Overview

Dataset statistics

Number of variables14
Number of observations143
Missing cells148
Missing cells (%)7.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.2 KiB
Average record size in memory115.9 B

Variable types

Numeric3
Categorical6
Text4
Boolean1

Dataset

Description「물의 재이용 촉진 및 지원에 관한 법률」에 따른 물 재이용시설에 대한 성남시 빗물이용시설 현황에 대한 데이터로 시설명/위치/집수면적/저류조용량/연간빗물사용량 등의 항목을 제공합니다.
Author경기도 성남시
URLhttps://www.data.go.kr/data/15054335/fileData.do

Alerts

시도별 has constant value ""Constant
시군구별 has constant value ""Constant
데이터기준일자 has constant value ""Constant
법적시설여부 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
집수면 is highly overall correlated with 연간 빗물사용량(제곱미터) and 1 other fieldsHigh correlation
처리공정 is highly overall correlated with 연간 빗물사용량(제곱미터) and 1 other fieldsHigh correlation
건축물 주용도 is highly overall correlated with 집수면적(제곱미터) and 2 other fieldsHigh correlation
연번 is highly overall correlated with 법적시설여부High correlation
집수면적(제곱미터) is highly overall correlated with 건축물 주용도High correlation
연간 빗물사용량(제곱미터) is highly overall correlated with 집수면 and 1 other fieldsHigh correlation
집수면 is highly imbalanced (94.0%)Imbalance
처리공정 is highly imbalanced (59.2%)Imbalance
법적시설여부 is highly imbalanced (51.6%)Imbalance
위치(도로명) has 17 (11.9%) missing valuesMissing
연간 빗물사용량(제곱미터) has 131 (91.6%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:16:49.042576
Analysis finished2024-04-06 08:16:53.198786
Duration4.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct143
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72
Minimum1
Maximum143
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-06T17:16:53.352173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.1
Q136.5
median72
Q3107.5
95-th percentile135.9
Maximum143
Range142
Interquartile range (IQR)71

Descriptive statistics

Standard deviation41.42463
Coefficient of variation (CV)0.57534209
Kurtosis-1.2
Mean72
Median Absolute Deviation (MAD)36
Skewness0
Sum10296
Variance1716
MonotonicityStrictly increasing
2024-04-06T17:16:53.639381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
2 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
Other values (133) 133
93.0%
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 (%)
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%

시도별
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
경기도
143 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 143
100.0%

Length

2024-04-06T17:16:53.934644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:16:54.129359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 143
100.0%

시군구별
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
성남시
143 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 143
100.0%

Length

2024-04-06T17:16:54.342756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:16:54.601396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시 143
100.0%

시설명
Text

UNIQUE 

Distinct143
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-06T17:16:55.099662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length16
Mean length10.727273
Min length4

Characters and Unicode

Total characters1534
Distinct characters261
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique143 ?
Unique (%)100.0%

Sample

1st row산성 실내배드민턴장
2nd row성남시 수정구보건소
3rd row자연앤자이이편한세상
4th row성남시의료원
5th row호반써밋아파트
ValueCountFrequency (%)
휴먼시아 20
 
7.5%
아파트 12
 
4.5%
힐스테이트 5
 
1.9%
판교 5
 
1.9%
판교알파돔 4
 
1.5%
판교제2테크노밸리 4
 
1.5%
복합시설 4
 
1.5%
판교엘포레 3
 
1.1%
푸르지오 3
 
1.1%
n-square 3
 
1.1%
Other values (194) 202
76.2%
2024-04-06T17:16:56.205019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
 
8.0%
교 64
 
4.2%
아 54
 
3.5%
지 49
 
3.2%
판 41
 
2.7%
시 36
 
2.3%
단 36
 
2.3%
파 33
 
2.2%
트 32
 
2.1%
스 28
 
1.8%
Other values (251) 1039
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1179
76.9%
Space Separator 122
 
8.0%
Decimal Number 80
 
5.2%
Uppercase Letter 73
 
4.8%
Lowercase Letter 40
 
2.6%
Open Punctuation 11
 
0.7%
Close Punctuation 11
 
0.7%
Dash Punctuation 10
 
0.7%
Other Punctuation 4
 
0.3%
Other Symbol 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 64
 
5.4%
아 54
 
4.6%
지 49
 
4.2%
판 41
 
3.5%
시 36
 
3.1%
단 36
 
3.1%
파 33
 
2.8%
트 32
 
2.7%
스 28
 
2.4%
학 24
 
2.0%
Other values (203) 782
66.3%
Uppercase Letter
ValueCountFrequency (%)
N 8
11.0%
D 8
11.0%
L 7
9.6%
B 7
9.6%
R 6
8.2%
S 6
8.2%
C 6
8.2%
E 5
6.8%
K 4
 
