Overview

Dataset statistics

Number of variables10
Number of observations64
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory86.1 B

Variable types

Categorical4
Text2
Numeric4

Dataset

Description인천광역시 추정분담금정보시스템 등록된 조합에 대한 토지정보(구명, 구역명칭, 위치,면적,사업유형,추진단계, 사업시행자, 국공유지, 사유지, 토지 필수지(필지), 용도지역 등)에 대한 정보
Author인천광역시
URLhttps://www.data.go.kr/data/15080868/fileData.do

Alerts

면적(제곱미터) is highly overall correlated with 국공유지 and 2 other fieldsHigh correlation
국공유지 is highly overall correlated with 면적(제곱미터) and 2 other fieldsHigh correlation
사유지 is highly overall correlated with 면적(제곱미터) and 2 other fieldsHigh correlation
토지필지수(필지) is highly overall correlated with 면적(제곱미터) and 2 other fieldsHigh correlation
구 역 명 has unique valuesUnique
위치 has unique valuesUnique
면적(제곱미터) has unique valuesUnique
국공유지 has 10 (15.6%) zerosZeros
사유지 has 4 (6.2%) zerosZeros
토지필지수(필지) has 6 (9.4%) zerosZeros

Reproduction

Analysis started2024-04-06 08:09:44.570070
Analysis finished2024-04-06 08:09:48.772688
Duration4.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구별
Categorical

Distinct8
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size644.0 B
부평구
21 
미추홀구
15 
동구
9 
중구
5 
계양구
5 
Other values (3)
9 

Length

Max length4
Median length3.5
Mean length2.96875
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부평구 21
32.8%
미추홀구 15
23.4%
동구 9
14.1%
중구 5
 
7.8%
계양구 5
 
7.8%
남동구 4
 
6.2%
서구 3
 
4.7%
연수구 2
 
3.1%

Length

2024-04-06T17:09:48.945571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:09:49.252882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부평구 21
32.8%
미추홀구 15
23.4%
동구 9
14.1%
중구 5
 
7.8%
계양구 5
 
7.8%
남동구 4
 
6.2%
서구 3
 
4.7%
연수구 2
 
3.1%

구 역 명
Text

UNIQUE 

Distinct64
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-04-06T17:09:49.702056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4
Min length2

Characters and Unicode

Total characters256
Distinct characters102
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)100.0%

Sample

1st row경동율목
2nd row송월
3rd row송월아파트
4th row경동
5th row인천여상주변
ValueCountFrequency (%)
경동율목 1
 
1.6%
송월 1
 
1.6%
산곡 1
 
1.6%
상인천초교주변 1
 
1.6%
갈산1 1
 
1.6%
부평2 1
 
1.6%
부평4 1
 
1.6%
산곡2-1 1
 
1.6%
산곡3 1
 
1.6%
산곡5 1
 
1.6%
Other values (54) 54
84.4%
2024-04-06T17:09:50.432440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 14
 
5.5%
1 11
 
4.3%
송 9
 
3.5%
산 9
 
3.5%
4 8
 
3.1%
주 8
 
3.1%
곡 7
 
2.7%
천 5
 
2.0%
3 5
 
2.0%
림 5
 
2.0%
Other values (92) 175
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 200
78.1%
Decimal Number 37
 
14.5%
Uppercase Letter 14
 
5.5%
Other Punctuation 2
 
0.8%
Dash Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
송 9
 
4.5%
산 9
 
4.5%
주 8
 
4.0%
곡 7
 
3.5%
천 5
 
2.5%
림 5
 
2.5%
대 5
 
2.5%
부 5
 
2.5%
평 4
 
2.0%
진 4
 
2.0%
Other values (79) 139
69.5%
Decimal Number
ValueCountFrequency (%)
1 11
29.7%
4 8
21.6%
3 5
13.5%
2 5
13.5%
5 4
 
10.8%
6 2
 
5.4%
7 1
 
2.7%
0 1
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
A 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 200
78.1%
Common 42
 
