Overview

Dataset statistics

Number of variables42
Number of observations155
Missing cells712
Missing cells (%)10.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory55.5 KiB
Average record size in memory366.9 B

Variable types

Text5
Categorical22
Numeric12
DateTime1
Unsupported2

Dataset

Description공공데이터 중장기 개방계획에 따라 공개하는 경상남도 하천관리 시스템의 데이터 입니다. 하천관리시스템의 댐 홍수조절지 저류지 정보를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15093459

Alerts

구분코드 is highly imbalanced (58.4%)Imbalance
공사기간_착공 is highly imbalanced (50.0%)Imbalance
일반현황_지번_본번 is highly imbalanced (91.6%)Imbalance
일반현황_지번_부번 is highly imbalanced (94.4%)Imbalance
일반현황_산지 is highly imbalanced (82.7%)Imbalance
제체_형식 is highly imbalanced (54.9%)Imbalance
구체_여수로마루표고 is highly imbalanced (79.4%)Imbalance
구체_댐마루폭 is highly imbalanced (75.7%)Imbalance
구체_경사상류측 is highly imbalanced (72.3%)Imbalance
구체_경사하류측 is highly imbalanced (73.4%)Imbalance
저수지_용수공급량_최대발전 is highly imbalanced (79.4%)Imbalance
저수지_용수공급량_최대농업 is highly imbalanced (79.4%)Imbalance
저수지_용수공급량_최대공업 is highly imbalanced (79.4%)Imbalance
저수지_용수공급량_최대생활 is highly imbalanced (79.4%)Imbalance
저수지_용수공급량_상시평균_발전 is highly imbalanced (79.4%)Imbalance
저수지_용수공급량_상시평균_농업 is highly imbalanced (79.4%)Imbalance
저수지_용수공급량_상시평균_공업 is highly imbalanced (79.4%)Imbalance
저수지_용수공급량_상시평균_생활 is highly imbalanced (79.4%)Imbalance
저수지_시설용량_발전시설용량 is highly imbalanced (79.4%)Imbalance
저수지_시설용량_연간발전량 is highly imbalanced (79.4%)Imbalance
저수지_시설용량_연간용수공급총량 is highly imbalanced (79.4%)Imbalance
저수지_시설용량_홍수조절용량 is highly imbalanced (79.4%)Imbalance
수리대장조서일련번호 has 131 (84.5%) missing valuesMissing
공사기간준공 has 79 (51.0%) missing valuesMissing
일반현황_동코드 has 155 (100.0%) missing valuesMissing
일반현황_기타주소 has 14 (9.0%) missing valuesMissing
일반현황_측점번호 has 124 (80.0%) missing valuesMissing
제체_계획홍수량 has 5 (3.2%) missing valuesMissing
구체_댐마루길이 has 5 (3.2%) missing valuesMissing
구체_바닥폭 has 5 (3.2%) missing valuesMissing
구체_댐체적 has 5 (3.2%) missing valuesMissing
저수지_수위및수량_계획홍수위 has 5 (3.2%) missing valuesMissing
저수지_수위및수량_상시만수위 has 5 (3.2%) missing valuesMissing
저수지_수위및수량_홍수기제한수위 has 5 (3.2%) missing valuesMissing
저수지_수위및수량_최저수위 has 5 (3.2%) missing valuesMissing
저수지_수위및수량_만수면적 has 5 (3.2%) missing valuesMissing
저수용량_총저수용량 has 155 (100.0%) missing valuesMissing
저수용량_유효저수용량 has 4 (2.6%) missing valuesMissing
저수용량_사수용량 has 5 (3.2%) missing valuesMissing
일반현황_동코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
저수용량_총저수용량 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제체_계획홍수량 has 140 (90.3%) zerosZeros
구체_댐마루길이 has 137 (88.4%) zerosZeros
구체_바닥폭 has 141 (91.0%) zerosZeros
구체_댐체적 has 141 (91.0%) zerosZeros
저수지_수위및수량_계획홍수위 has 134 (86.5%) zerosZeros
저수지_수위및수량_상시만수위 has 134 (86.5%) zerosZeros
저수지_수위및수량_홍수기제한수위 has 142 (91.6%) zerosZeros
저수지_수위및수량_최저수위 has 142 (91.6%) zerosZeros
저수지_수위및수량_만수면적 has 122 (78.7%) zerosZeros
저수용량_유효저수용량 has 85 (54.8%) zerosZeros
저수용량_사수용량 has 140 (90.3%) zerosZeros

Reproduction

Analysis started2023-12-10 23:55:58.443091
Analysis finished2023-12-10 23:55:58.967322
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

하천관리코드
Text

Distinct75
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T08:55:59.133026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters2945
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)33.5%

Sample

1st row20230002010F01Q0101
2nd row27206402018F02Q0101
3rd row27208002014F02Q0101
4th row27208002014F02Q0101
5th row27208002014F02Q0101
ValueCountFrequency (%)
20255601997f02q0101 14
 
9.0%
27209901994f02q0101 9
 
5.8%
20250301997f01q0101 9
 
5.8%
20243201996f01q0101 8
 
5.2%
20247402010f01q0101 5
 
3.2%
20250002010f01q0101 5
 
3.2%
20245802010f01q0101 5
 
3.2%
20239502010f01q0101 5
 
3.2%
27208002014f02q0101 4
 
2.6%
20240802004f01q0101 4
 
2.6%
Other values (65) 87
56.1%
2023-12-11T08:55:59.535977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1013
34.4%
1 549
18.6%
2 497
16.9%
9 176
 
6.0%
F 155
 
5.3%
Q 155
 
5.3%
5 99
 
3.4%
4 81
 
2.8%
7 76
 
2.6%
3 60
 
2.0%
Other values (2) 84
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2635
89.5%
Uppercase Letter 310
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1013
38.4%
1 549
20.8%
2 497
18.9%
9 176
 
6.7%
5 99
 
3.8%
4 81
 
3.1%
7 76
 
2.9%
3 60
 
2.3%
6 43
 
1.6%
8 41
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
F 155
50.0%
Q 155
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2635
89.5%
Latin 310
 
