Overview

Dataset statistics

Number of variables27
Number of observations1000
Missing cells1129
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory218.9 KiB
Average record size in memory224.1 B

Variable types

Numeric7
Categorical9
DateTime3
Text6
Boolean2

Dataset

Description인천광역시 미추홀구 의회전자회의록 시스템의 회의록 테이블에 존재하는 데이터로 위원회코드, 위원회명, 파일명, 등록시간, 수정시간 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15117649/fileData.do

Alerts

수정자 has constant value ""Constant
공개여부 has constant value ""Constant
작성자 has constant value ""Constant
의회아이디 has constant value ""Constant
최근회의력여부 has constant value ""Constant
파일명 has 111 (11.1%) missing valuesMissing
행정사무감사 has 907 (90.7%) missing valuesMissing
원본파일명 has 111 (11.1%) missing valuesMissing
고유번호 has unique valuesUnique
회의록고유번호 has unique valuesUnique
텍스트파일명 has unique valuesUnique
XML파일명 has unique valuesUnique
차수 has 47 (4.7%) zerosZeros

Reproduction

Analysis started2023-12-12 18:49:11.965671
Analysis finished2023-12-12 18:49:12.965236
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고유번호
Real number (ℝ)

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4628.629
Minimum411
Maximum5374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T03:49:13.115409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum411
5-th percentile4121.95
Q14362.75
median4655.5
Q35010.25
95-th percentile5300.05
Maximum5374
Range4963
Interquartile range (IQR)647.5

Descriptive statistics

Standard deviation582.45696
Coefficient of variation (CV)0.1258379
Kurtosis15.385652
Mean4628.629
Median Absolute Deviation (MAD)322
Skewness-3.0102064
Sum4628629
Variance339256.11
MonotonicityStrictly increasing
2023-12-13T03:49:13.414415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
411 1
 
0.1%
4900 1
 
0.1%
4878 1
 
0.1%
4879 1
 
0.1%
4881 1
 
0.1%
4885 1
 
0.1%
4886 1
 
0.1%
4888 1
 
0.1%
4889 1
 
0.1%
4891 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
411 1
0.1%
783 1
0.1%
788 1
0.1%
1046 1
0.1%
1056 1
0.1%
1415 1
0.1%
1416 1
0.1%
1417 1
0.1%
1768 1
0.1%
1769 1
0.1%
ValueCountFrequency (%)
5374 1
0.1%
5369 1
0.1%
5368 1
0.1%
5367 1
0.1%
5366 1
0.1%
5365 1
0.1%
5361 1
0.1%
5359 1
0.1%
5356 1
0.1%
5355 1
0.1%

종료시간
Real number (ℝ)

Distinct352
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean738.955
Minimum0
Maximum1360
Zeros9
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T03:49:13.666379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile601
Q1614
median704
Q3871
95-th percentile1033.1
Maximum1360
Range1360
Interquartile range (IQR)257

Descriptive statistics

Standard deviation162.93057
Coefficient of variation (CV)0.22048781
Kurtosis3.0275726
Mean738.955
Median Absolute Deviation (MAD)92
Skewness-0.0016718771
Sum738955
Variance26546.369
MonotonicityNot monotonic
2023-12-13T03:49:13.941387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
602 44
 
4.4%
601 32
 
3.2%
604 27
 
2.7%
603 24
 
2.4%
610 20
 
2.0%
611 13
 
1.3%
605 12
 
1.2%
612 11
 
1.1%
606 10
 
1.0%
724 10
 
1.0%
Other values (342) 797
79.7%
ValueCountFrequency (%)
0 9
0.9%
547 1
 
0.1%
548 1
 
0.1%
549 1
 
0.1%
550 1
 
0.1%
556 1
 
0.1%
581 1
 
0.1%
582 1
 
0.1%
584 1
 
0.1%
585 1
 
0.1%
ValueCountFrequency (%)
1360 1
0.1%
1273 1
0.1%
1181 1
0.1%
1180 1
0.1%
1169 1
0.1%
1158 1
0.1%
1154 1
0.1%
1153 1
0.1%
1152 1
0.1%
1150 1
0.1%

위원회코드
Categorical

Distinct13
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
C801
240 
C501
239 
A011
150 
C601
117 
E011
67 
Other values (8)
187 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowA011
2nd rowC401
3rd rowC401
4th rowC801
5th rowC801

Common Values

ValueCountFrequency (%)
C801 240
24.0%
C501 239
23.9%
A011 150
15.0%
C601 117
11.7%
E011 67
 
6.7%
J501 47
 
4.7%
J801 39
 
3.9%
C901 38
 
3.8%
C701 36
 
3.6%
J901 13
 
1.3%
Other values (3) 14
 
1.4%

Length

2023-12-13T03:49:14.168224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
c801 240
24.0%
c501 239
23.9%
a011 150
15.0%
c601 117
11.7%
e011 67
 
6.7%
j501 47
 
4.7%
j801 39
 
3.9%
c901 38
 
3.8%
c701 36
 
3.6%
j901 13
 
1.3%
Other values (3) 14
 
1.4%

위원회명
Categorical

Distinct15
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
복지건설위원회
240 
기획행정위원회
239 
본회의
150 
의회운영위원회
117 
예산결산특별위원회
67 
Other values (10)
187 

