Overview

Dataset statistics

Number of variables8
Number of observations102
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory69.3 B

Variable types

Categorical4
Numeric4

Dataset

Description인천광역시 미추홀구의 학익동지역 구유지 현황 데이터로 재산구분, 재산관리관, 동명, 번지, 지목, 면적 등에 대한 데이터를 제공합니다
URLhttps://www.data.go.kr/data/15099944/fileData.do

Alerts

재산구분 has constant value ""Constant
재산관리관 has constant value ""Constant
동명 has constant value ""Constant
실소유면적 is highly overall correlated with 공부면적 High correlation
공부면적 is highly overall correlated with 실소유면적 High correlation

Reproduction

Analysis started2023-12-12 23:39:55.877376
Analysis finished2023-12-12 23:39:57.401379
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

재산구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
일반재산
102 

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 102
100.0%

Length

2023-12-13T08:39:57.449583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:39:57.520033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반재산 102
100.0%

재산관리관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
미추홀구청 재무과
102 

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 102
100.0%

Length

2023-12-13T08:39:57.591524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:39:57.661728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미추홀구청 102
50.0%
재무과 102
50.0%

동명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
학익동
102 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
학익동 102
100.0%

Length

2023-12-13T08:39:57.736782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:39:57.827726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학익동 102
100.0%

번지
Real number (ℝ)

Distinct25
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean297.65686
Minimum2
Maximum649
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T08:39:57.912772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile53.2
Q1304
median306
Q3312
95-th percentile332
Maximum649
Range647
Interquartile range (IQR)8

Descriptive statistics

Standard deviation95.251153
Coefficient of variation (CV)0.32000321
Kurtosis6.8401419
Mean297.65686
Median Absolute Deviation (MAD)5
Skewness-0.34205822
Sum30361
Variance9072.7821
MonotonicityIncreasing
2023-12-13T08:39:57.999734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
306 43
42.2%
312 20
19.6%
288 4
 
3.9%
302 4
 
3.9%
304 3
 
2.9%
294 2
 
2.0%
649 2
 
2.0%
332 2
 
2.0%
329 2
 
2.0%
5 2
 
2.0%
Other values (15) 18
17.6%
ValueCountFrequency (%)
2 2
2.0%
5 2
2.0%
10 1
 
1.0%
45 1
 
1.0%
209 1
 
1.0%
210 2
2.0%
213 1
 
1.0%
263 2
2.0%
288 4
3.9%
289 1
 
1.0%
ValueCountFrequency (%)
649 2
 
2.0%
536 1
 
1.0%
518 1
 
1.0%
456 1
 
1.0%
332 2
 
2.0%
331 1
 
1.0%
329 2
 
2.0%
314 1
 
1.0%
312 20
19.6%
306 43
42.2%

호
Real number (ℝ)

Distinct83
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.22549
Minimum1
Maximum348
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T08:39:58.097661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111.25
median91
Q3201.25
95-th percentile284.95
Maximum348
Range347
Interquartile range (IQR)190

Descriptive statistics

Standard deviation103.18616
Coefficient of variation (CV)0.91133333
Kurtosis-1.0697582
Mean113.22549
Median Absolute Deviation (MAD)82.5
Skewness0.51926746
Sum11549
Variance10647.384
MonotonicityNot monotonic
2023-12-13T08:39:58.211180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 4
 
3.9%
9 3
 
2.9%
1 3
 
2.9%
8 3
 
2.9%
6 3
 
2.9%
3 3
 
2.9%
48 2
 
2.0%
4 2
 
2.0%
17 2
 
2.0%
150 2
 
2.0%
Other values (73) 75
73.5%
ValueCountFrequency (%)
1 3
2.9%
2 2
2.0%
3 3
2.9%
4 2
2.0%
5 4
3.9%
6 3
2.9%
7 1
 
1.0%
8 3
2.9%
9 3
2.9%
11 2
2.0%
ValueCountFrequency (%)
348 1
1.0%
324 1
1.0%
308 1
1.0%
304 1
1.0%
290 1
1.0%
285 1
1.0%
284 1
1.0%
283 1
1.0%
280 1
1.0%
278 1
1.0%

공부지목
Categorical

Distinct6
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size948.0 B
대
49 
임야
37 
잡종지
5 
전
5 
답
5 

Length

Max length3
Median length1
Mean length1.4705882
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
대 49
48.0%
임야 37
36.3%
잡종지 5
 
4.9%
전 5
 
4.9%
답 5
 
4.9%
도로 1
 
1.0%

Length

2023-12-13T08:39:58.332463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:39:58.424659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 49
48.0%
임야 37
36.3%
잡종지 5
 
4.9%
전 5
 
4.9%
답 5
 
4.9%
도로 1
 
1.0%

실소유면적
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.156863
Minimum0.3
Maximum489
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T08:39:58.524939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile1
Q17
median22
Q363.4
95-th percentile163.3
Maximum489
Range488.7
Interquartile range (IQR)56.4

