Overview

Dataset statistics

Number of variables12
Number of observations149
Missing cells30
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.4 KiB
Average record size in memory98.9 B

Variable types

Numeric2
Categorical4
Text4
DateTime2

Dataset

Description서울특별시 영등포구 민간공사장현황입니다. 제공 데이터: 공사분류, 구분, 대지위치, 허가일자, 착공일자, 준공예정일자, 규모(지하층, 지상층, 연면적), 용도 데이터기준일자: 2022-11-02
Author서울특별시 영등포구
URLhttps://www.data.go.kr/data/15108024/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 규모(연면적 제곱미터) and 1 other fieldsHigh correlation
규모(연면적 제곱미터) is highly overall correlated with 연번 and 2 other fieldsHigh correlation
공사분류 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
규모(지하층) is highly overall correlated with 공사분류 and 1 other fieldsHigh correlation
규모(지상층) is highly overall correlated with 규모(연면적 제곱미터) and 2 other fieldsHigh correlation
용도 is highly overall correlated with 규모(연면적 제곱미터)High correlation
준공예정일자 has 30 (20.1%) missing valuesMissing
연번 has unique valuesUnique
구분 has unique valuesUnique
대지위치 has unique valuesUnique

Reproduction

Analysis started2024-04-20 17:38:30.257999
Analysis finished2024-04-20 17:38:32.955051
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct149
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75
Minimum1
Maximum149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-21T02:38:33.145755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.4
Q138
median75
Q3112
95-th percentile141.6
Maximum149
Range148
Interquartile range (IQR)74

Descriptive statistics

Standard deviation43.156691
Coefficient of variation (CV)0.57542255
Kurtosis-1.2
Mean75
Median Absolute Deviation (MAD)37
Skewness0
Sum11175
Variance1862.5
MonotonicityStrictly increasing
2024-04-21T02:38:33.586993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
95 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
Other values (139) 139
93.3%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%

공사분류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
소형
85 
중형
35 
대형
29 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소형 85
57.0%
중형 35
23.5%
대형 29
 
19.5%

Length

2024-04-21T02:38:34.012357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:38:34.331336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소형 85
57.0%
중형 35
23.5%
대형 29
 
19.5%

구분
Text

UNIQUE 

Distinct149
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-21T02:38:35.516629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length22
Mean length13.57047
Min length8

Characters and Unicode

Total characters2022
Distinct characters59
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique149 ?
Unique (%)100.0%

Sample

1st row 여의도동 31(여의도동 31 복합시설 신축공사)
2nd row 신길동 3608일대(신길동 역세권 청년주택 신축공사)
3rd row 당산동2가 45-5(당산동역세권청년주택신축공사)
4th row영등포동2가 439일대(가로주택정비사업)
5th row 대림동 990-80
ValueCountFrequency (%)
외1필지 33
 
9.1%
신길동 28
 
7.7%
대림동 25
 
6.9%
도림동 9
 
2.5%
당산동1가 9
 
2.5%
외3필지 8
 
2.2%
외2필지 8
 
2.2%
영등포동2가 8
 
2.2%
양평동1가 7
 
1.9%
여의도동 6
 
1.6%
Other values (180) 223
61.3%
2024-04-21T02:38:37.072022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
363
18.0%
1 192
 
9.5%
동 152
 
7.5%
- 121
 
6.0%
3 98
 
4.8%
2 96
 
4.7%
가 81
 
4.0%
지 60
 
3.0%
외 59
 
2.9%
필 59
 
2.9%
Other values (49) 741
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 803
39.7%
Decimal Number 723
35.8%
Space Separator 363
18.0%
Dash Punctuation 121
 
6.0%
Open Punctuation 6
 
0.3%
Close Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 152
18.9%
가 81
 
10.1%
지 60
 
7.5%
외 59
 
7.3%
필 59
 
7.3%
림 34
 
4.2%
신 32
 
4.0%
길 29
 
3.6%
당 28
 
3.5%
산 28
 
3.5%
Other values (35) 241
30.0%
Decimal Number
ValueCountFrequency (%)
1 192
26.6%
3 98
13.6%
2 96
13.3%
6 56
 
