Overview

Dataset statistics

Number of variables21
Number of observations64
Missing cells166
Missing cells (%)12.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.8 KiB
Average record size in memory172.1 B

Variable types

Numeric2
Text11
Categorical8

Dataset

Description전북특별자치도 김제시 하천현황(국가하천, 지방하천, 소하천)을 제공합니다.하천명, 본류, 기점 위치, 기점 경계, 기점 빈도, 기점 홍수위, 기점 하폭 등
Author전북특별자치도 김제시
URLhttps://www.data.go.kr/data/15103494/fileData.do

Alerts

제5지류 has constant value ""Constant
제2지류 has 10 (15.6%) missing valuesMissing
제3지류 has 36 (56.2%) missing valuesMissing
제4지류 has 57 (89.1%) missing valuesMissing
제5지류 has 63 (98.4%) missing valuesMissing

Reproduction

Analysis started2024-03-16 04:11:36.221396
Analysis finished2024-03-16 04:11:37.117459
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

Distinct50
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.046875
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2024-03-16T13:11:37.223245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q17
median18.5
Q334.25
95-th percentile46.85
Maximum50
Range49
Interquartile range (IQR)27.25

Descriptive statistics

Standard deviation15.479048
Coefficient of variation (CV)0.7354559
Kurtosis-1.2402291
Mean21.046875
Median Absolute Deviation (MAD)13
Skewness0.3544751
Sum1347
Variance239.60094
MonotonicityNot monotonic
2024-03-16T13:11:37.431250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3
 
4.7%
3 3
 
4.7%
2 3
 
4.7%
8 2
 
3.1%
11 2
 
3.1%
9 2
 
3.1%
10 2
 
3.1%
7 2
 
3.1%
6 2
 
3.1%
5 2
 
3.1%
Other values (40) 41
64.1%
ValueCountFrequency (%)
1 3
4.7%
2 3
4.7%
3 3
4.7%
4 2
3.1%
5 2
3.1%
6 2
3.1%
7 2
3.1%
8 2
3.1%
9 2
3.1%
10 2
3.1%
ValueCountFrequency (%)
50 1
1.6%
49 1
1.6%
48 1
1.6%
47 1
1.6%
46 1
1.6%
45 1
1.6%
44 1
1.6%
43 1
1.6%
42 1
1.6%
41 1
1.6%

하천명
Text

Distinct62
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-03-16T13:11:37.736376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.03125
Min length3

Characters and Unicode

Total characters194
Distinct characters75
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)93.8%

Sample

1st row만경강
2nd row동진강
3rd row원평천
4th row마산천
5th row목천포천
ValueCountFrequency (%)
원평천 2
 
3.1%
용복천 2
 
3.1%
유산천 1
 
1.6%
구성천 1
 
1.6%
만경강 1
 
1.6%
순동천 1
 
1.6%
어유천 1
 
1.6%
기룡천 1
 
1.6%
소용천 1
 
1.6%
율치천 1
 
1.6%
Other values (52) 52
81.2%
2024-03-16T13:11:38.400884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 65
33.5%
산 9
 
4.6%
용 5
 
2.6%
평 4
 
2.1%
복 4
 
2.1%
곡 4
 
2.1%
동 4
 
2.1%
목 4
 
2.1%
구 3
 
1.5%
교 3
 
1.5%
Other values (65) 89
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 193
99.5%
Decimal Number 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 65
33.7%
산 9
 
4.7%
용 5
 
2.6%
평 4
 
2.1%
복 4
 
2.1%
곡 4
 
2.1%
동 4
 
2.1%
목 4
 
2.1%
구 3
 
1.6%
교 3
 
1.6%
Other values (64) 88
45.6%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 193
99.5%
Common 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 65
33.7%
산 9
 
4.7%
용 5
 
2.6%
평 4
 
2.1%
복 4
 
2.1%
곡 4
 
2.1%
동 4
 
2.1%
목 4
 
2.1%
구 3
 
1.6%
교 3
 
1.6%
Other values (64) 88
45.6%
Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 193
99.5%
ASCII 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 65
33.7%
산 9
 
4.7%
용 5
 
2.6%
평 4
 
2.1%
복 4
 
2.1%
곡 4
 
2.1%
동 4
 
2.1%
목 4
 
2.1%
구 3
 
1.6%
교 3
 
1.6%
Other values (64) 88
45.6%
ASCII
ValueCountFrequency (%)
2 1
100.0%

본 류
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size644.0 B
동진강
46 
만경강
18 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row만경강
2nd row동진강
3rd row동진강
4th row만경강
5th row만경강

Common Values

ValueCountFrequency (%)
동진강 46
71.9%
만경강 18
 
28.1%

Length

2024-03-16T13:11:38.577802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:11:38.686860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동진강 46
71.9%
만경강 18
 
28.1%

제1지류
Categorical

Distinct10
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size644.0 B
원평천
44 
용암천
6 
<NA>
 
