Overview

Dataset statistics

Number of variables10
Number of observations164
Missing cells256
Missing cells (%)15.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.1 KiB
Average record size in memory81.8 B

Variable types

Categorical3
Text6
Numeric1

Dataset

Description부천시 내 정비유형(재개발, 가로주택정비, 소규모재건축사업)에 따른 구역명, 조합연락처, 정비구역, 면적, 조합설립인가 진행단계등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15051011/fileData.do

Alerts

세대수 is highly overall correlated with 정비 유형 and 2 other fieldsHigh correlation
정비 유형 is highly overall correlated with 세대수 and 2 other fieldsHigh correlation
건축계획 동수_층수 is highly overall correlated with 세대수 and 2 other fieldsHigh correlation
진행단계 is highly overall correlated with 세대수 and 2 other fieldsHigh correlation
조합연락처 및 조합주소 has 21 (12.8%) missing valuesMissing
세대수 has 19 (11.6%) missing valuesMissing
건축계획 건폐율 has 97 (59.1%) missing valuesMissing
건축계획 용적률 has 97 (59.1%) missing valuesMissing
조합설립인가일자 has 22 (13.4%) missing valuesMissing
구역명 has unique valuesUnique
정비구역위치 및 면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:56:01.465139
Analysis finished2023-12-12 15:56:02.939091
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정비 유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
가로주택정비
104 
소규모재건축
30 
재건축
23 
재개발
 
7

Length

Max length6
Median length6
Mean length5.4512195
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가로주택정비 104
63.4%
소규모재건축 30
 
18.3%
재건축 23
 
14.0%
재개발 7
 
4.3%

Length

2023-12-13T00:56:03.031616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:56:03.210917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가로주택정비 104
63.4%
소규모재건축 30
 
18.3%
재건축 23
 
14.0%
재개발 7
 
4.3%

구역명
Text

UNIQUE 

Distinct164
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T00:56:03.569311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19
Mean length10.640244
Min length2

Characters and Unicode

Total characters1745
Distinct characters176
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)100.0%

Sample

1st row괴안3D구역재개발
2nd row소사3구역 재개발
3rd row소사1-1구역재개발
4th row소사본1-1구역재개발
5th row괴안2D구역 재개발
ValueCountFrequency (%)
가로주택정비사업 17
 
6.7%
외 8
 
3.1%
원종동 8
 
3.1%
소사본동 7
 
2.8%
일원 7
 
2.8%
고강동 6
 
2.4%
역곡동 4
 
1.6%
한아름아파트 3
 
1.2%
건우아파트 2
 
0.8%
심곡본동 2
 
0.8%
Other values (187) 190
74.8%
2023-12-13T00:56:04.110454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
 
5.2%
아 77
 
4.4%
트 74
 
4.2%
파 73
 
4.2%
동 57
 
3.3%
주 50
 
2.9%
사 46
 
2.6%
택 43
 
2.5%
3 41
 
2.3%
- 41
 
2.3%
Other values (166) 1153
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1380
79.1%
Decimal Number 158
 
9.1%
Space Separator 90
 
5.2%
Dash Punctuation 41
 
2.3%
Close Punctuation 25
 
1.4%
Open Punctuation 25
 
1.4%
Other Punctuation 14
 
0.8%
Uppercase Letter 12
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 77
 
5.6%
트 74
 
5.4%
파 73
 
5.3%
동 57
 
4.1%
주 50
 
3.6%
사 46
 
3.3%
택 43
 
3.1%
역 39
 
2.8%
원 39
 
2.8%
정 38
 
2.8%
Other values (143) 844
61.2%
Decimal Number
ValueCountFrequency (%)
3 41
25.9%
1 37
23.4%
2 30
19.0%
6 10
 
6.3%
5 9
 
5.7%
4 9
 
5.7%
7 7
 
4.4%
9 6
 
3.8%
8 5
 
3.2%
0 4
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
A 3
25.0%
L 2
16.7%
H 2
16.7%
D 2
16.7%
P 1
 
8.3%
T 1
 
8.3%
B 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 13
92.9%
. 1
 
7.1%
Space Separator
ValueCountFrequency (%)
90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1380
79.1%
Common 353
 
