Overview

Dataset statistics

Number of variables8
Number of observations314
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.0 KiB
Average record size in memory68.4 B

Variable types

Categorical4
Numeric4

Dataset

Description인천광역시 미추홀구의 공유재산 시유지 현황에 대한 데이터로 재산구분, 동명, 번지, 호, 공부지목, 면적 등의 정보를 제공합니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15127298/fileData.do

Alerts

재산구분 has constant value ""Constant
위임 재산관리관 has constant value ""Constant
실소유(연)면적 is highly overall correlated with 공부면적 High correlation
공부면적 is highly overall correlated with 실소유(연)면적 High correlation
호 has 10 (3.2%) zerosZeros

Reproduction

Analysis started2024-03-23 04:36:21.286937
Analysis finished2024-03-23 04:36:29.174300
Duration7.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

재산구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
일반재산
314 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반재산 314
100.0%

Length

2024-03-23T04:36:29.451362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T04:36:29.732696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반재산 314
100.0%

위임 재산관리관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
미추홀구청 재무과
314 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미추홀구청 재무과
2nd row미추홀구청 재무과
3rd row미추홀구청 재무과
4th row미추홀구청 재무과
5th row미추홀구청 재무과

Common Values

ValueCountFrequency (%)
미추홀구청 재무과 314
100.0%

Length

2024-03-23T04:36:30.016326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T04:36:30.380844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미추홀구청 314
50.0%
재무과 314
50.0%

동명
Categorical

Distinct7
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
주안동
83 
숭의동
77 
도화동
55 
용현동
46 
학익동
30 
Other values (2)
23 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주안동 83
26.4%
숭의동 77
24.5%
도화동 55
17.5%
용현동 46
14.6%
학익동 30
 
9.6%
문학동 18
 
5.7%
관교동 5
 
1.6%

Length

2024-03-23T04:36:30.718412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T04:36:31.142856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주안동 83
26.4%
숭의동 77
24.5%
도화동 55
17.5%
용현동 46
14.6%
학익동 30
 
9.6%
문학동 18
 
5.7%
관교동 5
 
1.6%

번지
Real number (ℝ)

Distinct154
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean441.07643
Minimum1
Maximum1599
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-23T04:36:31.597840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.15
Q1106.75
median327
Q3530.75
95-th percentile1536.35
Maximum1599
Range1598
Interquartile range (IQR)424

Descriptive statistics

Standard deviation455.7668
Coefficient of variation (CV)1.0333057
Kurtosis1.1505266
Mean441.07643
Median Absolute Deviation (MAD)216
Skewness1.493424
Sum138498
Variance207723.37
MonotonicityNot monotonic
2024-03-23T04:36:32.240602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
454 9
 
2.9%
413 9
 
2.9%
234 8
 
2.5%
82 7
 
2.2%
360 6
 
1.9%
124 5
 
1.6%
1512 5
 
1.6%
55 5
 
1.6%
1539 5
 
1.6%
33 5
 
1.6%
Other values (144) 250
79.6%
ValueCountFrequency (%)
1 3
1.0%
2 2
0.6%
4 1
 
0.3%
5 3
1.0%
7 1
 
0.3%
8 2
0.6%
10 2
0.6%
13 2
0.6%
24 1
 
0.3%
31 3
1.0%
ValueCountFrequency (%)
1599 1
 
0.3%
1574 1
 
0.3%
1546 1
 
0.3%
1539 5
1.6%
1538 4
1.3%
1537 4
1.3%
1536 3
1.0%
1533 1
 
0.3%
1516 2
 
0.6%
1515 2
 
0.6%

호
Real number (ℝ)

ZEROS 

Distinct122
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.952229
Minimum0
Maximum612
Zeros10
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-23T04:36:32.804623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median22.5
Q354.75
95-th percentile253.75
Maximum612
Range612
Interquartile range (IQR)45.75

Descriptive statistics

Standard deviation103.44516
Coefficient of variation (CV)1.7254598
Kurtosis11.138408
Mean59.952229
Median Absolute Deviation (MAD)16.5
Skewness3.2069913
Sum18825
Variance10700.902
MonotonicityNot monotonic
2024-03-23T04:36:33.319701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 13
 
