Overview

Dataset statistics

Number of variables17
Number of observations377
Missing cells122
Missing cells (%)1.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.9 KiB
Average record size in memory138.4 B

Variable types

Text3
DateTime3
Numeric2
Categorical9

Dataset

Description경상남도 함양군의회 의안정보로 의안번호, 의안명, 제안일자, 제안회기, 제안자, 소관위원회, 본회의상정일, 본회의 의결일, 소관위원회처리결과, 본회의상정일, 본회의의결일, 본회의처리결과, 집행부이송일, 집행부공포번호, 집행부공포일자, 데이터기준일자 등으로 구성되어 있다.
Author경상남도 함양군
URLhttps://www.data.go.kr/data/15038073/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
본회의의결일 is highly overall correlated with 제안회기 and 5 other fieldsHigh correlation
집행부이송일 is highly overall correlated with 제안회기 and 5 other fieldsHigh correlation
소관위원회처리결과 is highly overall correlated with 본회의처리결과High correlation
소관위원회회부일 is highly overall correlated with 제안회기 and 6 other fieldsHigh correlation
본회의처리결과 is highly overall correlated with 소관위원회처리결과High correlation
집행부공포일자 is highly overall correlated with 제안회기 and 5 other fieldsHigh correlation
본회의상정일 is highly overall correlated with 제안회기 and 5 other fieldsHigh correlation
제안회기 is highly overall correlated with 집행부공포번호 and 5 other fieldsHigh correlation
집행부공포번호 is highly overall correlated with 제안회기 and 5 other fieldsHigh correlation
소관위위원회명 is highly overall correlated with 소관위원회회부일High correlation
소관위원회처리결과 is highly imbalanced (68.2%)Imbalance
본회의처리결과 is highly imbalanced (63.7%)Imbalance
소관위원회의결일 has 4 (1.1%) missing valuesMissing
집행부공포번호 has 117 (31.0%) missing valuesMissing

Reproduction

Analysis started2023-12-11 23:52:32.298729
Analysis finished2023-12-11 23:52:34.267296
Duration1.97 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

의안번호
Text

Distinct376
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T08:52:34.533255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.938992
Min length6

Characters and Unicode

Total characters2616
Distinct characters35
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique375 ?
Unique (%)99.5%

Sample

1st row2019-45
2nd row2019-46
3rd row2019-47
4th row2019-48
5th row2019-49
ValueCountFrequency (%)
2022-48 2
 
0.5%
22-jul 1
 
0.3%
2022-16 1
 
0.3%
2022-15 1
 
0.3%
2022-14 1
 
0.3%
2022-13 1
 
0.3%
22-dec 1
 
0.3%
22-nov 1
 
0.3%
22-oct 1
 
0.3%
22-sep 1
 
0.3%
Other values (366) 366
97.1%
2023-12-12T08:52:35.036137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 818
31.3%
0 456
17.4%
- 377
14.4%
1 243
 
9.3%
3 116
 
4.4%
9 97
 
3.7%
7 76
 
2.9%
4 75
 
2.9%
8 75
 
2.9%
5 75
 
2.9%
Other values (25) 208
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2100
80.3%
Dash Punctuation 377
 
14.4%
Lowercase Letter 90
 
3.4%
Uppercase Letter 45
 
1.7%
Other Letter 4
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 12
13.3%
e 11
12.2%
a 10
11.1%
c 8
8.9%
r 8
8.9%
p 8
8.9%
n 7
7.8%
t 4
 
4.4%
v 4
 
4.4%
o 4
 
4.4%
Other values (4) 14
15.6%
Decimal Number
ValueCountFrequency (%)
2 818
39.0%
0 456
21.7%
1 243
 
11.6%
3 116
 
5.5%
9 97
 
4.6%
7 76
 
3.6%
4 75
 
3.6%
8 75
 
3.6%
5 75
 
3.6%
6 69
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
J 11
24.4%
A 8
17.8%
M 7
15.6%
N 4
 
8.9%
S 4
 
8.9%
O 4
 
8.9%
D 4
 
8.9%
F 3
 
6.7%
Other Letter
ValueCountFrequency (%)
관 2
50.0%
련 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 377
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2477
94.7%
Latin 135
 