20.2%
Latin 12
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 77
 
5.6%
트 74
 
5.4%
파 73
 
5.3%
동 57
 
4.1%
주 50
 
3.6%
사 46
 
3.3%
택 43
 
3.1%
역 39
 
2.8%
원 39
 
2.8%
정 38
 
2.8%
Other values (143) 844
61.2%
Common
ValueCountFrequency (%)
90
25.5%
3 41
11.6%
- 41
11.6%
1 37
10.5%
2 30
 
8.5%
) 25
 
7.1%
( 25
 
7.1%
, 13
 
3.7%
6 10
 
2.8%
5 9
 
2.5%
Other values (6) 32
 
9.1%
Latin
ValueCountFrequency (%)
A 3
25.0%
L 2
16.7%
H 2
16.7%
D 2
16.7%
P 1
 
8.3%
T 1
 
8.3%
B 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1380
79.1%
ASCII 365
 
20.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90
24.7%
3 41
11.2%
- 41
11.2%
1 37
10.1%
2 30
 
8.2%
) 25
 
6.8%
( 25
 
6.8%
, 13
 
3.6%
6 10
 
2.7%
5 9
 
2.5%
Other values (13) 44
12.1%
Hangul
ValueCountFrequency (%)
아 77
 
5.6%
트 74
 
5.4%
파 73
 
5.3%
동 57
 
4.1%
주 50
 
3.6%
사 46
 
3.3%
택 43
 
3.1%
역 39
 
2.8%
원 39
 
2.8%
정 38
 
2.8%
Other values (143) 844
61.2%

조합연락처 및 조합주소
Text

MISSING 

Distinct142
Distinct (%)99.3%
Missing21
Missing (%)12.8%
Memory size1.4 KiB
2023-12-13T00:56:04.479702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length27.125874
Min length9

Characters and Unicode

Total characters3879
Distinct characters145
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)98.6%

Sample

1st row032-342-5156 / 경인로 536번길 57, 5층
2nd row032-344-5834 / 부흥로 487
3rd row032-347-3551 / 부일로 509, 5층
4th row032-345-0744 / 부천시 소삼로 2, 2층
5th row032-351-1921 / 경인로 553, 2층
ValueCountFrequency (%)
75
 
10.9%
부천시 29
 
4.2%
원종동 18
 
2.6%
고강동 16
 
2.3%
1층 11
 
1.6%
관리사무실 9
 
1.3%
102호 9
 
1.3%
2층 8
 
1.2%
괴안동 8
 
1.2%
3층 7
 
1.0%
Other values (398) 498
72.4%
2023-12-13T00:56:05.010721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
580
 
15.0%
2 252
 
6.5%
3 234
 
6.0%
1 224
 
5.8%
- 218
 
5.6%
0 204
 
5.3%
4 130
 
3.4%
6 129
 
3.3%
동 120
 
3.1%
7 116
 
3.0%
Other values (135) 1672
43.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1578
40.7%
Other Letter 1294
33.4%
Space Separator 580
 
15.0%
Dash Punctuation 218
 
5.6%
Other Punctuation 154
 
4.0%
Open Punctuation 24
 
0.6%
Close Punctuation 24
 
0.6%
Uppercase Letter 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 120
 
9.3%
로 80
 
6.2%
번 73
 
5.6%
호 59
 
4.6%
길 55
 
4.3%
부 46
 
3.6%
층 43
 
3.3%
천 37
 
2.9%
원 33
 
2.6%
사 31
 
2.4%
Other values (115) 717
55.4%
Decimal Number
ValueCountFrequency (%)
2 252
16.0%
3 234
14.8%
1 224
14.2%
0 204
12.9%
4 130
8.2%
6 129
8.2%
7 116
7.4%
5 113
7.2%
8 107
6.8%
9 69
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
B 4
57.1%
E 1
 
14.3%
G 1
 
14.3%
C 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
, 79
51.3%
/ 75
48.7%
Space Separator
ValueCountFrequency (%)
580
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 218
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2578
66.5%
Hangul 1294
33.4%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 120
 
9.3%
로 80
 
6.2%
번 73
 
5.6%
호 59
 
4.6%
길 55
 
4.3%
부 46
 
3.6%
층 43
 
3.3%
천 37
 
2.9%
원 33
 
2.6%
사 31
 
2.4%
Other values (115) 717
55.4%
Common
ValueCountFrequency (%)
580
22.5%
2 252
9.8%
3 234
9.1%
1 224
 