Descriptive statistics

Standard deviation71.37168
Coefficient of variation (CV)1.5134951
Kurtosis16.588685
Mean47.156863
Median Absolute Deviation (MAD)18.9
Skewness3.5847579
Sum4810
Variance5093.9167
MonotonicityNot monotonic
2023-12-13T08:39:58.872816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.0 6
 
5.9%
1.0 6
 
5.9%
13.0 5
 
4.9%
5.0 4
 
3.9%
3.0 3
 
2.9%
8.0 3
 
2.9%
10.0 3
 
2.9%
2.0 3
 
2.9%
20.0 3
 
2.9%
15.0 2
 
2.0%
Other values (55) 64
62.7%
ValueCountFrequency (%)
0.3 1
 
1.0%
1.0 6
5.9%
2.0 3
2.9%
2.1 1
 
1.0%
3.0 3
2.9%
3.2 1
 
1.0%
5.0 4
3.9%
6.0 2
 
2.0%
7.0 6
5.9%
7.7 1
 
1.0%
ValueCountFrequency (%)
489.0 1
1.0%
316.3 1
1.0%
271.0 1
1.0%
258.0 1
1.0%
178.0 1
1.0%
165.0 1
1.0%
131.0 1
1.0%
122.0 1
1.0%
112.0 1
1.0%
102.0 1
1.0%

공부면적
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.647059
Minimum1
Maximum489
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T08:39:58.984881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.05
Q18
median25.5
Q376
95-th percentile215.95
Maximum489
Range488
Interquartile range (IQR)68

Descriptive statistics

Standard deviation85.482167
Coefficient of variation (CV)1.4828539
Kurtosis10.116193
Mean57.647059
Median Absolute Deviation (MAD)20.5
Skewness2.9407655
Sum5880
Variance7307.2009
MonotonicityNot monotonic
2023-12-13T08:39:59.130128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 6
 
5.9%
7 6
 
5.9%
5 5
 
4.9%
13 5
 
4.9%
10 3
 
2.9%
8 3
 
2.9%
2 3
 
2.9%
20 3
 
2.9%
25 3
 
2.9%
3 3
 
2.9%
Other values (54) 62
60.8%
ValueCountFrequency (%)
1 6
5.9%
2 3
2.9%
3 3
2.9%
5 5
4.9%
6 2
 
2.0%
7 6
5.9%
8 3
2.9%
9 1
 
1.0%
10 3
2.9%
11 1
 
1.0%
ValueCountFrequency (%)
489 1
1.0%
434 1
1.0%
344 1
1.0%
271 1
1.0%
258 1
1.0%
217 1
1.0%
196 1
1.0%
188 1
1.0%
178 1
1.0%
165 1
1.0%

Interactions

2023-12-13T08:39:56.949193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.060350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.353131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.662063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:57.019174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.140451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.428136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.738201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:57.094060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.216435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.507149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.815440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:57.178061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.281093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.590486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:39:56.880597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:39:59.206913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번지호공부지목실소유면적공부면적
번지1.0000.0000.5750.0000.000
호0.0001.0000.4040.1380.000
공부지목0.5750.4041.0000.0000.000
실소유면적0.0000.1380.0001.0000.965
공부면적0.0000.0000.0000.9651.000
2023-12-13T08:39:59.290884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번지호실소유면적공부면적공부지목
번지1.0000.221-0.126-0.0860.386
호0.2211.000-0.202-0.2190.219
실소유면적-0.126-0.2021.0000.9180.000
공부면적-0.086-0.2190.9181.0000.000
공부지목0.3860.2190.0000.0001.000

Missing values

2023-12-13T08:39:57.267946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:39:57.365068image/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 재무과학익동213대102.0102
1일반재산미추홀구청 재무과학익동217대23.023
2일반재산미추홀구청 재무과학익동54잡종지14.0344
3일반재산미추홀구청 재무과학익동518잡종지13.013
4일반재산미추홀구청 재무과학익동105도로68.068
5일반재산미추홀구청 재무과학익동4561잡종지43.043
6일반재산미추홀구청 재무과학익동2098전25.025
7일반재산미추홀구청 재무과학익동2105대38.038
8일반재산미추홀구청 재무과학익동21048대77.077
9일반재산미추홀구청 재무과학익동2131대61.061
재산구분재산관리관동명번지호공부지목실소유면적공부면적
92일반재산미추홀구청 재무과학익동32948임야93.093
93일반재산미추홀구청 재무과학익동32951임야69.069
94일반재산미추홀구청 재무과학익동3315대122.0122
95일반재산미추홀구청 재무과학익동3323대33.033
96일반재산미추홀구청 재무과학익동3328대3.03
97일반재산미추홀구청 재무과학익동4563대112.0112
98일반재산미추홀구청 재무과학익동5183답19.019
99일반재산미추홀구청 재무과학익동5366대1.01
100일반재산미추홀구청 재무과학익동6496전5.05
101일반재산미추홀구청 재무과학익동64911전10.010