Overview

Dataset statistics

Number of variables14
Number of observations33
Missing cells74
Missing cells (%)16.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory120.0 B

Variable types

Categorical2
Text6
DateTime3
Numeric3

Dataset

Description안양시 공동주택 시공 현황(시군명, 공사명, 공사시작일, 공사완료일, 시공사명, 시공사전화번호, 세대수, 입주예정일, 우편번호, 시공위치지번주소, 시공위치도로명주소, WGS84위도, WGS84경도, 비고)입니다.
URLhttps://www.data.go.kr/data/15114535/fileData.do

Alerts

시군명 has constant value ""Constant
세대수 is highly overall correlated with 우편번호High correlation
WGS84위도 is highly overall correlated with WGS84경도 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
우편번호 is highly overall correlated with 세대수 and 2 other fieldsHigh correlation
우편번호 is highly imbalanced (62.7%)Imbalance
공사완료일 has 1 (3.0%) missing valuesMissing
시공사전화번호 has 5 (15.2%) missing valuesMissing
세대수 has 1 (3.0%) missing valuesMissing
입주예정일 has 6 (18.2%) missing valuesMissing
시공위치도로명주소 has 31 (93.9%) missing valuesMissing
비고 has 30 (90.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 23:04:58.074160
Analysis finished2023-12-12 23:05:00.274057
Duration2.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
안양시
33 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안양시 33
100.0%

Length

2023-12-13T08:05:00.330931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:00.420102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안양시 33
100.0%

공사명
Text

Distinct22
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T08:05:00.591986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length15.878788
Min length12

Characters and Unicode

Total characters524
Distinct characters89
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)42.4%

Sample

1st row삼영(아) 주변지구 재개발정비사업
2nd row예술공원입구 주변지구 재개발정비사업
3rd row소곡지구 재개발정비사업
4th row소곡지구 재개발정비사업
5th row비산1동주민센터 주변지구 재개발정비사업
ValueCountFrequency (%)
재개발정비사업 19
27.1%
재건축정비사업 6
 
8.6%
임곡3지구 3
 
4.3%
융창(아)주변지구 3
 
4.3%
비산초교주변지구 3
 
4.3%
주변지구 3
 
4.3%
진흥아파트 2
 
2.9%
냉천지구 2
 
2.9%
주거환경개선사업 2
 
2.9%
소곡지구 2
 
2.9%
Other values (22) 25
35.7%
2023-12-13T08:05:00.884413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
 
7.1%
비 34
 
6.5%
사 34
 
6.5%
업 33
 
6.3%
지 28
 
5.3%
구 28
 
5.3%
재 27
 
5.2%
정 27
 
5.2%
주 26
 
5.0%
개 21
 
4.0%
Other values (79) 229
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 463
88.4%
Space Separator 37
 
7.1%
Decimal Number 12
 
2.3%
Open Punctuation 5
 
1.0%
Close Punctuation 5
 
1.0%
Dash Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 34
 
7.3%
사 34
 
7.3%
업 33
 
7.1%
지 28
 
6.0%
구 28
 
6.0%
재 27
 
5.8%
정 27
 
5.8%
주 26
 
5.6%
개 21
 
4.5%
발 19
 
4.1%
Other values (69) 186
40.2%
Decimal Number
ValueCountFrequency (%)
3 4
33.3%
2 3
25.0%
5 2
16.7%
1 2
16.7%
6 1
 
8.3%
Space Separator
ValueCountFrequency (%)
37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 463
88.4%
Common 61
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 34
 