8.7%
- 218
 
8.5%
0 204
 
7.9%
4 130
 
5.0%
6 129
 
5.0%
7 116
 
4.5%
5 113
 
4.4%
Other values (6) 378
14.7%
Latin
ValueCountFrequency (%)
B 4
57.1%
E 1
 
14.3%
G 1
 
14.3%
C 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2585
66.6%
Hangul 1294
33.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
580
22.4%
2 252
9.7%
3 234
9.1%
1 224
 
8.7%
- 218
 
8.4%
0 204
 
7.9%
4 130
 
5.0%
6 129
 
5.0%
7 116
 
4.5%
5 113
 
4.4%
Other values (10) 385
14.9%
Hangul
ValueCountFrequency (%)
동 120
 
9.3%
로 80
 
6.2%
번 73
 
5.6%
호 59
 
4.6%
길 55
 
4.3%
부 46
 
3.6%
층 43
 
3.3%
천 37
 
2.9%
원 33
 
2.6%
사 31
 
2.4%
Other values (115) 717
55.4%

정비구역위치 및 면적(제곱미터)
Text

UNIQUE 

Distinct164
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T00:56:05.311781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length26
Mean length19.817073
Min length9

Characters and Unicode

Total characters3250
Distinct characters59
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)100.0%

Sample

1st row괴안동 201번지 일원(38,322.5)
2nd row소사동 48-21번지 일원(76,081.0)
3rd row소사동 8-5번지 일원(25,880.9)
4th row소사본동 88-39번지 일원(45,429.0)
5th row괴안동 189번지 일원(25,876.6)
ValueCountFrequency (%)
외 48
 
9.9%
원종동 35
 
7.2%
괴안동 26
 
5.4%
고강동 25
 
5.2%
소사본동 14
 
2.9%
역곡동 11
 
2.3%
송내동 11
 
2.3%
오정동 7
 
1.4%
심곡본동 7
 
1.4%
심곡동 6
 
1.2%
Other values (273) 294
60.7%
2023-12-13T00:56:05.724572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
324
 
10.0%
1 249
 
7.7%
3 178
 
5.5%
2 174
 
5.4%
동 164
 
5.0%
지 152
 
4.7%
6 130
 
4.0%
) 126
 
3.9%
( 126
 
3.9%
, 126
 
3.9%
Other values (49) 1501
46.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1371
42.2%
Other Letter 959
29.5%
Space Separator 324
 
10.0%
Other Punctuation 220
 
6.8%
Close Punctuation 126
 
3.9%
Open Punctuation 126
 
3.9%
Dash Punctuation 123
 
3.8%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 164
17.1%
지 152
15.8%
외 79
 
8.2%
번 77
 
8.0%
필 74
 
7.7%
원 67
 
7.0%
종 36
 
3.8%
안 27
 
2.8%
괴 27
 
2.8%
고 25
 
2.6%
Other values (31) 231
24.1%
Decimal Number
ValueCountFrequency (%)
1 249
18.2%
3 178
13.0%
2 174
12.7%
6 130
9.5%
4 119
8.7%
5 112
8.2%
8 111
8.1%
7 103
7.5%
9 100
7.3%
0 95
 
6.9%
Other Punctuation
ValueCountFrequency (%)
, 126
57.3%
. 93
42.3%
· 1
 
0.5%
Space Separator
ValueCountFrequency (%)
324
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 123
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2291
70.5%
Hangul 959
29.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 164
17.1%
지 152
15.8%
외 79
 
8.2%
번 77
 
8.0%
필 74
 
7.7%
원 67
 
7.0%
종 36
 
3.8%
안 27
 
2.8%
괴 27
 
2.8%
고 25
 
2.6%
Other values (31) 231
24.1%
Common
ValueCountFrequency (%)
324
14.1%
1 249
10.9%
3 178
 
7.8%
2 174
 
7.6%
6 130
 
5.7%
) 126
 
5.5%
( 126
 
5.5%
, 126
 
5.5%
- 123
 
5.4%
4 119
 
5.2%
Other values (8) 616
26.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2289
70.4%
Hangul 959
29.5%
CJK Compat 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
324
14.2%
1 249
10.9%
3 178
 
