Overview

Dataset statistics

Number of variables17
Number of observations2919
Missing cells2925
Missing cells (%)5.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory390.7 KiB
Average record size in memory137.0 B

Variable types

Categorical1
Numeric1
Text14
DateTime1

Dataset

Description전라남도 담양군 의회 의안 정보(의안번호, 의안명, 제안자, 소관상임위원회, 본회의처리일)등에 대한 정보를 제공하고 있으며, 공공데이터포털에 제공데이터는 기관승인 없이 무료로 활용이 가능합니다.
Author전라남도 담양군
URLhttps://www.data.go.kr/data/15037994/fileData.do

Alerts

데이터기준일 has constant value ""Constant
회기 is highly overall correlated with 역대의회High correlation
역대의회 is highly overall correlated with 회기High correlation
위원회 상정일 has 53 (1.8%) missing valuesMissing
위원회 처리일 has 64 (2.2%) missing valuesMissing
집행부이송일 has 55 (1.9%) missing valuesMissing
공포번호 has 1357 (46.5%) missing valuesMissing
공포일자 has 1267 (43.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 10:36:04.093499
Analysis finished2023-12-12 10:36:06.486602
Duration2.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

역대의회
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size22.9 KiB
8대
508 
7대
459 
4대
364 
3대
349 
6대
341 
Other values (4)
898 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1대
2nd row1대
3rd row1대
4th row1대
5th row1대

Common Values

ValueCountFrequency (%)
8대 508
17.4%
7대 459
15.7%
4대 364
12.5%
3대 349
12.0%
6대 341
11.7%
1대 313
10.7%
5대 305
10.4%
2대 262
9.0%
9대 18
 
0.6%

Length

2023-12-12T19:36:06.595394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:36:06.761443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8대 508
17.4%
7대 459
15.7%
4대 364
12.5%
3대 349
12.0%
6대 341
11.7%
1대 313
10.7%
5대 305
10.4%
2대 262
9.0%
9대 18
 
0.6%

회기
Real number (ℝ)

HIGH CORRELATION 

Distinct293
Distinct (%)10.1%
Missing4
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean175.15712
Minimum1
Maximum314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.8 KiB
2023-12-12T19:36:06.963571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.7
Q188
median189
Q3264
95-th percentile304
Maximum314
Range313
Interquartile range (IQR)176

Descriptive statistics

Standard deviation95.266912
Coefficient of variation (CV)0.54389404
Kurtosis-1.3126919
Mean175.15712
Median Absolute Deviation (MAD)82
Skewness-0.24160556
Sum510583
Variance9075.7845
MonotonicityIncreasing
2023-12-12T19:36:07.169186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59 65
 
2.2%
269 38
 
1.3%
266 36
 
1.2%
280 36
 
1.2%
306 36
 
1.2%
272 32
 
1.1%
305 31
 
1.1%
8 28
 
1.0%
78 28
 
1.0%
256 26
 
0.9%
Other values (283) 2559
87.7%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 4
 
0.1%
3 7
 
0.2%
4 4
 
0.1%
5 7
 
0.2%
6 9
 
0.3%
7 6
 
0.2%
8 28
1.0%
9 4
 
0.1%
10 4
 
0.1%
ValueCountFrequency (%)
314 10
 
0.3%
313 4
 
0.1%
312 2
 
0.1%
311 2
 
0.1%
310 20
0.7%
309 20
0.7%
308 11
 
0.4%
307 1
 
< 0.1%
306 36
1.2%
305 31
1.1%
Distinct521
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size22.9 KiB
2023-12-12T19:36:07.668117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.5560123
Min length1

Characters and Unicode

Total characters7461
Distinct characters17
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)1.4%

Sample

1st row1
2nd row1
3rd row2
4th row3
5th row4
ValueCountFrequency (%)
1 48
 
1.6%
2 47
 
1.6%
3 45
 
1.5%
4 43
 
1.5%
5 36
 
1.2%
6 35
 
1.2%
7 29
 
1.0%
8 24
 
0.8%
9 21
 
0.7%
10 16
 
0.5%
Other values (512) 2577
88.2%
2023-12-12T19:36:08.842618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1374
18.4%
2 1238
16.6%
3 956
12.8%
4 742
9.9%
5 544
 
7.3%
6 543
 
7.3%
7 529
 
7.1%
8 510
 
6.8%
9 505
 
6.8%
0 486
 
6.5%
Other values (7) 34
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7427
99.5%
Dash Punctuation 22
 
0.3%
Other Letter 4
 
0.1%
Lowercase Letter 4
 
0.1%
Space Separator 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1374
18.5%
2 1238
16.7%
3 956
12.9%
4 742
10.0%
5 544
 
7.3%
6 543
 
7.3%
7 529
 
7.1%
8 510
 
6.9%
9 505
 
6.8%
0 486
 
6.5%
Other Letter
ValueCountFrequency (%)
2
50.0%
2
50.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
50.0%
n 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7451
99.9%
Latin 6
 
0.1%
Hangul 4
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1374
18.4%
2 1238
16.6%
3 956
12.8%
4 742
10.0%
5 544
 
