Overview

Dataset statistics

Number of variables21
Number of observations5201
Missing cells35161
Missing cells (%)32.2%
Duplicate rows10
Duplicate rows (%)0.2%
Total size in memory909.3 KiB
Average record size in memory179.0 B

Variable types

Categorical5
Text7
Numeric8
Unsupported1

Dataset

Description구분코드,관리기관,관리부서,시설물명,집수정명,집수정위치,자치구,유출시설(kw),조사명,조사년도,총발생량(톤),일평균발생량(톤/일),일평균이용현황(톤/일)_하천방류,일평균이용현황(톤/일)_도로청소,일평균이용현황(톤/일)_공원용수,일평균이용현황(톤/일)_화장실세척,일평균이용현황(톤/일)_건물용수,미사용_하수도방류(톤/일),방류하천명,방류일,하천관로길이
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15608/S/1/datasetView.do

Alerts

Dataset has 10 (0.2%) duplicate rowsDuplicates
일평균이용현황(톤/일)_공원용수 is highly imbalanced (99.3%)Imbalance
방류하천명 is highly imbalanced (65.7%)Imbalance
관리부서 has 155 (3.0%) missing valuesMissing
집수정명 has 3234 (62.2%) missing valuesMissing
집수정위치 has 109 (2.1%) missing valuesMissing
자치구 has 155 (3.0%) missing valuesMissing
유출시설(kw) has 156 (3.0%) missing valuesMissing
총발생량(톤) has 424 (8.2%) missing valuesMissing
일평균발생량(톤/일) has 922 (17.7%) missing valuesMissing
일평균이용현황(톤/일)_하천방류 has 3643 (70.0%) missing valuesMissing
일평균이용현황(톤/일)_도로청소 has 4955 (95.3%) missing valuesMissing
일평균이용현황(톤/일)_화장실세척 has 5175 (99.5%) missing valuesMissing
일평균이용현황(톤/일)_건물용수 has 4980 (95.8%) missing valuesMissing
미사용_하수도방류(톤/일) has 992 (19.1%) missing valuesMissing
방류일 has 5014 (96.4%) missing valuesMissing
하천관로길이 has 5201 (100.0%) missing valuesMissing
하천관로길이 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총발생량(톤) has 2032 (39.1%) zerosZeros
일평균발생량(톤/일) has 1403 (27.0%) zerosZeros
일평균이용현황(톤/일)_하천방류 has 188 (3.6%) zerosZeros
일평균이용현황(톤/일)_도로청소 has 209 (4.0%) zerosZeros
일평균이용현황(톤/일)_건물용수 has 212 (4.1%) zerosZeros
미사용_하수도방류(톤/일) has 2832 (54.5%) zerosZeros

Reproduction

Analysis started2024-03-13 15:53:28.126915
Analysis finished2024-03-13 15:53:28.945354
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.8 KiB
1
3516 
2
1685 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 3516
67.6%
2 1685
32.4%

Length

2024-03-14T00:53:29.001728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T00:53:29.107224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3516
67.6%
2 1685
32.4%

관리기관
Categorical

Distinct36
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size40.8 KiB
한국전력공사 서울지역본부 및 남서울지역본부
2673 
㈜KT
875 
KT 강북, 서부, 중부
426 
통신구팀
 
176
서울본부 성동전력지사(02-2290-3354)
 
172
Other values (31)
879 

Length

Max length29
Median length23
Mean length17.931744
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울본부 성동전력지사(02-2290-3354)
2nd row서울본부 성동전력지사(02-2290-3354)
3rd row서울본부 성동전력지사(02-2290-3354)
4th row서울본부 성동전력지사(02-2290-3354)
5th row서울본부 성동전력지사(02-2290-3354)

Common Values

ValueCountFrequency (%)
한국전력공사 서울지역본부 및 남서울지역본부 2673
51.4%
㈜KT 875
 
16.8%
KT 강북, 서부, 중부 426
 
8.2%
통신구팀 176
 
3.4%
서울본부 성동전력지사(02-2290-3354) 172
 
3.3%
서울본부 중부전력지사(02-320-7352) 146
 
2.8%
서울본부 성동전력지사 (02-2290-3354) 86
 
1.7%
서울본부성동전력지사(02-2290-3319) 86
 
1.7%
서울본부중부전력지사(02-320-7352) 74
 
1.4%
서울본부 중부전력지사 (02-320-7352) 74
 
1.4%
Other values (26) 413
 
7.9%

Length

2024-03-14T00:53:29.219248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한국전력공사 2673
17.2%
및 2673
17.2%
남서울지역본부 2673
17.2%
서울지역본부 2673
17.2%
㈜kt 875
 
5.6%
kt 598
 
3.9%
서울본부 478
 
3.1%
강북 426
 
2.7%
서부 426
 
2.7%
중부 426
 
2.7%
Other values (40) 1592
10.3%

관리부서
Text

MISSING 

Distinct145
Distinct (%)2.9%
Missing155
Missing (%)3.0%
Memory size40.8 KiB
2024-03-14T00:53:29.468700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.5653983
Min length2

Characters and Unicode

Total characters43221
Distinct characters154
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row화양
2nd row뚝도인출
3rd row신내
4th row신내
5th row신내
ValueCountFrequency (%)
서울본부 1902
23.0%
성동전력지사 1062
12.8%
중부전력소 692
 
8.4%
남서울본부 571
 
6.9%
통신구팀 517
 
6.2%
kt 461
 
5.6%
강남전력지사 298
 
3.6%
중부전력지사 189
 
2.3%
전력구 136
 
1.6%
영등포전력지사 126
 
1.5%
Other values (135) 2321
28.0%
2024-03-14T00:53:29.879331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 3690
 
8.5%
3573
 
8.3%
서 2942
 
6.8%
전 2779
 
6.4%
울 2745
 
6.4%
력 2741
 
6.3%
본 2564
 
5.9%
지 2484
 
5.7%
사 2012
 
4.7%
동 1354
 
3.1%
Other values (144) 16337
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36667
84.8%
Space Separator 3573
 
8.3%
Lowercase Letter 922
 
2.1%
Decimal Number 592
 
1.4%
Uppercase Letter 404
 
0.9%
Open Punctuation 326
 
0.8%
Close Punctuation 326
 
0.8%
Dash Punctuation 222
 
0.5%
Other Punctuation 189
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 3690
 
10.1%
서 2942
 
8.0%
전 2779
 
7.6%
울 2745
 
7.5%
력 2741
 
7.5%
본 2564
 
7.0%
지 2484
 
6.8%
사 2012
 
5.5%
동 1354
 
3.7%
성 1262
 
3.4%
Other values (121) 12094
33.0%
Decimal Number
ValueCountFrequency (%)
2 192
32.4%
4 136
23.0%
3 116
19.6%
1 72
 
12.2%
6 36
 
6.1%
5 28
 
4.7%
7 8
 
1.4%
8 4
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
T 189
46.8%
K 189
46.8%
C 10
 
2.5%
I 8
 
2.0%
R 4
 
1.0%
M 2
 
0.5%
S 2
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
k 461
50.0%
t 461
50.0%
Other Punctuation
ValueCountFrequency (%)
# 188
99.5%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
3573
100.0%
Open Punctuation
ValueCountFrequency (%)
( 326
100.0%
Close Punctuation
ValueCountFrequency (%)
) 326
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 222
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36667
84.8%
Common 5228
 
