Overview

Dataset statistics

Number of variables54
Number of observations5370
Missing cells47598
Missing cells (%)16.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 MiB
Average record size in memory470.0 B

Variable types

Text8
Categorical18
Numeric28

Dataset

Description공공데이터 중장기 개방계획에 따라 공개하는 경상남도 하천관리 시스템의 제방 현황입니다. 하천관리시스템의 제방 정보를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15093452

Alerts

하천등급 has constant value ""Constant
구분코드 is highly imbalanced (95.0%)Imbalance
기점_산지 is highly imbalanced (58.0%)Imbalance
개수구간_비고 is highly imbalanced (95.0%)Imbalance
비탈구배_제외지 is highly imbalanced (76.9%)Imbalance
종점_산지 is highly imbalanced (60.5%)Imbalance
소단폭 is highly imbalanced (85.2%)Imbalance
소단폭_제내지 is highly imbalanced (81.4%)Imbalance
소단폭_제외지 is highly imbalanced (81.7%)Imbalance
주요시설현황_기타 is highly imbalanced (72.4%)Imbalance
기점_동코드 has 664 (12.4%) missing valuesMissing
기점_기타주소 has 523 (9.7%) missing valuesMissing
기점_지번_본번 has 5033 (93.7%) missing valuesMissing
기점_지번_부번 has 4886 (91.0%) missing valuesMissing
종점_동코드 has 681 (12.7%) missing valuesMissing
종점_기타주소 has 512 (9.5%) missing valuesMissing
종점_지번_본번 has 5032 (93.7%) missing valuesMissing
종점_지번_부번 has 4912 (91.5%) missing valuesMissing
종점_측점번호 has 291 (5.4%) missing valuesMissing
보호면적 및 시설 has 385 (7.2%) missing valuesMissing
수리수문현황_하구로부터제방종점까지의거리 has 291 (5.4%) missing valuesMissing
비탈구배_제내지 has 3107 (57.9%) missing valuesMissing
수리수문현황_계획홍수량2 has 138 (2.6%) missing valuesMissing
수리수문현황_계획홍수위시점 has 260 (4.8%) missing valuesMissing
수리수문현황_계획홍수위종점 has 262 (4.9%) missing valuesMissing
수리수문현황_계획하폭2 has 67 (1.2%) missing valuesMissing
제방_둑마루표고_상류측 has 266 (5.0%) missing valuesMissing
제방_둑마루표고_하류측 has 293 (5.5%) missing valuesMissing
제방_둑마루턱의폭_마루1 has 93 (1.7%) missing valuesMissing
제방_둑마루턱의폭_마루2 has 254 (4.7%) missing valuesMissing
천단폭 has 368 (6.9%) missing valuesMissing
축제고_최대 has 368 (6.9%) missing valuesMissing
축제고_평균 has 368 (6.9%) missing valuesMissing
주요시설현황_배수통관 has 4460 (83.1%) missing valuesMissing
주요시설현황_배수암거 has 4475 (83.3%) missing valuesMissing
주요시설현황_보 has 4473 (83.3%) missing valuesMissing
주요시설현황_낙차공 has 4465 (83.1%) missing valuesMissing
시설등록 및 관리담당_등록일자 has 518 (9.6%) missing valuesMissing
보호면적 및 시설 is highly skewed (γ1 = 37.88733789)Skewed
제방_둑마루턱의폭_마루1 is highly skewed (γ1 = 53.60188431)Skewed
축제고_최대 is highly skewed (γ1 = 48.75720144)Skewed
축제고_평균 is highly skewed (γ1 = 61.02061059)Skewed
기점_지번_본번 has 291 (5.4%) zerosZeros
기점_지번_부번 has 460 (8.6%) zerosZeros
종점_지번_본번 has 291 (5.4%) zerosZeros
종점_지번_부번 has 428 (8.0%) zerosZeros
보호면적 및 시설 has 4305 (80.2%) zerosZeros
수리수문현황_하구로부터제방종점까지의거리 has 2265 (42.2%) zerosZeros
수리수문현황_계획홍수량1 has 1523 (28.4%) zerosZeros
수리수문현황_계획홍수량2 has 3597 (67.0%) zerosZeros
수리수문현황_계획홍수위시점 has 1647 (30.7%) zerosZeros
수리수문현황_계획홍수위종점 has 1763 (32.8%) zerosZeros
수리수문현황_계획하폭1 has 1532 (28.5%) zerosZeros
수리수문현황_계획하폭2 has 2007 (37.4%) zerosZeros
제방_연장 has 120 (2.2%) zerosZeros
제방_둑마루표고_상류측 has 1814 (33.8%) zerosZeros
제방_둑마루표고_하류측 has 1800 (33.5%) zerosZeros
제방_둑마루턱의폭_마루1 has 2540 (47.3%) zerosZeros
제방_둑마루턱의폭_마루2 has 3377 (62.9%) zerosZeros
천단폭 has 4683 (87.2%) zerosZeros
축제고_최대 has 4616 (86.0%) zerosZeros
축제고_평균 has 4616 (86.0%) zerosZeros
주요시설현황_배수통관 has 852 (15.9%) zerosZeros
주요시설현황_배수암거 has 852 (15.9%) zerosZeros
주요시설현황_보 has 852 (15.9%) zerosZeros
주요시설현황_낙차공 has 852 (15.9%) zerosZeros
시설등록 및 관리담당_등록일자 has 4820 (89.8%) zerosZeros

Reproduction

Analysis started2023-12-11 00:24:20.630324
Analysis finished2023-12-11 00:24:22.055209
Duration1.42 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct687
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
2023-12-11T09:24:22.177798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters102030
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

Unique8 ?
Unique (%)0.1%

Sample

1st row20231102014F02Q0101
2nd row40226702016F01Q0101
3rd row40226502016F02Q0101
4th row20231102014F02Q0101
5th row20268902015F02Q0101
ValueCountFrequency (%)
20228802004f01q0101 48
 
0.9%
20239602006f02q0101 44
 
0.8%
20275001994f01q0101 44
 
0.8%
20248701986f01q0101 37
 
0.7%
40226902007f02q0101 35
 
0.7%
20231502019f02q0101 34
 
0.6%
20231502004f02q0101 31
 
0.6%
20272002012f02q0101 31
 
0.6%
20237601988f01q0101 31
 
0.6%
20272002012f02q0102 31
 
0.6%
Other values (677) 5004
93.2%
2023-12-11T09:24:22.449288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34413
33.7%
1 19155
18.8%
2 19100
18.7%
F 5370
 
5.3%
Q 5370
 
5.3%
9 4330
 
4.2%
7 3134
 
3.1%
4 2592
 
2.5%
6 2407
 
2.4%
3 2308
 
2.3%
Other values (2) 3851
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91290
89.5%
Uppercase Letter 10740
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34413
37.7%
1 19155
21.0%
2 19100
20.9%
9 4330
 
4.7%
7 3134
 
3.4%
4 2592
 
2.8%
6 2407
 
2.6%
3 2308
 
2.5%
5 2224
 
2.4%
8 1627
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
F 5370
50.0%
Q 5370
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 91290
89.5%
Latin 10740
 
10.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34413
37.7%
1 19155
21.0%
2 19100
20.9%
9 4330
 
4.7%
7 3134
 
3.4%
4 2592
 
2.8%
6 2407
 
2.6%
3 2308
 
2.5%
5 2224
 
2.4%
8 1627
 
1.8%
Latin
ValueCountFrequency (%)
F 5370
50.0%
Q 5370
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102030
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34413
33.7%
1 19155
18.8%
2 19100
18.7%
F 5370
 
5.3%
Q 5370
 
5.3%
9 4330
 
4.2%
7 3134
 
3.1%
4 2592
 
2.5%
6 2407
 
2.4%
3 2308
 
2.3%
Other values (2) 3851
 
3.8%

구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
B01
5320 
B99
 
46
B02
 
4

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB01
2nd rowB01
3rd rowB01
4th rowB01
5th rowB01

Common Values

ValueCountFrequency (%)
B01 5320
99.1%
B99 46
 
0.9%
B02 4
 
0.1%

Length

2023-12-11T09:24:22.559714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:22.638547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b01 5320
99.1%
b99 46
 
0.9%
b02 4
 
0.1%

일련번호
Real number (ℝ)

Distinct281
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.96797
Minimum0
Maximum280
Zeros9
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:22.722804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median6
Q313
95-th percentile55
Maximum280
Range280
Interquartile range (IQR)10

Descriptive statistics

Standard deviation36.410693
Coefficient of variation (CV)2.280233
Kurtosis25.029078
Mean15.96797
Median Absolute Deviation (MAD)4
Skewness4.8525302
Sum85748
Variance1325.7386
MonotonicityNot monotonic
2023-12-11T09:24:22.833991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 586
 
10.9%
2 574
 
10.7%
3 481
 
9.0%
4 448
 
8.3%
5 391
 
7.3%
6 329
 
6.1%
7 274
 
5.1%
8 246
 
4.6%
9 203
 
3.8%
10 164
 
3.1%
Other values (271) 1674
31.2%
ValueCountFrequency (%)
0 9
 
0.2%
1 586
10.9%
2 574
10.7%
3 481
9.0%
4 448
8.3%
5 391
7.3%
6 329
6.1%
7 274
5.1%
8 246
4.6%
9 203
 
3.8%
ValueCountFrequency (%)
280 1
< 0.1%
279 1
< 0.1%
278 1
< 0.1%
277 1
< 0.1%
276 1
< 0.1%
275 1
< 0.1%
274 1
< 0.1%
273 1
< 0.1%
272 1
< 0.1%
271 1
< 0.1%
Distinct4439
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
2023-12-11T09:24:23.113492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length4.8363128
Min length2

Characters and Unicode

Total characters25971
Distinct characters283
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3983 ?
Unique (%)74.2%

Sample

1st row대산좌1
2nd row신성우2제
3rd row악양우1제
4th row대산우1
5th row용덕우4제
ValueCountFrequency (%)
계수천 50
 
0.9%
우1 29
 
0.5%
좌1 28
 
0.5%
우2 22
 
0.4%
좌2 20
 
0.4%
양곡지구 19
 
0.4%
무제부 19
 
0.4%
주항제 14
 
0.3%
좌안1제 13
 
0.2%
우3 11
 
0.2%
Other values (4428) 5189
95.8%
2023-12-11T09:24:23.486559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4281
 
16.5%
1713
 
6.6%
1 1706
 
6.6%
1703
 
6.6%
1680
 
6.5%
2 1178
 
4.5%
751
 
2.9%
734
 
2.8%
3 661
 
2.5%
500
 
1.9%
Other values (273) 11064
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21132
81.4%
Decimal Number 4704
 
18.1%
Space Separator 44
 
0.2%
Connector Punctuation 29
 
0.1%
Open Punctuation 28
 
0.1%
Close Punctuation 28
 
0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4281
20.3%
1713
 
8.1%
1703
 
8.1%
1680
 
8.0%
751
 
3.6%
734
 
3.5%
500
 
2.4%
484
 
2.3%
465
 
2.2%
240
 
1.1%
Other values (257) 8581
40.6%
Decimal Number
ValueCountFrequency (%)
1 1706
36.3%
2 1178
25.0%
3 661
 
14.1%
4 401
 
8.5%
5 278
 
5.9%
6 188
 
4.0%
7 131
 
2.8%
8 79
 
1.7%
9 45
 
1.0%
0 37
 
0.8%
Space Separator
ValueCountFrequency (%)
44
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21132
81.4%
Common 4839
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4281
20.3%
1713
 
