Overview

Dataset statistics

Number of variables24
Number of observations77
Missing cells22
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.2 KiB
Average record size in memory201.7 B

Variable types

Numeric6
Categorical6
Text5
Boolean6
DateTime1

Dataset

Description경상남도 하동군에 있는 공동주택 현황 (연번, 건물명, 대지위치, 연면적, 세대수, 동수, 층수, 사용승인일, 비고)의 정보를 제공하고 있습니다.
Author경상남도 하동군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15086629

Alerts

시군 has constant value ""Constant
시군구 has constant value ""Constant
중앙집중식난방(지역난방방식) has constant value ""Constant
단지수 has constant value ""Constant
법정동코드(시군) has constant value ""Constant
의무 is highly imbalanced (70.5%)Imbalance
비의무 is highly imbalanced (70.5%)Imbalance
임대 is highly imbalanced (90.0%)Imbalance
위탁관리 is highly imbalanced (51.9%)Imbalance
부번 has 22 (28.6%) missing valuesMissing
연번 has unique valuesUnique
경과연수 has 1 (1.3%) zerosZeros

Reproduction

Analysis started2023-12-10 22:39:29.155976
Analysis finished2023-12-10 22:39:29.763700
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39
Minimum1
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T07:39:29.841718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.8
Q120
median39
Q358
95-th percentile73.2
Maximum77
Range76
Interquartile range (IQR)38

Descriptive statistics

Standard deviation22.371857
Coefficient of variation (CV)0.57363737
Kurtosis-1.2
Mean39
Median Absolute Deviation (MAD)19
Skewness0
Sum3003
Variance500.5
MonotonicityStrictly increasing
2023-12-11T07:39:29.957023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
50 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
49 1
 
1.3%
Other values (67) 67
87.0%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%

시군
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
하동군
77 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
하동군 77
100.0%

Length

2023-12-11T07:39:30.066192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:39:30.152237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하동군 77
100.0%

용도
Categorical

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size748.0 B
다세대주택
32 
아파트
26 
연립주택
19 

Length

Max length5
Median length4
Mean length4.0779221
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
다세대주택 32
41.6%
아파트 26
33.8%
연립주택 19
24.7%

Length

2023-12-11T07:39:30.247387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:39:30.334421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다세대주택 32
41.6%
아파트 26
33.8%
연립주택 19
24.7%

단지명
Text

Distinct72
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-11T07:39:30.509414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length5.4805195
Min length3

Characters and Unicode

Total characters422
Distinct characters120
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)87.0%

Sample

1st row연화연립(다세대)
2nd row연화빌라
3rd row신촌빌라
4th row하평다세대(선창아파트)
5th row무지개맨션
ValueCountFrequency (%)
대근하버빌타운 2
 
2.6%
금오빌라 2
 
2.6%
성우빌라(다세대 2
 
2.6%
연화빌라 2
 
2.6%
흥룡빌라 2
 
2.6%
연화연립(다세대 1
 
1.3%
다금빌라(아파트 1
 
1.3%
하동한국남부발전사원아파트 1
 
1.3%
동원아트빌라 1
 
1.3%
문화빌라 1
 
1.3%
Other values (62) 62
80.5%
2023-12-11T07:39:30.807137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 49
 
11.6%
라 37
 
8.8%
아 15
 
3.6%
트 13
 
3.1%
파 13
 
3.1%
동 11
 
2.6%
대 10
 
2.4%
하 9
 
2.1%
( 9
 
2.1%
) 9
 
2.1%
Other values (110) 247
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 400
94.8%
Open Punctuation 9
 
2.1%
Close Punctuation 9
 
2.1%
Uppercase Letter 2
 
0.5%
Decimal Number 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 49
 
12.2%
라 37
 
9.2%
아 15
 
3.8%
트 13
 
3.2%
파 13
 
3.2%
동 11
 
2.8%
대 10
 
2.5%
하 9
 
2.2%
금 8
 
2.0%
연 7
 
1.8%
Other values (104) 228
57.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
H 1
50.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 400
94.8%
Common 20
 
