9%
진 27
 
1.8%
Other values (126) 962
65.9%
ASCII
ValueCountFrequency (%)
3
100.0%

성별
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
남
323 
여
166 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남 323
66.1%
여 166
33.9%

Length

2024-01-28T14:57:22.635552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:57:22.710319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 323
66.1%
여 166
33.9%

생년월일
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)8.4%
Missing70
Missing (%)14.3%
Infinite0
Infinite (%)0.0%
Mean1966.3747
Minimum1947
Maximum1987
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-01-28T14:57:22.791631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1947
5-th percentile1953
Q11961
median1967
Q31972
95-th percentile1977
Maximum1987
Range40
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.3608579
Coefficient of variation (CV)0.0037433648
Kurtosis-0.29148291
Mean1966.3747
Median Absolute Deviation (MAD)5
Skewness-0.24448758
Sum823911
Variance54.182229
MonotonicityNot monotonic
2024-01-28T14:57:22.893933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1969 39
 
8.0%
1967 29
 
5.9%
1972 29
 
5.9%
1966 24
 
4.9%
1970 22
 
4.5%
1973 21
 
4.3%
1965 20
 
4.1%
1960 16
 
3.3%
1971 15
 
3.1%
1957 14
 
2.9%
Other values (25) 190
38.9%
(Missing) 70
 
14.3%
ValueCountFrequency (%)
1947 2
 
0.4%
1948 3
 
0.6%
1949 1
 
0.2%
1951 2
 
0.4%
1952 3
 
0.6%
1953 13
2.7%
1954 4
 
0.8%
1955 8
1.6%
1956 12
2.5%
1957 14
2.9%
ValueCountFrequency (%)
1987 1
 
0.2%
1983 6
 
1.2%
1980 3
 
0.6%
1979 6
 
1.2%
1978 4
 
0.8%
1977 6
 
1.2%
1976 12
2.5%
1975 12
2.5%
1974 11
2.2%
1973 21
4.3%

멤버소속
Text

Distinct281
Distinct (%)57.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-01-28T14:57:23.347671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length16
Mean length9.5848671
Min length3

Characters and Unicode

Total characters4687
Distinct characters268
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192 ?
Unique (%)39.3%

Sample

1st row인천광역시
2nd row인천광역시
3rd row인하대학교
4th row인천발전연구원
5th row인천대학교
ValueCountFrequency (%)
인천광역시 29
 
4.0%
인천대학교 22
 
3.0%
인하공업전문대학 19
 
2.6%
인천발전연구원 17
 
2.3%
인하대학교 13
 
1.8%
도시건축학부 12
 
1.6%
디자인학부 11
 
1.5%
건축도시공간연구소 10
 
1.4%
홍익대학교 10
 
1.4%
건축공학과 9
 
1.2%
Other values (326) 582
79.3%
2024-01-28T14:57:23.656563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 313
 
6.7%
대 261
 
5.6%
인 254
 
5.4%
246
 
5.2%
교 167
 
3.6%
천 142
 
3.0%
건 129
 
2.8%
시 121
 
2.6%
축 110
 
2.3%
과 109
 
2.3%
Other values (258) 2835
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4287
91.5%
Space Separator 246
 
5.2%
Other Symbol 47
 
1.0%
Close Punctuation 35
 
0.7%
Open Punctuation 35
 
0.7%
Other Punctuation 18
 
0.4%
Uppercase Letter 15
 
0.3%
Letter Number 2
 
< 0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 313
 
7.3%
대 261
 
6.1%
인 254
 
5.9%
교 167
 
3.9%
천 142
 
3.3%
건 129
 
3.0%
시 121
 
2.8%
축 110
 
2.6%
과 109
 
2.5%
사 101
 
2.4%
Other values (240) 2580
60.2%
Uppercase Letter
ValueCountFrequency (%)
U 3
20.0%
A 3
20.0%
N 3
20.0%
K 2
13.3%
R 1
 
6.7%
J 1
 
6.7%
S 1
 
6.7%
M 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
; 16
88.9%
, 1
 
5.6%
/ 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
246
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4333
92.4%
Common 336
 
7.2%
Latin 17
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 313
 
7.2%
대 261
 
6.0%
인 254
 
5.9%
교 167
 
3.9%
천 142
 
3.3%
건 129
 
3.0%
시 121
 
2.8%
축 110
 
2.5%
과 109
 
2.5%
사 101
 
2.3%
Other values (240) 2626
60.6%
Latin
ValueCountFrequency (%)
U 3
17.6%
A 3
17.6%
N 3
17.6%
Ⅱ 2
11.8%
K 2
11.8%
R 1
 