12.1%
Latin 1326
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 3690
 
10.1%
서 2942
 
8.0%
전 2779
 
7.6%
울 2745
 
7.5%
력 2741
 
7.5%
본 2564
 
7.0%
지 2484
 
6.8%
사 2012
 
5.5%
동 1354
 
3.7%
성 1262
 
3.4%
Other values (121) 12094
33.0%
Common
ValueCountFrequency (%)
3573
68.3%
( 326
 
6.2%
) 326
 
6.2%
- 222
 
4.2%
2 192
 
3.7%
# 188
 
3.6%
4 136
 
2.6%
3 116
 
2.2%
1 72
 
1.4%
6 36
 
0.7%
Other values (4) 41
 
0.8%
Latin
ValueCountFrequency (%)
k 461
34.8%
t 461
34.8%
T 189
14.3%
K 189
14.3%
C 10
 
0.8%
I 8
 
0.6%
R 4
 
0.3%
M 2
 
0.2%
S 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36667
84.8%
ASCII 6554
 
15.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 3690
 
10.1%
서 2942
 
8.0%
전 2779
 
7.6%
울 2745
 
7.5%
력 2741
 
7.5%
본 2564
 
7.0%
지 2484
 
6.8%
사 2012
 
5.5%
동 1354
 
3.7%
성 1262
 
3.4%
Other values (121) 12094
33.0%
ASCII
ValueCountFrequency (%)
3573
54.5%
k 461
 
7.0%
t 461
 
7.0%
( 326
 
5.0%
) 326
 
5.0%
- 222
 
3.4%
2 192
 
2.9%
T 189
 
2.9%
K 189
 
2.9%
# 188
 
2.9%
Other values (13) 427
 
6.5%

시설물명
Text

Distinct564
Distinct (%)10.9%
Missing46
Missing (%)0.9%
Memory size40.8 KiB
2024-03-14T00:53:30.183094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length6.9784675
Min length2

Characters and Unicode

Total characters35974
Distinct characters312
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)2.6%

Sample

1st row용곡중학교
2nd row뚝도S/S PT실
3rd row화랑로입구
4th row북부간선1
5th row북부간선2
ValueCountFrequency (%)
통신구 405
 
5.7%
전력구 382
 
5.4%
미금-성동 254
 
3.6%
2호선 247
 
3.5%
3호선 222
 
3.1%
4호선 209
 
2.9%
서울시 208
 
2.9%
신내 180
 
2.5%
2호선통신구 116
 
1.6%
중부구내 99
 
1.4%
Other values (681) 4778
67.3%
2024-03-14T00:53:30.586695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3129
 
8.7%
구 2400
 
6.7%
신 1521
 
4.2%
호 1128
 
3.1%
선 1050
 
2.9%
통 945
 
2.6%
동 934
 
2.6%
- 816
 
2.3%
2 801
 
2.2%
전 766
 
2.1%
Other values (302) 22484
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26040
72.4%
Decimal Number 3364
 
9.4%
Space Separator 3129
 
8.7%
Dash Punctuation 816
 
2.3%
Open Punctuation 663
 
1.8%
Close Punctuation 663
 
1.8%
Other Punctuation 656
 
1.8%
Uppercase Letter 595
 
1.7%
Lowercase Letter 48
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2400
 
9.2%
신 1521
 
5.8%
호 1128
 
4.3%
선 1050
 
4.0%
통 945
 
3.6%
동 934
 
3.6%
전 766
 
2.9%
력 720
 
2.8%
수 711
 
2.7%
정 563
 
2.2%
Other values (272) 15302
58.8%
Uppercase Letter
ValueCountFrequency (%)
S 348
58.5%
R 58
 
9.7%
C 43
 
7.2%
I 38
 
6.4%
T 36
 
6.1%
K 29
 
4.9%
P 20
 
3.4%
B 9
 
1.5%
G 7
 
1.2%
L 6
 
1.0%
Decimal Number
ValueCountFrequency (%)
2 801
23.8%
4 596
17.7%
1 532
15.8%
3 507
15.1%
6 250
 
7.4%
5 193
 
5.7%
7 145
 
4.3%
8 124
 
3.7%
9 116
 
3.4%
0 100
 
3.0%
Other Punctuation
ValueCountFrequency (%)
# 436
66.5%
/ 164
 
25.0%
, 56
 
8.5%
Lowercase Letter
ValueCountFrequency (%)
k 24
50.0%
t 24
50.0%
Space Separator
ValueCountFrequency (%)
3129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 816
100.0%
Open Punctuation
ValueCountFrequency (%)
( 663
100.0%
Close Punctuation
ValueCountFrequency (%)
) 663
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26040
72.4%
Common 9291
 
25.8%
Latin 643
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2400
 
9.2%
신 1521
 
5.8%
호 1128
 
4.3%
선 1050
 
4.0%
통 945
 
3.6%
동 934
 
3.6%
전 766
 
2.9%
력 720
 
2.8%
수 711
 
2.7%
정 563
 
2.2%
Other values (272) 15302
58.8%
Common
ValueCountFrequency (%)
3129
33.7%
- 816
 
8.8%
2 801
 
8.6%
( 663
 
7.1%
) 663
 
7.1%
4 596
 
6.4%
1 532
 
5.7%
3 507
 
5.5%
# 436
 
4.7%
6 250
 
2.7%
Other values (7) 898
 
9.7%
Latin
ValueCountFrequency (%)
S 348
54.1%
R 58
 
9.0%
C 43
 
6.7%
I 38
 
5.9%
T 36
 
5.6%
K 29
 
4.5%
k 24
 
3.7%
t 24
 
3.7%
P 20
 
3.1%
B 9
 
1.4%
Other values (3) 14
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26040
72.4%
ASCII 9934
 
27.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3129
31.5%
- 816
 
8.2%
2 801
 
8.1%
( 663
 
6.7%
) 663
 
6.7%
4 596
 
6.0%
1 532
 
5.4%
3 507
 
5.1%
# 436
 
4.4%
S 348
 
3.5%
Other values (20) 1443
14.5%
Hangul
ValueCountFrequency (%)
구 2400
 
9.2%
신 1521
 
5.8%
호 1128
 
4.3%
선 1050
 
4.0%
통 945
 
3.6%
동 934
 
3.6%
전 766
 
2.9%
력 720
 
2.8%
수 711
 
2.7%
정 563
 
2.2%
Other values (272) 15302
58.8%

집수정명
Text

MISSING 

Distinct332
Distinct (%)16.9%
Missing3234
Missing (%)62.2%
Memory size40.8 KiB
2024-03-14T00:53:30.811494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length11.190646
Min length3

Characters and Unicode

Total characters22012
Distinct characters296
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.5%

Sample

1st row용곡중학교
2nd row뚝도S/S PT실
3rd row화랑로입구
4th row북부간선1
5th row북부간선2
ValueCountFrequency (%)
서울시 299
 
7.5%
집수정 132
 
3.3%
앞 105
 
2.6%
성북구 90
 
2.2%
서대문구 64
 
1.6%
동대문구 54
 
1.4%
종로구 50
 
1.2%
용산구 42
 
1.1%
마포구 42
 
1.1%
관악구 37
 
0.9%
Other values (467) 3085
77.1%
2024-03-14T00:53:31.168481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2092
 