7.3%
사 34
 
7.3%
업 33
 
7.1%
지 28
 
6.0%
구 28
 
6.0%
재 27
 
5.8%
정 27
 
5.8%
주 26
 
5.6%
개 21
 
4.5%
발 19
 
4.1%
Other values (69) 186
40.2%
Common
ValueCountFrequency (%)
37
60.7%
( 5
 
8.2%
) 5
 
8.2%
3 4
 
6.6%
2 3
 
4.9%
5 2
 
3.3%
1 2
 
3.3%
- 1
 
1.6%
· 1
 
1.6%
6 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 463
88.4%
ASCII 60
 
11.5%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37
61.7%
( 5
 
8.3%
) 5
 
8.3%
3 4
 
6.7%
2 3
 
5.0%
5 2
 
3.3%
1 2
 
3.3%
- 1
 
1.7%
6 1
 
1.7%
Hangul
ValueCountFrequency (%)
비 34
 
7.3%
사 34
 
7.3%
업 33
 
7.1%
지 28
 
6.0%
구 28
 
6.0%
재 27
 
5.8%
정 27
 
5.8%
주 26
 
5.6%
개 21
 
4.5%
발 19
 
4.1%
Other values (69) 186
40.2%
None
ValueCountFrequency (%)
· 1
100.0%

공사시작일
Date

Distinct21
Distinct (%)63.6%
Missing0
Missing (%)0.0%
Memory size396.0 B
Minimum2018-05-01 00:00:00
Maximum2022-08-05 00:00:00
2023-12-13T08:05:00.985857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:01.079727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

공사완료일
Date

MISSING 

Distinct22
Distinct (%)68.8%
Missing1
Missing (%)3.0%
Memory size396.0 B
Minimum2021-06-11 00:00:00
Maximum2025-06-01 00:00:00
2023-12-13T08:05:01.179857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:01.273880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

시공사명
Text

Distinct17
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T08:05:01.411587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length4
Mean length5.2121212
Min length2

Characters and Unicode

Total characters172
Distinct characters52
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)27.3%

Sample

1st row두산건설
2nd rowGS건설
3rd rowGS건설
4th rowGS건설
5th row한신공영
ValueCountFrequency (%)
gs건설 7
19.4%
현대건설 4
11.1%
두산건설 3
8.3%
현대산업개발 3
8.3%
대우건설 3
8.3%
대림산업 3
8.3%
코오롱글로벌 2
 
5.6%
포스코건설 2
 
5.6%
한신공영 1
 
2.8%
sk에코플랜트 1
 
2.8%
Other values (7) 7
19.4%
2023-12-13T08:05:01.662080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
건 21
 
12.2%
설 21
 
12.2%
대 13
 
7.6%
산 10
 
5.8%
S 8
 
4.7%
G 7
 
4.1%
현 7
 
4.1%
업 6
 
3.5%
코 5
 
2.9%
발 4
 
2.3%
Other values (42) 70
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
86.6%
Uppercase Letter 16
 
9.3%
Other Punctuation 3
 
1.7%
Space Separator 3
 
1.7%
Other Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
건 21
 
14.1%
설 21
 
14.1%
대 13
 
8.7%
산 10
 
6.7%
현 7
 
4.7%
업 6
 
4.0%
코 5
 
3.4%
발 4
 
2.7%
개 4
 
2.7%
두 3
 
2.0%
Other values (36) 55
36.9%
Uppercase Letter
ValueCountFrequency (%)
S 8
50.0%
G 7
43.8%
K 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150
87.2%
Latin 16
 
9.3%
Common 6
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
건 21
 
14.0%
설 21
 
14.0%
대 13
 
8.7%
산 10
 
6.7%
현 7
 
4.7%
업 6
 
4.0%
코 5
 
3.3%
발 4
 
2.7%
개 4
 
2.7%
두 3
 
2.0%
Other values (37) 56
37.3%
Latin
ValueCountFrequency (%)
S 8
50.0%
G 7
43.8%
K 1
 
6.2%
Common
ValueCountFrequency (%)
, 3
50.0%
3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
86.6%
ASCII 22
 
12.8%
None 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
건 21
 
14.1%
설 21
 
14.1%
대 13
 
8.7%
산 10
 
6.7%
현 7
 
4.7%
업 6
 
4.0%
코 5
 
3.4%
발 4
 
2.7%
개 4
 
2.7%
두 3
 
2.0%
Other values (36) 55
36.9%
ASCII
ValueCountFrequency (%)
S 8
36.4%
G 7
31.8%
, 3
 
13.6%
3
 
13.6%
K 1
 
4.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

시공사전화번호
Text

MISSING 

Distinct26
Distinct (%)92.9%
Missing5
Missing (%)15.2%
Memory size396.0 B
2023-12-13T08:05:01.832375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.071429
Min length11

Characters and Unicode

Total characters338
Distinct characters11
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

Unique24 ?
Unique (%)85.7%

Sample

1st row031-473-9881
2nd row031-471-3809
3rd row031-965-5049
4th row031-965-5049
5th row031-468-8313
ValueCountFrequency (%)
031-443-9114 2
 