Length

Max length32
Median length7
Mean length7.243
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row본회의
2nd row사회도시위원회
3rd row사회도시위원회
4th row복지건설위원회
5th row복지건설위원회

Common Values

ValueCountFrequency (%)
복지건설위원회 240
24.0%
기획행정위원회 239
23.9%
본회의 150
15.0%
의회운영위원회 117
11.7%
예산결산특별위원회 67
 
6.7%
기획행정위원회행정사무감사 40
 
4.0%
복지건설위원회행정사무감사 39
 
3.9%
행정도시위원회 38
 
3.8%
기획복지위원회 36
 
3.6%
사회도시위원회 7
 
0.7%
Other values (5) 27
 
2.7%

Length

2023-12-13T03:49:14.366347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
복지건설위원회 240
24.0%
기획행정위원회 239
23.9%
본회의 150
15.0%
의회운영위원회 117
11.7%
예산결산특별위원회 67
 
6.7%
기획행정위원회행정사무감사 40
 
4.0%
복지건설위원회행정사무감사 39
 
3.9%
행정도시위원회 38
 
3.8%
기획복지위원회 36
 
3.6%
사회도시위원회 7
 
0.7%
Other values (5) 27
 
2.7%

날짜_년월일
Date

Distinct542
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
Minimum2002-08-19 00:00:00
Maximum2019-04-19 00:00:00
2023-12-13T03:49:14.588593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:49:14.812316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

날짜텍스트
Text

Distinct548
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-12-13T03:49:15.273883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14000
Distinct characters19
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

Unique187 ?
Unique (%)18.7%

Sample

1st row2009-10-27 화요일
2nd row2010-10-28 목요일
3rd row2010-11-03 수요일
4th row2013-03-14 목요일
5th row2013-07-10 수요일
ValueCountFrequency (%)
화요일 228
 
11.4%
수요일 219
 
10.9%
목요일 212
 
10.6%
월요일 171
 
8.6%
금요일 170
 
8.5%
2012-07-10 5
 
0.2%
2015-05-18 4
 
0.2%
2016-06-21 4
 
0.2%
2014-09-25 3
 
0.1%
2015-07-21 3
 
0.1%
Other values (537) 981
49.0%
2023-12-13T03:49:15.902823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2084
14.9%
0 2035
14.5%
- 2000
14.3%
2 1830
13.1%
1000
7.1%
요 1000
7.1%
일 1000
7.1%
7 370
 
2.6%
3 360
 
2.6%
6 311
 
2.2%
Other values (9) 2010
14.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8000
57.1%
Other Letter 3000
 
21.4%
Dash Punctuation 2000
 
14.3%
Space Separator 1000
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2084
26.1%
0 2035
25.4%
2 1830
22.9%
7 370
 
4.6%
3 360
 
4.5%
6 311
 
3.9%
8 278
 
3.5%
4 273
 
3.4%
5 268
 
3.4%
9 191
 
2.4%
Other Letter
ValueCountFrequency (%)
요 1000
33.3%
일 1000
33.3%
화 228
 
7.6%
수 219
 
7.3%
목 212
 
7.1%
월 171
 
5.7%
금 170
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Space Separator
ValueCountFrequency (%)
1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11000
78.6%
Hangul 3000
 
21.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2084
18.9%
0 2035
18.5%
- 2000
18.2%
2 1830
16.6%
1000
9.1%
7 370
 
3.4%
3 360
 
3.3%
6 311
 
2.8%
8 278
 
2.5%
4 273
 
2.5%
Other values (2) 459
 
4.2%
Hangul
ValueCountFrequency (%)
요 1000
33.3%
일 1000
33.3%
화 228
 
7.6%
수 219
 
7.3%
목 212
 
7.1%
월 171
 
5.7%
금 170
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11000
78.6%
Hangul 3000
 
21.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2084
18.9%
0 2035
18.5%
- 2000
18.2%
2 1830
16.6%
1000
9.1%
7 370
 
3.4%
3 360
 
3.3%
6 311
 
2.8%
8 278
 
2.5%
4 273
 
2.5%
Other values (2) 459
 
4.2%
Hangul
ValueCountFrequency (%)
요 1000
33.3%
일 1000
33.3%
화 228
 
7.6%
수 219
 
7.3%
목 212
 
7.1%
월 171
 
5.7%
금 170
 
5.7%

파일확장자
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
.hwp
889 
<NA>
111 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row.hwp
2nd row.hwp
3rd row.hwp
4th row.hwp
5th row.hwp

Common Values

ValueCountFrequency (%)
.hwp 889
88.9%
<NA> 111
 
11.1%

Length

2023-12-13T03:49:16.111799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:49:16.264939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
hwp 889
88.9%
na 111
 
11.1%

파일명
Text

MISSING 

Distinct889
Distinct (%)100.0%
Missing111
Missing (%)11.1%
Memory size7.9 KiB
2023-12-13T03:49:16.506353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters18669
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique889 ?
Unique (%)100.0%