3
마산천
 
3
신평천
 
3
Other values (5)
5 

Length

Max length4
Median length3
Mean length3.078125
Min length3

Unique

Unique5 ?
Unique (%)7.8%

Sample

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

Common Values

ValueCountFrequency (%)
원평천 44
68.8%
용암천 6
 
9.4%
<NA> 3
 
4.7%
마산천 3
 
4.7%
신평천 3
 
4.7%
목천포천 1
 
1.6%
화호천 1
 
1.6%
원평천 1
 
1.6%
소동천 1
 
1.6%
만경강 1
 
1.6%

Length

2024-03-16T13:11:38.808499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:11:38.934861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원평천 45
70.3%
용암천 6
 
9.4%
na 3
 
4.7%
마산천 3
 
4.7%
신평천 3
 
4.7%
목천포천 1
 
1.6%
화호천 1
 
1.6%
소동천 1
 
1.6%
만경강 1
 
1.6%

제2지류
Text

MISSING 

Distinct27
Distinct (%)50.0%
Missing10
Missing (%)15.6%
Memory size644.0 B
2024-03-16T13:11:39.091126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0185185
Min length3

Characters and Unicode

Total characters163
Distinct characters44
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)38.9%

Sample

1st row주평천
2nd row유각천
3rd row유각천
4th row금구천
5th row두월천
ValueCountFrequency (%)
두월천 15
27.8%
유각천 7
13.0%
반곡천 3
 
5.6%
금구천 3
 
5.6%
주평천 3
 
5.6%
아직천 2
 
3.7%
석교천 1
 
1.9%
구산천 1
 
1.9%
존걸천 1
 
1.9%
사정천 1
 
1.9%
Other values (17) 17
31.5%
2024-03-16T13:11:39.346686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 54
33.1%
두 15
 
9.2%
월 15
 
9.2%
유 8
 
4.9%
각 7
 
4.3%
곡 4
 
2.5%
금 4
 
2.5%
구 4
 
2.5%
교 3
 
1.8%
용 3
 
1.8%
Other values (34) 46
28.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162
99.4%
Decimal Number 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 54
33.3%
두 15
 
9.3%
월 15
 
9.3%
유 8
 
4.9%
각 7
 
4.3%
곡 4
 
2.5%
금 4
 
2.5%
구 4
 
2.5%
교 3
 
1.9%
용 3
 
1.9%
Other values (33) 45
27.8%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162
99.4%
Common 1
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 54
33.3%
두 15
 
9.3%
월 15
 
9.3%
유 8
 
4.9%
각 7
 
4.3%
곡 4
 
2.5%
금 4
 
2.5%
구 4
 
2.5%
교 3
 
1.9%
용 3
 
1.9%
Other values (33) 45
27.8%
Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162
99.4%
ASCII 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 54
33.3%
두 15
 
9.3%
월 15
 
9.3%
유 8
 
4.9%
각 7
 
4.3%
곡 4
 
2.5%
금 4
 
2.5%
구 4
 
2.5%
교 3
 
1.9%
용 3
 
1.9%
Other values (33) 45
27.8%
ASCII
ValueCountFrequency (%)
2 1
100.0%

제3지류
Text

MISSING 

Distinct22
Distinct (%)78.6%
Missing36
Missing (%)56.2%
Memory size644.0 B
2024-03-16T13:11:39.499222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters84
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)60.7%

Sample

1st row금산천
2nd row용복천
3rd row봉림천
4th row대야천
5th row어전천
ValueCountFrequency (%)
봉림천 3
 
10.7%
의곡천 2
 
7.1%
순동천 2
 
7.1%
금산천 2
 
7.1%
당월천 2
 
7.1%
안양천 1
 
3.6%
유산천 1
 
3.6%
은곡천 1
 
3.6%
뒷골천 1
 
3.6%
진천천 1
 
3.6%
Other values (12) 12
42.9%
2024-03-16T13:11:39.768448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 30
35.7%
봉 4
 
4.8%
곡 4
 
4.8%
산 4
 
4.8%
의 3
 
3.6%
림 3
 
3.6%
당 2
 
2.4%
월 2
 
2.4%
순 2
 
2.4%
동 2
 
2.4%
Other values (27) 28
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 30
35.7%
봉 4
 
4.8%
곡 4
 
4.8%
산 4
 
4.8%
의 3
 
3.6%
림 3
 
3.6%
당 2
 
2.4%
월 2
 
2.4%
순 2
 
2.4%
동 2
 
2.4%
Other values (27) 28
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 30
35.7%
봉 4
 
4.8%
곡 4
 
4.8%
산 4
 
4.8%
의 3
 
3.6%
림 3
 
3.6%
당 2
 
2.4%
월 2
 
2.4%
순 2
 
2.4%
동 2
 
2.4%
Other values (27) 28
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 30
35.7%
봉 4
 