7.1%
031-965-5049 2
 
7.1%
031-473-9881 1
 
3.6%
031-459-5107 1
 
3.6%
062-365-7171 1
 
3.6%
031-360-0301 1
 
3.6%
031-426-8482 1
 
3.6%
031-337-3382 1
 
3.6%
031-469-8561 1
 
3.6%
031-441-8048 1
 
3.6%
Other values (16) 16
57.1%
2023-12-13T08:05:02.118251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 56
16.6%
0 47
13.9%
3 46
13.6%
1 42
12.4%
4 33
9.8%
7 25
7.4%
6 20
 
5.9%
2 19
 
5.6%
9 18
 
5.3%
8 17
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 282
83.4%
Dash Punctuation 56
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47
16.7%
3 46
16.3%
1 42
14.9%
4 33
11.7%
7 25
8.9%
6 20
7.1%
2 19
6.7%
9 18
 
6.4%
8 17
 
6.0%
5 15
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 338
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 56
16.6%
0 47
13.9%
3 46
13.6%
1 42
12.4%
4 33
9.8%
7 25
7.4%
6 20
 
5.9%
2 19
 
5.6%
9 18
 
5.3%
8 17
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 338
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 56
16.6%
0 47
13.9%
3 46
13.6%
1 42
12.4%
4 33
9.8%
7 25
7.4%
6 20
 
5.9%
2 19
 
5.6%
9 18
 
5.3%
8 17
 
5.0%

세대수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)65.6%
Missing1
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean1624
Minimum61
Maximum4154
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T08:05:02.231932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61
5-th percentile141.75
Q1468
median1394
Q32736.25
95-th percentile2886
Maximum4154
Range4093
Interquartile range (IQR)2268.25

Descriptive statistics

Standard deviation1149.8256
Coefficient of variation (CV)0.70802069
Kurtosis-1.2225178
Mean1624
Median Absolute Deviation (MAD)1090.5
Skewness0.14267597
Sum51968
Variance1322098.9
MonotonicityNot monotonic
2023-12-13T08:05:02.326872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2739 3
 
9.1%
2417 3
 
9.1%
2736 2
 
6.1%
1394 2
 
6.1%
230 2
 
6.1%
2737 2
 
6.1%
2886 2
 
6.1%
1199 2
 
6.1%
2329 2
 
6.1%
303 1
 
3.0%
Other values (11) 11
33.3%
ValueCountFrequency (%)
61 1
3.0%
139 1
3.0%
144 1
3.0%
230 2
6.1%
303 1
3.0%
304 1
3.0%
456 1
3.0%
472 1
3.0%
558 1
3.0%
855 1
3.0%
ValueCountFrequency (%)
4154 1
 
3.0%
2886 2
6.1%
2739 3
9.1%
2737 2
6.1%
2736 2
6.1%
2417 3
9.1%
2329 2
6.1%
1394 2
6.1%
1199 2
6.1%
1021 1
 
3.0%

입주예정일
Date

MISSING 

Distinct15
Distinct (%)55.6%
Missing6
Missing (%)18.2%
Memory size396.0 B
Minimum2021-02-01 00:00:00
Maximum2025-06-01 00:00:00
2023-12-13T08:05:02.432639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:02.525478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

우편번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
28 
431050
 
1
431080
 
1
431070
 
1
430030
 
1

Length

Max length6
Median length4
Mean length4.2727273
Min length4

Unique

Unique5 ?
Unique (%)15.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 28
84.8%
431050 1
 
3.0%
431080 1
 
3.0%
431070 1
 
3.0%
430030 1
 
3.0%
14084 1
 
3.0%

Length

2023-12-13T08:05:02.658075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:02.813915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
84.8%
431050 1
 
3.0%
431080 1
 
3.0%
431070 1
 
3.0%
430030 1
 
3.0%
14084 1
 
3.0%

시공위치지번주소
Text

Distinct23
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T08:05:03.000687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length34
Mean length26.090909
Min length19

Characters and Unicode

Total characters861
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row경기도 안양시 만안구 안양2동 34-1번지 일원
2nd row경기도 안양시 만안구 안양2동 18-1번지 일원
3rd row경기도 안양시 만안구 안양6동 585-2번지 일원
4th row경기도 안양시 만안구 안양6동 585-2번지 일원
5th row경기도 안양시 동안구 비산1동 554-5번지 일원
ValueCountFrequency (%)
경기도 33
17.2%
안양시 33
17.2%
일원 24
12.5%
동안구 22
11.5%
만안구 11
 