Sample

1st row05A0110162021-3156204
2nd row06C4010170011-7219588
3rd row06C4010170051-7057459
4th row06C8010188031-2564149
5th row06C8010191021-4199090
ValueCountFrequency (%)
04c2010122011-6435917 1
 
0.1%
06c5010194012-4479040 1
 
0.1%
06c5010194022-7530138 1
 
0.1%
06c5010195012-0987262 1
 
0.1%
06c6010195013-1155658 1
 
0.1%
06c6010195011-0866573 1
 
0.1%
06c8010195011-4567225 1
 
0.1%
06c8010195022-6754298 1
 
0.1%
06c8010195031-4056103 1
 
0.1%
06c8010195041-7365713 1
 
0.1%
Other values (879) 879
98.9%
2023-12-13T03:49:16.962679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4477
24.0%
1 2968
15.9%
2 2098
11.2%
7 1284
 
6.9%
8 1197
 
6.4%
6 1145
 
6.1%
5 1041
 
5.6%
3 990
 
5.3%
9 898
 
4.8%
- 889
 
4.8%
Other values (4) 1682
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16891
90.5%
Dash Punctuation 889
 
4.8%
Uppercase Letter 889
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4477
26.5%
1 2968
17.6%
2 2098
12.4%
7 1284
 
7.6%
8 1197
 
7.1%
6 1145
 
6.8%
5 1041
 
6.2%
3 990
 
5.9%
9 898
 
5.3%
4 793
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
C 674
75.8%
A 149
 
16.8%
E 66
 
7.4%
Dash Punctuation
ValueCountFrequency (%)
- 889
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17780
95.2%
Latin 889
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4477
25.2%
1 2968
16.7%
2 2098
11.8%
7 1284
 
7.2%
8 1197
 
6.7%
6 1145
 
6.4%
5 1041
 
5.9%
3 990
 
5.6%
9 898
 
5.1%
- 889
 
5.0%
Latin
ValueCountFrequency (%)
C 674
75.8%
A 149
 
16.8%
E 66
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4477
24.0%
1 2968
15.9%
2 2098
11.2%
7 1284
 
6.9%
8 1197
 
6.4%
6 1145
 
6.1%
5 1041
 
5.6%
3 990
 
5.3%
9 898
 
4.8%
- 889
 
4.8%
Other values (4) 1682
 
9.0%

행정사무감사
Text

MISSING 

Distinct70
Distinct (%)75.3%
Missing907
Missing (%)90.7%
Memory size7.9 KiB
2023-12-13T03:49:17.209377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length33
Mean length22.913978
Min length10

Characters and Unicode

Total characters2131
Distinct characters109
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)65.6%

Sample

1st row남구청(동 주민센터)
2nd row남구청(동 주민센터(계속))
3rd row남구청(기획조정실ㆍ지혜로운시민실ㆍ미디어홍보실ㆍ감사실)
4th row남구청(평생학습관ㆍ총무과ㆍ안전관리과)
5th row남구청(재산회계과ㆍ문화예술과ㆍ세무1과ㆍ세무2과)
ValueCountFrequency (%)
남구청(동 12
 
8.9%
주민센터 9
 
6.7%
남구청(동주민센터 8
 
5.9%
미추홀구청(동 4
 
3.0%
숭의보건지소(현지감사 4
 
3.0%
주민센터(계속 3
 
2.2%
남구청(환경보전과 2
 
1.5%
건강증진과 2
 
1.5%
남구청(보건행정과 2
 
1.5%
건설과 2
 
1.5%
Other values (75) 87
64.4%
2023-12-13T03:49:17.713052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 177
 
8.3%
ㆍ 135
 
6.3%
( 109
 
5.1%
) 108
 
5.1%
구 96
 
4.5%
청 95
 
4.5%
남 82
 
3.8%
지 60
 
2.8%
정 53
 
2.5%
보 45
 
2.1%
Other values (99) 1171
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1828
85.8%
Open Punctuation 109
 
5.1%
Close Punctuation 108
 
5.1%
Space Separator 42
 
2.0%
Other Punctuation 32
 
1.5%
Decimal Number 12
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 177
 
9.7%
ㆍ 135
 
7.4%
구 96
 
5.3%
청 95
 
5.2%
남 82
 
4.5%
지 60
 
3.3%
정 53
 
2.9%
보 45
 
2.5%
민 36
 
2.0%
건 35
 
1.9%
Other values (92) 1014
55.5%
Other Punctuation
ValueCountFrequency (%)
, 24
75.0%
? 8
 
25.0%
Decimal Number
ValueCountFrequency (%)
1 6
50.0%
2 6
50.0%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Close Punctuation
ValueCountFrequency (%)
) 108
100.0%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1828
85.8%
Common 303
 
14.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 177
 
9.7%
ㆍ 135
 
7.4%
구 96
 
5.3%
청 95
 
5.2%
남 82
 
4.5%
지 60
 
3.3%
정 53
 
2.9%
보 45
 
2.5%
민 36
 
2.0%
건 35
 
1.9%
Other values (92) 1014
55.5%
Common
ValueCountFrequency (%)
( 109
36.0%
) 108
35.6%
42
 
13.9%
, 24
 
7.9%
? 8
 
2.6%
1 6
 
2.0%
2 6
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1693
79.4%
ASCII 303
 