4.8%
곡 4
 
4.8%
산 4
 
4.8%
의 3
 
3.6%
림 3
 
3.6%
당 2
 
2.4%
월 2
 
2.4%
순 2
 
2.4%
동 2
 
2.4%
Other values (27) 28
33.3%

제4지류
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing57
Missing (%)89.1%
Memory size644.0 B
2024-03-16T13:11:39.963255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters21
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st row양석천
2nd row봉산천
3rd row지장천
4th row매산천
5th row청도천
ValueCountFrequency (%)
양석천 1
14.3%
봉산천 1
14.3%
지장천 1
14.3%
매산천 1
14.3%
청도천 1
14.3%
기룡천 1
14.3%
검산천 1
14.3%
2024-03-16T13:11:40.263354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 7
33.3%
산 3
14.3%
양 1
 
4.8%
석 1
 
4.8%
봉 1
 
4.8%
지 1
 
4.8%
장 1
 
4.8%
매 1
 
4.8%
청 1
 
4.8%
도 1
 
4.8%
Other values (3) 3
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 7
33.3%
산 3
14.3%
양 1
 
4.8%
석 1
 
4.8%
봉 1
 
4.8%
지 1
 
4.8%
장 1
 
4.8%
매 1
 
4.8%
청 1
 
4.8%
도 1
 
4.8%
Other values (3) 3
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 7
33.3%
산 3
14.3%
양 1
 
4.8%
석 1
 
4.8%
봉 1
 
4.8%
지 1
 
4.8%
장 1
 
4.8%
매 1
 
4.8%
청 1
 
4.8%
도 1
 
4.8%
Other values (3) 3
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 7
33.3%
산 3
14.3%
양 1
 
4.8%
석 1
 
4.8%
봉 1
 
4.8%
지 1
 
4.8%
장 1
 
4.8%
매 1
 
4.8%
청 1
 
4.8%
도 1
 
4.8%
Other values (3) 3
14.3%

제5지류
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing63
Missing (%)98.4%
Memory size644.0 B
2024-03-16T13:11:40.390406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row율리천
ValueCountFrequency (%)
율리천 1
100.0%
2024-03-16T13:11:40.626755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
율 1
33.3%
리 1
33.3%
천 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
율 1
33.3%
리 1
33.3%
천 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
율 1
33.3%
리 1
33.3%
천 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
율 1
33.3%
리 1
33.3%
천 1
33.3%

구분
Categorical

Distinct3
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size644.0 B
소하천
50 
지방하천
11 
국가하천
 
3

Length

Max length4
Median length3
Mean length3.21875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소하천 50
78.1%
지방하천 11
 
17.2%
국가하천 3
 
4.7%

Length

2024-03-16T13:11:40.747071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:11:40.834739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소하천 50
78.1%
지방하천 11
 
17.2%
국가하천 3
 
4.7%

기점
Text

Distinct46
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-03-16T13:11:41.007526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length7
Mean length8
Min length2

Characters and Unicode

Total characters512
Distinct characters83
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)53.1%

Sample

1st row고산천(지방)합류점
2nd row태인면 신태인읍의 경계
3rd row금구천(지방)합류점
4th row은교리 123-2번지선
5th row석암동 634-2번지선
ValueCountFrequency (%)
금산면 22
 
17.2%
금구면 10
 
7.8%
용지면 6
 
4.7%
오봉리 5
 
3.9%
화율리 4
 
3.1%
청도리 4
 
3.1%
황산면 4
 
3.1%
장흥리 3
 
2.3%
월전리 3
 
2.3%
용산리 3
 
2.3%
Other values (55) 64
50.0%
2024-03-16T13:11:41.294377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
 
12.5%
리 56
 
10.9%
면 47
 
9.2%
산 38
 
7.4%
금 37
 
7.2%
지 19
 
3.7%
선 16
 
3.1%
구 13
 
2.5%
용 12
 
2.3%
번 11
 
2.1%
Other values (73) 199
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 397
77.5%
Space Separator 64
 
12.5%
Decimal Number 39
 
7.6%
Dash Punctuation 8
 
1.6%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 56
14.1%
면 47
 
11.8%
산 38
 
9.6%
금 37
 
9.3%
지 19
 
4.8%
선 16
 
4.0%
구 13
 
3.3%
용 12
 
3.0%
번 11
 
2.8%
봉 9
 
2.3%
Other values (60) 139
35.0%
Decimal Number
ValueCountFrequency (%)
1 8
20.5%
2 8
20.5%
7 5
12.8%
5 4
10.3%
3 4
10.3%
4 4
10.3%
6 3
 
7.7%
9 2
 
5.1%
0 1
 
2.6%
Space Separator
ValueCountFrequency (%)
64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 397
77.5%
Common 115
 
