Overview

Dataset statistics

Number of variables7
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory66.7 B

Variable types

Text1
Numeric5
DateTime1

Dataset

Description인천광역시 서구 구청장 주민소환 투표 청구권자 총수 및 최소서명인수 데이터 로 행정동명 주민수,등록외국인수, 청구권자 총계, 최소서명인수 등으로 구성 되어 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15091236&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
주민수(19세이상) is highly overall correlated with 등록외국인수(19세이상) and 3 other fieldsHigh correlation
등록외국인수(19세이상) is highly overall correlated with 주민수(19세이상) and 3 other fieldsHigh correlation
청구권자 총수 is highly overall correlated with 주민수(19세이상) and 3 other fieldsHigh correlation
서명인수 is highly overall correlated with 주민수(19세이상) and 3 other fieldsHigh correlation
최소서명인수 is highly overall correlated with 주민수(19세이상) and 3 other fieldsHigh correlation
행정동명 has unique valuesUnique
주민수(19세이상) has unique valuesUnique
청구권자 총수 has unique valuesUnique
서명인수 has unique valuesUnique

Reproduction

Analysis started2024-01-28 13:43:16.234774
Analysis finished2024-01-28 13:43:18.755747
Duration2.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-01-28T22:43:18.867302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9130435
Min length3

Characters and Unicode

Total characters90
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row검암경서동
2nd row연희동
3rd row청라1동
4th row청라2동
5th row청라3동
ValueCountFrequency (%)
검암경서동 1
 
4.3%
가좌1동 1
 
4.3%
마전동 1
 
4.3%
오류왕길동 1
 
4.3%
당하동 1
 
4.3%
원당동 1
 
4.3%
불로대곡동 1
 
4.3%
검단동 1
 
4.3%
가좌4동 1
 
4.3%
가좌3동 1
 
4.3%
Other values (13) 13
56.5%
2024-01-28T22:43:19.167381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 23
25.6%
가 7
 
7.8%
좌 4
 
4.4%
라 4
 
4.4%
1 4
 
4.4%
2 4
 
4.4%
3 4
 
4.4%
석 3
 
3.3%
정 3
 
3.3%
남 3
 
3.3%
Other values (26) 31
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77
85.6%
Decimal Number 13
 
14.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 23
29.9%
가 7
 
9.1%
좌 4
 
5.2%
라 4
 
5.2%
석 3
 
3.9%
정 3
 
3.9%
남 3
 
3.9%
청 3
 
3.9%
당 2
 
2.6%
원 2
 
2.6%
Other values (22) 23
29.9%
Decimal Number
ValueCountFrequency (%)
1 4
30.8%
2 4
30.8%
3 4
30.8%
4 1
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77
85.6%
Common 13
 
14.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 23
29.9%
가 7
 
9.1%
좌 4
 
5.2%
라 4
 
5.2%
석 3
 
3.9%
정 3
 
3.9%
남 3
 
3.9%
청 3
 
3.9%
당 2
 
2.6%
원 2
 
2.6%
Other values (22) 23
29.9%
Common
ValueCountFrequency (%)
1 4
30.8%
2 4
30.8%
3 4
30.8%
4 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77
85.6%
ASCII 13
 
14.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 23
29.9%
가 7
 
9.1%
좌 4
 
5.2%
라 4
 
5.2%
석 3
 
3.9%
정 3
 
3.9%
남 3
 
3.9%
청 3
 
3.9%
당 2
 
2.6%
원 2
 
2.6%
Other values (22) 23
29.9%
ASCII
ValueCountFrequency (%)
1 4
30.8%
2 4
30.8%
3 4
30.8%
4 1
 
7.7%

주민수(19세이상)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19741.739
Minimum5860
Maximum37288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-28T22:43:19.284106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5860
5-th percentile8659.5
Q112415.5
median18700
Q323465.5
95-th percentile36399.1
Maximum37288
Range31428
Interquartile range (IQR)11050

Descriptive statistics

Standard deviation8785.884
Coefficient of variation (CV)0.44504103
Kurtosis-0.21798571
Mean19741.739
Median Absolute Deviation (MAD)6155
Skewness0.55420299
Sum454060
Variance77191757
MonotonicityNot monotonic
2024-01-28T22:43:19.378020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
37288 1
 
