Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory732.4 KiB
Average record size in memory75.0 B

Variable types

Numeric4
Text3
Categorical1

Dataset

Description공공데이터 중장기 개방계획에 따라 공개하는 경상남도 하천관리 시스템의 데이터 입니다. 하천관리시스템의 횡단 정보를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15093457

Alerts

구분코드 has constant value ""Constant
일련번호 is highly overall correlated with 종단측점_일련번호High correlation
종단측점_일련번호 is highly overall correlated with 일련번호High correlation
라벨 is highly skewed (γ1 = 28.18505054)Skewed
공간아이디 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:36:47.390991
Analysis finished2023-12-10 23:38:21.775611
Duration1 minute and 34.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간아이디
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean224107.55
Minimum180341
Maximum267187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:38:21.859289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum180341
5-th percentile184743.45
Q1201999.75
median224290.5
Q3245863.25
95-th percentile262928.05
Maximum267187
Range86846
Interquartile range (IQR)43863.5

Descriptive statistics

Standard deviation25102.871
Coefficient of variation (CV)0.11201261
Kurtosis-1.201707
Mean224107.55
Median Absolute Deviation (MAD)21899.5
Skewness-0.023583798
Sum2.2410755 × 109
Variance6.3015413 × 108
MonotonicityNot monotonic
2023-12-11T08:38:22.016339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
238229 1
 
< 0.1%
238286 1
 
< 0.1%
220815 1
 
< 0.1%
228945 1
 
< 0.1%
228231 1
 
< 0.1%
183255 1
 
< 0.1%
233099 1
 
< 0.1%
218344 1
 
< 0.1%
230716 1
 
< 0.1%
256175 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
180341 1
< 0.1%
180362 1
< 0.1%
180384 1
< 0.1%
180388 1
< 0.1%
180389 1
< 0.1%
180395 1
< 0.1%
180396 1
< 0.1%
180414 1
< 0.1%
180419 1
< 0.1%
180432 1
< 0.1%
ValueCountFrequency (%)
267187 1
< 0.1%
267185 1
< 0.1%
267176 1
< 0.1%
267166 1
< 0.1%
267161 1
< 0.1%
267153 1
< 0.1%
267150 1
< 0.1%
267119 1
< 0.1%
267100 1
< 0.1%
267087 1
< 0.1%

하천관리코드
Text

Distinct112
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:38:22.270377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters190000
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

Unique0 ?
Unique (%)0.0%

Sample

1st row20266602013F02Q0101
2nd row20262602016F02Q0102
3rd row20260602011F01Q0101
4th row20266102010F01Q0101
5th row20265802017F02Q0101
ValueCountFrequency (%)
20268002012f02q0101 1603
 
16.0%
20262602016f02q0102 707
 
7.1%
20268702008f02q0101 322
 
3.2%
20261102010f02q0101 290
 
2.9%
20261502014f02q0101 202
 
2.0%
20260602011f01q0101 200
 
2.0%
20265801995f02q0101 192
 
1.9%
20261102014f02q0101 186
 
1.9%
20264102018f02q0101 181
 
1.8%
20266102010f01q0101 180
 
1.8%
Other values (102) 5937
59.4%
2023-12-11T08:38:22.647308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 65487
34.5%
2 39658
20.9%
1 34246
18.0%
6 13987
 
7.4%
F 10000
 
5.3%
Q 10000
 
5.3%
8 4219
 
2.2%
9 2944
 
1.5%
5 2638
 
1.4%
4 2447
 
1.3%
Other values (2) 4374
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 170000
89.5%
Uppercase Letter 20000
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 65487
38.5%
2 39658
23.3%
1 34246
20.1%
6 13987
 
8.2%
8 4219
 
2.5%
9 2944
 
1.7%
5 2638
 
1.6%
4 2447
 
1.4%
3 2393
 
1.4%
7 1981
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
F 10000
50.0%
Q 10000
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 170000
89.5%
Latin 20000
 
10.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 65487
38.5%
2 39658
23.3%
1 34246
20.1%
6 13987
 
8.2%
8 4219
 
2.5%
9 2944
 
1.7%
5 2638
 
1.6%
4 2447
 
1.4%
3 2393
 
1.4%
7 1981
 
1.2%
Latin
ValueCountFrequency (%)
F 10000
50.0%
Q 10000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 190000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 65487
34.5%
2 39658
20.9%
1 34246
18.0%
6 13987
 
7.4%
F 10000
 
5.3%
Q 10000
 
5.3%
8 4219
 
2.2%
9 2944
 
1.5%
5 2638
 
1.4%
4 2447
 
1.3%
Other values (2) 4374
 
2.3%

구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
E01
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowE01
2nd rowE01
3rd rowE01
4th rowE01
5th rowE01