4.1%
1 12
 
3.8%
9 11
 
3.5%
0 10
 
3.2%
7 10
 
3.2%
14 8
 
2.5%
6 8
 
2.5%
4 8
 
2.5%
18 8
 
2.5%
5 7
 
2.2%
Other values (112) 219
69.7%
ValueCountFrequency (%)
0 10
3.2%
1 12
3.8%
2 13
4.1%
3 1
 
0.3%
4 8
2.5%
5 7
2.2%
6 8
2.5%
7 10
3.2%
8 5
 
1.6%
9 11
3.5%
ValueCountFrequency (%)
612 1
0.3%
611 1
0.3%
596 1
0.3%
522 1
0.3%
513 1
0.3%
459 1
0.3%
438 1
0.3%
429 1
0.3%
425 1
0.3%
409 1
0.3%

공부지목
Categorical

Distinct9
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
대
172 
도로
56 
잡종지
34 
전
27 
구거
18 
Other values (4)
 
7

Length

Max length4
Median length1
Mean length1.4968153
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row대
2nd row잡종지
3rd row잡종지
4th row전
5th row잡종지

Common Values

ValueCountFrequency (%)
대 172
54.8%
도로 56
 
17.8%
잡종지 34
 
10.8%
전 27
 
8.6%
구거 18
 
5.7%
철도용지 3
 
1.0%
답 2
 
0.6%
학교용지 1
 
0.3%
주차장 1
 
0.3%

Length

2024-03-23T04:36:34.046116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T04:36:34.442144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 172
54.8%
도로 56
 
17.8%
잡종지 34
 
10.8%
전 27
 
8.6%
구거 18
 
5.7%
철도용지 3
 
1.0%
답 2
 
0.6%
학교용지 1
 
0.3%
주차장 1
 
0.3%

실소유(연)면적
Real number (ℝ)

HIGH CORRELATION 

Distinct238
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.52223
Minimum0.1
Maximum4641
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-23T04:36:34.954999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile2
Q110.21
median36
Q3100.825
95-th percentile348.505
Maximum4641
Range4640.9
Interquartile range (IQR)90.615

Descriptive statistics

Standard deviation379.01993
Coefficient of variation (CV)3.2250914
Kurtosis92.615089
Mean117.52223
Median Absolute Deviation (MAD)29.265
Skewness8.960591
Sum36901.98
Variance143656.11
MonotonicityNot monotonic
2024-03-23T04:36:35.418112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 8
 
2.5%
3.0 7
 
2.2%
13.0 7
 
2.2%
7.0 5
 
1.6%
4.0 5
 
1.6%
5.0 5
 
1.6%
11.0 5
 
1.6%
26.0 4
 
1.3%
30.0 4
 
1.3%
10.0 4
 
1.3%
Other values (228) 260
82.8%
ValueCountFrequency (%)
0.1 1
 
0.3%
0.16 1
 
0.3%
0.8 1
 
0.3%
0.83 1
 
0.3%
1.0 8
2.5%
1.8 1
 
0.3%
2.0 4
1.3%
2.5 1
 
0.3%
2.6 1
 
0.3%
2.7 1
 
0.3%
ValueCountFrequency (%)
4641.0 1
0.3%
3675.6 1
0.3%
2339.4 1
0.3%
1134.59 1
0.3%
958.98 1
0.3%
937.0 1
0.3%
920.0 1
0.3%
666.67 1
0.3%
665.0 1
0.3%
574.0 1
0.3%

공부면적
Real number (ℝ)

HIGH CORRELATION 

Distinct232
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148.4965
Minimum0.1
Maximum4641
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-23T04:36:35.777750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile2.565
Q111.975
median42.25
Q3113.675
95-th percentile438.285
Maximum4641
Range4640.9
Interquartile range (IQR)101.7

Descriptive statistics

Standard deviation433.68368
Coefficient of variation (CV)2.9204977
Kurtosis56.40942
Mean148.4965
Median Absolute Deviation (MAD)35.05
Skewness6.9080882
Sum46627.9
Variance188081.53
MonotonicityNot monotonic
2024-03-23T04:36:36.269339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 9
 