10.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1013
38.4%
1 549
20.8%
2 497
18.9%
9 176
 
6.7%
5 99
 
3.8%
4 81
 
3.1%
7 76
 
2.9%
3 60
 
2.3%
6 43
 
1.6%
8 41
 
1.6%
Latin
ValueCountFrequency (%)
F 155
50.0%
Q 155
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2945
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1013
34.4%
1 549
18.6%
2 497
16.9%
9 176
 
6.0%
F 155
 
5.3%
Q 155
 
5.3%
5 99
 
3.4%
4 81
 
2.8%
7 76
 
2.6%
3 60
 
2.0%
Other values (2) 84
 
2.9%

구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
S03
142 
S04
 
13

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowS04
2nd rowS03
3rd rowS03
4th rowS03
5th rowS03

Common Values

ValueCountFrequency (%)
S03 142
91.6%
S04 13
 
8.4%

Length

2023-12-11T08:55:59.667929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:55:59.761386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
s03 142
91.6%
s04 13
 
8.4%

일련번호
Real number (ℝ)

Distinct60
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.63871
Minimum1
Maximum1007
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:55:59.867650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median9
Q344.5
95-th percentile538
Maximum1007
Range1006
Interquartile range (IQR)42.5

Descriptive statistics

Standard deviation221.64022
Coefficient of variation (CV)2.9302486
Kurtosis13.564892
Mean75.63871
Median Absolute Deviation (MAD)8
Skewness3.8613689
Sum11724
Variance49124.388
MonotonicityNot monotonic
2023-12-11T08:56:00.071179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 36
23.2%
2 7
 
4.5%
3 6
 
3.9%
9 6
 
3.9%
4 5
 
3.2%
5 5
 
3.2%
6 5
 
3.2%
7 5
 
3.2%
11 4
 
2.6%
8 4
 
2.6%
Other values (50) 72
46.5%
ValueCountFrequency (%)
1 36
23.2%
2 7
 
4.5%
3 6
 
3.9%
4 5
 
3.2%
5 5
 
3.2%
6 5
 
3.2%
7 5
 
3.2%
8 4
 
2.6%
9 6
 
3.9%
10 3
 
1.9%
ValueCountFrequency (%)
1007 1
0.6%
1006 1
0.6%
1005 1
0.6%
1004 1
0.6%
1003 1
0.6%
1002 1
0.6%
1001 1
0.6%
1000 1
0.6%
340 1
0.6%
339 1
0.6%

수리대장조서일련번호
Text

MISSING 

Distinct16
Distinct (%)66.7%
Missing131
Missing (%)84.5%
Memory size1.3 KiB
2023-12-11T08:56:00.222519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.4583333
Min length1

Characters and Unicode

Total characters59
Distinct characters12
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

Unique15 ?
Unique (%)62.5%

Sample

1st row62
2nd row63
3rd row64
4th row65
5th row농-38
ValueCountFrequency (%)
1 9
37.5%
62 1
 
4.2%
63 1
 
4.2%
64 1
 
4.2%
65 1
 
4.2%
농-38 1
 
4.2%
농-32 1
 
4.2%
농-33 1
 
4.2%
농-35 1
 
4.2%
농-36 1
 
4.2%
Other values (6) 6
25.0%
2023-12-11T08:56:00.496412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
20.3%
3 11
18.6%
농 10
16.9%
- 9
15.3%
6 6
10.2%
2 2
 
3.4%
4 2
 
3.4%
5 2
 
3.4%
9 2
 
3.4%
8 1
 
1.7%
Other values (2) 2
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39
66.1%
Other Letter 11
 
18.6%
Dash Punctuation 9
 
15.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
30.8%
3 11
28.2%
6 6
15.4%
2 2
 
5.1%
4 2
 
5.1%
5 2
 
5.1%
9 2
 
5.1%
8 1
 
2.6%
7 1
 
2.6%
Other Letter
ValueCountFrequency (%)
농 10
90.9%
호 1
 
9.1%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48
81.4%
Hangul 11
 
18.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
25.0%
3 11
22.9%
- 9
18.8%
6 6
12.5%
2 2
 
4.2%
4 2
 
4.2%
5 2
 
4.2%
9 2
 
4.2%
8 1
 
2.1%
7 1
 
2.1%
Hangul
ValueCountFrequency (%)
농 10
90.9%
호 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48
81.4%
Hangul 11
 
18.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
25.0%
3 11
22.9%
- 9
18.8%
6 6
12.5%
2 2
 
4.2%
4 2
 
4.2%
5 2
 
4.2%
9 2
 
4.2%
8 1
 
2.1%
7 1
 
2.1%
Hangul
ValueCountFrequency (%)
농 10
90.9%
호 1
 
9.1%

일반현황_시설명
Text

Distinct150
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T08:56:00.880734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length5
Mean length5.7870968
Min length2

Characters and Unicode

Total characters897
Distinct characters137
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)93.5%

Sample

1st row사방댐
2nd row양정저수지
3rd row남전저수지
4th row양산저수지
5th row금평1저수지
ValueCountFrequency (%)
사방댐 2
 
1.3%
석리저수지 2
 
1.3%
구룡저수지 2
 
1.3%
운용저수지 2
 
1.3%
연초댐 2
 
1.3%
죽산저수지 1
 
0.6%
죽산무명5저수지 1
 
0.6%
하교무명1저수지 1
 
0.6%
지곡 1
 
0.6%
죽산무명3저수지 1
 
0.6%
Other values (141) 141
90.4%
2023-12-11T08:56:01.475572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 148
16.5%
수 121
 
13.5%
저 119
 
13.3%
명 39
 
4.3%
무 38
 
4.2%
산 25
 
2.8%
소 22
 
2.5%
류 22
 
2.5%
1 21
 
2.3%
곡 13
 
1.4%
Other values (127) 329
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 845
94.2%
Decimal Number 43
 
4.8%
Open Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 148
17.5%
수 121
14.3%
저 119
14.1%
명 39
 