16.4%
Latin 14
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
송 9
 
4.5%
산 9
 
4.5%
주 8
 
4.0%
곡 7
 
3.5%
천 5
 
2.5%
림 5
 
2.5%
대 5
 
2.5%
부 5
 
2.5%
평 4
 
2.0%
진 4
 
2.0%
Other values (79) 139
69.5%
Common
ValueCountFrequency (%)
1 11
26.2%
4 8
19.0%
3 5
11.9%
2 5
11.9%
5 4
 
9.5%
, 2
 
4.8%
6 2
 
4.8%
7 1
 
2.4%
- 1
 
2.4%
0 1
 
2.4%
Other values (2) 2
 
4.8%
Latin
ValueCountFrequency (%)
A 14
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 200
78.1%
ASCII 56
 
21.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 14
25.0%
1 11
19.6%
4 8
14.3%
3 5
 
8.9%
2 5
 
8.9%
5 4
 
7.1%
, 2
 
3.6%
6 2
 
3.6%
7 1
 
1.8%
- 1
 
1.8%
Other values (3) 3
 
5.4%
Hangul
ValueCountFrequency (%)
송 9
 
4.5%
산 9
 
4.5%
주 8
 
4.0%
곡 7
 
3.5%
천 5
 
2.5%
림 5
 
2.5%
대 5
 
2.5%
부 5
 
2.5%
평 4
 
2.0%
진 4
 
2.0%
Other values (79) 139
69.5%

위치
Text

UNIQUE 

Distinct64
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-04-06T17:09:50.907871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length24
Mean length14.359375
Min length10

Characters and Unicode

Total characters919
Distinct characters72
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

Unique64 ?
Unique (%)100.0%

Sample

1st row경동 40번지 및 율목동 10번지 일원
2nd row송월동1가 12-16번지 일원(당초 : 송월동 11번지 일원)
3rd row송월동1가 10-1번지 일원
4th row경동 96-1번지 일원
5th row사동 23-4번지 일원
ValueCountFrequency (%)
일원 60
29.7%
송림동 6
 
3.0%
산곡동 6
 
3.0%
주안동 4
 
2.0%
십정동 3
 
1.5%
숭의동 3
 
1.5%
작전동 3
 
1.5%
경동 2
 
1.0%
용현동 2
 
1.0%
가좌동 2
 
1.0%
Other values (102) 111
55.0%
2024-04-06T17:09:51.641623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
138
15.0%
동 67
 
7.3%
번 66
 
7.2%
지 65
 
7.1%
원 62
 
6.7%
일 62
 
6.7%
1 62
 
6.7%
- 45
 
4.9%
2 31
 
3.4%
3 28
 
3.0%
Other values (62) 293
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 466
50.7%
Decimal Number 262
28.5%
Space Separator 138
 
15.0%
Dash Punctuation 45
 
4.9%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 67
14.4%
번 66
14.2%
지 65
13.9%
원 62
13.3%
일 62
13.3%
송 11
 
2.4%
산 9
 
1.9%
림 7
 
1.5%
곡 7
 
1.5%
부 6
 
1.3%
Other values (44) 104
22.3%
Decimal Number
ValueCountFrequency (%)
1 62
23.7%
2 31
11.8%
3 28
10.7%
0 25
9.5%
4 23
 
8.8%
6 23
 
8.8%
5 20
 
7.6%
9 19
 
7.3%
8 16
 
6.1%
7 15
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
138
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 466
50.7%
Common 451
49.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 67
14.4%
번 66
14.2%
지 65
13.9%
원 62
13.3%
일 62
13.3%
송 11
 
2.4%
산 9
 
1.9%
림 7
 
1.5%
곡 7
 
1.5%
부 6
 
1.3%
Other values (44) 104
22.3%
Common
ValueCountFrequency (%)
138
30.6%
1 62
13.7%
- 45
 