7.7%
4 55
 
7.6%
5 51
 
7.1%
7 50
 
6.9%
0 47
 
6.5%
8 39
 
5.4%
9 39
 
5.4%
Space Separator
ValueCountFrequency (%)
363
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1219
60.3%
Hangul 803
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 152
18.9%
가 81
 
10.1%
지 60
 
7.5%
외 59
 
7.3%
필 59
 
7.3%
림 34
 
4.2%
신 32
 
4.0%
길 29
 
3.6%
당 28
 
3.5%
산 28
 
3.5%
Other values (35) 241
30.0%
Common
ValueCountFrequency (%)
363
29.8%
1 192
15.8%
- 121
 
9.9%
3 98
 
8.0%
2 96
 
7.9%
6 56
 
4.6%
4 55
 
4.5%
5 51
 
4.2%
7 50
 
4.1%
0 47
 
3.9%
Other values (4) 90
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1219
60.3%
Hangul 803
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
363
29.8%
1 192
15.8%
- 121
 
9.9%
3 98
 
8.0%
2 96
 
7.9%
6 56
 
4.6%
4 55
 
4.5%
5 51
 
4.2%
7 50
 
4.1%
0 47
 
3.9%
Other values (4) 90
 
7.4%
Hangul
ValueCountFrequency (%)
동 152
18.9%
가 81
 
10.1%
지 60
 
7.5%
외 59
 
7.3%
필 59
 
7.3%
림 34
 
4.2%
신 32
 
4.0%
길 29
 
3.6%
당 28
 
3.5%
산 28
 
3.5%
Other values (35) 241
30.0%

대지위치
Text

UNIQUE 

Distinct149
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-21T02:38:38.215143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length23.060403
Min length18

Characters and Unicode

Total characters3436
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique149 ?
Unique (%)100.0%

Sample

1st row서울특별시 영등포구 여의도동 31
2nd row서울특별시 영등포구 신길동 3608
3rd row서울특별시 영등포구 당산동2가 45-5
4th row서울특별시 영등포구영등포동2가 439일대(가로주택정비사업)
5th row서울특별시 영등포구 대림동 990-80
ValueCountFrequency (%)
서울특별시 149
22.8%
영등포구 148
22.6%
외1필지 33
 
5.0%
신길동 28
 
4.3%
대림동 25
 
3.8%
도림동 9
 
1.4%
당산동1가 9
 
1.4%
외2필지 8
 
1.2%
외3필지 8
 
1.2%
영등포동2가 7
 
1.1%
Other values (177) 230
35.2%
2024-04-21T02:38:39.837382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
505
 
14.7%
1 191
 
5.6%
영 175
 
5.1%
등 175
 
5.1%
포 175
 
5.1%
서 149
 
4.3%
동 149
 
4.3%
특 149
 
4.3%
별 149
 
4.3%
시 149
 
4.3%
Other values (39) 1470
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2087
60.7%
Decimal Number 721
 
21.0%
Space Separator 505
 
14.7%
Dash Punctuation 121
 
3.5%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 175
 
8.4%
등 175
 
8.4%
포 175
 
8.4%
서 149
 
7.1%
동 149
 
7.1%
특 149
 
7.1%
별 149
 
7.1%
시 149
 
7.1%
구 149
 
7.1%
울 149
 
7.1%
Other values (25) 519
24.9%
Decimal Number
ValueCountFrequency (%)
1 191
26.5%
3 97
13.5%
2 96
13.3%
6 56
 
7.8%
4 55
 
7.6%
5 51
 
7.1%
7 50
 
6.9%
0 47
 
6.5%
9 39
 
5.4%
8 39
 
5.4%
Space Separator
ValueCountFrequency (%)
505
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2087
60.7%
Common 1349
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 175
 
8.4%
등 175
 
8.4%
포 175
 
8.4%
서 149
 
7.1%
동 149
 
7.1%
특 149
 
7.1%
별 149
 
7.1%
시 149
 
7.1%
구 149
 
7.1%
울 149
 
7.1%
Other values (25) 519
24.9%
Common
ValueCountFrequency (%)
505
37.4%
1 191
 
14.2%
- 121
 
9.0%
3 97
 
7.2%
2 96
 
7.1%
6 56
 
4.2%
4 55
 
4.1%
5 51
 
3.8%
7 50
 
3.7%
0 47
 
3.5%
Other values (4) 80
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2087
60.7%
ASCII 1349
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
505
37.4%
1 191
 