4.3%
35527 1
 
4.3%
12545 1
 
4.3%
18079 1
 
4.3%
20820 1
 
4.3%
22214 1
 
4.3%
18700 1
 
4.3%
18509 1
 
4.3%
27353 1
 
4.3%
9123 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
5860 1
4.3%
8608 1
4.3%
9123 1
4.3%
11054 1
4.3%
11637 1
4.3%
12286 1
4.3%
12545 1
4.3%
14883 1
4.3%
17073 1
4.3%
18079 1
4.3%
ValueCountFrequency (%)
37288 1
4.3%
36496 1
4.3%
35527 1
4.3%
27353 1
4.3%
26349 1
4.3%
23753 1
4.3%
23178 1
4.3%
22844 1
4.3%
22214 1
4.3%
20820 1
4.3%

등록외국인수(19세이상)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.913043
Minimum6
Maximum111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-28T22:43:19.511444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile15.3
Q127.5
median44
Q369.5
95-th percentile104.5
Maximum111
Range105
Interquartile range (IQR)42

Descriptive statistics

Standard deviation30.241322
Coefficient of variation (CV)0.60588014
Kurtosis-0.5647095
Mean49.913043
Median Absolute Deviation (MAD)22
Skewness0.61695969
Sum1148
Variance914.53755
MonotonicityNot monotonic
2024-01-28T22:43:19.643072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
18 2
 
8.7%
111 1
 
4.3%
73 1
 
4.3%
15 1
 
4.3%
66 1
 
4.3%
80 1
 
4.3%
34 1
 
4.3%
30 1
 
4.3%
105 1
 
4.3%
25 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
6 1
4.3%
15 1
4.3%
18 2
8.7%
20 1
4.3%
25 1
4.3%
30 1
4.3%
33 1
4.3%
34 1
4.3%
36 1
4.3%
38 1
4.3%
ValueCountFrequency (%)
111 1
4.3%
105 1
4.3%
100 1
4.3%
82 1
4.3%
80 1
4.3%
73 1
4.3%
66 1
4.3%
60 1
4.3%
53 1
4.3%
51 1
4.3%

청구권자 총수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19791.652
Minimum5866
Maximum37399
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-28T22:43:19.736655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5866
5-th percentile8680
Q112439.5
median18734
Q323509.5
95-th percentile36455
Maximum37399
Range31533
Interquartile range (IQR)11070

Descriptive statistics

Standard deviation8804.6492
Coefficient of variation (CV)0.44486681
Kurtosis-0.21818395
Mean19791.652
Median Absolute Deviation (MAD)6174
Skewness0.55388475
Sum455208
Variance77521848
MonotonicityNot monotonic
2024-01-28T22:43:19.828214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
37399 1
 
4.3%
35609 1
 
4.3%
12560 1
 
4.3%
18097 1
 
4.3%
20886 1
 
4.3%
22294 1
 
4.3%
18734 1
 
4.3%
18539 1
 
4.3%
27458 1
 
4.3%
9148 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
5866 1
4.3%
8628 1
4.3%
9148 1
4.3%
11127 1
4.3%
11697 1
4.3%
12319 1
4.3%
12560 1
4.3%
14919 1
4.3%
17091 1
4.3%
18097 1
4.3%
ValueCountFrequency (%)
37399 1
4.3%
36549 1
4.3%
35609 1
4.3%
27458 1
4.3%
26393 1
4.3%
23803 1
4.3%
23216 1
4.3%
22895 1
4.3%
22294 1
4.3%
20886 1
4.3%

서명인수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2969.2174
Minimum880
Maximum5610
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-28T22:43:19.933034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum880
5-th percentile1302.8
Q11866
median2811
Q33527
95-th percentile5468.9
Maximum5610
Range4730
Interquartile range (IQR)1661

Descriptive statistics

Standard deviation1320.6982
Coefficient of variation (CV)0.44479672
Kurtosis-0.21823499
Mean2969.2174
Median Absolute Deviation (MAD)927
Skewness0.5538357
Sum68292
Variance1744243.6
MonotonicityNot monotonic
2024-01-28T22:43:20.036101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
5610 1
 
4.3%
5342 1
 
4.3%
1884 1
 
4.3%
2715 1
 
4.3%
3133 1
 
4.3%
3345 1
 
4.3%
2811 1
 
4.3%
2781 1
 
4.3%
4119 1
 
4.3%
1373 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
880 1
4.3%
1295 1
4.3%
1373 1
4.3%
1670 1
4.3%
1755 1
4.3%
1848 1
4.3%
1884 1
4.3%
2238 1
4.3%
2564 1
4.3%
2715 1
4.3%
ValueCountFrequency (%)
5610 1
4.3%
5483 1
4.3%
5342 1
4.3%
4119 1
4.3%
3959 1
4.3%
3571 1
4.3%
3483 1
4.3%
3435 1
4.3%
3345 1
4.3%
3133 1
4.3%