2.9%
13.0 7
 
2.2%
3.0 7
 
2.2%
11.0 5
 
1.6%
7.0 5
 
1.6%
26.0 5
 
1.6%
4.0 5
 
1.6%
5.0 5
 
1.6%
10.0 4
 
1.3%
2.0 4
 
1.3%
Other values (222) 258
82.2%
ValueCountFrequency (%)
0.1 1
 
0.3%
1.0 9
2.9%
1.8 1
 
0.3%
2.0 4
1.3%
2.5 1
 
0.3%
2.6 1
 
0.3%
2.9 1
 
0.3%
3.0 7
2.2%
3.5 1
 
0.3%
4.0 5
1.6%
ValueCountFrequency (%)
4641.0 1
0.3%
3675.6 1
0.3%
2623.1 1
0.3%
2339.4 1
0.3%
1880.7 1
0.3%
1762.3 1
0.3%
1620.5 1
0.3%
1255.0 1
0.3%
937.0 1
0.3%
920.0 1
0.3%

Interactions

2024-03-23T04:36:26.502871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:22.082688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:23.457101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:25.018701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:26.970142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:22.455319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:23.936023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:25.432106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:27.427302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:22.766624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:24.335629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:25.779052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:27.891885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:23.175156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:24.662495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:36:26.221490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T04:36:36.706012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동명번지호공부지목실소유(연)면적공부면적
동명1.0000.5670.4010.5060.3010.322
번지0.5671.0000.2560.7890.0000.151
호0.4010.2561.0000.0000.0000.000
공부지목0.5060.7890.0001.0000.0000.309
실소유(연)면적0.3010.0000.0000.0001.0000.928
공부면적0.3220.1510.0000.3090.9281.000
2024-03-23T04:36:36.991254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동명공부지목
동명1.0000.296
공부지목0.2961.000
2024-03-23T04:36:37.309062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번지호실소유(연)면적공부면적동명공부지목
번지1.000-0.1100.0720.0530.3430.363
호-0.1101.000-0.298-0.3200.2150.000
실소유(연)면적0.072-0.2981.0000.9250.1840.000
공부면적0.053-0.3200.9251.0000.1780.156
동명0.3430.2150.1840.1781.0000.296
공부지목0.3630.0000.0000.1560.2961.000

Missing values

2024-03-23T04:36:28.391870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T04:36:28.818587image/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

재산구분위임 재산관리관동명번지호공부지목실소유(연)면적공부면적
0일반재산미추홀구청 재무과관교동3192대203.8203.8
1일반재산미추홀구청 재무과관교동32129잡종지0.161.0
2일반재산미추홀구청 재무과관교동3230잡종지74.874.8
3일반재산미추홀구청 재무과관교동45114전38.038.0
4일반재산미추홀구청 재무과관교동5090잡종지3675.63675.6
5일반재산미추홀구청 재무과도화동24136대2.92.9
6일반재산미추홀구청 재무과도화동816대20.720.7
7일반재산미추홀구청 재무과도화동819대427.4427.4
8일반재산미추홀구청 재무과도화동8816대20.520.5
9일반재산미추홀구청 재무과도화동9215대10.310.3
재산구분위임 재산관리관동명번지호공부지목실소유(연)면적공부면적
304일반재산미추홀구청 재무과학익동312203대10.010.0
305일반재산미추홀구청 재무과학익동32120대142.0142.0
306일반재산미추홀구청 재무과학익동3319대216.0216.0
307일반재산미추홀구청 재무과학익동3324대53.053.0
308일반재산미추홀구청 재무과학익동3365잡종지4641.04641.0
309일반재산미추홀구청 재무과학익동33619잡종지937.0937.0
310일반재산미추홀구청 재무과학익동42216대73.073.0
311일반재산미추홀구청 재무과학익동4924전89.089.0
312일반재산미추홀구청 재무과학익동6831잡종지200.7200.7
313일반재산미추홀구청 재무과학익동68410잡종지294.5294.5