Overview

Dataset statistics

Number of variables5
Number of observations108
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory44.2 B

Variable types

Numeric3
Categorical1
Text1

Dataset

Description인천광역시 미추홀구 위원회 현황에 대한 데이터로 담당부서, 위원회명, 위원수 등의 정보를 제공하고 있습니다. 이용에 참고하시기 바랍니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15117524&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 담당부서High correlation
담당부서 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
위원수(당연직) has 2 (1.9%) zerosZeros
위원수(위촉직) has 4 (3.7%) zerosZeros

Reproduction

Analysis started2024-03-18 03:36:21.500038
Analysis finished2024-03-18 03:36:23.818473
Duration2.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.5
Minimum1
Maximum108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-18T12:36:23.901142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.35
Q127.75
median54.5
Q381.25
95-th percentile102.65
Maximum108
Range107
Interquartile range (IQR)53.5

Descriptive statistics

Standard deviation31.32092
Coefficient of variation (CV)0.57469577
Kurtosis-1.2
Mean54.5
Median Absolute Deviation (MAD)27
Skewness0
Sum5886
Variance981
MonotonicityStrictly increasing
2024-03-18T12:36:24.040976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (98) 98
90.7%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%

담당부서
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)31.5%
Missing0
Missing (%)0.0%
Memory size996.0 B
여성가족과
10 
총무과
9 
기획예산실
 
7
문화예술과
 
6
안전총괄과
 
6
Other values (29)
70 

Length

Max length8
Median length5
Mean length4.8888889
Min length3

Unique

Unique11 ?
Unique (%)10.2%

Sample

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

Common Values

ValueCountFrequency (%)
여성가족과 10
 
9.3%
총무과 9
 
8.3%
기획예산실 7
 
6.5%
문화예술과 6
 
5.6%
안전총괄과 6
 
5.6%
일자리정책과 5
 
4.6%
평생학습과 5
 
4.6%
주택관리과 5
 
4.6%
노인장애인복지과 5
 
4.6%
도시경관과 4
 
3.7%
Other values (24) 46
42.6%

Length

2024-03-18T12:36:24.177348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여성가족과 10
 
9.3%
총무과 9
 
8.3%
기획예산실 7
 
6.5%
문화예술과 6
 
5.6%
안전총괄과 6
 
5.6%
일자리정책과 5
 
4.6%
평생학습과 5
 
4.6%
주택관리과 5
 
4.6%
노인장애인복지과 5
 
4.6%
토지정보과 4
 
3.7%
Other values (24) 46
42.6%

위원회명
Text

Distinct107
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-03-18T12:36:24.332125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length10.388889
Min length5

Characters and Unicode

Total characters1122
Distinct characters193
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)98.1%

Sample

1st row구정조정위원회
2nd row지방재정계획심의위원회
3rd row주민참여예산위원회
4th row주민참여예산민관협의회
5th row지방보조금관리위원회
ValueCountFrequency (%)
운영위원회 7
 
5.1%
미추홀구 4
 
2.9%
성과평가위원회 2
 
1.5%
운용심의위원회 2
 
1.5%
지역교육혁신협의회 2
 
1.5%
심의위원회 2
 
1.5%
정신건강심의(사)워원회 1
 
0.7%
유해폐기물 1
 
0.7%
식품진흥기금 1
 
0.7%
발생억제 1
 
0.7%
Other values (113) 113
83.1%
2024-03-18T12:36:24.592788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 111
 
9.9%
원 102
 
9.1%
위 96
 
8.6%
의 49
 
4.4%
심 40
 
3.6%
28
 
2.5%
지 25
 
2.2%
정 24
 
2.1%
사 20
 
1.8%
기 18
 
1.6%
Other values (183) 609
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1090
97.1%
Space Separator 28
 
2.5%
Other Punctuation 2
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 111
 
10.2%
원 102
 
9.4%
위 96
 
8.8%
의 49
 
4.5%
심 40
 
3.7%
지 25
 
2.3%
정 24
 
2.2%
사 20
 
1.8%
기 18
 
1.7%
공 15
 
1.4%
Other values (178) 590
54.1%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1090
97.1%
Common 32
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 111
 
