Overview

Dataset statistics

Number of variables6
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory58.3 B

Variable types

Text1
Numeric4
Categorical1

Dataset

Description인천광역시 서구 부동산거래현황에 관한 데이터입니다. 데이터기준일자 이전 일년동안의 부동산거래현황을 제공합니다. 행정구역, 물건수, 토지면적(제곱미터),건축물면적(제곱미터),금액(백만원) 등의 항목을 제공합니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15105652&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
물건수 is highly overall correlated with 건축물면적(제곱미터) and 1 other fieldsHigh correlation
토지면적(제곱미터) is highly overall correlated with 건축물면적(제곱미터) and 1 other fieldsHigh correlation
건축물면적(제곱미터) is highly overall correlated with 물건수 and 2 other fieldsHigh correlation
금액(백만원) is highly overall correlated with 물건수 and 2 other fieldsHigh correlation
행정구역 has unique valuesUnique
물건수 has unique valuesUnique
토지면적(제곱미터) has unique valuesUnique
건축물면적(제곱미터) has unique valuesUnique
금액(백만원) has unique valuesUnique
건축물면적(제곱미터) has 1 (4.8%) zerosZeros

Reproduction

Analysis started2024-03-18 05:16:57.201017
Analysis finished2024-03-18 05:16:59.489615
Duration2.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정구역
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-18T14:16:59.604456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters63
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row백석동
2nd row시천동
3rd row검암동
4th row경서동
5th row공촌동
ValueCountFrequency (%)
백석동 1
 
4.8%
가좌동 1
 
4.8%
불로동 1
 
4.8%
왕길동 1
 
4.8%
오류동 1
 
4.8%
금곡동 1
 
4.8%
대곡동 1
 
4.8%
원당동 1
 
4.8%
당하동 1
 
4.8%
마전동 1
 
4.8%
Other values (11) 11
52.4%
2024-03-18T14:16:59.891301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 21
33.3%
곡 3
 
4.8%
원 2
 
3.2%
석 2
 
3.2%
가 2
 
3.2%
당 2
 
3.2%
대 1
 
1.6%
좌 1
 
1.6%
마 1
 
1.6%
전 1
 
1.6%
Other values (27) 27
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 21
33.3%
곡 3
 
4.8%
원 2
 
3.2%
석 2
 
3.2%
가 2
 
3.2%
당 2
 
3.2%
대 1
 
1.6%
좌 1
 
1.6%
마 1
 
1.6%
전 1
 
1.6%
Other values (27) 27
42.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 21
33.3%
곡 3
 
4.8%
원 2
 
3.2%
석 2
 
3.2%
가 2
 
3.2%
당 2
 
3.2%
대 1
 
1.6%
좌 1
 
1.6%
마 1
 
1.6%
전 1
 
1.6%
Other values (27) 27
42.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 21
33.3%
곡 3
 
4.8%
원 2
 
3.2%
석 2
 
3.2%
가 2
 
3.2%
당 2
 
3.2%
대 1
 
1.6%
좌 1
 
1.6%
마 1
 
1.6%
전 1
 
1.6%
Other values (27) 27
42.9%

물건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean804.14286
Minimum18
Maximum3419
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-18T14:17:00.060634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile69
Q1203
median363
Q31098
95-th percentile2268
Maximum3419
Range3401
Interquartile range (IQR)895

Descriptive statistics

Standard deviation892.15084
Coefficient of variation (CV)1.1094432
Kurtosis2.4737889
Mean804.14286
Median Absolute Deviation (MAD)294
Skewness1.6390614
Sum16887
Variance795933.13
MonotonicityNot monotonic
2024-03-18T14:17:00.202955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
939 1
 