Common Values

ValueCountFrequency (%)
E01 10000
100.0%

Length

2023-12-11T08:38:22.776946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:38:22.856447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
e01 10000
100.0%

일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct3521
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1700.5431
Minimum1
Maximum13722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:38:22.942313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile39
Q1209.75
median514.5
Q31355
95-th percentile9382.2
Maximum13722
Range13721
Interquartile range (IQR)1145.25

Descriptive statistics

Standard deviation2893.5616
Coefficient of variation (CV)1.7015515
Kurtosis5.3435044
Mean1700.5431
Median Absolute Deviation (MAD)380
Skewness2.4608415
Sum17005431
Variance8372698.9
MonotonicityNot monotonic
2023-12-11T08:38:23.063514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 20
 
0.2%
101 20
 
0.2%
54 20
 
0.2%
24 19
 
0.2%
88 19
 
0.2%
182 19
 
0.2%
39 19
 
0.2%
64 19
 
0.2%
158 19
 
0.2%
118 18
 
0.2%
Other values (3511) 9808
98.1%
ValueCountFrequency (%)
1 10
0.1%
2 18
0.2%
3 18
0.2%
4 12
0.1%
5 11
0.1%
6 16
0.2%
7 20
0.2%
8 15
0.1%
9 10
0.1%
10 17
0.2%
ValueCountFrequency (%)
13722 1
< 0.1%
13702 1
< 0.1%
13688 1
< 0.1%
13680 1
< 0.1%
13668 1
< 0.1%
13666 1
< 0.1%
13658 1
< 0.1%
13650 1
< 0.1%
13644 1
< 0.1%
13622 1
< 0.1%

측점번호
Text

Distinct760
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:38:23.357684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length9.0029
Min length9

Characters and Unicode

Total characters90029
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

Unique193 ?
Unique (%)1.9%

Sample

1st row0040+0000
2nd row0005+0000
3rd row0001+0350
4th row0011+0000
5th row0000+0700
ValueCountFrequency (%)
0000+0000 191
 
1.9%
0002+0000 191
 
1.9%
0001+0000 182
 
1.8%
0008+0000 177
 
1.8%
0005+0000 166
 
1.7%
0003+0000 162
 
1.6%
0006+0000 161
 
1.6%
0011+0000 158
 
1.6%
0007+0000 152
 
1.5%
0010+0000 151
 
1.5%
Other values (748) 8309
83.1%
2023-12-11T08:38:23.782151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 60715
67.4%
+ 10000
 
11.1%
1 4075
 
4.5%
5 2884
 
3.2%
2 2862
 
3.2%
3 2311
 
2.6%
4 1924
 
2.1%
6 1468
 
1.6%
7 1400
 
1.6%
8 1236
 
1.4%
Other values (3) 1154
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80011
88.9%
Math Symbol 10000
 
11.1%
Other Punctuation 11
 
< 0.1%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 60715
75.9%
1 4075
 
5.1%
5 2884
 
3.6%
2 2862
 
3.6%
3 2311
 
2.9%
4 1924
 
2.4%
6 1468
 
1.8%
7 1400
 
1.7%
8 1236
 
1.5%
9 1136
 
1.4%
Math Symbol
ValueCountFrequency (%)
+ 10000
100.0%
Other Punctuation
ValueCountFrequency (%)
. 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 90029
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 60715
67.4%
+ 10000
 
11.1%
1 4075
 
4.5%
5 2884
 
3.2%
2 2862
 
3.2%
3 2311
 
2.6%
4 1924
 
2.1%
6 1468
 
1.6%
7 1400
 
1.6%
8 1236
 
1.4%
Other values (3) 1154
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 60715
67.4%
+ 10000
 
11.1%
1 4075
 
4.5%
5 2884
 
3.2%
2 2862
 
3.2%
3 2311
 
2.6%
4 1924
 
2.1%
6 1468
 
1.6%
7 1400
 
1.6%
8 1236
 
1.4%
Other values (3) 1154
 
1.3%

라벨
Real number (ℝ)

SKEWED 

Distinct5282
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.72287
Minimum-5.43
Maximum2757.05
Zeros1
Zeros (%)< 0.1%
Negative80
Negative (%)0.8%
Memory size166.0 KiB
2023-12-11T08:38:23.915127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5.43
5-th percentile2.33
Q17.26375
median16.51
Q345.62
95-th percentile100.792
Maximum2757.05
Range2762.48
Interquartile range (IQR)38.35625