7.3%
6 543
 
7.3%
7 529
 
7.1%
8 510
 
6.8%
9 505
 
6.8%
0 486
 
6.5%
Other values (2) 24
 
0.3%
Latin
ValueCountFrequency (%)
J 2
33.3%
a 2
33.3%
n 2
33.3%
Hangul
ValueCountFrequency (%)
2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7457
99.9%
Hangul 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1374
18.4%
2 1238
16.6%
3 956
12.8%
4 742
10.0%
5 544
 
7.3%
6 543
 
7.3%
7 529
 
7.1%
8 510
 
6.8%
9 505
 
6.8%
0 486
 
6.5%
Other values (5) 30
 
0.4%
Hangul
ValueCountFrequency (%)
2
50.0%
2
50.0%
Distinct2290
Distinct (%)78.5%
Missing0
Missing (%)0.0%
Memory size22.9 KiB
2023-12-12T19:36:09.447033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length49
Mean length22.541966
Min length5

Characters and Unicode

Total characters65800
Distinct characters446
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2080 ?
Unique (%)71.3%

Sample

1st row제1회 담양군의회 임시회 회기결정의 건
2nd row제2회 담양군의회 임시회 회기결정의 건
3rd row군수 및 관계공무원 출석 요구의 건
4th row의사일정 변경 요구의 건
5th row군청사 확장 부지 매입건
ValueCountFrequency (%)
담양군 1401
 
9.5%
725
 
4.9%
608
 
4.1%
조례안 586
 
4.0%
관한 493
 
3.4%
조례 482
 
3.3%
일부개정조례안 419
 
2.8%
개정조례안 283
 
1.9%
임시회 230
 
1.6%
관계공무원 228
 
1.5%
Other values (2736) 9259
62.9%
2023-12-12T19:36:10.149673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11806
 
17.9%
2719
 
4.1%
2617
 
4.0%
2252
 
3.4%
2051
 
3.1%
1993
 
3.0%
1743
 
2.6%
1734
 
2.6%
1635
 
2.5%
1436
 
2.2%
Other values (436) 35814
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50978
77.5%
Space Separator 11806
 
17.9%
Decimal Number 2532
 
3.8%
Open Punctuation 167
 
0.3%
Close Punctuation 167
 
0.3%
Other Punctuation 134
 
0.2%
Uppercase Letter 7
 
< 0.1%
Dash Punctuation 4
 
< 0.1%
Math Symbol 4
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2719
 
5.3%
2617
 
5.1%
2252
 
4.4%
2051
 
4.0%
1993
 
3.9%
1743
 
3.4%
1734
 
3.4%
1635
 
3.2%
1436
 
2.8%
1270
 
2.5%
Other values (405) 31528
61.8%
Decimal Number
ValueCountFrequency (%)
2 628
24.8%
0 576
22.7%
1 429
16.9%
9 232
 
9.2%
3 162
 
6.4%
5 112
 
4.4%
4 108
 
4.3%
6 103
 
4.1%
7 93
 
3.7%
8 89
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
28.6%
W 1
14.3%
O 1
14.3%
B 1
14.3%
L 1
14.3%
H 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 97
72.4%
· 25
 
18.7%
, 10
 
7.5%
' 1
 
0.7%
% 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 165
98.8%
1
 
0.6%
[ 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 165
98.8%
1
 
0.6%
] 1
 
0.6%
Space Separator
ValueCountFrequency (%)
11806
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50979
77.5%
Common 14814
 
22.5%
Latin 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2719
 
5.3%
2617
 
5.1%
2252
 
4.4%
2051
 
4.0%
1993
 
3.9%
1743
 
3.4%
1734
 
3.4%
1635
 
3.2%
1436
 
2.8%
1270
 
2.5%
Other values (406) 31529
61.8%
Common
ValueCountFrequency (%)
11806
79.7%
2 628
 
4.2%
0 576
 
3.9%
1 429
 
2.9%
9 232
 
1.6%
( 165
 
1.1%
) 165
 
1.1%
3 162
 
1.1%
5 112
 
0.8%
4 108
 
0.7%
Other values (14) 431
 
2.9%
Latin
ValueCountFrequency (%)
T 2
28.6%
W 1
14.3%
O 1
14.3%
B 1
14.3%
L 1
14.3%
H 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50975
77.5%
ASCII 14794
 
22.5%
None 28
 
< 0.1%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11806
79.8%
2 628
 
4.2%
0 576
 
3.9%
1 429
 
2.9%
9 232
 
1.6%
( 165
 
1.1%
) 165
 
1.1%
3 162
 
1.1%
5 112
 
0.8%
4 108
 
0.7%
Other values (17) 411
 
2.8%
Hangul
ValueCountFrequency (%)
2719
 
5.3%
2617
 
5.1%
2252
 
4.4%
2051
 
4.0%
1993
 
3.9%
1743
 
3.4%
1734
 
3.4%
1635
 
3.2%
1436
 
2.8%
1270
 
2.5%
Other values (403) 31525
61.8%
None
ValueCountFrequency (%)
· 25
89.3%
1
 
3.6%
1
 
3.6%
1
 
3.6%
Compat Jamo
ValueCountFrequency (%)
2
66.7%
1
33.3%
Distinct268
Distinct (%)9.3%
Missing23
Missing (%)0.8%
Memory size22.9 KiB
2023-12-12T19:36:10.449309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length2
Mean length3.5700967
Min length1