8.1%
1703
 
8.1%
1680
 
8.0%
751
 
3.6%
734
 
3.5%
500
 
2.4%
484
 
2.3%
465
 
2.2%
240
 
1.1%
Other values (257) 8581
40.6%
Common
ValueCountFrequency (%)
1 1706
35.3%
2 1178
24.3%
3 661
 
13.7%
4 401
 
8.3%
5 278
 
5.7%
6 188
 
3.9%
7 131
 
2.7%
8 79
 
1.6%
9 45
 
0.9%
44
 
0.9%
Other values (6) 128
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21132
81.4%
ASCII 4839
 
18.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4281
20.3%
1713
 
8.1%
1703
 
8.1%
1680
 
8.0%
751
 
3.6%
734
 
3.5%
500
 
2.4%
484
 
2.3%
465
 
2.2%
240
 
1.1%
Other values (257) 8581
40.6%
ASCII
ValueCountFrequency (%)
1 1706
35.3%
2 1178
24.3%
3 661
 
13.7%
4 401
 
8.3%
5 278
 
5.7%
6 188
 
3.9%
7 131
 
2.7%
8 79
 
1.6%
9 45
 
0.9%
44
 
0.9%
Other values (6) 128
 
2.6%
Distinct432
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
2023-12-11T09:24:23.747834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0247672
Min length2

Characters and Unicode

Total characters16243
Distinct characters199
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row대산천
2nd row신성천
3rd row악양천
4th row대산천
5th row용덕천
ValueCountFrequency (%)
대산천 90
 
1.7%
횡천강 87
 
1.6%
양산천 82
 
1.5%
가천천 80
 
1.5%
유곡천 67
 
1.2%
운봉천 64
 
1.2%
단장천 62
 
1.2%
죽천천 61
 
1.1%
미곡천 59
 
1.1%
창녕천 53
 
1.0%
Other values (422) 4665
86.9%
2023-12-11T09:24:24.151224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5656
34.8%
599
 
3.7%
539
 
3.3%
295
 
1.8%
233
 
1.4%
217
 
1.3%
216
 
1.3%
213
 
1.3%
197
 
1.2%
195
 
1.2%
Other values (189) 7883
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16156
99.5%
Space Separator 39
 
0.2%
Open Punctuation 24
 
0.1%
Close Punctuation 24
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5656
35.0%
599
 
3.7%
539
 
3.3%
295
 
1.8%
233
 
1.4%
217
 
1.3%
216
 
1.3%
213
 
1.3%
197
 
1.2%
195
 
1.2%
Other values (186) 7796
48.3%
Space Separator
ValueCountFrequency (%)
39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16156
99.5%
Common 87
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5656
35.0%
599
 
3.7%
539
 
3.3%
295
 
1.8%
233
 
1.4%
217
 
1.3%
216
 
1.3%
213
 
1.3%
197
 
1.2%
195
 
1.2%
Other values (186) 7796
48.3%
Common
ValueCountFrequency (%)
39
44.8%
( 24
27.6%
) 24
27.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16156
99.5%
ASCII 87
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5656
35.0%
599
 
3.7%
539
 
3.3%
295
 
1.8%
233
 
1.4%
217
 
1.3%
216
 
1.3%
213
 
1.3%
197
 
1.2%
195
 
1.2%
Other values (186) 7796
48.3%
ASCII
ValueCountFrequency (%)
39
44.8%
( 24
27.6%
) 24
27.6%

하천등급
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
지방하천
5370 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방하천 5370
100.0%

Length

2023-12-11T09:24:24.288716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:24.391356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방하천 5370
100.0%

좌우안 코드
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
D01
2712 
D02
2619 
D00
 
39

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowD01
2nd rowD02
3rd rowD02
4th rowD02
5th rowD02

Common Values

ValueCountFrequency (%)
D01 2712
50.5%
D02 2619
48.8%
D00 39
 
0.7%

Length

2023-12-11T09:24:24.490194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:24.596229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
d01 2712
50.5%
d02 2619
48.8%
d00 39
 
0.7%

기점_동코드
Real number (ℝ)

MISSING 

Distinct984
Distinct (%)20.9%
Missing664
Missing (%)12.4%
Infinite0
Infinite (%)0.0%
Mean4.8570311 × 109
Minimum4.783037 × 109
Maximum4.889046 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:24.723114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.783037 × 109
5-th percentile4.8154963 × 109
Q14.825037 × 109
median4.873032 × 109
Q34.886031 × 109
95-th percentile4.889033 × 109
Maximum4.889046 × 109
Range1.0600899 × 108
Interquartile range (IQR)60993998

Descriptive statistics

Standard deviation29682938
Coefficient of variation (CV)0.0061113338
Kurtosis-1.7196612
Mean4.8570311 × 109
Median Absolute Deviation (MAD)15009004
Skewness-0.28938288
Sum2.2857188 × 1013
Variance8.8107682 × 1014
MonotonicityNot monotonic
2023-12-11T09:24:24.862605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4833011200 30
 
0.6%
4874032028 27
 
0.5%
4882042026 24
 
0.4%
4888037028 24
 
0.4%
4873037023 23
 
0.4%
4831037023 22
 
0.4%
4817043028 22
 
0.4%
4831032023 21
 
0.4%
4885040024 20
 
0.4%
4831036026 19
 
0.4%
Other values (974) 4474
83.3%
(Missing) 664
 
12.4%
ValueCountFrequency (%)
4783037043 1
 
< 0.1%
4811010200 2
 
< 0.1%
4811010500 6
0.1%
4811010700 4
0.1%
4811010800 6
0.1%
4811011200 2
 
< 0.1%
4811011300 2
 
< 0.1%
4811011400 2
 
< 0.1%
4811011500 2
 
< 0.1%
4811011800 2
 
< 0.1%
ValueCountFrequency (%)
4889046035 1
 
< 0.1%
4889046033 6
0.1%
4889045029 4
 
0.1%
4889045028 14
0.3%
4889045027 5
 
0.1%
4889045026 4
 
0.1%
4889045025 4
 
0.1%
4889045024 1
 
< 0.1%
4889045023 9
0.2%
4889044028 10
0.2%

기점_기타주소
Text

MISSING 

Distinct2046
Distinct (%)42.2%
Missing523
Missing (%)9.7%
Memory size42.1 KiB
2023-12-11T09:24:25.151306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length37
Mean length17.4281
Min length4

Characters and Unicode

Total characters84474
Distinct characters277
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1260 ?
Unique (%)26.0%

Sample

1st row경남 거창군 남상면 둔동리 (No.74+20)
2nd row경남 하동군 악양면 신성리 355번지선
3rd row경남 하동군 악양면 신대리 831-3번지선
4th row경남 거창군 남상면 오계리 (No.74+73)
5th row경남 김해시 한림면 신천리 389-15도
ValueCountFrequency (%)
경상남도 3560
 
18.0%
경남 657
 
3.3%
합천군 509
 
2.6%
거창군 424
 
2.1%
밀양시 342
 
1.7%
창녕군 334
 
1.7%
고성군 294
 
1.5%
함안군 292
 
1.5%
김해시 270
 
1.4%
진주시 269
 
1.4%
Other values (2351) 12864
64.9%
2023-12-11T09:24:25.586017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15067
 
17.8%
4594
 
5.4%
4406
 
5.2%
4244
 
5.0%
3975
 
4.7%
3838
 
4.5%
3820
 
4.5%
2913
 
3.4%
2001
 
2.4%
1348
 
1.6%
Other values (267) 38268
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58718
69.5%
Space Separator 15067
 
17.8%
Decimal Number 5868
 
6.9%
Close Punctuation 820
 
1.0%
Open Punctuation 820
 
1.0%
Math Symbol 818
 
1.0%
Uppercase Letter 672
 
0.8%
Other Punctuation 663
 
0.8%
Lowercase Letter 596
 
0.7%
Dash Punctuation 432
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4594
 
7.8%
4406
 
7.5%
4244
 
7.2%
3975
 
6.8%
3838
 
6.5%
3820
 
6.5%
2913
 
5.0%
2001
 
3.4%
1348
 
2.3%
1268
 
2.2%
Other values (248) 26311
44.8%
Decimal Number
ValueCountFrequency (%)
1 979
16.7%
0 757
12.9%
2 674
11.5%
3 595
10.1%
5 556
9.5%
4 541
9.2%
6 484
8.2%
8 447
7.6%
7 441
7.5%
9 394
6.7%
Uppercase Letter
ValueCountFrequency (%)
N 634
94.3%
O 38
 
5.7%
Space Separator
ValueCountFrequency (%)
15067
100.0%
Close Punctuation
ValueCountFrequency (%)
) 820
100.0%
Open Punctuation
ValueCountFrequency (%)
( 820
100.0%
Math Symbol
ValueCountFrequency (%)
+ 818
100.0%
Other Punctuation
ValueCountFrequency (%)
. 663
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 596
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 432
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58718
69.5%
Common 24488
29.0%
Latin 1268
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4594
 
7.8%
4406
 
7.5%
4244
 
7.2%
3975
 
6.8%
3838
 
6.5%
3820
 
6.5%
2913
 
5.0%
2001
 
3.4%
1348
 
2.3%
1268
 
2.2%
Other values (248) 26311
44.8%
Common
ValueCountFrequency (%)
15067
61.5%
1 979
 
4.0%
) 820
 
3.3%
( 820
 
3.3%
+ 818
 
3.3%
0 757
 
3.1%
2 674
 
2.8%
. 663
 
2.7%
3 595
 
2.4%
5 556
 
2.3%
Other values (6) 2739
 
11.2%
Latin
ValueCountFrequency (%)
N 634
50.0%
o 596
47.0%
O 38
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58717
69.5%
ASCII 25756
30.5%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15067
58.5%
1 979
 
3.8%
) 820
 
3.2%
( 820
 
3.2%
+ 818
 
3.2%
0 757
 
2.9%
2 674
 
2.6%
. 663
 
2.6%
N 634
 
2.5%
o 596
 
2.3%
Other values (9) 3928
 
15.3%
Hangul
ValueCountFrequency (%)
4594
 
7.8%
4406
 
7.5%
4244
 
7.2%
3975
 
6.8%
3838
 
6.5%
3820
 
6.5%
2913
 
5.0%
2001
 
3.4%
1348
 
2.3%
1268
 
2.2%
Other values (247) 26310
44.8%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

기점_지번_본번
Real number (ℝ)

MISSING  ZEROS 

Distinct45
Distinct (%)13.4%
Missing5033
Missing (%)93.7%
Infinite0
Infinite (%)0.0%
Mean65.818991
Minimum0
Maximum1481
Zeros291
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:25.717611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile486.8
Maximum1481
Range1481
Interquartile range (IQR)0

Descriptive statistics

Standard deviation229.79512
Coefficient of variation (CV)3.4913194
Kurtosis16.814761
Mean65.818991
Median Absolute Deviation (MAD)0
Skewness4.0632131
Sum22181
Variance52805.797
MonotonicityNot monotonic
2023-12-11T09:24:25.839058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 291
 
