Overview

Dataset statistics

Number of variables8
Number of observations122
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory69.1 B

Variable types

Categorical4
Numeric4

Dataset

Description인천광역시 미추홀구의 용현동지역 구유지현황 데이터로 재산구분,재산관리관,동명,지목, 면적 등의 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15099939/fileData.do

Alerts

재산구분 has constant value ""Constant
재산관리관 has constant value ""Constant
동명 has constant value ""Constant
번지 is highly overall correlated with 공부지목High correlation
실소유면적 is highly overall correlated with 공부면적 High correlation
공부면적 is highly overall correlated with 실소유면적 High correlation
공부지목 is highly overall correlated with 번지High correlation
공부지목 is highly imbalanced (66.0%)Imbalance

Reproduction

Analysis started2023-12-12 12:10:53.497329
Analysis finished2023-12-12 12:10:56.341784
Duration2.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

재산구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
일반재산
122 

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 122
100.0%

Length

2023-12-12T21:10:56.413334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:10:56.516549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반재산 122
100.0%

재산관리관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
미추홀구청 재무과
122 

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 122
100.0%

Length

2023-12-12T21:10:56.618032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:10:56.730628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미추홀구청 122
50.0%
재무과 122
50.0%

동명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
용현동
122 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용현동 122
100.0%

Length

2023-12-12T21:10:56.863621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:10:56.990388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용현동 122
100.0%

번지
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean349.10656
Minimum58
Maximum685
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T21:10:57.117045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58
5-th percentile130.05
Q1145
median441.5
Q3456
95-th percentile632
Maximum685
Range627
Interquartile range (IQR)311

Descriptive statistics

Standard deviation182.16516
Coefficient of variation (CV)0.52180389
Kurtosis-1.3658639
Mean349.10656
Median Absolute Deviation (MAD)149.5
Skewness-0.04118871
Sum42591
Variance33184.146
MonotonicityIncreasing
2023-12-12T21:10:57.271384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
456 15
 
12.3%
454 14
 
11.5%
141 11
 
9.0%
523 6
 
4.9%
145 6
 
4.9%
147 6
 
4.9%
450 5
 
4.1%
685 4
 
3.3%
632 4
 
3.3%
433 4
 
3.3%
Other values (30) 47
38.5%
ValueCountFrequency (%)
58 2
1.6%
68 1
 
0.8%
99 1
 
0.8%
126 1
 
0.8%
128 1
 
0.8%
130 1
 
0.8%
131 2
1.6%
132 4
3.3%
133 1
 
0.8%
136 1
 
0.8%
ValueCountFrequency (%)
685 4
3.3%
632 4
3.3%
627 2
 
1.6%
620 1
 
0.8%
618 1
 
0.8%
542 1
 
0.8%
541 2
 
1.6%
523 6
4.9%
509 1
 
0.8%
490 1
 
0.8%

호
Real number (ℝ)

Distinct96
Distinct (%)79.3%
Missing1
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean152.91736
Minimum2
Maximum813
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T21:10:57.804564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q124
median63
Q3198
95-th percentile573
Maximum813
Range811
Interquartile range (IQR)174

Descriptive statistics

Standard deviation195.71099
Coefficient of variation (CV)1.2798481
Kurtosis0.95506865
Mean152.91736
Median Absolute Deviation (MAD)48
Skewness1.4935714
Sum18503
Variance38302.793
MonotonicityNot monotonic
2023-12-12T21:10:57.991026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
65 4
 
3.3%
7 3
 
2.5%
13 3
 
2.5%
8 3
 
2.5%
66 3
 
2.5%
3 3
 
2.5%
31 2
 
1.6%
15 2
 
1.6%
6 2
 
1.6%
61 2
 
1.6%
Other values (86) 94
77.0%
ValueCountFrequency (%)
2 1
 
0.8%
3 3
2.5%
5 1
 
0.8%
6 2
1.6%
7 3
2.5%
8 3
2.5%
9 1
 
0.8%
10 1
 
0.8%
11 1
 
0.8%
12 1
 
0.8%
ValueCountFrequency (%)
813 1
0.8%
620 1
0.8%
619 1
0.8%
584 1
0.8%
581 1
0.8%
579 1
0.8%
573 1
0.8%
558 1
0.8%
556 1
0.8%
554 1
0.8%

공부지목
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
대
105 
잡종지
 
5
전
 
5
철도용지
 
4
답
 
2

Length

Max length4
Median length1
Mean length1.1967213
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
대 105
86.1%
잡종지 5
 
4.1%
전 5
 
4.1%
철도용지 4
 
3.3%
답 2
 
1.6%
주차장 1
 
0.8%

Length

2023-12-12T21:10:58.174328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:10:58.322844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 105
86.1%
잡종지 5
 
4.1%
전 5
 
4.1%
철도용지 4
 
3.3%
답 2
 
1.6%
주차장 1
 
0.8%

실소유면적
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.834426
Minimum0.6
Maximum347.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T21:10:58.465638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile1.03
Q16.15
median16
Q336
95-th percentile81.805
Maximum347.7
Range347.1
Interquartile range (IQR)29.85

