Overview

Dataset statistics

Number of variables12
Number of observations3339
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory326.2 KiB
Average record size in memory100.0 B

Variable types

Numeric4
DateTime1
Categorical4
Boolean2
Text1

Dataset

Description남양주시 의회 회의록 목록에 대한 데이터로 년도, 대수, 회수, 차수, 회의날짜, 회의구분, 회의명, 회의정보 등의 항목을 제공합니다.
Author경기도 남양주시
URLhttps://www.data.go.kr/data/15067368/fileData.do

Alerts

데이터기준일 has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
년도 is highly overall correlated with 대수 and 1 other fieldsHigh correlation
대수 is highly overall correlated with 년도 and 1 other fieldsHigh correlation
회기 is highly overall correlated with 년도 and 1 other fieldsHigh correlation
회의명 is highly overall correlated with 임시회의록구분High correlation
임시회의록구분 is highly overall correlated with 회의명High correlation
안건유무 is highly imbalanced (53.8%)Imbalance
임시회의록구분 is highly imbalanced (85.8%)Imbalance
차수 has 291 (8.7%) zerosZeros

Reproduction

Analysis started2024-03-14 12:22:08.516871
Analysis finished2024-03-14 12:22:13.952725
Duration5.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2009.3055
Minimum1995
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.5 KiB
2024-03-14T21:22:14.108625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1995
5-th percentile1996
Q12002
median2010
Q32017
95-th percentile2023
Maximum2024
Range29
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.7720007
Coefficient of variation (CV)0.0043656879
Kurtosis-1.2546795
Mean2009.3055
Median Absolute Deviation (MAD)8
Skewness-0.069656419
Sum6709071
Variance76.947996
MonotonicityDecreasing
2024-03-14T21:22:14.503022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1995 157
 
4.7%
2023 156
 
4.7%
1996 147
 
4.4%
2022 138
 
4.1%
2011 125
 
3.7%
2017 122
 
3.7%
2020 119
 
3.6%
2019 118
 
3.5%
2016 118
 
3.5%
1998 117
 
3.5%
Other values (20) 2022
60.6%
ValueCountFrequency (%)
1995 157
4.7%
1996 147
4.4%
1997 109
3.3%
1998 117
3.5%
1999 103
3.1%
2000 105
3.1%
2001 96
2.9%
2002 99
3.0%
2003 106
3.2%
2004 102
3.1%
ValueCountFrequency (%)
2024 12
 
0.4%
2023 156
4.7%
2022 138
4.1%
2021 115
3.4%
2020 119
3.6%
2019 118
3.5%
2018 116
3.5%
2017 122
3.7%
2016 118
3.5%
2015 116
3.5%

대수
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3788559
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.5 KiB
2024-03-14T21:22:14.856882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q37
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.241671
Coefficient of variation (CV)0.4167561
Kurtosis-1.1560096
Mean5.3788559
Median Absolute Deviation (MAD)2
Skewness-0.071824445
Sum17960
Variance5.025089
MonotonicityDecreasing
2024-03-14T21:22:15.217076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
8 471
14.1%
7 470
14.1%
6 461
13.8%
3 425
12.7%
5 408
12.2%
4 396
11.9%
2 393
11.8%
9 267
8.0%
1 48
 
1.4%
ValueCountFrequency (%)
1 48
 
1.4%
2 393
11.8%
3 425
12.7%
4 396
11.9%
5 408
12.2%
6 461
13.8%
7 470
14.1%
8 471
14.1%
9 267
8.0%
ValueCountFrequency (%)
9 267
8.0%
8 471
14.1%
7 470
14.1%
6 461
13.8%
5 408
12.2%
4 396
11.9%
3 425
12.7%
2 393
11.8%
1 48
 
1.4%

회기
Real number (ℝ)

HIGH CORRELATION 

Distinct300
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean165.7074
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.5 KiB
2024-03-14T21:22:15.614881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19
Q186
median177
Q3244
95-th percentile292
Maximum300
Range299
Interquartile range (IQR)158

