Overview

Dataset statistics

Number of variables6
Number of observations678
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.9 KiB
Average record size in memory51.2 B

Variable types

Numeric3
Text2
DateTime1

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 신규 아파트 단지 목록 데이터입니다. - (대상) 22.01.01. ~ 22.12.31. 사용승인분
URLhttps://www.data.go.kr/data/15120697/fileData.do

Alerts

단지코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:35:06.913334
Analysis finished2023-12-12 00:35:08.382097
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단지코드
Real number (ℝ)

UNIQUE 

Distinct678
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20436783
Minimum20336743
Maximum20442243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2023-12-12T09:35:08.474736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20336743
5-th percentile20432008
Q120433591
median20438031
Q320440076
95-th percentile20441539
Maximum20442243
Range105500
Interquartile range (IQR)6485.25

Descriptive statistics

Standard deviation5984.0149
Coefficient of variation (CV)0.00029280611
Kurtosis130.41146
Mean20436783
Median Absolute Deviation (MAD)2796.5
Skewness-8.9670431
Sum1.3856139 × 1010
Variance35808435
MonotonicityNot monotonic
2023-12-12T09:35:08.619599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20439501 1
 
0.1%
20434958 1
 
0.1%
20431931 1
 
0.1%
20439221 1
 
0.1%
20441960 1
 
0.1%
20438906 1
 
0.1%
20432505 1
 
0.1%
20435005 1
 
0.1%
20437754 1
 
0.1%
20438869 1
 
0.1%
Other values (668) 668
98.5%
ValueCountFrequency (%)
20336743 1
0.1%
20380966 1
0.1%
20391486 1
0.1%
20416306 1
0.1%
20416937 1
0.1%
20418633 1
0.1%
20418833 1
0.1%
20421617 1
0.1%
20430802 1
0.1%
20430951 1
0.1%
ValueCountFrequency (%)
20442243 1
0.1%
20442223 1
0.1%
20442171 1
0.1%
20442157 1
0.1%
20442137 1
0.1%
20442129 1
0.1%
20442125 1
0.1%
20442121 1
0.1%
20442077 1
0.1%
20441964 1
0.1%

단지명
Text

Distinct677
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-12T09:35:08.824594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length9.1179941
Min length2

Characters and Unicode

Total characters6182
Distinct characters427
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique676 ?
Unique (%)99.7%

Sample

1st row힐스테이트창경궁
2nd row청계랜드힐아파트
3rd row용산원효루미니
4th row용산소미글로벌리버파크
5th row히페리온리버팰리스
ValueCountFrequency (%)
엘리하임 2
 
0.3%
해오름마을14단지푸르지오파르세나 1
 
0.1%
김포양곡엘에이치1단지아파트 1
 
0.1%
위례숲우미린 1
 
0.1%
위례중흥에스-클래스 1
 
0.1%
위례우미린 1
 
0.1%
용인죽전경기행복주택 1
 
0.1%
한화포레나수지동천 1
 
0.1%
힐스테이트광교산 1
 
0.1%
수지스카이뷰푸르지오 1
 
0.1%
Other values (667) 667
98.4%
2023-12-12T09:35:09.148578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
트 222
 
3.6%
스 192
 
3.1%
파 164
 
2.7%
아 157
 
2.5%
지 156
 
2.5%
이 146
 
2.4%
리 130
 
2.1%
단 99
 
1.6%
시 92
 
1.5%
1 87
 
1.4%
Other values (417) 4737
76.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5542
89.6%
Decimal Number 276
 
4.5%
Uppercase Letter 238
 
3.8%
Lowercase Letter 42
 
0.7%
Open Punctuation 28
 
0.5%
Close Punctuation 28
 
0.5%
Dash Punctuation 17
 
0.3%
Letter Number 8
 
0.1%
Other Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 222
 
4.0%
스 192
 
3.5%
파 164
 
3.0%
아 157
 
2.8%
지 156
 
2.8%
이 146
 
2.6%
리 130
 
2.3%
단 99
 
1.8%
시 92
 
1.7%
크 81
 
1.5%
Other values (365) 4103
74.0%
Uppercase Letter
ValueCountFrequency (%)
L 42
17.6%
H 38
16.0%
S 16
 
6.7%
I 14
 
5.9%
T 14
 
5.9%
E 13
 
5.5%
A 13
 
5.5%
C 11
 
4.6%
M 11
 
4.6%
D 9
 
3.8%
Other values (12) 57
23.9%
Lowercase Letter
ValueCountFrequency (%)
e 19
45.2%
t 4
 
9.5%
y 4
 
9.5%
i 3
 
7.1%
h 3
 
7.1%
c 2
 
4.8%
k 2
 
4.8%
s 2
 
4.8%
r 1
 
2.4%
d 1
 
2.4%
Decimal Number
ValueCountFrequency (%)
1 87
31.5%
2 76
27.5%
3 29
 
10.5%
0 21
 
7.6%
4 20
 
7.2%
6 12
 
4.3%
5 11
 
4.0%
8 9
 
3.3%
9 6
 
2.2%
7 5
 
1.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
50.0%
Ⅰ 2
25.0%
Ⅲ 2
25.0%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
' 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5540
89.6%
Common 352
 