5.9%
J 1
 
5.9%
S 1
 
5.9%
M 1
 
5.9%
Common
ValueCountFrequency (%)
246
73.2%
) 35
 
10.4%
( 35
 
10.4%
; 16
 
4.8%
2 1
 
0.3%
1 1
 
0.3%
, 1
 
0.3%
/ 1
 
0.3%
Han
ValueCountFrequency (%)
前 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4286
91.4%
ASCII 351
 
7.5%
None 47
 
1.0%
Number Forms 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 313
 
7.3%
대 261
 
6.1%
인 254
 
5.9%
교 167
 
3.9%
천 142
 
3.3%
건 129
 
3.0%
시 121
 
2.8%
축 110
 
2.6%
과 109
 
2.5%
사 101
 
2.4%
Other values (239) 2579
60.2%
ASCII
ValueCountFrequency (%)
246
70.1%
) 35
 
10.0%
( 35
 
10.0%
; 16
 
4.6%
U 3
 
0.9%
A 3
 
0.9%
N 3
 
0.9%
K 2
 
0.6%
R 1
 
0.3%
2 1
 
0.3%
Other values (6) 6
 
1.7%
None
ValueCountFrequency (%)
㈜ 47
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
CJK
ValueCountFrequency (%)
前 1
100.0%

직책
Text

Distinct79
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-01-28T14:57:23.848953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length2.8834356
Min length1

Characters and Unicode

Total characters1410
Distinct characters86
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

Unique41 ?
Unique (%)8.4%

Sample

1st row행정부시장
2nd row도시계획국장
3rd row교수
4th row연구기획본부장
5th row교수
ValueCountFrequency (%)
교수 182
36.8%
대표 42
 
8.5%
연구위원 32
 
6.5%
대표이사 23
 
4.7%
조교수 22
 
4.5%
소장 20
 
4.0%
부사장 9
 
1.8%
부교수 8
 
1.6%
이사 8
 
1.6%
부장 7
 
1.4%
Other values (70) 141
28.5%
2024-01-28T14:57:24.133928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 229
16.2%
수 228
16.2%
장 111
 
7.9%
원 66
 
4.7%
표 65
 
4.6%
대 65
 
4.6%
부 59
 
4.2%
연 52
 
3.7%
구 52
 
3.7%
사 51
 
3.6%
Other values (76) 432
30.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1395
98.9%
Dash Punctuation 6
 
0.4%
Space Separator 5
 
0.4%
Decimal Number 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 229
16.4%
수 228
16.3%
장 111
 
8.0%
원 66
 
4.7%
표 65
 
4.7%
대 65
 
4.7%
부 59
 
4.2%
연 52
 
3.7%
구 52
 
3.7%
사 51
 
3.7%
Other values (71) 417
29.9%
Decimal Number
ValueCountFrequency (%)
9 2
50.0%
1 1
25.0%
5 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1395
98.9%
Common 15
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 229
16.4%
수 228
16.3%
장 111
 
8.0%
원 66
 
4.7%
표 65
 
4.7%
대 65
 
4.7%
부 59
 
4.2%
연 52
 
3.7%
구 52
 
3.7%
사 51
 
3.7%
Other values (71) 417
29.9%
Common
ValueCountFrequency (%)
- 6
40.0%
5
33.3%
9 2
 
13.3%
1 1
 
6.7%
5 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1395
98.9%
ASCII 15
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 229
16.4%
수 228
16.3%
장 111
 
8.0%
원 66
 
4.7%
표 65
 
4.7%
대 65
 
4.7%
부 59
 
4.2%
연 52
 
3.7%
구 52
 
3.7%
사 51
 
3.7%
Other values (71) 417
29.9%
ASCII
ValueCountFrequency (%)
- 6
40.0%
5
33.3%
9 2
 
13.3%
1 1
 
6.7%
5 1
 
6.7%

직위
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
위원
470 
위원장
 
11
부위원장
 
8

Length

Max length4
Median length2
Mean length2.0552147
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row위원장
2nd row위원
3rd row위원
4th row위원
5th row위원

Common Values

ValueCountFrequency (%)
위원 470
96.1%
위원장 11
 
2.2%
부위원장 8
 
1.6%

Length

2024-01-28T14:57:24.257086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:57:24.344790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위원 470
96.1%
위원장 11
 
2.2%
부위원장 8
 
1.6%

임기
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2기
80 
3기
74 
10대
63 
9기
53 
7기
53 
Other values (5)
166 

Length

Max length3
Median length2
Mean length2.1288344
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1기
2nd row1기
3rd row1기
4th row1기
5th row1기

Common Values

ValueCountFrequency (%)
2기 80
16.4%
3기 74
15.1%
10대 63
12.9%
9기 53
10.8%
7기 53
10.8%
8기 49
10.0%
6기 42
8.6%
1기 39
8.0%
4기 20
 