Descriptive statistics

Standard deviation89.045237
Coefficient of variation (CV)0.53736429
Kurtosis-1.216046
Mean165.7074
Median Absolute Deviation (MAD)77
Skewness-0.20770422
Sum553297
Variance7929.0543
MonotonicityNot monotonic
2024-03-14T21:22:16.055377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16 54
 
1.6%
299 52
 
1.6%
291 45
 
1.3%
29 45
 
1.3%
40 38
 
1.1%
247 37
 
1.1%
62 37
 
1.1%
238 37
 
1.1%
256 36
 
1.1%
52 36
 
1.1%
Other values (290) 2922
87.5%
ValueCountFrequency (%)
1 6
0.2%
2 4
 
0.1%
3 10
0.3%
4 5
0.1%
5 3
 
0.1%
6 8
0.2%
7 6
0.2%
8 4
 
0.1%
9 2
 
0.1%
10 5
0.1%
ValueCountFrequency (%)
300 11
 
0.3%
299 52
1.6%
298 12
 
0.4%
297 23
0.7%
296 7
 
0.2%
295 17
 
0.5%
294 26
0.8%
293 7
 
0.2%
292 16
 
0.5%
291 45
1.3%

차수
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6651692
Minimum0
Maximum20
Zeros291
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size29.5 KiB
2024-03-14T21:22:16.446982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile8
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.5941619
Coefficient of variation (CV)0.97335731
Kurtosis5.2253995
Mean2.6651692
Median Absolute Deviation (MAD)1
Skewness2.022888
Sum8899
Variance6.7296762
MonotonicityNot monotonic
2024-03-14T21:22:16.846631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1137
34.1%
2 720
21.6%
3 374
 
11.2%
0 291
 
8.7%
4 241
 
7.2%
5 155
 
4.6%
6 121
 
3.6%
7 95
 
2.8%
8 64
 
1.9%
9 46
 
1.4%
Other values (11) 95
 
2.8%
ValueCountFrequency (%)
0 291
 
8.7%
1 1137
34.1%
2 720
21.6%
3 374
 
11.2%
4 241
 
7.2%
5 155
 
4.6%
6 121
 
3.6%
7 95
 
2.8%
8 64
 
1.9%
9 46
 
1.4%
ValueCountFrequency (%)
20 1
 
< 0.1%
19 1
 
< 0.1%
18 1
 
< 0.1%
17 2
 
0.1%
16 3
 
0.1%
15 4
 
0.1%
14 7
 
0.2%
13 12
0.4%
12 16
0.5%
11 19
0.6%

회의날짜
Date

Distinct1841
Distinct (%)55.1%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
Minimum1995-01-03 00:00:00
Maximum2024-01-31 00:00:00
2024-03-14T21:22:17.257541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:17.867539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

회의요일
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
화요일
692 
수요일
659 
월요일
649 
목요일
637 
금요일
625 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수요일
2nd row화요일
3rd row화요일
4th row월요일
5th row월요일

Common Values

ValueCountFrequency (%)
화요일 692
20.7%
수요일 659
19.7%
월요일 649
19.4%
목요일 637
19.1%
금요일 625
18.7%
토요일 77
 
2.3%

Length

2024-03-14T21:22:18.085468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:22:18.280498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화요일 692
20.7%
수요일 659
19.7%
월요일 649
19.4%
목요일 637
19.1%
금요일 625
18.7%
토요일 77
 
2.3%

회의구분
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
임시회
1955 
제2차정례회
535 
제1차정례회
354 
<NA>
215 
제2차 정례회
200 

Length

Max length7
Median length3
Mean length4.1985624
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
임시회 1955
58.6%
제2차정례회 535
 
16.0%
제1차정례회 354
 
10.6%
<NA> 215
 
6.4%
제2차 정례회 200
 
6.0%
제1차 정례회 80
 
2.4%

Length

2024-03-14T21:22:18.512466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:22:18.721937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임시회 1955
54.0%
제2차정례회 535
 