4.7%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 49
 
12.2%
라 37
 
9.2%
아 15
 
3.8%
트 13
 
3.2%
파 13
 
3.2%
동 11
 
2.8%
대 10
 
2.5%
하 9
 
2.2%
금 8
 
2.0%
연 7
 
1.8%
Other values (104) 228
57.0%
Common
ValueCountFrequency (%)
( 9
45.0%
) 9
45.0%
2 1
 
5.0%
1 1
 
5.0%
Latin
ValueCountFrequency (%)
L 1
50.0%
H 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 400
94.8%
ASCII 22
 
5.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 49
 
12.2%
라 37
 
9.2%
아 15
 
3.8%
트 13
 
3.2%
파 13
 
3.2%
동 11
 
2.8%
대 10
 
2.5%
하 9
 
2.2%
금 8
 
2.0%
연 7
 
1.8%
Other values (104) 228
57.0%
ASCII
ValueCountFrequency (%)
( 9
40.9%
) 9
40.9%
L 1
 
4.5%
H 1
 
4.5%
2 1
 
4.5%
1 1
 
4.5%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
하동군
77 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
하동군 77
100.0%

Length

2023-12-11T07:39:30.909546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:39:30.979601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하동군 77
100.0%

법정동
Categorical

Distinct16
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size748.0 B
하동읍 읍내리
24 
진교면 진교리
17 
하동읍 비파리
9 
하동읍 광평리
8 
옥종면 청룡리
3 
Other values (11)
16 

Length

Max length7
Median length7
Mean length6.987013
Min length6

Unique

Unique7 ?
Unique (%)9.1%

Sample

1st row하동읍 읍내리
2nd row하동읍 읍내리
3rd row하동읍 비파리
4th row진교면 진교리
5th row하동읍 비파리

Common Values

ValueCountFrequency (%)
하동읍 읍내리 24
31.2%
진교면 진교리 17
22.1%
하동읍 비파리 9
 
11.7%
하동읍 광평리 8
 
10.4%
옥종면 청룡리 3
 
3.9%
고전면 전도리 3
 
3.9%
하동읍 두곡리 2
 
2.6%
금남면 송문리 2
 
2.6%
금남면 계천리 2
 
2.6%
하동읍 신기리 1
 
1.3%
Other values (6) 6
 
7.8%

Length

2023-12-11T07:39:31.058487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
하동읍 44
28.6%
읍내리 24
15.6%
진교면 18
11.7%
진교리 17
 
11.0%
비파리 9
 
5.8%
광평리 8
 
5.2%
금남면 5
 
3.2%
옥종면 3
 
1.9%
청룡리 3
 
1.9%
고전면 3
 
1.9%
Other values (14) 20
13.0%

본번
Real number (ℝ)

Distinct61
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean498.63636
Minimum3
Maximum1565
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T07:39:31.173501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile64.4
Q1246
median370
Q3628
95-th percentile1405.8
Maximum1565
Range1562
Interquartile range (IQR)382

Descriptive statistics

Standard deviation395.92992
Coefficient of variation (CV)0.79402535
Kurtosis0.76412471
Mean498.63636
Median Absolute Deviation (MAD)148
Skewness1.2599941
Sum38395
Variance156760.5
MonotonicityNot monotonic
2023-12-11T07:39:31.299415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
302 4
 
5.2%
306 3
 
3.9%
112 3
 
3.9%
611 3
 
3.9%
101 2
 
2.6%
628 2
 
2.6%
426 2
 
2.6%
242 2
 
2.6%
428 2
 
2.6%
241 2
 
2.6%
Other values (51) 52
67.5%
ValueCountFrequency (%)
3 1
 
1.3%
36 1
 
1.3%
53 1
 
1.3%
58 1
 
1.3%
66 1
 
1.3%
101 2
2.6%
105 1
 
1.3%
112 3
3.9%
116 1
 
1.3%
182 1
 
1.3%
ValueCountFrequency (%)
1565 1
1.3%
1494 2
2.6%
1477 1
1.3%
1388 1
1.3%
1292 1
1.3%
1247 1
1.3%
1196 1
1.3%
1184 1
1.3%
1104 1
1.3%
970 1
1.3%