5.7%
호계2동 4
 
2.1%
비산1동 4
 
2.1%
281-1번지 3
 
1.6%
929번지 3
 
1.6%
비산3동 3
 
1.6%
Other values (35) 52
27.1%
2023-12-13T08:05:03.366872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
159
18.5%
안 75
 
8.7%
동 59
 
6.9%
1 42
 
4.9%
양 42
 
4.9%
경 33
 
3.8%
도 33
 
3.8%
시 33
 
3.8%
구 33
 
3.8%
기 33
 
3.8%
Other values (28) 319
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 510
59.2%
Decimal Number 163
 
18.9%
Space Separator 159
 
18.5%
Dash Punctuation 22
 
2.6%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 75
14.7%
동 59
11.6%
양 42
 
8.2%
경 33
 
6.5%
도 33
 
6.5%
시 33
 
6.5%
구 33
 
6.5%
기 33
 
6.5%
지 28
 
5.5%
번 28
 
5.5%
Other values (13) 113
22.2%
Decimal Number
ValueCountFrequency (%)
1 42
25.8%
2 27
16.6%
8 19
11.7%
5 18
11.0%
9 17
10.4%
3 11
 
6.7%
4 9
 
5.5%
6 7
 
4.3%
0 7
 
4.3%
7 6
 
3.7%
Space Separator
ValueCountFrequency (%)
159
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 510
59.2%
Common 351
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 75
14.7%
동 59
11.6%
양 42
 
8.2%
경 33
 
6.5%
도 33
 
6.5%
시 33
 
6.5%
구 33
 
6.5%
기 33
 
6.5%
지 28
 
5.5%
번 28
 
5.5%
Other values (13) 113
22.2%
Common
ValueCountFrequency (%)
159
45.3%
1 42
 
12.0%
2 27
 
7.7%
- 22
 
6.3%
8 19
 
5.4%
5 18
 
5.1%
9 17
 
4.8%
3 11
 
3.1%
4 9
 
2.6%
6 7
 
2.0%
Other values (5) 20
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 510
59.2%
ASCII 351
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
159
45.3%
1 42
 
12.0%
2 27
 
7.7%
- 22
 
6.3%
8 19
 
5.4%
5 18
 
5.1%
9 17
 
4.8%
3 11
 
3.1%
4 9
 
2.6%
6 7
 
2.0%
Other values (5) 20
 
5.7%
Hangul
ValueCountFrequency (%)
안 75
14.7%
동 59
11.6%
양 42
 
8.2%
경 33
 
6.5%
도 33
 
6.5%
시 33
 
6.5%
구 33
 
6.5%
기 33
 
6.5%
지 28
 
5.5%
번 28
 
5.5%
Other values (13) 113
22.2%

시공위치도로명주소
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing31
Missing (%)93.9%
Memory size396.0 B
2023-12-13T08:05:03.535927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20.5
Mean length20.5
Min length19

Characters and Unicode

Total characters41
Distinct characters22
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

Unique2 ?
Unique (%)100.0%

Sample

1st row경기도 안양시 만안구 박달로 427
2nd row경기도 안양시 만안구 전파로61번길 20
ValueCountFrequency (%)
경기도 2
20.0%
안양시 2
20.0%
만안구 2
20.0%
박달로 1
10.0%
427 1
10.0%
전파로61번길 1
10.0%
20 1
10.0%
2023-12-13T08:05:03.892862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
19.5%
안 4
 
9.8%
경 2
 
4.9%
만 2
 
4.9%
2 2
 
4.9%
기 2
 
4.9%
구 2
 
4.9%
로 2
 
4.9%
시 2
 
4.9%
양 2
 
4.9%
Other values (12) 13
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26
63.4%
Space Separator 8
 
19.5%
Decimal Number 7
 
17.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 4
15.4%
경 2
 
7.7%
만 2
 
7.7%
기 2
 
7.7%
구 2
 
7.7%
로 2
 
7.7%
시 2
 
7.7%
양 2
 
7.7%
도 2
 
7.7%
박 1
 
3.8%
Other values (5) 5
19.2%
Decimal Number
ValueCountFrequency (%)
2 2
28.6%
4 1
14.3%
7 1
14.3%
6 1
14.3%
1 1
14.3%
0 1
14.3%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26
63.4%
Common 15
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 4
15.4%
경 2
 