14.8%
제1차정례회 354
 
9.8%
정례회 280
 
7.7%
na 215
 
5.9%
제2차 200
 
5.5%
제1차 80
 
2.2%

안건유무
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
True
3012 
False
327 
ValueCountFrequency (%)
True 3012
90.2%
False 327
 
9.8%
2024-03-14T21:22:18.972053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

회의명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
본회의
958 
산업건설위원회
740 
자치행정위원회
596 
내무위원회
217 
예산결산특별위원회
210 
Other values (16)
618 

Length

Max length36
Median length32
Mean length6.4097035
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row본회의
2nd row복지환경위원회
3rd row도시교통위원회
4th row복지환경위원회
5th row도시교통위원회

Common Values

ValueCountFrequency (%)
본회의 958
28.7%
산업건설위원회 740
22.2%
자치행정위원회 596
17.8%
내무위원회 217
 
6.5%
예산결산특별위원회 210
 
6.3%
운영위원회 157
 
4.7%
산업건설위원회행정사무감사 138
 
4.1%
자치행정위원회행정사무감사 121
 
3.6%
복지환경위원회 56
 
1.7%
도시교통위원회 53
 
1.6%
Other values (11) 93
 
2.8%

Length

2024-03-14T21:22:19.352283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
본회의 958
28.7%
산업건설위원회 740
22.2%
자치행정위원회 596
17.8%
내무위원회 217
 
6.5%
예산결산특별위원회 210
 
6.3%
운영위원회 157
 
4.7%
산업건설위원회행정사무감사 138
 
4.1%
자치행정위원회행정사무감사 121
 
3.6%
복지환경위원회 56
 
1.7%
도시교통위원회 53
 
1.6%
Other values (11) 93
 
2.8%

회의정보
Text

Distinct3337
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
2024-03-14T21:22:20.930263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length62
Mean length32.237496
Min length27

Characters and Unicode

Total characters107641
Distinct characters107
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3336 ?
Unique (%)99.9%

Sample

1st row제300회 제2차 본회의(2024.01.31 수요일)
2nd row제300회 제4차 복지환경위원회(2024.01.30 화요일)
3rd row제300회 제4차 도시교통위원회(2024.01.30 화요일)
4th row제300회 제3차 복지환경위원회(2024.01.29 월요일)
5th row제300회 제3차 도시교통위원회(2024.01.29 월요일)
ValueCountFrequency (%)
제1차 1110
 
8.3%
제2차 707
 
5.3%
화요일 692
 
5.2%
수요일 659
 
4.9%
월요일 649
 
4.9%
목요일 637
 
4.8%
금요일 625
 
4.7%
제3차 366
 
2.7%
개회식 289
 
2.2%
제4차 238
 
1.8%
Other values (3370) 7384
55.3%
2024-03-14T21:22:22.917654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10017
 
9.3%
2 8698
 
8.1%
1 8593
 
8.0%
0 8187
 
7.6%
회 7031
 
6.5%
. 6678
 
6.2%
제 6387
 
5.9%
요 3341
 
3.1%
) 3339
 
3.1%
일 3339
 
3.1%
Other values (97) 42031
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45257
42.0%
Decimal Number 38883
36.1%
Space Separator 10017
 
9.3%
Other Punctuation 6678
 
6.2%
Close Punctuation 3403
 
3.2%
Open Punctuation 3403
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 7031
15.5%
제 6387
14.1%
요 3341
 
7.4%
일 3339
 
7.4%
차 3048
 
6.7%
원 2383
 
5.3%
위 2381
 
5.3%
산 1298
 
2.9%
정 1059
 
2.3%
행 1057
 
2.3%
Other values (81) 13933
30.8%
Decimal Number
ValueCountFrequency (%)
2 8698
22.4%
1 8593
22.1%
0 8187
21.1%
9 3021
 