5.2%
Hangul 4
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 12
 
8.9%
J 11
 
8.1%
e 11
 
8.1%
a 10
 
7.4%
c 8
 
5.9%
r 8
 
5.9%
p 8
 
5.9%
A 8
 
5.9%
n 7
 
5.2%
M 7
 
5.2%
Other values (12) 45
33.3%
Common
ValueCountFrequency (%)
2 818
33.0%
0 456
18.4%
- 377
15.2%
1 243
 
9.8%
3 116
 
4.7%
9 97
 
3.9%
7 76
 
3.1%
4 75
 
3.0%
8 75
 
3.0%
5 75
 
3.0%
Hangul
ValueCountFrequency (%)
관 2
50.0%
련 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2612
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 818
31.3%
0 456
17.5%
- 377
14.4%
1 243
 
9.3%
3 116
 
4.4%
9 97
 
3.7%
7 76
 
2.9%
4 75
 
2.9%
8 75
 
2.9%
5 75
 
2.9%
Other values (23) 204
 
7.8%
Hangul
ValueCountFrequency (%)
관 2
50.0%
련 2
50.0%

의안명
Text

Distinct346
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T08:52:35.293814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length38
Mean length24.814324
Min length10

Characters and Unicode

Total characters9355
Distinct characters335
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique324 ?
Unique (%)85.9%

Sample

1st row2019년도 제2회 추가경정 예산안
2nd row2020년도 함양군 출자·출연 동의안
3rd row함양군 시설관리공단 설립 및 운영에 관한 조례안
4th row함양군 공유재산 관리 조례 일부개정조례안
5th row2019년도 수시분 공유재산 관리계획안
ValueCountFrequency (%)
함양군 265
 
12.2%
조례 139
 
6.4%
조례안 139
 
6.4%
관한 104
 
4.8%
및 104
 
4.8%
일부개정조례안 96
 
4.4%
동의안 45
 
2.1%
운영 41
 
1.9%
설치 34
 
1.6%
지원 30
 
1.4%
Other values (603) 1170
54.0%
2023-12-12T08:52:35.754570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1795
 
19.2%
조 442
 
4.7%
례 426
 
4.6%
안 383
 
4.1%
양 332
 
3.5%
함 322
 
3.4%
군 313
 
3.3%
정 221
 
2.4%
관 199
 
2.1%
개 166
 
1.8%
Other values (325) 4756
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7279
77.8%
Space Separator 1795
 
19.2%
Decimal Number 225
 
2.4%
Close Punctuation 18
 
0.2%
Open Punctuation 18
 
0.2%
Other Punctuation 13
 
0.1%
Uppercase Letter 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 442
 
6.1%
례 426
 
5.9%
안 383
 
5.3%
양 332
 
4.6%
함 322
 
4.4%
군 313
 
4.3%
정 221
 
3.0%
관 199
 
2.7%
개 166
 
2.3%
부 160
 
2.2%
Other values (308) 4315
59.3%
Decimal Number
ValueCountFrequency (%)
2 113
50.2%
0 62
27.6%
1 27
 
12.0%
3 13
 
5.8%
9 7
 
3.1%
5 2
 
0.9%
6 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
C 3
42.9%
T 1
 
14.3%
V 1
 
14.3%
E 1
 
14.3%
O 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
· 11
84.6%
, 2
 
15.4%
Space Separator
ValueCountFrequency (%)
1795
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7278
77.8%
Common 2069
 
22.1%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 442
 
6.1%
례 426
 
5.9%
안 383
 
5.3%
양 332
 
4.6%
함 322
 
4.4%
군 313
 
4.3%
정 221
 
3.0%
관 199
 
2.7%
개 166
 
2.3%
부 160
 
2.2%
Other values (307) 4314
59.3%
Common
ValueCountFrequency (%)
1795
86.8%
2 113
 
5.5%
0 62
 
3.0%
1 27
 
1.3%
) 18
 
0.9%
( 18
 
0.9%
3 13
 
0.6%
· 11
 
0.5%
9 7
 
0.3%
, 2
 
0.1%
Other values (2) 3
 
0.1%
Latin
ValueCountFrequency (%)
C 3
37.5%
T 1
 
12.5%
V 1
 
12.5%
E 1
 
12.5%
O 1
 
12.5%
º 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7278
77.8%
ASCII 2065
 