22.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 56
14.1%
면 47
 
11.8%
산 38
 
9.6%
금 37
 
9.3%
지 19
 
4.8%
선 16
 
4.0%
구 13
 
3.3%
용 12
 
3.0%
번 11
 
2.8%
봉 9
 
2.3%
Other values (60) 139
35.0%
Common
ValueCountFrequency (%)
64
55.7%
1 8
 
7.0%
- 8
 
7.0%
2 8
 
7.0%
7 5
 
4.3%
5 4
 
3.5%
3 4
 
3.5%
4 4
 
3.5%
6 3
 
2.6%
) 2
 
1.7%
Other values (3) 5
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 397
77.5%
ASCII 115
 
22.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
55.7%
1 8
 
7.0%
- 8
 
7.0%
2 8
 
7.0%
7 5
 
4.3%
5 4
 
3.5%
3 4
 
3.5%
4 4
 
3.5%
6 3
 
2.6%
) 2
 
1.7%
Other values (3) 5
 
4.3%
Hangul
ValueCountFrequency (%)
리 56
14.1%
면 47
 
11.8%
산 38
 
9.6%
금 37
 
9.3%
지 19
 
4.8%
선 16
 
4.0%
구 13
 
3.3%
용 12
 
3.0%
번 11
 
2.8%
봉 9
 
2.3%
Other values (60) 139
35.0%

기점 빈도
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size644.0 B
50년
50 
데이터미집계
14 

Length

Max length6
Median length3
Mean length3.65625
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
50년 50
78.1%
데이터미집계 14
 
21.9%

Length

2024-03-16T13:11:41.401949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:11:41.486490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50년 50
78.1%
데이터미집계 14
 
21.9%

기점 홍수량
Text

Distinct38
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-03-16T13:11:41.615362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length3.046875
Min length1

Characters and Unicode

Total characters195
Distinct characters17
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

Unique27 ?
Unique (%)42.2%

Sample

1st row데이터미집계
2nd row데이터미집계
3rd row데이터미집계
4th row데이터미집계
5th row데이터미집계
ValueCountFrequency (%)
데이터미집계 14
21.9%
14 4
 
6.2%
9 3
 
4.7%
34 2
 
3.1%
53 2
 
3.1%
13.6 2
 
3.1%
51 2
 
3.1%
12 2
 
3.1%
44 2
 
3.1%
36 2
 
3.1%
Other values (28) 29
45.3%
2024-03-16T13:11:41.861468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
11.3%
3 16
 
8.2%
데 14
 
7.2%
터 14
 
7.2%
미 14
 
7.2%
집 14
 
7.2%
계 14
 
7.2%
4 14
 
7.2%
이 14
 
7.2%
2 10
 
5.1%
Other values (7) 49
25.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103
52.8%
Other Letter 84
43.1%
Other Punctuation 8
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
21.4%
3 16
15.5%
4 14
13.6%
2 10
9.7%
5 9
8.7%
6 8
 
7.8%
7 7
 
6.8%
9 7
 
6.8%
0 6
 
5.8%
8 4
 
3.9%
Other Letter
ValueCountFrequency (%)
데 14
16.7%
터 14
16.7%
미 14
16.7%
집 14
16.7%
계 14
16.7%
이 14
16.7%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 111
56.9%
Hangul 84
43.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
19.8%
3 16
14.4%
4 14
12.6%
2 10
9.0%
5 9
8.1%
. 8
 
7.2%
6 8
 
7.2%
7 7
 
6.3%
9 7
 
6.3%
0 6
 
5.4%
Hangul
ValueCountFrequency (%)
데 14
16.7%
터 14
16.7%
미 14
16.7%
집 14
16.7%
계 14
16.7%
이 14
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 111
56.9%
Hangul 84
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
19.8%
3 16
14.4%
4 14
12.6%
2 10
9.0%
5 9
8.1%
. 8
 
7.2%
6 8
 
7.2%
7 7
 
6.3%
9 7
 
6.3%
0 6
 
5.4%
Hangul
ValueCountFrequency (%)
데 14
16.7%
터 14
16.7%
미 14
16.7%
집 14
16.7%
계 14
16.7%
이 14
16.7%

기점 홍수위
Text

Distinct49
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-03-16T13:11:42.023035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.328125
Min length4

Characters and Unicode

Total characters341
Distinct characters17
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

Unique46 ?
Unique (%)71.9%

Sample

1st row데이터미집계
2nd row데이터미집계
3rd row데이터미집계
4th row데이터미집계
5th row데이터미집계
ValueCountFrequency (%)
데이터미집계 14
 
21.9%
23.47 2
 
3.1%
16.09 2
 
3.1%
17.96 1
 
1.6%
143.18 1
 
1.6%
11.67 1
 
1.6%
10.82 1
 
1.6%
89.74 1
 
1.6%
82.56 1
 
1.6%
146.06 1
 
1.6%
Other values (39) 39
60.9%
2024-03-16T13:11:42.350874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 50
14.7%
1 38
 
11.1%
7 27
 
7.9%
0 22
 
6.5%
2 21
 
6.2%
6 20
 
5.9%
5 19
 
5.6%
3 18
 
5.3%
8 15
 
4.4%
이 14
 
4.1%
Other values (7) 97
28.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 207
60.7%
Other Letter 84
24.6%
Other Punctuation 50
 