14.2%
Compat Jamo 135
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 177
 
10.5%
구 96
 
5.7%
청 95
 
5.6%
남 82
 
4.8%
지 60
 
3.5%
정 53
 
3.1%
보 45
 
2.7%
민 36
 
2.1%
건 35
 
2.1%
관 32
 
1.9%
Other values (91) 982
58.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 135
100.0%
ASCII
ValueCountFrequency (%)
( 109
36.0%
) 108
35.6%
42
 
13.9%
, 24
 
7.9%
? 8
 
2.6%
1 6
 
2.0%
2 6
 
2.0%

수정자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
jeyun
1000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
jeyun 1000
100.0%

Length

2023-12-13T03:49:17.887285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:49:18.032139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
jeyun 1000
100.0%

시작시간
Real number (ℝ)

Distinct126
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean610.671
Minimum0
Maximum1142
Zeros9
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T03:49:18.188332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile600
Q1601
median603
Q3610
95-th percentile681
Maximum1142
Range1142
Interquartile range (IQR)9

Descriptive statistics

Standard deviation78.448728
Coefficient of variation (CV)0.12846316
Kurtosis41.403624
Mean610.671
Median Absolute Deviation (MAD)2
Skewness-2.2209672
Sum610671
Variance6154.203
MonotonicityNot monotonic
2023-12-13T03:49:18.418223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
601 174
17.4%
602 138
13.8%
600 127
12.7%
603 92
 
9.2%
604 70
 
7.0%
605 40
 
4.0%
610 36
 
3.6%
612 24
 
2.4%
606 23
 
2.3%
611 19
 
1.9%
Other values (116) 257
25.7%
ValueCountFrequency (%)
0 9
0.9%
545 2
 
0.2%
547 1
 
0.1%
548 1
 
0.1%
552 1
 
0.1%
571 1
 
0.1%
578 1
 
0.1%
580 1
 
0.1%
581 1
 
0.1%
583 1
 
0.1%
ValueCountFrequency (%)
1142 1
0.1%
1133 1
0.1%
1084 1
0.1%
1063 1
0.1%
1057 1
0.1%
1050 1
0.1%
1005 1
0.1%
986 1
0.1%
975 1
0.1%
912 1
0.1%

차수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.003
Minimum0
Maximum11
Zeros47
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T03:49:18.648432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q34
95-th percentile8
Maximum11
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3401853
Coefficient of variation (CV)0.7792825
Kurtosis0.31373981
Mean3.003
Median Absolute Deviation (MAD)1
Skewness1.0369582
Sum3003
Variance5.4764675
MonotonicityNot monotonic
2023-12-13T03:49:18.865799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 301
30.1%
2 195
19.5%
3 122
12.2%
4 101
 
10.1%
5 76
 
7.6%
6 52
 
5.2%
0 47
 
4.7%
7 42
 
4.2%
8 29
 
2.9%
9 27
 
2.7%
Other values (2) 8
 
0.8%
ValueCountFrequency (%)
0 47
 
4.7%
1 301
30.1%
2 195
19.5%
3 122
12.2%
4 101
 
10.1%
5 76
 
7.6%
6 52
 
5.2%
7 42
 
4.2%
8 29
 
2.9%
9 27
 
2.7%
ValueCountFrequency (%)
11 1
 
0.1%
10 7
 
0.7%
9 27
 
2.7%
8 29
 
2.9%
7 42
 
4.2%
6 52
 
5.2%
5 76
 
7.6%
4 101
10.1%
3 122
12.2%
2 195
19.5%

차수텍스트
Categorical

Distinct13
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
제1차
301 
제2차
195 
제3차
122 
제4차
101 
제5차
76 
Other values (8)
205 

Length

Max length4
Median length3
Mean length3.008
Min length3

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row제2차
2nd row제1차
3rd row제5차
4th row제3차
5th row제2차

Common Values

ValueCountFrequency (%)
제1차 301
30.1%
제2차 195
19.5%
제3차 122
12.2%
제4차 101
 
10.1%
제5차 76
 
7.6%
제6차 52
 
5.2%
개회식 46
 
4.6%
제7차 42
 
4.2%
제8차 29
 
2.9%
제9차 27
 
2.7%
Other values (3) 9
 
0.9%

Length

2023-12-13T03:49:19.089586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제1차 301
30.1%
제2차 195
19.5%
제3차 122
12.2%
제4차 101
 
10.1%
제5차 76
 
7.6%
제6차 52
 
5.2%
개회식 46
 
4.6%
제7차 42
 
4.2%
제8차 29
 
2.9%
제9차 27
 
2.7%
Other values (3) 9
 
0.9%

원본파일명
Text

MISSING 

Distinct889
Distinct (%)100.0%
Missing111
Missing (%)11.1%
Memory size7.9 KiB
2023-12-13T03:49:19.437291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters15113
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique889 ?
Unique (%)100.0%

Sample

1st row05A0110162021.hwp
2nd row06C4010170011.hwp
3rd row06C4010170051.hwp
4th row06C8010188031.hwp
5th row06C8010191021.hwp
ValueCountFrequency (%)
04c2010122011.hwp 1
 