5.7%
Latin 288
 
4.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 222
 
4.0%
스 192
 
3.5%
파 164
 
3.0%
아 157
 
2.8%
지 156
 
2.8%
이 146
 
2.6%
리 130
 
2.3%
단 99
 
1.8%
시 92
 
1.7%
크 81
 
1.5%
Other values (364) 4101
74.0%
Latin
ValueCountFrequency (%)
L 42
14.6%
H 38
 
13.2%
e 19
 
6.6%
S 16
 
5.6%
I 14
 
4.9%
T 14
 
4.9%
E 13
 
4.5%
A 13
 
4.5%
C 11
 
3.8%
M 11
 
3.8%
Other values (26) 97
33.7%
Common
ValueCountFrequency (%)
1 87
24.7%
2 76
21.6%
3 29
 
8.2%
( 28
 
8.0%
) 28
 
8.0%
0 21
 
6.0%
4 20
 
5.7%
- 17
 
4.8%
6 12
 
3.4%
5 11
 
3.1%
Other values (6) 23
 
6.5%
Han
ValueCountFrequency (%)
愛 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5540
89.6%
ASCII 632
 
10.2%
Number Forms 8
 
0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
트 222
 
4.0%
스 192
 
3.5%
파 164
 
3.0%
아 157
 
2.8%
지 156
 
2.8%
이 146
 
2.6%
리 130
 
2.3%
단 99
 
1.8%
시 92
 
1.7%
크 81
 
1.5%
Other values (364) 4101
74.0%
ASCII
ValueCountFrequency (%)
1 87
 
13.8%
2 76
 
12.0%
L 42
 
6.6%
H 38
 
6.0%
3 29
 
4.6%
( 28
 
4.4%
) 28
 
4.4%
0 21
 
3.3%
4 20
 
3.2%
e 19
 
3.0%
Other values (39) 244
38.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
50.0%
Ⅰ 2
25.0%
Ⅲ 2
25.0%
CJK
ValueCountFrequency (%)
愛 2
100.0%

소재지
Text

Distinct415
Distinct (%)61.2%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-12T09:35:09.469445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length12.340708
Min length10

Characters and Unicode

Total characters8367
Distinct characters233
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique275 ?
Unique (%)40.6%

Sample

1st row서울특별시 종로구 충신동
2nd row서울특별시 중구 황학동
3rd row서울특별시 용산구 원효로1가
4th row서울특별시 용산구 원효로3가
5th row서울특별시 성동구 송정동
ValueCountFrequency (%)
경기도 198
 
9.8%
서울특별시 111
 
5.5%
부천시 54
 
2.7%
부산광역시 45
 
2.2%
인천광역시 45
 
2.2%
충청남도 45
 
2.2%
전라남도 36
 
1.8%
대구광역시 36
 
1.8%
서구 33
 
1.6%
중구 24
 
1.2%
Other values (563) 1400
69.1%
2023-12-12T09:35:09.924456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1362
 
16.3%
동 622
 
7.4%
시 559
 
6.7%
구 412
 
4.9%
도 392
 
4.7%
광 254
 
3.0%
경 239
 
2.9%
기 209
 
2.5%
서 201
 
2.4%
역 192
 
2.3%
Other values (223) 3925
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6989
83.5%
Space Separator 1362
 
16.3%
Decimal Number 16
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 622
 
8.9%
시 559
 
8.0%
구 412
 
5.9%
도 392
 
5.6%
광 254
 
3.6%
경 239
 
3.4%
기 209
 
3.0%
서 201
 
2.9%
역 192
 
2.7%
남 173
 
2.5%
Other values (219) 3736
53.5%
Decimal Number
ValueCountFrequency (%)
1 10
62.5%
3 4
 
25.0%
2 2
 
12.5%
Space Separator
ValueCountFrequency (%)
1362
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6989
83.5%
Common 1378
 
16.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 622
 
8.9%
시 559
 
8.0%
구 412
 
5.9%
도 392
 
5.6%
광 254
 
3.6%
경 239
 
3.4%
기 209
 
3.0%
서 201
 
2.9%
역 192
 
2.7%
남 173
 
2.5%
Other values (219) 3736
53.5%
Common
ValueCountFrequency (%)
1362
98.8%
1 10
 
0.7%
3 4
 
0.3%
2 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6989
83.5%
ASCII 1378
 