부번
Text

MISSING 

Distinct30
Distinct (%)54.5%
Missing22
Missing (%)28.6%
Memory size748.0 B
2023-12-11T07:39:31.425434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6727273
Min length1

Characters and Unicode

Total characters92
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)43.6%

Sample

1st row4외1
2nd row2
3rd row11외1
4th row150외5
5th row46
ValueCountFrequency (%)
2 9
16.4%
3 7
 
12.7%
1 7
 
12.7%
외2 3
 
5.5%
8 3
 
5.5%
5 2
 
3.6%
11 1
 
1.8%
2외1 1
 
1.8%
18 1
 
1.8%
6 1
 
1.8%
Other values (20) 20
36.4%
2023-12-11T07:39:31.673850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24
26.1%
2 17
18.5%
3 10
10.9%
외 9
 
9.8%
8 8
 
8.7%
5 8
 
8.7%
4 5
 
5.4%
0 4
 
4.3%
9 4
 
4.3%
6 2
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83
90.2%
Other Letter 9
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
28.9%
2 17
20.5%
3 10
12.0%
8 8
 
9.6%
5 8
 
9.6%
4 5
 
6.0%
0 4
 
4.8%
9 4
 
4.8%
6 2
 
2.4%
7 1
 
1.2%
Other Letter
ValueCountFrequency (%)
외 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83
90.2%
Hangul 9
 
9.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
28.9%
2 17
20.5%
3 10
12.0%
8 8
 
9.6%
5 8
 
9.6%
4 5
 
6.0%
0 4
 
4.8%
9 4
 
4.8%
6 2
 
2.4%
7 1
 
1.2%
Hangul
ValueCountFrequency (%)
외 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
90.2%
Hangul 9
 
9.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24
28.9%
2 17
20.5%
3 10
12.0%
8 8
 
9.6%
5 8
 
9.6%
4 5
 
6.0%
0 4
 
4.8%
9 4
 
4.8%
6 2
 
2.4%
7 1
 
1.2%
Hangul
ValueCountFrequency (%)
외 9
100.0%

도로명주소
Text

Distinct75
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-11T07:39:31.904517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length12.87013
Min length10

Characters and Unicode

Total characters991
Distinct characters97
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)94.8%

Sample

1st row 하동읍 산복2길 77-1
2nd row 하동읍 수박등길 12
3rd row 하동읍 군청로 143
4th row 진교면 선창길 11-12외5
5th row 하동읍 소재1길 9
ValueCountFrequency (%)
하동읍 44
 
19.1%
진교면 18
 
7.8%
금남면 5
 
2.2%
산복2길 5
 
2.2%
소재1길 4
 
1.7%
산복1길 4
 
1.7%
수박등길 4
 
1.7%
진교중앙길 4
 
1.7%
민다리안길 4
 
1.7%
남당길 4
 
1.7%
Other values (106) 134
58.3%
2023-12-11T07:39:32.234199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
228
23.0%
1 69
 
7.0%
길 65
 
6.6%
동 49
 
4.9%
하 48
 
4.8%
읍 45
 
4.5%
면 33
 
3.3%
2 33
 
3.3%
진 27
 
2.7%
교 25
 
2.5%
Other values (87) 369
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 521
52.6%
Space Separator 228
23.0%
Decimal Number 216
21.8%
Dash Punctuation 24
 
2.4%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 65
 
12.5%
동 49
 
9.4%
하 48
 
9.2%
읍 45
 
8.6%
면 33
 
6.3%
진 27
 
5.2%
교 25
 
4.8%
로 12
 
2.3%
산 11
 
2.1%
남 10
 
1.9%
Other values (73) 196
37.6%
Decimal Number
ValueCountFrequency (%)
1 69
31.9%
2 33
15.3%
3 19
 