14.2%
- 121
 
9.0%
3 97
 
7.2%
2 96
 
7.1%
6 56
 
4.2%
4 55
 
4.1%
5 51
 
3.8%
7 50
 
3.7%
0 47
 
3.5%
Other values (4) 80
 
5.9%
Hangul
ValueCountFrequency (%)
영 175
 
8.4%
등 175
 
8.4%
포 175
 
8.4%
서 149
 
7.1%
동 149
 
7.1%
특 149
 
7.1%
별 149
 
7.1%
시 149
 
7.1%
구 149
 
7.1%
울 149
 
7.1%
Other values (25) 519
24.9%

허가일자
Date

Distinct127
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2015-12-21 00:00:00
Maximum2022-08-26 00:00:00
2024-04-21T02:38:40.244212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:38:40.661779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공일자
Text

Distinct120
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-21T02:38:41.756456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.8926174
Min length2

Characters and Unicode

Total characters1474
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

Unique99 ?
Unique (%)66.4%

Sample

1st row2019-07-19
2nd row2021-09-01
3rd row2020-04-24
4th row2021-05-31
5th row2020-03-04
ValueCountFrequency (%)
2022-06-28 4
 
2.7%
2020-04-29 3
 
2.0%
2022-05-17 3
 
2.0%
2022-08-01 3
 
2.0%
2021-03-09 3
 
2.0%
2022-04-04 3
 
2.0%
2022-05-18 3
 
2.0%
2022-05-03 2
 
1.3%
2022-07-14 2
 
1.3%
2022-06-02 2
 
1.3%
Other values (110) 121
81.2%
2024-04-21T02:38:43.296774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 473
32.1%
0 351
23.8%
- 294
19.9%
1 144
 
9.8%
5 35
 
2.4%
8 34
 
2.3%
9 33
 
2.2%
4 32
 
2.2%
3 31
 
2.1%
6 23
 
1.6%
Other values (3) 24
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1176
79.8%
Dash Punctuation 294
 
19.9%
Other Letter 4
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 473
40.2%
0 351
29.8%
1 144
 
12.2%
5 35
 
3.0%
8 34
 
2.9%
9 33
 
2.8%
4 32
 
2.7%
3 31
 
2.6%
6 23
 
2.0%
7 20
 
1.7%
Other Letter
ValueCountFrequency (%)
미 2
50.0%
정 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 294
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1470
99.7%
Hangul 4
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 473
32.2%
0 351
23.9%
- 294
20.0%
1 144
 
9.8%
5 35
 
2.4%
8 34
 
2.3%
9 33
 
2.2%
4 32
 
2.2%
3 31
 
2.1%
6 23
 
1.6%
Hangul
ValueCountFrequency (%)
미 2
50.0%
정 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1470
99.7%
Hangul 4
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 473
32.2%
0 351
23.9%
- 294
20.0%
1 144
 
9.8%
5 35
 
2.4%
8 34
 
2.3%
9 33
 
2.2%
4 32
 
2.2%
3 31
 
2.1%
6 23
 
1.6%
Hangul
ValueCountFrequency (%)
미 2
50.0%
정 2
50.0%

준공예정일자
Text

MISSING 

Distinct55
Distinct (%)46.2%
Missing30
Missing (%)20.1%
Memory size1.3 KiB
2024-04-21T02:38:44.139292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.6638655
Min length2

Characters and Unicode

Total characters1150
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

Unique34 ?
Unique (%)28.6%

Sample

1st row2023-04-30
2nd row2024-07-31
3rd row2022-12-31
4th row2024-06-14
5th row2022-10-31
ValueCountFrequency (%)
2022-09-30 11
 