7.8%
2 174
 
7.6%
6 130
 
5.7%
) 126
 
5.5%
( 126
 
5.5%
, 126
 
5.5%
- 123
 
5.4%
4 119
 
5.2%
Other values (6) 614
26.8%
Hangul
ValueCountFrequency (%)
동 164
17.1%
지 152
15.8%
외 79
 
8.2%
번 77
 
8.0%
필 74
 
7.7%
원 67
 
7.0%
종 36
 
3.8%
안 27
 
2.8%
괴 27
 
2.8%
고 25
 
2.6%
Other values (31) 231
24.1%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

세대수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct109
Distinct (%)75.2%
Missing19
Missing (%)11.6%
Infinite0
Infinite (%)0.0%
Mean186.66897
Minimum29
Maximum2291
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T00:56:05.894324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile46.4
Q177
median116
Q3195
95-th percentile424.2
Maximum2291
Range2262
Interquartile range (IQR)118

Descriptive statistics

Standard deviation284.46729
Coefficient of variation (CV)1.5239131
Kurtosis30.795572
Mean186.66897
Median Absolute Deviation (MAD)54
Skewness5.2280943
Sum27067
Variance80921.64
MonotonicityNot monotonic
2023-12-13T00:56:06.043806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
130 3
 
1.8%
100 3
 
1.8%
92 3
 
1.8%
108 3
 
1.8%
72 3
 
1.8%
136 2
 
1.2%
89 2
 
1.2%
48 2
 
1.2%
79 2
 
1.2%
164 2
 
1.2%
Other values (99) 120
73.2%
(Missing) 19
 
11.6%
ValueCountFrequency (%)
29 1
0.6%
30 1
0.6%
33 1
0.6%
42 2
1.2%
45 2
1.2%
46 1
0.6%
48 2
1.2%
49 2
1.2%
50 2
1.2%
54 1
0.6%
ValueCountFrequency (%)
2291 1
0.6%
1728 1
0.6%
1649 1
0.6%
1045 1
0.6%
759 1
0.6%
748 1
0.6%
602 1
0.6%
441 1
0.6%
357 1
0.6%
334 1
0.6%

건축계획 동수_층수
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
56 
1동
49 
2동
20 
4동
6 
3동
 
5
Other values (24)
28 

Length

Max length7
Median length6.5
Mean length3.304878
Min length2

Unique

Unique21 ?
Unique (%)12.8%

Sample

1st row6동/35층
2nd row13동/38층
3rd row6동/28층
4th row5동/46층
5th row4동/36층

Common Values

ValueCountFrequency (%)
<NA> 56
34.1%
1동 49
29.9%
2동 20
 
12.2%
4동 6
 
3.7%
3동 5
 
3.0%
1동/15층 3
 
1.8%
2동/15층 2
 
1.2%
3동/17층 2
 
1.2%
22동/28층 1
 
0.6%
13동/38층 1
 
0.6%
Other values (19) 19
 
11.6%

Length

2023-12-13T00:56:06.194403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 56
34.1%
1동 49
29.9%
2동 20
 
12.2%
4동 6
 
3.7%
3동 5
 
3.0%
1동/15층 3
 
1.8%
2동/15층 2
 
1.2%
3동/17층 2
 
1.2%
1동/20층 1
 
0.6%
1동/13층 1
 
0.6%
Other values (19) 19
 
11.6%

건축계획 건폐율
Text

MISSING 

Distinct65
Distinct (%)97.0%
Missing97
Missing (%)59.1%
Memory size1.4 KiB
2023-12-13T00:56:06.522501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.6567164
Min length2

Characters and Unicode

Total characters312
Distinct characters13
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

Unique63 ?
Unique (%)94.0%

Sample

1st row22.68
2nd row17.9
3rd row24.98
4th row29.2
5th row60
ValueCountFrequency (%)
35.45 2
 