16.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1362
98.8%
1 10
 
0.7%
3 4
 
0.3%
2 2
 
0.1%
Hangul
ValueCountFrequency (%)
동 622
 
8.9%
시 559
 
8.0%
구 412
 
5.9%
도 392
 
5.6%
광 254
 
3.6%
경 239
 
3.4%
기 209
 
3.0%
서 201
 
2.9%
역 192
 
2.7%
남 173
 
2.5%
Other values (219) 3736
53.5%

시군구코드
Real number (ℝ)

Distinct172
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33873.587
Minimum11110
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2023-12-12T09:35:10.052100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11380
Q127237.5
median41190
Q342130
95-th percentile47761.5
Maximum50130
Range39020
Interquartile range (IQR)14892.5

Descriptive statistics

Standard deviation12069.959
Coefficient of variation (CV)0.3563236
Kurtosis-0.69527187
Mean33873.587
Median Absolute Deviation (MAD)6090
Skewness-0.7444966
Sum22966292
Variance1.456839 × 108
MonotonicityIncreasing
2023-12-12T09:35:10.181316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41190 54
 
8.0%
41590 21
 
3.1%
28260 21
 
3.1%
41281 14
 
2.1%
11680 13
 
1.9%
31140 11
 
1.6%
41630 11
 
1.6%
50110 11
 
1.6%
44200 11
 
1.6%
11380 11
 
1.6%
Other values (162) 500
73.7%
ValueCountFrequency (%)
11110 1
 
0.1%
11140 1
 
0.1%
11170 2
 
0.3%
11200 1
 
0.1%
11215 5
0.7%
11230 1
 
0.1%
11260 5
0.7%
11290 6
0.9%
11305 6
0.9%
11320 3
0.4%
ValueCountFrequency (%)
50130 3
 
0.4%
50110 11
1.6%
48880 1
 
0.1%
48860 1
 
0.1%
48850 2
 
0.3%
48740 1
 
0.1%
48330 4
 
0.6%
48310 1
 
0.1%
48270 3
 
0.4%
48250 1
 
0.1%

읍면동코드
Real number (ℝ)

Distinct95
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14279.544
Minimum10100
Maximum41021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2023-12-12T09:35:10.301775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10100
5-th percentile10100
Q110500
median11300
Q313275
95-th percentile26222
Maximum41021
Range30921
Interquartile range (IQR)2775

Descriptive statistics

Standard deviation6686.2746
Coefficient of variation (CV)0.46824146
Kurtosis2.5876446
Mean14279.544
Median Absolute Deviation (MAD)1000
Skewness1.8986722
Sum9681531
Variance44706268
MonotonicityNot monotonic
2023-12-12T09:35:10.424757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10200 48
 
7.1%
10100 47
 
6.9%
10300 37
 
5.5%
10800 34
 
5.0%
10400 33
 
4.9%
10600 28
 
4.1%
10500 27
 
4.0%
11300 23
 
3.4%
10700 23
 
3.4%
10900 21
 
3.1%
Other values (85) 357
52.7%
ValueCountFrequency (%)
10100 47
6.9%
10200 48
7.1%
10300 37
5.5%
10400 33
4.9%
10500 27
4.0%
10600 28
4.1%
10700 23
3.4%
10800 34
5.0%
10900 21
3.1%
11000 16
 
2.4%
ValueCountFrequency (%)
41021 2
0.3%
40024 1
0.1%
39031 1
0.1%
39028 1
0.1%
39021 1
0.1%
37026 1
0.1%
37022 1
0.1%
36046 1
0.1%
36021 2
0.3%
34025 2
0.3%

준공일자
Date

Distinct222
Distinct (%)32.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2022-01-05 00:00:00
Maximum2022-12-30 00:00:00
2023-12-12T09:35:10.540111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:10.652510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T09:35:07.935756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.297334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.613784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:08.020616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.395040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.723060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:08.114227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.507397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:35:07.828616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:35:10.729312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단지코드시군구코드읍면동코드
단지코드1.0000.0220.056
시군구코드0.0221.0000.414
읍면동코드0.0560.4141.000
2023-12-12T09:35:10.805279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단지코드시군구코드읍면동코드
단지코드1.0000.1160.101
시군구코드0.1161.0000.448
읍면동코드0.1010.4481.000

Missing values

2023-12-12T09:35:08.226478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:35:08.337856image/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

단지코드단지명소재지시군구코드읍면동코드준공일자
020439501힐스테이트창경궁서울특별시 종로구 충신동11110167002022-09-29
120432203청계랜드힐아파트서울특별시 중구 황학동11140165002022-02-07
220435423용산원효루미니서울특별시 용산구 원효로1가11170112002022-04-28
320437907용산소미글로벌리버파크서울특별시 용산구 원효로3가11170117002022-07-06
420431766히페리온리버팰리스서울특별시 성동구 송정동11200118002022-01-14
520439181리마크빌군자서울특별시 광진구 중곡동11215101002022-08-30
620432091현대팰리스서울특별시 광진구 구의동11215103002022-01-24
720437221광진더프레236서울특별시 광진구 구의동11215103002022-06-10
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