22.1%
None 12
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1795
86.9%
2 113
 
5.5%
0 62
 
3.0%
1 27
 
1.3%
) 18
 
0.9%
( 18
 
0.9%
3 13
 
0.6%
9 7
 
0.3%
C 3
 
0.1%
, 2
 
0.1%
Other values (6) 7
 
0.3%
Hangul
ValueCountFrequency (%)
조 442
 
6.1%
례 426
 
5.9%
안 383
 
5.3%
양 332
 
4.6%
함 322
 
4.4%
군 313
 
4.3%
정 221
 
3.0%
관 199
 
2.7%
개 166
 
2.3%
부 160
 
2.2%
Other values (307) 4314
59.3%
None
ValueCountFrequency (%)
· 11
91.7%
º 1
 
8.3%

제안일자
Date

Distinct57
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2019-09-09 00:00:00
Maximum2023-05-24 00:00:00
2023-12-12T08:52:35.929913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:36.066917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제안회기
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean263.5305
Minimum250
Maximum276
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T08:52:36.184492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile251
Q1258
median265
Q3272
95-th percentile276
Maximum276
Range26
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.3318632
Coefficient of variation (CV)0.031616314
Kurtosis-1.1965216
Mean263.5305
Median Absolute Deviation (MAD)7
Skewness-0.12826966
Sum99351
Variance69.419945
MonotonicityIncreasing
2023-12-12T08:52:36.317433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
273 46
12.2%
251 33
 
8.8%
265 30
 
8.0%
266 27
 
7.2%
275 27
 
7.2%
259 23
 
6.1%
252 21
 
5.6%
258 21
 
5.6%
262 20
 
5.3%
276 20
 
5.3%
Other values (12) 109
28.9%
ValueCountFrequency (%)
250 15
4.0%
251 33
8.8%
252 21
5.6%
253 4
 
1.1%
254 12
 
3.2%
257 1
 
0.3%
258 21
5.6%
259 23
6.1%
260 18
4.8%
262 20
5.3%
ValueCountFrequency (%)
276 20
5.3%
275 27
7.2%
273 46
12.2%
272 9
 
2.4%
271 1
 
0.3%
270 6
 
1.6%
268 14
 
3.7%
267 14
 
3.7%
266 27
7.2%
265 30
8.0%

제안자
Text

Distinct62
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T08:52:36.579937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length4
Mean length5.668435
Min length3

Characters and Unicode

Total characters2137
Distinct characters39
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

Unique59 ?
Unique (%)15.6%

Sample

1st row함양군수
2nd row함양군수
3rd row함양군수
4th row함양군수
5th row함양군수
ValueCountFrequency (%)
함양군수 314
83.3%
이용권(대표)+서영재+김윤택 2
 
0.5%
임채숙(대표)+홍정덕+정현철 2
 
0.5%
양인호(대표)+김윤택+임채숙 1
 
0.3%
함양군순 1
 
0.3%
임채숙(대표)+서영재+양인호 1
 
0.3%
배우진(대표)+김윤택+권대근 1
 
0.3%
정광석(대표)+임채숙+양인호 1
 
0.3%
강신택(대표)+홍정덕+이영재 1
 
0.3%
이경규(대표)+이영재+임채숙 1
 
0.3%
Other values (52) 52
 
13.8%
2023-12-12T08:52:36.957093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 321
15.0%
함 315
14.7%
군 315
14.7%
수 314
14.7%
+ 104
 
4.9%
대 62
 
2.9%
( 61
 
2.9%
) 61
 
2.9%
표 57
 
2.7%
정 46
 
2.2%
Other values (29) 481
22.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1911
89.4%
Math Symbol 104
 
4.9%
Open Punctuation 61
 
2.9%
Close Punctuation 61
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 321
16.8%
함 315
16.5%
군 315
16.5%
수 314
16.4%
대 62
 
3.2%
표 57
 
3.0%
정 46
 
2.4%
이 43
 
2.3%
택 32
 
1.7%
영 30
 
1.6%
Other values (26) 376
19.7%
Math Symbol
ValueCountFrequency (%)
+ 104
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1911
89.4%
Common 226
 
10.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 321
16.8%
함 315
16.5%
군 315
16.5%
수 314
16.4%
대 62
 