5.4%
28 2
 
< 0.1%
132 2
 
< 0.1%
693 1
 
< 0.1%
1481 1
 
< 0.1%
1051 1
 
< 0.1%
319 1
 
< 0.1%
458 1
 
< 0.1%
312 1
 
< 0.1%
998 1
 
< 0.1%
Other values (35) 35
 
0.7%
(Missing) 5033
93.7%
ValueCountFrequency (%)
0 291
5.4%
2 1
 
< 0.1%
3 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
28 2
 
< 0.1%
47 1
 
< 0.1%
50 1
 
< 0.1%
66 1
 
< 0.1%
76 1
 
< 0.1%
ValueCountFrequency (%)
1481 1
< 0.1%
1341 1
< 0.1%
1339 1
< 0.1%
1337 1
< 0.1%
1109 1
< 0.1%
1051 1
< 0.1%
998 1
< 0.1%
964 1
< 0.1%
932 1
< 0.1%
926 1
< 0.1%

기점_지번_부번
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)2.3%
Missing4886
Missing (%)91.0%
Infinite0
Infinite (%)0.0%
Mean0.24173554
Minimum0
Maximum24
Zeros460
Zeros (%)8.6%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:25.956495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7929682
Coefficient of variation (CV)7.4170649
Kurtosis129.77344
Mean0.24173554
Median Absolute Deviation (MAD)0
Skewness10.865453
Sum117
Variance3.2147349
MonotonicityNot monotonic
2023-12-11T09:24:26.050978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 460
 
8.6%
1 10
 
0.2%
4 4
 
0.1%
2 3
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
16 1
 
< 0.1%
3 1
 
< 0.1%
23 1
 
< 0.1%
24 1
 
< 0.1%
(Missing) 4886
91.0%
ValueCountFrequency (%)
0 460
8.6%
1 10
 
0.2%
2 3
 
0.1%
3 1
 
< 0.1%
4 4
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
16 1
 
< 0.1%
23 1
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
23 1
 
< 0.1%
16 1
 
< 0.1%
8 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 4
 
0.1%
3 1
 
< 0.1%
2 3
 
0.1%
1 10
0.2%
Distinct3007
Distinct (%)56.2%
Missing18
Missing (%)0.3%
Memory size42.1 KiB
2023-12-11T09:24:26.254313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length9.0136398
Min length9

Characters and Unicode

Total characters48241
Distinct characters12
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

Unique2011 ?
Unique (%)37.6%

Sample

1st row0074+0020
2nd row0000+0000
3rd row0000+0000
4th row0074+0073
5th row0000+0000
ValueCountFrequency (%)
0000+0000 336
 
6.3%
0009+0000 29
 
0.5%
0013+0000 23
 
0.4%
0025+0000 23
 
0.4%
0007+0000 21
 
0.4%
0020+0000 21
 
0.4%
0022+0000 21
 
0.4%
0010+0000 19
 
0.4%
0030+0000 19
 
0.4%
0011+0000 19
 
0.4%
Other values (2997) 4821
90.1%
2023-12-11T09:24:26.598979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27107
56.2%
+ 5352
 
11.1%
1 3046
 
6.3%
2 2282
 
4.7%
5 2035
 
4.2%
3 1775
 
3.7%
4 1646
 
3.4%
7 1341
 
2.8%
6 1320
 
2.7%
8 1185
 
2.5%
Other values (2) 1152
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42860
88.8%
Math Symbol 5352
 
11.1%
Other Punctuation 29
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27107
63.2%
1 3046
 
7.1%
2 2282
 
5.3%
5 2035
 
4.7%
3 1775
 
4.1%
4 1646
 
3.8%
7 1341
 
3.1%
6 1320
 
3.1%
8 1185
 
2.8%
9 1123
 
2.6%
Math Symbol
ValueCountFrequency (%)
+ 5352
100.0%
Other Punctuation
ValueCountFrequency (%)
. 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48241
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27107
56.2%
+ 5352
 
11.1%
1 3046
 
6.3%
2 2282
 
4.7%
5 2035
 
4.2%
3 1775
 
3.7%
4 1646
 
3.4%
7 1341
 
2.8%
6 1320
 
2.7%
8 1185
 
2.5%
Other values (2) 1152
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27107
56.2%
+ 5352
 
11.1%
1 3046
 
6.3%
2 2282
 
4.7%
5 2035
 
4.2%
3 1775
 
3.7%
4 1646
 
3.4%
7 1341
 
2.8%
6 1320
 
2.7%
8 1185
 
2.5%
Other values (2) 1152
 
2.4%

기점_산지
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
M00
4698 
<NA>
 
406
M01
 
266

Length

Max length4
Median length3
Mean length3.0756052
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M00 4698
87.5%
<NA> 406
 
7.6%
M01 266
 
5.0%

Length

2023-12-11T09:24:26.709778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:26.791496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m00 4698
87.5%
na 406
 
7.6%
m01 266
 
5.0%

종점_동코드
Real number (ℝ)

MISSING 

Distinct997
Distinct (%)21.3%
Missing681
Missing (%)12.7%
Infinite0
Infinite (%)0.0%
Mean4.8571643 × 109
Minimum4.783037 × 109
Maximum4.889046 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:26.880523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.783037 × 109
5-th percentile4.8160102 × 109
Q14.8270107 × 109
median4.873032 × 109
Q34.886031 × 109
95-th percentile4.889033 × 109
Maximum4.889046 × 109
Range1.0600899 × 108
Interquartile range (IQR)59020325

Descriptive statistics

Standard deviation29639685
Coefficient of variation (CV)0.0061022612
Kurtosis-1.7172513
Mean4.8571643 × 109
Median Absolute Deviation (MAD)15009001
Skewness-0.29374087
Sum2.2775243 × 1013
Variance8.7851094 × 1014
MonotonicityNot monotonic
2023-12-11T09:24:26.997427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4833011200 28
 
0.5%
4874032028 26
 
0.5%
4882033021 24
 
0.4%
4888037028 24
 
0.4%
4882042026 23
 
0.4%
4873037023 23
 
0.4%
4817043028 22
 
0.4%
4885040024 22
 
0.4%
4825036022 21
 
0.4%
4831032023 21
 
0.4%
Other values (987) 4455
83.0%
(Missing) 681
 
12.7%
ValueCountFrequency (%)
4783037043 1
 
< 0.1%
4811010200 1
 
< 0.1%
4811010500 6
 
0.1%
4811010700 2
 
< 0.1%
4811010800 4
 
0.1%
4811011200 3
 
0.1%
4811011300 4
 
0.1%
4811011500 4
 
0.1%
4811012100 2
 
< 0.1%
4811013300 18
0.3%
ValueCountFrequency (%)
4889046035 1
 
< 0.1%
4889046033 5
 
0.1%
4889046032 1
 
< 0.1%
4889045029 6
0.1%
4889045028 14
0.3%
4889045027 5
 
0.1%
4889045026 4
 
0.1%
4889045025 2
 
< 0.1%
4889045024 1
 
< 0.1%
4889045023 9
0.2%

종점_기타주소
Text

MISSING 

Distinct2025
Distinct (%)41.7%
Missing512
Missing (%)9.5%
Memory size42.1 KiB
2023-12-11T09:24:27.252218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length37
Mean length17.172705
Min length1

Characters and Unicode

Total characters83425
Distinct characters277
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1254 ?
Unique (%)25.8%

Sample

1st row경남 거창군 남상면 오계리 (No.60+00)
2nd row경남 하동군 악양면 신성리 407번지선
3rd row경남 하동군 악양면 미점리 310-2번지선
4th row경남 거창군 남상면 오계리 (No.60+00)
5th row경남 김해시 한림면 신천리 375-4창
ValueCountFrequency (%)
경상남도 3535
 
18.0%
경남 658
 
3.4%
합천군 512
 
2.6%
거창군 425
 
2.2%
밀양시 342
 
1.7%
창녕군 333
 
1.7%
함안군 294
 
1.5%
고성군 287
 
1.5%
김해시 271
 
1.4%
진주시 266
 
1.4%
Other values (2279) 12667
64.7%
2023-12-11T09:24:27.636363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14835
 
17.8%
4589
 
5.5%
4227
 
5.1%
4208
 
5.0%
3946
 
4.7%
3820
 
4.6%
3801
 
4.6%
2910
 
3.5%
1985
 
2.4%
1336
 
1.6%
Other values (267) 37768
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57959
69.5%
Space Separator 14835
 
17.8%
Decimal Number 5808
 
7.0%
Close Punctuation 813
 
1.0%
Open Punctuation 813
 
1.0%
Math Symbol 812
 
1.0%
Uppercase Letter 671
 
0.8%
Other Punctuation 668
 
0.8%
Lowercase Letter 595
 
0.7%
Dash Punctuation 451
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4589
 
7.9%
4227
 
7.3%
4208
 
7.3%
3946
 
6.8%
3820
 
6.6%
3801
 
6.6%
2910
 
5.0%
1985
 
3.4%
1336
 
2.3%
1286
 
2.2%
Other values (246) 25851
44.6%
Decimal Number
ValueCountFrequency (%)
0 1132
19.5%
1 868
14.9%
2 627
10.8%
3 595
10.2%
5 519
8.9%
4 494
8.5%
6 429
 
7.4%
7 417
 
7.2%
8 381
 
6.6%
9 346
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 658
98.5%
? 9
 
1.3%
, 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 633
94.3%
O 38
 
5.7%
Space Separator
ValueCountFrequency (%)
14835
100.0%
Close Punctuation
ValueCountFrequency (%)
) 813
100.0%
Open Punctuation
ValueCountFrequency (%)
( 813
100.0%
Math Symbol
ValueCountFrequency (%)
+ 812
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 595
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 451
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57959
69.5%
Common 24200
29.0%
Latin 1266
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4589
 
7.9%
4227
 
7.3%
4208
 
7.3%
3946
 
6.8%
3820
 
6.6%
3801
 
6.6%
2910
 
5.0%
1985
 
3.4%
1336
 
2.3%
1286
 
2.2%
Other values (246) 25851
44.6%
Common
ValueCountFrequency (%)
14835
61.3%
0 1132
 
4.7%
1 868
 
3.6%
) 813
 
3.4%
( 813
 
3.4%
+ 812
 
3.4%
. 658
 
2.7%
2 627
 
2.6%
3 595
 
2.5%
5 519
 
2.1%
Other values (8) 2528
 
10.4%
Latin
ValueCountFrequency (%)
N 633
50.0%
o 595
47.0%
O 38
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57959
69.5%
ASCII 25466
30.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14835
58.3%
0 1132
 
4.4%
1 868
 
3.4%
) 813
 
3.2%
( 813
 
3.2%
+ 812
 
3.2%
. 658
 
2.6%
N 633
 
2.5%
2 627
 
2.5%
3 595
 
2.3%
Other values (11) 3680
 
14.5%
Hangul
ValueCountFrequency (%)
4589
 
7.9%
4227
 
7.3%
4208
 
7.3%
3946
 
6.8%
3820
 
6.6%
3801
 
6.6%
2910
 
5.0%
1985
 
3.4%
1336
 
2.3%
1286
 
2.2%
Other values (246) 25851
44.6%

종점_지번_본번
Real number (ℝ)

MISSING  ZEROS 

Distinct46
Distinct (%)13.6%
Missing5032
Missing (%)93.7%
Infinite0
Infinite (%)0.0%
Mean59.739645
Minimum0
Maximum1355
Zeros291
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:27.756804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile462.15
Maximum1355
Range1355
Interquartile range (IQR)0

Descriptive statistics

Standard deviation210.16642
Coefficient of variation (CV)3.5180394
Kurtosis17.325023
Mean59.739645
Median Absolute Deviation (MAD)0
Skewness4.1209619
Sum20192
Variance44169.926
MonotonicityNot monotonic
2023-12-11T09:24:27.928155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 291
 