5.5%
A 4
 
5.5%
Other values (7) 12
16.4%
Lowercase Letter
ValueCountFrequency (%)
e 10
25.0%
r 6
15.0%
a 5
12.5%
q 3
 
7.5%
u 3
 
7.5%
y 2
 
5.0%
t 2
 
5.0%
n 2
 
5.0%
i 1
 
2.5%
h 1
 
2.5%
Other values (5) 5
12.5%
Decimal Number
ValueCountFrequency (%)
1 21
26.2%
2 13
16.2%
3 10
12.5%
7 8
 
10.0%
6 8
 
10.0%
5 7
 
8.8%
8 5
 
6.2%
4 4
 
5.0%
9 3
 
3.8%
0 1
 
1.2%
Space Separator
ValueCountFrequency (%)
122
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
& 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1183
77.1%
Common 238
 
15.5%
Latin 113
 
7.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 64
 
5.4%
아 54
 
4.6%
지 49
 
4.1%
판 41
 
3.5%
시 36
 
3.0%
단 36
 
3.0%
파 33
 
2.8%
트 32
 
2.7%
스 28
 
2.4%
학 24
 
2.0%
Other values (204) 786
66.4%
Latin
ValueCountFrequency (%)
e 10
 
8.8%
N 8
 
7.1%
D 8
 
7.1%
L 7
 
6.2%
B 7
 
6.2%
r 6
 
5.3%
R 6
 
5.3%
S 6
 
5.3%
C 6
 
5.3%
a 5
 
4.4%
Other values (22) 44
38.9%
Common
ValueCountFrequency (%)
122
51.3%
1 21
 
8.8%
2 13
 
5.5%
( 11
 
4.6%
) 11
 
4.6%
- 10
 
4.2%
3 10
 
4.2%
7 8
 
3.4%
6 8
 
3.4%
5 7
 
2.9%
Other values (5) 17
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1179
76.9%
ASCII 351
 
22.9%
None 4
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
34.8%
1 21
 
6.0%
2 13
 
3.7%
( 11
 
3.1%
) 11
 
3.1%
- 10
 
2.8%
3 10
 
2.8%
e 10
 
2.8%
7 8
 
2.3%
6 8
 
2.3%
Other values (37) 127
36.2%
Hangul
ValueCountFrequency (%)
교 64
 
5.4%
아 54
 
4.6%
지 49
 
4.2%
판 41
 
3.5%
시 36
 
3.1%
단 36
 
3.1%
파 33
 
2.8%
트 32
 
2.7%
스 28
 
2.4%
학 24
 
2.0%
Other values (203) 782
66.3%
None
ValueCountFrequency (%)
㈜ 4
100.0%

위치(주소)
Text

Distinct139
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-06T17:16:57.035500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length31
Mean length21.265734
Min length18

Characters and Unicode

Total characters3041
Distinct characters84
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

Unique136 ?
Unique (%)95.1%

Sample

1st row경기도 성남시 수정구 산성동 산6
2nd row경기도 성남시 수정구 신흥동 3435
3rd row경기도 성남시 수정구 창곡동 504
4th row경기도 성남시 수정구 태평동 3309
5th row경기도 성남시 수정구 고등동 592
ValueCountFrequency (%)
경기도 143
19.7%
성남시 143
19.7%
분당구 97
13.4%
수정구 35
 
4.8%
삼평동 27
 
3.7%
백현동 25
 
3.4%
운중동 14
 
1.9%
판교동 14
 
1.9%
중원구 11
 
1.5%
정자동 6
 
0.8%
Other values (172) 210
29.0%
2024-04-06T17:16:58.223763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
583
19.2%
시 149
 
4.9%
도 145
 
4.8%
성 145
 
4.8%
남 144
 
4.7%
구 144
 
4.7%
경 143
 
4.7%
기 143
 
4.7%
동 142
 
4.7%
1 103
 
3.4%
Other values (74) 1200
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1764
58.0%
Space Separator 583
 