14.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 38
18.4%
7 27
13.0%
0 22
10.6%
2 21
10.1%
6 20
9.7%
5 19
9.2%
3 18
8.7%
8 15
 
7.2%
4 14
 
6.8%
9 13
 
6.3%
Other Letter
ValueCountFrequency (%)
이 14
16.7%
계 14
16.7%
집 14
16.7%
미 14
16.7%
터 14
16.7%
데 14
16.7%
Other Punctuation
ValueCountFrequency (%)
. 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 257
75.4%
Hangul 84
 
24.6%

Most frequent character per script

Common
ValueCountFrequency (%)
. 50
19.5%
1 38
14.8%
7 27
10.5%
0 22
8.6%
2 21
8.2%
6 20
 
7.8%
5 19
 
7.4%
3 18
 
7.0%
8 15
 
5.8%
4 14
 
5.4%
Hangul
ValueCountFrequency (%)
이 14
16.7%
계 14
16.7%
집 14
16.7%
미 14
16.7%
터 14
16.7%
데 14
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 257
75.4%
Hangul 84
 
24.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 50
19.5%
1 38
14.8%
7 27
10.5%
0 22
8.6%
2 21
8.2%
6 20
 
7.8%
5 19
 
7.4%
3 18
 
7.0%
8 15
 
5.8%
4 14
 
5.4%
Hangul
ValueCountFrequency (%)
이 14
16.7%
계 14
16.7%
집 14
16.7%
미 14
16.7%
터 14
16.7%
데 14
16.7%

기점 하폭
Categorical

Distinct14
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size644.0 B
7
18 
데이터미집계
14 
6
9 
3
4 
10
4 
Other values (9)
15 

Length

Max length6
Median length1
Mean length2.25
Min length1

Unique

Unique6 ?
Unique (%)9.4%

Sample

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

Common Values

ValueCountFrequency (%)
7 18
28.1%
데이터미집계 14
21.9%
6 9
14.1%
3 4
 
6.2%
10 4
 
6.2%
8 4
 
6.2%
5 3
 
4.7%
4 2
 
3.1%
15 1
 
1.6%
16 1
 
1.6%
Other values (4) 4
 
6.2%

Length

2024-03-16T13:11:42.479806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
7 18
28.1%
데이터미집계 14
21.9%
6 9
14.1%
3 4
 
6.2%
10 4
 
6.2%
8 4
 
6.2%
5 3
 
4.7%
4 2
 
3.1%
15 1
 
1.6%
16 1
 
1.6%
Other values (4) 4
 
6.2%

종점 위치
Text

Distinct49
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-03-16T13:11:42.784352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length7
Mean length9.875
Min length3

Characters and Unicode

Total characters632
Distinct characters99
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)57.8%

Sample

1st row국사봉 산정에서 북12도 서그은선
2nd row안성리삼각점(25m)에서 북50도동그은선
3rd row동진강(국가)합류점
4th row마산리 5-5번지선
5th row익산시 목천동1431-7번지선(만경강 합류점)
ValueCountFrequency (%)
금산면 20
 
14.1%
금구면 9
 
6.3%
용지면 6
 
4.2%
합류점 5
 
3.5%
황산면 4
 
2.8%
용산리 3
 
2.1%
오봉리 3
 
2.1%
금성리 3
 
2.1%
봉남면 3
 
2.1%
장흥리 3
 
2.1%
Other values (69) 83
58.5%
2024-03-16T13:11:43.227474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
78
 
12.3%
리 56
 
8.9%
면 47
 
7.4%
산 39
 
6.2%
금 36
 
5.7%
지 19
 
3.0%
동 17
 
2.7%
선 14
 
2.2%
용 13
 
2.1%
5 11
 
1.7%
Other values (89) 302
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 473
74.8%
Space Separator 78
 
12.3%
Decimal Number 51
 
8.1%
Close Punctuation 10
 
1.6%
Open Punctuation 10
 
1.6%
Dash Punctuation 9
 
1.4%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 56
 
11.8%
면 47
 
9.9%
산 39
 
8.2%
금 36
 
7.6%
지 19
 
4.0%
동 17
 
3.6%
선 14
 
3.0%
용 13
 
2.7%
구 10
 
2.1%
봉 10
 
2.1%
Other values (74) 212
44.8%
Decimal Number
ValueCountFrequency (%)
5 11
21.6%
1 9
17.6%
3 8
15.7%
2 4
 
7.8%
7 4
 
7.8%
9 4
 
7.8%
4 4
 
7.8%
6 3
 
5.9%
0 3
 
5.9%
8 1
 
2.0%
Space Separator
ValueCountFrequency (%)
78
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 473
74.8%
Common 158
 