9.5%
구 859
 
3.9%
로 637
 
2.9%
동 625
 
2.8%
( 600
 
2.7%
) 600
 
2.7%
1 531
 
2.4%
수 472
 
2.1%
서 449
 
2.0%
S 407
 
1.8%
Other values (286) 14740
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14626
66.4%
Decimal Number 2698
 
12.3%
Space Separator 2092
 
9.5%
Uppercase Letter 630
 
2.9%
Open Punctuation 600
 
2.7%
Close Punctuation 600
 
2.7%
Other Punctuation 455
 
2.1%
Dash Punctuation 247
 
1.1%
Lowercase Letter 64
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 859
 
5.9%
로 637
 
4.4%
동 625
 
4.3%
수 472
 
3.2%
서 449
 
3.1%
정 387
 
2.6%
시 368
 
2.5%
신 358
 
2.4%
앞 353
 
2.4%
울 340
 
2.3%
Other values (257) 9778
66.9%
Decimal Number
ValueCountFrequency (%)
1 531
19.7%
2 403
14.9%
4 356
13.2%
3 298
11.0%
6 249
9.2%
5 206
 
7.6%
7 190
 
7.0%
9 165
 
6.1%
8 159
 
5.9%
0 141
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
S 407
64.6%
R 50
 
7.9%
T 49
 
7.8%
K 41
 
6.5%
P 25
 
4.0%
C 21
 
3.3%
I 16
 
2.5%
B 11
 
1.7%
L 5
 
0.8%
G 5
 
0.8%
Other Punctuation
ValueCountFrequency (%)
/ 195
42.9%
# 190
41.8%
, 70
 
15.4%
Lowercase Letter
ValueCountFrequency (%)
t 32
50.0%
k 32
50.0%
Space Separator
ValueCountFrequency (%)
2092
100.0%
Open Punctuation
ValueCountFrequency (%)
( 600
100.0%
Close Punctuation
ValueCountFrequency (%)
) 600
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 247
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14626
66.4%
Common 6692
30.4%
Latin 694
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 859
 
5.9%
로 637
 
4.4%
동 625
 
4.3%
수 472
 
3.2%
서 449
 
3.1%
정 387
 
2.6%
시 368
 
2.5%
신 358
 
2.4%
앞 353
 
2.4%
울 340
 
2.3%
Other values (257) 9778
66.9%
Common
ValueCountFrequency (%)
2092
31.3%
( 600
 
9.0%
) 600
 
9.0%
1 531
 
7.9%
2 403
 
6.0%
4 356
 
5.3%
3 298
 
4.5%
6 249
 
3.7%
- 247
 
3.7%
5 206
 
3.1%
Other values (7) 1110
16.6%
Latin
ValueCountFrequency (%)
S 407
58.6%
R 50
 
7.2%
T 49
 
7.1%
K 41
 
5.9%
t 32
 
4.6%
k 32
 
4.6%
P 25
 
3.6%
C 21
 
3.0%
I 16
 
2.3%
B 11
 
1.6%
Other values (2) 10
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14626
66.4%
ASCII 7386
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2092
28.3%
( 600
 
8.1%
) 600
 
8.1%
1 531
 
7.2%
S 407
 
5.5%
2 403
 
5.5%
4 356
 
4.8%
3 298
 
4.0%
6 249
 
3.4%
- 247
 
3.3%
Other values (19) 1603
21.7%
Hangul
ValueCountFrequency (%)
구 859
 
5.9%
로 637
 
4.4%
동 625
 
4.3%
수 472
 
3.2%
서 449
 
3.1%
정 387
 
2.6%
시 368
 
2.5%
신 358
 
2.4%
앞 353
 
2.4%
울 340
 
2.3%
Other values (257) 9778
66.9%

집수정위치
Text

MISSING 

Distinct585
Distinct (%)11.5%
Missing109
Missing (%)2.1%
Memory size40.8 KiB
2024-03-14T00:53:31.455142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length32
Mean length12.272781
Min length3

Characters and Unicode

Total characters62493
Distinct characters320
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)2.1%

Sample

1st row용곡중학교
2nd row뚝도S/S PT실
3rd row화랑로입구
4th row북부간선1
5th row북부간선2
ValueCountFrequency (%)
서울시 520
 
4.6%
집수정 347
 
3.0%
성북구 282
 
2.5%
앞 281
 
2.5%
서울특별시 260
 
2.3%
서대문구 196
 
1.7%
성동구 185
 
1.6%
동대문구 175
 
1.5%
종로구 161
 
1.4%
용산구 134
 
1.2%
Other values (625) 8864
77.7%
2024-03-14T00:53:31.864631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6479
 
10.4%
구 2487
 
4.0%
로 2020
 
3.2%
동 1891
 
3.0%
( 1833
 
2.9%
) 1833
 
2.9%
1 1447
 
2.3%
S 1220
 
2.0%
서 1179
 
1.9%
2 1088
 
1.7%
Other values (310) 41016
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41127
65.8%
Decimal Number 7637
 
12.2%
Space Separator 6479
 
10.4%
Uppercase Letter 1882
 
3.0%
Open Punctuation 1833
 
2.9%
Close Punctuation 1833
 
2.9%
Other Punctuation 805
 
1.3%
Dash Punctuation 695
 
1.1%
Lowercase Letter 202
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2487
 
6.0%
로 2020
 
4.9%
동 1891
 
4.6%
서 1179
 
2.9%
앞 1032
 
2.5%
문 941
 
2.3%
대 939
 
2.3%
시 937
 
2.3%
성 836
 
2.0%
울 835
 
2.0%
Other values (279) 28030
68.2%
Uppercase Letter
ValueCountFrequency (%)
S 1220
64.8%
R 147
 
7.8%
T 147
 
7.8%
K 115
 
6.1%
P 80
 
4.3%
C 60
 
3.2%
I 46
 
2.4%
B 32
 
1.7%
G 19
 
1.0%
L 15
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 1447
18.9%
2 1088
14.2%
3 870
11.4%
4 836
10.9%
7 787
10.3%
6 658
8.6%
5 545
 
7.1%
0 483
 
6.3%
9 471
 
6.2%
8 452
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/ 590
73.3%
, 174
 
21.6%
# 41
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
k 96
47.5%
t 96
47.5%
s 10
 
5.0%
Space Separator
ValueCountFrequency (%)
6479
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1833
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1833
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 695
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41126
65.8%
Common 19282
30.9%
Latin 2084
 
3.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2487
 
6.0%
로 2020
 
4.9%
동 1891
 
4.6%
서 1179
 
2.9%
앞 1032
 
2.5%
문 941
 
2.3%
대 939
 
2.3%
시 937
 
2.3%
성 836
 
2.0%
울 835
 
2.0%
Other values (278) 28029
68.2%
Common
ValueCountFrequency (%)
6479
33.6%
( 1833
 
9.5%
) 1833
 
9.5%
1 1447
 
7.5%
2 1088
 
5.6%
3 870
 
4.5%
4 836
 
4.3%
7 787
 
4.1%
- 695
 
3.6%
6 658
 
3.4%
Other values (7) 2756
14.3%
Latin
ValueCountFrequency (%)
S 1220
58.5%
R 147
 