19.2%
Decimal Number 578
 
19.0%
Close Punctuation 36
 
1.2%
Open Punctuation 36
 
1.2%
Dash Punctuation 31
 
1.0%
Uppercase Letter 10
 
0.3%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 149
 
8.4%
도 145
 
8.2%
성 145
 
8.2%
남 144
 
8.2%
구 144
 
8.2%
경 143
 
8.1%
기 143
 
8.1%
동 142
 
8.0%
분 97
 
5.5%
당 97
 
5.5%
Other values (56) 415
23.5%
Decimal Number
ValueCountFrequency (%)
1 103
17.8%
5 75
13.0%
2 66
11.4%
6 58
10.0%
3 56
9.7%
0 56
9.7%
4 48
8.3%
9 41
 
7.1%
7 41
 
7.1%
8 34
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
E 4
40.0%
B 3
30.0%
L 3
30.0%
Space Separator
ValueCountFrequency (%)
583
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1764
58.0%
Common 1267
41.7%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 149
 
8.4%
도 145
 
8.2%
성 145
 
8.2%
남 144
 
8.2%
구 144
 
8.2%
경 143
 
8.1%
기 143
 
8.1%
동 142
 
8.0%
분 97
 
5.5%
당 97
 
5.5%
Other values (56) 415
23.5%
Common
ValueCountFrequency (%)
583
46.0%
1 103
 
8.1%
5 75
 
5.9%
2 66
 
5.2%
6 58
 
4.6%
3 56
 
4.4%
0 56
 
4.4%
4 48
 
3.8%
9 41
 
3.2%
7 41
 
3.2%
Other values (5) 140
 
11.0%
Latin
ValueCountFrequency (%)
E 4
40.0%
B 3
30.0%
L 3
30.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1764
58.0%
ASCII 1277
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
583
45.7%
1 103
 
8.1%
5 75
 
5.9%
2 66
 
5.2%
6 58
 
4.5%
3 56
 
4.4%
0 56
 
4.4%
4 48
 
3.8%
9 41
 
3.2%
7 41
 
3.2%
Other values (8) 150
 
11.7%
Hangul
ValueCountFrequency (%)
시 149
 
8.4%
도 145
 
8.2%
성 145
 
8.2%
남 144
 
8.2%
구 144
 
8.2%
경 143
 
8.1%
기 143
 
8.1%
동 142
 
8.0%
분 97
 
5.5%
당 97
 
5.5%
Other values (56) 415
23.5%

위치(도로명)
Text

MISSING 

Distinct123
Distinct (%)97.6%
Missing17
Missing (%)11.9%
Memory size1.2 KiB
2024-04-06T17:16:58.760617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length40
Mean length30.373016
Min length18

Characters and Unicode

Total characters3827
Distinct characters156
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

Unique121 ?
Unique (%)96.0%

Sample

1st row경기도 성남시 수정구 수정로456번길 19 (산성동)
2nd row경기도 성남시 수정구 수정로 218 (신흥동)
3rd row경기도 성남시 수정구 위례광장로 97(창곡동)위례 A2-2BL
4th row경기도 성남시 수정구 수정로171번길 10 (태평동)
5th row경기도 성남시 수정구 고등로 34
ValueCountFrequency (%)
경기도 126
16.3%
성남시 126
16.3%
분당구 93
 
12.0%
삼평동 25
 
3.2%
수정구 24
 
3.1%
백현동 17
 
2.2%
동판교로 15
 
1.9%
판교동 14
 
1.8%
운중동 14
 
1.8%
판교역로 13
 
1.7%
Other values (228) 307
39.7%
2024-04-06T17:16:59.728687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
648
 
16.9%
성 135
 
3.5%
도 131
 
3.4%
경 130
 
3.4%
남 130
 
3.4%
구 128
 
3.3%
시 127
 
3.3%
로 127
 
3.3%
기 126
 
3.3%
동 123
 
3.2%
Other values (146) 2022
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2456
64.2%
Space Separator 648
 
16.9%
Decimal Number 443
 
11.6%
Close Punctuation 110
 
2.9%
Open Punctuation 110
 
2.9%
Other Punctuation 43
 
1.1%
Uppercase Letter 11
 
0.3%
Dash Punctuation 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 135
 
5.5%
도 131
 
5.3%
경 130
 
5.3%
남 130
 
5.3%
구 128
 
5.2%
시 127
 
5.2%
로 127
 
5.2%
기 126
 
5.1%
동 123
 
5.0%
판 108
 
4.4%
Other values (125) 1191
48.5%
Decimal Number
ValueCountFrequency (%)
1 84
19.0%
2 81
18.3%
5 48
10.8%
3 40
9.0%
0 37
8.4%
6 37
8.4%
7 32
 