25.0%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 56
 
11.8%
면 47
 
9.9%
산 39
 
8.2%
금 36
 
7.6%
지 19
 
4.0%
동 17
 
3.6%
선 14
 
3.0%
용 13
 
2.7%
구 10
 
2.1%
봉 10
 
2.1%
Other values (74) 212
44.8%
Common
ValueCountFrequency (%)
78
49.4%
5 11
 
7.0%
) 10
 
6.3%
( 10
 
6.3%
1 9
 
5.7%
- 9
 
5.7%
3 8
 
5.1%
2 4
 
2.5%
7 4
 
2.5%
9 4
 
2.5%
Other values (4) 11
 
7.0%
Latin
ValueCountFrequency (%)
m 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 473
74.8%
ASCII 159
 
25.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
49.1%
5 11
 
6.9%
) 10
 
6.3%
( 10
 
6.3%
1 9
 
5.7%
- 9
 
5.7%
3 8
 
5.0%
2 4
 
2.5%
7 4
 
2.5%
9 4
 
2.5%
Other values (5) 12
 
7.5%
Hangul
ValueCountFrequency (%)
리 56
 
11.8%
면 47
 
9.9%
산 39
 
8.2%
금 36
 
7.6%
지 19
 
4.0%
동 17
 
3.6%
선 14
 
3.0%
용 13
 
2.7%
구 10
 
2.1%
봉 10
 
2.1%
Other values (74) 212
44.8%

종점 빈도
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size644.0 B
50년
50 
데이터미집계
14 

Length

Max length6
Median length3
Mean length3.65625
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
50년 50
78.1%
데이터미집계 14
 
21.9%

Length

2024-03-16T13:11:43.418732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:11:43.542205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50년 50
78.1%
데이터미집계 14
 
21.9%

종점 홍수량
Text

Distinct38
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-03-16T13:11:43.742841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length3.140625
Min length1

Characters and Unicode

Total characters201
Distinct characters17
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

Unique28 ?
Unique (%)43.8%

Sample

1st row데이터미집계
2nd row데이터미집계
3rd row데이터미집계
4th row데이터미집계
5th row데이터미집계
ValueCountFrequency (%)
데이터미집계 14
21.9%
14 4
 
6.2%
21 3
 
4.7%
9 3
 
4.7%
78 2
 
3.1%
69.9 2
 
3.1%
39 2
 
3.1%
51 2
 
3.1%
42 2
 
3.1%
36 2
 
3.1%
Other values (28) 28
43.8%
2024-03-16T13:11:44.076866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
10.9%
3 16
 
8.0%
9 15
 
7.5%
데 14
 
7.0%
터 14
 
7.0%
미 14
 
7.0%
집 14
 
7.0%
계 14
 
7.0%
이 14
 
7.0%
4 11
 
5.5%
Other values (7) 53
26.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108
53.7%
Other Letter 84
41.8%
Other Punctuation 9
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
20.4%
3 16
14.8%
9 15
13.9%
4 11
10.2%
7 9
8.3%
5 8
 
7.4%
2 8
 
7.4%
6 8
 
7.4%
0 6
 
5.6%
8 5
 
4.6%
Other Letter
ValueCountFrequency (%)
데 14
16.7%
터 14
16.7%
미 14
16.7%
집 14
16.7%
계 14
16.7%
이 14
16.7%
Other Punctuation
ValueCountFrequency (%)
. 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 117
58.2%
Hangul 84
41.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
18.8%
3 16
13.7%
9 15
12.8%
4 11
9.4%
. 9
7.7%
7 9
7.7%
5 8
 
6.8%
2 8
 
6.8%
6 8
 
6.8%
0 6
 
5.1%
Hangul
ValueCountFrequency (%)
데 14
16.7%
터 14
16.7%
미 14
16.7%
집 14
16.7%
계 14
16.7%
이 14
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117
58.2%
Hangul 84
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
18.8%
3 16
13.7%
9 15
12.8%
4 11
9.4%
. 9
7.7%
7 9
7.7%
5 8
 
6.8%
2 8
 
6.8%
6 8
 
6.8%
0 6
 
5.1%
Hangul
ValueCountFrequency (%)
데 14
16.7%
터 14
16.7%
미 14
16.7%
집 14
16.7%
계 14
16.7%
이 14
16.7%

종점 홍수위
Text

Distinct49
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-03-16T13:11:44.310529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.640625
Min length2

Characters and Unicode

Total characters297
Distinct characters17
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

Unique46 ?
Unique (%)71.9%

Sample

1st row데이터미집계
2nd row데이터미집계
3rd row데이터미집계
4th row데이터미집계
5th row데이터미집계
ValueCountFrequency (%)
데이터미집계 14
 
21.9%
12.82 2
 
3.1%
10 2
 
3.1%
8.76 1
 
1.6%
129.48 1
 
1.6%
5.76 1
 
1.6%
5.81 1
 
1.6%
55.07 1
 
1.6%
48 1
 
1.6%
91.22 1
 
1.6%
Other values (39) 39
60.9%
2024-03-16T13:11:44.823869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 46
15.5%
1 22
 