7.1%
T 147
 
7.1%
K 115
 
5.5%
k 96
 
4.6%
t 96
 
4.6%
P 80
 
3.8%
C 60
 
2.9%
I 46
 
2.2%
B 32
 
1.5%
Other values (4) 45
 
2.2%
Han
ValueCountFrequency (%)
下 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41126
65.8%
ASCII 21366
34.2%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6479
30.3%
( 1833
 
8.6%
) 1833
 
8.6%
1 1447
 
6.8%
S 1220
 
5.7%
2 1088
 
5.1%
3 870
 
4.1%
4 836
 
3.9%
7 787
 
3.7%
- 695
 
3.3%
Other values (21) 4278
20.0%
Hangul
ValueCountFrequency (%)
구 2487
 
6.0%
로 2020
 
4.9%
동 1891
 
4.6%
서 1179
 
2.9%
앞 1032
 
2.5%
문 941
 
2.3%
대 939
 
2.3%
시 937
 
2.3%
성 836
 
2.0%
울 835
 
2.0%
Other values (278) 28029
68.2%
CJK
ValueCountFrequency (%)
下 1
100.0%

자치구
Text

MISSING 

Distinct66
Distinct (%)1.3%
Missing155
Missing (%)3.0%
Memory size40.8 KiB
2024-03-14T00:53:32.054084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.1783591
Min length2

Characters and Unicode

Total characters16038
Distinct characters50
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.5%

Sample

1st row광진구
2nd row광진구
3rd row노원구
4th row중랑구
5th row중랑구
ValueCountFrequency (%)
마포구 636
 
12.1%
동대문구 421
 
8.0%
성북구 366
 
7.0%
서초구 329
 
6.3%
중랑구 325
 
6.2%
종로구 313
 
6.0%
서대문구 292
 
5.6%
성동구 276
 
5.3%
용산구 271
 
5.2%
중구 262
 
5.0%
Other values (46) 1754
33.4%
2024-03-14T00:53:32.406904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 5032
31.4%
동 736
 
4.6%
중 727
 
4.5%
대 713
 
4.4%
문 713
 
4.4%
서 699
 
4.4%
포 686
 
4.3%
성 642
 
4.0%
마 636
 
4.0%
북 499
 
3.1%
Other values (40) 4955
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15318
95.5%
Space Separator 340
 
2.1%
Decimal Number 234
 
1.5%
Other Punctuation 71
 
0.4%
Uppercase Letter 54
 
0.3%
Lowercase Letter 13
 
0.1%
Math Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 5032
32.9%
동 736
 
4.8%
중 727
 
4.7%
대 713
 
4.7%
문 713
 
4.7%
서 699
 
4.6%
포 686
 
4.5%
성 642
 
4.2%
마 636
 
4.2%
북 499
 
3.3%
Other values (26) 4235
27.6%
Decimal Number
ValueCountFrequency (%)
2 97
41.5%
1 43
18.4%
3 32
 
13.7%
5 27
 
11.5%
4 19
 
8.1%
9 9
 
3.8%
7 6
 
2.6%
6 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 48
67.6%
. 23
32.4%
Space Separator
ValueCountFrequency (%)
340
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 54
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 13
100.0%
Math Symbol
ValueCountFrequency (%)
× 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15318
95.5%
Common 653
 
4.1%
Latin 67
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 5032
32.9%
동 736
 
4.8%
중 727
 
4.7%
대 713
 
4.7%
문 713
 
4.7%
서 699
 
4.6%
포 686
 
4.5%
성 642
 
4.2%
마 636
 
4.2%
북 499
 
3.3%
Other values (26) 4235
27.6%
Common
ValueCountFrequency (%)
340
52.1%
2 97
 
14.9%
, 48
 
7.4%
1 43
 
6.6%
3 32
 
4.9%
5 27
 
4.1%
. 23
 
3.5%
4 19
 
2.9%
9 9
 
1.4%
× 8
 
1.2%
Other values (2) 7
 
1.1%
Latin
ValueCountFrequency (%)
X 54
80.6%
x 13
 
19.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15318
95.5%
ASCII 712
 
4.4%
None 8
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 5032
32.9%
동 736
 
4.8%
중 727
 
4.7%
대 713
 
4.7%
문 713
 
4.7%
서 699
 
4.6%
포 686
 
4.5%
성 642
 
4.2%
마 636
 
4.2%
북 499
 
3.3%
Other values (26) 4235
27.6%
ASCII
ValueCountFrequency (%)
340
47.8%
2 97
 
13.6%
X 54
 
7.6%
, 48
 
6.7%
1 43
 
6.0%
3 32
 
4.5%
5 27
 
3.8%
. 23
 
3.2%
4 19
 
2.7%
x 13
 
1.8%
Other values (3) 16
 
2.2%
None
ValueCountFrequency (%)
× 8
100.0%

유출시설(kw)
Text

MISSING 

Distinct138
Distinct (%)2.7%
Missing156
Missing (%)3.0%
Memory size40.8 KiB
2024-03-14T00:53:32.589645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length6.8570862
Min length4

Characters and Unicode

Total characters34594
Distinct characters20
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

Unique19 ?
Unique (%)0.4%

Sample

1st row15 × 2
2nd row0.75 × 1
3rd row2.2 × 2
4th row2.2 × 2
5th row2.2 × 2
ValueCountFrequency (%)
× 2448
19.9%
2 2038
16.6%
×2 946
 
7.7%
22 686
 
5.6%
x 549
 
4.5%
15 475
 
3.9%
5.5 465
 
3.8%
4 337
 
2.7%
1 326
 
2.7%
3.7kw 325
 
2.6%
Other values (57) 3706
30.1%
2024-03-14T00:53:33.183273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7345
21.2%
2 6679
19.3%
× 3552
10.3%
5 3128
9.0%
. 2546
 
7.4%
1 2476
 
7.2%
3 1600
 
4.6%
k 1581
 
4.6%
W 1531
 
4.4%
X 1259
 
3.6%
Other values (10) 2897
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16175
46.8%
Space Separator 7345
21.2%
Math Symbol 3552
 
10.3%
Uppercase Letter 2790
 
8.1%
Other Punctuation 2691
 
7.8%
Lowercase Letter 2041
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6679
41.3%
5 3128
19.3%
1 2476
 
15.3%
3 1600
 
9.9%
7 1060
 
6.6%
4 667
 
4.1%
0 345
 
2.1%
9 181
 
1.1%
8 21
 
0.1%
6 18
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 2546
94.6%
, 98
 
3.6%
* 47
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
k 1581
77.5%
x 410
 
20.1%
w 50
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
W 1531
54.9%
X 1259
45.1%
Space Separator
ValueCountFrequency (%)
7345
100.0%
Math Symbol
ValueCountFrequency (%)
× 3552
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29763
86.0%
Latin 4831
 
14.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7345
24.7%
2 6679
22.4%
× 3552
11.9%
5 3128
10.5%
. 2546
 