0.1%
06c5010194012.hwp 1
 
0.1%
06c5010194022.hwp 1
 
0.1%
06c5010195012.hwp 1
 
0.1%
06c6010195013.hwp 1
 
0.1%
06c6010195011.hwp 1
 
0.1%
06c8010195011.hwp 1
 
0.1%
06c8010195022.hwp 1
 
0.1%
06c8010195031.hwp 1
 
0.1%
06c8010195041.hwp 1
 
0.1%
Other values (879) 879
98.9%
2023-12-13T03:49:20.032240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3831
25.3%
1 2311
15.3%
2 1493
 
9.9%
h 889
 
5.9%
w 889
 
5.9%
p 889
 
5.9%
. 889
 
5.9%
C 674
 
4.5%
7 659
 
4.4%
8 610
 
4.0%
Other values (7) 1979
13.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10668
70.6%
Lowercase Letter 2667
 
17.6%
Other Punctuation 889
 
5.9%
Uppercase Letter 889
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3831
35.9%
1 2311
21.7%
2 1493
 
14.0%
7 659
 
6.2%
8 610
 
5.7%
6 533
 
5.0%
5 398
 
3.7%
3 357
 
3.3%
9 276
 
2.6%
4 200
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
h 889
33.3%
w 889
33.3%
p 889
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 674
75.8%
A 149
 
16.8%
E 66
 
7.4%
Other Punctuation
ValueCountFrequency (%)
. 889
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11557
76.5%
Latin 3556
 
23.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3831
33.1%
1 2311
20.0%
2 1493
 
12.9%
. 889
 
7.7%
7 659
 
5.7%
8 610
 
5.3%
6 533
 
4.6%
5 398
 
3.4%
3 357
 
3.1%
9 276
 
2.4%
Latin
ValueCountFrequency (%)
h 889
25.0%
w 889
25.0%
p 889
25.0%
C 674
19.0%
A 149
 
4.2%
E 66
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15113
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3831
25.3%
1 2311
15.3%
2 1493
 
9.9%
h 889
 
5.9%
w 889
 
5.9%
p 889
 
5.9%
. 889
 
5.9%
C 674
 
4.5%
7 659
 
4.4%
8 610
 
4.0%
Other values (7) 1979
13.1%

회의록고유번호
Real number (ℝ)

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4628.629
Minimum411
Maximum5374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T03:49:20.277617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum411
5-th percentile4121.95
Q14362.75
median4655.5
Q35010.25
95-th percentile5300.05
Maximum5374
Range4963
Interquartile range (IQR)647.5

Descriptive statistics

Standard deviation582.45696
Coefficient of variation (CV)0.1258379
Kurtosis15.385652
Mean4628.629
Median Absolute Deviation (MAD)322
Skewness-3.0102064
Sum4628629
Variance339256.11
MonotonicityStrictly increasing
2023-12-13T03:49:20.524199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
411 1
 
0.1%
4900 1
 
0.1%
4878 1
 
0.1%
4879 1
 
0.1%
4881 1
 
0.1%
4885 1
 
0.1%
4886 1
 
0.1%
4888 1
 
0.1%
4889 1
 
0.1%
4891 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
411 1
0.1%
783 1
0.1%
788 1
0.1%
1046 1
0.1%
1056 1
0.1%
1415 1
0.1%
1416 1
0.1%
1417 1
0.1%
1768 1
0.1%
1769 1
0.1%
ValueCountFrequency (%)
5374 1
0.1%
5369 1
0.1%
5368 1
0.1%
5367 1
0.1%
5366 1
0.1%
5365 1
0.1%
5361 1
0.1%
5359 1
0.1%
5356 1
0.1%
5355 1
0.1%

회기
Real number (ℝ)

Distinct73
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean207.15
Minimum92
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T03:49:20.728800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum92
5-th percentile178.95
Q1191
median209
Q3225
95-th percentile237
Maximum240
Range148
Interquartile range (IQR)34

Descriptive statistics

Standard deviation21.366844
Coefficient of variation (CV)0.10314673
Kurtosis2.5683526
Mean207.15
Median Absolute Deviation (MAD)16.5
Skewness-0.92590251
Sum207150
Variance456.54204
MonotonicityNot monotonic
2023-12-13T03:49:20.946165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
237 46
 
4.6%
221 44
 
4.4%
229 43
 
4.3%
203 42
 
4.2%
212 40
 
4.0%
194 38
 
3.8%
186 38
 
3.8%
183 29
 
2.9%
209 27
 
2.7%
191 27
 
2.7%
Other values (63) 626
62.6%
ValueCountFrequency (%)
92 1
 
0.1%
98 1
 
0.1%
118 3
0.3%
122 7
0.7%
124 1
 
0.1%
153 1
 
0.1%
155 1
 
0.1%
162 1
 
0.1%
170 2
 
0.2%
177 7
0.7%
ValueCountFrequency (%)
240 6
 
0.6%
239 8
 
0.8%
238 10
 
1.0%
237 46
4.6%
236 13
 
1.3%
235 25
2.5%
234 14
 
1.4%
233 6
 
0.6%
232 3
 
0.3%
231 12
 
1.2%

공개여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
True
1000 
ValueCountFrequency (%)
True 1000
100.0%
2023-12-13T03:49:21.120425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