10.0%
2 31
 
6.9%
3 28
 
6.2%
0 25
 
5.5%
4 23
 
5.1%
6 23
 
5.1%
5 20
 
4.4%
9 19
 
4.2%
Other values (6) 37
 
8.2%
Latin
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 466
50.7%
ASCII 453
49.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
138
30.5%
1 62
13.7%
- 45
 
9.9%
2 31
 
6.8%
3 28
 
6.2%
0 25
 
5.5%
4 23
 
5.1%
6 23
 
5.1%
5 20
 
4.4%
9 19
 
4.2%
Other values (8) 39
 
8.6%
Hangul
ValueCountFrequency (%)
동 67
14.4%
번 66
14.2%
지 65
13.9%
원 62
13.3%
일 62
13.3%
송 11
 
2.4%
산 9
 
1.9%
림 7
 
1.5%
곡 7
 
1.5%
부 6
 
1.3%
Other values (44) 104
22.3%

면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct64
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60854.604
Minimum8548
Maximum223175.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2024-04-06T17:09:51.921061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8548
5-th percentile11263.63
Q123307.362
median48981.15
Q381175.15
95-th percentile161297.54
Maximum223175.2
Range214627.2
Interquartile range (IQR)57867.788

Descriptive statistics

Standard deviation49830.346
Coefficient of variation (CV)0.81884266
Kurtosis2.1836745
Mean60854.604
Median Absolute Deviation (MAD)28306.2
Skewness1.5131865
Sum3894694.6
Variance2.4830633 × 109
MonotonicityNot monotonic
2024-04-06T17:09:52.226144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34218.0 1
 
1.6%
32366.5 1
 
1.6%
50415.9 1
 
1.6%
59954.0 1
 
1.6%
80720.2 1
 
1.6%
58457.1 1
 
1.6%
26195.0 1
 
1.6%
88025.5 1
 
1.6%
34552.0 1
 
1.6%
45191.1 1
 
1.6%
Other values (54) 54
84.4%
ValueCountFrequency (%)
8548.0 1
1.6%
10146.1 1
1.6%
11007.5 1
1.6%
11143.0 1
1.6%
11947.2 1
1.6%
14512.1 1
1.6%
15034.0 1
1.6%
15244.0 1
1.6%
15402.8 1
1.6%
17713.0 1
1.6%
ValueCountFrequency (%)
223175.2 1
1.6%
219169.5 1
1.6%
180998.0 1
1.6%
162623.3 1
1.6%
153784.9 1
1.6%
137852.1 1
1.6%
123549.7 1
1.6%
122432.5 1
1.6%
117300.0 1
1.6%
115976.4 1
1.6%

사업유형
Categorical

Distinct3
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size644.0 B
재개발
47 
재건축
14 
주거환경개선(전면개량)
 
3

Length

Max length12
Median length3
Mean length3.421875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재개발 47
73.4%
재건축 14
 
21.9%
주거환경개선(전면개량) 3
 
4.7%

Length

2024-04-06T17:09:52.477084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:09:52.801871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재개발 47
73.4%
재건축 14
 
21.9%
주거환경개선(전면개량 3
 
4.7%

추진단계
Categorical

Distinct5
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size644.0 B
착공
19 
관리처분계획인가
17 
조합설립인가
15 
사업시행계획인가
8 
준공
5 

Length

Max length8
Median length6
Mean length5.28125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조합설립인가
2nd row조합설립인가
3rd row조합설립인가
4th row조합설립인가
5th row관리처분계획인가

Common Values

ValueCountFrequency (%)
착공 19
29.7%
관리처분계획인가 17
26.6%
조합설립인가 15
23.4%
사업시행계획인가 8
12.5%
준공 5
 
7.8%

Length

2024-04-06T17:09:53.069120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:09:53.301353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
착공 19
29.7%
관리처분계획인가 17
26.6%
조합설립인가 15
23.4%
사업시행계획인가 8
12.5%
준공 5
 