7.7%
만 2
 
7.7%
기 2
 
7.7%
구 2
 
7.7%
로 2
 
7.7%
시 2
 
7.7%
양 2
 
7.7%
도 2
 
7.7%
박 1
 
3.8%
Other values (5) 5
19.2%
Common
ValueCountFrequency (%)
8
53.3%
2 2
 
13.3%
4 1
 
6.7%
7 1
 
6.7%
6 1
 
6.7%
1 1
 
6.7%
0 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26
63.4%
ASCII 15
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
53.3%
2 2
 
13.3%
4 1
 
6.7%
7 1
 
6.7%
6 1
 
6.7%
1 1
 
6.7%
0 1
 
6.7%
Hangul
ValueCountFrequency (%)
안 4
15.4%
경 2
 
7.7%
만 2
 
7.7%
기 2
 
7.7%
구 2
 
7.7%
로 2
 
7.7%
시 2
 
7.7%
양 2
 
7.7%
도 2
 
7.7%
박 1
 
3.8%
Other values (5) 5
19.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.393051
Minimum37.36234
Maximum37.43633
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T08:05:04.033837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.36234
5-th percentile37.367311
Q137.381219
median37.392752
Q337.401106
95-th percentile37.413573
Maximum37.43633
Range0.07398967
Interquartile range (IQR)0.01988621

Descriptive statistics

Standard deviation0.015674967
Coefficient of variation (CV)0.00041919466
Kurtosis0.64956038
Mean37.393051
Median Absolute Deviation (MAD)0.00949102
Skewness0.19632925
Sum1233.9707
Variance0.0002457046
MonotonicityNot monotonic
2023-12-13T08:05:04.202531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
37.40110553 3
 
9.1%
37.40741801 3
 
9.1%
37.38121932 3
 
9.1%
37.39837833 2
 
6.1%
37.38699805 2
 
6.1%
37.37447537 2
 
6.1%
37.39749483 2
 
6.1%
37.3913317 2
 
6.1%
37.40546686 1
 
3.0%
37.367181 1
 
3.0%
Other values (12) 12
36.4%
ValueCountFrequency (%)
37.36233987 1
 
3.0%
37.367181 1
 
3.0%
37.36739697 1
 
3.0%
37.37224756 1
 
3.0%
37.37447537 2
6.1%
37.38121932 3
9.1%
37.38699805 2
6.1%
37.38769704 1
 
3.0%
37.39088703 1
 
3.0%
37.3913317 2
6.1%
ValueCountFrequency (%)
37.43632954 1
 
3.0%
37.41535856 1
 
3.0%
37.41238324 1
 
3.0%
37.40741801 3
9.1%
37.40546686 1
 
3.0%
37.40224348 1
 
3.0%
37.40110553 3
9.1%
37.39958253 1
 
3.0%
37.39837833 2
6.1%
37.39749483 2
6.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.9382
Minimum126.90021
Maximum126.97654
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T08:05:04.369166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.90021
5-th percentile126.90998
Q1126.92751
median126.93876
Q3126.94928
95-th percentile126.96206
Maximum126.97654
Range0.0763288
Interquartile range (IQR)0.0217721

Descriptive statistics

Standard deviation0.017126619
Coefficient of variation (CV)0.00013492092
Kurtosis0.1671535
Mean126.9382
Median Absolute Deviation (MAD)0.0112481
Skewness-0.18481274
Sum4188.9607
Variance0.00029332109
MonotonicityNot monotonic
2023-12-13T08:05:04.535094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
126.9337067 3
 
9.1%
126.9436968 3
 
9.1%
126.9492839 3
 
9.1%
126.9275118 2
 
6.1%
126.9230941 2
 
6.1%
126.9607254 2
 
6.1%
126.9387599 2
 
6.1%
126.9227846 2
 
6.1%
126.934482 1
 
3.0%
126.951793 1
 
3.0%
Other values (12) 12
36.4%
ValueCountFrequency (%)
126.9002074 1
 
3.0%
126.9014037 1
 
3.0%
126.9157024 1
 
3.0%
126.9184552 1
 
3.0%
126.9227846 2
6.1%
126.9230941 2
6.1%
126.9275118 2
6.1%
126.9331999 1
 
3.0%
126.9337067 3
9.1%
126.934482 1
 
3.0%
ValueCountFrequency (%)
126.9765362 1
 
3.0%
126.9640621 1
 
3.0%
126.9607254 2
6.1%
126.9546754 1
 
3.0%
126.953948 1
 
3.0%
126.951793 1
 
3.0%
126.9492839 3
9.1%
126.9480936 1
 
3.0%
126.9436968 3
9.1%
126.9417816 1
 
3.0%

비고
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing30
Missing (%)90.9%
Memory size396.0 B
2023-12-13T08:05:04.674367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.6666667
Min length3

