Overview

Dataset statistics

Number of variables13
Number of observations108
Missing cells756
Missing cells (%)53.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.9 KiB
Average record size in memory113.2 B

Variable types

Categorical3
Text2
Numeric1
Unsupported7

Dataset

Description인천광역시 도시환경 정비사업 현황(구별,구역명,위치, 면적(제곱미터),사업유형 등)에 대한 정보입니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15055212&srcSe=7661IVAWM27C61E190

Alerts

사업유형 is highly overall correlated with 진행단계High correlation
진행단계 is highly overall correlated with 사업유형High correlation
Unnamed: 6 has 108 (100.0%) missing valuesMissing
Unnamed: 7 has 108 (100.0%) missing valuesMissing
Unnamed: 8 has 108 (100.0%) missing valuesMissing
Unnamed: 9 has 108 (100.0%) missing valuesMissing
Unnamed: 10 has 108 (100.0%) missing valuesMissing
Unnamed: 11 has 108 (100.0%) missing valuesMissing
Unnamed: 12 has 108 (100.0%) missing valuesMissing
구 역 명 has unique valuesUnique
면적(제곱미터) has unique valuesUnique
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-14 03:11:58.274022
Analysis finished2024-04-14 03:11:58.774639
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구명
Categorical

Distinct9
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size996.0 B
부평구
34 
미추홀구
24 
동구
16 
계양구
9 
남동구
8 
Other values (4)
17 

Length

Max length4
Median length3
Mean length2.9537037
Min length2

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
부평구 34
31.5%
미추홀구 24
22.2%
동구 16
14.8%
계양구 9
 
8.3%
남동구 8
 
7.4%
중구 7
 
6.5%
서구 6
 
5.6%
연수구 3
 
2.8%
강화군 1
 
0.9%

Length

2024-04-14T12:11:58.845893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T12:11:58.963667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부평구 34
31.5%
미추홀구 24
22.2%
동구 16
14.8%
계양구 9
 
8.3%
남동구 8
 
7.4%
중구 7
 
6.5%
서구 6
 
5.6%
연수구 3
 
2.8%
강화군 1
 
0.9%

구 역 명
Text

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-04-14T12:11:59.187685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.287037
Min length2

Characters and Unicode

Total characters463
Distinct characters136
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

Unique108 ?
Unique (%)100.0%

Sample

1st row경동율목
2nd row송월
3rd row송월아파트
4th row경동
5th row인천여상주변
ValueCountFrequency (%)
경동율목 1
 
0.9%
송월 1
 
0.9%
신촌 1
 
0.9%
삼산1 1
 
0.9%
산곡 1
 
0.9%
부평아파트 1
 
0.9%
청천2 1
 
0.9%
청천1 1
 
0.9%
십정5 1
 
0.9%
십정4 1
 
0.9%
Other values (100) 100
90.9%
2024-04-14T12:11:59.521286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 16
 
3.5%
1 14
 
3.0%
산 14
 
3.0%
주 14
 
3.0%
송 12
 
2.6%
마 11
 
2.4%
부 11
 
2.4%
동 11
 
2.4%
2 11
 
2.4%
4 10
 
2.2%
Other values (126) 339
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 379
81.9%
Decimal Number 56
 
12.1%
Uppercase Letter 16
 
3.5%
Open Punctuation 3
 
0.6%
Close Punctuation 3
 
0.6%
Dash Punctuation 2
 
0.4%
Other Punctuation 2
 
0.4%
Space Separator 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 14
 
3.7%
주 14
 
3.7%
송 12
 
3.2%
마 11
 
2.9%
부 11
 
2.9%
동 11
 
2.9%
을 9
 
2.4%
곡 9
 
2.4%
남 8
 
2.1%
변 7
 
1.8%
Other values (111) 273
72.0%
Decimal Number
ValueCountFrequency (%)
1 14
25.0%
2 11
19.6%
4 10
17.9%
3 10
17.9%
5 6
10.7%
6 2
 
3.6%
9 1
 
1.8%
7 1
 
1.8%
0 1
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
A 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 379
81.9%
Common 68
 