Descriptive statistics

Standard deviation49.365418
Coefficient of variation (CV)1.556146
Kurtosis1442.2576
Mean31.72287
Median Absolute Deviation (MAD)12.16
Skewness28.185051
Sum317228.7
Variance2436.9445
MonotonicityNot monotonic
2023-12-11T08:38:24.032348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.0 30
 
0.3%
13.0 23
 
0.2%
8.0 20
 
0.2%
11.0 19
 
0.2%
6.0 18
 
0.2%
9.0 17
 
0.2%
9.28 16
 
0.2%
10.0 15
 
0.1%
15.0 15
 
0.1%
10.5 15
 
0.1%
Other values (5272) 9812
98.1%
ValueCountFrequency (%)
-5.43 1
< 0.1%
-2.3 1
< 0.1%
-1.86 1
< 0.1%
-1.68 1
< 0.1%
-1.62 1
< 0.1%
-1.56 1
< 0.1%
-1.55 1
< 0.1%
-1.4 1
< 0.1%
-1.38 1
< 0.1%
-1.28 1
< 0.1%
ValueCountFrequency (%)
2757.05 1
< 0.1%
2382.0 1
< 0.1%
278.69 1
< 0.1%
278.32 1
< 0.1%
277.09 1
< 0.1%
245.67 1
< 0.1%
241.82 1
< 0.1%
239.23 1
< 0.1%
236.79 1
< 0.1%
235.95 1
< 0.1%

종단측점_일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct298
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.606
Minimum0
Maximum1002
Zeros13
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:38:24.170738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q118
median38
Q368
95-th percentile168
Maximum1002
Range1002
Interquartile range (IQR)50

Descriptive statistics

Standard deviation55.613653
Coefficient of variation (CV)1.0571732
Kurtosis24.272552
Mean52.606
Median Absolute Deviation (MAD)24
Skewness3.3068064
Sum526060
Variance3092.8785
MonotonicityNot monotonic
2023-12-11T08:38:24.302922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 191
 
1.9%
1 180
 
1.8%
4 163
 
1.6%
7 161
 
1.6%
10 160
 
1.6%
13 159
 
1.6%
3 159
 
1.6%
20 152
 
1.5%
9 144
 
1.4%
5 144
 
1.4%
Other values (288) 8387
83.9%
ValueCountFrequency (%)
0 13
 
0.1%
1 180
1.8%
2 121
1.2%
3 159
1.6%
4 163
1.6%
5 144
1.4%
6 191
1.9%
7 161
1.6%
8 135
1.4%
9 144
1.4%
ValueCountFrequency (%)
1002 1
 
< 0.1%
821 1
 
< 0.1%
815 1
 
< 0.1%
812 1
 
< 0.1%
327 2
< 0.1%
326 2
< 0.1%
325 3
< 0.1%
324 2
< 0.1%
323 4
< 0.1%
322 1
 
< 0.1%

공간정보
Text

Distinct9998
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:38:24.511987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length45
Mean length44.4772
Min length41

Characters and Unicode

Total characters444772
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9996 ?
Unique (%)> 99.9%

Sample

1st rowPOINT (1102384.96788096 1724013.3161328847)
2nd rowPOINT (1087414.2366284681 1715343.8885639296)
3rd rowPOINT (1076882.0000155717 1695605.8718460014)
4th rowPOINT (1101861.1093126368 1728068.7336608355)
5th rowPOINT (1104496.605496301 1710383.5933185178)
ValueCountFrequency (%)
point 10000
33.3%
1709701.5435747898 2
 
< 0.1%
1110376.40034697 2
 
< 0.1%
1711441.1973178629 2
 
< 0.1%
1110098.9469189085 2
 
< 0.1%
1699585.2729530453 1
 
< 0.1%
1093218.1939057577 1
 
< 0.1%
1700359.2675706693 1
 
< 0.1%
1119464.165067809 1
 
< 0.1%
1709315.0292373118 1
 
< 0.1%
Other values (19987) 19987
66.6%
2023-12-11T08:38:24.895046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 55132
12.4%
0 36708
 
8.3%
7 35417
 
8.0%
6 31311
 
7.0%
8 31251
 
7.0%
9 30580
 
6.9%
2 29193
 
6.6%
4 28790
 
6.5%
3 28218
 
6.3%
5 28172
 
6.3%
Other values (9) 110000
24.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 334772
75.3%
Uppercase Letter 50000
 
11.2%
Space Separator 20000
 
4.5%
Other Punctuation 20000
 
4.5%
Open Punctuation 10000
 
2.2%
Close Punctuation 10000
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 55132
16.5%
0 36708
11.0%
7 35417
10.6%
6 31311
9.4%
8 31251
9.3%
9 30580
9.1%
2 29193
8.7%
4 28790
8.6%
3 28218
8.4%
5 28172
8.4%
Uppercase Letter
ValueCountFrequency (%)
O 10000
20.0%
T 10000
20.0%
N 10000
20.0%
I 10000
20.0%
P 10000
20.0%
Space Separator
ValueCountFrequency (%)
20000
100.0%
Other Punctuation
ValueCountFrequency (%)
. 20000
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10000
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 394772
88.8%
Latin 50000
 