3.2%
표 57
 
3.0%
정 46
 
2.4%
이 43
 
2.3%
택 32
 
1.7%
영 30
 
1.6%
Other values (26) 376
19.7%
Common
ValueCountFrequency (%)
+ 104
46.0%
( 61
27.0%
) 61
27.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1911
89.4%
ASCII 226
 
10.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 321
16.8%
함 315
16.5%
군 315
16.5%
수 314
16.4%
대 62
 
3.2%
표 57
 
3.0%
정 46
 
2.4%
이 43
 
2.3%
택 32
 
1.7%
영 30
 
1.6%
Other values (26) 376
19.7%
ASCII
ValueCountFrequency (%)
+ 104
46.0%
( 61
27.0%
) 61
27.0%

소관위위원회명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
기획행정
215 
산업건설
103 
의회운영
27 
예결위
 
20
예산결산
 
9
Other values (3)
 
3

Length

Max length6
Median length4
Mean length3.9496021
Min length3

Unique

Unique3 ?
Unique (%)0.8%

Sample

1st row예결위
2nd row기획행정
3rd row기획행정
4th row기획행정
5th row기획행정

Common Values

ValueCountFrequency (%)
기획행정 215
57.0%
산업건설 103
27.3%
의회운영 27
 
7.2%
예결위 20
 
5.3%
예산결산 9
 
2.4%
<NA> 1
 
0.3%
운영위 1
 
0.3%
행정사무감사 1
 
0.3%

Length

2023-12-12T08:52:37.109034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:52:37.214647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기획행정 215
57.0%
산업건설 103
27.3%
의회운영 27
 
7.2%
예결위 20
 
5.3%
예산결산 9
 
2.4%
na 1
 
0.3%
운영위 1
 
0.3%
행정사무감사 1
 
0.3%

소관위원회회부일
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2022-11-14
45 
2019-11-22
33 
2021-10-22
30 
2021-11-14
27 
2023-03-07
26 
Other values (28)
216 

Length

Max length10
Median length10
Mean length9.9840849
Min length4

Unique

Unique10 ?
Unique (%)2.7%

Sample

1st row2019-09-10
2nd row2019-09-10
3rd row2019-09-10
4th row2019-09-10
5th row2019-09-10

Common Values

ValueCountFrequency (%)
2022-11-14 45
 
11.9%
2019-11-22 33
 
8.8%
2021-10-22 30
 
8.0%
2021-11-14 27
 
7.2%
2023-03-07 26
 
6.9%
2020-11-12 23
 
6.1%
2020-03-30 23
 
6.1%
2020-09-25 21
 
5.6%
2023-05-23 18
 
4.8%
2021-05-17 18
 
4.8%
Other values (23) 113
30.0%

Length

2023-12-12T08:52:37.334958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-11-14 45
 
11.9%
2019-11-22 33
 
8.8%
2021-10-22 30
 
8.0%
2021-11-14 27
 
7.2%
2023-03-07 26
 
6.9%
2020-11-12 23
 
6.1%
2020-03-30 23
 
6.1%
2020-09-25 21
 
5.6%
2023-05-23 18
 
4.8%
2021-05-17 18
 
4.8%
Other values (23) 113
30.0%

소관위원회상정일
Date

Distinct62
Distinct (%)16.5%
Missing1
Missing (%)0.3%
Memory size3.1 KiB
Minimum2019-09-27 00:00:00
Maximum2023-06-20 00:00:00
2023-12-12T08:52:37.447309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:37.570500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소관위원회의결일
Date

MISSING 

Distinct61
Distinct (%)16.4%
Missing4
Missing (%)1.1%
Memory size3.1 KiB
Minimum1900-01-03 00:00:00
Maximum2023-06-20 00:00:00
2023-12-12T08:52:37.938697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:38.069910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소관위원회처리결과
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
원안가결
323 
수정가결
40 
부결
 
12
<NA>
 
1
부 결
 
1

Length

Max length6
Median length4
Mean length3.9416446
Min length2

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row수정가결
2nd row원안가결
3rd row부결
4th row원안가결
5th row수정가결

Common Values

ValueCountFrequency (%)
원안가결 323
85.7%
수정가결 40
 
10.6%
부결 12
 
3.2%
<NA> 1
 
0.3%
부 결 1
 
0.3%

Length

2023-12-12T08:52:38.191925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:52:38.292628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원안가결 323
85.4%
수정가결 40
 