4.6%
무 38
 
4.5%
산 25
 
3.0%
소 22
 
2.6%
류 22
 
2.6%
곡 13
 
1.5%
동 10
 
1.2%
Other values (119) 288
34.1%
Decimal Number
ValueCountFrequency (%)
1 21
48.8%
2 12
27.9%
3 7
 
16.3%
4 2
 
4.7%
5 1
 
2.3%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 845
94.2%
Common 52
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 148
17.5%
수 121
14.3%
저 119
14.1%
명 39
 
4.6%
무 38
 
4.5%
산 25
 
3.0%
소 22
 
2.6%
류 22
 
2.6%
곡 13
 
1.5%
동 10
 
1.2%
Other values (119) 288
34.1%
Common
ValueCountFrequency (%)
1 21
40.4%
2 12
23.1%
3 7
 
13.5%
( 4
 
7.7%
) 4
 
7.7%
4 2
 
3.8%
5 1
 
1.9%
1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 845
94.2%
ASCII 52
 
5.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 148
17.5%
수 121
14.3%
저 119
14.1%
명 39
 
4.6%
무 38
 
4.5%
산 25
 
3.0%
소 22
 
2.6%
류 22
 
2.6%
곡 13
 
1.5%
동 10
 
1.2%
Other values (119) 288
34.1%
ASCII
ValueCountFrequency (%)
1 21
40.4%
2 12
23.1%
3 7
 
13.5%
( 4
 
7.7%
) 4
 
7.7%
4 2
 
3.8%
5 1
 
1.9%
1
 
1.9%

공사기간_착공
Categorical

IMBALANCE 

Distinct29
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
97 
1945-01-01
20 
1978-01-01
 
4
1997-01-01
 
3
1959-01-01
 
2
Other values (24)
29 

Length

Max length10
Median length4
Mean length6.2451613
Min length4

Unique

Unique19 ?
Unique (%)12.3%

Sample

1st row1988-01-01
2nd row1953-01-01
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 97
62.6%
1945-01-01 20
 
12.9%
1978-01-01 4
 
2.6%
1997-01-01 3
 
1.9%
1959-01-01 2
 
1.3%
1958-01-01 2
 
1.3%
1970-01-01 2
 
1.3%
1953-01-01 2
 
1.3%
1968-01-01 2
 
1.3%
1977-12-01 2
 
1.3%
Other values (19) 19
 
12.3%

Length

2023-12-11T08:56:02.183205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 97
62.6%
1945-01-01 20
 
12.9%
1978-01-01 4
 
2.6%
1997-01-01 3
 
1.9%
1953-01-01 2
 
1.3%
1968-01-01 2
 
1.3%
1977-12-01 2
 
1.3%
1970-01-01 2
 
1.3%
1958-01-01 2
 
1.3%
1959-01-01 2
 
1.3%
Other values (19) 19
 
12.3%

공사기간준공
Date

MISSING 

Distinct41
Distinct (%)53.9%
Missing79
Missing (%)51.0%
Memory size1.3 KiB
Minimum1905-04-24 00:00:00
Maximum2014-01-01 00:00:00
2023-12-11T08:56:02.334581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:56:02.537145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)

일반현황_동코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing155
Missing (%)100.0%
Memory size1.5 KiB

일반현황_기타주소
Text

MISSING 

Distinct93
Distinct (%)66.0%
Missing14
Missing (%)9.0%
Memory size1.3 KiB
2023-12-11T08:56:02.999409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length14.560284
Min length10

Characters and Unicode

Total characters2053
Distinct characters130
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

Unique67 ?
Unique (%)47.5%

Sample

1st row경상남도 거창군 소정리
2nd row경상남도 거제시 양정동
3rd row경남 통영시 산양읍 남평리
4th row경남 통영시 산양읍 남평리
5th row경남 통영시 산양읍 남평리
ValueCountFrequency (%)
경상남도 100
 
19.0%
산청군 30
 
5.7%
함양군 20
 
3.8%
고성군 16
 
3.0%
신등면 13
 
2.5%
진주시 12
 
2.3%
창녕군 11
 
2.1%
거창군 11
 
2.1%
수동면 11
 
2.1%
사천시 9
 
1.7%
Other values (145) 294
55.8%
2023-12-11T08:56:03.654406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
386
18.8%
리 138
 
6.7%
남 127
 
6.2%
면 127
 
6.2%
상 113
 
5.5%
군 107
 
5.2%
경 105
 
5.1%
도 100
 
4.9%
산 69
 
3.4%
천 41
 
2.0%
Other values (120) 740
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1664
81.1%
Space Separator 386
 
18.8%
Decimal Number 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 138
 
8.3%
남 127
 
7.6%
면 127
 
7.6%
상 113
 
6.8%
군 107
 
6.4%
경 105
 
6.3%
도 100
 
6.0%
산 69
 
4.1%
천 41
 
2.5%
양 40
 
2.4%
Other values (117) 697
41.9%
Decimal Number
ValueCountFrequency (%)
4 2
66.7%
0 1
33.3%
Space Separator
ValueCountFrequency (%)
386
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1664
81.1%
Common 389
 
18.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 138
 
8.3%
남 127
 
7.6%
면 127
 
7.6%
상 113
 
6.8%
군 107
 
6.4%
경 105
 
6.3%
도 100
 
6.0%
산 69
 
4.1%
천 41
 
2.5%
양 40
 
2.4%
Other values (117) 697
41.9%
Common
ValueCountFrequency (%)
386
99.2%
4 2
 
0.5%
0 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1664
81.1%
ASCII 389
 
18.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
386
99.2%
4 2
 
0.5%
0 1
 
0.3%
Hangul
ValueCountFrequency (%)
리 138
 
8.3%
남 127
 
7.6%
면 127
 
7.6%
상 113
 
6.8%
군 107
 
6.4%
경 105
 
6.3%
도 100
 
6.0%
산 69
 
4.1%
천 41
 
2.5%
양 40
 
2.4%
Other values (117) 697
41.9%

일반현황_지번_본번
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
576
 
1
29
 
1
404
 
1

Length

Max length4
Median length4
Mean length3.9741935
Min length2

Unique

Unique3 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
98.1%
576 1
 
0.6%
29 1
 
0.6%
404 1
 
0.6%

Length

2023-12-11T08:56:03.824084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:03.969929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
98.1%
576 1
 