7.8%

국공유지
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct55
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10382.804
Minimum0
Maximum64569
Zeros10
Zeros (%)15.6%
Negative0
Negative (%)0.0%
Memory size708.0 B
2024-04-06T17:09:53.552215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12055.875
median7317.15
Q313275.858
95-th percentile26702.68
Maximum64569
Range64569
Interquartile range (IQR)11219.983

Descriptive statistics

Standard deviation11821.787
Coefficient of variation (CV)1.138593
Kurtosis7.5375781
Mean10382.804
Median Absolute Deviation (MAD)5477.74
Skewness2.3688952
Sum664499.44
Variance1.3975465 × 108
MonotonicityNot monotonic
2024-04-06T17:09:53.884518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 10
 
15.6%
10089.4 1
 
1.6%
5788.7 1
 
1.6%
66.0 1
 
1.6%
1786.1 1
 
1.6%
11310.2 1
 
1.6%
5650.0 1
 
1.6%
26801.8 1
 
1.6%
6401.0 1
 
1.6%
10528.0 1
 
1.6%
Other values (45) 45
70.3%
ValueCountFrequency (%)
0.0 10
15.6%
66.0 1
 
1.6%
766.0 1
 
1.6%
970.7 1
 
1.6%
1683.0 1
 
1.6%
1786.1 1
 
1.6%
1954.1 1
 
1.6%
2089.8 1
 
1.6%
2157.1 1
 
1.6%
2781.8 1
 
1.6%
ValueCountFrequency (%)
64569.0 1
1.6%
49041.44 1
1.6%
38945.0 1
1.6%
26801.8 1
1.6%
26141.0 1
1.6%
24567.0 1
1.6%
23565.2 1
1.6%
22846.0 1
1.6%
20031.0 1
1.6%
18762.0 1
1.6%

사유지
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct61
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42968.127
Minimum0
Maximum158606
Zeros4
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size708.0 B
2024-04-06T17:09:54.588857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1252.41
Q117433.75
median29452.95
Q361157
95-th percentile113202.13
Maximum158606
Range158606
Interquartile range (IQR)43723.25

Descriptive statistics

Standard deviation34452.348
Coefficient of variation (CV)0.80181173
Kurtosis1.124417
Mean42968.127
Median Absolute Deviation (MAD)15789.55
Skewness1.1893587
Sum2749960.1
Variance1.1869643 × 109
MonotonicityNot monotonic
2024-04-06T17:09:54.892136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4
 
6.2%
24128.6 1
 
1.6%
89835.4 1
 
1.6%
26879.0 1
 
1.6%
111050.3 1
 
1.6%
43966.0 1
 
1.6%
49426.0 1
 
1.6%
70799.7 1
 
1.6%
47791.0 1
 
1.6%
21307.0 1
 
1.6%
Other values (51) 51
79.7%
ValueCountFrequency (%)
0.0 4
6.2%
8349.4 1
 
1.6%
8482.0 1
 
1.6%
10980.5 1
 
1.6%
11143.0 1
 
1.6%
13053.0 1
 
1.6%
14273.8 1
 
1.6%
14512.1 1
 
1.6%
15034.0 1
 
1.6%
15151.0 1
 
1.6%
ValueCountFrequency (%)
158606.0 1
1.6%
115553.6 1
1.6%
114839.9 1
1.6%
113581.86 1
1.6%
111050.3 1
1.6%
109739.0 1
1.6%
97269.0 1
1.6%
89835.4 1
1.6%
79755.31 1
1.6%
74726.0 1
1.6%

토지필지수(필지)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct55
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean371.70312
Minimum0
Maximum2399
Zeros6
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size708.0 B
2024-04-06T17:09:55.193238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q127.5
median228.5
Q3519
95-th percentile1305.3
Maximum2399
Range2399
Interquartile range (IQR)491.5

