Overview

Dataset statistics

Number of variables5
Number of observations27
Missing cells1
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory46.9 B

Variable types

Numeric2
Text1
Categorical2

Dataset

Description파일 다운로드
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-22034/F/1/datasetView.do

Alerts

전용면적(제곱미터) is highly overall correlated with 주택유형High correlation
주택유형 is highly overall correlated with 전용면적(제곱미터)High correlation
전용면적(제곱미터) has 1 (3.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 04:21:27.293798
Analysis finished2023-12-11 04:21:28.052495
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-11T13:21:28.133443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3
Q17.5
median14
Q320.5
95-th percentile25.7
Maximum27
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.56694671
Kurtosis-1.2
Mean14
Median Absolute Deviation (MAD)7
Skewness0
Sum378
Variance63
MonotonicityStrictly increasing
2023-12-11T13:21:28.596419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 1
 
3.7%
2 1
 
3.7%
27 1
 
3.7%
26 1
 
3.7%
25 1
 
3.7%
24 1
 
3.7%
23 1
 
3.7%
22 1
 
3.7%
21 1
 
3.7%
20 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
2 1
3.7%
3 1
3.7%
4 1
3.7%
5 1
3.7%
6 1
3.7%
7 1
3.7%
8 1
3.7%
9 1
3.7%
10 1
3.7%
ValueCountFrequency (%)
27 1
3.7%
26 1
3.7%
25 1
3.7%
24 1
3.7%
23 1
3.7%
22 1
3.7%
21 1
3.7%
20 1
3.7%
19 1
3.7%
18 1
3.7%

소재지
Text

Distinct22
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T13:21:28.794393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length19.518519
Min length17

Characters and Unicode

Total characters527
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)63.0%

Sample

1st row서울특별시 양천구 목동 131-**
2nd row서울특별시 양천구 목동 523-**
3rd row서울특별시 양천구 신월동 234-**
4th row서울특별시 양천구 신월동 331-**
5th row서울특별시 양천구 신월동 331-**
ValueCountFrequency (%)
서울특별시 27
25.0%
양천구 27
25.0%
신월동 15
13.9%
신정동 8
 
7.4%
목동 4
 
3.7%
13 2
 
1.9%
177 2
 
1.9%
331 2
 
1.9%
176 2
 
1.9%
201 2
 
1.9%
Other values (17) 17
15.7%
2023-12-11T13:21:29.169626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
15.4%
* 49
 
9.3%
서 27
 
5.1%
특 27
 
5.1%
별 27
 
5.1%
시 27
 
5.1%
양 27
 
5.1%
천 27
 
5.1%
구 27
 
5.1%
동 27
 
5.1%
Other values (16) 181
34.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 293
55.6%
Space Separator 81
 
15.4%
Decimal Number 77
 
14.6%
Other Punctuation 49
 
9.3%
Dash Punctuation 27
 
5.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 27
9.2%
특 27
9.2%
별 27
9.2%
시 27
9.2%
양 27
9.2%
천 27
9.2%
구 27
9.2%
동 27
9.2%
울 27
9.2%
신 23
7.8%
Other values (3) 27
9.2%
Decimal Number
ValueCountFrequency (%)
1 22
28.6%
3 10
13.0%
7 9
11.7%
4 7
 
9.1%
9 7
 
9.1%
2 6
 
7.8%
5 6
 
7.8%
6 4
 
5.2%
0 4
 
5.2%
8 2
 
2.6%
Space Separator
ValueCountFrequency (%)
81
100.0%
Other Punctuation
ValueCountFrequency (%)
* 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 293
55.6%
Common 234
44.4%

Most frequent character per script

Common
ValueCountFrequency (%)
81
34.6%
* 49
20.9%
- 27
 
11.5%
1 22
 
9.4%
3 10
 
4.3%
7 9
 
3.8%
4 7
 
3.0%
9 7
 
3.0%
2 6
 
2.6%
5 6
 
2.6%
Other values (3) 10
 
4.3%
Hangul
ValueCountFrequency (%)
서 27
9.2%
특 27
9.2%
별 27
9.2%
시 27
9.2%
양 27
9.2%
천 27
9.2%
구 27
9.2%
동 27
9.2%
울 27
9.2%
신 23
7.8%
Other values (3) 27
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 293
55.6%
ASCII 234
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
34.6%
* 49
20.9%
- 27
 
11.5%
1 22
 
9.4%
3 10
 
4.3%
7 9
 
3.8%
4 7
 
3.0%
9 7
 
3.0%
2 6
 
2.6%
5 6
 
2.6%
Other values (3) 10
 
4.3%
Hangul
ValueCountFrequency (%)
서 27
9.2%
특 27
9.2%
별 27
9.2%
시 27
9.2%
양 27
9.2%
천 27
9.2%
구 27
9.2%
동 27
9.2%
울 27
9.2%
신 23
7.8%
Other values (3) 27
9.2%

주택유형
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
다세대주택
15 
단독주택
11 
연립주택
 
1

Length

Max length5
Median length5
Mean length4.5555556
Min length4

Unique

Unique1 ?
Unique (%)3.7%

Sample

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

Common Values

ValueCountFrequency (%)
다세대주택 15
55.6%
단독주택 11
40.7%
연립주택 1
 
3.7%

Length

2023-12-11T13:21:29.321072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:21:29.432953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다세대주택 15
55.6%
단독주택 11
40.7%
연립주택 1
 