텍스트파일경로
Categorical

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
<NA>
524 
[정례회]
401 
[폐회중]
64 
[정례회][폐회중]
 
6
[임시회]
 
5

Length

Max length10
Median length4
Mean length4.506
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row[정례회]

Common Values

ValueCountFrequency (%)
<NA> 524
52.4%
[정례회] 401
40.1%
[폐회중] 64
 
6.4%
[정례회][폐회중] 6
 
0.6%
[임시회] 5
 
0.5%

Length

2023-12-13T03:49:21.277569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:49:21.416641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 524
52.4%
정례회 401
40.1%
폐회중 64
 
6.4%
정례회][폐회중 6
 
0.6%
임시회 5
 
0.5%

텍스트파일명
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-12-13T03:49:21.678157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17000
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row05A0110162021.txt
2nd row06C4010170011.txt
3rd row06C4010170051.txt
4th row06C8010188031.txt
5th row06C8010191021.txt
ValueCountFrequency (%)
05a0110162021.txt 1
 
0.1%
08c7010235042.txt 1
 
0.1%
06c6010195013.txt 1
 
0.1%
06c8010194051.txt 1
 
0.1%
06c6010195011.txt 1
 
0.1%
06c8010195011.txt 1
 
0.1%
06c8010195022.txt 1
 
0.1%
06c8010195031.txt 1
 
0.1%
06c8010195041.txt 1
 
0.1%
06c8010195052.txt 1
 
0.1%
Other values (990) 990
99.0%
2023-12-13T03:49:22.208668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4295
25.3%
1 2560
15.1%
t 2000
11.8%
2 1689
 
9.9%
. 1000
 
5.9%
x 1000
 
5.9%
7 749
 
4.4%
8 685
 
4.0%
C 683
 
4.0%
6 606
 
3.6%
Other values (8) 1733
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12000
70.6%
Lowercase Letter 3000
 
17.6%
Other Punctuation 1000
 
5.9%
Uppercase Letter 1000
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4295
35.8%
1 2560
21.3%
2 1689
 
14.1%
7 749
 
6.2%
8 685
 
5.7%
6 606
 
5.1%
5 459
 
3.8%
3 406
 
3.4%
9 324
 
2.7%
4 227
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 683
68.3%
A 150
 
15.0%
J 99
 
9.9%
E 67
 
6.7%
G 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
t 2000
66.7%
x 1000
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13000
76.5%
Latin 4000
 
23.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4295
33.0%
1 2560
19.7%
2 1689
 
13.0%
. 1000
 
7.7%
7 749
 
5.8%
8 685
 
5.3%
6 606
 
4.7%
5 459
 
3.5%
3 406
 
3.1%
9 324
 
2.5%
Latin
ValueCountFrequency (%)
t 2000
50.0%
x 1000
25.0%
C 683
 
17.1%
A 150
 
3.8%
J 99
 
2.5%
E 67
 
1.7%
G 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4295
25.3%
1 2560
15.1%
t 2000
11.8%
2 1689
 
9.9%
. 1000
 
5.9%
x 1000
 
5.9%
7 749
 
4.4%
8 685
 
4.0%
C 683
 
4.0%
6 606
 
3.6%
Other values (8) 1733
10.2%

대수
Categorical

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
7
527 
6
329 
8
128 
4
 
13
5
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row6
3rd row6
4th row6
5th row6

Common Values

ValueCountFrequency (%)
7 527
52.7%
6 329
32.9%
8 128
 
12.8%
4 13
 
1.3%
5 3
 
0.3%

Length

2023-12-13T03:49:22.941746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:49:23.111288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 527
52.7%
6 329
32.9%
8 128
 
12.8%
4 13
 
1.3%
5 3
 
0.3%

등록시간_년월시분초
Date

Distinct30
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
Minimum2019-06-24 10:05:00
Maximum2019-06-24 20:09:00
2023-12-13T03:49:23.283469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:49:23.508040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

수정시간_년월시분초
Date

Distinct765
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
Minimum2019-06-24 11:06:00
Maximum2019-07-12 11:00:00
2023-12-13T03:49:23.765969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:49:24.055263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

작성자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
jeyun
1000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
jeyun 1000
100.0%

Length

2023-12-13T03:49:24.325454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:49:24.517133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
jeyun 1000
100.0%

XML파일명
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2023-12-13T03:49:24.826413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17000
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row05A0110162021.xml
2nd row06C4010170011.xml
3rd row06C4010170051.xml
4th row06C8010188031.xml
5th row06C8010191021.xml
ValueCountFrequency (%)
05a0110162021.xml 1
 
0.1%
08c7010235042.xml 1
 
0.1%
06c6010195013.xml 1
 
0.1%
06c8010194051.xml 1
 
0.1%
06c6010195011.xml 1
 
0.1%
06c8010195011.xml 1
 
0.1%
06c8010195022.xml 1
 
0.1%
06c8010195031.xml 1
 
0.1%
06c8010195041.xml 1
 
0.1%
06c8010195052.xml 1
 
0.1%
Other values (990) 990
99.0%
2023-12-13T03:49:25.388633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4295
25.3%
1 2560
15.1%
2 1689
 