Descriptive statistics

Standard deviation457.52927
Coefficient of variation (CV)1.2308997
Kurtosis6.1763156
Mean371.70312
Median Absolute Deviation (MAD)223
Skewness2.2132053
Sum23789
Variance209333.04
MonotonicityNot monotonic
2024-04-06T17:09:55.644588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
9.4%
3 3
 
4.7%
1 2
 
3.1%
594 2
 
3.1%
381 1
 
1.6%
103 1
 
1.6%
89 1
 
1.6%
192 1
 
1.6%
145 1
 
1.6%
589 1
 
1.6%
Other values (45) 45
70.3%
ValueCountFrequency (%)
0 6
9.4%
1 2
 
3.1%
3 3
4.7%
5 1
 
1.6%
6 1
 
1.6%
8 1
 
1.6%
15 1
 
1.6%
20 1
 
1.6%
30 1
 
1.6%
49 1
 
1.6%
ValueCountFrequency (%)
2399 1
1.6%
1630 1
1.6%
1575 1
1.6%
1329 1
1.6%
1171 1
1.6%
1037 1
1.6%
854 1
1.6%
720 1
1.6%
706 1
1.6%
594 2
3.1%

용도지역
Categorical

Distinct13
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Memory size644.0 B
제2종 일반주거지역
21 
제3종 일반주거지역
17 
일반상업지역
6 
준주거지역
6 
제2.3종 일반주거지역
3 
Other values (8)
11 

Length

Max length18
Median length10
Mean length10.296875
Min length5

Unique

Unique5 ?
Unique (%)7.8%

Sample

1st row제2종 일반주거지역, 일반상업지역
2nd row제2종 일반주거지역
3rd row제3종 일반주거지역
4th row일반상업지역
5th row일반상업지역

Common Values

ValueCountFrequency (%)
제2종 일반주거지역 21
32.8%
제3종 일반주거지역 17
26.6%
일반상업지역 6
 
9.4%
준주거지역 6
 
9.4%
제2.3종 일반주거지역 3
 
4.7%
제3종 일반주거지역, 일반상업지역 2
 
3.1%
제2종 일반주거지역, 준주거지역 2
 
3.1%
제1.2종 일반주거지역 2
 
3.1%
제2종 일반주거지역, 일반상업지역 1
 
1.6%
준주거지역, 제2종 일반주거지역 1
 
1.6%
Other values (3) 3
 
4.7%

Length

2024-04-06T17:09:55.887532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반주거지역 51
41.1%
제2종 26
21.0%
제3종 20
 
16.1%
준주거지역 11
 
8.9%
일반상업지역 9
 
7.3%
제2.3종 3
 
2.4%
제1.2종 2
 
1.6%
일반미관지구 1
 
0.8%
자연녹지지역 1
 
0.8%

Interactions

2024-04-06T17:09:47.639179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:45.534432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:46.202418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:46.899070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:47.803432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:45.692212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:46.383164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:47.058452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:47.983954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:45.861270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:46.564503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:47.273108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:48.155056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:46.052499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:46.741671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:47.477500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:09:56.063992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구별구 역 명위치면적(제곱미터)사업유형추진단계국공유지사유지토지필지수(필지)용도지역
구별1.0001.0001.0000.0000.4770.0000.0000.3040.2830.000
구 역 명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위치1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
면적(제곱미터)0.0001.0001.0001.0000.5620.3040.8650.8500.8460.422
사업유형0.4771.0001.0000.5621.0000.2990.5350.7460.5940.689
추진단계0.0001.0001.0000.3040.2991.0000.0990.2540.0000.000
국공유지0.0001.0001.0000.8650.5350.0991.0000.7980.9320.690
사유지0.3041.0001.0000.8500.7460.2540.7981.0000.8320.626
토지필지수(필지)0.2831.0001.0000.8460.5940.0000.9320.8321.0000.635
용도지역0.0001.0001.0000.4220.6890.0000.6900.6260.6351.000
2024-04-06T17:09:56.297046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업유형추진단계구별용도지역
사업유형1.0000.2310.3290.469
추진단계0.2311.0000.0000.000
구별0.3290.0001.0000.000
용도지역0.4690.0000.0001.000
2024-04-06T17:09:56.482479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(제곱미터)국공유지사유지토지필지수(필지)구별사업유형추진단계용도지역
면적(제곱미터)1.0000.7100.7940.6690.0000.3600.0960.182
국공유지0.7101.0000.8480.7840.0000.3820.0400.379
사유지0.7940.8481.0000.8460.1450.4270.1370.312
토지필지수(필지)0.6690.7840.8461.0000.0880.4410.0000.331
구별0.0000.0000.1450.0881.0000.3290.0000.000
사업유형0.3600.3820.4270.4410.3291.0000.2310.469
추진단계0.0960.0400.1370.0000.0000.2311.0000.000
용도지역0.1820.3790.3120.3310.0000.4690.0001.000