7.2%
4 32
 
7.2%
9 27
 
6.1%
8 25
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
L 3
27.3%
C 2
18.2%
B 2
18.2%
A 2
18.2%
I 1
 
9.1%
G 1
 
9.1%
Space Separator
ValueCountFrequency (%)
648
100.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Open Punctuation
ValueCountFrequency (%)
( 110
100.0%
Other Punctuation
ValueCountFrequency (%)
, 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2456
64.2%
Common 1360
35.5%
Latin 11
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 135
 
5.5%
도 131
 
5.3%
경 130
 
5.3%
남 130
 
5.3%
구 128
 
5.2%
시 127
 
5.2%
로 127
 
5.2%
기 126
 
5.1%
동 123
 
5.0%
판 108
 
4.4%
Other values (125) 1191
48.5%
Common
ValueCountFrequency (%)
648
47.6%
) 110
 
8.1%
( 110
 
8.1%
1 84
 
6.2%
2 81
 
6.0%
5 48
 
3.5%
, 43
 
3.2%
3 40
 
2.9%
0 37
 
2.7%
6 37
 
2.7%
Other values (5) 122
 
9.0%
Latin
ValueCountFrequency (%)
L 3
27.3%
C 2
18.2%
B 2
18.2%
A 2
18.2%
I 1
 
9.1%
G 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2456
64.2%
ASCII 1371
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
648
47.3%
) 110
 
8.0%
( 110
 
8.0%
1 84
 
6.1%
2 81
 
5.9%
5 48
 
3.5%
, 43
 
3.1%
3 40
 
2.9%
0 37
 
2.7%
6 37
 
2.7%
Other values (11) 133
 
9.7%
Hangul
ValueCountFrequency (%)
성 135
 
5.5%
도 131
 
5.3%
경 130
 
5.3%
남 130
 
5.3%
구 128
 
5.2%
시 127
 
5.2%
로 127
 
5.2%
기 126
 
5.1%
동 123
 
5.0%
판 108
 
4.4%
Other values (125) 1191
48.5%

건축물 주용도
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
공동주택
54 
기타
46 
학교
22 
공공기관청사
8 
공공업무시설
6 
Other values (5)
7 

Length

Max length9
Median length6
Mean length3.3146853
Min length2

Unique

Unique4 ?
Unique (%)2.8%

Sample

1st row실내체육관
2nd row공공기관청사
3rd row공동주택
4th row공공업무시설
5th row공동주택

Common Values

ValueCountFrequency (%)
공동주택 54
37.8%
기타 46
32.2%
학교 22
15.4%
공공기관청사 8
 
5.6%
공공업무시설 6
 
4.2%
실내체육관 3
 
2.1%
골프장 1
 
0.7%
대규모점포 1
 
0.7%
업무시설(사무소) 1
 
0.7%
지식산업센터 1
 
0.7%

Length

2024-04-06T17:17:00.106675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:00.511641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동주택 54
37.8%
기타 46
32.2%
학교 22
15.4%
공공기관청사 8
 
5.6%
공공업무시설 6
 
4.2%
실내체육관 3
 
2.1%
골프장 1
 
0.7%
대규모점포 1
 
0.7%
업무시설(사무소 1
 
0.7%
지식산업센터 1
 
0.7%

집수면
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
지붕면
142 
부지면적
 
1

Length

Max length4
Median length3
Mean length3.006993
Min length3

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
지붕면 142
99.3%
부지면적 1
 
0.7%

Length

2024-04-06T17:17:00.865026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:01.106917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지붕면 142
99.3%
부지면적 1
 
0.7%

집수면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct141
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13146.615
Minimum79
Maximum1118446
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-06T17:17:01.345070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum79
5-th percentile837.131
Q12350.675
median4050.88
Q37766.5
95-th percentile13819.101
Maximum1118446
Range1118367
Interquartile range (IQR)5415.825

Descriptive statistics

Standard deviation93191.588
Coefficient of variation (CV)7.0886375
Kurtosis142.30607
Mean13146.615
Median Absolute Deviation (MAD)2288.88
Skewness11.915256
Sum1879965.9
Variance8.684672 × 109
MonotonicityNot monotonic
2024-04-06T17:17:01.644283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1762.0 2
 