9.9%
. 1000
 
5.9%
m 1000
 
5.9%
x 1000
 
5.9%
l 1000
 
5.9%
7 749
 
4.4%
8 685
 
4.0%
C 683
 
4.0%
Other values (9) 2339
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12000
70.6%
Lowercase Letter 3000
 
17.6%
Other Punctuation 1000
 
5.9%
Uppercase Letter 1000
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4295
35.8%
1 2560
21.3%
2 1689
 
14.1%
7 749
 
6.2%
8 685
 
5.7%
6 606
 
5.1%
5 459
 
3.8%
3 406
 
3.4%
9 324
 
2.7%
4 227
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 683
68.3%
A 150
 
15.0%
J 99
 
9.9%
E 67
 
6.7%
G 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
m 1000
33.3%
x 1000
33.3%
l 1000
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13000
76.5%
Latin 4000
 
23.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4295
33.0%
1 2560
19.7%
2 1689
 
13.0%
. 1000
 
7.7%
7 749
 
5.8%
8 685
 
5.3%
6 606
 
4.7%
5 459
 
3.5%
3 406
 
3.1%
9 324
 
2.5%
Latin
ValueCountFrequency (%)
m 1000
25.0%
x 1000
25.0%
l 1000
25.0%
C 683
17.1%
A 150
 
3.8%
J 99
 
2.5%
E 67
 
1.7%
G 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4295
25.3%
1 2560
15.1%
2 1689
 
9.9%
. 1000
 
5.9%
m 1000
 
5.9%
x 1000
 
5.9%
l 1000
 
5.9%
7 749
 
4.4%
8 685
 
4.0%
C 683
 
4.0%
Other values (9) 2339
13.8%

년도
Real number (ℝ)

Distinct14
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.792
Minimum2002
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.9 KiB
2023-12-13T03:49:25.583018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2012
Q12013
median2015
Q32017
95-th percentile2018
Maximum2019
Range17
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.49057
Coefficient of variation (CV)0.0012361425
Kurtosis2.287001
Mean2014.792
Median Absolute Deviation (MAD)2
Skewness-0.8627304
Sum2014792
Variance6.2029389
MonotonicityNot monotonic
2023-12-13T03:49:25.762424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2012 143
14.3%
2016 141
14.1%
2015 131
13.1%
2018 131
13.1%
2014 131
13.1%
2017 126
12.6%
2013 124
12.4%
2011 30
 
3.0%
2019 25
 
2.5%
2005 11
 
1.1%
Other values (4) 7
 
0.7%
ValueCountFrequency (%)
2002 2
 
0.2%
2005 11
 
1.1%
2008 2
 
0.2%
2009 1
 
0.1%
2010 2
 
0.2%
2011 30
 
3.0%
2012 143
14.3%
2013 124
12.4%
2014 131
13.1%
2015 131
13.1%
ValueCountFrequency (%)
2019 25
 
2.5%
2018 131
13.1%
2017 126
12.6%
2016 141
14.1%
2015 131
13.1%
2014 131
13.1%
2013 124
12.4%
2012 143
14.3%
2011 30
 
3.0%
2010 2
 
0.2%

의회아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
MICHU
1000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
MICHU 1000
100.0%

Length

2023-12-13T03:49:25.957384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:49:26.135499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
michu 1000
100.0%

최근회의력여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
True
1000 
ValueCountFrequency (%)
True 1000
100.0%
2023-12-13T03:49:26.258223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