Characters and Unicode

Total characters10339
Distinct characters124
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique156 ?
Unique (%)5.4%

Sample

1st row이상로 외 2인
2nd row강영수 외 7인
3rd row최창옥 외 7인
4th row최창옥 외 3인
5th row담양군수
ValueCountFrequency (%)
군수 1493
42.0%
의장 406
 
11.4%
담양군수 352
 
9.9%
249
 
7.0%
의회운영위원장 130
 
3.7%
의원 107
 
3.0%
3인 59
 
1.7%
2 58
 
1.6%
4인 37
 
1.0%
이규현의원 18
 
0.5%
Other values (182) 648
18.2%
2023-12-12T19:36:10.974151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1874
18.1%
1845
17.8%
906
 
8.8%
668
 
6.5%
592
 
5.7%
556
 
5.4%
381
 
3.7%
369
 
3.6%
353
 
3.4%
211
 
2.0%
Other values (114) 2584
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9277
89.7%
Space Separator 668
 
6.5%
Decimal Number 392
 
3.8%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1874
20.2%
1845
19.9%
906
9.8%
592
 
6.4%
556
 
6.0%
381
 
4.1%
369
 
4.0%
353
 
3.8%
211
 
2.3%
200
 
2.2%
Other values (101) 1990
21.5%
Decimal Number
ValueCountFrequency (%)
3 104
26.5%
2 75
19.1%
4 73
18.6%
5 48
12.2%
7 35
 
8.9%
8 20
 
5.1%
1 15
 
3.8%
6 11
 
2.8%
0 7
 
1.8%
9 4
 
1.0%
Space Separator
ValueCountFrequency (%)
668
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9277
89.7%
Common 1062
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1874
20.2%
1845
19.9%
906
9.8%
592
 
6.4%
556
 
6.0%
381
 
4.1%
369
 
4.0%
353
 
3.8%
211
 
2.3%
200
 
2.2%
Other values (101) 1990
21.5%
Common
ValueCountFrequency (%)
668
62.9%
3 104
 
9.8%
2 75
 
7.1%
4 73
 
6.9%
5 48
 
4.5%
7 35
 
3.3%
8 20
 
1.9%
1 15
 
1.4%
6 11
 
1.0%
0 7
 
0.7%
Other values (3) 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9277
89.7%
ASCII 1062
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1874
20.2%
1845
19.9%
906
9.8%
592
 
6.4%
556
 
6.0%
381
 
4.1%
369
 
4.0%
353
 
3.8%
211
 
2.3%
200
 
2.2%
Other values (101) 1990
21.5%
ASCII
ValueCountFrequency (%)
668
62.9%
3 104
 
9.8%
2 75
 
7.1%
4 73
 
6.9%
5 48
 
4.5%
7 35
 
3.3%
8 20
 
1.9%
1 15
 
1.4%
6 11
 
1.0%
0 7
 
0.7%
Other values (3) 6
 
0.6%
Distinct1125
Distinct (%)38.6%
Missing4
Missing (%)0.1%
Memory size22.9 KiB
2023-12-12T19:36:11.312655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.5927959
Min length1

Characters and Unicode

Total characters27963
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique544 ?
Unique (%)18.7%

Sample

1st row1991-04-15
2nd row1991-05-17
3rd row1991-05-17
4th row1991-05-24
5th row1991-05-23
ValueCountFrequency (%)
132
 
4.5%
1997-08-19 45
 
1.5%
2017-06-08 30
 
1.0%
2018-11-20 27
 
0.9%
2017-11-20 23
 
0.8%
2021-04-20 21
 
0.7%
1996-11-15 21
 
0.7%
2022-06-10 20
 
0.7%
2019-08-19 20
 
0.7%
2016-11-17 20
 
0.7%
Other values (1115) 2556
87.7%
2023-12-12T19:36:11.823439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6412
22.9%
- 5699
20.4%
1 4795
17.1%
2 4239
15.2%
9 2191
 
7.8%
8 826
 
3.0%
3 815
 
2.9%
7 797
 
2.9%
6 790
 
2.8%
5 737
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22264
79.6%
Dash Punctuation 5699
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6412
28.8%
1 4795
21.5%
2 4239
19.0%
9 2191
 
9.8%
8 826
 
3.7%
3 815
 
3.7%
7 797
 
3.6%
6 790
 
3.5%
5 737
 
3.3%
4 662
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 5699
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27963
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6412
22.9%
- 5699
20.4%
1 4795
17.1%
2 4239
15.2%
9 2191
 
7.8%
8 826
 
3.0%
3 815
 
2.9%
7 797
 
2.9%
6 790
 
2.8%
5 737
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27963
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6412
22.9%
- 5699
20.4%
1 4795
17.1%
2 4239
15.2%
9 2191
 