Missing values

2024-04-06T17:09:48.373841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:09:48.654836image/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

구별구 역 명위치면적(제곱미터)사업유형추진단계국공유지사유지토지필지수(필지)용도지역
0중구경동율목경동 40번지 및 율목동 10번지 일원34218.0재개발조합설립인가10089.424128.6381제2종 일반주거지역, 일반상업지역
1중구송월송월동1가 12-16번지 일원(당초 : 송월동 11번지 일원)27338.0재개발조합설립인가3893.023445.0354제2종 일반주거지역
2중구송월아파트송월동1가 10-1번지 일원33683.0재개발조합설립인가8274.8725408.13134제3종 일반주거지역
3중구경동경동 96-1번지 일원41970.0재개발조합설립인가11655.230314.8362일반상업지역
4중구인천여상주변사동 23-4번지 일원20481.0재개발관리처분계획인가4306.116174.9186일반상업지역
5동구대헌학교뒤송림동 37-10번지 일원39943.9주거환경개선(전면개량)착공11487.025772.0452준주거지역, 제2종 일반주거지역
6동구송림4송림동 2, 4번지 일원23915.0주거환경개선(전면개량)사업시행계획인가6418.017635.0189준주거지역
7동구금송송림동 80-34 및 창영동 116-1번지 일원162623.3재개발관리처분계획인가49041.44113581.861575제2종 일반주거지역
8동구서림송림동 64-55번지 일원19477.1재개발사업시행계획인가6424.113053.0153제2종 일반주거지역
9동구송림1,2동송림동 160번지 일원153784.9재개발관리처분계획인가38945.0114839.91630제3종 일반주거지역, 일반상업지역
구별구 역 명위치면적(제곱미터)사업유형추진단계국공유지사유지토지필지수(필지)용도지역
54부평구삼산대보A삼산동 191번지 일원18513.0재건축관리처분계획인가1683.016830.03제3종 일반주거지역
55부평구청천대진A청천2동 236번지 일원14512.1재건축조합설립인가0.014512.10제2종 일반주거지역
56계양구계양1작전동 765번지 일원122432.5재개발착공0.00.00제2.3종 일반주거지역
57계양구작전현대A작전동 439-7번지 일원64004.9재개발착공0.00.00제3종 일반주거지역
58계양구작전우영A작전동 869-17번지 일원11007.5재건축사업시행계획인가0.010980.55제2종 일반주거지역
59계양구효성뉴서울A효성동 99-11번지17713.0재건축조합설립인가0.017713.01제3종 일반주거지역
60계양구효성새사미A효성동 623-16번지15034.0재건축조합설립인가0.015034.03제3종 일반주거지역
61서구가좌라이프빌라가좌동 344번지 일원53855.0재건축준공9235.744619.315제3종 일반주거지역
62서구가좌진주1차A가좌동 30-2번지21484.45재건축조합설립인가0.021488.451제3종 일반주거지역
63서구롯데우람A석남동 491-3번지 일원15244.0재건축착공970.714273.88일반상업지역