고유번호종료시간위원회코드위원회명날짜_년월일날짜텍스트파일확장자파일명행정사무감사수정자시작시간차수차수텍스트원본파일명회의록고유번호회기공개여부텍스트파일경로텍스트파일명대수등록시간_년월시분초수정시간_년월시분초작성자XML파일명년도의회아이디최근회의력여부
04111023A011본회의2009-10-272009-10-27 화요일.hwp05A0110162021-3156204<NA>jeyun6022제2차05A0110162021.hwp411162Y<NA>05A0110162021.txt52019-06-24 11:062019-06-24 11:06jeyun05A0110162021.xml2009MICHUY
1783898C401사회도시위원회2010-10-282010-10-28 목요일.hwp06C4010170011-7219588<NA>jeyun6011제1차06C4010170011.hwp783170Y<NA>06C4010170011.txt62019-06-24 13:242019-06-24 13:24jeyun06C4010170011.xml2010MICHUY
2788718C401사회도시위원회2010-11-032010-11-03 수요일.hwp06C4010170051-7057459<NA>jeyun6015제5차06C4010170051.hwp788170Y<NA>06C4010170051.txt62019-06-24 13:242019-06-24 13:24jeyun06C4010170051.xml2010MICHUY
31046605C801복지건설위원회2013-03-142013-03-14 목요일.hwp06C8010188031-2564149<NA>jeyun6043제3차06C8010188031.hwp1046188Y<NA>06C8010188031.txt62019-06-24 14:232019-06-24 14:23jeyun06C8010188031.xml2013MICHUY
41056890C801복지건설위원회2013-07-102013-07-10 수요일.hwp06C8010191021-4199090<NA>jeyun6032제2차06C8010191021.hwp1056191Y[정례회]06C8010191021.txt62019-06-24 14:232019-06-24 14:23jeyun06C8010191021.xml2013MICHUY
514151006A011본회의2005-07-112005-07-11 월요일.hwp04A0110122021-5793590<NA>jeyun6022제2차04A0110122021.hwp1415122Y[정례회]04A0110122021.txt42019-06-24 15:222019-06-24 15:22jeyun04A0110122021.xml2005MICHUY
61416635A011본회의2005-07-182005-07-18 월요일.hwp04A0110122031-4113831<NA>jeyun6023제3차04A0110122031.hwp1416122Y[정례회]04A0110122031.txt42019-06-24 15:222019-06-24 15:22jeyun04A0110122031.xml2005MICHUY
71417655A011본회의2005-07-082005-07-08 금요일.hwp04A0110122011-0436438<NA>jeyun6101제1차04A0110122011.hwp1417122Y[정례회]04A0110122011.txt42019-06-24 15:222019-06-24 15:22jeyun04A0110122011.xml2005MICHUY
81768740C401사회도시위원회2005-01-312005-01-31 월요일.hwp04C4010118021-2056300<NA>jeyun6022제2차04C4010118021.hwp1768118Y<NA>04C4010118021.txt42019-06-24 16:072019-06-24 16:07jeyun04C4010118021.xml2005MICHUY
91769745C401사회도시위원회2005-02-012005-02-01 화요일.hwp04C4010118031-1547847<NA>jeyun6103제3차04C4010118031.hwp1769118Y<NA>04C4010118031.txt42019-06-24 16:072019-06-24 16:07jeyun04C4010118031.xml2005MICHUY
고유번호종료시간위원회코드위원회명날짜_년월일날짜텍스트파일확장자파일명행정사무감사수정자시작시간차수차수텍스트원본파일명회의록고유번호회기공개여부텍스트파일경로텍스트파일명대수등록시간_년월시분초수정시간_년월시분초작성자XML파일명년도의회아이디최근회의력여부
9905355920E011예산결산특별위원회2011-12-152011-12-15 목요일.hwp06E0110178032-1667025<NA>jeyun6323제3차06E0110178032.hwp5355178Y[정례회]06E0110178032.txt62019-06-24 14:232019-07-12 10:11jeyun06E0110178032.xml2011MICHUY
99153561169E011예산결산특별위원회2011-12-162011-12-16 금요일.hwp06E0110178042-2887841<NA>jeyun6124제4차06E0110178042.hwp5356178Y[정례회]06E0110178042.txt62019-06-24 14:232019-07-12 10:11jeyun06E0110178042.xml2011MICHUY
9925359602J501기획복지위원회행정사무감사2018-11-212018-11-21 수요일<NA><NA>미추홀구청(동 행정복지센터)jeyun6001제1차<NA>5359237Y[정례회]08J5010237011.txt82019-06-24 10:232019-07-12 10:44jeyun08J5010237011.xml2018MICHUY
9935361612A011본회의2011-10-252011-10-25 화요일.hwp06A0110177002-2983587<NA>jeyun6120개회식06A0110177002.hwp5361177Y<NA>06A0110177002.txt62019-06-24 11:132019-07-12 10:47jeyun06A0110177002.xml2011MICHUY
9945365620A011본회의2011-10-252011-10-25 화요일.hwp06A0110177011-3575606<NA>jeyun6121제1차06A0110177011.hwp5365177Y<NA>06A0110177011.txt62019-06-24 11:132019-07-12 10:51jeyun06A0110177011.xml2011MICHUY
9955366630A011본회의2011-11-032011-11-03 목요일.hwp06A0110177021-7446696<NA>jeyun6052제2차06A0110177021.hwp5366177Y<NA>06A0110177021.txt62019-06-24 11:132019-07-12 10:51jeyun06A0110177021.xml2011MICHUY
9965367756C501기획행정위원회2011-10-262011-10-26 수요일.hwp06C5010177012-8484610<NA>jeyun6041제1차06C5010177012.hwp5367177Y<NA>06C5010177012.txt62019-06-24 14:052019-07-12 10:52jeyun06C5010177012.xml2011MICHUY
9975368913C501기획행정위원회2011-10-272011-10-27 목요일.hwp06C5010177022-8409344<NA>jeyun6042제2차06C5010177022.hwp5368177Y<NA>06C5010177022.txt62019-06-24 14:052019-07-12 10:55jeyun06C5010177022.xml2011MICHUY
99853691026C501기획행정위원회2011-10-282011-10-28 금요일.hwp06C5010177032-9216393<NA>jeyun6033제3차06C5010177032.hwp5369177Y<NA>06C5010177032.txt62019-06-24 14:052019-07-12 10:55jeyun06C5010177032.xml2011MICHUY
9995374913C501기획행정위원회2011-10-312011-10-31 월요일.hwp06C5010177042-0209356<NA>jeyun6034제4차06C5010177042.hwp5374177Y<NA>06C5010177042.txt62019-06-24 19:402019-07-12 11:00jeyun06C5010177042.xml2011MICHUY