8.6%
1 2476
 
8.3%
3 1600
 
5.4%
7 1060
 
3.6%
4 667
 
2.2%
0 345
 
1.2%
Other values (5) 365
 
1.2%
Latin
ValueCountFrequency (%)
k 1581
32.7%
W 1531
31.7%
X 1259
26.1%
x 410
 
8.5%
w 50
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31042
89.7%
None 3552
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7345
23.7%
2 6679
21.5%
5 3128
10.1%
. 2546
 
8.2%
1 2476
 
8.0%
3 1600
 
5.2%
k 1581
 
5.1%
W 1531
 
4.9%
X 1259
 
4.1%
7 1060
 
3.4%
Other values (9) 1837
 
5.9%
None
ValueCountFrequency (%)
× 3552
100.0%

조사명
Categorical

Distinct19
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size40.8 KiB
2018년 하반기 : 2018.6월~12월
 
351
2022년 하반기 : 2022.7월~12월
 
307
2019년 하반기 : 2019.7월~12월
 
307
2019년 상반기 : 2019.1월~6월
 
307
2018년 상반기 : 2018.1월~6월
 
307
Other values (14)
3622 

Length

Max length23
Median length22
Mean length20.953663
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022년 하반기 : 2022.7월~12월
2nd row2022년 하반기 : 2022.7월~12월
3rd row2022년 하반기 : 2022.7월~12월
4th row2022년 하반기 : 2022.7월~12월
5th row2022년 하반기 : 2022.7월~12월

Common Values

ValueCountFrequency (%)
2018년 하반기 : 2018.6월~12월 351
 
6.7%
2022년 하반기 : 2022.7월~12월 307
 
5.9%
2019년 하반기 : 2019.7월~12월 307
 
5.9%
2019년 상반기 : 2019.1월~6월 307
 
5.9%
2018년 상반기 : 2018.1월~6월 307
 
5.9%
2020년 상반기 : 2020.1월~6월 307
 
5.9%
2021년 상반기 : 2021.1월~6월 307
 
5.9%
2021년 하반기 : 2021.7월~12월 307
 
5.9%
2016년 하반기 : 2016.7월~12월 306
 
5.9%
2022년 상반기 : 2022.1월~6월 306
 
5.9%
Other values (9) 2089
40.2%

Length

2024-03-14T00:53:33.339079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4605
23.5%
상반기 2602
13.3%
하반기 2599
13.3%
2018년 658
 
3.4%
2019년 614
 
3.1%
2021년 614
 
3.1%
2022년 613
 
3.1%
2016년 611
 
3.1%
2017년 610
 
3.1%
2015년 610
 
3.1%
Other values (19) 5476
27.9%

조사년도
Real number (ℝ)

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.105
Minimum2014
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-03-14T00:53:33.438427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12016
median2018
Q32020
95-th percentile2022
Maximum2022
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.5116146
Coefficient of variation (CV)0.0012445411
Kurtosis-1.1836752
Mean2018.105
Median Absolute Deviation (MAD)2
Skewness0.021651423
Sum10496164
Variance6.3082079
MonotonicityDecreasing
2024-03-14T00:53:33.551984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2018 658
12.7%
2021 614
11.8%
2019 614
11.8%
2022 613
11.8%
2016 611
11.7%
2017 610
11.7%
2015 610
11.7%
2020 464
8.9%
2014 407
7.8%
ValueCountFrequency (%)
2014 407
7.8%
2015 610
11.7%
2016 611
11.7%
2017 610
11.7%
2018 658
12.7%
2019 614
11.8%
2020 464
8.9%
2021 614
11.8%
2022 613
11.8%
ValueCountFrequency (%)
2022 613
11.8%
2021 614
11.8%
2020 464
8.9%
2019 614
11.8%
2018 658
12.7%
2017 610
11.7%
2016 611
11.7%
2015 610
11.7%
2014 407
7.8%

총발생량(톤)
Real number (ℝ)

MISSING  ZEROS 

Distinct1769
Distinct (%)37.0%
Missing424
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean17683.331
Minimum0
Maximum289600
Zeros2032
Zeros (%)39.1%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-03-14T00:53:33.676810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median458
Q322386
95-th percentile82005.924
Maximum289600
Range289600
Interquartile range (IQR)22386

Descriptive statistics

Standard deviation35303.347
Coefficient of variation (CV)1.9964195
Kurtosis15.06987
Mean17683.331
Median Absolute Deviation (MAD)458
Skewness3.4014612
Sum84473273
Variance1.2463263 × 109
MonotonicityNot monotonic
2024-03-14T00:53:33.820366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2032
39.1%
184.0 28
 
0.5%
1840.0 27
 
0.5%
1810.0 18
 
0.3%
43240.0 17
 
0.3%
1656.0 11
 
0.2%
24288.0 11
 
0.2%
1472.0 11
 
0.2%
905.0 11
 
0.2%
9936.0 9
 
0.2%
Other values (1759) 2602
50.0%
(Missing) 424
 
8.2%
ValueCountFrequency (%)
0.0 2032
39.1%
0.6 2
 
< 0.1%
0.9 3
 
0.1%
0.92 3
 
0.1%
1.0 3
 
0.1%
1.11 1
 
< 0.1%
1.64 3
 
0.1%
1.73 3
 
0.1%
1.81 3
 
0.1%
2.0 4
 
0.1%
ValueCountFrequency (%)
289600.0 1
 
< 0.1%
270390.0 1
 
< 0.1%
268308.8 1
 
< 0.1%
267940.8 2
< 0.1%
267518.0 2
< 0.1%
265428.8 1
 
< 0.1%
265415.0 1
 
< 0.1%
263572.2 2
< 0.1%
263536.0 3
0.1%
263230.4 1
 
< 0.1%

일평균발생량(톤/일)
Real number (ℝ)

MISSING  ZEROS 

Distinct1268
Distinct (%)29.6%
Missing922
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean114.24503
Minimum0
Maximum1600
Zeros1403
Zeros (%)27.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-03-14T00:53:33.963188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12
Q3146.795
95-th percentile475.3
Maximum1600
Range1600
Interquartile range (IQR)146.795

Descriptive statistics

Standard deviation205.53828
Coefficient of variation (CV)1.7991004
Kurtosis12.652239
Mean114.24503
Median Absolute Deviation (MAD)12
Skewness3.1181659
Sum488854.5
Variance42245.986
MonotonicityNot monotonic
2024-03-14T00:53:34.088048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1403
27.0%
1.0 77
 
1.5%
10.0 57
 
1.1%
5.0 38
 
0.7%
235.0 28
 
0.5%
2.0 27
 
0.5%
132.0 25
 
0.5%
9.0 23
 
0.4%
8.0 23
 
0.4%
12.0 22
 
0.4%
Other values (1258) 2556
49.1%
(Missing) 922
 
17.7%
ValueCountFrequency (%)
0.0 1403
27.0%
0.01 20
 
0.4%
0.02 16
 
0.3%
0.03 6
 
0.1%
0.04 14
 
0.3%
0.05 2
 
< 0.1%
0.06 1
 
< 0.1%
0.07 7
 
0.1%
0.08 8
 
0.2%
0.09 1
 
< 0.1%
ValueCountFrequency (%)
1600.0 1
 
< 0.1%
1478.0 3
0.1%
1469.51 1
 
< 0.1%
1466.38 1
 
< 0.1%
1458.4 1
 
< 0.1%
1458.2 1
 
< 0.1%
1456.2 4
0.1%
1456.0 3
0.1%
1430.64 1
 
< 0.1%
1430.6 1
 
< 0.1%

일평균이용현황(톤/일)_하천방류
Real number (ℝ)