0.6%
29 1
 
0.6%
404 1
 
0.6%

일반현황_지번_부번
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
154 
0
 
1

Length

Max length4
Median length4
Mean length3.9806452
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 154
99.4%
0 1
 
0.6%

Length

2023-12-11T08:56:04.134745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:04.236540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 154
99.4%
0 1
 
0.6%

일반현황_측점번호
Text

MISSING 

Distinct28
Distinct (%)90.3%
Missing124
Missing (%)80.0%
Memory size1.3 KiB
2023-12-11T08:56:04.403032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters279
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)83.9%

Sample

1st row0000+7645
2nd row0000+0131
3rd row0001+3131
4th row0000+0116
5th row0000+0000
ValueCountFrequency (%)
0000+0000 3
 
9.7%
0000+0080 2
 
6.5%
0000+7645 1
 
3.2%
0000+0034 1
 
3.2%
0000+0240 1
 
3.2%
0000+0028 1
 
3.2%
0000+0343 1
 
3.2%
0000+0113 1
 
3.2%
0000+0029 1
 
3.2%
0000+0198 1
 
3.2%
Other values (18) 18
58.1%
2023-12-11T08:56:04.786572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 172
61.6%
+ 31
 
11.1%
1 18
 
6.5%
2 13
 
4.7%
3 12
 
4.3%
4 9
 
3.2%
8 7
 
2.5%
7 7
 
2.5%
5 4
 
1.4%
6 3
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 248
88.9%
Math Symbol 31
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 172
69.4%
1 18
 
7.3%
2 13
 
5.2%
3 12
 
4.8%
4 9
 
3.6%
8 7
 
2.8%
7 7
 
2.8%
5 4
 
1.6%
6 3
 
1.2%
9 3
 
1.2%
Math Symbol
ValueCountFrequency (%)
+ 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 279
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 172
61.6%
+ 31
 
11.1%
1 18
 
6.5%
2 13
 
4.7%
3 12
 
4.3%
4 9
 
3.2%
8 7
 
2.5%
7 7
 
2.5%
5 4
 
1.4%
6 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 279
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 172
61.6%
+ 31
 
11.1%
1 18
 
6.5%
2 13
 
4.7%
3 12
 
4.3%
4 9
 
3.2%
8 7
 
2.5%
7 7
 
2.5%
5 4
 
1.4%
6 3
 
1.1%

일반현황_산지
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
M00
151 
<NA>
 
4

Length

Max length4
Median length3
Mean length3.0258065
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM00
2nd rowM00
3rd rowM00
4th rowM00
5th rowM00

Common Values

ValueCountFrequency (%)
M00 151
97.4%
<NA> 4
 
2.6%

Length

2023-12-11T08:56:04.953433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:05.089090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m00 151
97.4%
na 4
 
2.6%

제체_형식
Categorical

IMBALANCE 

Distinct12
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
106 
토언제중심점토형
27 
필댐(죤형)
 
6
토양제
 
6
중심코아형흙댐
 
3
Other values (7)
 
7

Length

Max length9
Median length4
Mean length4.8322581
Min length1

Unique

Unique7 ?
Unique (%)4.5%

Sample

1st row<NA>
2nd row필댐(죤형)
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 106
68.4%
토언제중심점토형 27
 
17.4%
필댐(죤형) 6
 
3.9%
토양제 6
 
3.9%
중심코아형흙댐 3
 
1.9%
토언제 1
 
0.6%
0 1
 
0.6%
토언제중 심점토형 1
 
0.6%
토언제중심전토 1
 
0.6%
휠댐(죤형) 1
 
0.6%
Other values (2) 2
 
1.3%

Length

2023-12-11T08:56:05.217860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 106
67.9%
토언제중심점토형 27
 
17.3%
필댐(죤형 6
 
3.8%
토양제 6
 
3.8%
중심코아형흙댐 3
 
1.9%
토언제 1
 
0.6%
0 1
 
0.6%
토언제중 1
 
0.6%
심점토형 1
 
0.6%
토언제중심전토 1
 
0.6%
Other values (3) 3
 
1.9%

제체_계획홍수량
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)6.7%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean68.698533
Minimum0
Maximum8573
Zeros140
Zeros (%)90.3%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:05.356659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile97.188
Maximum8573
Range8573
Interquartile range (IQR)0

Descriptive statistics

Standard deviation701.08316
Coefficient of variation (CV)10.205213
Kurtosis148.21852
Mean68.698533
Median Absolute Deviation (MAD)0
Skewness12.141326
Sum10304.78
Variance491517.59
MonotonicityNot monotonic
2023-12-11T08:56:05.459909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 140
90.3%
256.0 2
 
1.3%
93.72 1
 
0.6%
8573.0 1
 
0.6%
100.5 1
 
0.6%
329.4 1
 
0.6%
96.0 1
 
0.6%
98.16 1
 
0.6%
400.0 1
 
0.6%
102.0 1
 
0.6%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
0.0 140
90.3%
93.72 1
 
0.6%
96.0 1
 
0.6%
98.16 1
 
0.6%
100.5 1
 
0.6%
102.0 1
 
0.6%
256.0 2
 
1.3%
329.4 1
 
0.6%
400.0 1
 
0.6%
8573.0 1
 
0.6%
ValueCountFrequency (%)
8573.0 1
 
0.6%
400.0 1
 
0.6%
329.4 1
 
0.6%
256.0 2
 
1.3%
102.0 1
 
0.6%
100.5 1
 
0.6%
98.16 1
 
0.6%
96.0 1
 
0.6%
93.72 1
 
0.6%
0.0 140
90.3%

구체_여수로마루표고
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:05.629037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:05.753772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

구체_댐마루길이
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)8.0%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean11.36
Minimum0
Maximum291
Zeros137
Zeros (%)88.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:05.849836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile94
Maximum291
Range291
Interquartile range (IQR)0