4.8%
18 1
 
4.8%
3419 1
 
4.8%
2268 1
 
4.8%
303 1
 
4.8%
451 1
 
4.8%
128 1
 
4.8%
69 1
 
4.8%
1759 1
 
4.8%
1243 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
18 1
4.8%
69 1
4.8%
127 1
4.8%
128 1
4.8%
144 1
4.8%
203 1
4.8%
213 1
4.8%
303 1
4.8%
313 1
4.8%
323 1
4.8%
ValueCountFrequency (%)
3419 1
4.8%
2268 1
4.8%
2012 1
4.8%
1759 1
4.8%
1243 1
4.8%
1098 1
4.8%
939 1
4.8%
751 1
4.8%
743 1
4.8%
451 1
4.8%

토지면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean274907.01
Minimum14487.54
Maximum1207049.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-18T14:17:00.326708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14487.54
5-th percentile17936.68
Q187119.46
median188052.98
Q3358330.79
95-th percentile678667.05
Maximum1207049.7
Range1192562.2
Interquartile range (IQR)271211.33

Descriptive statistics

Standard deviation285501.92
Coefficient of variation (CV)1.03854
Kurtosis4.8738795
Mean274907.01
Median Absolute Deviation (MAD)135545.08
Skewness2.0308834
Sum5773047.2
Variance8.1511349 × 1010
MonotonicityNot monotonic
2024-03-18T14:17:00.467434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
183609.64 1
 
4.8%
169238.25 1
 
4.8%
358330.79 1
 
4.8%
243233.97 1
 
4.8%
403686.73 1
 
4.8%
188052.98 1
 
4.8%
50332.3 1
 
4.8%
32981.26 1
 
4.8%
678667.05 1
 
4.8%
661147.52 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
14487.54 1
4.8%
17936.68 1
4.8%
32981.26 1
4.8%
50332.3 1
4.8%
52507.9 1
4.8%
87119.46 1
4.8%
114141.25 1
4.8%
169238.25 1
4.8%
179858.42 1
4.8%
183609.64 1
4.8%
ValueCountFrequency (%)
1207049.7 1
4.8%
678667.05 1
4.8%
661147.52 1
4.8%
443943.12 1
4.8%
403686.73 1
4.8%
358330.79 1
4.8%
243233.97 1
4.8%
235235.72 1
4.8%
234139.83 1
4.8%
217347.06 1
4.8%

건축물면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean346921.95
Minimum0
Maximum4654591.5
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-18T14:17:00.627669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1211.58
Q111847.53
median55655.3
Q3141300.05
95-th percentile1302209.3
Maximum4654591.5
Range4654591.5
Interquartile range (IQR)129452.52

Descriptive statistics

Standard deviation1025432.5
Coefficient of variation (CV)2.9558017
Kurtosis17.585637
Mean346921.95
Median Absolute Deviation (MAD)50725.29
Skewness4.1167712
Sum7285360.9
Variance1.0515118 × 1012
MonotonicityNot monotonic
2024-03-18T14:17:00.773238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
62012.85 1
 
4.8%
0.0 1
 
4.8%
248567.23 1
 
4.8%
162235.74 1
 
4.8%
29218.3 1
 
4.8%
113427.53 1
 
4.8%
4930.01 1
 
4.8%
1211.58 1
 
4.8%
141300.05 1
 
4.8%
107863.0 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
0.0 1
4.8%
1211.58 1
4.8%
4930.01 1
4.8%
6617.25 1
4.8%
11621.66 1
4.8%
11847.53 1
4.8%
20409.44 1
4.8%
28953.02 1
4.8%
29218.3 1
4.8%
32892.83 1
4.8%
ValueCountFrequency (%)
4654591.48 1
4.8%
1302209.33 1
4.8%
248567.23 1
4.8%
221299.39 1
4.8%
162235.74 1
4.8%
141300.05 1
4.8%
113427.53 1
4.8%
107863.0 1
4.8%
68497.34 1
4.8%
62012.85 1
4.8%

금액(백만원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean335044.14
Minimum3959
Maximum1168717
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-18T14:17:00.881581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3959
5-th percentile11313
Q150195
median158272
Q3671647
95-th percentile943819
Maximum1168717
Range1164758
Interquartile range (IQR)621452