MISSING  ZEROS 

Distinct616
Distinct (%)39.5%
Missing3643
Missing (%)70.0%
Infinite0
Infinite (%)0.0%
Mean238.60563
Minimum0
Maximum1478
Zeros188
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-03-14T00:53:34.218184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q172
median156
Q3332.2075
95-th percentile803.85
Maximum1478
Range1478
Interquartile range (IQR)260.2075

Descriptive statistics

Standard deviation259.39243
Coefficient of variation (CV)1.0871178
Kurtosis5.6194595
Mean238.60563
Median Absolute Deviation (MAD)120.5
Skewness2.1258354
Sum371747.57
Variance67284.435
MonotonicityNot monotonic
2024-03-14T00:53:34.352861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 188
 
3.6%
235.0 28
 
0.5%
132.0 25
 
0.5%
108.0 16
 
0.3%
25.0 15
 
0.3%
105.0 15
 
0.3%
40.0 15
 
0.3%
450.0 14
 
0.3%
10.0 14
 
0.3%
219.0 14
 
0.3%
Other values (606) 1214
 
23.3%
(Missing) 3643
70.0%
ValueCountFrequency (%)
0.0 188
3.6%
0.04 1
 
< 0.1%
0.33 1
 
< 0.1%
3.0 1
 
< 0.1%
5.0 9
 
0.2%
6.0 4
 
0.1%
8.71 1
 
< 0.1%
9.0 1
 
< 0.1%
9.67 2
 
< 0.1%
9.78 1
 
< 0.1%
ValueCountFrequency (%)
1478.0 4
0.1%
1469.51 1
 
< 0.1%
1458.4 1
 
< 0.1%
1456.2 4
0.1%
1456.0 2
< 0.1%
1430.64 1
 
< 0.1%
1430.6 1
 
< 0.1%
1428.32 1
 
< 0.1%
1390.0 1
 
< 0.1%
1318.48 1
 
< 0.1%

일평균이용현황(톤/일)_도로청소
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)12.6%
Missing4955
Missing (%)95.3%
Infinite0
Infinite (%)0.0%
Mean12.514431
Minimum0
Maximum270
Zeros209
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-03-14T00:53:34.518290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile108
Maximum270
Range270
Interquartile range (IQR)0

Descriptive statistics

Standard deviation43.146056
Coefficient of variation (CV)3.4477042
Kurtosis19.486338
Mean12.514431
Median Absolute Deviation (MAD)0
Skewness4.2469467
Sum3078.55
Variance1861.5821
MonotonicityNot monotonic
2024-03-14T00:53:34.658589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 209
 
4.0%
264.0 3
 
0.1%
1.32 2
 
< 0.1%
100.0 2
 
< 0.1%
45.0 2
 
< 0.1%
108.0 2
 
< 0.1%
31.0 2
 
< 0.1%
190.0 1
 
< 0.1%
111.0 1
 
< 0.1%
55.0 1
 
< 0.1%
Other values (21) 21
 
0.4%
(Missing) 4955
95.3%
ValueCountFrequency (%)
0.0 209
4.0%
1.32 2
 
< 0.1%
3.0 1
 
< 0.1%
4.0 1
 
< 0.1%
4.1 1
 
< 0.1%
5.3 1
 
< 0.1%
5.53 1
 
< 0.1%
6.0 1
 
< 0.1%
7.0 1
 
< 0.1%
10.0 1
 
< 0.1%
ValueCountFrequency (%)
270.0 1
 
< 0.1%
264.0 3
0.1%
190.0 1
 
< 0.1%
130.0 1
 
< 0.1%
120.0 1
 
< 0.1%
114.0 1
 
< 0.1%
113.48 1
 
< 0.1%
111.0 1
 
< 0.1%
110.0 1
 
< 0.1%
109.0 1
 
< 0.1%

일평균이용현황(톤/일)_공원용수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.8 KiB
<NA>
5198 
0
 
3

Length

Max length4
Median length4
Mean length3.9982696
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5198
99.9%
0 3
 
0.1%

Length

2024-03-14T00:53:34.774163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T00:53:34.857593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5198
99.9%
0 3
 
0.1%

일평균이용현황(톤/일)_화장실세척
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)88.5%
Missing5175
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean420.36077
Minimum0
Maximum1600
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-03-14T00:53:34.941358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile96.5
Q1293.2275
median317.5
Q3340
95-th percentile1355.75
Maximum1600
Range1600
Interquartile range (IQR)46.7725

Descriptive statistics

Standard deviation400.53121
Coefficient of variation (CV)0.95282729
Kurtosis3.315585
Mean420.36077
Median Absolute Deviation (MAD)25
Skewness1.9687503
Sum10929.38
Variance160425.25
MonotonicityNot monotonic
2024-03-14T00:53:35.053551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
312.0 2
 
< 0.1%
310.0 2
 
< 0.1%
320.0 2
 
< 0.1%
95.0 1
 
< 0.1%
332.0 1
 
< 0.1%
693.0 1
 
< 0.1%
691.0 1
 
< 0.1%
1390.0 1
 
< 0.1%
1600.0 1
 
< 0.1%
0.0 1
 
< 0.1%
Other values (13) 13
 
0.2%
(Missing) 5175
99.5%
ValueCountFrequency (%)
0.0 1
< 0.1%
95.0 1
< 0.1%
101.0 1
< 0.1%
104.0 1
< 0.1%
106.0 1
< 0.1%
106.97 1
< 0.1%
292.0 1
< 0.1%
296.91 1
< 0.1%
310.0 2
< 0.1%
312.0 2
< 0.1%
ValueCountFrequency (%)
1600.0 1
< 0.1%
1390.0 1
< 0.1%
1253.0 1
< 0.1%
693.0 1
< 0.1%
691.0 1
< 0.1%
343.9 1
< 0.1%
342.0 1
< 0.1%
334.0 1
< 0.1%
332.0 1
< 0.1%
328.0 1
< 0.1%

일평균이용현황(톤/일)_건물용수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)4.5%
Missing4980
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean8.3866968
Minimum0
Maximum672
Zeros212
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-03-14T00:53:35.160289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum672
Range672
Interquartile range (IQR)0

Descriptive statistics

Standard deviation64.455618
Coefficient of variation (CV)7.6854594
Kurtosis79.292824
Mean8.3866968
Median Absolute Deviation (MAD)0
Skewness8.806315
Sum1853.46
Variance4154.5267
MonotonicityNot monotonic
2024-03-14T00:53:35.252450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 212
 