7.4%
6 20
 
6.7%
3 20
 
6.7%
2 18
 
6.1%
7 18
 
6.1%
8 17
 
5.7%
5 17
 
5.7%
4 16
 
5.4%
계 14
 
4.7%
Other values (7) 89
30.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 167
56.2%
Other Letter 84
28.3%
Other Punctuation 46
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
13.2%
6 20
12.0%
3 20
12.0%
2 18
10.8%
7 18
10.8%
8 17
10.2%
5 17
10.2%
4 16
9.6%
0 12
7.2%
9 7
 
4.2%
Other Letter
ValueCountFrequency (%)
계 14
16.7%
이 14
16.7%
집 14
16.7%
미 14
16.7%
터 14
16.7%
데 14
16.7%
Other Punctuation
ValueCountFrequency (%)
. 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 213
71.7%
Hangul 84
 
28.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 46
21.6%
1 22
10.3%
6 20
9.4%
3 20
9.4%
2 18
 
8.5%
7 18
 
8.5%
8 17
 
8.0%
5 17
 
8.0%
4 16
 
7.5%
0 12
 
5.6%
Hangul
ValueCountFrequency (%)
계 14
16.7%
이 14
16.7%
집 14
16.7%
미 14
16.7%
터 14
16.7%
데 14
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 213
71.7%
Hangul 84
 
28.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 46
21.6%
1 22
10.3%
6 20
9.4%
3 20
9.4%
2 18
 
8.5%
7 18
 
8.5%
8 17
 
8.0%
5 17
 
8.0%
4 16
 
7.5%
0 12
 
5.6%
Hangul
ValueCountFrequency (%)
계 14
16.7%
이 14
16.7%
집 14
16.7%
미 14
16.7%
터 14
16.7%
데 14
16.7%

종점 하폭
Categorical

Distinct21
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Memory size644.0 B
데이터미집계
14 
10
7 
7
6 
8
5 
6
5 
Other values (16)
27 

Length

Max length6
Median length4
Mean length2.5625
Min length1

Unique

Unique9 ?
Unique (%)14.1%

Sample

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

Common Values

ValueCountFrequency (%)
데이터미집계 14
21.9%
10 7
10.9%
7 6
9.4%
8 5
 
7.8%
6 5
 
7.8%
20 4
 
6.2%
12 3
 
4.7%
18 3
 
4.7%
11 2
 
3.1%
13 2
 
3.1%
Other values (11) 13
20.3%

Length

2024-03-16T13:11:45.038447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
데이터미집계 14
21.9%
10 7
10.9%
7 6
9.4%
8 5
 
7.8%
6 5
 
7.8%
20 4
 
6.2%
12 3
 
4.7%
18 3
 
4.7%
9 2
 
3.1%
5 2
 
3.1%
Other values (11) 13
20.3%

관리주체
Categorical

Distinct3
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size644.0 B
김제시청
50 
전북특별자치도
11 
전북지방환경청
 
3

Length

Max length7
Median length4
Mean length4.65625
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북지방환경청
2nd row전북지방환경청
3rd row전북지방환경청
4th row전북특별자치도
5th row전북특별자치도

Common Values

ValueCountFrequency (%)
김제시청 50
78.1%
전북특별자치도 11
 
17.2%
전북지방환경청 3
 
4.7%

Length

2024-03-16T13:11:45.216799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:11:45.380607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김제시청 50
78.1%
전북특별자치도 11
 
17.2%
전북지방환경청 3
 
4.7%

연장(m)
Real number (ℝ)

Distinct62
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4556.625
Minimum410
Maximum54150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2024-03-16T13:11:45.560008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum410
5-th percentile540.5
Q1962.5
median1757
Q33718
95-th percentile16812
Maximum54150
Range53740
Interquartile range (IQR)2755.5

Descriptive statistics

Standard deviation8043.6345
Coefficient of variation (CV)1.7652615
Kurtosis23.026858
Mean4556.625
Median Absolute Deviation (MAD)971
Skewness4.2645036
Sum291624
Variance64700056
MonotonicityNot monotonic
2024-03-16T13:11:45.769948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
630 2
 
3.1%
530 2
 
3.1%
54150 1
 
1.6%
2300 1
 
1.6%
1510 1
 
1.6%
2390 1
 
1.6%
2730 1
 
1.6%
1630 1
 
1.6%
940 1
 
1.6%
1140 1
 
1.6%
Other values (52) 52
81.2%
ValueCountFrequency (%)
410 1
1.6%
522 1
1.6%
530 2
3.1%
600 1
1.6%
625 1
1.6%
630 2
3.1%
650 1
1.6%
660 1
1.6%
680 1
1.6%
788 1
1.6%
ValueCountFrequency (%)
54150 1
1.6%
23000 1
1.6%
19200 1
1.6%
16920 1
1.6%
16200 1
1.6%
14190 1
1.6%
11900 1
1.6%
11220 1
1.6%
11070 1
1.6%
11020 1
1.6%