8.8%
4 18
 
8.3%
6 18
 
8.3%
7 16
 
7.4%
5 14
 
6.5%
9 10
 
4.6%
8 10
 
4.6%
0 9
 
4.2%
Space Separator
ValueCountFrequency (%)
228
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 521
52.6%
Common 470
47.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 65
 
12.5%
동 49
 
9.4%
하 48
 
9.2%
읍 45
 
8.6%
면 33
 
6.3%
진 27
 
5.2%
교 25
 
4.8%
로 12
 
2.3%
산 11
 
2.1%
남 10
 
1.9%
Other values (73) 196
37.6%
Common
ValueCountFrequency (%)
228
48.5%
1 69
 
14.7%
2 33
 
7.0%
- 24
 
5.1%
3 19
 
4.0%
4 18
 
3.8%
6 18
 
3.8%
7 16
 
3.4%
5 14
 
3.0%
9 10
 
2.1%
Other values (4) 21
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 521
52.6%
ASCII 470
47.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
228
48.5%
1 69
 
14.7%
2 33
 
7.0%
- 24
 
5.1%
3 19
 
4.0%
4 18
 
3.8%
6 18
 
3.8%
7 16
 
3.4%
5 14
 
3.0%
9 10
 
2.1%
Other values (4) 21
 
4.5%
Hangul
ValueCountFrequency (%)
길 65
 
12.5%
동 49
 
9.4%
하 48
 
9.2%
읍 45
 
8.6%
면 33
 
6.3%
진 27
 
5.2%
교 25
 
4.8%
로 12
 
2.3%
산 11
 
2.1%
남 10
 
1.9%
Other values (73) 196
37.6%

대지면적
Text

Distinct75
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-11T07:39:32.443232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.6103896
Min length3

Characters and Unicode

Total characters278
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)94.8%

Sample

1st row450
2nd row1026
3rd row983
4th row1804
5th row3027
ValueCountFrequency (%)
450 2
 
2.6%
235 2
 
2.6%
15619 1
 
1.3%
668 1
 
1.3%
768 1
 
1.3%
1501 1
 
1.3%
560 1
 
1.3%
5942 1
 
1.3%
2622 1
 
1.3%
7864.628 1
 
1.3%
Other values (65) 65
84.4%
2023-12-11T07:39:32.778381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 40
14.4%
3 38
13.7%
5 34
12.2%
2 32
11.5%
4 27
9.7%
6 25
9.0%
7 22
7.9%
9 20
7.2%
0 19
6.8%
8 18
6.5%
Other values (2) 3
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 275
98.9%
Other Punctuation 3
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 40
14.5%
3 38
13.8%
5 34
12.4%
2 32
11.6%
4 27
9.8%
6 25
9.1%
7 22
8.0%
9 20
7.3%
0 19
6.9%
8 18
6.5%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 278
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 40
14.4%
3 38
13.7%
5 34
12.2%
2 32
11.5%
4 27
9.7%
6 25
9.0%
7 22
7.9%
9 20
7.2%
0 19
6.8%
8 18
6.5%
Other values (2) 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 278
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 40
14.4%
3 38
13.7%
5 34
12.2%
2 32
11.5%
4 27
9.7%
6 25
9.0%
7 22
7.9%
9 20
7.2%
0 19
6.8%
8 18
6.5%
Other values (2) 3
 
1.1%

연면적
Text

Distinct76
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-11T07:39:32.990026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.6363636
Min length3

Characters and Unicode

Total characters511
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)97.4%

Sample

1st row517.11
2nd row1155.69
3rd row658.8
4th row1858.95
5th row4048.98
ValueCountFrequency (%)
657.36 2
 