4.1%
28.5 1
 
< 0.1%
33.0 1
 
< 0.1%
33.35 1
 
< 0.1%
29.0 1
 
< 0.1%
48.61 1
 
< 0.1%
48.88 1
 
< 0.1%
415.12 1
 
< 0.1%
545.0 1
 
< 0.1%
672.0 1
 
< 0.1%
(Missing) 4980
95.8%
ValueCountFrequency (%)
0.0 212
4.1%
28.5 1
 
< 0.1%
29.0 1
 
< 0.1%
33.0 1
 
< 0.1%
33.35 1
 
< 0.1%
48.61 1
 
< 0.1%
48.88 1
 
< 0.1%
415.12 1
 
< 0.1%
545.0 1
 
< 0.1%
672.0 1
 
< 0.1%
ValueCountFrequency (%)
672.0 1
 
< 0.1%
545.0 1
 
< 0.1%
415.12 1
 
< 0.1%
48.88 1
 
< 0.1%
48.61 1
 
< 0.1%
33.35 1
 
< 0.1%
33.0 1
 
< 0.1%
29.0 1
 
< 0.1%
28.5 1
 
< 0.1%
0.0 212
4.1%

미사용_하수도방류(톤/일)
Real number (ℝ)

MISSING  ZEROS 

Distinct668
Distinct (%)15.9%
Missing992
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean22.514193
Minimum0
Maximum978.56
Zeros2832
Zeros (%)54.5%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2024-03-14T00:53:35.382404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.22
95-th percentile159.888
Maximum978.56
Range978.56
Interquartile range (IQR)2.22

Descriptive statistics

Standard deviation76.074862
Coefficient of variation (CV)3.3789734
Kurtosis34.365673
Mean22.514193
Median Absolute Deviation (MAD)0
Skewness5.237649
Sum94762.24
Variance5787.3846
MonotonicityNot monotonic
2024-03-14T00:53:35.548122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2832
54.5%
1.0 76
 
1.5%
10.0 36
 
0.7%
0.01 32
 
0.6%
5.0 29
 
0.6%
2.0 27
 
0.5%
8.0 22
 
0.4%
9.0 21
 
0.4%
4.0 20
 
0.4%
11.0 18
 
0.3%
Other values (658) 1096
 
21.1%
(Missing) 992
 
19.1%
ValueCountFrequency (%)
0.0 2832
54.5%
0.01 32
 
0.6%
0.02 7
 
0.1%
0.03 5
 
0.1%
0.04 11
 
0.2%
0.05 2
 
< 0.1%
0.07 5
 
0.1%
0.08 3
 
0.1%
0.09 1
 
< 0.1%
0.1 6
 
0.1%
ValueCountFrequency (%)
978.56 1
< 0.1%
817.35 1
< 0.1%
762.0 1
< 0.1%
730.0 1
< 0.1%
724.1 1
< 0.1%
714.13 1
< 0.1%
707.07 2
< 0.1%
661.0 1
< 0.1%
629.71 1
< 0.1%
585.0 1
< 0.1%

방류하천명
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size40.8 KiB
<NA>
3987 
정릉천
 
167
성북천
 
129
하수도
 
101
안양천
 
96
Other values (28)
721 

Length

Max length12
Median length4
Mean length3.7658143
Min length2

Unique

Unique7 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3987
76.7%
정릉천 167
 
3.2%
성북천 129
 
2.5%
하수도 101
 
1.9%
안양천 96
 
1.8%
욱천 90
 
1.7%
청계천 88
 
1.7%
홍제천 84
 
1.6%
불광천 81
 
1.6%
안암천 60
 
1.2%
Other values (23) 318
 
6.1%

Length

2024-03-14T00:53:35.676617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3987
76.6%
정릉천 167
 
3.2%
성북천 129
 
2.5%
하수도 101
 
1.9%
안양천 96
 
1.8%
욱천 90
 
1.7%
청계천 89
 
1.7%
홍제천 84
 
1.6%
불광천 81
 
1.6%
안암천 60
 
1.2%
Other values (21) 323
 
6.2%

방류일
Text

MISSING 

Distinct56
Distinct (%)29.9%
Missing5014
Missing (%)96.4%
Memory size40.8 KiB
2024-03-14T00:53:35.853487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.802139
Min length6

Characters and Unicode

Total characters1646
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)4.8%

Sample

1st row'17.9.5
2nd row2008.9
3rd row2008.9
4th row2006.12.10
5th row2006.11
ValueCountFrequency (%)
05.09.25 30
 
12.4%
2009 22
 
9.1%
8 12
 
5.0%
2006.12.10 8
 
3.3%
2007.6.12 8
 
3.3%
2008.7 8
 
3.3%
15.12.04 7
 
2.9%
13.08.01 6
 
2.5%
2007.8.12 6
 
2.5%
05 6
 
2.5%
Other values (51) 128
53.1%
2024-03-14T00:53:36.209006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 401
24.4%
. 335
20.4%
2 227
13.8%
1 185
11.2%
5 117
 
7.1%
9 104
 
6.3%
8 65
 
3.9%
54
 
3.3%
' 53
 
3.2%
6 30
 
1.8%
Other values (3) 75
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1204
73.1%
Other Punctuation 388
 
23.6%
Space Separator 54
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 401
33.3%
2 227
18.9%
1 185
15.4%
5 117
 
9.7%
9 104
 
8.6%
8 65
 
5.4%
6 30
 
2.5%
3 29
 
2.4%
7 26
 
2.2%
4 20
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 335
86.3%
' 53
 
13.7%
Space Separator
ValueCountFrequency (%)
54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1646
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 401
24.4%
. 335
20.4%
2 227
13.8%
1 185
11.2%
5 117
 
7.1%
9 104
 
6.3%
8 65
 
3.9%
54
 
3.3%
' 53
 
3.2%
6 30
 
1.8%
Other values (3) 75
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1646
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 401
24.4%
. 335
20.4%
2 227
13.8%
1 185
11.2%
5 117
 
7.1%
9 104
 
6.3%
8 65
 
3.9%
54
 
3.3%
' 53
 
3.2%
6 30
 
1.8%
Other values (3) 75
 
4.6%

하천관로길이
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5201
Missing (%)100.0%
Memory size45.8 KiB