9.2%
2022-12-31 10
 
8.4%
2023-01-30 6
 
5.0%
2022-08-15 5
 
4.2%
미정 5
 
4.2%
2023-06-30 5
 
4.2%
2022-11-30 4
 
3.4%
2022-12-30 4
 
3.4%
2023-03-30 3
 
2.5%
2023-02-15 3
 
2.5%
Other values (45) 63
52.9%
2024-04-21T02:38:45.596472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 314
27.3%
0 269
23.4%
- 228
19.8%
3 127
11.0%
1 98
 
8.5%
5 30
 
2.6%
8 23
 
2.0%
4 17
 
1.5%
9 15
 
1.3%
6 10
 
0.9%
Other values (3) 19
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 912
79.3%
Dash Punctuation 228
 
19.8%
Other Letter 10
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 314
34.4%
0 269
29.5%
3 127
13.9%
1 98
 
10.7%
5 30
 
3.3%
8 23
 
2.5%
4 17
 
1.9%
9 15
 
1.6%
6 10
 
1.1%
7 9
 
1.0%
Other Letter
ValueCountFrequency (%)
미 5
50.0%
정 5
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1140
99.1%
Hangul 10
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 314
27.5%
0 269
23.6%
- 228
20.0%
3 127
11.1%
1 98
 
8.6%
5 30
 
2.6%
8 23
 
2.0%
4 17
 
1.5%
9 15
 
1.3%
6 10
 
0.9%
Hangul
ValueCountFrequency (%)
미 5
50.0%
정 5
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1140
99.1%
Hangul 10
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 314
27.5%
0 269
23.6%
- 228
20.0%
3 127
11.1%
1 98
 
8.6%
5 30
 
2.6%
8 23
 
2.0%
4 17
 
1.5%
9 15
 
1.3%
6 10
 
0.9%
Hangul
ValueCountFrequency (%)
미 5
50.0%
정 5
50.0%

규모(지하층)
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
지하1층
51 
지하0층
45 
지하2층
21 
지하4층
12 
지하5층
7 
Other values (3)
13 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지하6층
2nd row지하5층
3rd row지하6층
4th row지하4층
5th row지하2층

Common Values

ValueCountFrequency (%)
지하1층 51
34.2%
지하0층 45
30.2%
지하2층 21
14.1%
지하4층 12
 
8.1%
지하5층 7
 
4.7%
지하6층 6
 
4.0%
지하3층 5
 
3.4%
지하7층 2
 
1.3%

Length

2024-04-21T02:38:46.013365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:38:46.357762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하1층 51
34.2%
지하0층 45
30.2%
지하2층 21
14.1%
지하4층 12
 
8.1%
지하5층 7
 
4.7%
지하6층 6
 
4.0%
지하3층 5
 
3.4%
지하7층 2
 
1.3%

규모(지상층)
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
지상5층
32 
지상4층
14 
지상6층
11 
지상8층
11 
지상10층
10 
Other values (20)
71 

Length

Max length5
Median length4
Mean length4.4161074
Min length4

Unique

Unique8 ?
Unique (%)5.4%

Sample

1st row지상49층
2nd row지상23층
3rd row지상19층
4th row지상29층
5th row지상20층

Common Values

ValueCountFrequency (%)
지상5층 32
21.5%
지상4층 14
9.4%
지상6층 11
 
7.4%
지상8층 11
 
7.4%
지상10층 10
 
6.7%
지상9층 9
 
6.0%
지상7층 8
 
5.4%
지상11층 7
 
4.7%
지상12층 7
 
4.7%
지상15층 7
 
4.7%
Other values (15) 33
22.1%

Length

2024-04-21T02:38:46.682667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지상5층 32
21.5%
지상4층 14
9.4%
지상6층 11
 
7.4%
지상8층 11
 
7.4%
지상10층 10
 
6.7%
지상9층 9
 
6.0%
지상7층 8
 
5.4%
지상11층 7
 
4.7%
지상12층 7
 
4.7%
지상15층 7
 
4.7%
Other values (15) 33
22.1%

규모(연면적 제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct146
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9091.0537
Minimum125
Maximum246299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-21T02:38:46.903328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum125
5-th percentile229.8
Q1559
median1519
Q35253
95-th percentile36998
Maximum246299
Range246174
Interquartile range (IQR)4694