14.7%
Latin 16
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 14
 
3.7%
주 14
 
3.7%
송 12
 
3.2%
마 11
 
2.9%
부 11
 
2.9%
동 11
 
2.9%
을 9
 
2.4%
곡 9
 
2.4%
남 8
 
2.1%
변 7
 
1.8%
Other values (111) 273
72.0%
Common
ValueCountFrequency (%)
1 14
20.6%
2 11
16.2%
4 10
14.7%
3 10
14.7%
5 6
8.8%
( 3
 
4.4%
) 3
 
4.4%
- 2
 
2.9%
, 2
 
2.9%
6 2
 
2.9%
Other values (4) 5
 
7.4%
Latin
ValueCountFrequency (%)
A 16
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 379
81.9%
ASCII 84
 
18.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 16
19.0%
1 14
16.7%
2 11
13.1%
4 10
11.9%
3 10
11.9%
5 6
 
7.1%
( 3
 
3.6%
) 3
 
3.6%
- 2
 
2.4%
, 2
 
2.4%
Other values (5) 7
8.3%
Hangul
ValueCountFrequency (%)
산 14
 
3.7%
주 14
 
3.7%
송 12
 
3.2%
마 11
 
2.9%
부 11
 
2.9%
동 11
 
2.9%
을 9
 
2.4%
곡 9
 
2.4%
남 8
 
2.1%
변 7
 
1.8%
Other values (111) 273
72.0%

위치
Text

Distinct107
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-04-14T12:11:59.732100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length21
Mean length13.814815
Min length10

Characters and Unicode

Total characters1492
Distinct characters97
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

Unique106 ?
Unique (%)98.1%

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 101
30.1%
산곡동 8
 
2.4%
송림동 8
 
2.4%
십정동 6
 
1.8%
주안동 6
 
1.8%
도화동 4
 
1.2%
효성동 4
 
1.2%
부평동 4
 
1.2%
작전동 4
 
1.2%
숭의동 4
 
1.2%
Other values (169) 186
55.5%
2024-04-14T12:12:00.036657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
227
15.2%
원 105
 
7.0%
번 104
 
7.0%
일 103
 
6.9%
동 101
 
6.8%
지 98
 
6.6%
1 89
 
6.0%
- 69
 
4.6%
3 50
 
3.4%
2 50
 
3.4%
Other values (87) 496
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 764
51.2%
Decimal Number 425
28.5%
Space Separator 227
 
15.2%
Dash Punctuation 69
 
4.6%
Other Punctuation 3
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 105
13.7%
번 104
13.6%
일 103
13.5%
동 101
13.2%
지 98
12.8%
산 14
 
1.8%
송 14
 
1.8%
부 12
 
1.6%
로 10
 
1.3%
림 9
 
1.2%
Other values (71) 194
25.4%
Decimal Number
ValueCountFrequency (%)
1 89
20.9%
3 50
11.8%
2 50
11.8%
4 40
9.4%
6 37
8.7%
0 36
8.5%
5 35
 
8.2%
7 31
 
7.3%
8 30
 
7.1%
9 27
 
6.4%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
: 1
33.3%
Space Separator
ValueCountFrequency (%)
227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 764
51.2%
Common 728
48.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 105
13.7%
번 104
13.6%
일 103
13.5%
동 101
13.2%
지 98
12.8%
산 14
 
1.8%
송 14
 
1.8%
부 12
 
1.6%
로 10
 
1.3%
림 9
 
1.2%
Other values (71) 194
25.4%
Common
ValueCountFrequency (%)
227
31.2%
1 89
 
12.2%
- 69
 
9.5%
3 50
 
6.9%
2 50
 
6.9%
4 40
 
5.5%
6 37
 
5.1%
0 36
 
4.9%
5 35
 
4.8%
7 31
 
4.3%
Other values (6) 64
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 764
51.2%
ASCII 728
48.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
227
31.2%
1 89
 