최소서명인수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2848.5217
Minimum880
Maximum4553
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-28T22:43:20.136652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum880
5-th percentile1302.8
Q11866
median2811
Q33527
95-th percentile4553
Maximum4553
Range3673
Interquartile range (IQR)1661

Descriptive statistics

Standard deviation1100.423
Coefficient of variation (CV)0.38631371
Kurtosis-0.97109113
Mean2848.5217
Median Absolute Deviation (MAD)927
Skewness-0.01598081
Sum65516
Variance1210930.8
MonotonicityNot monotonic
2024-01-28T22:43:20.271899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
4553 3
 
13.0%
3571 1
 
4.3%
1884 1
 
4.3%
2715 1
 
4.3%
3133 1
 
4.3%
3345 1
 
4.3%
2811 1
 
4.3%
2781 1
 
4.3%
4119 1
 
4.3%
1373 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
880 1
4.3%
1295 1
4.3%
1373 1
4.3%
1670 1
4.3%
1755 1
4.3%
1848 1
4.3%
1884 1
4.3%
2238 1
4.3%
2564 1
4.3%
2715 1
4.3%
ValueCountFrequency (%)
4553 3
13.0%
4119 1
 
4.3%
3959 1
 
4.3%
3571 1
 
4.3%
3483 1
 
4.3%
3435 1
 
4.3%
3345 1
 
4.3%
3133 1
 
4.3%
2998 1
 
4.3%
2811 1
 
4.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2022-09-30 00:00:00
Maximum2022-09-30 00:00:00
2024-01-28T22:43:20.364441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:20.435566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T22:43:18.223514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:16.773371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.135905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.472902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.849731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:18.298643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:16.843499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.209081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.551042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.920141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:18.367824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:16.917204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.272785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.627899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.984377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:18.442756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:16.989060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.339409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.702670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:18.057263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:18.512439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.058084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.402532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:17.769283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:43:18.132433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T22:43:20.495115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명주민수(19세이상)등록외국인수(19세이상)청구권자 총수서명인수최소서명인수
행정동명1.0001.0001.0001.0001.0001.000
주민수(19세이상)1.0001.0000.4971.0001.0000.928
등록외국인수(19세이상)1.0000.4971.0000.4970.4970.356
청구권자 총수1.0001.0000.4971.0001.0000.928
서명인수1.0001.0000.4971.0001.0000.928
최소서명인수1.0000.9280.3560.9280.9281.000
2024-01-28T22:43:20.590987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주민수(19세이상)등록외국인수(19세이상)청구권자 총수서명인수최소서명인수
주민수(19세이상)1.0000.6431.0001.0000.999
등록외국인수(19세이상)0.6431.0000.6430.6430.641
청구권자 총수1.0000.6431.0001.0000.999
서명인수1.0000.6431.0001.0000.999
최소서명인수0.9990.6410.9990.9991.000

Missing values

2024-01-28T22:43:18.614995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T22:43:18.717929image/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

행정동명주민수(19세이상)등록외국인수(19세이상)청구권자 총수서명인수최소서명인수데이터기준일자
0검암경서동3728811137399561045532022-09-30
1연희동355278235609534245532022-09-30
2청라1동237535023803357135712022-09-30
3청라2동364965336549548345532022-09-30
4청라3동231783823216348334832022-09-30
5가정1동228445122895343534352022-09-30
6가정2동5860658668808802022-09-30
7가정3동8608208628129512952022-09-30
8신현원창동263494426393395939592022-09-30
9석남1동1988110019981299829982022-09-30
행정동명주민수(19세이상)등록외국인수(19세이상)청구권자 총수서명인수최소서명인수데이터기준일자
13가좌2동170731817091256425642022-09-30
14가좌3동148833614919223822382022-09-30
15가좌4동9123259148137313732022-09-30
16검단동2735310527458411941192022-09-30
17불로대곡동185093018539278127812022-09-30
18원당동187003418734281128112022-09-30
19당하동222148022294334533452022-09-30
20오류왕길동208206620886313331332022-09-30
21마전동180791818097271527152022-09-30
22아라동125451512560188418842022-09-30