Descriptive statistics

Standard deviation25299.905
Coefficient of variation (CV)2.7829452
Kurtosis54.021825
Mean9091.0537
Median Absolute Deviation (MAD)1102
Skewness6.5109404
Sum1354567
Variance6.4008517 × 108
MonotonicityNot monotonic
2024-04-21T02:38:47.154864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
529 2
 
1.3%
660 2
 
1.3%
559 2
 
1.3%
1333 1
 
0.7%
891 1
 
0.7%
573 1
 
0.7%
602 1
 
0.7%
603 1
 
0.7%
610 1
 
0.7%
620 1
 
0.7%
Other values (136) 136
91.3%
ValueCountFrequency (%)
125 1
0.7%
142 1
0.7%
155 1
0.7%
185 1
0.7%
186 1
0.7%
201 1
0.7%
207 1
0.7%
213 1
0.7%
255 1
0.7%
281 1
0.7%
ValueCountFrequency (%)
246299 1
0.7%
99998 1
0.7%
85189 1
0.7%
83955 1
0.7%
70507 1
0.7%
55168 1
0.7%
52545 1
0.7%
38870 1
0.7%
34190 1
0.7%
27227 1
0.7%

용도
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
공동주택
44 
업무시설
42 
제2종근린생활시설
14 
단독주택
13 
공장
8 
Other values (22)
28 

Length

Max length20
Median length4
Mean length5.1812081
Min length2

Unique

Unique20 ?
Unique (%)13.4%

Sample

1st row공동주택(1303세대)
2nd row공동주택(576세대)
3rd row공동주택(아파트)496세대 판매시설
4th row공동주택(156세대)+근린생활시설
5th row공동주택(아파트)

Common Values

ValueCountFrequency (%)
공동주택 44
29.5%
업무시설 42
28.2%
제2종근린생활시설 14
 
9.4%
단독주택 13
 
8.7%
공장 8
 
5.4%
오피스텔 6
 
4.0%
제1종근린생활시설 2
 
1.3%
공동주택(576세대) 1
 
0.7%
공동주택(아파트)496세대 판매시설 1
 
0.7%
공동주택(156세대)+근린생활시설 1
 
0.7%
Other values (17) 17
 
11.4%

Length

2024-04-21T02:38:47.404300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공동주택 45
29.2%
업무시설 42
27.3%
제2종근린생활시설 14
 
9.1%
단독주택 13
 
8.4%
공장 8
 
5.2%
오피스텔 7
 
4.5%
다세대주택 2
 
1.3%
제1종근린생활시설 2
 
1.3%
지식산업센터 2
 
1.3%
노유자시설 1
 
0.6%
Other values (18) 18
 
11.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2022-11-02 00:00:00
Maximum2022-11-02 00:00:00
2024-04-21T02:38:47.588285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:38:47.745008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T02:38:31.618255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:38:31.114225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:38:31.869905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:38:31.369708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T02:38:47.876495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번공사분류준공예정일자규모(지하층)규모(지상층)규모(연면적 제곱미터)용도
연번1.0000.9560.3860.6870.7540.5460.640
공사분류0.9561.0000.7100.7820.8000.7540.800
준공예정일자0.3860.7101.0000.9030.9240.7800.940
규모(지하층)0.6870.7820.9031.0000.8830.6140.789
규모(지상층)0.7540.8000.9240.8831.0000.9200.891
규모(연면적 제곱미터)0.5460.7540.7800.6140.9201.0000.950
용도0.6400.8000.9400.7890.8910.9501.000
2024-04-21T02:38:48.066433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사분류규모(지하층)규모(지상층)용도
공사분류1.0000.6850.5560.496
규모(지하층)0.6851.0000.5690.430
규모(지상층)0.5560.5691.0000.439
용도0.4960.4300.4391.000
2024-04-21T02:38:48.230787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번규모(연면적 제곱미터)공사분류규모(지하층)규모(지상층)용도
연번1.000-0.9980.9290.4120.3530.266
규모(연면적 제곱미터)-0.9981.0000.4280.3970.6740.727
공사분류0.9290.4281.0000.6850.5560.496
규모(지하층)0.4120.3970.6851.0000.5690.430
규모(지상층)0.3530.6740.5560.5691.0000.439
용도0.2660.7270.4960.4300.4391.000