10.2%
원 102
 
9.4%
위 96
 
8.8%
의 49
 
4.5%
심 40
 
3.7%
지 25
 
2.3%
정 24
 
2.2%
사 20
 
1.8%
기 18
 
1.7%
공 15
 
1.4%
Other values (178) 590
54.1%
Common
ValueCountFrequency (%)
28
87.5%
. 1
 
3.1%
( 1
 
3.1%
) 1
 
3.1%
· 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1090
97.1%
ASCII 31
 
2.8%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 111
 
10.2%
원 102
 
9.4%
위 96
 
8.8%
의 49
 
4.5%
심 40
 
3.7%
지 25
 
2.3%
정 24
 
2.2%
사 20
 
1.8%
기 18
 
1.7%
공 15
 
1.4%
Other values (178) 590
54.1%
ASCII
ValueCountFrequency (%)
28
90.3%
. 1
 
3.2%
( 1
 
3.2%
) 1
 
3.2%
None
ValueCountFrequency (%)
· 1
100.0%

위원수(당연직)
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3611111
Minimum0
Maximum16
Zeros2
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-18T12:36:24.684011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile7.65
Maximum16
Range16
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.3539918
Coefficient of variation (CV)0.70036119
Kurtosis7.0711307
Mean3.3611111
Median Absolute Deviation (MAD)1
Skewness2.0831021
Sum363
Variance5.5412773
MonotonicityNot monotonic
2024-03-18T12:36:24.769949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 38
35.2%
3 22
20.4%
1 11
 
10.2%
4 11
 
10.2%
5 7
 
6.5%
7 6
 
5.6%
6 5
 
4.6%
9 3
 
2.8%
8 2
 
1.9%
0 2
 
1.9%
ValueCountFrequency (%)
0 2
 
1.9%
1 11
 
10.2%
2 38
35.2%
3 22
20.4%
4 11
 
10.2%
5 7
 
6.5%
6 5
 
4.6%
7 6
 
5.6%
8 2
 
1.9%
9 3
 
2.8%
ValueCountFrequency (%)
16 1
 
0.9%
9 3
 
2.8%
8 2
 
1.9%
7 6
 
5.6%
6 5
 
4.6%
5 7
 
6.5%
4 11
 
10.2%
3 22
20.4%
2 38
35.2%
1 11
 
10.2%

위원수(위촉직)
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6018519
Minimum0
Maximum50
Zeros4
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-18T12:36:24.869953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q15
median7
Q310
95-th percentile17
Maximum50
Range50
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.0312252
Coefficient of variation (CV)0.81740831
Kurtosis17.067083
Mean8.6018519
Median Absolute Deviation (MAD)2.5
Skewness3.4944353
Sum929
Variance49.438127
MonotonicityNot monotonic
2024-03-18T12:36:24.962486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
7 15
13.9%
5 12
11.1%
8 12
11.1%
10 9
8.3%
6 9
8.3%
4 7
 
6.5%
12 7
 
6.5%
3 6
 
5.6%
9 6
 
5.6%
13 4
 
3.7%
Other values (11) 21
19.4%
ValueCountFrequency (%)
0 4
 
3.7%
1 1
 
0.9%
2 3
 
2.8%
3 6
 
5.6%
4 7
6.5%
5 12
11.1%
6 9
8.3%
7 15
13.9%
8 12
11.1%
9 6
 
5.6%
ValueCountFrequency (%)
50 1
 
0.9%
45 1
 
0.9%
30 1
 
0.9%
18 2
 
1.9%
17 3
2.8%
16 1
 
0.9%
14 3
2.8%
13 4
3.7%
12 7
6.5%
11 1
 
0.9%

Interactions

2024-03-18T12:36:23.478019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:36:22.926440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:36:23.240864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:36:23.541023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:36:23.078775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:36:23.321188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:36:23.613082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:36:23.179671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:36:23.413203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T12:36:25.029854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번담당부서위원수(당연직)위원수(위촉직)
연번1.0000.9880.0000.268
담당부서0.9881.0000.0000.680
위원수(당연직)0.0000.0001.0000.622
위원수(위촉직)0.2680.6800.6221.000
2024-03-18T12:36:25.104044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위원수(당연직)위원수(위촉직)담당부서
연번1.000-0.0420.0460.789
위원수(당연직)-0.0421.000-0.0010.000
위원수(위촉직)0.046-0.0011.0000.244
담당부서0.7890.0000.2441.000

Missing values

2024-03-18T12:36:23.698701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T12:36:23.779938image/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

연번담당부서위원회명위원수(당연직)위원수(위촉직)
01기획예산실구정조정위원회160
12기획예산실지방재정계획심의위원회28
23기획예산실주민참여예산위원회745
34기획예산실주민참여예산민관협의회88
45기획예산실지방보조금관리위원회28
56기획예산실구정평가위원회712
67기획예산실행정규제개혁위원회25
78미디어홍보실구정소식지 나이스미추 편집위원회23
89감사실공직자윤리위원회16
910감사실인권위원회114
연번담당부서위원회명위원수(당연직)위원수(위촉직)
9899도시정비과도시분쟁조정위원회28
99100도시경관과옥외광고심의위원회310
100101도시경관과옥외광고발전기금운용심의위원회33
101102도시경관과공공조형물심의위원회44
102103도시경관과공공디자인진흥위원회210
103104보건행정과지역보건의료심의위원회213
104105건강증진과건강생활실천협의회28
105106치매정신건강과정신건강심의(사)워원회27
106107위생과식품진흥기금 심의위원회25
107108위생과위생관리 심의위원회25