4.1%
5기 16
 
3.3%

Length

2024-01-28T14:57:24.420189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:57:24.509656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2기 80
16.4%
3기 74
15.1%
10대 63
12.9%
9기 53
10.8%
7기 53
10.8%
8기 49
10.0%
6기 42
8.6%
1기 39
8.0%
4기 20
 
4.1%
5기 16
 
3.3%

연임여부
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
301 
2기
96 
최초
37 
3기
 
26
연임
 
21
Other values (2)
 
8

Length

Max length4
Median length4
Mean length3.2310838
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row최초
4th row최초
5th row최초

Common Values

ValueCountFrequency (%)
<NA> 301
61.6%
2기 96
 
19.6%
최초 37
 
7.6%
3기 26
 
5.3%
연임 21
 
4.3%
4기 5
 
1.0%
5기 3
 
0.6%

Length

2024-01-28T14:57:24.624061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:57:24.715994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 301
61.6%
2기 96
 
19.6%
최초 37
 
7.6%
3기 26
 
5.3%
연임 21
 
4.3%
4기 5
 
1.0%
5기 3
 
0.6%

비고
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing488
Missing (%)99.8%
Memory size3.9 KiB
2024-01-28T14:57:24.808800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
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

Unique1 ?
Unique (%)100.0%

Sample

1st row당연직
ValueCountFrequency (%)
당연직 1
100.0%
2024-01-28T14:57:25.017771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 1
33.3%
연 1
33.3%
직 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 1
33.3%
연 1
33.3%
직 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 1
33.3%
연 1
33.3%
직 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 1
33.3%
연 1
33.3%
직 1
33.3%

등록일자
Date

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2020-07-09 00:00:00
Maximum2023-02-20 00:00:00
2024-01-28T14:57:25.106755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:57:25.188950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

등록시간
Date

Distinct63
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2024-01-28 11:51:43
Maximum2024-01-28 20:08:56
2024-01-28T14:57:25.284557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:57:25.386767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일자
Date

MISSING 

Distinct2
Distinct (%)13.3%
Missing474
Missing (%)96.9%
Memory size3.9 KiB
Minimum2022-04-20 00:00:00
Maximum2023-03-03 00:00:00
2024-01-28T14:57:25.466976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:57:25.535677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

수정시간
Date

MISSING 

Distinct8
Distinct (%)53.3%
Missing474
Missing (%)96.9%
Memory size3.9 KiB
Minimum2024-01-28 14:46:33
Maximum2024-01-28 17:24:23
2024-01-28T14:57:25.616117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:57:25.694041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

삭제여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
N
487 
Y
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 487
99.6%
Y 2
 
0.4%

Length

2024-01-28T14:57:25.784033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:57:25.854208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 487
99.6%
y 2
 
0.4%

Interactions

2024-01-28T14:57:20.876743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:57:20.717899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:57:20.967227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T14:57:20.788321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T14:57:25.912316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위원회명단일련번호(SEQ)소속위원회전문분야성별생년월일직책직위임기연임여부등록일자등록시간수정일자수정시간삭제여부
위원회명단일련번호(SEQ)1.0000.9920.6830.2060.2100.5100.1240.9750.7890.5650.7600.0000.0000.000
소속위원회0.9921.0000.6750.0660.0000.4860.0551.0000.8740.3760.690NaNNaN0.000
전문분야0.6830.6751.0000.4960.6190.9260.7210.7080.2590.0000.0000.0001.0000.000
성별0.2060.0660.4961.0000.3570.4120.0780.1900.2780.0000.0000.0001.0000.000
생년월일0.2100.0000.6190.3571.0000.5990.1430.2080.0850.0000.000NaN1.0000.580
직책0.5100.4860.9260.4120.5991.0000.9700.4590.0000.9040.5901.0001.0000.000
직위0.1240.0550.7210.0780.1430.9701.0000.0140.1570.6360.8100.5871.0000.000
임기0.9751.0000.7080.1900.2080.4590.0141.0000.8900.6100.647NaNNaN0.127
연임여부0.7890.8740.2590.2780.0850.0000.1570.8901.0000.9620.733NaNNaN0.342
등록일자0.5650.3760.0000.0000.0000.9040.6360.6100.9621.0001.0001.0000.3660.000
등록시간0.7600.6900.0000.0000.0000.5900.8100.6470.7331.0001.0001.0000.5190.767
수정일자0.000NaN0.0000.000NaN1.0000.587NaNNaN1.0001.0001.0001.0000.000
수정시간0.000NaN1.0001.0001.0001.0001.000NaNNaN0.3660.5191.0001.0001.000
삭제여부0.0000.0000.0000.0000.5800.0000.0000.1270.3420.0000.7670.0001.0001.000
2024-01-28T14:57:26.030577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별임기연임여부삭제여부전문분야소속위원회직위
성별1.0000.1440.1980.0000.3950.0420.129
임기0.1441.0000.6840.0970.3160.9920.006
연임여부0.1980.6841.0000.2430.1130.6780.064
삭제여부0.0000.0970.2431.0000.0000.0000.000
전문분야0.3950.3160.1130.0001.0000.5450.463
소속위원회0.0420.9920.6780.0000.5451.0000.091
직위0.1290.0060.0640.0000.4630.0911.000
2024-01-28T14:57:26.121635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위원회명단일련번호(SEQ)생년월일소속위원회전문분야성별직위임기연임여부삭제여부
위원회명단일련번호(SEQ)1.0000.0630.9120.2970.1560.0730.7250.5640.000
생년월일0.0631.0000.0000.2340.2760.1090.0880.0510.444
소속위원회0.9120.0001.0000.5450.0420.0910.9920.6780.000
전문분야0.2970.2340.5451.0000.3950.4630.3160.1130.000
성별0.1560.2760.0420.3951.0000.1290.1440.1980.000
직위0.0730.1090.0910.4630.1291.0000.0060.0640.000
임기0.7250.0880.9920.3160.1440.0061.0000.6840.097
연임여부0.5640.0510.6780.1130.1980.0640.6841.0000.243
삭제여부0.0000.4440.0000.0000.0000.0000.0970.2431.000