7.8%
3 2027
 
5.2%
4 1783
 
4.6%
7 1777
 
4.6%
6 1670
 
4.3%
5 1645
 
4.2%
8 1482
 
3.8%
Close Punctuation
ValueCountFrequency (%)
) 3339
98.1%
] 64
 
1.9%
Open Punctuation
ValueCountFrequency (%)
( 3339
98.1%
[ 64
 
1.9%
Space Separator
ValueCountFrequency (%)
10017
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6678
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62384
58.0%
Hangul 45257
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 7031
15.5%
제 6387
14.1%
요 3341
 
7.4%
일 3339
 
7.4%
차 3048
 
6.7%
원 2383
 
5.3%
위 2381
 
5.3%
산 1298
 
2.9%
정 1059
 
2.3%
행 1057
 
2.3%
Other values (81) 13933
30.8%
Common
ValueCountFrequency (%)
10017
16.1%
2 8698
13.9%
1 8593
13.8%
0 8187
13.1%
. 6678
10.7%
) 3339
 
5.4%
( 3339
 
5.4%
9 3021
 
4.8%
3 2027
 
3.2%
4 1783
 
2.9%
Other values (6) 6702
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62384
58.0%
Hangul 45257
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10017
16.1%
2 8698
13.9%
1 8593
13.8%
0 8187
13.1%
. 6678
10.7%
) 3339
 
5.4%
( 3339
 
5.4%
9 3021
 
4.8%
3 2027
 
3.2%
4 1783
 
2.9%
Other values (6) 6702
10.7%
Hangul
ValueCountFrequency (%)
회 7031
15.5%
제 6387
14.1%
요 3341
 
7.4%
일 3339
 
7.4%
차 3048
 
6.7%
원 2383
 
5.3%
위 2381
 
5.3%
산 1298
 
2.9%
정 1059
 
2.3%
행 1057
 
2.3%
Other values (81) 13933
30.8%

임시회의록구분
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
True
3272 
False
 
67
ValueCountFrequency (%)
True 3272
98.0%
False 67
 
2.0%
2024-03-14T21:22:23.269531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
2024-02-15
3339 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-15
2nd row2024-02-15
3rd row2024-02-15
4th row2024-02-15
5th row2024-02-15

Common Values

ValueCountFrequency (%)
2024-02-15 3339
100.0%

Length

2024-03-14T21:22:23.600315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:22:23.895479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-15 3339
100.0%

Interactions

2024-03-14T21:22:12.222163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:09.630346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:10.679579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:11.439856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:12.397828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:09.899817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:10.892596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:11.608914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:12.587602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:10.182219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:11.078489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:11.806669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:12.823774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:10.453563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:11.252255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:22:12.039487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:22:24.086456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도대수회기차수회의요일회의구분안건유무회의명임시회의록구분
년도1.0000.9580.9780.1840.1900.6880.0800.6710.551
대수0.9581.0000.9410.1630.1970.5260.0700.6500.459
회기0.9780.9411.0000.1780.1840.6720.0760.5620.444
차수0.1840.1630.1781.0000.0690.5560.4050.7400.332
회의요일0.1900.1970.1840.0691.0000.0000.0540.0690.000
회의구분0.6880.5260.6720.5560.0001.0000.0990.5570.353
안건유무0.0800.0700.0760.4050.0540.0991.0000.5600.037
회의명0.6710.6500.5620.7400.0690.5570.5601.0000.587
임시회의록구분0.5510.4590.4440.3320.0000.3530.0370.5871.000
2024-03-14T21:22:24.391308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
안건유무회의요일회의구분회의명임시회의록구분
안건유무1.0000.0390.1220.4940.024
회의요일0.0391.0000.0000.0310.000
회의구분0.1220.0001.0000.3110.430
회의명0.4940.0310.3111.0000.519
임시회의록구분0.0240.0000.4300.5191.000
2024-03-14T21:22:24.672316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도대수회기차수회의요일회의구분안건유무회의명임시회의록구분
년도1.0000.9910.9990.0920.0960.3610.0610.2770.426
대수0.9911.0000.9920.1050.0990.3370.0700.3160.459
회기0.9990.9921.0000.1040.0980.3420.0580.2440.341
차수0.0920.1050.1041.0000.0310.2630.1840.3840.251
회의요일0.0960.0990.0980.0311.0000.0000.0390.0310.000
회의구분0.3610.3370.3420.2630.0001.0000.1220.3110.430
안건유무0.0610.0700.0580.1840.0390.1221.0000.4940.024
회의명0.2770.3160.2440.3840.0310.3110.4941.0000.519
임시회의록구분0.4260.4590.3410.2510.0000.4300.0240.5191.000