5.4%
984 2
 
< 0.1%
52 2
 
< 0.1%
463 1
 
< 0.1%
76 1
 
< 0.1%
180 1
 
< 0.1%
590 1
 
< 0.1%
319 1
 
< 0.1%
458 1
 
< 0.1%
342 1
 
< 0.1%
Other values (36) 36
 
0.7%
(Missing) 5032
93.7%
ValueCountFrequency (%)
0 291
5.4%
3 1
 
< 0.1%
5 1
 
< 0.1%
10 1
 
< 0.1%
12 1
 
< 0.1%
29 1
 
< 0.1%
35 1
 
< 0.1%
43 1
 
< 0.1%
50 1
 
< 0.1%
52 2
 
< 0.1%
ValueCountFrequency (%)
1355 1
< 0.1%
1337 1
< 0.1%
1186 1
< 0.1%
1109 1
< 0.1%
984 2
< 0.1%
950 1
< 0.1%
944 1
< 0.1%
938 1
< 0.1%
929 1
< 0.1%
774 1
< 0.1%

종점_지번_부번
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.7%
Missing4912
Missing (%)91.5%
Infinite0
Infinite (%)0.0%
Mean0.18995633
Minimum0
Maximum9
Zeros428
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:28.030240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.98175233
Coefficient of variation (CV)5.1683054
Kurtosis50.950453
Mean0.18995633
Median Absolute Deviation (MAD)0
Skewness6.8444161
Sum87
Variance0.96383763
MonotonicityNot monotonic
2023-12-11T09:24:28.114963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 428
 
8.0%
1 14
 
0.3%
2 5
 
0.1%
3 4
 
0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
6 2
 
< 0.1%
5 1
 
< 0.1%
(Missing) 4912
91.5%
ValueCountFrequency (%)
0 428
8.0%
1 14
 
0.3%
2 5
 
0.1%
3 4
 
0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
9 2
 
< 0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
5 1
 
< 0.1%
3 4
 
0.1%
2 5
 
0.1%
1 14
 
0.3%
0 428
8.0%

종점_측점번호
Text

MISSING 

Distinct2737
Distinct (%)53.9%
Missing291
Missing (%)5.4%
Memory size42.1 KiB
2023-12-11T09:24:28.325395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.9996062
Min length2

Characters and Unicode

Total characters45709
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1931 ?
Unique (%)38.0%

Sample

1st row0031+0062
2nd row0050+0077
3rd row0005+0073
4th row0016+0002
5th row0003+0052
ValueCountFrequency (%)
0000+0000 714
 
14.1%
0019+0000 22
 
0.4%
0015+0000 22
 
0.4%
0022+0000 22
 
0.4%
0011+0000 22
 
0.4%
0016+0000 21
 
0.4%
0010+0000 21
 
0.4%
0008+0000 21
 
0.4%
0002+0000 20
 
0.4%
0007+0000 19
 
0.4%
Other values (2727) 4175
82.2%
2023-12-11T09:24:28.672324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27108
59.3%
+ 5068
 
11.1%
1 2699
 
5.9%
2 1873
 
4.1%
5 1765
 
3.9%
3 1522
 
3.3%
4 1326
 
2.9%
7 1151
 
2.5%
6 1147
 
2.5%
8 1071
 
2.3%
Other values (3) 979
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40602
88.8%
Math Symbol 5068
 
11.1%
Other Punctuation 28
 
0.1%
Dash Punctuation 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27108
66.8%
1 2699
 
6.6%
2 1873
 
4.6%
5 1765
 
4.3%
3 1522
 
3.7%
4 1326
 
3.3%
7 1151
 
2.8%
6 1147
 
2.8%
8 1071
 
2.6%
9 940
 
2.3%
Math Symbol
ValueCountFrequency (%)
+ 5068
100.0%
Other Punctuation
ValueCountFrequency (%)
. 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45709
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27108
59.3%
+ 5068
 
11.1%
1 2699
 
5.9%
2 1873
 
4.1%
5 1765
 
3.9%
3 1522
 
3.3%
4 1326
 
2.9%
7 1151
 
2.5%
6 1147
 
2.5%
8 1071
 
2.3%
Other values (3) 979
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45709
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27108
59.3%
+ 5068
 
11.1%
1 2699
 
5.9%
2 1873
 
4.1%
5 1765
 
3.9%
3 1522
 
3.3%
4 1326
 
2.9%
7 1151
 
2.5%
6 1147
 
2.5%
8 1071
 
2.3%
Other values (3) 979
 
2.1%

보호면적 및 시설
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct456
Distinct (%)9.1%
Missing385
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean2073.0235
Minimum0
Maximum2438891
Zeros4305
Zeros (%)80.2%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:28.808819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile15
Maximum2438891
Range2438891
Interquartile range (IQR)0

Descriptive statistics

Standard deviation50359.548
Coefficient of variation (CV)24.292801
Kurtosis1568.3311
Mean2073.0235
Median Absolute Deviation (MAD)0
Skewness37.887338
Sum10334022
Variance2.536084 × 109
MonotonicityNot monotonic
2023-12-11T09:24:28.933671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4305
80.2%
15.0 15
 
0.3%
3.0 11
 
0.2%
2.0 10
 
0.2%
1.0 10
 
0.2%
499.0 10
 
0.2%
5.0 9
 
0.2%
10.0 8
 
0.1%
8.0 7
 
0.1%
6.0 6
 
0.1%
Other values (446) 594
 
11.1%
(Missing) 385
 
7.2%
ValueCountFrequency (%)
0.0 4305
80.2%
0.03 3
 
0.1%
0.05 3
 
0.1%
0.06 1
 
< 0.1%
0.1 4
 
0.1%
0.15 2
 
< 0.1%
0.19 2
 
< 0.1%
0.2 6
 
0.1%
0.21 1
 
< 0.1%
0.24 1
 
< 0.1%
ValueCountFrequency (%)
2438891.0 1
< 0.1%
1780200.0 1
< 0.1%
1360700.0 1
< 0.1%
1132667.0 1
< 0.1%
246413.0 1
< 0.1%
207800.0 1
< 0.1%
184502.0 1
< 0.1%
172800.0 1
< 0.1%
169941.0 1
< 0.1%
168534.0 1
< 0.1%

개수구간_비고
Categorical

IMBALANCE 

Distinct39
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
<NA>
5230 
준용하천
 
56
더돋기 구간
 
19
NO.0지점은의령군의령읍정암리직할하천남강합류점
 
13
호안구간
 
10
Other values (34)
 
42

Length

Max length25
Median length4
Mean length4.1147114
Min length1

Unique

Unique31 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5230
97.4%
준용하천 56
 
1.0%
더돋기 구간 19
 
0.4%
NO.0지점은의령군의령읍정암리직할하천남강합류점 13
 
0.2%
호안구간 10
 
0.2%
기수립구간 7
 
0.1%
피허가자 : 고성군, 준공년월일 : 1964 2
 
< 0.1%
신현읍 시가지 구성 2
 
< 0.1%
금회수립구간 1
 
< 0.1%
신설구간(소석제) 1
 
< 0.1%
Other values (29) 29
 
0.5%

Length

2023-12-11T09:24:29.101852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5230
96.0%
준용하천 56
 
1.0%
구간 21
 
0.4%
더돋기 19
 
0.3%
16
 
0.3%
no.0지점은의령군의령읍정암리직할하천남강합류점 13
 
0.2%
호안구간 10
 
0.2%
피허가자 8
 
0.1%
준공년월일 8
 
0.1%
기수립구간 7
 
0.1%
Other values (40) 62
 
1.1%
Distinct1609
Distinct (%)31.7%
Missing291
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean98.02109
Minimum0
Maximum9850
Zeros2265
Zeros (%)42.2%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:29.231375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.421
Q32.76
95-th percentile31.3615
Maximum9850
Range9850
Interquartile range (IQR)2.76

Descriptive statistics

Standard deviation534.27747
Coefficient of variation (CV)5.4506379
Kurtosis66.389273
Mean98.02109
Median Absolute Deviation (MAD)0.421
Skewness7.3074368
Sum497849.12
Variance285452.42
MonotonicityNot monotonic
2023-12-11T09:24:29.391128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2265
42.2%
1.0 55
 
1.0%
2.0 38
 
0.7%
15.05 31
 
0.6%
6.0 29
 
0.5%
1.8 20
 
0.4%
3.0 20
 
0.4%
5.0 16
 
0.3%
0.4 16
 
0.3%
10.24 15
 
0.3%
Other values (1599) 2574
47.9%
(Missing) 291
 
5.4%
ValueCountFrequency (%)
0.0 2265
42.2%
0.002 1
 
< 0.1%
0.01 3
 
0.1%
0.013 1
 
< 0.1%
0.016 2
 
< 0.1%
0.02 1
 
< 0.1%
0.027 1
 
< 0.1%
0.028 1
 
< 0.1%
0.03 12
 
0.2%
0.036 3
 
0.1%
ValueCountFrequency (%)
9850.0 1
< 0.1%
6450.0 2
< 0.1%
5707.0 1
< 0.1%
5600.0 1
< 0.1%
5510.0 1
< 0.1%
5450.0 1
< 0.1%
5045.0 1
< 0.1%
5030.0 1
< 0.1%
4940.0 1
< 0.1%
4840.0 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
<NA>
4609 
0
761 

Length

Max length4
Median length4
Mean length3.5748603
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4609
85.8%
0 761
 
14.2%

Length

2023-12-11T09:24:29.759017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:29.840712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4609
85.8%
0 761
 
14.2%
Distinct52
Distinct (%)2.3%
Missing3107
Missing (%)57.9%
Memory size42.1 KiB
2023-12-11T09:24:29.969401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.0092797
Min length1

Characters and Unicode

Total characters9073
Distinct characters14
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 (%)0.7%

Sample

1st row1:01
2nd row01:01.5
3rd row01:00.2
4th row01:01.5
5th row01:02.4
ValueCountFrequency (%)
0 958
42.3%
01:00.3 245
 
10.8%
01:02.0 244
 
10.8%
1:02 179
 
7.9%
01:00.5 170
 
7.5%
01:01.5 97
 
4.3%
01:01.0 91
 
4.0%
수직 32
 
1.4%
1:01 23
 
1.0%
01:00.2 23
 
1.0%
Other values (42) 201
 
8.9%
2023-12-11T09:24:30.261490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4079
45.0%
1 1510
 
16.6%
: 1228
 
13.5%
. 1044
 
11.5%
2 506
 
5.6%
3 291
 
3.2%
5 285
 
3.1%
32
 
0.4%
32
 
0.4%
8 18
 
0.2%
Other values (4) 48
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6737
74.3%
Other Punctuation 2272
 
25.0%
Other Letter 64
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4079
60.5%
1 1510
 
22.4%
2 506
 
7.5%
3 291
 
4.3%
5 285
 
4.2%
8 18
 
0.3%
4 18
 
0.3%
9 12
 
0.2%
7 10
 
0.1%
6 8
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 1228
54.0%
. 1044
46.0%
Other Letter
ValueCountFrequency (%)
32
50.0%
32
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9009
99.3%
Hangul 64
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4079
45.3%
1 1510
 
16.8%
: 1228
 
13.6%
. 1044
 
11.6%
2 506
 
5.6%
3 291
 
3.2%
5 285
 
3.2%
8 18
 
0.2%
4 18
 
0.2%
9 12
 
0.1%
Other values (2) 18
 
0.2%
Hangul
ValueCountFrequency (%)
32
50.0%
32
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9009
99.3%
Hangul 64
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4079
45.3%
1 1510
 