Characters and Unicode

Total characters11
Distinct characters6
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

Unique1 ?
Unique (%)33.3%

Sample

1st row122동
2nd row122동
3rd row3획지
ValueCountFrequency (%)
122동 2
66.7%
3획지 1
33.3%
2023-12-13T08:05:04.959414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4
36.4%
1 2
18.2%
동 2
18.2%
3 1
 
9.1%
획 1
 
9.1%
지 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
63.6%
Other Letter 4
36.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
57.1%
1 2
28.6%
3 1
 
14.3%
Other Letter
ValueCountFrequency (%)
동 2
50.0%
획 1
25.0%
지 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7
63.6%
Hangul 4
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
57.1%
1 2
28.6%
3 1
 
14.3%
Hangul
ValueCountFrequency (%)
동 2
50.0%
획 1
25.0%
지 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
63.6%
Hangul 4
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4
57.1%
1 2
28.6%
3 1
 
14.3%
Hangul
ValueCountFrequency (%)
동 2
50.0%
획 1
25.0%
지 1
25.0%

Interactions

2023-12-13T08:04:59.171661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:04:58.541480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:04:58.811270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:04:59.255267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:04:58.616479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:04:58.911876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:04:59.355878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:04:58.720613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:04:59.043907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:05:05.080616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사명공사시작일공사완료일시공사명시공사전화번호세대수입주예정일우편번호시공위치지번주소시공위치도로명주소WGS84위도WGS84경도비고
공사명1.0001.0001.0000.9171.0001.0000.9761.0001.0000.0001.0001.0000.000
공사시작일1.0001.0001.0000.9161.0000.9980.9761.0001.0000.0001.0000.9660.000
공사완료일1.0001.0001.0000.8760.9801.0000.9871.0001.0000.0001.0001.0001.000
시공사명0.9170.9160.8761.0001.0000.1820.3171.0000.8950.0000.7560.7880.000
시공사전화번호1.0001.0000.9801.0001.0001.0000.3921.0001.0000.0001.0001.0000.000
세대수1.0000.9981.0000.1821.0001.0000.8991.0001.000NaN0.6340.5400.000
입주예정일0.9760.9760.9870.3170.3920.8991.000NaN0.976NaN0.9670.9491.000
우편번호1.0001.0001.0001.0001.0001.000NaN1.0001.0000.0001.0001.000NaN
시공위치지번주소1.0001.0001.0000.8951.0001.0000.9761.0001.0000.0001.0001.0000.000
시공위치도로명주소0.0000.0000.0000.0000.000NaNNaN0.0000.0001.0000.0000.000NaN
WGS84위도1.0001.0001.0000.7561.0000.6340.9671.0001.0000.0001.0000.9320.000
WGS84경도1.0000.9661.0000.7881.0000.5400.9491.0001.0000.0000.9321.0000.000
비고0.0000.0001.0000.0000.0000.0001.000NaN0.000NaN0.0000.0001.000
2023-12-13T08:05:05.236602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수WGS84위도WGS84경도우편번호
세대수1.000-0.0920.2691.000
WGS84위도-0.0921.000-0.6371.000
WGS84경도0.269-0.6371.0001.000
우편번호1.0001.0001.0001.000

