Overview

Dataset statistics

Number of variables10
Number of observations106
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.8 KiB
Average record size in memory85.2 B

Variable types

Numeric3
Categorical4
DateTime2
Text1

Dataset

Description인천광역시 중구에서 조사한 개발행위허가현황에 대한 데이터 입니다.파일명 인천광역시_중구_개발행위허가현황파일내용 해당년도, 허가일자, 위치, 용도지역 등
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15036869&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 해당년도High correlation
허가면적(미터제곱) is highly overall correlated with 협의면적(미터제곱)High correlation
협의면적(미터제곱) is highly overall correlated with 허가면적(미터제곱)High correlation
해당년도 is highly overall correlated with 연번High correlation
용도지역 is highly overall correlated with 지목명High correlation
지목명 is highly overall correlated with 용도지역High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 10:45:04.032430
Analysis finished2024-01-28 10:45:05.370765
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct106
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.5
Minimum1
Maximum106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-28T19:45:05.426960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.25
Q127.25
median53.5
Q379.75
95-th percentile100.75
Maximum106
Range105
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation30.743563
Coefficient of variation (CV)0.57464604
Kurtosis-1.2
Mean53.5
Median Absolute Deviation (MAD)26.5
Skewness0
Sum5671
Variance945.16667
MonotonicityStrictly increasing
2024-01-28T19:45:05.559029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
81 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
72 1
 
0.9%
Other values (96) 96
90.6%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%
98 1
0.9%
97 1
0.9%

해당년도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size980.0 B
2022
68 
2021
38 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2022 68
64.2%
2021 38
35.8%

Length

2024-01-28T19:45:05.655438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:45:05.723603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 68
64.2%
2021 38
35.8%

허가일자
Date

Distinct76
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Memory size980.0 B
Minimum2021-09-13 00:00:00
Maximum2022-09-05 00:00:00
2024-01-28T19:45:05.811832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:45:05.939642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

허가위치
Text

Distinct92
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size980.0 B
2024-01-28T19:45:06.129387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length17.698113
Min length14

Characters and Unicode

Total characters1876
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)77.4%

Sample

1st row인천광역시 중구 항동7가112-10
2nd row인천광역시 중구 항동7가1-68
3rd row인천광역시 중구 항동7가112-10
4th row인천광역시 중구 항동7가1-31
5th row인천광역시 중구 북성동1가125-5
ValueCountFrequency (%)
인천광역시 106
33.0%
중구 106
33.0%
운북동35-3 4
 
1.2%
항동7가1-8 3
 
0.9%
운북동450-2 3
 
0.9%
중산동 3
 
0.9%
운남동105-13 2
 
0.6%
항동7가112-10 2
 
0.6%
중산동1097-553 2
 
0.6%
중산동1255-98 2
 
0.6%
Other values (85) 88
27.4%
2024-01-28T19:45:06.429677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
215
 
11.5%
중 140
 
7.5%
인 107
 
5.7%
천 106
 
5.7%
광 106
 
5.7%
역 106
 
5.7%
시 106
 
5.7%
구 106
 
5.7%
동 106
 
5.7%
1 105
 
5.6%
Other values (21) 673
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1070
57.0%
Decimal Number 499
26.6%
Space Separator 215
 
11.5%
Dash Punctuation 92
 
4.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 140
13.1%
인 107
10.0%
천 106
9.9%
광 106
9.9%
역 106
9.9%
시 106
9.9%
구 106
9.9%
동 106
9.9%
운 55
 
5.1%
산 39
 
3.6%
Other values (9) 93
8.7%
Decimal Number
ValueCountFrequency (%)
1 105
21.0%
5 69
13.8%
3 56
11.2%
7 50
10.0%
2 41
 
8.2%
0 40
 
8.0%
8 36
 
7.2%
6 35
 
7.0%
9 35
 
7.0%
4 32
 
6.4%
Space Separator
ValueCountFrequency (%)
215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1070
57.0%
Common 806
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 140
13.1%
인 107
10.0%
천 106
9.9%
광 106
9.9%
역 106
9.9%
시 106
9.9%
구 106
9.9%
동 106
9.9%
운 55
 