7.8%
8 826
 
3.0%
3 815
 
2.9%
7 797
 
2.9%
6 790
 
2.8%
5 737
 
2.6%
Distinct318
Distinct (%)11.0%
Missing28
Missing (%)1.0%
Memory size22.9 KiB
2023-12-12T19:36:12.188133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length5.2244898
Min length1

Characters and Unicode

Total characters15104
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)4.3%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
1534
53.1%
2021-11-19 30
 
1.0%
2017-06-08 30
 
1.0%
2018-11-20 27
 
0.9%
2021-10-12 25
 
0.9%
2019-11-18 23
 
0.8%
2017-11-20 23
 
0.8%
2020-06-08 21
 
0.7%
2021-04-30 21
 
0.7%
2019-08-19 20
 
0.7%
Other values (308) 1137
39.3%
2023-12-12T19:36:12.716968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4248
28.1%
0 3173
21.0%
1 2618
17.3%
2 2420
16.0%
8 491
 
3.3%
9 439
 
2.9%
7 414
 
2.7%
3 374
 
2.5%
6 362
 
2.4%
5 347
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10856
71.9%
Dash Punctuation 4248
 
28.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3173
29.2%
1 2618
24.1%
2 2420
22.3%
8 491
 
4.5%
9 439
 
4.0%
7 414
 
3.8%
3 374
 
3.4%
6 362
 
3.3%
5 347
 
3.2%
4 218
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 4248
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15104
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4248
28.1%
0 3173
21.0%
1 2618
17.3%
2 2420
16.0%
8 491
 
3.3%
9 439
 
2.9%
7 414
 
2.7%
3 374
 
2.5%
6 362
 
2.4%
5 347
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4248
28.1%
0 3173
21.0%
1 2618
17.3%
2 2420
16.0%
8 491
 
3.3%
9 439
 
2.9%
7 414
 
2.7%
3 374
 
2.5%
6 362
 
2.4%
5 347
 
2.3%

위원회 상정일
Text

MISSING 

Distinct301
Distinct (%)10.5%
Missing53
Missing (%)1.8%
Memory size22.9 KiB
2023-12-12T19:36:13.047766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length5.1985345
Min length1

Characters and Unicode

Total characters14899
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)3.3%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
1529
53.3%
2021-12-13 31
 
1.1%
2018-12-19 29
 
1.0%
2017-06-26 28
 
1.0%
2021-10-14 27
 
0.9%
2016-12-15 25
 
0.9%
2017-11-28 24
 
0.8%
2021-05-04 20
 
0.7%
2019-12-16 20
 
0.7%
2019-10-23 20
 
0.7%
Other values (291) 1113
38.8%
2023-12-12T19:36:13.890859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4203
28.2%
0 3016
20.2%
2 2661
17.9%
1 2375
15.9%
9 508
 
3.4%
7 421
 
2.8%
3 407
 
2.7%
6 388
 
2.6%
5 350
 
2.3%
8 292
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10696
71.8%
Dash Punctuation 4203
 
28.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3016
28.2%
2 2661
24.9%
1 2375
22.2%
9 508
 
4.7%
7 421
 
3.9%
3 407
 
3.8%
6 388
 
3.6%
5 350
 
3.3%
8 292
 
2.7%
4 278
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 4203
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14899
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4203
28.2%
0 3016
20.2%
2 2661
17.9%
1 2375
15.9%
9 508
 
3.4%
7 421
 
2.8%
3 407
 
2.7%
6 388
 
2.6%
5 350
 
2.3%
8 292
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4203
28.2%
0 3016
20.2%
2 2661
17.9%
1 2375
15.9%
9 508
 
3.4%
7 421
 
2.8%
3 407
 
2.7%
6 388
 
2.6%
5 350
 
2.3%
8 292
 
2.0%

위원회 처리일
Text

MISSING 

Distinct259
Distinct (%)9.1%
Missing64
Missing (%)2.2%
Memory size22.9 KiB
2023-12-12T19:36:14.440190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length5.1831874
Min length1

Characters and Unicode

Total characters14798
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)2.3%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
1528
53.5%
2017-06-27 33
 
1.2%
2021-12-17 31
 
1.1%
2018-12-19 29
 
1.0%
2016-12-16 26
 
0.9%
2021-10-26 25
 
0.9%
2017-11-30 24
 
0.8%
2021-05-06 23
 
0.8%
2015-09-10 21
 
0.7%
2020-06-22 21
 
0.7%
Other values (249) 1094
38.3%
2023-12-12T19:36:15.196196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4182
28.3%
0 2997
20.3%
2 2710
18.3%
1 2312
15.6%
9 482
 
3.3%
6 469
 
3.2%
7 459
 
3.1%
3 404
 
2.7%
5 310
 
2.1%
4 239
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10616
71.7%
Dash Punctuation 4182
 
28.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2997
28.2%
2 2710
25.5%
1 2312
21.8%
9 482
 
4.5%
6 469
 
4.4%
7 459
 
4.3%
3 404
 
3.8%
5 310
 
2.9%
4 239
 
2.3%
8 234
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 4182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14798
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4182
28.3%
0 2997
20.3%
2 2710
18.3%
1 2312
15.6%
9 482
 