2.6%
1940 1
 
1.3%
38088.584 1
 
1.3%
1657.36 1
 
1.3%
2453.58 1
 
1.3%
16602.01 1
 
1.3%
5837.945 1
 
1.3%
2096.69 1
 
1.3%
656.68 1
 
1.3%
1037.49 1
 
1.3%
Other values (66) 66
85.7%
2023-12-11T07:39:33.343720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 73
14.3%
1 61
11.9%
5 60
11.7%
2 51
10.0%
6 45
8.8%
4 41
8.0%
0 38
7.4%
3 37
7.2%
9 37
7.2%
8 35
6.8%
Other values (2) 33
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 437
85.5%
Other Punctuation 74
 
14.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 61
14.0%
5 60
13.7%
2 51
11.7%
6 45
10.3%
4 41
9.4%
0 38
8.7%
3 37
8.5%
9 37
8.5%
8 35
8.0%
7 32
7.3%
Other Punctuation
ValueCountFrequency (%)
. 73
98.6%
, 1
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 73
14.3%
1 61
11.9%
5 60
11.7%
2 51
10.0%
6 45
8.8%
4 41
8.0%
0 38
7.4%
3 37
7.2%
9 37
7.2%
8 35
6.8%
Other values (2) 33
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 73
14.3%
1 61
11.9%
5 60
11.7%
2 51
10.0%
6 45
8.8%
4 41
8.0%
0 38
7.4%
3 37
7.2%
9 37
7.2%
8 35
6.8%
Other values (2) 33
6.5%

최상층
Real number (ℝ)

Distinct13
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6493506
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T07:39:33.442636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q14
median4
Q35
95-th percentile15
Maximum18
Range17
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.7688691
Coefficient of variation (CV)0.66713316
Kurtosis2.7175477
Mean5.6493506
Median Absolute Deviation (MAD)1
Skewness1.9157331
Sum435
Variance14.204375
MonotonicityNot monotonic
2023-12-11T07:39:33.531039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
4 30
39.0%
5 15
19.5%
3 10
 
13.0%
15 5
 
6.5%
8 5
 
6.5%
2 3
 
3.9%
6 3
 
3.9%
9 1
 
1.3%
1 1
 
1.3%
16 1
 
1.3%
Other values (3) 3
 
3.9%
ValueCountFrequency (%)
1 1
 
1.3%
2 3
 
3.9%
3 10
 
13.0%
4 30
39.0%
5 15
19.5%
6 3
 
3.9%
8 5
 
6.5%
9 1
 
1.3%
13 1
 
1.3%
14 1
 
1.3%
ValueCountFrequency (%)
18 1
 
1.3%
16 1
 
1.3%
15 5
 
6.5%
14 1
 
1.3%
13 1
 
1.3%
9 1
 
1.3%
8 5
 
6.5%
6 3
 
3.9%
5 15
19.5%
4 30
39.0%

동수
Real number (ℝ)

Distinct6
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5714286
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T07:39:33.625932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile4.4
Maximum7
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.341921
Coefficient of variation (CV)0.85394971
Kurtosis8.2716187
Mean1.5714286
Median Absolute Deviation (MAD)0
Skewness2.91266
Sum121
Variance1.8007519
MonotonicityNot monotonic
2023-12-11T07:39:33.708836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 58
75.3%
2 10
 
13.0%
3 3
 
3.9%
6 2
 
2.6%
4 2
 
2.6%
7 2
 
2.6%
ValueCountFrequency (%)
1 58
75.3%
2 10
 
13.0%
3 3
 
3.9%
4 2
 
2.6%
6 2
 
2.6%
7 2
 
2.6%
ValueCountFrequency (%)
7 2
 
2.6%
6 2
 
2.6%
4 2
 
2.6%
3 3
 
3.9%
2 10
 
13.0%
1 58
75.3%

세대수
Real number (ℝ)

Distinct35
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.298701
Minimum2
Maximum420
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T07:39:33.808069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q18
median16
Q324
95-th percentile199.2
Maximum420
Range418
Interquartile range (IQR)16