Descriptive statistics

Standard deviation43.288835
Coefficient of variation (CV)3.8106369
Kurtosis18.916276
Mean11.36
Median Absolute Deviation (MAD)0
Skewness4.2826184
Sum1704
Variance1873.9232
MonotonicityNot monotonic
2023-12-11T08:56:05.980642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 137
88.4%
47 2
 
1.3%
50 2
 
1.3%
40 1
 
0.6%
130 1
 
0.6%
197 1
 
0.6%
167 1
 
0.6%
161 1
 
0.6%
209 1
 
0.6%
163 1
 
0.6%
Other values (2) 2
 
1.3%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
0 137
88.4%
40 1
 
0.6%
47 2
 
1.3%
50 2
 
1.3%
130 1
 
0.6%
152 1
 
0.6%
161 1
 
0.6%
163 1
 
0.6%
167 1
 
0.6%
197 1
 
0.6%
ValueCountFrequency (%)
291 1
0.6%
209 1
0.6%
197 1
0.6%
167 1
0.6%
163 1
0.6%
161 1
0.6%
152 1
0.6%
130 1
0.6%
50 2
1.3%
47 2
1.3%

구체_댐마루폭
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
141 
<NA>
 
5
3
 
4
2
 
2
6
 
2

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 141
91.0%
<NA> 5
 
3.2%
3 4
 
2.6%
2 2
 
1.3%
6 2
 
1.3%
4 1
 
0.6%

Length

2023-12-11T08:56:06.115567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:06.222373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 141
91.0%
na 5
 
3.2%
3 4
 
2.6%
2 2
 
1.3%
6 2
 
1.3%
4 1
 
0.6%

구체_바닥폭
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)6.7%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean2.472
Minimum0
Maximum111.7
Zeros141
Zeros (%)91.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:06.336547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile15.235
Maximum111.7
Range111.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.478007
Coefficient of variation (CV)5.452268
Kurtosis56.158152
Mean2.472
Median Absolute Deviation (MAD)0
Skewness7.2665317
Sum370.8
Variance181.65666
MonotonicityNot monotonic
2023-12-11T08:56:06.443866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 141
91.0%
13.2 1
 
0.6%
19.5 1
 
0.6%
26.5 1
 
0.6%
25.0 1
 
0.6%
24.4 1
 
0.6%
23.1 1
 
0.6%
16.9 1
 
0.6%
110.5 1
 
0.6%
111.7 1
 
0.6%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
0.0 141
91.0%
13.2 1
 
0.6%
16.9 1
 
0.6%
19.5 1
 
0.6%
23.1 1
 
0.6%
24.4 1
 
0.6%
25.0 1
 
0.6%
26.5 1
 
0.6%
110.5 1
 
0.6%
111.7 1
 
0.6%
ValueCountFrequency (%)
111.7 1
 
0.6%
110.5 1
 
0.6%
26.5 1
 
0.6%
25.0 1
 
0.6%
24.4 1
 
0.6%
23.1 1
 
0.6%
19.5 1
 
0.6%
16.9 1
 
0.6%
13.2 1
 
0.6%
0.0 141
91.0%

구체_경사상류측
Categorical

IMBALANCE 

Distinct7
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
136 
01:02.0
 
10
01:02.5
 
4
01:03.0
 
2
01:01.8
 
1
Other values (2)
 
2

Length

Max length7
Median length4
Mean length4.3290323
Min length1

Unique

Unique3 ?
Unique (%)1.9%

Sample

1st row<NA>
2nd row01:02.0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 136
87.7%
01:02.0 10
 
6.5%
01:02.5 4
 
2.6%
01:03.0 2
 
1.3%
01:01.8 1
 
0.6%
0 1
 
0.6%
01:02.8 1
 
0.6%

Length

2023-12-11T08:56:06.564188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:06.673758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 136
87.7%
01:02.0 10
 
6.5%
01:02.5 4
 
2.6%
01:03.0 2
 
1.3%
01:01.8 1
 
0.6%
0 1
 
0.6%
01:02.8 1
 
0.6%

구체_경사하류측
Categorical

IMBALANCE 

Distinct8
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
137 
01:02.0
 
7
01:01.5
 
4
01:02.5
 
2
01:01.8
 
2
Other values (3)
 
3

Length

Max length7
Median length4
Mean length4.3096774
Min length1

Unique

Unique3 ?
Unique (%)1.9%

Sample

1st row<NA>
2nd row01:02.5
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 137
88.4%
01:02.0 7
 
4.5%
01:01.5 4
 
2.6%
01:02.5 2
 
1.3%
01:01.8 2
 
1.3%
01:02.7 1
 
0.6%
0 1
 
0.6%
01:02.3 1
 
0.6%

Length

2023-12-11T08:56:06.780511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:06.885683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 137
88.4%
01:02.0 7
 
4.5%
01:01.5 4
 
2.6%
01:02.5 2
 
1.3%
01:01.8 2
 
1.3%
01:02.7 1
 
0.6%
0 1
 
0.6%
01:02.3 1
 
0.6%

구체_댐체적
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)6.7%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean3728.48
Minimum0
Maximum322064
Zeros141
Zeros (%)91.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:06.974234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1827.15
Maximum322064
Range322064
Interquartile range (IQR)0

Descriptive statistics

Standard deviation30272.805
Coefficient of variation (CV)8.1193421
Kurtosis91.424629
Mean3728.48
Median Absolute Deviation (MAD)0
Skewness9.376921
Sum559272
Variance9.1644271 × 108
MonotonicityNot monotonic
2023-12-11T08:56:07.066204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 141
91.0%
973 1
 