Missing values

2023-12-13T08:04:59.796529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:04:59.998979image/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.
2023-12-13T08:05:00.178950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명공사명공사시작일공사완료일시공사명시공사전화번호세대수입주예정일우편번호시공위치지번주소시공위치도로명주소WGS84위도WGS84경도비고
0안양시삼영(아) 주변지구 재개발정비사업2019-10-082022-06-01두산건설031-473-98815582022-06-01<NA>경기도 안양시 만안구 안양2동 34-1번지 일원<NA>37.412383126.915702<NA>
1안양시예술공원입구 주변지구 재개발정비사업2019-11-272022-08-01GS건설031-471-380910212022-08-01<NA>경기도 안양시 만안구 안양2동 18-1번지 일원<NA>37.415359126.918455<NA>
2안양시소곡지구 재개발정비사업2018-05-292021-10-07GS건설031-965-504913942021-02-01<NA>경기도 안양시 만안구 안양6동 585-2번지 일원<NA>37.386998126.923094<NA>
3안양시소곡지구 재개발정비사업2018-05-292021-10-07GS건설031-965-504913942021-04-01<NA>경기도 안양시 만안구 안양6동 585-2번지 일원<NA>37.386998126.923094<NA>
4안양시비산1동주민센터 주변지구 재개발정비사업2020-08-252023-12-01한신공영031-468-83132302023-12-01<NA>경기도 안양시 동안구 비산1동 554-5번지 일원<NA>37.399583126.9332<NA>
5안양시임곡3지구 재개발정비사업2018-12-172021-12-29GS건설, 현대산업개발031-360-3613<NA>2021-12-01<NA>경기도 안양시 동안구 비산1동 488-80번지 일원(101동~121동)<NA>37.401106126.933707<NA>
6안양시임곡3지구 재개발정비사업2018-12-172021-12-29GS건설, 현대산업개발031-443-911427372021-12-01<NA>경기도 안양시 동안구 비산1동 488-80번지 일원(122동)<NA>37.401106126.933707122동
7안양시임곡3지구 재개발정비사업2018-12-172023-08-01GS건설, 현대산업개발031-443-911427372021-08-01<NA>경기도 안양시 동안구 비산1동 488-80번지 일원(122동)<NA>37.401106126.933707122동
8안양시비산초교주변지구 재개발정비사업2021-05-282024-05-01대우건설02-2288-312427392024-06-01<NA>경기도 안양시 동안구 비산3동 281-1번지 일원<NA>37.407418126.943697<NA>
9안양시비산초교주변지구 재개발정비사업2021-05-282024-05-01현대건설02-746-752927392024-06-01<NA>경기도 안양시 동안구 비산3동 281-1번지 일원<NA>37.407418126.943697<NA>
시군명공사명공사시작일공사완료일시공사명시공사전화번호세대수입주예정일우편번호시공위치지번주소시공위치도로명주소WGS84위도WGS84경도비고
23안양시진흥·로얄아파트 재건축정비사업2019-05-312021-11-15한양031-441-80483042021-11-01<NA>경기도 안양시 동안구 비산2동 577-1번지 일원<NA>37.392227126.941782<NA>
24안양시냉천지구 주거환경개선사업2021-12-302024-12-01대림산업<NA>23292024-12-01<NA>경기도 안양시 만안구 안양5동 618번지 일원<NA>37.391332126.922785<NA>
25안양시냉천지구 주거환경개선사업2021-12-302024-12-01경기도시공사<NA>23292024-12-01<NA>경기도 안양시 만안구 안양5동 618번지 일원<NA>37.391332126.922785<NA>
26안양시비산동 평화지구공동주택 신축사업2019-10-252022-04-30현대건설031-469-8561303<NA>431050경기도 안양시 동안구 비산동 510<NA>37.405467126.934482<NA>
27안양시남강주택지구주택재건축정비사업2019-12-302022-03-28신원종합개발031-337-3382144<NA>431080경기도 안양시 동안구 호계동 851-27<NA>37.36234126.964062<NA>
28안양시평촌동지역주택조합 주택건설사업2021-11-292024-06-01현대건설031-426-8482472<NA>431070경기도 안양시 동안구 평촌동 54-1<NA>37.392752126.976536<NA>
29안양시삼봉초교주변지구 주택건설사업2020-08-212022-11-01자이에스앤디031-360-0301139<NA>430030경기도 안양시 만안구 박달동 157-1경기도 안양시 만안구 박달로 42737.402243126.900207<NA>
30안양시동성2차아파트 소규모재건축정비사업2018-12-132021-06-11㈜광신종합건설062-365-7171230<NA>14084경기도 안양시 만안구 안양동 1429번지경기도 안양시 만안구 전파로61번길 2037.390887126.940504<NA>
31안양시하임유(석수동 355-1번지 도시형생활주택사업)2022-07-05<NA>투탑건설<NA>61<NA><NA>경기도 안양시 만안구 석수동 355-1<NA>37.43633126.901404<NA>
32안양시삼신6차아파트 재건축정비사업2022-08-052025-06-01두산건설031-249-89634562025-06-01<NA>경기도 안양시 동안구 호계3동 651-1번지 일원<NA>37.367181126.951793<NA>