Descriptive statistics

Standard deviation70.700083
Coefficient of variation (CV)1.754401
Kurtosis13.151976
Mean40.298701
Median Absolute Deviation (MAD)8
Skewness3.4273384
Sum3103
Variance4998.5017
MonotonicityNot monotonic
2023-12-11T07:39:33.907688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
8 12
15.6%
24 6
 
7.8%
12 6
 
7.8%
16 6
 
7.8%
6 4
 
5.2%
19 4
 
5.2%
7 4
 
5.2%
14 3
 
3.9%
28 2
 
2.6%
15 2
 
2.6%
Other values (25) 28
36.4%
ValueCountFrequency (%)
2 1
 
1.3%
4 2
 
2.6%
6 4
 
5.2%
7 4
 
5.2%
8 12
15.6%
9 2
 
2.6%
11 1
 
1.3%
12 6
7.8%
14 3
 
3.9%
15 2
 
2.6%
ValueCountFrequency (%)
420 1
1.3%
306 1
1.3%
219 1
1.3%
200 1
1.3%
199 1
1.3%
173 1
1.3%
144 1
1.3%
95 1
1.3%
80 1
1.3%
71 1
1.3%

의무
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size209.0 B
False
73 
True
 
4
ValueCountFrequency (%)
False 73
94.8%
True 4
 
5.2%
2023-12-11T07:39:33.994934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

비의무
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size209.0 B
True
73 
False
 
4
ValueCountFrequency (%)
True 73
94.8%
False 4
 
5.2%
2023-12-11T07:39:34.064081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

임대
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size209.0 B
False
76 
True
 
1
ValueCountFrequency (%)
False 76
98.7%
True 1
 
1.3%
2023-12-11T07:39:34.144551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위탁관리
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size209.0 B
False
69 
True
8 
ValueCountFrequency (%)
False 69
89.6%
True 8
 
10.4%
2023-12-11T07:39:34.220042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

승강기설치
Boolean

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size209.0 B
False
60 
True
17 
ValueCountFrequency (%)
False 60
77.9%
True 17
 
22.1%
2023-12-11T07:39:34.291903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

중앙집중식난방(지역난방방식)
Boolean

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size209.0 B
False
77 
ValueCountFrequency (%)
False 77
100.0%
2023-12-11T07:39:34.361637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

사용승인일
Date

Distinct74
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size748.0 B
Minimum1983-01-01 00:00:00
Maximum2022-05-17 00:00:00
2023-12-11T07:39:34.679085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:34.813682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

경과연수
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.818182
Minimum0
Maximum39
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T07:39:34.937314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q114
median25
Q330
95-th percentile32.2
Maximum39
Range39
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.9283317
Coefficient of variation (CV)0.45504854
Kurtosis-0.68994194
Mean21.818182
Median Absolute Deviation (MAD)5
Skewness-0.6615058
Sum1680
Variance98.57177
MonotonicityNot monotonic
2023-12-11T07:39:35.038119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
25 9
 
11.7%
30 8
 
10.4%
31 7
 
9.1%
26 4
 
5.2%
4 4
 
5.2%
8 3
 
3.9%
23 3
 
3.9%
24 3
 
3.9%
20 3
 
3.9%
27 3
 
3.9%
Other values (21) 30
39.0%
ValueCountFrequency (%)
0 1
 
1.3%
2 1
 
1.3%
3 1
 
1.3%
4 4
5.2%
5 2
2.6%
8 3
3.9%
9 3
3.9%
10 1
 
1.3%
11 1
 
1.3%
12 1
 
1.3%
ValueCountFrequency (%)
39 1
 
1.3%
38 1
 
1.3%
36 1
 
1.3%
33 1
 
1.3%
32 3
 
3.9%
31 7
9.1%
30 8
10.4%
29 3
 
3.9%
28 1
 
1.3%
27 3
 
3.9%

단지수
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
1
77 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 77
100.0%

Length

2023-12-11T07:39:35.136846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:39:35.208827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 77
100.0%

