Overview

Dataset statistics

Number of variables6
Number of observations126
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory50.0 B

Variable types

Categorical3
Text2
Numeric1

Dataset

Description인천광역시 도시환경 정비사업 현황(구별,구역명,위치, 면적(제곱미터),사업유형 등)에 대한 정보입니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15055212/fileData.do

Alerts

사업유형 is highly overall correlated with 진행단계High correlation
진행단계 is highly overall correlated with 사업유형High correlation
구 역 명 has unique valuesUnique
면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:43:00.183447
Analysis finished2024-04-06 08:43:01.722206
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구명
Categorical

Distinct9
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
부평구
31 
미추홀구
28 
남동구
17 
동구
14 
서구
13 
Other values (4)
23 

Length

Max length4
Median length3.5
Mean length2.9444444
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
부평구 31
24.6%
미추홀구 28
22.2%
남동구 17
13.5%
동구 14
11.1%
서구 13
10.3%
계양구 11
 
8.7%
중구 8
 
6.3%
연수구 3
 
2.4%
강화군 1
 
0.8%

Length

2024-04-06T17:43:01.955547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:43:02.319754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부평구 31
24.6%
미추홀구 28
22.2%
남동구 17
13.5%
동구 14
11.1%
서구 13
10.3%
계양구 11
 
8.7%
중구 8
 
6.3%
연수구 3
 
2.4%
강화군 1
 
0.8%

구 역 명
Text

UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T17:43:02.908308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.7539683
Min length2

Characters and Unicode

Total characters599
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

Unique126 ?
Unique (%)100.0%

Sample

1st row경동율목
2nd row송월
3rd row송월아파트
4th row경동
5th row인천여상주변
ValueCountFrequency (%)
경동율목 1
 
0.8%
화수화평 1
 
0.8%
하하골마을 1
 
0.8%
청천대진a 1
 
0.8%
삼산대보a 1
 
0.8%
산곡재원a 1
 
0.8%
산곡7 1
 
0.8%
산곡6 1
 
0.8%
부개5 1
 
0.8%
부개4 1
 
0.8%
Other values (118) 118
92.2%
2024-04-06T17:43:03.897690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
4.7%
17
 
2.8%
15
 
2.5%
1 14
 
2.3%
A 14
 
2.3%
13
 
2.2%
4 12
 
2.0%
3 12
 
2.0%
5 12
 
2.0%
11
 
1.8%
Other values (135) 451
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 493
82.3%
Decimal Number 78
 
13.0%
Uppercase Letter 14
 
2.3%
Dash Punctuation 4
 
0.7%
Open Punctuation 3
 
0.5%
Close Punctuation 3
 
0.5%
Other Punctuation 2
 
0.3%
Space Separator 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
28
 
5.7%
17
 
3.4%
15
 
3.0%
13
 
2.6%
11
 
2.2%
11
 
2.2%
11
 
2.2%
11
 
2.2%
10
 
2.0%
10
 
2.0%
Other values (119) 356
72.2%
Decimal Number
ValueCountFrequency (%)
1 14
17.9%
4 12
15.4%
3 12
15.4%
5 12
15.4%
2 9
11.5%
7 5
 
6.4%
0 5
 
6.4%
8 4
 
5.1%
6 3
 
3.8%
9 2
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
A 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 493
82.3%
Common 92
 
15.4%
Latin 14
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
28
 
5.7%
17
 
3.4%
15
 
3.0%
13
 
2.6%
11
 
2.2%
11
 
2.2%
11
 
2.2%
11
 
2.2%
10
 
2.0%
10
 
2.0%
Other values (119) 356
72.2%
Common
ValueCountFrequency (%)
1 14
15.2%
4 12
13.0%
3 12
13.0%
5 12
13.0%
2 9
9.8%
7 5
 
5.4%
0 5
 
5.4%
8 4
 
4.3%
- 4
 
4.3%
( 3
 
3.3%
Other values (5) 12
13.0%
Latin
ValueCountFrequency (%)
A 14
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 493
82.3%
ASCII 106
 
17.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
28
 
5.7%
17
 
3.4%
15
 
3.0%
13
 
2.6%
11
 
2.2%
11
 
2.2%
11
 
2.2%
11
 
2.2%
10
 
2.0%
10
 
2.0%
Other values (119) 356
72.2%
ASCII
ValueCountFrequency (%)
1 14
13.2%
A 14
13.2%
4 12
11.3%
3 12
11.3%
5 12
11.3%
2 9
8.5%
7 5
 
4.7%
0 5
 
4.7%
8 4
 
3.8%
- 4
 
3.8%
Other values (6) 15
14.2%

위치
Text

Distinct125
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T17:43:04.571651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length24
Mean length13.849206
Min length10

Characters and Unicode

Total characters1745
Distinct characters99
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

Unique124 ?
Unique (%)98.4%

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 120
30.6%
주안동 9
 
2.3%
부평동 7
 
1.8%
송림동 7
 
1.8%
산곡동 6
 
1.5%
십정동 6
 
1.5%
작전동 5
 
1.3%
도화동 5
 
1.3%
간석동 5
 
1.3%
구월동 4
 
1.0%
Other values (188) 218
55.6%
2024-04-06T17:43:05.923837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
266
15.2%
125
 
7.2%
123
 
7.0%
122
 
7.0%
119
 
6.8%
114
 
6.5%
1 108
 
6.2%
- 81
 
4.6%
3 58
 
3.3%
2 53
 
3.0%
Other values (89) 576
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 897
51.4%
Decimal Number 491
28.1%
Space Separator 266
 