3.3%
6 469
 
3.2%
7 459
 
3.1%
3 404
 
2.7%
5 310
 
2.1%
4 239
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14798
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4182
28.3%
0 2997
20.3%
2 2710
18.3%
1 2312
15.6%
9 482
 
3.3%
6 469
 
3.2%
7 459
 
3.1%
3 404
 
2.7%
5 310
 
2.1%
4 239
 
1.6%
Distinct575
Distinct (%)19.8%
Missing21
Missing (%)0.7%
Memory size22.9 KiB
2023-12-12T19:36:15.641873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.6614907
Min length1

Characters and Unicode

Total characters27999
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)4.5%

Sample

1st row1991-04-16
2nd row1991-05-22
3rd row1991-05-22
4th row1991-05-25
5th row1991-05-27
ValueCountFrequency (%)
109
 
3.8%
1997-10-04 61
 
2.1%
2021-12-17 32
 
1.1%
2017-06-27 31
 
1.1%
2018-12-19 29
 
1.0%
1996-11-25 26
 
0.9%
2016-12-16 26
 
0.9%
2021-10-26 25
 
0.9%
2021-05-06 23
 
0.8%
2017-11-30 22
 
0.8%
Other values (565) 2514
86.7%
2023-12-12T19:36:16.285912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6219
22.2%
- 5687
20.3%
2 4737
16.9%
1 4614
16.5%
9 2149
 
7.7%
7 935
 
3.3%
3 825
 
2.9%
5 783
 
2.8%
6 779
 
2.8%
4 702
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22312
79.7%
Dash Punctuation 5687
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6219
27.9%
2 4737
21.2%
1 4614
20.7%
9 2149
 
9.6%
7 935
 
4.2%
3 825
 
3.7%
5 783
 
3.5%
6 779
 
3.5%
4 702
 
3.1%
8 569
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 5687
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27999
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6219
22.2%
- 5687
20.3%
2 4737
16.9%
1 4614
16.5%
9 2149
 
7.7%
7 935
 
3.3%
3 825
 
2.9%
5 783
 
2.8%
6 779
 
2.8%
4 702
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27999
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6219
22.2%
- 5687
20.3%
2 4737
16.9%
1 4614
16.5%
9 2149
 
7.7%
7 935
 
3.3%
3 825
 
2.9%
5 783
 
2.8%
6 779
 
2.8%
4 702
 
2.5%
Distinct552
Distinct (%)19.1%
Missing24
Missing (%)0.8%
Memory size22.9 KiB
2023-12-12T19:36:16.775437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.6362694
Min length1

Characters and Unicode

Total characters27897
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)3.1%

Sample

1st row1991-04-16
2nd row1991-05-22
3rd row1991-05-22
4th row1991-05-25
5th row1991-05-27
ValueCountFrequency (%)
117
 
4.0%
1997-10-04 59
 
2.0%
2021-12-21 33
 
1.1%
2017-06-28 32
 
1.1%
2018-12-21 29
 
1.0%
2016-12-20 27
 
0.9%
2021-10-27 26
 
0.9%
2015-09-11 24
 
0.8%
1996-12-26 24
 
0.8%
2021-05-07 23
 
0.8%
Other values (542) 2501
86.4%
2023-12-12T19:36:17.376925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6046
21.7%
- 5673
20.3%
2 4911
17.6%
1 4584
16.4%
9 2146
 
7.7%
7 918
 
3.3%
3 912
 
3.3%
5 776
 
2.8%
6 744
 
2.7%
4 653
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22224
79.7%
Dash Punctuation 5673
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6046
27.2%
2 4911
22.1%
1 4584
20.6%
9 2146
 
9.7%
7 918
 
4.1%
3 912
 
4.1%
5 776
 
3.5%
6 744
 
3.3%
4 653
 
2.9%
8 534
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 5673
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27897
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6046
21.7%
- 5673
20.3%
2 4911
17.6%
1 4584
16.4%
9 2146
 
7.7%
7 918
 
3.3%
3 912
 
3.3%
5 776
 
2.8%
6 744
 
2.7%
4 653
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27897
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6046
21.7%
- 5673
20.3%
2 4911
17.6%
1 4584
16.4%
9 2146
 
7.7%
7 918
 
3.3%
3 912
 
3.3%
5 776
 
2.8%
6 744
 
2.7%
4 653
 
2.3%
Distinct561
Distinct (%)19.4%
Missing24
Missing (%)0.8%
Memory size22.9 KiB
2023-12-12T19:36:17.813001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.6829016
Min length1

Characters and Unicode

Total characters28032
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)2.8%

Sample

1st row1991-04-16
2nd row1991-05-22
3rd row1991-05-22
4th row1991-05-25
5th row1991-05-27
ValueCountFrequency (%)
102
 
3.5%
1997-10-04 58
 
2.0%
2021-12-21 33
 
1.1%
2017-06-28 32
 
1.1%
2018-12-21 29
 
1.0%
2016-12-20 27
 
0.9%
2021-10-27 26
 
0.9%
1996-12-26 24
 
0.8%
2015-09-11 24
 
0.8%
2019-12-20 23
 
0.8%
Other values (551) 2517
86.9%
2023-12-12T19:36:18.347752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6032
21.5%
- 5688
20.3%
2 4929
17.6%
1 4677
16.7%
9 2177
 