Missing values

2024-01-28T14:57:21.097697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T14:57:21.278195image/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.
2024-01-28T14:57:21.384369image/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

위원회명단일련번호(SEQ)소속위원회전문분야이름성별생년월일멤버소속직책직위임기연임여부비고등록일자등록시간수정일자수정시간삭제여부
01공공디자인위원회당연직전성수남<NA>인천광역시행정부시장위원장1기<NA><NA>2020-07-0916:28:14<NA><NA>N
12공공디자인위원회임명직이종호남<NA>인천광역시도시계획국장위원1기<NA><NA>2020-07-0916:28:14<NA><NA>N
23공공디자인위원회도시김경배남<NA>인하대학교교수위원1기최초<NA>2020-07-0916:28:14<NA><NA>N
34공공디자인위원회도시이인재남1968인천발전연구원연구기획본부장위원1기최초<NA>2020-07-0916:28:14<NA><NA>N
45공공디자인위원회디자인곽동하남1967인천대학교교수위원1기최초<NA>2020-07-0916:28:14<NA><NA>N
56공공디자인위원회도시심재만남1960선진엔지니어링부사장위원1기최초<NA>2020-07-0916:28:14<NA><NA>N
67공공디자인위원회디자인홍세표남<NA>인하공업전문대학교수위원1기최초<NA>2020-07-0916:28:14<NA><NA>N
78공공디자인위원회디자인김희교남1964인하공업전문대학교수위원1기최초<NA>2020-07-0916:28:14<NA><NA>N
89공공디자인위원회건축이혁준남1972인하공업전문대학교수위원1기최초<NA>2020-07-0916:28:14<NA><NA>N
910공공디자인위원회디자인김용수남<NA>국토교통부사무관위원1기최초<NA>2020-07-0916:28:14<NA><NA>N
위원회명단일련번호(SEQ)소속위원회전문분야이름성별생년월일멤버소속직책직위임기연임여부비고등록일자등록시간수정일자수정시간삭제여부
479433경관위원회건축최영희남1971㈜아인그룹건축사사무소대표위원10대<NA><NA>2022-04-2015:30:25<NA><NA>N
480437경관위원회건축강신원남1973(주)마리스건축사사무소대표위원10대<NA><NA>2022-04-2016:35:08<NA><NA>N
481446경관위원회도시김혜정여1972한라대학교 영상커뮤니케이션학부교수위원10대<NA><NA>2022-04-2016:43:11<NA><NA>N
482448경관위원회디자인강호섭남1955한국실내건축가협회이사위원10대<NA><NA>2022-04-2016:45:11<NA><NA>N
483453경관위원회디자인이승민여1972남서울대학교 멀티미디어학과교수위원10대<NA><NA>2022-04-2016:48:33<NA><NA>N
484454경관위원회경관이용환남1971한국교원대학교교수위원10대<NA><NA>2022-04-2016:49:36<NA><NA>N
485459경관위원회경관주신하남1969서울여자대학교 원예생명조경학과교수위원10대<NA><NA>2022-04-2016:53:13<NA><NA>N
486471경관위원회색채유명선여1979한국색채학회이사위원10대<NA><NA>2022-04-2017:05:19<NA><NA>N
487476경관위원회조명이지은여1979디자인온대표위원10대<NA><NA>2022-04-2017:08:23<NA><NA>N
488136경관위원회공무원최도수남<NA>인천광역시주택녹지국장부위원장9기<NA>당연직2020-09-0911:51:43<NA><NA>N