0.6%
2526 1
 
0.6%
9912 1
 
0.6%
15996 1
 
0.6%
4179 1
 
0.6%
11550 1
 
0.6%
6728 1
 
0.6%
322064 1
 
0.6%
185344 1
 
0.6%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
0 141
91.0%
973 1
 
0.6%
2526 1
 
0.6%
4179 1
 
0.6%
6728 1
 
0.6%
9912 1
 
0.6%
11550 1
 
0.6%
15996 1
 
0.6%
185344 1
 
0.6%
322064 1
 
0.6%
ValueCountFrequency (%)
322064 1
 
0.6%
185344 1
 
0.6%
15996 1
 
0.6%
11550 1
 
0.6%
9912 1
 
0.6%
6728 1
 
0.6%
4179 1
 
0.6%
2526 1
 
0.6%
973 1
 
0.6%
0 141
91.0%

저수지_수위및수량_계획홍수위
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)9.3%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean12.852067
Minimum0
Maximum535
Zeros134
Zeros (%)86.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:07.163291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile60.5
Maximum535
Range535
Interquartile range (IQR)0

Descriptive statistics

Standard deviation61.75634
Coefficient of variation (CV)4.8051681
Kurtosis55.553358
Mean12.852067
Median Absolute Deviation (MAD)0
Skewness7.1916474
Sum1927.81
Variance3813.8456
MonotonicityNot monotonic
2023-12-11T08:56:07.262698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0 134
86.5%
60.5 3
 
1.9%
50.0 2
 
1.3%
46.86 1
 
0.6%
79.5 1
 
0.6%
20.05 1
 
0.6%
93.3 1
 
0.6%
35.4 1
 
0.6%
45.6 1
 
0.6%
81.0 1
 
0.6%
Other values (4) 4
 
2.6%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
0.0 134
86.5%
20.05 1
 
0.6%
35.4 1
 
0.6%
45.6 1
 
0.6%
46.86 1
 
0.6%
50.0 2
 
1.3%
52.5 1
 
0.6%
60.5 3
 
1.9%
79.5 1
 
0.6%
81.0 1
 
0.6%
ValueCountFrequency (%)
535.0 1
 
0.6%
478.0 1
 
0.6%
179.1 1
 
0.6%
93.3 1
 
0.6%
81.0 1
 
0.6%
79.5 1
 
0.6%
60.5 3
1.9%
52.5 1
 
0.6%
50.0 2
1.3%
46.86 1
 
0.6%

저수지_수위및수량_상시만수위
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)9.3%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean12.698533
Minimum0
Maximum533.8
Zeros134
Zeros (%)86.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:07.367466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile58.5
Maximum533.8
Range533.8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation61.535378
Coefficient of variation (CV)4.845865
Kurtosis55.93417
Mean12.698533
Median Absolute Deviation (MAD)0
Skewness7.2238924
Sum1904.78
Variance3786.6027
MonotonicityNot monotonic
2023-12-11T08:56:07.473405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0 134
86.5%
58.5 3
 
1.9%
48.0 2
 
1.3%
45.86 1
 
0.6%
79.0 1
 
0.6%
17.0 1
 
0.6%
91.7 1
 
0.6%
34.22 1
 
0.6%
45.0 1
 
0.6%
80.0 1
 
0.6%
Other values (4) 4
 
2.6%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
0.0 134
86.5%
17.0 1
 
0.6%
34.22 1
 
0.6%
45.0 1
 
0.6%
45.86 1
 
0.6%
48.0 2
 
1.3%
51.5 1
 
0.6%
58.5 3
 
1.9%
79.0 1
 
0.6%
80.0 1
 
0.6%
ValueCountFrequency (%)
533.8 1
 
0.6%
477.0 1
 
0.6%
178.2 1
 
0.6%
91.7 1
 
0.6%
80.0 1
 
0.6%
79.0 1
 
0.6%
58.5 3
1.9%
51.5 1
 
0.6%
48.0 2
1.3%
45.86 1
 
0.6%

저수지_수위및수량_홍수기제한수위
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)5.3%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean2.4748
Minimum0
Maximum91.7
Zeros142
Zeros (%)91.6%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:07.564218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile9.35
Maximum91.7
Range91.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.459439
Coefficient of variation (CV)4.6304506
Kurtosis30.881118
Mean2.4748
Median Absolute Deviation (MAD)0
Skewness5.2861757
Sum371.22
Variance131.31875
MonotonicityNot monotonic
2023-12-11T08:56:07.671137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 142
91.6%
50.0 2
 
1.3%
34.0 1
 
0.6%
17.0 1
 
0.6%
91.7 1
 
0.6%
34.22 1
 
0.6%
44.5 1
 
0.6%
49.8 1
 
0.6%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
0.0 142
91.6%
17.0 1
 
0.6%
34.0 1
 
0.6%
34.22 1
 
0.6%
44.5 1
 
0.6%
49.8 1
 
0.6%
50.0 2
 
1.3%
91.7 1
 
0.6%
ValueCountFrequency (%)
91.7 1
 
0.6%
50.0 2
 
1.3%
49.8 1
 
0.6%
44.5 1
 
0.6%
34.22 1
 
0.6%
34.0 1
 
0.6%
17.0 1
 
0.6%
0.0 142
91.6%

저수지_수위및수량_최저수위
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)5.3%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean6.3478667
Minimum0
Maximum455
Zeros142
Zeros (%)91.6%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:07.753895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7.7
Maximum455
Range455
Interquartile range (IQR)0

Descriptive statistics

Standard deviation43.487802
Coefficient of variation (CV)6.8507743
Kurtosis84.824087
Mean6.3478667
Median Absolute Deviation (MAD)0
Skewness8.9235171
Sum952.18
Variance1891.1889
MonotonicityNot monotonic
2023-12-11T08:56:07.838592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 142
91.6%
36.3 2
 
1.3%
34.0 1
 
0.6%
14.0 1
 
0.6%
72.5 1
 
0.6%
264.58 1
 
0.6%
455.0 1
 
0.6%
39.5 1
 
0.6%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
0.0 142
91.6%
14.0 1
 
0.6%
34.0 1
 
0.6%
36.3 2
 
1.3%
39.5 1
 
0.6%
72.5 1
 
0.6%
264.58 1
 
0.6%
455.0 1
 
0.6%
ValueCountFrequency (%)
455.0 1
 
0.6%
264.58 1
 
0.6%
72.5 1
 
0.6%
39.5 1
 
0.6%
36.3 2
 
1.3%
34.0 1
 
0.6%
14.0 1
 
0.6%
0.0 142
91.6%

저수지_수위및수량_만수면적
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)13.3%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean0.265
Minimum0
Maximum19.5
Zeros122
Zeros (%)78.7%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:07.932614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.382
Maximum19.5
Range19.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8715492
Coefficient of variation (CV)7.0624497
Kurtosis84.705995
Mean0.265
Median Absolute Deviation (MAD)0
Skewness8.9721507
Sum39.75
Variance3.5026963
MonotonicityNot monotonic
2023-12-11T08:56:08.049268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 122
78.7%
0.01 7
 