5.1%
산 39
 
3.6%
Other values (9) 93
8.7%
Common
ValueCountFrequency (%)
215
26.7%
1 105
13.0%
- 92
11.4%
5 69
 
8.6%
3 56
 
6.9%
7 50
 
6.2%
2 41
 
5.1%
0 40
 
5.0%
8 36
 
4.5%
6 35
 
4.3%
Other values (2) 67
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1070
57.0%
ASCII 806
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
215
26.7%
1 105
13.0%
- 92
11.4%
5 69
 
8.6%
3 56
 
6.9%
7 50
 
6.2%
2 41
 
5.1%
0 40
 
5.0%
8 36
 
4.5%
6 35
 
4.3%
Other values (2) 67
 
8.3%
Hangul
ValueCountFrequency (%)
중 140
13.1%
인 107
10.0%
천 106
9.9%
광 106
9.9%
역 106
9.9%
시 106
9.9%
구 106
9.9%
동 106
9.9%
운 55
 
5.1%
산 39
 
3.6%
Other values (9) 93
8.7%

용도지역
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size980.0 B
자연녹지지역
56 
보전녹지
18 
생산녹지지역
14 
준공업지역
10 
일반상업지역
 
5
Other values (2)
 
3

Length

Max length6
Median length6
Mean length5.5471698
Min length4

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row준공업지역
2nd row준공업지역
3rd row준공업지역
4th row준공업지역
5th row일반상업지역

Common Values

ValueCountFrequency (%)
자연녹지지역 56
52.8%
보전녹지 18
 
17.0%
생산녹지지역 14
 
13.2%
준공업지역 10
 
9.4%
일반상업지역 5
 
4.7%
일반공업지역 2
 
1.9%
자연녹지 1
 
0.9%

Length

2024-01-28T19:45:06.762033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:45:06.850775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자연녹지지역 56
52.8%
보전녹지 18
 
17.0%
생산녹지지역 14
 
13.2%
준공업지역 10
 
9.4%
일반상업지역 5
 
4.7%
일반공업지역 2
 
1.9%
자연녹지 1
 
0.9%

지목명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size980.0 B
임
30 
전
26 
답
22 
잡
11 
대
7 
Other values (6)
10 

Length

Max length3
Median length1
Mean length1.0471698
Min length1

Unique

Unique4 ?
Unique (%)3.8%

Sample

1st row잡
2nd row도로
3rd row잡
4th row잡
5th row공원

Common Values

ValueCountFrequency (%)
임 30
28.3%
전 26
24.5%
답 22
20.8%
잡 11
 
10.4%
대 7
 
6.6%
원 4
 
3.8%
유 2
 
1.9%
도로 1
 
0.9%
공원 1
 
0.9%
공장 1
 
0.9%

Length

2024-01-28T19:45:06.950190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
임 30
28.3%
전 26
24.5%
답 22
20.8%
잡 11
 
10.4%
대 7
 
6.6%
원 4
 
3.8%
유 2
 
1.9%
도로 1
 
0.9%
공원 1
 
0.9%
공장 1
 
0.9%

허가면적(미터제곱)
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1325.2142
Minimum18
Maximum10041
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-28T19:45:07.054256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile60.75
Q1363.75
median673
Q31452.25
95-th percentile4597.675
Maximum10041
Range10023
Interquartile range (IQR)1088.5

Descriptive statistics

Standard deviation1753.905
Coefficient of variation (CV)1.323488
Kurtosis9.9084462
Mean1325.2142
Median Absolute Deviation (MAD)352.38
Skewness2.9320102
Sum140472.7
Variance3076182.7
MonotonicityNot monotonic
2024-01-28T19:45:07.163122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
659.0 4
 
3.8%
337.0 3
 
2.8%
329.0 3
 
2.8%
366.0 3
 
2.8%
27.0 2
 
1.9%
569.0 2
 
1.9%
3048.0 1
 
0.9%
972.0 1
 
0.9%
893.0 1
 
0.9%
892.0 1
 
0.9%
Other values (85) 85
80.2%
ValueCountFrequency (%)
18.0 1
0.9%
20.0 1
0.9%
27.0 2
1.9%
36.0 1
0.9%
60.0 1
0.9%
63.0 1
0.9%
122.0 1
0.9%
202.0 1
0.9%
214.0 1
0.9%
223.0 1
0.9%
ValueCountFrequency (%)
10041.0 1
0.9%
8733.0 1
0.9%
8454.0 1
0.9%
4946.0 1
0.9%
4864.0 1
0.9%
4688.0 1
0.9%
4326.7 1
0.9%
4260.3 1
0.9%
3966.0 1
0.9%
3941.0 1
0.9%