Descriptive statistics

Standard deviation366490.46
Coefficient of variation (CV)1.0938572
Kurtosis-0.29823664
Mean335044.14
Median Absolute Deviation (MAD)146959
Skewness1.0149276
Sum7035927
Variance1.3431526 × 1011
MonotonicityNot monotonic
2024-03-18T14:17:01.034524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
376199 1
 
4.8%
3959 1
 
4.8%
1168717 1
 
4.8%
943819 1
 
4.8%
106969 1
 
4.8%
189217 1
 
4.8%
29926 1
 
4.8%
11313 1
 
4.8%
746582 1
 
4.8%
722809 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
3959 1
4.8%
11313 1
4.8%
28468 1
4.8%
29926 1
4.8%
34544 1
4.8%
50195 1
4.8%
64531 1
4.8%
70688 1
4.8%
106969 1
4.8%
118518 1
4.8%
ValueCountFrequency (%)
1168717 1
4.8%
943819 1
4.8%
899044 1
4.8%
746582 1
4.8%
722809 1
4.8%
671647 1
4.8%
376199 1
4.8%
322760 1
4.8%
317750 1
4.8%
189217 1
4.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-07-31
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-31
2nd row2023-07-31
3rd row2023-07-31
4th row2023-07-31
5th row2023-07-31

Common Values

ValueCountFrequency (%)
2023-07-31 21
100.0%

Length

2024-03-18T14:17:01.198196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:17:01.288527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-31 21
100.0%

Interactions

2024-03-18T14:16:59.001351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:57.619828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:57.917560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:58.267833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:59.083552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:57.695415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:58.012931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:58.378299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:59.162440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:57.767426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:58.085657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:58.478904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:59.237410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:57.833069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:58.155050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:16:58.573313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:17:01.380061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역물건수토지면적(제곱미터)건축물면적(제곱미터)금액(백만원)
행정구역1.0001.0001.0001.0001.000
물건수1.0001.0000.5950.0000.860
토지면적(제곱미터)1.0000.5951.0000.3990.883
건축물면적(제곱미터)1.0000.0000.3991.0001.000
금액(백만원)1.0000.8600.8831.0001.000
2024-03-18T14:17:01.575701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
물건수토지면적(제곱미터)건축물면적(제곱미터)금액(백만원)
물건수1.0000.3780.7560.799
토지면적(제곱미터)0.3781.0000.5120.610
건축물면적(제곱미터)0.7560.5121.0000.925
금액(백만원)0.7990.6100.9251.000

Missing values

2024-03-18T14:16:59.351416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:16:59.448755image/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

행정구역물건수토지면적(제곱미터)건축물면적(제곱미터)금액(백만원)데이터기준일자
0백석동939183609.6462012.853761992023-07-31
1시천동18169238.250.039592023-07-31
2검암동32352507.920409.44706882023-07-31
3경서동203114141.2511847.53501952023-07-31
4공촌동1441207049.76617.25345442023-07-31
5연희동21387119.4611621.66284682023-07-31
6심곡동31314487.5432892.83645312023-07-31
7가정동2012234139.834654591.486716472023-07-31
8신현동36317936.6828953.021185182023-07-31
9석남동743235235.7268497.343227602023-07-31
행정구역물건수토지면적(제곱미터)건축물면적(제곱미터)금액(백만원)데이터기준일자
11가좌동1098179858.42221299.393177502023-07-31
12마전동751217347.0655655.31582722023-07-31
13당하동1243661147.52107863.07228092023-07-31
14원당동1759678667.05141300.057465822023-07-31
15대곡동6932981.261211.58113132023-07-31
16금곡동12850332.34930.01299262023-07-31
17오류동451188052.98113427.531892172023-07-31
18왕길동303403686.7329218.31069692023-07-31
19불로동2268243233.97162235.749438192023-07-31
20청라동3419358330.79248567.2311687172023-07-31