16.8%
: 1228
 
13.6%
. 1044
 
11.6%
2 506
 
5.6%
3 291
 
3.2%
5 285
 
3.2%
8 18
 
0.2%
4 18
 
0.2%
9 12
 
0.1%
Other values (2) 18
 
0.2%
Hangul
ValueCountFrequency (%)
32
50.0%
32
50.0%

비탈구배_제외지
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
<NA>
4858 
0
508 
01:02.0
 
2
01:01.0
 
2

Length

Max length7
Median length4
Mean length3.7184358
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 4858
90.5%
0 508
 
9.5%
01:02.0 2
 
< 0.1%
01:01.0 2
 
< 0.1%

Length

2023-12-11T09:24:30.377101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:30.465322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4858
90.5%
0 508
 
9.5%
01:02.0 2
 
< 0.1%
01:01.0 2
 
< 0.1%

종점_산지
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
M00
4746 
<NA>
 
408
M01
 
216

Length

Max length4
Median length3
Mean length3.0759777
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M00 4746
88.4%
<NA> 408
 
7.6%
M01 216
 
4.0%

Length

2023-12-11T09:24:30.598502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:30.701774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m00 4746
88.4%
na 408
 
7.6%
m01 216
 
4.0%

수리수문현황_계획홍수량1
Real number (ℝ)

ZEROS 

Distinct494
Distinct (%)9.3%
Missing45
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean201.32008
Minimum0
Maximum3579
Zeros1523
Zeros (%)28.4%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:30.807042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median85
Q3215
95-th percentile820
Maximum3579
Range3579
Interquartile range (IQR)215

Descriptive statistics

Standard deviation368.7996
Coefficient of variation (CV)1.8319067
Kurtosis23.802506
Mean201.32008
Median Absolute Deviation (MAD)85
Skewness4.1970996
Sum1072029.4
Variance136013.14
MonotonicityNot monotonic
2023-12-11T09:24:30.946202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1523
28.4%
110.0 43
 
0.8%
61.0 41
 
0.8%
120.0 34
 
0.6%
51.0 34
 
0.6%
40.0 33
 
0.6%
98.0 33
 
0.6%
117.0 33
 
0.6%
45.0 31
 
0.6%
80.0 30
 
0.6%
Other values (484) 3490
65.0%
(Missing) 45
 
0.8%
ValueCountFrequency (%)
0.0 1523
28.4%
4.0 1
 
< 0.1%
5.0 5
 
0.1%
6.0 3
 
0.1%
8.0 1
 
< 0.1%
10.0 2
 
< 0.1%
11.0 7
 
0.1%
12.0 5
 
0.1%
13.0 3
 
0.1%
14.0 6
 
0.1%
ValueCountFrequency (%)
3579.0 5
 
0.1%
3576.0 1
 
< 0.1%
3272.0 8
 
0.1%
3250.0 1
 
< 0.1%
2589.0 1
 
< 0.1%
2435.0 20
0.4%
1920.0 8
 
0.1%
1915.0 1
 
< 0.1%
1860.0 10
0.2%
1735.0 5
 
0.1%

수리수문현황_계획홍수량2
Real number (ℝ)

MISSING  ZEROS 

Distinct407
Distinct (%)7.8%
Missing138
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean81.587083
Minimum0
Maximum3579
Zeros3597
Zeros (%)67.0%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:31.100894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q374
95-th percentile405.45
Maximum3579
Range3579
Interquartile range (IQR)74

Descriptive statistics

Standard deviation228.47124
Coefficient of variation (CV)2.800336
Kurtosis55.333018
Mean81.587083
Median Absolute Deviation (MAD)0
Skewness6.2187229
Sum426863.62
Variance52199.109
MonotonicityNot monotonic
2023-12-11T09:24:31.240982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3597
67.0%
145.0 20
 
0.4%
110.0 18
 
0.3%
119.0 17
 
0.3%
89.0 16
 
0.3%
113.0 16
 
0.3%
85.0 16
 
0.3%
61.0 16
 
0.3%
105.0 15
 
0.3%
160.0 15
 
0.3%
Other values (397) 1486
27.7%
(Missing) 138
 
2.6%
ValueCountFrequency (%)
0.0 3597
67.0%
5.0 1
 
< 0.1%
6.0 1
 
< 0.1%
8.0 1
 
< 0.1%
10.0 2
 
< 0.1%
11.0 1
 
< 0.1%
13.0 2
 
< 0.1%
15.72 1
 
< 0.1%
18.0 1
 
< 0.1%
18.92 2
 
< 0.1%
ValueCountFrequency (%)
3579.0 1
 
< 0.1%
3272.0 1
 
< 0.1%
2685.0 4
0.1%
2589.0 1
 
< 0.1%
2435.0 4
0.1%
1915.0 5
0.1%
1810.0 4
0.1%
1735.0 5
0.1%
1625.0 2
 
< 0.1%
1487.0 2
 
< 0.1%

수리수문현황_계획홍수위시점
Real number (ℝ)

MISSING  ZEROS 

Distinct2549
Distinct (%)49.9%
Missing260
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean76.028268
Minimum0
Maximum761.51
Zeros1647
Zeros (%)30.7%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:31.353498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median23.105
Q397.0825
95-th percentile339.8005
Maximum761.51
Range761.51
Interquartile range (IQR)97.0825

Descriptive statistics

Standard deviation116.24787
Coefficient of variation (CV)1.5290085
Kurtosis4.9126761
Mean76.028268
Median Absolute Deviation (MAD)23.105
Skewness2.1384714
Sum388504.45
Variance13513.567
MonotonicityNot monotonic
2023-12-11T09:24:31.483144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1647
30.7%
40.0 18
 
0.3%
8.0 15
 
0.3%
20.0 12
 
0.2%
57.35 12
 
0.2%
65.0 10
 
0.2%
47.44 10
 
0.2%
8.3 8
 
0.1%
16.7 8
 
0.1%
18.94 7
 
0.1%
Other values (2539) 3363
62.6%
(Missing) 260
 
4.8%
ValueCountFrequency (%)
0.0 1647
30.7%
0.59 4
 
0.1%
1.0 1
 
< 0.1%
1.34 1
 
< 0.1%
1.66 4
 
0.1%
1.71 2
 
< 0.1%
1.95 2
 
< 0.1%
2.0 1
 
< 0.1%
2.02 2
 
< 0.1%
2.04 1
 
< 0.1%
ValueCountFrequency (%)
761.51 1
< 0.1%
746.5 1
< 0.1%
739.19 1
< 0.1%
737.98 1
< 0.1%
723.73 1
< 0.1%
707.62 1
< 0.1%
705.34 1
< 0.1%
700.7 1
< 0.1%
696.27 1
< 0.1%
694.96 1
< 0.1%

수리수문현황_계획홍수위종점
Real number (ℝ)

MISSING  ZEROS 

Distinct2386
Distinct (%)46.7%
Missing262
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean68.29472
Minimum0
Maximum768
Zeros1763
Zeros (%)32.8%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:31.595448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median15.8
Q386.3025
95-th percentile321.183
Maximum768
Range768
Interquartile range (IQR)86.3025

Descriptive statistics

Standard deviation111.57344
Coefficient of variation (CV)1.6337053
Kurtosis5.8440127
Mean68.29472
Median Absolute Deviation (MAD)15.8
Skewness2.2843769
Sum348849.43
Variance12448.633
MonotonicityNot monotonic
2023-12-11T09:24:31.706856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1763
32.8%
8.3 24
 
0.4%
6.0 21
 
0.4%
8.0 14
 
0.3%
20.0 13
 
0.2%
11.47 12
 
0.2%
7.3 10
 
0.2%
16.7 8
 
0.1%
1.0 7
 
0.1%
179.0 7
 
0.1%
Other values (2376) 3229
60.1%
(Missing) 262
 
4.9%
ValueCountFrequency (%)
0.0 1763
32.8%
0.59 6
 
0.1%
0.69 1
 
< 0.1%
0.74 1
 
< 0.1%
0.86 4
 
0.1%
0.98 2
 
< 0.1%
1.0 7
 
0.1%
1.02 2
 
< 0.1%
1.12 6
 
0.1%
1.2 2
 
< 0.1%
ValueCountFrequency (%)
768.0 1
< 0.1%
764.46 1
< 0.1%
752.57 1
< 0.1%
740.97 1
< 0.1%
736.17 1
< 0.1%
736.0 1
< 0.1%
717.96 1
< 0.1%
700.7 1
< 0.1%
693.43 1
< 0.1%
692.81 1
< 0.1%

수리수문현황_계획하폭1
Real number (ℝ)

ZEROS 

Distinct263
Distinct (%)4.9%
Missing45
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean23.957228
Minimum0
Maximum684
Zeros1532
Zeros (%)28.5%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:31.815017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median15
Q330
95-th percentile88
Maximum684
Range684
Interquartile range (IQR)30

Descriptive statistics

Standard deviation33.047646
Coefficient of variation (CV)1.3794437
Kurtosis43.364291
Mean23.957228
Median Absolute Deviation (MAD)15
Skewness4.2223584
Sum127572.24
Variance1092.1469
MonotonicityNot monotonic
2023-12-11T09:24:31.926484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1532
28.5%
20.0 227
 
4.2%
30.0 161
 
3.0%
15.0 159
 
3.0%
25.0 130
 
2.4%
13.0 129
 
2.4%
18.0 127
 
2.4%
10.0 123
 
2.3%
12.0 121
 
2.3%
16.0 98
 
1.8%
Other values (253) 2518
46.9%
ValueCountFrequency (%)
0.0 1532
28.5%
2.0 2
 
< 0.1%
3.0 14
 
0.3%
4.0 28
 
0.5%
5.0 61
 
1.1%
5.4 2
 
< 0.1%
5.5 2
 
< 0.1%
5.6 1
 
< 0.1%
5.7 1
 
< 0.1%
5.8 1
 
< 0.1%
ValueCountFrequency (%)
684.0 1
< 0.1%
409.0 1
< 0.1%
353.0 2
< 0.1%
281.0 1
< 0.1%
260.0 2
< 0.1%
238.0 1
< 0.1%
235.0 1
< 0.1%
227.0 2
< 0.1%
211.0 1
< 0.1%
209.0 2
< 0.1%

수리수문현황_계획하폭2
Real number (ℝ)

MISSING  ZEROS 

Distinct336
Distinct (%)6.3%
Missing67
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean34.915642
Minimum0
Maximum935
Zeros2007
Zeros (%)37.4%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:32.040709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median20
Q344
95-th percentile129
Maximum935
Range935
Interquartile range (IQR)44

Descriptive statistics

Standard deviation56.433308
Coefficient of variation (CV)1.6162758
Kurtosis40.501312
Mean34.915642
Median Absolute Deviation (MAD)20
Skewness4.6876059
Sum185157.65
Variance3184.7183
MonotonicityNot monotonic
2023-12-11T09:24:32.170747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2007
37.4%
20.0 120
 