협의면적(미터제곱)
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)89.5%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean1300.6248
Minimum18
Maximum10041
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-28T19:45:07.272730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile60.6
Q1363
median660
Q31438
95-th percentile4615.74
Maximum10041
Range10023
Interquartile range (IQR)1075

Descriptive statistics

Standard deviation1743.8617
Coefficient of variation (CV)1.3407877
Kurtosis10.471828
Mean1300.6248
Median Absolute Deviation (MAD)337
Skewness3.0235087
Sum136565.6
Variance3041053.5
MonotonicityNot monotonic
2024-01-28T19:45:07.381057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
659.0 4
 
3.8%
337.0 3
 
2.8%
366.0 3
 
2.8%
329.0 3
 
2.8%
27.0 2
 
1.9%
569.0 2
 
1.9%
3048.0 1
 
0.9%
972.0 1
 
0.9%
893.0 1
 
0.9%
892.0 1
 
0.9%
Other values (84) 84
79.2%
ValueCountFrequency (%)
18.0 1
0.9%
20.0 1
0.9%
27.0 2
1.9%
36.0 1
0.9%
60.0 1
0.9%
63.0 1
0.9%
122.0 1
0.9%
202.0 1
0.9%
214.0 1
0.9%
223.0 1
0.9%
ValueCountFrequency (%)
10041.0 1
0.9%
8733.0 1
0.9%
8454.0 1
0.9%
4946.0 1
0.9%
4864.0 1
0.9%
4688.0 1
0.9%
4326.7 1
0.9%
4260.3 1
0.9%
3966.0 1
0.9%
3941.0 1
0.9%

개발행위 목적
Categorical

Distinct8
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size980.0 B
토지형질변경(신축)
65 
토지분할
12 
토지형질변경
10 
공작물설치
7 
건축물의 건축
 
6
Other values (3)
 
6

Length

Max length20
Median length10
Mean length8.6603774
Min length4

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row건축물의 건축
2nd row건축물의 건축
3rd row건축물의 건축
4th row건축물의 건축
5th row건축물의 건축

Common Values

ValueCountFrequency (%)
토지형질변경(신축) 65
61.3%
토지분할 12
 
11.3%
토지형질변경 10
 
9.4%
공작물설치 7
 
6.6%
건축물의 건축 6
 
5.7%
토지분할(기반시설 공사완료 후 분할) 3
 
2.8%
공작물 설치 2
 
1.9%
토지분할(공유물분할) 1
 
0.9%

Length

2024-01-28T19:45:07.489799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:45:07.581401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토지형질변경(신축 65
52.8%
토지분할 12
 