7.8%
3 921
 
3.3%
7 902
 
3.2%
5 765
 
2.7%
6 727
 
2.6%
4 678
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22344
79.7%
Dash Punctuation 5688
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6032
27.0%
2 4929
22.1%
1 4677
20.9%
9 2177
 
9.7%
3 921
 
4.1%
7 902
 
4.0%
5 765
 
3.4%
6 727
 
3.3%
4 678
 
3.0%
8 536
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 5688
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28032
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6032
21.5%
- 5688
20.3%
2 4929
17.6%
1 4677
16.7%
9 2177
 
7.8%
3 921
 
3.3%
7 902
 
3.2%
5 765
 
2.7%
6 727
 
2.6%
4 678
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28032
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6032
21.5%
- 5688
20.3%
2 4929
17.6%
1 4677
16.7%
9 2177
 
7.8%
3 921
 
3.3%
7 902
 
3.2%
5 765
 
2.7%
6 727
 
2.6%
4 678
 
2.4%
Distinct53
Distinct (%)1.8%
Missing1
Missing (%)< 0.1%
Memory size22.9 KiB
2023-12-12T19:36:18.588893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length4
Mean length3.5753941
Min length1

Characters and Unicode

Total characters10433
Distinct characters83
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)0.9%

Sample

1st row원안가결
2nd row원안가결
3rd row원안가결
4th row원안가결
5th row원안가결
ValueCountFrequency (%)
원안가결 1884
63.2%
가결 447
 
15.0%
원안의결 107
 
3.6%
의결 101
 
3.4%
수정가결 94
 
3.2%
92
 
3.1%
수정의결 24
 
0.8%
임기만료로 20
 
0.7%
인한 20
 
0.7%
폐기 20
 
0.7%
Other values (55) 172
 
5.8%
2023-12-12T19:36:18.986115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2675
25.6%
2428
23.3%
2040
19.6%
2036
19.5%
292
 
2.8%
131
 
1.3%
125
 
1.2%
- 92
 
0.9%
76
 
0.7%
42
 
0.4%
Other values (73) 496
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10228
98.0%
Dash Punctuation 92
 
0.9%
Space Separator 76
 
0.7%
Close Punctuation 11
 
0.1%
Open Punctuation 11
 
0.1%
Other Punctuation 10
 
0.1%
Decimal Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2675
26.2%
2428
23.7%
2040
19.9%
2036
19.9%
292
 
2.9%
131
 
1.3%
125
 
1.2%
42
 
0.4%
42
 
0.4%
41
 
0.4%
Other values (64) 376
 
3.7%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
6 2
40.0%
1 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 6
60.0%
: 4
40.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%
Space Separator
ValueCountFrequency (%)
76
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10228
98.0%
Common 205
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2675
26.2%
2428
23.7%
2040
19.9%
2036
19.9%
292
 
2.9%
131
 
1.3%
125
 
1.2%
42
 
0.4%
42
 
0.4%
41
 
0.4%
Other values (64) 376
 
3.7%
Common
ValueCountFrequency (%)
- 92
44.9%
76
37.1%
) 11
 
5.4%
( 11
 
5.4%
, 6
 
2.9%
: 4
 
2.0%
2 2
 
1.0%
6 2
 
1.0%
1 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10228
98.0%
ASCII 205
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2675
26.2%
2428
23.7%
2040
19.9%
2036
19.9%
292
 
2.9%
131
 
1.3%
125
 
1.2%
42
 
0.4%
42
 
0.4%
41
 
0.4%
Other values (64) 376
 
3.7%
ASCII
ValueCountFrequency (%)
- 92
44.9%
76
37.1%
) 11
 
5.4%
( 11
 
5.4%
, 6
 
2.9%
: 4
 
2.0%
2 2
 
1.0%
6 2
 
1.0%
1 1
 
0.5%

집행부이송일
Text

MISSING 

Distinct322
Distinct (%)11.2%
Missing55
Missing (%)1.9%
Memory size22.9 KiB
2023-12-12T19:36:19.348487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length7.0649441
Min length1

Characters and Unicode

Total characters20234
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)2.4%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
934
32.6%
1997-10-07 56
 
2.0%
2021-12-21 34
 
1.2%
2018-12-21 29
 
1.0%
2021-05-10 24
 
0.8%
1996-12-27 24
 
0.8%
2015-09-11 24
 
0.8%
2021-11-01 24
 
0.8%
2017-12-04 22
 
0.8%
2016-12-21 22
 
0.8%
Other values (312) 1671
58.3%
2023-12-12T19:36:19.831826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4794
23.7%
0 4054
20.0%
2 3608
17.8%
1 3308
16.3%
9 1447
 
7.2%
3 664
 
3.3%
7 630
 
3.1%
6 523
 
2.6%
5 437
 
2.2%
4 432
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15440
76.3%
Dash Punctuation 4794
 