11.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 55132
14.0%
0 36708
9.3%
7 35417
9.0%
6 31311
7.9%
8 31251
7.9%
9 30580
7.7%
2 29193
7.4%
4 28790
7.3%
3 28218
7.1%
5 28172
7.1%
Other values (4) 60000
15.2%
Latin
ValueCountFrequency (%)
O 10000
20.0%
T 10000
20.0%
N 10000
20.0%
I 10000
20.0%
P 10000
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 444772
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 55132
12.4%
0 36708
 
8.3%
7 35417
 
8.0%
6 31311
 
7.0%
8 31251
 
7.0%
9 30580
 
6.9%
2 29193
 
6.6%
4 28790
 
6.5%
3 28218
 
6.3%
5 28172
 
6.3%
Other values (9) 110000
24.7%

Interactions

2023-12-11T08:38:05.446957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:36:48.157858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:37:03.691292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:37:16.166212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:05.540239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:36:48.239780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:37:03.798534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:37:23.924029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:05.696006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:36:48.376069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:37:03.924392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:37:32.334714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:38:21.453194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:37:03.604095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:37:16.081597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:37:54.292554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:38:25.016572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간아이디일련번호라벨종단측점_일련번호
공간아이디1.0000.7890.0420.461
일련번호0.7891.0000.0000.789
라벨0.0420.0001.0000.000
종단측점_일련번호0.4610.7890.0001.000
2023-12-11T08:38:25.109337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간아이디일련번호라벨종단측점_일련번호
공간아이디1.0000.243-0.0890.184
일련번호0.2431.000-0.0600.781
라벨-0.089-0.0601.000-0.039
종단측점_일련번호0.1840.781-0.0391.000

Missing values

2023-12-11T08:38:21.574312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:38:21.701860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

공간아이디하천관리코드구분코드일련번호측점번호라벨종단측점_일련번호공간정보
5789223822920266602013F02Q0101E011450040+000060.0611POINT (1102384.96788096 1724013.3161328847)
2478220511920262602016F02Q0102E014400005+00007.616POINT (1087414.2366284681 1715343.8885639296)
190618224320260602011F01Q0101E016360001+035024.5535POINT (1076882.0000155717 1695605.8718460014)
5597623631320266102010F01Q0101E015750011+000079.2330POINT (1101861.1093126368 1728068.7336608355)
5189123222820265802017F02Q0101E012250000+0700-5.439POINT (1104496.605496301 1710383.5933185178)
6043824077520267002013F01Q0101E018290035+000081.8271POINT (1099331.4363463782 1719371.6698626275)
7107325141020268002012F02Q0101E0144660005+01001.9269POINT (1118622.3227817467 1702844.050816171)
947018980720261102010F02Q0101E0124000083+0000104.66122POINT (1087028.8151624382 1689640.8167679743)
3700421734120263702016F02Q0101E01520002+000018.956POINT (1090727.6030304905 1700769.3300336627)
1331719365420261502000F01Q0101E011020017+00008.4422POINT (1081064.0740713393 1697690.5260052911)
공간아이디하천관리코드구분코드일련번호측점번호라벨종단측점_일련번호공간정보
1389819423520261602014F02Q0101E011690008+000015.58414POINT (1081869.2805060102 1697386.6209480928)
5175423209120265802017F02Q0101E01880000+02009.933POINT (1104382.221353075 1709943.1413898773)
5602223635920266102010F01Q0101E016210012+000080.9633POINT (1101801.073883339 1727987.2371513108)
5082823116520265801995F02Q0101E0112880090+000033.35123POINT (1104684.2035116148 1725781.9067617452)
5294223327920265802017F02Q0101E0112760004+080014.3451POINT (1104347.1252269235 1714246.6661852584)
7977626011320268501986F01Q0101E01610000+02001.734POINT (1116896.5510747493 1702758.4823506773)
5444623478320265902010F01Q0101E0110480030+0050132.9071POINT (1099923.226030149 1730677.2205580275)
7855125888820268002012F02Q0101E01119440014+085014.24239POINT (1114083.5780801624 1695532.559028132)
4422422456120264502010F01Q0101E014980016+003222.2944POINT (1094664.4028553881 1708029.865761842)
4132722166420264302010F01Q0101E011990014+000020.7617POINT (1092836.1420541788 1705868.986191881)