4.5%
0.17 2
 
1.3%
0.63 2
 
1.3%
0.14 2
 
1.3%
0.02 1
 
0.6%
0.06 1
 
0.6%
0.11 1
 
0.6%
0.36 1
 
0.6%
3.6 1
 
0.6%
Other values (10) 10
 
6.5%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
0.0 122
78.7%
0.01 7
 
4.5%
0.02 1
 
0.6%
0.03 1
 
0.6%
0.05 1
 
0.6%
0.06 1
 
0.6%
0.07 1
 
0.6%
0.11 1
 
0.6%
0.14 2
 
1.3%
0.17 2
 
1.3%
ValueCountFrequency (%)
19.5 1
0.6%
11.7 1
0.6%
3.6 1
0.6%
0.8 1
0.6%
0.63 2
1.3%
0.6 1
0.6%
0.4 1
0.6%
0.36 1
0.6%
0.3 1
0.6%
0.2 1
0.6%

저수용량_총저수용량
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing155
Missing (%)100.0%
Memory size1.5 KiB

저수용량_유효저수용량
Real number (ℝ)

MISSING  ZEROS 

Distinct49
Distinct (%)32.5%
Missing4
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean116.17695
Minimum0
Maximum8000
Zeros85
Zeros (%)54.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:08.175372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.275
95-th percentile549.6
Maximum8000
Range8000
Interquartile range (IQR)0.275

Descriptive statistics

Standard deviation680.41331
Coefficient of variation (CV)5.8566978
Kurtosis122.19572
Mean116.17695
Median Absolute Deviation (MAD)0
Skewness10.620995
Sum17542.72
Variance462962.28
MonotonicityNot monotonic
2023-12-11T08:56:08.298578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0.0 85
54.8%
0.02 8
 
5.2%
0.01 4
 
2.6%
0.06 3
 
1.9%
41.4 3
 
1.9%
0.09 2
 
1.3%
0.11 2
 
1.3%
0.32 2
 
1.3%
0.04 2
 
1.3%
166.3 1
 
0.6%
Other values (39) 39
25.2%
(Missing) 4
 
2.6%
ValueCountFrequency (%)
0.0 85
54.8%
0.01 4
 
2.6%
0.02 8
 
5.2%
0.04 2
 
1.3%
0.06 3
 
1.9%
0.07 1
 
0.6%
0.08 1
 
0.6%
0.09 2
 
1.3%
0.1 1
 
0.6%
0.11 2
 
1.3%
ValueCountFrequency (%)
8000.0 1
0.6%
1450.69 1
0.6%
1207.9 1
0.6%
1081.0 1
0.6%
787.0 1
0.6%
629.81 1
0.6%
566.03 1
0.6%
550.2 1
0.6%
549.0 1
0.6%
486.5 1
0.6%

저수용량_사수용량
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)6.7%
Missing5
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean3.0068
Minimum0
Maximum133.42
Zeros140
Zeros (%)90.3%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T08:56:08.401593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile18.895
Maximum133.42
Range133.42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.667251
Coefficient of variation (CV)4.8780268
Kurtosis47.825824
Mean3.0068
Median Absolute Deviation (MAD)0
Skewness6.4289218
Sum451.02
Variance215.12825
MonotonicityNot monotonic
2023-12-11T08:56:08.502280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 140
90.3%
37.0 2
 
1.3%
23.0 1
 
0.6%
52.8 1
 
0.6%
15.1 1
 
0.6%
22.0 1
 
0.6%
79.0 1
 
0.6%
51.0 1
 
0.6%
0.7 1
 
0.6%
133.42 1
 
0.6%
(Missing) 5
 
3.2%
ValueCountFrequency (%)
0.0 140
90.3%
0.7 1
 
0.6%
15.1 1
 
0.6%
22.0 1
 
0.6%
23.0 1
 
0.6%
37.0 2
 
1.3%
51.0 1
 
0.6%
52.8 1
 
0.6%
79.0 1
 
0.6%
133.42 1
 
0.6%
ValueCountFrequency (%)
133.42 1
 
0.6%
79.0 1
 
0.6%
52.8 1
 
0.6%
51.0 1
 
0.6%
37.0 2
 
1.3%
23.0 1
 
0.6%
22.0 1
 
0.6%
15.1 1
 
0.6%
0.7 1
 
0.6%
0.0 140
90.3%

저수지_용수공급량_최대발전
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:08.620733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:08.709929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_용수공급량_최대농업
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:08.800901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:08.900161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_용수공급량_최대공업
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:08.998314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:09.118700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_용수공급량_최대생활
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:09.378496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:09.589067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_용수공급량_상시평균_발전
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:09.757721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:09.851994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_용수공급량_상시평균_농업
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:10.244856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:10.357112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_용수공급량_상시평균_공업
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:10.461345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:10.565400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_용수공급량_상시평균_생활
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:10.674303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:10.800280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_시설용량_발전시설용량
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:10.908945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:11.016365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_시설용량_연간발전량
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:11.119654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:11.233433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_시설용량_연간용수공급총량
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:11.372176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:11.497936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

저수지_시설용량_홍수조절용량
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
150 
<NA>
 
5

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 150
96.8%
<NA> 5
 
3.2%

Length

2023-12-11T08:56:11.668962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:11.809307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 150
96.8%
na 5
 