법정동코드(시군)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
4885000000
77 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4885000000
2nd row4885000000
3rd row4885000000
4th row4885000000
5th row4885000000

Common Values

ValueCountFrequency (%)
4885000000 77
100.0%

Length

2023-12-11T07:39:35.279459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:39:35.351544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4885000000 77
100.0%

Sample

연번시군용도단지명시군구법정동본번부번도로명주소대지면적연면적최상층동수세대수의무비의무임대위탁관리승강기설치중앙집중식난방(지역난방방식)사용승인일경과연수단지수법정동코드(시군)
01하동군다세대주택연화연립(다세대)하동군하동읍 읍내리1014외1하동읍 산복2길 77-1450517.11218NYNNNN1983-01-013914885000000
12하동군연립주택연화빌라하동군하동읍 읍내리1122하동읍 수박등길 1210261155.693118NYNNNN1984-06-203814885000000
23하동군다세대주택신촌빌라하동군하동읍 비파리3611외1하동읍 군청로 143983658.83112NYNNNN1986-12-293614885000000
34하동군다세대주택하평다세대(선창아파트)하동군진교면 진교리302150외5진교면 선창길 11-12외518041858.953642NYNNNN1989-08-263314885000000
45하동군아파트무지개맨션하동군하동읍 비파리61146하동읍 소재1길 930274048.985250NYNNNN1990-04-063214885000000
56하동군연립주택대림연립하동군진교면 진교리661진교면 민다리안길 116-7450705.543112NYNNNN1990-01-013214885000000
67하동군아파트흥한로얄맨션하동군하동읍 비파리61153하동읍 소재1길 21655313740.9764144NYNNNN1991-10-143114885000000
78하동군아파트미도빌라하동군하동읍 읍내리149421하동읍 섬진강대로 217432265083.355260NYNNNN1991-06-143114885000000
89하동군아파트강변타운(한영아파트)하동군하동읍 신기리369외2하동읍 부두길 730105506.096171NYNNNN1991-10-143114885000000
910하동군아파트한다사아파트하동군하동읍 읍내리53<NA>하동읍 연화길 3617311694.45120NYNNNN1990-12-123214885000000
연번시군용도단지명시군구법정동본번부번도로명주소대지면적연면적최상층동수세대수의무비의무임대위탁관리승강기설치중앙집중식난방(지역난방방식)사용승인일경과연수단지수법정동코드(시군)
6768하동군다세대주택태영금빛고을하동군하동읍 두곡리6333하동읍 산복1길 613291317.925216NYNNNN2014-08-22814885000000
6869하동군아파트파밀리에하동군하동읍 광평리2541하동읍 송림3길 19-239771353.40468114NYNNYN2017-01-26514885000000
6970하동군아파트미라벨아파트하동군하동읍 읍내리11842하동읍 서동길 15-439007254.1316163NYNYYN2017-05-04514885000000
7071하동군아파트금강블레스하동군진교면 진교리302113진교면 진교시장길 17-1346037780.757218168NYNNYN2018-05-01414885000000
7172하동군아파트LH천년나무아파트하동군하동읍 읍내리1565<NA>하동읍 군청로 2414555.116817.53153306YNYNYN2018-08-14414885000000
7273하동군아파트하동경인아네뜨하동군하동읍 비파리3672하동읍 경서대로 2414771545.928112NYNNYN2018-09-13414885000000
7374하동군다세대주택전도강변빌라하동군고전면 전도리2412고전면 하동읍성로 21-1121971963.284324NYNNNN2018-05-16414885000000
7475하동군아파트그린나래하동군하동읍 비파리4002하동읍 산복2길 1826523458.7728128NYNNYN2019-07-10314885000000
7576하동군아파트승원센트레빌하동군진교면 진교리42699진교면 진교중앙길 14-7668343214123NYNNYN2020-01-31214885000000
7677하동군아파트제이엠스퀘어하동군하동읍 비파리58<NA>하동읍 군청로 165-71,8132,832.5213124NYNNYN2022-05-17014885000000