Sample

연번하천명본 류제1지류제2지류제3지류제4지류제5지류구분기점기점 빈도기점 홍수량기점 홍수위기점 하폭종점 위치종점 빈도종점 홍수량종점 홍수위종점 하폭관리주체연장(m)
01만경강만경강<NA><NA><NA><NA><NA>국가하천고산천(지방)합류점데이터미집계데이터미집계데이터미집계데이터미집계국사봉 산정에서 북12도 서그은선데이터미집계데이터미집계데이터미집계데이터미집계전북지방환경청54150
12동진강동진강<NA><NA><NA><NA><NA>국가하천태인면 신태인읍의 경계데이터미집계데이터미집계데이터미집계데이터미집계안성리삼각점(25m)에서 북50도동그은선데이터미집계데이터미집계데이터미집계데이터미집계전북지방환경청19200
23원평천동진강<NA><NA><NA><NA><NA>국가하천금구천(지방)합류점데이터미집계데이터미집계데이터미집계데이터미집계동진강(국가)합류점데이터미집계데이터미집계데이터미집계데이터미집계전북지방환경청16200
31마산천만경강마산천<NA><NA><NA><NA>지방하천은교리 123-2번지선데이터미집계데이터미집계데이터미집계데이터미집계마산리 5-5번지선데이터미집계데이터미집계데이터미집계데이터미집계전북특별자치도11020
42목천포천만경강목천포천<NA><NA><NA><NA>지방하천석암동 634-2번지선데이터미집계데이터미집계데이터미집계데이터미집계익산시 목천동1431-7번지선(만경강 합류점)데이터미집계데이터미집계데이터미집계데이터미집계전북특별자치도16920
53용암천만경강용암천<NA><NA><NA><NA>지방하천부교리 150-2번지선데이터미집계데이터미집계데이터미집계데이터미집계동계리 1056-34번지선데이터미집계데이터미집계데이터미집계데이터미집계전북특별자치도14190
64화호천동진강화호천<NA><NA><NA><NA>지방하천전라북도 정읍시 신태인읍 양괴리 2561번지선데이터미집계데이터미집계데이터미집계데이터미집계전라북도 김제시 부량면 옥정리 1093번지선 동진강(국가하천) 합류점데이터미집계데이터미집계데이터미집계데이터미집계전북특별자치도4760
75원평천동진강원평천<NA><NA><NA><NA>지방하천화율리 27-1번지선데이터미집계데이터미집계데이터미집계데이터미집계종덕리 277-5번지선 원평천(국가) 합류점데이터미집계데이터미집계데이터미집계데이터미집계전북특별자치도11220
86주평천동진강원평천주평천<NA><NA><NA>지방하천장흥리 17-1번지선데이터미집계데이터미집계데이터미집계데이터미집계장흥리 339-1번지 원평천(지방) 합류점데이터미집계데이터미집계데이터미집계데이터미집계전북특별자치도3080
97유각천동진강원평천유각천<NA><NA><NA>지방하천청도리 59번지선데이터미집계데이터미집계데이터미집계데이터미집계성계리 331-165번지선 원평천(지방)합류점데이터미집계데이터미집계데이터미집계데이터미집계전북특별자치도9060
연번하천명본 류제1지류제2지류제3지류제4지류제5지류구분기점기점 빈도기점 홍수량기점 홍수위기점 하폭종점 위치종점 빈도종점 홍수량종점 홍수위종점 하폭관리주체연장(m)
5441마교천만경강용암천마교천<NA><NA><NA>소하천용지면 신정리50년53.720.133용지면 예촌리50년53.77.3518김제시청3772
5542영등천만경강마산천영등천<NA><NA><NA>소하천용지면 용수리50년13.616.097용지면 장신리50년69.91020김제시청1764
5643상목천동진강원평천두월천상목천<NA><NA>소하천황산면 진흥리50년13.616.097황산면 용마리50년69.91020김제시청1493
5744진천천동진강원평천두월천진천천<NA><NA>소하천황산면 진흥리50년1223.477황산면 진흥리50년13.912.8214김제시청1355
5845석교천만경강신평천석교천<NA><NA><NA>소하천백산면 석교리50년13.123.477백산면 석교리50년35.612.8213김제시청1728
5946뒷골천동진강원평천주평천뒷골천<NA><NA>소하천금산면 장흥리50년7.374.235금산면 장흥리50년9.750.366김제시청530
6047은곡천동진강원평천주평천은곡천<NA><NA>소하천금산면 장흥리50년27.890.355금산면 장흥리50년27.867.055김제시청650
6148구성천동진강원평천유각천구성천<NA><NA>소하천금산면 청도리50년14143.187금산면 청도리50년14129.487김제시청410
6249남조천만경강만경강남조천<NA><NA><NA>소하천백산면 조종리50년3817.967백산면 수록리50년428.7612김제시청1500
6350용복2천동진강원평천용복2천<NA><NA><NA>소하천금산면 금성리50년20114.717금산면 금성리50년2170.269김제시청630