3.0%
28.75 2
 
3.0%
56.69 1
 
1.5%
36.85 1
 
1.5%
28.1 1
 
1.5%
35.36 1
 
1.5%
36.06 1
 
1.5%
41.58 1
 
1.5%
26.63 1
 
1.5%
34.08 1
 
1.5%
Other values (55) 55
82.1%
2023-12-13T00:56:06.994365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 62
19.9%
2 41
13.1%
3 37
11.9%
5 28
9.0%
4 28
9.0%
6 28
9.0%
8 23
 
7.4%
9 19
 
6.1%
7 17
 
5.4%
1 15
 
4.8%
Other values (3) 14
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 248
79.5%
Other Punctuation 62
 
19.9%
Other Letter 2
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 41
16.5%
3 37
14.9%
5 28
11.3%
4 28
11.3%
6 28
11.3%
8 23
9.3%
9 19
7.7%
7 17
6.9%
1 15
 
6.0%
0 12
 
4.8%
Other Letter
ValueCountFrequency (%)
이 1
50.0%
하 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 310
99.4%
Hangul 2
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
. 62
20.0%
2 41
13.2%
3 37
11.9%
5 28
9.0%
4 28
9.0%
6 28
9.0%
8 23
 
7.4%
9 19
 
6.1%
7 17
 
5.5%
1 15
 
4.8%
Hangul
ValueCountFrequency (%)
이 1
50.0%
하 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 310
99.4%
Hangul 2
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 62
20.0%
2 41
13.2%
3 37
11.9%
5 28
9.0%
4 28
9.0%
6 28
9.0%
8 23
 
7.4%
9 19
 
6.1%
7 17
 
5.5%
1 15
 
4.8%
Hangul
ValueCountFrequency (%)
이 1
50.0%
하 1
50.0%

건축계획 용적률
Text

MISSING 

Distinct58
Distinct (%)86.6%
Missing97
Missing (%)59.1%
Memory size1.4 KiB
2023-12-13T00:56:07.277910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length6
Mean length5.8507463
Min length3

Characters and Unicode

Total characters392
Distinct characters24
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

Unique52 ?
Unique (%)77.6%

Sample

1st row273.77
2nd row287.64
3rd row316.97
4th row765.8
5th row400(300)주거부분계획용적률
ValueCountFrequency (%)
249.97 4
 
6.0%
249.51 3
 
4.5%
249.95 2
 
3.0%
224.34 2
 
3.0%
249.94 2
 
3.0%
249.7 2
 
3.0%
249.31 1
 
1.5%
248.24 1
 
1.5%
249.89 1
 
1.5%
248.92 1
 
1.5%
Other values (48) 48
71.6%
2023-12-13T00:56:07.749128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 82
20.9%
9 68
17.3%
. 62
15.8%
4 57
14.5%
3 23
 
5.9%
8 20
 
5.1%
7 17
 
4.3%
1 14
 
3.6%
5 13
 
3.3%
6 12
 
3.1%
Other values (14) 24
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 317
80.9%
Other Punctuation 62
 
15.8%
Other Letter 11
 
2.8%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
적 1
9.1%
부 1
9.1%
용 1
9.1%
획 1
9.1%
계 1
9.1%
분 1
9.1%
하 1
9.1%
거 1
9.1%
주 1
9.1%
이 1
9.1%
Decimal Number
ValueCountFrequency (%)
2 82
25.9%
9 68
21.5%
4 57
18.0%
3 23
 
7.3%
8 20
 
6.3%
7 17
 
5.4%
1 14
 
4.4%
5 13
 
4.1%
6 12
 
3.8%
0 11
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 381
97.2%
Hangul 11
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 82
21.5%
9 68
17.8%
. 62
16.3%
4 57
15.0%
3 23
 
6.0%
8 20
 
5.2%
7 17
 
4.5%
1 14
 
3.7%
5 13
 
3.4%
6 12
 
3.1%
Other values (3) 13
 
3.4%
Hangul
ValueCountFrequency (%)
적 1
9.1%
부 1
9.1%
용 1
9.1%
획 1
9.1%
계 1
9.1%
분 1
9.1%
하 1
9.1%
거 1
9.1%
주 1
9.1%
이 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 381
97.2%
Hangul 11
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 82
21.5%
9 68
17.8%
. 62
16.3%
4 57
15.0%
3 23
 