10.6%
부결 12
 
3.2%
na 1
 
0.3%
부 1
 
0.3%
결 1
 
0.3%

본회의상정일
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2022-12-16
46 
2019-12-20
33 
2021-10-29
30 
2023-03-31
27 
2021-12-21
26 
Other values (19)
215 

Length

Max length10
Median length10
Mean length9.8408488
Min length4

Unique

Unique4 ?
Unique (%)1.1%

Sample

1st row2019-10-10
2nd row2019-10-10
3rd row<NA>
4th row2019-10-10
5th row2019-10-10

Common Values

ValueCountFrequency (%)
2022-12-16 46
12.2%
2019-12-20 33
 
8.8%
2021-10-29 30
 
8.0%
2023-03-31 27
 
7.2%
2021-12-21 26
 
6.9%
2020-04-17 23
 
6.1%
2020-12-18 22
 
5.8%
2023-06-22 20
 
5.3%
2021-05-31 20
 
5.3%
2020-10-30 18
 
4.8%
Other values (14) 112
29.7%

Length

2023-12-12T08:52:38.402873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-12-16 46
12.2%
2019-12-20 33
 
8.8%
2021-10-29 30
 
8.0%
2023-03-31 27
 
7.2%
2021-12-21 26
 
6.9%
2020-04-17 23
 
6.1%
2020-12-18 22
 
5.8%
2023-06-22 20
 
5.3%
2021-05-31 20
 
5.3%
2020-10-30 18
 
4.8%
Other values (14) 112
29.7%

본회의의결일
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2022-12-16
46 
2019-12-20
33 
2021-10-29
30 
2023-03-31
27 
2021-12-21
26 
Other values (19)
215 

Length

Max length10
Median length10
Mean length9.8408488
Min length4

Unique

Unique4 ?
Unique (%)1.1%

Sample

1st row2019-10-10
2nd row2019-10-10
3rd row<NA>
4th row2019-10-10
5th row2019-10-10

Common Values

ValueCountFrequency (%)
2022-12-16 46
12.2%
2019-12-20 33
 
8.8%
2021-10-29 30
 
8.0%
2023-03-31 27
 
7.2%
2021-12-21 26
 
6.9%
2020-04-17 23
 
6.1%
2020-12-18 22
 
5.8%
2023-06-22 20
 
5.3%
2021-05-31 20
 
5.3%
2020-10-30 18
 
4.8%
Other values (14) 112
29.7%

Length

2023-12-12T08:52:38.553662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-12-16 46
12.2%
2019-12-20 33
 
8.8%
2021-10-29 30
 
8.0%
2023-03-31 27
 
7.2%
2021-12-21 26
 
6.9%
2020-04-17 23
 
6.1%
2020-12-18 22
 
5.8%
2023-06-22 20
 
5.3%
2021-05-31 20
 
5.3%
2020-10-30 18
 
4.8%
Other values (14) 112
29.7%

본회의처리결과
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
원안가결
324 
수정가결
40 
<NA>
 
10
부결
 
3

Length

Max length4
Median length4
Mean length3.9840849
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원안가결 324
85.9%
수정가결 40
 
10.6%
<NA> 10
 
2.7%
부결 3
 
0.8%

Length

2023-12-12T08:52:38.703275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:52:38.810005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원안가결 324
85.9%
수정가결 40
 
10.6%
na 10
 
2.7%
부결 3
 
0.8%

집행부이송일
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2022-12-16
46 
2019-12-20
32 
2021-11-01
29 
2023-03-31
27 
2021-12-21
26 
Other values (18)
217 

Length

Max length10
Median length10
Mean length9.7931034
Min length4

Unique

Unique3 ?
Unique (%)0.8%

Sample

1st row2019-10-15
2nd row2019-10-15
3rd row<NA>
4th row2019-10-15
5th row2019-10-15