Missing values

2024-04-21T02:38:32.221204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T02:38:32.748565image/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

연번공사분류구분대지위치허가일자착공일자준공예정일자규모(지하층)규모(지상층)규모(연면적 제곱미터)용도데이터기준일자
01대형여의도동 31(여의도동 31 복합시설 신축공사)서울특별시 영등포구 여의도동 312018-12-172019-07-192023-04-30지하6층지상49층246299공동주택(1303세대)2022-11-02
12대형신길동 3608일대(신길동 역세권 청년주택 신축공사)서울특별시 영등포구 신길동 36082020-11-052021-09-012024-07-31지하5층지상23층55168공동주택(576세대)2022-11-02
23대형당산동2가 45-5(당산동역세권청년주택신축공사)서울특별시 영등포구 당산동2가 45-52018-09-062020-04-242022-12-31지하6층지상19층52545공동주택(아파트)496세대 판매시설2022-11-02
34대형영등포동2가 439일대(가로주택정비사업)서울특별시 영등포구영등포동2가 439일대(가로주택정비사업)2019-11-012021-05-312024-06-14지하4층지상29층24578공동주택(156세대)+근린생활시설2022-11-02
45대형대림동 990-80서울특별시 영등포구 대림동 990-802019-12-162020-03-042022-10-31지하2층지상20층25151공동주택(아파트)2022-11-02
56중형당산동 121-103(나라키움 영등포복합청사)서울특별시 영등포구 당산동 121-1032020-06-012021-03-022022-10-25지하2층지상13층5986업무시설(근린생활시설, 공동주택)2022-11-02
67대형당산동1가 12-1 외1필지서울특별시 영등포구 당산동1가 12-1 외1필지2019-12-202020-04-292022-08-10지하4층지상15층99998지식산업센터2022-11-02
78대형여의도동 25-11서울특별시 영등포구 여의도동 25-112021-03-112022-09-20<NA>지하7층지상29층85189업무시설2022-11-02
89대형당산동5가 9-9 외2필지서울특별시 영등포구 당산동5가 9-9 외2필지2021-10-182022-10-05<NA>지하5층지상35층83955공장2022-11-02
910대형신길동 255-9 외16필지서울특별시 영등포구 신길동 255-9 외16필지2021-06-182021-10-192024-06-28지하5층지상24층70507공동주택2022-11-02
연번공사분류구분대지위치허가일자착공일자준공예정일자규모(지하층)규모(지상층)규모(연면적 제곱미터)용도데이터기준일자
139140소형신길동 90-28 외3필지서울특별시 영등포구 신길동 90-28 외3필지2021-12-292022-08-012023-04-01지하0층지상4층281제1종근린생활시설2022-11-02
140141소형신길동 115-16서울특별시 영등포구 신길동 115-162020-06-10미정미정지하0층지상5층255공동주택2022-11-02
141142소형도림동 141-154서울특별시 영등포구 도림동 141-1542022-08-052022-09-22<NA>지하0층지상5층213공동주택2022-11-02
142143소형양평동4가 187-1서울특별시 영등포구 양평동4가 187-12022-02-162022-03-222022-09-30지하0층지상4층207단독주택2022-11-02
143144소형영등포동1가 54서울특별시 영등포구 영등포동1가 542021-07-082022-04-152022-10-30지하0층지상3층201단독주택2022-11-02
144145소형도림동 247-37서울특별시 영등포구 도림동 247-372021-07-072022-06-022022-12-30지하0층지상5층186단독주택2022-11-02
145146소형도림동 138-3서울특별시 영등포구 도림동 138-32021-07-152022-09-26<NA>지하0층지상5층185공동주택2022-11-02
146147소형문래동3가 76-3서울특별시 영등포구 문래동3가 76-32022-07-012022-08-24<NA>지하0층지상1층155위험물저장및처리시설2022-11-02
147148소형신길동 4300서울특별시 영등포구 신길동 43002021-08-032021-12-212022-08-15지하0층지상4층142단독주택2022-11-02
148149소형신길동 3919서울특별시 영등포구 신길동 39192022-06-132022-09-16<NA>지하0층지상5층125제2종근린생활시설2022-11-02