9.8%
토지형질변경 10
 
8.1%
공작물설치 7
 
5.7%
건축물의 6
 
4.9%
건축 6
 
4.9%
토지분할(기반시설 3
 
2.4%
공사완료 3
 
2.4%
후 3
 
2.4%
분할 3
 
2.4%
Other values (3) 5
 
4.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size980.0 B
Minimum2022-10-27 00:00:00
Maximum2022-10-27 00:00:00
2024-01-28T19:45:07.677778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:45:07.761798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T19:45:05.002135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:45:04.599053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:45:04.780710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:45:05.070928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:45:04.655850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:45:04.856929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:45:05.134197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:45:04.714753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:45:04.929559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T19:45:07.831807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번해당년도허가일자허가위치용도지역지목명허가면적(미터제곱)협의면적(미터제곱)개발행위 목적
연번1.0000.9920.9520.8590.6260.4940.3080.3210.637
해당년도0.9921.0001.0000.7430.2290.1610.0690.0530.461
허가일자0.9521.0001.0000.9700.8910.8950.9540.9480.944
허가위치0.8590.7430.9701.0001.0000.9980.6110.4020.868
용도지역0.6260.2290.8911.0001.0000.8440.0000.0000.589
지목명0.4940.1610.8950.9980.8441.0000.2240.2080.676
허가면적(미터제곱)0.3080.0690.9540.6110.0000.2241.0001.0000.032
협의면적(미터제곱)0.3210.0530.9480.4020.0000.2081.0001.0000.064
개발행위 목적0.6370.4610.9440.8680.5890.6760.0320.0641.000
2024-01-28T19:45:07.949777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지목명해당년도용도지역개발행위 목적
지목명1.0000.1440.6200.395
해당년도0.1441.0000.2390.336
용도지역0.6200.2391.0000.364
개발행위 목적0.3950.3360.3641.000
2024-01-28T19:45:08.081383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번허가면적(미터제곱)협의면적(미터제곱)해당년도용도지역지목명개발행위 목적
연번1.0000.0260.0420.8790.3660.2250.367
허가면적(미터제곱)0.0261.0001.0000.0680.0000.1050.000
협의면적(미터제곱)0.0421.0001.0000.0500.0000.0970.022
해당년도0.8790.0680.0501.0000.2390.1440.336
용도지역0.3660.0000.0000.2391.0000.6200.364
지목명0.2250.1050.0970.1440.6201.0000.395
개발행위 목적0.3670.0000.0220.3360.3640.3951.000

Missing values

2024-01-28T19:45:05.219618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T19:45:05.328279image/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

연번해당년도허가일자허가위치용도지역지목명허가면적(미터제곱)협의면적(미터제곱)개발행위 목적데이터기준일자
0120212021-09-27인천광역시 중구 항동7가112-10준공업지역잡27.027.0건축물의 건축2022-10-27
1220212021-10-07인천광역시 중구 항동7가1-68준공업지역도로36.036.0건축물의 건축2022-10-27
2320212021-10-08인천광역시 중구 항동7가112-10준공업지역잡27.027.0건축물의 건축2022-10-27
3420212021-10-25인천광역시 중구 항동7가1-31준공업지역잡20.020.0건축물의 건축2022-10-27
4520212021-10-27인천광역시 중구 북성동1가125-5일반상업지역공원318.24318.24건축물의 건축2022-10-27
5620212021-10-29인천광역시 중구 인현동1-336일반상업지역대63.063.0공작물설치2022-10-27
6720212021-11-16인천광역시 중구 항동7가1-8준공업지역잡18.018.0건축물의 건축2022-10-27
7820212021-11-18인천광역시 중구 관동2가9일반상업지역대122.0122.0공작물설치2022-10-27
8920212021-12-02인천광역시 중구 북성동1가6-85일반공업지역공장273.46273.46공작물설치2022-10-27
91020212021-12-10인천광역시 중구 신흥동3가47-1일반상업지역주유소1304.91304.9공작물설치2022-10-27
연번해당년도허가일자허가위치용도지역지목명허가면적(미터제곱)협의면적(미터제곱)개발행위 목적데이터기준일자
969720222022-07-05인천광역시 중구 운남동산20-3보전녹지임1438.01438.0토지분할(공유물분할)2022-10-27
979820222022-07-14인천광역시 중구 운북동564-8자연녹지지역임1122.01122.0토지형질변경(신축)2022-10-27
989920222022-07-14인천광역시 중구 운북동564-10자연녹지지역임686.0686.0토지형질변경(신축)2022-10-27
9910020222022-07-15인천광역시 중구 운북동658자연녹지지역전908.0908.0토지형질변경(신축)2022-10-27
10010120222022-07-18인천광역시 중구 운남동636자연녹지지역전1194.01194.0토지형질변경(신축)2022-10-27
10110220222022-07-29인천광역시 중구 운남동181생산녹지지역답408.0408.0토지형질변경(신축)2022-10-27
10210320222022-08-04인천광역시 중구 운남동105-13자연녹지지역전299.0299.0토지형질변경(신축)2022-10-27
10310420222022-08-09인천광역시 중구 중산동 산134-4자연녹지지역임991.0991.0토지형질변경(신축)2022-10-27
10410520222022-08-30인천광역시 중구 중산동1830-31자연녹지지역원10041.010041.0토지분할2022-10-27
10510620222022-09-05인천광역시 중구 운남동84생산녹지지역답3941.03941.0토지형질변경(신축)2022-10-27