3.7%

용도지역
Categorical

Distinct5
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size348.0 B
제2종일반주거지역
14 
제1종일반주거지역
7 
준주거지역
3 
제2종일반주거지역,자연녹지지역
2 
제3종일반주거지역
 
1

Length

Max length16
Median length9
Mean length9.0740741
Min length5

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row제1종일반주거지역
2nd row제2종일반주거지역
3rd row제2종일반주거지역
4th row제1종일반주거지역
5th row제1종일반주거지역

Common Values

ValueCountFrequency (%)
제2종일반주거지역 14
51.9%
제1종일반주거지역 7
25.9%
준주거지역 3
 
11.1%
제2종일반주거지역,자연녹지지역 2
 
7.4%
제3종일반주거지역 1
 
3.7%

Length

2023-12-11T13:21:29.560471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:21:29.713783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2종일반주거지역 14
51.9%
제1종일반주거지역 7
25.9%
준주거지역 3
 
11.1%
제2종일반주거지역,자연녹지지역 2
 
7.4%
제3종일반주거지역 1
 
3.7%

전용면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)100.0%
Missing1
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean57.58
Minimum25.77
Maximum233.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-11T13:21:29.835257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.77
5-th percentile27.1825
Q132.865
median39.35
Q359.3325
95-th percentile180.1525
Maximum233.76
Range207.99
Interquartile range (IQR)26.4675

Descriptive statistics

Standard deviation51.346958
Coefficient of variation (CV)0.89174989
Kurtosis7.7986926
Mean57.58
Median Absolute Deviation (MAD)10.92
Skewness2.844959
Sum1497.08
Variance2636.5101
MonotonicityNot monotonic
2023-12-11T13:21:29.973967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
36.51 1
 
3.7%
38.87 1
 
3.7%
64.02 1
 
3.7%
57.63 1
 
3.7%
75.06 1
 
3.7%
74.51 1
 
3.7%
35.93 1
 
3.7%
27.18 1
 
3.7%
59.9 1
 
3.7%
233.76 1
 
3.7%
Other values (16) 16
59.3%
ValueCountFrequency (%)
25.77 1
3.7%
27.18 1
3.7%
27.19 1
3.7%
27.55 1
3.7%
28.8 1
3.7%
30.41 1
3.7%
32.34 1
3.7%
34.44 1
3.7%
35.44 1
3.7%
35.93 1
3.7%
ValueCountFrequency (%)
233.76 1
3.7%
211.33 1
3.7%
86.62 1
3.7%
75.06 1
3.7%
74.51 1
3.7%
64.02 1
3.7%
59.9 1
3.7%
57.63 1
3.7%
50.64 1
3.7%
43.38 1
3.7%

Interactions

2023-12-11T13:21:27.688479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:21:27.503287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:21:27.790755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:21:27.598201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T13:21:30.061023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재지주택유형용도지역전용면적(제곱미터)
연번1.0000.9810.6790.8470.645
소재지0.9811.0001.0001.0000.950
주택유형0.6791.0001.0000.1220.623
용도지역0.8471.0000.1221.0000.772
전용면적(제곱미터)0.6450.9500.6230.7721.000
2023-12-11T13:21:30.164628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주택유형용도지역
주택유형1.0000.039
용도지역0.0391.000
2023-12-11T13:21:30.267878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전용면적(제곱미터)주택유형용도지역
연번1.0000.2570.4200.386
전용면적(제곱미터)0.2571.0000.5520.386
주택유형0.4200.5521.0000.039
용도지역0.3860.3860.0391.000

Missing values

2023-12-11T13:21:27.913305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:21:28.012206image/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

연번소재지주택유형용도지역전용면적(제곱미터)
01서울특별시 양천구 목동 131-**다세대주택제1종일반주거지역36.51
12서울특별시 양천구 목동 523-**다세대주택제2종일반주거지역28.8
23서울특별시 양천구 신월동 234-**다세대주택제2종일반주거지역41.49
34서울특별시 양천구 신월동 331-**다세대주택제1종일반주거지역35.44
45서울특별시 양천구 신월동 331-**다세대주택제1종일반주거지역39.83
56서울특별시 양천구 신월동 49-*다세대주택준주거지역34.44
67서울특별시 양천구 신월동 914-**다세대주택제2종일반주거지역40.28
78서울특별시 양천구 신월동 975-*다세대주택제2종일반주거지역43.38
89서울특별시 양천구 신정동 911-*다세대주택제2종일반주거지역27.55
910서울특별시 양천구 목동 794-**단독주택준주거지역211.33
연번소재지주택유형용도지역전용면적(제곱미터)
1718서울특별시 양천구 신월동 13-**다세대주택제2종일반주거지역25.77
1819서울특별시 양천구 신월동 175-**단독주택제2종일반주거지역<NA>
1920서울특별시 양천구 신월동 549-**단독주택준주거지역233.76
2021서울특별시 양천구 신정동 1155-**단독주택제1종일반주거지역59.9
2122서울특별시 양천구 신정동 176-**단독주택제2종일반주거지역27.18
2223서울특별시 양천구 신정동 176-**단독주택제2종일반주거지역35.93
2324서울특별시 양천구 신정동 1023-**단독주택제2종일반주거지역74.51
2425서울특별시 양천구 신정동 177-**단독주택제2종일반주거지역,자연녹지지역75.06
2526서울특별시 양천구 신정동 177-**단독주택제2종일반주거지역,자연녹지지역57.63
2627서울특별시 양천구 신정동 89-**단독주택제3종일반주거지역64.02