6.0%
8 20
 
5.2%
7 17
 
4.5%
1 14
 
3.7%
5 13
 
3.4%
6 12
 
3.1%
Other values (3) 13
 
3.4%
Hangul
ValueCountFrequency (%)
적 1
9.1%
부 1
9.1%
용 1
9.1%
획 1
9.1%
계 1
9.1%
분 1
9.1%
하 1
9.1%
거 1
9.1%
주 1
9.1%
이 1
9.1%

조합설립인가일자
Text

MISSING 

Distinct133
Distinct (%)93.7%
Missing22
Missing (%)13.4%
Memory size1.4 KiB
2023-12-13T00:56:08.061434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length10
Mean length13.626761
Min length10

Characters and Unicode

Total characters1935
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)88.0%

Sample

1st row2011-04-06(2021-04-28)
2nd row2008-09-24(2021-08-18)
3rd row2011-06-21(2021-11-19)
4th row2009-08-24(2021-06-10)
5th row2011-10-27(2021-01-27)
ValueCountFrequency (%)
2021-08-30 3
 
2.1%
2021-06-17 2
 
1.4%
2021-06-09 2
 
1.4%
2022-04-21 2
 
1.4%
2022-04-06 2
 
1.4%
2020-11-17 2
 
1.4%
2022-06-16 2
 
1.4%
2022-07-08 2
 
1.4%
2022-01-13 1
 
0.7%
2021-12-31 1
 
0.7%
Other values (123) 123
86.6%
2023-12-13T00:56:08.970065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 458
23.7%
2 441
22.8%
- 370
19.1%
1 267
13.8%
9 62
 
3.2%
8 54
 
2.8%
3 46
 
2.4%
6 45
 
2.3%
( 43
 
2.2%
) 43
 
2.2%
Other values (3) 106
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1479
76.4%
Dash Punctuation 370
 
19.1%
Open Punctuation 43
 
2.2%
Close Punctuation 43
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 458
31.0%
2 441
29.8%
1 267
18.1%
9 62
 
4.2%
8 54
 
3.7%
3 46
 
3.1%
6 45
 
3.0%
4 41
 
2.8%
7 40
 
2.7%
5 25
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 370
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1935
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 458
23.7%
2 441
22.8%
- 370
19.1%
1 267
13.8%
9 62
 
3.2%
8 54
 
2.8%
3 46
 
2.4%
6 45
 
2.3%
( 43
 
2.2%
) 43
 
2.2%
Other values (3) 106
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1935
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 458
23.7%
2 441
22.8%
- 370
19.1%
1 267
13.8%
9 62
 
3.2%
8 54
 
2.8%
3 46
 
2.4%
6 45
 
2.3%
( 43
 
2.2%
) 43
 
2.2%
Other values (3) 106
 
5.5%

진행단계
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
조합설립인가
87 
사업시행계획인가
27 
정비예정구역
15 
착공
 
6
준공인가
 
6
Other values (20)
23 

Length

Max length71
Median length6
Mean length8.8536585
Min length2

Unique

Unique18 ?
Unique (%)11.0%

Sample

1st row관리처분인가
2nd row관리처분인가
3rd row사업시행인가(조합설립무효확인 소송, 민원처리불가 처분취소 소송)
4th row사업시행인가(2022-06-21감정평가 업체선정)
5th row정비구역 해제처분 소송중(2021-08-02 정비구역 해제 고시/2022-01-19 정비구역등 해제 고시 효력정지 결정 공고)

Common Values

ValueCountFrequency (%)
조합설립인가 87
53.0%
사업시행계획인가 27
 
16.5%
정비예정구역 15
 
9.1%
착공 6
 
3.7%
준공인가 6
 
3.7%
관리처분인가 3
 
1.8%
정비예정구역(안전진단 실시 결과-유지보수,2018-08-09) 2
 
1.2%
사업시행인가(조합설립무효확인 소송, 민원처리불가 처분취소 소송) 1
 
0.6%
사업시행인가(2022-06-21감정평가 업체선정) 1
 
0.6%
정비구역 해제처분 소송중(2021-08-02 정비구역 해제 고시/2022-01-19 정비구역등 해제 고시 효력정지 결정 공고) 1
 
0.6%
Other values (15) 15
 
9.1%

Length

2023-12-13T00:56:09.693019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조합설립인가 87
41.2%
사업시행계획인가 27
 