2.2%
25.0 100
 
1.9%
30.0 92
 
1.7%
18.0 90
 
1.7%
40.0 90
 
1.7%
15.0 84
 
1.6%
24.0 75
 
1.4%
27.0 74
 
1.4%
28.0 68
 
1.3%
Other values (326) 2503
46.6%
(Missing) 67
 
1.2%
ValueCountFrequency (%)
0.0 2007
37.4%
4.0 3
 
0.1%
6.0 10
 
0.2%
7.0 2
 
< 0.1%
8.0 18
 
0.3%
9.0 6
 
0.1%
10.0 22
 
0.4%
11.0 27
 
0.5%
11.3 6
 
0.1%
12.0 37
 
0.7%
ValueCountFrequency (%)
935.0 1
 
< 0.1%
881.0 1
 
< 0.1%
670.0 2
< 0.1%
564.0 1
 
< 0.1%
559.0 2
< 0.1%
493.0 1
 
< 0.1%
453.0 1
 
< 0.1%
419.0 2
< 0.1%
408.0 1
 
< 0.1%
405.0 4
0.1%

제방_연장
Real number (ℝ)

ZEROS 

Distinct1857
Distinct (%)34.9%
Missing45
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean795.20682
Minimum0
Maximum19822
Zeros120
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:32.287073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile62
Q1235
median520
Q31034
95-th percentile2274.8
Maximum19822
Range19822
Interquartile range (IQR)799

Descriptive statistics

Standard deviation975.82218
Coefficient of variation (CV)1.22713
Kurtosis69.29975
Mean795.20682
Median Absolute Deviation (MAD)340
Skewness5.7844352
Sum4234476.3
Variance952228.94
MonotonicityNot monotonic
2023-12-11T09:24:32.396132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 120
 
2.2%
400.0 45
 
0.8%
200.0 41
 
0.8%
500.0 41
 
0.8%
300.0 35
 
0.7%
100.0 29
 
0.5%
220.0 22
 
0.4%
140.0 22
 
0.4%
700.0 22
 
0.4%
600.0 21
 
0.4%
Other values (1847) 4927
91.8%
(Missing) 45
 
0.8%
ValueCountFrequency (%)
0.0 120
2.2%
2.04 1
 
< 0.1%
3.0 2
 
< 0.1%
5.0 2
 
< 0.1%
6.0 1
 
< 0.1%
7.0 1
 
< 0.1%
10.0 5
 
0.1%
12.0 3
 
0.1%
13.0 1
 
< 0.1%
15.0 1
 
< 0.1%
ValueCountFrequency (%)
19822.0 1
< 0.1%
16945.0 1
< 0.1%
14637.0 1
< 0.1%
14412.0 1
< 0.1%
11991.0 1
< 0.1%
11760.0 1
< 0.1%
8400.0 1
< 0.1%
8312.0 1
< 0.1%
8211.31 1
< 0.1%
8173.0 1
< 0.1%

제방_둑마루표고_상류측
Real number (ℝ)

MISSING  ZEROS 

Distinct2745
Distinct (%)53.8%
Missing266
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean76.272882
Minimum0
Maximum772.28
Zeros1814
Zeros (%)33.8%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:32.508687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median21.89
Q399.715
95-th percentile347.5025
Maximum772.28
Range772.28
Interquartile range (IQR)99.715

Descriptive statistics

Standard deviation117.76422
Coefficient of variation (CV)1.5439854
Kurtosis5.0739457
Mean76.272882
Median Absolute Deviation (MAD)21.89
Skewness2.1579822
Sum389296.79
Variance13868.411
MonotonicityNot monotonic
2023-12-11T09:24:32.617404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1814
33.8%
17.0 8
 
0.1%
20.0 8
 
0.1%
9.0 6
 
0.1%
7.0 6
 
0.1%
14.0 6
 
0.1%
12.0 6
 
0.1%
16.0 5
 
0.1%
42.0 5
 
0.1%
32.47 5
 
0.1%
Other values (2735) 3235
60.2%
(Missing) 266
 
5.0%
ValueCountFrequency (%)
0.0 1814
33.8%
0.57 1
 
< 0.1%
0.6 1
 
< 0.1%
0.68 1
 
< 0.1%
0.8 1
 
< 0.1%
0.9 1
 
< 0.1%
1.47 1
 
< 0.1%
1.56 1
 
< 0.1%
2.0 2
 
< 0.1%
2.07 1
 
< 0.1%
ValueCountFrequency (%)
772.28 1
< 0.1%
772.19 1
< 0.1%
761.68 1
< 0.1%
747.14 1
< 0.1%
739.23 1
< 0.1%
738.98 1
< 0.1%
726.85 1
< 0.1%
710.31 1
< 0.1%
705.8 1
< 0.1%
702.12 1
< 0.1%

제방_둑마루표고_하류측
Real number (ℝ)

MISSING  ZEROS 

Distinct2721
Distinct (%)53.6%
Missing293
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean69.11064
Minimum0
Maximum767.55
Zeros1800
Zeros (%)33.5%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:32.761899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16.79
Q387.47
95-th percentile321.804
Maximum767.55
Range767.55
Interquartile range (IQR)87.47

Descriptive statistics

Standard deviation111.58848
Coefficient of variation (CV)1.6146354
Kurtosis5.8481073
Mean69.11064
Median Absolute Deviation (MAD)16.79
Skewness2.2736424
Sum350874.72
Variance12451.99
MonotonicityNot monotonic
2023-12-11T09:24:32.907229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1800
33.5%
7.0 11
 
0.2%
9.0 9
 
0.2%
19.0 7
 
0.1%
20.0 7
 
0.1%
14.0 7
 
0.1%
18.0 6
 
0.1%
15.28 5
 
0.1%
19.47 5
 
0.1%
15.0 5
 
0.1%
Other values (2711) 3215
59.9%
(Missing) 293
 
5.5%
ValueCountFrequency (%)
0.0 1800
33.5%
0.6 1
 
< 0.1%
0.63 1
 
< 0.1%
0.68 1
 
< 0.1%
0.73 1
 
< 0.1%
0.83 1
 
< 0.1%
0.98 1
 
< 0.1%
1.2 1
 
< 0.1%
1.29 1
 
< 0.1%
1.34 1
 
< 0.1%
ValueCountFrequency (%)
767.55 1
< 0.1%
767.35 1
< 0.1%
752.35 1
< 0.1%
741.43 1
< 0.1%
739.16 1
< 0.1%
736.15 1
< 0.1%
725.08 1
< 0.1%
701.74 1
< 0.1%
695.35 1
< 0.1%
691.71 1
< 0.1%

제방_둑마루턱의폭_마루1
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct115
Distinct (%)2.2%
Missing93
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean1.4455713
Minimum0
Maximum303
Zeros2540
Zeros (%)47.3%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:33.032012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q33
95-th percentile4.5
Maximum303
Range303
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.6017173
Coefficient of variation (CV)3.1833208
Kurtosis3497.175
Mean1.4455713
Median Absolute Deviation (MAD)0.5
Skewness53.601884
Sum7628.28
Variance21.175802
MonotonicityNot monotonic
2023-12-11T09:24:33.136592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2540
47.3%
3.0 645
 
12.0%
1.0 275
 
5.1%
2.0 273
 
5.1%
4.0 250
 
4.7%
0.5 184
 
3.4%
5.0 76
 
1.4%
1.5 76
 
1.4%
2.5 69
 
1.3%
0.6 65
 
1.2%
Other values (105) 824
 
15.3%
(Missing) 93
 
1.7%
ValueCountFrequency (%)
0.0 2540
47.3%
0.1 5
 
0.1%
0.2 18
 
0.3%
0.3 43
 
0.8%
0.4 28
 
0.5%
0.43 1
 
< 0.1%
0.5 184
 
3.4%
0.6 65
 
1.2%
0.7 20
 
0.4%
0.78 1
 
< 0.1%
ValueCountFrequency (%)
303.0 1
< 0.1%
30.5 1
< 0.1%
29.0 1
< 0.1%
20.0 2
< 0.1%
19.0 2
< 0.1%
18.0 1
< 0.1%
17.0 2
< 0.1%
14.0 1
< 0.1%
12.0 2
< 0.1%
10.8 1
< 0.1%

제방_둑마루턱의폭_마루2
Real number (ℝ)

MISSING  ZEROS 

Distinct166
Distinct (%)3.2%
Missing254
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean1.6492142
Minimum0
Maximum153
Zeros3377
Zeros (%)62.9%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:33.262646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6.7
Maximum153
Range153
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.7707168
Coefficient of variation (CV)2.2863717
Kurtosis524.61786
Mean1.6492142
Median Absolute Deviation (MAD)0
Skewness15.156589
Sum8437.38
Variance14.218305
MonotonicityNot monotonic
2023-12-11T09:24:33.379993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3377
62.9%
4.0 239
 
4.5%
3.0 179
 
3.3%
5.0 154
 
2.9%
3.5 72
 
1.3%
6.0 72
 
1.3%
4.5 55
 
1.0%
1.0 50
 
0.9%
2.0 38
 
0.7%
8.0 36
 
0.7%
Other values (156) 844
 
15.7%
(Missing) 254
 
4.7%
ValueCountFrequency (%)
0.0 3377
62.9%
0.13 1
 
< 0.1%
0.2 1
 
< 0.1%
0.3 3
 
0.1%
0.4 2
 
< 0.1%
0.5 16
 
0.3%
0.6 4
 
0.1%
0.7 8
 
0.1%
0.8 10
 
0.2%
0.9 7
 
0.1%
ValueCountFrequency (%)
153.0 1
< 0.1%
46.3 1
< 0.1%
42.6 1
< 0.1%
41.9 1
< 0.1%
39.2 1
< 0.1%
36.0 1
< 0.1%
34.5 1
< 0.1%
32.5 1
< 0.1%
31.6 1
< 0.1%
30.0 1
< 0.1%

소단폭
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
0.0
4992 
<NA>
 
368
3.5
 
4
3.0
 
3
2.0
 
2

Length

Max length4
Median length3
Mean length3.0685289
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 4992
93.0%
<NA> 368
 
6.9%
3.5 4
 
0.1%
3.0 3
 
0.1%
2.0 2
 
< 0.1%
0.5 1
 
< 0.1%

Length

2023-12-11T09:24:33.482853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:33.799778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 4992
93.0%
na 368
 
6.9%
3.5 4
 
0.1%
3.0 3
 
0.1%
2.0 2
 
< 0.1%
0.5 1
 
< 0.1%

소단폭_제내지
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
0.0
4997 
<NA>
 
368
3.0
 
4
2.5
 
1

Length

Max length4
Median length3
Mean length3.0685289
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 4997
93.1%
<NA> 368
 
6.9%
3.0 4
 
0.1%
2.5 1
 
< 0.1%

Length

2023-12-11T09:24:33.887521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:33.984533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 4997
93.1%
na 368
 
6.9%
3.0 4
 
0.1%
2.5 1
 
< 0.1%

소단폭_제외지
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
0.0
5000 
<NA>
 
368
3.0
 
1
2.5
 
1

Length

Max length4
Median length3
Mean length3.0685289
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 5000
93.1%
<NA> 368
 
6.9%
3.0 1
 
< 0.1%
2.5 1
 
< 0.1%

Length

2023-12-11T09:24:34.075629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:34.161789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 5000
93.1%
na 368
 
6.9%
3.0 1
 
< 0.1%
2.5 1
 
< 0.1%

천단폭
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.2%
Missing368
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean0.19122351
Minimum0
Maximum9
Zeros4683
Zeros (%)87.2%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:34.235551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.5
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.76619288
Coefficient of variation (CV)4.0067923
Kurtosis20.162533
Mean0.19122351
Median Absolute Deviation (MAD)0
Skewness4.2679962
Sum956.5
Variance0.58705153
MonotonicityNot monotonic
2023-12-11T09:24:34.311855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 4683
87.2%
3.0 174
 