15.2%
Dash Punctuation 81
 
4.6%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%
Other Punctuation 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
125
13.9%
123
13.7%
122
13.6%
119
13.3%
114
12.7%
13
 
1.4%
12
 
1.3%
11
 
1.2%
11
 
1.2%
10
 
1.1%
Other values (71) 237
26.4%
Decimal Number
ValueCountFrequency (%)
1 108
22.0%
3 58
11.8%
2 53
10.8%
5 43
 
8.8%
0 43
 
8.8%
4 42
 
8.6%
9 40
 
8.1%
6 39
 
7.9%
7 34
 
6.9%
8 31
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
: 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
266
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 897
51.4%
Common 846
48.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
125
13.9%
123
13.7%
122
13.6%
119
13.3%
114
12.7%
13
 
1.4%
12
 
1.3%
11
 
1.2%
11
 
1.2%
10
 
1.1%
Other values (71) 237
26.4%
Common
ValueCountFrequency (%)
266
31.4%
1 108
12.8%
- 81
 
9.6%
3 58
 
6.9%
2 53
 
6.3%
5 43
 
5.1%
0 43
 
5.1%
4 42
 
5.0%
9 40
 
4.7%
6 39
 
4.6%
Other values (6) 73
 
8.6%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 897
51.4%
ASCII 848
48.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
266
31.4%
1 108
12.7%
- 81
 
9.6%
3 58
 
6.8%
2 53
 
6.2%
5 43
 
5.1%
0 43
 
5.1%
4 42
 
5.0%
9 40
 
4.7%
6 39
 
4.6%
Other values (8) 75
 
8.8%
Hangul
ValueCountFrequency (%)
125
13.9%
123
13.7%
122
13.6%
119
13.3%
114
12.7%
13
 
1.4%
12
 
1.3%
11
 
1.2%
11
 
1.2%
10
 
1.1%
Other values (71) 237
26.4%

면적(제곱미터)
Real number (ℝ)

UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68358.336
Minimum2785
Maximum247803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T17:43:06.384390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2785
5-th percentile13065.275
Q132993.925
median54374.25
Q383603
95-th percentile191514.5
Maximum247803
Range245018
Interquartile range (IQR)50609.075

Descriptive statistics

Standard deviation51745.553
Coefficient of variation (CV)0.75697502
Kurtosis2.2716469
Mean68358.336
Median Absolute Deviation (MAD)26402.75
Skewness1.5193633
Sum8613150.3
Variance2.6776022 × 109
MonotonicityNot monotonic
2024-04-06T17:43:06.847273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34218.0 1
 
0.8%
219169.5 1
 
0.8%
52490.0 1
 
0.8%
38942.0 1
 
0.8%
45363.0 1
 
0.8%
14512.1 1
 
0.8%
18513.0 1
 
0.8%
11143.0 1
 
0.8%
84118.0 1
 
0.8%
123549.7 1
 
0.8%
Other values (116) 116
92.1%
ValueCountFrequency (%)
2785.0 1
0.8%
8548.0 1
0.8%
10146.1 1
0.8%
11007.5 1
0.8%
11143.0 1
0.8%
11947.2 1
0.8%
12583.0 1
0.8%
14512.1 1
0.8%
15034.0 1
0.8%
15108.0 1
0.8%
ValueCountFrequency (%)
247803.0 1
0.8%
228810.0 1
0.8%
223175.2 1
0.8%
220200.0 1
0.8%
219169.5 1
0.8%
205088.0 1
0.8%
195020.0 1
0.8%
180998.0 1
0.8%
162623.3 1
0.8%
153784.9 1
0.8%

사업유형
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
재개발
47 
정비구역지정(후보지 2차)
33 
주거환경개선(현지개량)
19 
재건축
14 
정비구역지정(후보지 1차)
10 

Length

Max length14
Median length12
Mean length8.3253968
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재개발 47
37.3%
정비구역지정(후보지 2차) 33
26.2%
주거환경개선(현지개량) 19
15.1%
재건축 14
 
11.1%
정비구역지정(후보지 1차) 10
 
7.9%
주거환경개선(전면개량) 3
 
2.4%

Length

2024-04-06T17:43:07.454301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:43:07.834420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재개발 47
27.8%
정비구역지정(후보지 43
25.4%
2차 33
19.5%
주거환경개선(현지개량 19
11.2%
재건축 14
 
8.3%
1차 10
 
5.9%
주거환경개선(전면개량 3
 
1.8%

진행단계
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
정비구역지정(후보지 2차)
33 
착공
31 
관리처분계획인가
17 
조합설립인가
15 
사업시행계획인가
11 
Other values (2)
19 

Length

Max length14
Median length8
Mean length7.9047619
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정비구역지정(후보지 2차) 33
26.2%
착공 31
24.6%
관리처분계획인가 17
13.5%
조합설립인가 15
11.9%
사업시행계획인가 11
 
8.7%
정비구역지정(후보지 1차) 10
 
7.9%
준공 9
 
7.1%

Length

2024-04-06T17:43:08.396259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:43:08.802549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정비구역지정(후보지 43
25.4%
2차 33
19.5%
착공 31
18.3%
관리처분계획인가 17
 
10.1%
조합설립인가 15
 
8.9%
사업시행계획인가 11
 
6.5%
1차 10
 
5.9%
준공 9
 
5.3%

Interactions

2024-04-06T17:43:00.940259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:43:09.083313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구명면적(제곱미터)사업유형진행단계
구명1.0000.2980.3340.278
면적(제곱미터)0.2981.0000.4130.276
사업유형0.3340.4131.0000.823
진행단계0.2780.2760.8231.000
2024-04-06T17:43:09.384240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/