12.2%
- 69
 
9.5%
3 50
 
6.9%
2 50
 
6.9%
4 40
 
5.5%
6 37
 
5.1%
0 36
 
4.9%
5 35
 
4.8%
7 31
 
4.3%
Other values (6) 64
 
8.8%
Hangul
ValueCountFrequency (%)
원 105
13.7%
번 104
13.6%
일 103
13.5%
동 101
13.2%
지 98
12.8%
산 14
 
1.8%
송 14
 
1.8%
부 12
 
1.6%
로 10
 
1.3%
림 9
 
1.2%
Other values (71) 194
25.4%

면적(제곱미터)
Real number (ℝ)

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57644.25
Minimum2785
Maximum228810
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-14T12:12:00.147060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2785
5-th percentile12169.6
Q124497.75
median45277
Q373754.25
95-th percentile159529.7
Maximum228810
Range226025
Interquartile range (IQR)49256.5

Descriptive statistics

Standard deviation47387.906
Coefficient of variation (CV)0.82207516
Kurtosis3.3787464
Mean57644.25
Median Absolute Deviation (MAD)23870
Skewness1.7802213
Sum6225579
Variance2.2456136 × 109
MonotonicityNot monotonic
2024-04-14T12:12:00.250517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34218 1
 
0.9%
39382 1
 
0.9%
117300 1
 
0.9%
66689 1
 
0.9%
93662 1
 
0.9%
33054 1
 
0.9%
115976 1
 
0.9%
11947 1
 
0.9%
219135 1
 
0.9%
74925 1
 
0.9%
Other values (98) 98
90.7%
ValueCountFrequency (%)
2785 1
0.9%
8548 1
0.9%
10146 1
0.9%
11008 1
0.9%
11261 1
0.9%
11947 1
0.9%
12583 1
0.9%
13109 1
0.9%
13768 1
0.9%
13969 1
0.9%
ValueCountFrequency (%)
228810 1
0.9%
223175 1
0.9%
219135 1
0.9%
193385 1
0.9%
180998 1
0.9%
162623 1
0.9%
153785 1
0.9%
137852 1
0.9%
123550 1
0.9%
122433 1
0.9%

사업유형
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size996.0 B
재개발
58 
주거환경개선(현지개량)
17 
재건축
16 
정비구역지정(후보지)
10 
주거환경개선(전면개량)
6 

Length

Max length12
Median length3
Mean length5.7407407
Min length3

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
재개발 58
53.7%
주거환경개선(현지개량) 17
 
15.7%
재건축 16
 
14.8%
정비구역지정(후보지) 10
 
9.3%
주거환경개선(전면개량) 6
 
5.6%
정비구역지정(현지개량) 1
 
0.9%

Length

2024-04-14T12:12:00.351490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T12:12:00.449482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재개발 58
53.7%
주거환경개선(현지개량 17
 
15.7%
재건축 16
 
14.8%
정비구역지정(후보지 10
 
9.3%
주거환경개선(전면개량 6
 
5.6%
정비구역지정(현지개량 1
 
0.9%

진행단계
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size996.0 B
착공
39 
관리처분계획인가
17 
준공 등
17 
조합설립인가
15 
정비구역지정(후보지)
10 
Other values (2)
10 

Length

Max length11
Median length8
Mean length5.1666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
착공 39
36.1%
관리처분계획인가 17
15.7%
준공 등 17
15.7%
조합설립인가 15
 
13.9%
정비구역지정(후보지) 10
 
9.3%
사업시행계획인가 8
 
7.4%
정비구역지정 2
 
1.9%

Length

2024-04-14T12:12:00.564421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T12:12:00.658139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
착공 39
31.2%
관리처분계획인가 17
13.6%
준공 17
13.6%
등 17
13.6%
조합설립인가 15
 
12.0%
정비구역지정(후보지 10
 
8.0%
사업시행계획인가 8
 
6.4%
정비구역지정 2
 
1.6%

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing108
Missing (%)100.0%
Memory size1.1 KiB

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing108
Missing (%)100.0%
Memory size1.1 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing108
Missing (%)100.0%
Memory size1.1 KiB

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing108
Missing (%)100.0%
Memory size1.1 KiB

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing108
Missing (%)100.0%
Memory size1.1 KiB

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing108
Missing (%)100.0%
Memory size1.1 KiB