3.2%
4.0 54
 
1.0%
2.0 49
 
0.9%
2.5 19
 
0.4%
1.5 11
 
0.2%
5.0 4
 
0.1%
1.0 3
 
0.1%
9.0 2
 
< 0.1%
6.0 2
 
< 0.1%
(Missing) 368
 
6.9%
ValueCountFrequency (%)
0.0 4683
87.2%
1.0 3
 
0.1%
1.5 11
 
0.2%
2.0 49
 
0.9%
2.5 19
 
0.4%
3.0 174
 
3.2%
3.5 1
 
< 0.1%
4.0 54
 
1.0%
5.0 4
 
0.1%
6.0 2
 
< 0.1%
ValueCountFrequency (%)
9.0 2
 
< 0.1%
6.0 2
 
< 0.1%
5.0 4
 
0.1%
4.0 54
 
1.0%
3.5 1
 
< 0.1%
3.0 174
3.2%
2.5 19
 
0.4%
2.0 49
 
0.9%
1.5 11
 
0.2%
1.0 3
 
0.1%

축제고_최대
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct120
Distinct (%)2.4%
Missing368
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean32.371969
Minimum0
Maximum65780
Zeros4616
Zeros (%)86.0%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:34.407334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum65780
Range65780
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1265.0653
Coefficient of variation (CV)39.079036
Kurtosis2423.1801
Mean32.371969
Median Absolute Deviation (MAD)0
Skewness48.757201
Sum161924.59
Variance1600390.3
MonotonicityNot monotonic
2023-12-11T09:24:34.515357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4616
86.0%
3.0 63
 
1.2%
4.0 36
 
0.7%
3.5 22
 
0.4%
2.0 21
 
0.4%
5.0 13
 
0.2%
4.5 10
 
0.2%
6.0 9
 
0.2%
2.5 8
 
0.1%
3.6 8
 
0.1%
Other values (110) 196
 
3.6%
(Missing) 368
 
6.9%
ValueCountFrequency (%)
0.0 4616
86.0%
0.6 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 6
 
0.1%
1.11 1
 
< 0.1%
1.2 2
 
< 0.1%
1.22 1
 
< 0.1%
1.27 1
 
< 0.1%
1.3 2
 
< 0.1%
1.47 1
 
< 0.1%
ValueCountFrequency (%)
65780.0 1
< 0.1%
59309.0 1
< 0.1%
8646.0 1
< 0.1%
4261.0 1
< 0.1%
4122.0 2
< 0.1%
4111.0 1
< 0.1%
3187.0 1
< 0.1%
3044.0 1
< 0.1%
308.72 1
< 0.1%
308.67 1
< 0.1%

축제고_평균
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct116
Distinct (%)2.3%
Missing368
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean35.392323
Minimum0
Maximum97062
Zeros4616
Zeros (%)86.0%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:34.624144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.4
Maximum97062
Range97062
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1457.1144
Coefficient of variation (CV)41.170352
Kurtosis3972.1267
Mean35.392323
Median Absolute Deviation (MAD)0
Skewness61.020611
Sum177032.4
Variance2123182.4
MonotonicityNot monotonic
2023-12-11T09:24:34.732440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4616
86.0%
2.0 53
 
1.0%
3.0 50
 
0.9%
2.5 25
 
0.5%
4.0 23
 
0.4%
3.5 19
 
0.4%
1.0 17
 
0.3%
1.8 10
 
0.2%
2.4 8
 
0.1%
2.8 8
 
0.1%
Other values (106) 173
 
3.2%
(Missing) 368
 
6.9%
ValueCountFrequency (%)
0.0 4616
86.0%
0.4 1
 
< 0.1%
0.5 1
 
< 0.1%
0.6 2
 
< 0.1%
0.75 1
 
< 0.1%
0.85 1
 
< 0.1%
0.9 2
 
< 0.1%
1.0 17
 
0.3%
1.11 1
 
< 0.1%
1.2 3
 
0.1%
ValueCountFrequency (%)
97062.0 1
< 0.1%
30546.0 1
< 0.1%
9677.0 1
< 0.1%
7368.0 1
< 0.1%
7129.0 1
< 0.1%
3859.0 1
< 0.1%
3839.0 1
< 0.1%
3600.0 1
< 0.1%
3576.0 1
< 0.1%
2854.0 1
< 0.1%

설치사업명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
<NA>
4495 
0
875 

Length

Max length4
Median length4
Mean length3.5111732
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4495
83.7%
0 875
 
16.3%

Length

2023-12-11T09:24:34.833841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:34.908702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4495
83.7%
0 875
 
16.3%

시행기관
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
<NA>
4495 
0
875 

Length

Max length4
Median length4
Mean length3.5111732
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4495
83.7%
0 875
 
16.3%

Length

2023-12-11T09:24:34.999764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:35.072902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4495
83.7%
0 875
 
16.3%

시공회사
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
<NA>
4495 
0
875 

Length

Max length4
Median length4
Mean length3.5111732
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4495
83.7%
0 875
 
16.3%

Length

2023-12-11T09:24:35.155115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:35.235001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4495
83.7%
0 875
 
16.3%

공사기간
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
<NA>
4518 
0
852 

Length

Max length4
Median length4
Mean length3.5240223
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4518
84.1%
0 852
 
15.9%

Length

2023-12-11T09:24:35.317108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:35.394712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4518
84.1%
0 852
 
15.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
<NA>
4518 
0
852 

Length

Max length4
Median length4
Mean length3.5240223
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4518
84.1%
0 852
 
15.9%

Length

2023-12-11T09:24:35.475814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:35.555226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4518
84.1%
0 852
 
15.9%

주요시설현황_배수통관
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)2.9%
Missing4460
Missing (%)83.1%
Infinite0
Infinite (%)0.0%
Mean0.69120879
Minimum0
Maximum94
Zeros852
Zeros (%)15.9%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:35.632674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum94
Range94
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.0135383
Coefficient of variation (CV)7.2532907
Kurtosis166.86795
Mean0.69120879
Median Absolute Deviation (MAD)0
Skewness11.533164
Sum629
Variance25.135566
MonotonicityNot monotonic
2023-12-11T09:24:35.721405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 852
 
15.9%
1 18
 
0.3%
2 9
 
0.2%
5 4
 
0.1%
3 3
 
0.1%
4 3
 
0.1%
26 2
 
< 0.1%
40 1
 
< 0.1%
13 1
 
< 0.1%
6 1
 
< 0.1%
Other values (16) 16
 
0.3%
(Missing) 4460
83.1%
ValueCountFrequency (%)
0 852
15.9%
1 18
 
0.3%
2 9
 
0.2%
3 3
 
0.1%
4 3
 
0.1%
5 4
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
94 1
< 0.1%
55 1
< 0.1%
47 1
< 0.1%
40 1
< 0.1%
39 1
< 0.1%
31 1
< 0.1%
29 1
< 0.1%
28 1
< 0.1%
26 2
< 0.1%
20 1
< 0.1%

주요시설현황_배수암거
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.3%
Missing4475
Missing (%)83.3%
Infinite0
Infinite (%)0.0%
Mean0.16536313
Minimum0
Maximum21
Zeros852
Zeros (%)15.9%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:35.803286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum21
Range21
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1059764
Coefficient of variation (CV)6.6881679
Kurtosis170.98761
Mean0.16536313
Median Absolute Deviation (MAD)0
Skewness11.458799
Sum148
Variance1.2231837
MonotonicityNot monotonic
2023-12-11T09:24:35.880233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 852
 
15.9%
1 16
 
0.3%
2 8
 
0.1%
3 7
 
0.1%
4 3
 
0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
21 1
 
< 0.1%
5 1
 
< 0.1%
10 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 4475
83.3%
ValueCountFrequency (%)
0 852
15.9%
1 16
 
0.3%
2 8
 
0.1%
3 7
 
0.1%
4 3
 
0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
21 1
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
8 2
 
< 0.1%
7 1
 
< 0.1%
6 2
 
< 0.1%
5 1
 
< 0.1%
4 3
 
0.1%
3 7
0.1%
2 8
0.1%

주요시설현황_보
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.8%
Missing4473
Missing (%)83.3%
Infinite0
Infinite (%)0.0%
Mean0.098104794
Minimum0
Maximum6
Zeros852
Zeros (%)15.9%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:35.955410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.2
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.51034693
Coefficient of variation (CV)5.2020591
Kurtosis51.473155
Mean0.098104794
Median Absolute Deviation (MAD)0
Skewness6.6687987
Sum88
Variance0.26045399
MonotonicityNot monotonic
2023-12-11T09:24:36.029933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 852
 
15.9%
1 23
 
0.4%
2 10
 
0.2%
3 6
 
0.1%
4 4
 
0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 4473
83.3%
ValueCountFrequency (%)
0 852
15.9%
1 23
 
0.4%
2 10
 
0.2%
3 6
 
0.1%
4 4
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 1
 
< 0.1%
4 4
 
0.1%
3 6
 
0.1%
2 10
 
0.2%
1 23
 
0.4%
0 852
15.9%

주요시설현황_낙차공
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)2.3%
Missing4465
Missing (%)83.1%
Infinite0
Infinite (%)0.0%
Mean0.45524862
Minimum0
Maximum56
Zeros852
Zeros (%)15.9%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:36.114159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum56
Range56
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1430563
Coefficient of variation (CV)6.9040435
Kurtosis152.66129
Mean0.45524862
Median Absolute Deviation (MAD)0
Skewness11.133207
Sum412
Variance9.8788026
MonotonicityNot monotonic
2023-12-11T09:24:36.203232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 852
 
15.9%
2 12
 
0.2%
1 12
 
0.2%
3 5
 
0.1%
10 3
 
0.1%
15 2
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
5 2
 
< 0.1%
4 2
 
< 0.1%
Other values (11) 11
 
0.2%
(Missing) 4465
83.1%
ValueCountFrequency (%)
0 852
15.9%
1 12
 
0.2%
2 12
 
0.2%
3 5
 
0.1%
4 2
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
56 1
< 0.1%
39 1
< 0.1%
29 1
< 0.1%
28 1
< 0.1%
23 1
< 0.1%
21 1
< 0.1%
17 1
< 0.1%
15 2
< 0.1%
12 1
< 0.1%
11 1
< 0.1%

주요시설현황_기타
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
<NA>
4514 
0
852 
교량3개소
 
2
2
 
1
교량6개소
 
1

Length

Max length5
Median length4
Mean length3.5240223
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4514
84.1%
0 852
 
15.9%
교량3개소 2
 
< 0.1%
2 1
 
< 0.1%
교량6개소 1
 
< 0.1%

Length

2023-12-11T09:24:36.313377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:36.448808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4514
84.1%
0 852
 
15.9%
교량3개소 2
 
< 0.1%
2 1
 
< 0.1%
교량6개소 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
<NA>
4518 
0
852 

Length

Max length4
Median length4
Mean length3.5240223
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4518
84.1%
0 852
 
15.9%

Length

2023-12-11T09:24:36.570247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:24:36.677240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4518
84.1%
0 852
 