3.2%

Sample

하천관리코드구분코드일련번호수리대장조서일련번호일반현황_시설명공사기간_착공공사기간준공일반현황_동코드일반현황_기타주소일반현황_지번_본번일반현황_지번_부번일반현황_측점번호일반현황_산지제체_형식제체_계획홍수량구체_여수로마루표고구체_댐마루길이구체_댐마루폭구체_바닥폭구체_경사상류측구체_경사하류측구체_댐체적저수지_수위및수량_계획홍수위저수지_수위및수량_상시만수위저수지_수위및수량_홍수기제한수위저수지_수위및수량_최저수위저수지_수위및수량_만수면적저수용량_총저수용량저수용량_유효저수용량저수용량_사수용량저수지_용수공급량_최대발전저수지_용수공급량_최대농업저수지_용수공급량_최대공업저수지_용수공급량_최대생활저수지_용수공급량_상시평균_발전저수지_용수공급량_상시평균_농업저수지_용수공급량_상시평균_공업저수지_용수공급량_상시평균_생활저수지_시설용량_발전시설용량저수지_시설용량_연간발전량저수지_시설용량_연간용수공급총량저수지_시설용량_홍수조절용량
020230002010F01Q0101S0484<NA>사방댐1988-01-011988-01-01<NA>경상남도 거창군 소정리<NA><NA>0000+7645M00<NA>0.004700.0<NA><NA>00.00.00.00.00.0<NA>0.00.0000000000000
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227208002014F02Q0101S036262남전저수지<NA>1945-12-31<NA>경남 통영시 산양읍 남평리<NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.120.0000000000000
327208002014F02Q0101S036363양산저수지<NA>1945-12-31<NA>경남 통영시 산양읍 남평리<NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.060.0000000000000
427208002014F02Q0101S036464금평1저수지<NA>1945-12-31<NA>경남 통영시 산양읍 남평리<NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.090.0000000000000
527208002014F02Q0101S036565금평2저수지<NA>1945-12-31<NA>경남 통영시 산양읍 남평리<NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.070.0000000000000
627209901994F02Q0101S038농-38죄양소류지1945-01-011945-01-01<NA>경상남도 사천시 사남면 죄양리<NA><NA><NA>M00토양제0.0040213.201:02.001:01.59730.00.00.00.00.0<NA>0.00.0000000000000
720255601997F02Q0101S035<NA>검암무명1저수지<NA><NA><NA>경상남도 진주시 금곡면 검암리<NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.00.0000000000000
820255601997F02Q0101S036<NA>검암무명2저수지<NA><NA><NA>경상남도 진주시 금곡면 검암리<NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.00.0000000000000
920255601997F02Q0101S037<NA>검암무명3저수지<NA><NA><NA>경상남도 진주시 금곡면 검암리<NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.00.0000000000000
하천관리코드구분코드일련번호수리대장조서일련번호일반현황_시설명공사기간_착공공사기간준공일반현황_동코드일반현황_기타주소일반현황_지번_본번일반현황_지번_부번일반현황_측점번호일반현황_산지제체_형식제체_계획홍수량구체_여수로마루표고구체_댐마루길이구체_댐마루폭구체_바닥폭구체_경사상류측구체_경사하류측구체_댐체적저수지_수위및수량_계획홍수위저수지_수위및수량_상시만수위저수지_수위및수량_홍수기제한수위저수지_수위및수량_최저수위저수지_수위및수량_만수면적저수용량_총저수용량저수용량_유효저수용량저수용량_사수용량저수지_용수공급량_최대발전저수지_용수공급량_최대농업저수지_용수공급량_최대공업저수지_용수공급량_최대생활저수지_용수공급량_상시평균_발전저수지_용수공급량_상시평균_농업저수지_용수공급량_상시평균_공업저수지_용수공급량_상시평균_생활저수지_시설용량_발전시설용량저수지_시설용량_연간발전량저수지_시설용량_연간용수공급총량저수지_시설용량_홍수조절용량
14527209702018F02Q0101S031<NA>용치저수지1955-01-011958-01-01<NA>경상남도 사천시 용현면 구월리 40440400000+0000M00필댐(죤형)98.160000.001:02.0<NA>052.551.549.839.50.14<NA>566.030.0000000000000
14627209901994F02Q0101S031농-31구룡저수지1958-01-011958-01-01<NA>경상남도 사천시 사남면 우천리<NA><NA><NA>M00중심코아형흙댐400.002916110.501:03.001:02.532206460.558.50.00.00.36<NA>0.320.0000000000000
14727206502014F02Q0101S04119119연초댐1977-12-011979-12-01<NA>경상남도 거제시 연초면 덕치리<NA><NA>0000+0080M00필댐(죤형)256.00000.0<NA><NA>050.048.050.036.30.63<NA>41.437.0000000000000
14827209901994F02Q0101S039농-39내원저수지1978-01-011978-01-01<NA>경상남도 고성군 하이면 봉원리<NA><NA><NA>M00중심코아형흙댐0.001526111.701:02.801:02.3185344179.1178.20.00.00.11<NA>0.680.0000000000000
14920255601997F02Q0101S0310<NA>금산소류지<NA><NA><NA>경상남도 고성군 영오면 성곡리<NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.00.0000000000000
15020255600000F99Q9901S0317<NA>싸리재못<NA><NA><NA>경상남도 고성군 개천면 좌연리<NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.00.0000000000000
15120252002010F02Q0101S0328<NA>원리저수지1945-01-011945-01-01<NA>산청군 시천면 원리<NA><NA><NA>M00토언제중심점토형0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.00.0000000000000
15220240800000F99Q9901S035<NA>깊은골저수지<NA><NA><NA>경상남도 함양군 서상면 옥산리<NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.00.0000000000000
15320231202019F01Q0101S0310001매산저수지1985-10-011991-11-20<NA>거창군 남상면 무촌리<NA><NA>0000+2174M00필댐(죤형)102.00000.001:02.001:02.000.00.00.00.00.06<NA>629.810.0000000000000
15427209202010F02Q0101S0325<NA>하이저수지<NA><NA><NA><NA><NA><NA><NA>M00<NA>0.00000.0<NA><NA>00.00.00.00.00.0<NA>0.00.0000000000000