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing108
Missing (%)100.0%
Memory size1.1 KiB

Interactions

2024-04-14T12:11:58.515518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-14T12:12:00.722434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구명면적(제곱미터)사업유형진행단계
구명1.0000.1910.3310.290
면적(제곱미터)0.1911.0000.3800.000
사업유형0.3310.3801.0000.766
진행단계0.2900.0000.7661.000
2024-04-14T12:12:00.792307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진행단계구명사업유형
진행단계1.0000.1530.587
구명0.1531.0000.167
사업유형0.5870.1671.000
2024-04-14T12:12:00.865356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(제곱미터)구명사업유형진행단계
면적(제곱미터)1.0000.0850.1970.000
구명0.0851.0000.1670.153
사업유형0.1970.1671.0000.587
진행단계0.0000.1530.5871.000

Missing values

2024-04-14T12:11:58.601224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-14T12:11:58.727037image/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

구명구 역 명위치면적(제곱미터)사업유형진행단계Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
0중구경동율목경동 40번지 및 율목동 10번지 일원34218재개발조합설립인가<NA><NA><NA><NA><NA><NA><NA>
1중구송월송월동1가 12-16번지 일원(당초 : 송월동 11번지 일원)27338재개발조합설립인가<NA><NA><NA><NA><NA><NA><NA>
2중구송월아파트송월동1가 10-1번지 일원33683재개발조합설립인가<NA><NA><NA><NA><NA><NA><NA>
3중구경동경동 96-1번지 일원41970재개발조합설립인가<NA><NA><NA><NA><NA><NA><NA>
4중구인천여상주변사동 23-4번지 일원20481재개발관리처분계획인가<NA><NA><NA><NA><NA><NA><NA>
5중구광성고주변(도원)도원동 18-1번지 일원111070정비구역지정(후보지)정비구역지정(후보지)<NA><NA><NA><NA><NA><NA><NA>
6중구전동웃터골중구 전동 32-1번지 일원29933주거환경개선(현지개량)착공<NA><NA><NA><NA><NA><NA><NA>
7동구대헌학교뒤송림동 37-10번지 일원39095주거환경개선(전면개량)착공<NA><NA><NA><NA><NA><NA><NA>
8동구송림4송림동 2, 4번지 일원23915주거환경개선(전면개량)사업시행계획인가<NA><NA><NA><NA><NA><NA><NA>
9동구송림초교주변송림동 185번지 일원72617주거환경개선(전면개량)준공 등<NA><NA><NA><NA><NA><NA><NA>
구명구 역 명위치면적(제곱미터)사업유형진행단계Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
98계양구작전구역작전동 646번지 일원43930주거환경개선(현지개량)착공<NA><NA><NA><NA><NA><NA><NA>
99계양구계산역남측계산동 951-6번지 일원27597정비구역지정(후보지)정비구역지정(후보지)<NA><NA><NA><NA><NA><NA><NA>
100계양구효성효성동 273-1번지 일원23316정비구역지정(후보지)정비구역지정(후보지)<NA><NA><NA><NA><NA><NA><NA>
101서구가좌라이프빌라가좌동 344번지 일원53855재건축착공<NA><NA><NA><NA><NA><NA><NA>
102서구가좌진주1차A가좡동 30-2번지21484재건축조합설립인가<NA><NA><NA><NA><NA><NA><NA>
103서구롯데우람A석남동 491-3번지 일원15244재건축착공<NA><NA><NA><NA><NA><NA><NA>
104서구가좌3구역원적로 47번길 일원228810주거환경개선(현지개량)착공<NA><NA><NA><NA><NA><NA><NA>
105서구신현원마을새오개로 48번길 일원55000주거환경개선(현지개량)착공<NA><NA><NA><NA><NA><NA><NA>
106서구석남5석남동 573-36번지 일원53349정비구역지정(후보지)정비구역지정(후보지)<NA><NA><NA><NA><NA><NA><NA>
107강화군온수리마을길상면 온수리 502-3번지97439주거환경개선(현지개량)착공<NA><NA><NA><NA><NA><NA><NA>