Missing values

2024-03-14T21:22:13.212110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:22:13.731812image/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

년도대수회기차수회의날짜회의요일회의구분안건유무회의명회의정보임시회의록구분데이터기준일
02024930022024-01-31수요일임시회Y본회의제300회 제2차 본회의(2024.01.31 수요일)N2024-02-15
12024930042024-01-30화요일임시회Y복지환경위원회제300회 제4차 복지환경위원회(2024.01.30 화요일)N2024-02-15
22024930042024-01-30화요일임시회Y도시교통위원회제300회 제4차 도시교통위원회(2024.01.30 화요일)N2024-02-15
32024930032024-01-29월요일임시회Y복지환경위원회제300회 제3차 복지환경위원회(2024.01.29 월요일)N2024-02-15
42024930032024-01-29월요일임시회Y도시교통위원회제300회 제3차 도시교통위원회(2024.01.29 월요일)N2024-02-15
52024930062024-01-29월요일임시회Y왕숙천유역공공하수처리시설설치사업등에관한행정사무조사특별위원회제300회 제6차 왕숙천유역공공하수처리시설설치사업등에관한행정사무조사특별위원회(2024.01.29 월요일)N2024-02-15
62024930022024-01-26금요일임시회Y복지환경위원회제300회 제2차 복지환경위원회(2024.01.26 금요일)N2024-02-15
72024930022024-01-26금요일임시회Y도시교통위원회제300회 제2차 도시교통위원회(2024.01.26 금요일)N2024-02-15
82024930012024-01-25목요일임시회Y복지환경위원회제300회 제1차 복지환경위원회(2024.01.25 목요일)N2024-02-15
92024930012024-01-25목요일임시회Y도시교통위원회제300회 제1차 도시교통위원회(2024.01.25 목요일)N2024-02-15
년도대수회기차수회의날짜회의요일회의구분안건유무회의명회의정보임시회의록구분데이터기준일
332919951211995-02-15수요일임시회Y운영위원회제2회 제1차[폐회중] 운영위원회(1995.02.15 수요일)Y2024-02-15
333019951221995-02-14화요일임시회Y본회의제2회 제2차 본회의(1995.02.14 화요일)Y2024-02-15
333119951201995-02-13월요일임시회N본회의제2회 개회식 본회의(1995.02.13 월요일)Y2024-02-15
333219951211995-02-13월요일임시회Y본회의제2회 제1차 본회의(1995.02.13 월요일)Y2024-02-15
333319951111995-01-19목요일임시회Y내무위원회제1회 제1차[폐회중] 내무위원회(1995.01.19 목요일)Y2024-02-15
333419951111995-01-19목요일임시회Y산업건설위원회제1회 제1차[폐회중] 산업건설위원회(1995.01.19 목요일)Y2024-02-15
333519951111995-01-16월요일임시회Y운영위원회제1회 제1차[폐회중] 운영위원회(1995.01.16 월요일)Y2024-02-15
333619951121995-01-04수요일임시회Y본회의제1회 제2차 본회의(1995.01.04 수요일)Y2024-02-15
333719951101995-01-03화요일임시회N본회의제1회 개원식 본회의(1995.01.03 화요일)Y2024-02-15
333819951111995-01-03화요일임시회Y본회의제1회 제1차 본회의(1995.01.03 화요일)Y2024-02-15

Duplicate rows

Most frequently occurring

년도대수회기차수회의날짜회의요일회의구분안건유무회의명회의정보임시회의록구분데이터기준일# duplicates
02020829952020-12-07목요일제2차 정례회Y복지환경위원회제299회 제5차 복지환경위원회(2020.12.07 목요일)N2024-02-153