1.4%
11952.56 2
 
1.4%
2300.0 1
 
0.7%
79.0 1
 
0.7%
3552.0 1
 
0.7%
4247.0 1
 
0.7%
10799.671 1
 
0.7%
2360.35 1
 
0.7%
520.0 1
 
0.7%
5897.0 1
 
0.7%
Other values (131) 131
91.6%
ValueCountFrequency (%)
79.0 1
0.7%
426.73 1
0.7%
444.91 1
0.7%
510.84 1
0.7%
520.0 1
0.7%
687.83 1
0.7%
817.46 1
0.7%
834.65 1
0.7%
859.46 1
0.7%
874.0 1
0.7%
ValueCountFrequency (%)
1118446.0 1
0.7%
32341.32 1
0.7%
16738.76 1
0.7%
16063.88 1
0.7%
14870.0 1
0.7%
14157.0 1
0.7%
13915.0 1
0.7%
13822.334 1
0.7%
13790.0 1
0.7%
13380.56 1
0.7%

저류조 용량(제곱미터)
Text

Distinct94
Distinct (%)65.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-06T17:17:02.172529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.2027972
Min length1

Characters and Unicode

Total characters458
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)54.5%

Sample

1st row260
2nd row111.99
3rd row647
4th row504.8
5th row739
ValueCountFrequency (%)
30 9
 
6.3%
20 9
 
6.3%
17.5 9
 
6.3%
25 5
 
3.5%
36 5
 
3.5%
110 4
 
2.8%
60 4
 
2.8%
90 4
 
2.8%
280 2
 
1.4%
260 2
 
1.4%
Other values (84) 90
62.9%
2024-04-06T17:17:02.990926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 70
15.3%
1 58
12.7%
2 49
10.7%
5 43
9.4%
6 43
9.4%
3 41
9.0%
. 41
9.0%
7 33
7.2%
8 26
 
5.7%
4 26
 
5.7%
Other values (3) 28
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 414
90.4%
Other Punctuation 41
 
9.0%
Space Separator 2
 
0.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 70
16.9%
1 58
14.0%
2 49
11.8%
5 43
10.4%
6 43
10.4%
3 41
9.9%
7 33
8.0%
8 26
 
6.3%
4 26
 
6.3%
9 25
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 41
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 458
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 70
15.3%
1 58
12.7%
2 49
10.7%
5 43
9.4%
6 43
9.4%
3 41
9.0%
. 41
9.0%
7 33
7.2%
8 26
 
5.7%
4 26
 
5.7%
Other values (3) 28
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 70
15.3%
1 58
12.7%
2 49
10.7%
5 43
9.4%
6 43
9.4%
3 41
9.0%
. 41
9.0%
7 33
7.2%
8 26
 
5.7%
4 26
 
5.7%
Other values (3) 28
 
6.1%

연간 빗물사용량(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)100.0%
Missing131
Missing (%)91.6%
Infinite0
Infinite (%)0.0%
Mean721.57683
Minimum0.722
Maximum3537
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-06T17:17:03.224866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.722
5-th percentile1.4249
Q115.5
median117.5
Q3682.75
95-th percentile3100.85
Maximum3537
Range3536.278
Interquartile range (IQR)667.25

Descriptive statistics

Standard deviation1209.203
Coefficient of variation (CV)1.6757785
Kurtosis1.9649906
Mean721.57683
Median Absolute Deviation (MAD)112.5
Skewness1.7641682
Sum8658.922
Variance1462171.8
MonotonicityNot monotonic
2024-04-06T17:17:03.432076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2.0 1
 
0.7%
2744.0 1
 
0.7%
125.0 1
 
0.7%
157.2 1
 
0.7%
434.0 1
 
0.7%
1429.0 1
 
0.7%
8.0 1
 
0.7%
0.722 1
 
0.7%
18.0 1
 
0.7%
3537.0 1
 
0.7%
Other values (2) 2
 
1.4%
(Missing) 131
91.6%
ValueCountFrequency (%)
0.722 1
0.7%
2.0 1
0.7%
8.0 1
0.7%
18.0 1
0.7%
94.0 1
0.7%
110.0 1
0.7%
125.0 1
0.7%
157.2 1
0.7%
434.0 1
0.7%
1429.0 1
0.7%
ValueCountFrequency (%)
3537.0 1
0.7%
2744.0 1
0.7%
1429.0 1
0.7%
434.0 1
0.7%
157.2 1
0.7%
125.0 1
0.7%
110.0 1
0.7%
94.0 1
0.7%
18.0 1
0.7%
8.0 1
0.7%