12.8%
정비예정구역 15
 
7.1%
착공 6
 
2.8%
준공인가 6
 
2.8%
실시 5
 
2.4%
정비구역 5
 
2.4%
정비예정구역(안전진단 4
 
1.9%
관리처분인가 3
 
1.4%
조합해산 3
 
1.4%
Other values (39) 50
23.7%

Interactions

2023-12-13T00:56:02.295766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:56:09.943322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정비 유형세대수건축계획 동수_층수건축계획 건폐율건축계획 용적률진행단계
정비 유형1.0000.7541.0001.0000.9780.925
세대수0.7541.0000.9991.0001.0000.977
건축계획 동수_층수1.0000.9991.0000.9990.9540.965
건축계획 건폐율1.0001.0000.9991.0000.9960.928
건축계획 용적률0.9781.0000.9540.9961.0000.900
진행단계0.9250.9770.9650.9280.9001.000
2023-12-13T00:56:10.256334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축계획 동수_층수진행단계정비 유형
건축계획 동수_층수1.0000.6660.877
진행단계0.6661.0000.721
정비 유형0.8770.7211.000
2023-12-13T00:56:10.474706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수정비 유형건축계획 동수_층수진행단계
세대수1.0000.6280.8470.742
정비 유형0.6281.0000.8770.721
건축계획 동수_층수0.8470.8771.0000.666
진행단계0.7420.7210.6661.000

Missing values

2023-12-13T00:56:02.461847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:56:02.639126image/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.
2023-12-13T00:56:02.819829image/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

정비 유형구역명조합연락처 및 조합주소정비구역위치 및 면적(제곱미터)세대수건축계획 동수_층수건축계획 건폐율건축계획 용적률조합설립인가일자진행단계
0재개발괴안3D구역재개발032-342-5156 / 경인로 536번길 57, 5층괴안동 201번지 일원(38,322.5)7596동/35층22.68273.772011-04-06(2021-04-28)관리처분인가
1재개발소사3구역 재개발032-344-5834 / 부흥로 487소사동 48-21번지 일원(76,081.0)164913동/38층17.9287.642008-09-24(2021-08-18)관리처분인가
2재개발소사1-1구역재개발032-347-3551 / 부일로 509, 5층소사동 8-5번지 일원(25,880.9)7486동/28층24.98316.972011-06-21(2021-11-19)사업시행인가(조합설립무효확인 소송, 민원처리불가 처분취소 소송)
3재개발소사본1-1구역재개발032-345-0744 / 부천시 소삼로 2, 2층소사본동 88-39번지 일원(45,429.0)17285동/46층29.2765.82009-08-24(2021-06-10)사업시행인가(2022-06-21감정평가 업체선정)
4재개발괴안2D구역 재개발032-351-1921 / 경인로 553, 2층괴안동 189번지 일원(25,876.6)6024동/36층60400(300)주거부분계획용적률2011-10-27(2021-01-27)정비구역 해제처분 소송중(2021-08-02 정비구역 해제 고시/2022-01-19 정비구역등 해제 고시 효력정지 결정 공고)
5재개발심곡3-1구역재개발<NA>심곡동 194번지 일원(4,413.2)3341동/39층65993.2<NA>정비구역지정(2021-11-22 정비구역 해제기한 연장 고시)
6재개발도당1-1구역재개발032-675-5285 / 부천로 261, 3층도당동 263번지 일원(137,022.8)229122동/28층17.4251.92009-02-27(2023-01-16)정비구역 해제처분 소송중(2019-05-20 정비구역 해제 고시 /2022-02-07 1심판결에 따른 효력정지 결정 연장 공고)
7재건축송내1-1구역재건축032-664-5101(664-5103) / 송내대로 30번길 82, 4층송내1동 338(42,613.5)104512동/21층40이하2682017-03-14(2019-07-15)관리처분인가
8재건축성곡2-1구역재건축032-674-0361 / 까치로 124번길 50 미성아파트 관리사무소원종동 352(17,396)357<NA>40230이하2019-05-08조합설립인가
9재건축역곡1-2구역(일두아파트)032-346-3310(345-1747)역곡동 75-3(16,940)441<NA><NA><NA><NA>장기간 추진 지연
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