23.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4054
26.3%
2 3608
23.4%
1 3308
21.4%
9 1447
 
9.4%
3 664
 
4.3%
7 630
 
4.1%
6 523
 
3.4%
5 437
 
2.8%
4 432
 
2.8%
8 337
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 4794
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20234
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4794
23.7%
0 4054
20.0%
2 3608
17.8%
1 3308
16.3%
9 1447
 
7.2%
3 664
 
3.3%
7 630
 
3.1%
6 523
 
2.6%
5 437
 
2.2%
4 432
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4794
23.7%
0 4054
20.0%
2 3608
17.8%
1 3308
16.3%
9 1447
 
7.2%
3 664
 
3.3%
7 630
 
3.1%
6 523
 
2.6%
5 437
 
2.2%
4 432
 
2.1%

공포번호
Text

MISSING 

Distinct611
Distinct (%)39.1%
Missing1357
Missing (%)46.5%
Memory size22.9 KiB
2023-12-12T19:36:20.263055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length1
Mean length2.6056338
Min length1

Characters and Unicode

Total characters4070
Distinct characters21
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

Unique588 ?
Unique (%)37.6%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
930
59.5%
1581 2
 
0.1%
제2721호 2
 
0.1%
제2544호 2
 
0.1%
제2661호 2
 
0.1%
제2662호 2
 
0.1%
제2668호 2
 
0.1%
제2682호 2
 
0.1%
제2681호 2
 
0.1%
제2678호 2
 
0.1%
Other values (602) 615
39.3%
2023-12-12T19:36:20.872222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 930
22.9%
2 446
11.0%
1 437
10.7%
6 325
 
8.0%
5 317
 
7.8%
310
 
7.6%
309
 
7.6%
4 273
 
6.7%
3 189
 
4.6%
7 167
 
4.1%
Other values (11) 367
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2513
61.7%
Dash Punctuation 930
 
22.9%
Other Letter 626
 
15.4%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 446
17.7%
1 437
17.4%
6 325
12.9%
5 317
12.6%
4 273
10.9%
3 189
7.5%
7 167
 
6.6%
8 127
 
5.1%
9 119
 
4.7%
0 113
 
4.5%
Other Letter
ValueCountFrequency (%)
310
49.5%
309
49.4%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 930
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3444
84.6%
Hangul 626
 
15.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 930
27.0%
2 446
13.0%
1 437
12.7%
6 325
 
9.4%
5 317
 
9.2%
4 273
 
7.9%
3 189
 
5.5%
7 167
 
4.8%
8 127
 
3.7%
9 119
 
3.5%
Other values (2) 114
 
3.3%
Hangul
ValueCountFrequency (%)
310
49.5%
309
49.4%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3444
84.6%
Hangul 626
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 930
27.0%
2 446
13.0%
1 437
12.7%
6 325
 
9.4%
5 317
 
9.2%
4 273
 
7.9%
3 189
 
5.5%
7 167
 
4.8%
8 127
 
3.7%
9 119
 
3.5%
Other values (2) 114
 
3.3%
Hangul
ValueCountFrequency (%)
310
49.5%
309
49.4%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%
1
 
0.2%

공포일자
Text

MISSING 

Distinct125
Distinct (%)7.6%
Missing1267
Missing (%)43.4%
Memory size22.9 KiB
2023-12-12T19:36:21.220897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length1
Mean length5
Min length1

Characters and Unicode

Total characters8260
Distinct characters21
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

Unique24 ?
Unique (%)1.5%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
918
55.5%
1997-10-24 57
 
3.4%
2022-01-07 31
 
1.9%
2021-11-19 22
 
1.3%
2021-07-16 22
 
1.3%
2021-05-28 21
 
1.3%
1997-01-01 20
 
1.2%
2019-11-15 19
 
1.1%
2018-12-27 19
 
1.1%
2020-01-07 18
 
1.1%
Other values (117) 507
30.7%
2023-12-12T19:36:21.749096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2384
28.9%
0 1587
19.2%
1 1318
16.0%
2 1120
13.6%
9 768
 
9.3%
7 317
 
3.8%
5 222
 
2.7%
8 162
 
2.0%
4 149
 
1.8%
6 116
 
1.4%
Other values (11) 117
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5865
71.0%
Dash Punctuation 2384
28.9%
Other Letter 9
 
0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1587
27.1%
1 1318
22.5%
2 1120
19.1%
9 768
13.1%
7 317
 
5.4%
5 222
 
3.8%
8 162
 
2.8%
4 149
 
2.5%
6 116
 
2.0%
3 106
 
1.8%
Other Letter
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Dash Punctuation
ValueCountFrequency (%)
- 2384
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8251
99.9%
Hangul 9
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2384
28.9%
0 1587
19.2%
1 1318
16.0%
2 1120
13.6%
9 768
 
9.3%
7 317
 
3.8%
5 222
 
2.7%
8 162
 
2.0%
4 149
 
1.8%
6 116
 
1.4%
Other values (2) 108
 
1.3%
Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8251
99.9%
Hangul 9
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2384
28.9%
0 1587
19.2%
1 1318
16.0%
2 1120
13.6%
9 768
 