Descriptive statistics

Standard deviation40.807342
Coefficient of variation (CV)1.4660745
Kurtosis31.686996
Mean27.834426
Median Absolute Deviation (MAD)12.9
Skewness4.6927587
Sum3395.8
Variance1665.2391
MonotonicityNot monotonic
2023-12-12T21:10:58.626303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.0 9
 
7.4%
1.0 6
 
4.9%
13.0 5
 
4.1%
2.0 5
 
4.1%
8.0 5
 
4.1%
4.0 4
 
3.3%
11.0 4
 
3.3%
17.0 4
 
3.3%
18.0 4
 
3.3%
10.0 4
 
3.3%
Other values (51) 72
59.0%
ValueCountFrequency (%)
0.6 1
 
0.8%
1.0 6
4.9%
1.6 1
 
0.8%
2.0 5
4.1%
3.0 9
7.4%
3.2 1
 
0.8%
4.0 4
3.3%
5.0 1
 
0.8%
5.3 1
 
0.8%
6.0 2
 
1.6%
ValueCountFrequency (%)
347.7 1
0.8%
166.0 1
0.8%
136.0 1
0.8%
103.0 1
0.8%
97.0 1
0.8%
89.0 1
0.8%
81.9 1
0.8%
80.0 1
0.8%
79.0 2
1.6%
78.0 1
0.8%

공부면적
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean272.77049
Minimum1
Maximum14175.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T21:10:58.803123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median18.5
Q348
95-th percentile164.95
Maximum14175.9
Range14174.9
Interquartile range (IQR)40

Descriptive statistics

Standard deviation1552.8506
Coefficient of variation (CV)5.6928833
Kurtosis61.612164
Mean272.77049
Median Absolute Deviation (MAD)15
Skewness7.625641
Sum33278
Variance2411344.9
MonotonicityNot monotonic
2023-12-12T21:10:58.976519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.0 8
 
6.6%
2.0 6
 
4.9%
8.0 6
 
4.9%
1.0 6
 
4.9%
13.0 5
 
4.1%
30.0 4
 
3.3%
11.0 4
 
3.3%
17.0 4
 
3.3%
4.0 4
 
3.3%
7.0 3
 
2.5%
Other values (53) 72
59.0%
ValueCountFrequency (%)
1.0 6
4.9%
2.0 6
4.9%
3.0 8
6.6%
4.0 4
3.3%
6.0 2
 
1.6%
6.6 1
 
0.8%
7.0 3
 
2.5%
8.0 6
4.9%
10.0 3
 
2.5%
11.0 4
3.3%
ValueCountFrequency (%)
14175.9 1
0.8%
8989.0 1
0.8%
3876.9 1
0.8%
1803.4 1
0.8%
728.0 1
0.8%
204.0 1
0.8%
166.0 1
0.8%
145.0 2
1.6%
129.3 1
0.8%
116.0 1
0.8%

Interactions

2023-12-12T21:10:55.548008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:53.776519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:54.524719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:55.065869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:55.667678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:53.958539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:54.672279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:55.163740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:55.805434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:54.144166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:54.805382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:55.299076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:55.915149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:54.335901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:54.932891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:55.420660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:10:59.114760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번지호공부지목실소유면적공부면적
번지1.0000.1190.7850.2930.347
호0.1191.0000.1070.0000.000
공부지목0.7850.1071.0000.6290.607
실소유면적0.2930.0000.6291.0000.620
공부면적0.3470.0000.6070.6201.000
2023-12-12T21:10:59.234052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번지호실소유면적공부면적공부지목
번지1.0000.1740.0550.1560.556
호0.1741.000-0.174-0.2900.047
실소유면적0.055-0.1741.0000.8340.270
공부면적0.156-0.2900.8341.0000.465
공부지목0.5560.0470.2700.4651.000

Missing values

2023-12-12T21:10:56.099516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:10:56.272402image/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

재산구분재산관리관동명번지호공부지목실소유면적공부면적
0일반재산미추홀구청 재무과용현동5810대13.013.0
1일반재산미추홀구청 재무과용현동5834대7.07.0
2일반재산미추홀구청 재무과용현동6827대69.169.1
3일반재산미추홀구청 재무과용현동9914대17.817.8
4일반재산미추홀구청 재무과용현동12619대18.1129.3
5일반재산미추홀구청 재무과용현동12822주차장20.520.5
6일반재산미추홀구청 재무과용현동13051대2.02.0
7일반재산미추홀구청 재무과용현동13134대8.08.0
8일반재산미추홀구청 재무과용현동13136대1.01.0
9일반재산미추홀구청 재무과용현동13247대16.016.0
재산구분재산관리관동명번지호공부지목실소유면적공부면적
112일반재산미추홀구청 재무과용현동62765대26.026.0
113일반재산미추홀구청 재무과용현동62766대80.080.0
114일반재산미추홀구청 재무과용현동63259대13.013.0
115일반재산미추홀구청 재무과용현동63261대13.013.0
116일반재산미추홀구청 재무과용현동63263대10.010.0
117일반재산미추홀구청 재무과용현동63271대40.049.0
118일반재산미추홀구청 재무과용현동685<NA>철도용지33.31803.4
119일반재산미추홀구청 재무과용현동6853철도용지37.28989.0
120일반재산미추홀구청 재무과용현동68512철도용지1.614175.9
121일반재산미추홀구청 재무과용현동68513철도용지347.73876.9