15.9%

시설등록 및 관리담당_등록일자
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.2%
Missing518
Missing (%)9.6%
Infinite0
Infinite (%)0.0%
Mean0.012840066
Minimum0
Maximum4
Zeros4820
Zeros (%)89.8%
Negative0
Negative (%)0.0%
Memory size47.3 KiB
2023-12-11T09:24:36.761702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4
Range4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.18961388
Coefficient of variation (CV)14.767361
Kurtosis333.44126
Mean0.012840066
Median Absolute Deviation (MAD)0
Skewness17.61459
Sum62.3
Variance0.035953425
MonotonicityNot monotonic
2023-12-11T09:24:36.897489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 4820
89.8%
1.0 11
 
0.2%
4.0 6
 
0.1%
3.0 4
 
0.1%
0.5 3
 
0.1%
2.0 3
 
0.1%
1.1 2
 
< 0.1%
3.8 1
 
< 0.1%
0.2 1
 
< 0.1%
1.6 1
 
< 0.1%
(Missing) 518
 
9.6%
ValueCountFrequency (%)
0.0 4820
89.8%
0.2 1
 
< 0.1%
0.5 3
 
0.1%
1.0 11
 
0.2%
1.1 2
 
< 0.1%
1.6 1
 
< 0.1%
2.0 3
 
0.1%
3.0 4
 
0.1%
3.8 1
 
< 0.1%
4.0 6
 
0.1%
ValueCountFrequency (%)
4.0 6
 
0.1%
3.8 1
 
< 0.1%
3.0 4
 
0.1%
2.0 3
 
0.1%
1.6 1
 
< 0.1%
1.1 2
 
< 0.1%
1.0 11
 
0.2%
0.5 3
 
0.1%
0.2 1
 
< 0.1%
0.0 4820
89.8%

Sample

하천관리코드구분코드일련번호제방명하천명하천등급좌우안 코드기점_동코드기점_기타주소기점_지번_본번기점_지번_부번기점_측점번호기점_산지종점_동코드종점_기타주소종점_지번_본번종점_지번_부번종점_측점번호보호면적 및 시설개수구간_비고수리수문현황_하구로부터제방종점까지의거리수리수문현황_비고비탈구배_제내지비탈구배_제외지종점_산지수리수문현황_계획홍수량1수리수문현황_계획홍수량2수리수문현황_계획홍수위시점수리수문현황_계획홍수위종점수리수문현황_계획하폭1수리수문현황_계획하폭2제방_연장제방_둑마루표고_상류측제방_둑마루표고_하류측제방_둑마루턱의폭_마루1제방_둑마루턱의폭_마루2소단폭소단폭_제내지소단폭_제외지천단폭축제고_최대축제고_평균설치사업명시행기관시공회사공사기간주요시설현황_구분주요시설현황_배수통관주요시설현황_배수암거주요시설현황_보주요시설현황_낙차공주요시설현황_기타시설등록 및 관리담당_등록기관시설등록 및 관리담당_등록일자
020231102014F02Q0101B011대산좌1대산천지방하천D014888037023경남 거창군 남상면 둔동리 (No.74+20)000074+0020M004888037027경남 거창군 남상면 오계리 (No.60+00)00<NA>0.0<NA>0.001:010M00180.0235.0238.48221.6835.056.01420.0239.11224.862.04.00.00.00.00.00.00.0000<NA><NA><NA><NA><NA><NA><NA><NA><NA>
140226702016F01Q0101B017신성우2제신성천지방하천D024885032024경남 하동군 악양면 신성리 355번지선<NA>00000+0000M004885032024경남 하동군 악양면 신성리 407번지선<NA>0<NA>0.0<NA>1.62001:01.5<NA>M0064.00.0119.9692.88.013.0280.0120.0992.850.00.00.00.00.00.00.00.000000000000<NA>
240226502016F02Q0101B012악양우1제악양천지방하천D024885032023경남 하동군 악양면 신대리 831-3번지선<NA><NA>0000+0000M004885032021경남 하동군 악양면 미점리 310-2번지선<NA><NA><NA>0.0<NA>0.0001:00.2<NA>M00855.00.012.9412.7560.0126.02000.016.2715.472.56.80.00.00.00.00.00.000000000000<NA>
320231102014F02Q0101B018대산우1대산천지방하천D024888037027경남 거창군 남상면 오계리 (No.74+73)000074+0073M004888037027경남 거창군 남상면 오계리 (No.60+00)00<NA>0.0<NA>0.0001:01.50M00180.0235.0239.25221.6835.055.01473.0240.48222.352.03.00.00.00.00.00.00.0000<NA><NA><NA><NA><NA><NA><NA><NA><NA>
420268902015F02Q0101B018용덕우4제용덕천지방하천D024825034024경남 김해시 한림면 신천리 389-15도<NA><NA>0000+0000M004825034024경남 김해시 한림면 신천리 375-4창<NA><NA><NA>0.0<NA>4.884001:02.40M0060.00.048.4533.049.017.0726.051.1333.213.90.00.00.00.00.00.00.0000<NA><NA><NA><NA><NA><NA><NA><NA><NA>
520268602015F02Q0101B012퇴래우1제퇴래천지방하천D024825034021경남 김해시 한림면 명동리 17-1도<NA><NA>0000+0000M004825034027경남 김해시 한림면 안하리 2014도<NA>0<NA>0.0<NA>0.001.80M00125.00.08.047.9635.057.0375.08.519.970.00.00.00.00.00.00.00.0000<NA><NA><NA><NA><NA><NA><NA><NA><NA>
620268602015F02Q0101B013퇴래우2제퇴래천지방하천D024825034021경남 김해시 한림면 명동리 8-7대<NA><NA>0000+0000M004825034021경남 김해시 한림면 명동리 11-2구<NA><NA><NA>0.0<NA>0.37501.90M00125.00.08.138.0445.072.0183.08.768.510.00.00.00.00.00.00.00.0000<NA><NA><NA><NA><NA><NA><NA><NA><NA>
740226702016F01Q0101B011무제부신성천지방하천D00<NA><NA>000000+0000M00<NA>000<NA>0.0<NA>0.0000M000.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0000000000000.0
820268902015F02Q0101B017용덕우3제용덕천지방하천D024825034024경남 김해시 한림면 신천리 240-1잡<NA><NA>0000+0000M004825034024경남 김해시 한림면 신천리 58-4답<NA><NA><NA>0.0<NA>4.68001:01.50M00120.0135.032.5230.1411.016.0194.032.9530.150.00.00.00.00.00.00.00.0000<NA><NA><NA><NA><NA><NA><NA><NA><NA>
940226702016F01Q0101B014신성좌4제신성천지방하천D014885032024경남 하동군 악양면 신성리 210-1지선<NA><NA>0000+0000M004885032024경남 하동군 악양면 신성리 224번지선<NA><NA><NA>0.0<NA>1.64001:00.4<NA>M0064.00.0106.9297.1412.013.0108.0115.0197.190.00.00.00.00.00.00.00.000000000000<NA>
하천관리코드구분코드일련번호제방명하천명하천등급좌우안 코드기점_동코드기점_기타주소기점_지번_본번기점_지번_부번기점_측점번호기점_산지종점_동코드종점_기타주소종점_지번_본번종점_지번_부번종점_측점번호보호면적 및 시설개수구간_비고수리수문현황_하구로부터제방종점까지의거리수리수문현황_비고비탈구배_제내지비탈구배_제외지종점_산지수리수문현황_계획홍수량1수리수문현황_계획홍수량2수리수문현황_계획홍수위시점수리수문현황_계획홍수위종점수리수문현황_계획하폭1수리수문현황_계획하폭2제방_연장제방_둑마루표고_상류측제방_둑마루표고_하류측제방_둑마루턱의폭_마루1제방_둑마루턱의폭_마루2소단폭소단폭_제내지소단폭_제외지천단폭축제고_최대축제고_평균설치사업명시행기관시공회사공사기간주요시설현황_구분주요시설현황_배수통관주요시설현황_배수암거주요시설현황_보주요시설현황_낙차공주요시설현황_기타시설등록 및 관리담당_등록기관시설등록 및 관리담당_등록일자
536020259202020F02Q0101B019의령좌6제의령천지방하천D014872031028경남 의령군 가례면 대천리 410-341030008+0950<NA>4872031028경남 의령군 가례면 대천리 76-17610007+0890<NA><NA>7.89<NA><NA><NA><NA>554.0456.043.6937.3548.083.01060.045.0938.760.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>1<NA><NA><NA><NA>
536120259202020F02Q0101B0110의령좌7제의령천지방하천D014872032023경남 의령군 칠곡면 신포리 744-23744230010+0750<NA>4872031028경남 의령군 가례면 대천리 410-341030008+0950<NA><NA>8.95<NA><NA><NA><NA>456.0347.057.7143.6928.090.01800.057.3845.093.87.5<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>525<NA><NA><NA><NA>
536220259202020F02Q0101B0111의령우5제의령천지방하천D024872031028경남 의령군 가례면 대천리 260-126010008+0130<NA>4872031028경남 의령군 가례면 대천리 606000006+0590<NA><NA>7.94<NA><NA><NA><NA>554.0<NA>38.6937.5968.083.0195.040.7239.270.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>13<NA><NA><NA><NA>
536320259202020F02Q0101B0112의령우6제의령천지방하천D024872031028경남 의령군 가례면 대천리 47847800009+0480<NA>4872031028경남 의령군 가례면 대천리 260-126010008+0130<NA><NA>8.13<NA><NA><NA><NA>554.0456.048.1838.6948.090.01350.049.0540.722.04.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3<NA><NA><NA><NA>
536420259202020F02Q0101B0113의령우7제의령천지방하천D024872031029경남 의령군 가례면 봉두리 89-2489240010+0260<NA>4872031029경남 의령군 가례면 봉두리 909000009+0615<NA><NA>9.62<NA><NA><NA><NA>456.0347.053.9148.7840.059.0640.053.9850.182.54.3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>12<NA><NA><NA><NA>
536520259202020F02Q0101B0114의령우8제의령천지방하천D024872031029경남 의령군 가례면 봉두리 27627600010+0440<NA>4872031029경남 의령군 가례면 봉두리 28628600010+0360<NA><NA>10.36<NA><NA><NA><NA>347.0<NA>55.3154.7540.0<NA>80.054.855.110.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA>
536627205702020F02Q0101B0115안정좌1제안정천지방하천D024822034027경상남도 통영시 광도면 안정리 1109-8110980001+0700<NA>4822034027경상남도 통영시 광도면 안정리 1186118600001+0409<NA><NA>1.409<NA>01:00.5<NA><NA>96.0<NA>26.6718.4314.021.0291.026.921.030.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
536727205702020F02Q0101B0116안정좌2제안정천지방하천D024822034027경상남도 통영시 광도면 안정리 1337-1133710002+0200<NA>4822034027경상남도 통영시 광도면 안정리 1109-8110980001+0700<NA><NA>1.7<NA>01:00.5<NA><NA>96.0<NA>39.4326.6715.027.0500.041.5626.90.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
536827205702020F02Q0101B0117안정좌3제안정천지방하천D024822034027경상남도 통영시 광도면 안정리 1339133900002+0287<NA>4822034027경상남도 통영시 광도면 안정리 1337-1133710002+0200<NA><NA>2.2<NA>01:00.5<NA><NA>96.0<NA>50.5439.437.025.087.049.8641.560.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
536927205702020F02Q0101B0118안정우1제안정천지방하천D024822034027경상남도 통영시 광도면 안정리 1341-1134110002+0225<NA>4822034027경상남도 통영시 광도면 안정리 1355135500002+0000<NA><NA>2.0<NA>01:00.5<NA><NA>96.0<NA>45.6732.8717.027.0225.046.8634.193.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>