Common Values

ValueCountFrequency (%)
2022-12-16 46
12.2%
2019-12-20 32
 
8.5%
2021-11-01 29
 
7.7%
2023-03-31 27
 
7.2%
2021-12-21 26
 
6.9%
2020-04-20 23
 
6.1%
2020-12-18 22
 
5.8%
2023-06-22 20
 
5.3%
2021-05-31 20
 
5.3%
2020-10-30 18
 
4.8%
Other values (13) 114
30.2%

Length

2023-12-12T08:52:38.937577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-12-16 46
12.2%
2019-12-20 32
 
8.5%
2021-11-01 29
 
7.7%
2023-03-31 27
 
7.2%
2021-12-21 26
 
6.9%
2020-04-20 23
 
6.1%
2020-12-18 22
 
5.8%
2023-06-22 20
 
5.3%
2021-05-31 20
 
5.3%
2020-10-30 18
 
4.8%
Other values (13) 114
30.2%

집행부공포번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct260
Distinct (%)100.0%
Missing117
Missing (%)31.0%
Infinite0
Infinite (%)0.0%
Mean2673.9808
Minimum1198
Maximum44096
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T08:52:39.089947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1198
5-th percentile2438.95
Q12491.75
median2557.5
Q32623.25
95-th percentile2676.05
Maximum44096
Range42898
Interquartile range (IQR)131.5

Descriptive statistics

Standard deviation2591.7382
Coefficient of variation (CV)0.96924339
Kurtosis254.79171
Mean2673.9808
Median Absolute Deviation (MAD)66
Skewness15.87797
Sum695235
Variance6717106.9
MonotonicityNot monotonic
2023-12-12T08:52:39.266241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2596 1
 
0.3%
1198 1
 
0.3%
1199 1
 
0.3%
2605 1
 
0.3%
2606 1
 
0.3%
2607 1
 
0.3%
1203 1
 
0.3%
1200 1
 
0.3%
1201 1
 
0.3%
1202 1
 
0.3%
Other values (250) 250
66.3%
(Missing) 117
31.0%
ValueCountFrequency (%)
1198 1
0.3%
1199 1
0.3%
1200 1
0.3%
1201 1
0.3%
1202 1
0.3%
1203 1
0.3%
1204 1
0.3%
1219 1
0.3%
1220 1
0.3%
2435 1
0.3%
ValueCountFrequency (%)
44096 1
0.3%
2688 1
0.3%
2687 1
0.3%
2686 1
0.3%
2685 1
0.3%
2684 1
0.3%
2683 1
0.3%
2682 1
0.3%
2681 1
0.3%
2680 1
0.3%

집행부공포일자
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
109 
2022-12-29
34 
2021-11-18
26 
2020-01-02
24 
2020-05-07
20 
Other values (19)
164 

Length

Max length10
Median length10
Mean length8.265252
Min length4

Unique

Unique5 ?
Unique (%)1.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row2019-10-31
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 109
28.9%
2022-12-29 34
 
9.0%
2021-11-18 26
 
6.9%
2020-01-02 24
 
6.4%
2020-05-07 20
 
5.3%
2021-06-17 19
 
5.0%
2023-07-06 17
 
4.5%
2022-01-06 16
 
4.2%
2021-04-15 16
 
4.2%
2022-01-27 14
 
3.7%
Other values (14) 82
21.8%

Length

2023-12-12T08:52:39.453081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 109
28.9%
2022-12-29 34
 
9.0%
2021-11-18 26
 
6.9%
2020-01-02 24
 
6.4%
2020-05-07 20
 
5.3%
2021-06-17 19
 
5.0%
2023-07-06 17
 
4.5%
2022-01-06 16
 
4.2%
2021-04-15 16
 
4.2%
2022-01-27 14
 
3.7%
Other values (14) 82
21.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-09-12
377 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-12
2nd row2023-09-12
3rd row2023-09-12
4th row2023-09-12
5th row2023-09-12

Common Values

ValueCountFrequency (%)
2023-09-12 377
100.0%

Length

2023-12-12T08:52:39.585388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:52:39.689136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-12 377
100.0%