Sample

구분코드관리기관관리부서시설물명집수정명집수정위치자치구유출시설(kw)조사명조사년도총발생량(톤)일평균발생량(톤/일)일평균이용현황(톤/일)_하천방류일평균이용현황(톤/일)_도로청소일평균이용현황(톤/일)_공원용수일평균이용현황(톤/일)_화장실세척일평균이용현황(톤/일)_건물용수미사용_하수도방류(톤/일)방류하천명방류일하천관로길이
01서울본부 성동전력지사(02-2290-3354)화양용곡중학교용곡중학교용곡중학교광진구15 × 22022년 하반기 : 2022.7월~12월20220.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
11서울본부 성동전력지사(02-2290-3354)뚝도인출뚝도S/S PT실뚝도S/S PT실뚝도S/S PT실광진구0.75 × 12022년 하반기 : 2022.7월~12월20220.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
21서울본부 성동전력지사(02-2290-3354)신내화랑로입구화랑로입구화랑로입구노원구2.2 × 22022년 하반기 : 2022.7월~12월20220.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
31서울본부 성동전력지사(02-2290-3354)신내북부간선1북부간선1북부간선1중랑구2.2 × 22022년 하반기 : 2022.7월~12월20220.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
41서울본부 성동전력지사(02-2290-3354)신내북부간선2북부간선2북부간선2중랑구2.2 × 22022년 하반기 : 2022.7월~12월20220.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51서울본부 성동전력지사(02-2290-3354)신내근린공원근린공원근린공원중랑구2.2 × 22022년 하반기 : 2022.7월~12월20220.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
61서울본부 성동전력지사(02-2290-3354)신내인출신내S/S 인출 간이신내S/S 인출 간이신내S/S 인출 간이중랑구0.75 × 12022년 하반기 : 2022.7월~12월20220.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
71서울본부 성동전력지사(02-2290-3354)4호선강북웨딩홀강북웨딩홀강북웨딩홀강북구5.5 × 22022년 하반기 : 2022.7월~12월20220.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
81서울본부 성동전력지사(02-2290-3354)4호선수유역사수유역사수유역사강북구11 × 1, 5.5 × 12022년 하반기 : 2022.7월~12월202210616.857.7<NA><NA><NA><NA><NA><NA><NA><NA><NA>
91서울본부 성동전력지사(02-2290-3354)4호선전소아과의원전소아과의원전소아과의원강북구5.5 × 22022년 하반기 : 2022.7월~12월20220.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
구분코드관리기관관리부서시설물명집수정명집수정위치자치구유출시설(kw)조사명조사년도총발생량(톤)일평균발생량(톤/일)일평균이용현황(톤/일)_하천방류일평균이용현황(톤/일)_도로청소일평균이용현황(톤/일)_공원용수일평균이용현황(톤/일)_화장실세척일평균이용현황(톤/일)_건물용수미사용_하수도방류(톤/일)방류하천명방류일하천관로길이
51911한국전력공사 서울지역본부 및 남서울지역본부서울지역본부 중부전력지사원남-운니(서울대병원정문)<NA>서울대병원정문종로구2.2 × 12014년 하반기 : 2014.7월~12월2014184.01.0<NA><NA><NA><NA><NA>1.0<NA><NA><NA>
51921한국전력공사 서울지역본부 및 남서울지역본부서울지역본부 중부전력지사재동-을지로(낙원상가)<NA>교동초등학교종로구15 × 42014년 하반기 : 2014.7월~12월20148119.044.13<NA><NA><NA><NA><NA>44.13<NA><NA><NA>
51931한국전력공사 서울지역본부 및 남서울지역본부서울지역본부 중부전력지사재동-을지로(재동R)<NA>안국역종로구15 × 32014년 하반기 : 2014.7월~12월20143287.017.86<NA><NA><NA><NA><NA>17.86<NA><NA><NA>
51941한국전력공사 서울지역본부 및 남서울지역본부서울지역본부 중부전력지사옥인인출(환기구2)<NA>진이비인후과(모놀제화)종로구5.5 × 22014년 하반기 : 2014.7월~12월2014184.01.0<NA><NA><NA><NA><NA>1.0<NA><NA><NA>
51952KT 강북, 서부, 중부통신구팀2호선통신구<NA>중구 을지로264중 구7.5x22014년 하반기 : 2014.7월~12월201410672.058.0<NA><NA><NA><NA><NA>58.0<NA><NA><NA>
51962KT 강북, 서부, 중부통신구팀2호선통신구<NA>중구 을지로79 (분기구)중 구3.7X22014년 하반기 : 2014.7월~12월2014368.02.0<NA><NA><NA><NA><NA>2.0<NA><NA><NA>
51972KT 강북, 서부, 중부통신구팀2호선통신구<NA>중구 명동2길24 (중앙지사 동도앞)중 구3.7x22014년 하반기 : 2014.7월~12월2014368.02.0<NA><NA><NA><NA><NA>2.0<NA><NA><NA>
51982KT 강북, 서부, 중부통신구팀2호선통신구<NA>중구 서소문로131 (시청앞수직구)중 구11x22014년 하반기 : 2014.7월~12월20142392.013.0<NA><NA><NA><NA><NA>13.0<NA><NA><NA>
51992KT 강북, 서부, 중부통신구팀2호선통신구<NA>중구 퇴계로433 (중앙시장앞)중 구11X42014년 하반기 : 2014.7월~12월20143864.021.0<NA><NA><NA><NA><NA>21.0<NA><NA><NA>
52002KT 강북, 서부, 중부통신구팀2호선통신구<NA>중구 청파로456 (경제신문사)중 구7.5x22014년 하반기 : 2014.7월~12월201426680.0145.0145.0<NA><NA><NA><NA><NA>욱천<NA><NA>

Duplicate rows

Most frequently occurring

구분코드관리기관관리부서시설물명집수정명집수정위치자치구유출시설(kw)조사명조사년도총발생량(톤)일평균발생량(톤/일)일평균이용현황(톤/일)_하천방류일평균이용현황(톤/일)_도로청소일평균이용현황(톤/일)_공원용수일평균이용현황(톤/일)_화장실세척일평균이용현황(톤/일)_건물용수미사용_하수도방류(톤/일)방류하천명방류일# duplicates
01남서울본부 강남전력지사 (02-3496-9325)우면한국통신건너편한국통신건너편한국통신건너편서초구3.7kW × 22021년 상반기 : 2021.1월~6월20210.00.0<NA><NA><NA><NA><NA>0.0하수도<NA>2
11남서울본부 강남전력지사(02-3496-9325)우면한국통신건너편한국통신건너편한국통신건너편서초구3.7kW × 22022년 하반기 : 2022.7월~12월20220.00.0<NA><NA><NA><NA><NA><NA><NA><NA>2
21남서울본부강남전력지사(02-3496-9325)우면한국통신건너편한국통신건너편한국통신건너편서초구3.7kW × 22021년 하반기 : 2021.7월~12월20210.00.0<NA><NA><NA><NA><NA>0.0하수도<NA>2
31한국전력공사 서울지역본부 및 남서울지역본부남서울본부 강남전력지사우면<NA>한국통신건너편서초구3.7kW × 22015년 하반기 : 2015.7월~12월2015<NA>0.0<NA><NA><NA><NA><NA>0.0<NA><NA>2
41한국전력공사 서울지역본부 및 남서울지역본부남서울본부 강남전력지사우면<NA>한국통신건너편서초구3.7kW × 22016년 상반기 : 2016.1월~6월2016<NA>0.0<NA><NA><NA><NA><NA>0.0<NA><NA>2
51한국전력공사 서울지역본부 및 남서울지역본부남서울본부 강남전력지사우면<NA>한국통신건너편서초구3.7kW × 22016년 하반기 : 2016.7월~12월20160.00.0<NA><NA><NA><NA><NA>0.0<NA><NA>2
61한국전력공사 서울지역본부 및 남서울지역본부남서울본부 강남전력지사우면<NA>한국통신건너편서초구3.7kW × 22017년 상반기2017<NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA>2
71한국전력공사 서울지역본부 및 남서울지역본부남서울본부 강남전력지사우면<NA>한국통신건너편서초구3.7kW × 22017년 하반기20170.0<NA>0.00.0<NA><NA>0.00.0<NA><NA>2
81한국전력공사 서울지역본부 및 남서울지역본부남서울본부 강남전력지사우면<NA>한국통신건너편서초구3.7kW × 22018년 하반기 : 2018.6월~12월2018<NA>0.0<NA><NA><NA><NA><NA>0.0<NA><NA>2
91한국전력공사 서울지역본부 및 남서울지역본부남서울지역본부 강남전력지사우면<NA>한국통신건너편서초구3.7kW × 22015년 상반기 : 2015.1월~6월2015<NA>0.0<NA><NA><NA><NA><NA>0.0<NA><NA>2