처리공정
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
스크린
110 
여과식
 
11
초기우수배제+여과
 
11
여과+살균
 
2
초기우수배제+스크린+여과+살균
 
2
Other values (5)
 
7

Length

Max length16
Median length3
Mean length3.965035
Min length3

Unique

Unique3 ?
Unique (%)2.1%

Sample

1st row여과식
2nd row여과식
3rd row여과식
4th row여과식
5th row여과+살균

Common Values

ValueCountFrequency (%)
스크린 110
76.9%
여과식 11
 
7.7%
초기우수배제+여과 11
 
7.7%
여과+살균 2
 
1.4%
초기우수배제+스크린+여과+살균 2
 
1.4%
스크린, 살균 2
 
1.4%
스크린+여과설비 2
 
1.4%
초기우수배제+스크린+여과 1
 
0.7%
스크린,살균 1
 
0.7%
초기빗물배제+여과+UV소독 1
 
0.7%

Length

2024-04-06T17:17:03.697117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:03.948281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
스크린 112
77.2%
여과식 11
 
7.6%
초기우수배제+여과 11
 
7.6%
여과+살균 2
 
1.4%
초기우수배제+스크린+여과+살균 2
 
1.4%
살균 2
 
1.4%
스크린+여과설비 2
 
1.4%
초기우수배제+스크린+여과 1
 
0.7%
스크린,살균 1
 
0.7%
초기빗물배제+여과+uv소독 1
 
0.7%

법적시설여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size275.0 B
False
128 
True
15 
ValueCountFrequency (%)
False 128
89.5%
True 15
 
10.5%
2024-04-06T17:17:04.269534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-22
143 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-22
2nd row2024-03-22
3rd row2024-03-22
4th row2024-03-22
5th row2024-03-22

Common Values

ValueCountFrequency (%)
2024-03-22 143
100.0%

Length

2024-04-06T17:17:04.467407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:04.662448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-22 143
100.0%

Interactions

2024-04-06T17:16:51.302607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:50.230480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:50.751393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:51.481774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:50.404763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:50.953525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:51.704080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:50.573079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:16:51.122372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:17:04.814890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번건축물 주용도집수면집수면적(제곱미터)저류조 용량(제곱미터)연간 빗물사용량(제곱미터)처리공정법적시설여부
연번1.0000.7540.0600.0600.7580.0000.8511.000
건축물 주용도0.7541.0001.0001.0000.8780.3780.7160.763
집수면0.0601.0001.0000.6970.000NaN0.0000.000
집수면적(제곱미터)0.0601.0000.6971.0000.000NaN0.0000.000
저류조 용량(제곱미터)0.7580.8780.0000.0001.0001.0000.9840.913
연간 빗물사용량(제곱미터)0.0000.378NaNNaN1.0001.0000.9100.000
처리공정0.8510.7160.0000.0000.9840.9101.0000.998
법적시설여부1.0000.7630.0000.0000.9130.0000.9981.000
2024-04-06T17:17:05.258322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법적시설여부집수면처리공정건축물 주용도
법적시설여부1.0000.0000.9350.583
집수면0.0001.0000.0000.971
처리공정0.9350.0001.0000.293
건축물 주용도0.5830.9710.2931.000
2024-04-06T17:17:05.595229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번집수면적(제곱미터)연간 빗물사용량(제곱미터)건축물 주용도집수면처리공정법적시설여부
연번1.000-0.018-0.0910.3220.0390.4220.971
집수면적(제곱미터)-0.0181.0000.3570.9710.4910.0000.000
연간 빗물사용량(제곱미터)-0.0910.3571.0000.0771.0000.5610.000
건축물 주용도0.3220.9710.0771.0000.9710.2930.583
집수면0.0390.4911.0000.9711.0000.0000.000
처리공정0.4220.0000.5610.2930.0001.0000.935
법적시설여부0.9710.0000.0000.5830.0000.9351.000