Interactions

2023-12-12T08:52:33.516820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:33.357064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:33.600956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:33.440684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:52:39.766082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제안일자제안회기제안자소관위위원회명소관위원회회부일소관위원회상정일소관위원회의결일소관위원회처리결과본회의상정일본회의의결일본회의처리결과집행부이송일집행부공포번호집행부공포일자
제안일자1.0001.0000.9440.6910.9990.9860.9890.0001.0001.0000.0001.0001.0000.999
제안회기1.0001.0000.0000.2880.9981.0001.0000.0550.9970.9970.1460.9971.0000.996
제안자0.9440.0001.0000.7970.5060.0000.0000.0000.0000.0000.0000.0000.0000.697
소관위위원회명0.6910.2880.7971.0000.8470.9600.9650.2410.6260.6260.2970.6260.0200.721
소관위원회회부일0.9990.9980.5060.8471.0000.9950.9950.2691.0001.0000.3671.0001.0000.997
소관위원회상정일0.9861.0000.0000.9600.9951.0000.9990.5721.0001.0000.4671.0001.0000.997
소관위원회의결일0.9891.0000.0000.9650.9950.9991.0000.5861.0001.0000.4321.0001.0000.997
소관위원회처리결과0.0000.0550.0000.2410.2690.5720.5861.0000.3700.3701.0000.4230.1340.205
본회의상정일1.0000.9970.0000.6261.0001.0001.0000.3701.0001.0000.3631.0001.0001.000
본회의의결일1.0000.9970.0000.6261.0001.0001.0000.3701.0001.0000.3631.0001.0001.000
본회의처리결과0.0000.1460.0000.2970.3670.4670.4321.0000.3630.3631.0000.4230.1340.205
집행부이송일1.0000.9970.0000.6261.0001.0001.0000.4231.0001.0000.4231.0001.0001.000
집행부공포번호1.0001.0000.0000.0201.0001.0001.0000.1341.0001.0000.1341.0001.0001.000
집행부공포일자0.9990.9960.6970.7210.9970.9970.9970.2051.0001.0000.2051.0001.0001.000
2023-12-12T08:52:39.936258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본회의의결일집행부이송일소관위원회처리결과소관위원회회부일소관위위원회명본회의처리결과집행부공포일자본회의상정일
본회의의결일1.0001.0000.2020.9850.3190.1960.9941.000
집행부이송일1.0001.0000.2380.9850.3190.2380.9941.000
소관위원회처리결과0.2020.2381.0000.1250.1671.0000.1710.202
소관위원회회부일0.9850.9850.1251.0000.5370.1900.9470.985
소관위위원회명0.3190.3190.1670.5371.0000.2080.4590.319
본회의처리결과0.1960.2381.0000.1900.2081.0000.1710.196
집행부공포일자0.9940.9940.1710.9470.4590.1711.0000.994
본회의상정일1.0001.0000.2020.9850.3190.1960.9941.000
2023-12-12T08:52:40.062401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제안회기집행부공포번호소관위위원회명소관위원회회부일소관위원회처리결과본회의상정일본회의의결일본회의처리결과집행부이송일집행부공포일자
제안회기1.0000.8750.1510.9580.0490.9660.9660.0660.9670.955
집행부공포번호0.8751.0000.0340.9580.0850.9640.9640.0850.9640.958
소관위위원회명0.1510.0341.0000.5370.1670.3190.3190.2080.3190.459
소관위원회회부일0.9580.9580.5371.0000.1250.9850.9850.1900.9850.947
소관위원회처리결과0.0490.0850.1670.1251.0000.2020.2021.0000.2380.171
본회의상정일0.9660.9640.3190.9850.2021.0001.0000.1961.0000.994
본회의의결일0.9660.9640.3190.9850.2021.0001.0000.1961.0000.994
본회의처리결과0.0660.0850.2080.1901.0000.1960.1961.0000.2380.171
집행부이송일0.9670.9640.3190.9850.2381.0001.0000.2381.0000.994
집행부공포일자0.9550.9580.4590.9470.1710.9940.9940.1710.9941.000

Missing values

2023-12-12T08:52:33.725970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:52:33.972215image/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.
2023-12-12T08:52:34.151982image/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

의안번호의안명제안일자제안회기제안자소관위위원회명소관위원회회부일소관위원회상정일소관위원회의결일소관위원회처리결과본회의상정일본회의의결일본회의처리결과집행부이송일집행부공포번호집행부공포일자데이터기준일자
02019-452019년도 제2회 추가경정 예산안2019-09-09250함양군수예결위2019-09-102019-10-012019-10-08수정가결2019-10-102019-10-10수정가결2019-10-15<NA><NA>2023-09-12
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