9.3%
7 317
 
3.8%
5 222
 
2.7%
8 162
 
2.0%
4 149
 
1.8%
6 116
 
1.4%
Other values (2) 108
 
1.3%
Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.9 KiB
Minimum2022-08-09 00:00:00
Maximum2022-08-09 00:00:00
2023-12-12T19:36:21.926338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:36:22.042920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T19:36:05.284323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:36:22.136046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역대의회회기처리결과
역대의회1.0000.9370.684
회기0.9371.0000.650
처리결과0.6840.6501.000
2023-12-12T19:36:22.241756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회기역대의회
회기1.0000.790
역대의회0.7901.000

Missing values

2023-12-12T19:36:05.482988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:36:05.954050image/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.
2023-12-12T19:36:06.258626image/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

역대의회회기의안번호의안명발의자(제출자)접수일위원회 보고일위원회 상정일위원회 처리일본회의 보고일본회의 상정일본회의 처리일처리결과집행부이송일공포번호공포일자데이터기준일
01대11제1회 담양군의회 임시회 회기결정의 건이상로 외 2인1991-04-15---1991-04-161991-04-161991-04-16원안가결---2022-08-09
11대21제2회 담양군의회 임시회 회기결정의 건강영수 외 7인1991-05-17---1991-05-221991-05-221991-05-22원안가결---2022-08-09
21대22군수 및 관계공무원 출석 요구의 건최창옥 외 7인1991-05-17---1991-05-221991-05-221991-05-22원안가결---2022-08-09
31대23의사일정 변경 요구의 건최창옥 외 3인1991-05-24---1991-05-251991-05-251991-05-25원안가결---2022-08-09
41대24군청사 확장 부지 매입건담양군수1991-05-23---1991-05-271991-05-271991-05-27원안가결---2022-08-09
51대31제3회 담양군의회 임시회 회기결정의 건강여수 의원 외 8인1991-06-27---1991-07-031991-07-031991-07-03원안가결---2022-08-09
61대32군수 및 관계공무원 출석 요구의 건강여수 의원 외 8인1991-06-27---1991-07-031991-07-031991-07-03원안가결---2022-08-09
71대33도시계획지역 결정건담양군수1991-06-27---1991-07-031991-07-041991-07-04원안가결---2022-08-09
81대34지방채 발행 승인 신청 협의담양군수1991-06-28---1991-07-031991-07-041991-07-04협의---2022-08-09
91대35군유재산 매각 건담양군수1991-07-02---1991-07-031991-07-041991-07-04의결---2022-08-09
역대의회회기의안번호의안명발의자(제출자)접수일위원회 보고일위원회 상정일위원회 처리일본회의 보고일본회의 상정일본회의 처리일처리결과집행부이송일공포번호공포일자데이터기준일
29099대3149담양군 행정기구 설치 조례 일부개정조례안군수2022-07-082022-07-132022-07-152022-07-212022-07-212022-07-222022-07-22원안가결2022-07-22제2740호2022-08-012022-08-09
29109대31410담양군 지방공무원 정원 조례 일부개정조례안군수2022-07-082022-07-132022-07-152022-07-212022-07-212022-07-222022-07-22원안가결2022-07-22제2741호2022-08-012022-08-09
29119대31411담양군 관광진흥에 관한 조례 일부개정조례안군수2022-07-082022-07-132022-07-152022-07-212022-07-212022-07-222022-07-22원안가결2022-07-22제2742호2022-08-012022-08-09
29129대31412담양군 군세 감면 조례 일부개정조례안군수2022-07-082022-07-132022-07-152022-07-212022-07-212022-07-222022-07-22원안가결2022-07-22제2743호2022-08-012022-08-09
29139대31413담양군 군세 징수 조례 일부개정조례안군수2022-07-082022-07-132022-07-152022-07-212022-07-212022-07-222022-07-22원안가결2022-07-22제2744호2022-08-012022-08-09
29149대31414코로나19 지역경제 회복을 위한 재산세(건축물) 감면안군수2022-07-042022-07-132022-07-152022-07-212022-07-212022-07-222022-07-22원안가결2022-07-22<NA><NA>2022-08-09
29159대314152022 공유재산 관리계획 변경안군수2022-07-042022-07-132022-07-152022-07-212022-07-212022-07-222022-07-22원안가결2022-07-22<NA><NA>2022-08-09
29169대314162022년 지방채 발행 사전동의안군수2022-07-042022-07-132022-07-152022-07-212022-07-212022-07-222022-07-22원안가결2022-07-22<NA><NA>2022-08-09
29179대31417담양군의회 위원회 조례 일부개정조례안최용만 의원 외 12022-07-112022-07-132022-07-152022-07-212022-07-212022-07-222022-07-22원안가결2022-07-22제27452022-08-012022-08-09
29189대31418담양군 의회윤리특별위원회구성 등에 관한 규칙 전부개정규칙안장명영 의원 외 12022-07-112022-07-132022-07-152022-07-212022-07-212022-07-222022-07-22원안가결2022-07-22담양군의회규칙 제9호담양군의회규칙 제 9호2022-08-09