Missing values

2024-04-06T17:16:51.970211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:16:52.362098image/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.
2024-04-06T17:16:53.047462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번시도별시군구별시설명위치(주소)위치(도로명)건축물 주용도집수면집수면적(제곱미터)저류조 용량(제곱미터)연간 빗물사용량(제곱미터)처리공정법적시설여부데이터기준일자
01경기도성남시산성 실내배드민턴장경기도 성남시 수정구 산성동 산6경기도 성남시 수정구 수정로456번길 19 (산성동)실내체육관지붕면2300.02602.0여과식Y2024-03-22
12경기도성남시성남시 수정구보건소경기도 성남시 수정구 신흥동 3435경기도 성남시 수정구 수정로 218 (신흥동)공공기관청사지붕면1729.08111.992744.0여과식Y2024-03-22
23경기도성남시자연앤자이이편한세상경기도 성남시 수정구 창곡동 504경기도 성남시 수정구 위례광장로 97(창곡동)위례 A2-2BL공동주택지붕면12894.51647125.0여과식Y2024-03-22
34경기도성남시성남시의료원경기도 성남시 수정구 태평동 3309경기도 성남시 수정구 수정로171번길 10 (태평동)공공업무시설지붕면9405.0504.8157.2여과식Y2024-03-22
45경기도성남시호반써밋아파트경기도 성남시 수정구 고등동 592경기도 성남시 수정구 고등로 34공동주택지붕면10713.9739<NA>여과+살균Y2024-03-22
56경기도성남시성남우체국경기도 성남시 수정구 신흥동 2482경기도 성남시 수정구 산성대로 301 (신흥동)공공기관청사지붕면2719.0174<NA>여과식Y2024-03-22
67경기도성남시산성역 포레스티아경기도 성남시 수정구 신흥동 10번지 외경기도 성남시 수정구 수정로 319공동주택지붕면32341.321656434.0초기우수배제+스크린+여과Y2024-03-22
78경기도성남시성남시 분당세무서경기도 성남시 분당구 서현동 277경기도 성남시 분당구 분당로 23공공기관청사지붕면1338.15901429.0여과+살균Y2024-03-22
89경기도성남시야탑청소년수련관경기도 성남시 분당구 야탑동 262경기도 성남시 분당구 벌말로30번길 35공공기관청사지붕면2312.13139<NA>여과식Y2024-03-22
910경기도성남시성남국민체육센터경기도 성남시 분당구 수내동 43경기도 성남시 분당구 황새울로 273실내체육관지붕면2901.3162<NA>여과식Y2024-03-22
연번시도별시군구별시설명위치(주소)위치(도로명)건축물 주용도집수면집수면적(제곱미터)저류조 용량(제곱미터)연간 빗물사용량(제곱미터)처리공정법적시설여부데이터기준일자
133134경기도성남시중앙하이츠 금강프리미엄경기도 성남시 중원구 금광동 3125번지 외 2필지<NA>기타지붕면444.9117.8<NA>초기우수배제+여과N2024-03-22
134135경기도성남시슈어소프트테크 지란지교 통합사옥경기도 성남시 수정구 금토동 판교 제2테크노밸리 E9-1BL, E9-2BL<NA>기타지붕면3094.35162.04<NA>초기우수배제+여과N2024-03-22
135136경기도성남시판교디앤써밋에디션 오피스텔경기도 성남시 수정구 시흥동 268-1번지<NA>기타지붕면426.7325<NA>초기우수배제+여과N2024-03-22
136137경기도성남시The Zen City 오피스텔경기도 성남시 수정구 신흥동 2506-1번지<NA>기타지붕면687.8356<NA>여과식N2024-03-22
137138경기도성남시판교 KT사옥경기도 성남시 수정구 금토동 353-1<NA>기타지붕면4424.12234.99<NA>초기우수배제+여과N2024-03-22
138139경기도성남시판교제2테크노밸리 글로벌비즈센터경기도 성남시 수정구 시흥동 293<NA>기타지붕면6115.0353.34<NA>스크린+여과설비N2024-03-22
139140경기도성남시판교IT센터경기도 성남시 수정구 판교제2테크노밸리 E2-1BL<NA>기타지붕면4058.0212.36<NA>초기우수배제+여과N2024-03-22
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141142경기도성남시㈜영원무역경기도 성남시 중원구 상대원동 133-2, 132-5번지<NA>지식산업센터지붕면3622.0340<NA>스크린+여과설비N2024-03-22
142143경기도성남시고등동 행정복지센터경기도 성남시 수정구 고등동 584<NA>공공업무시설지붕면997.3462.7<NA>초기우수배제+여과N2024-03-22