Overview

Dataset statistics

Number of variables12
Number of observations3083
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory310.2 KiB
Average record size in memory103.0 B

Variable types

Categorical6
Numeric5
Text1

Dataset

Description한강홍수통제소에서 유지, 관리중인 수문모형 시설물의 하도유역 정보입니다. 예보유역 명, 하도 코드/명칭, 하도 폭, 수면 구배, 조도 계수 등 데이터를 제공합니다.
Author환경부 한강홍수통제소
URLhttps://www.data.go.kr/data/15086317/fileData.do

Alerts

관측소유형 has constant value ""Constant
조도계수 has constant value ""Constant
1시간최대허용변동량 has constant value ""Constant
하도코드 is highly overall correlated with 예보유역명High correlation
하도폭 is highly overall correlated with 수면구배High correlation
수면구배 is highly overall correlated with 하도폭High correlation
예보유역명 is highly overall correlated with 하도코드 and 1 other fieldsHigh correlation
적용시작일 is highly overall correlated with 예보유역명 and 1 other fieldsHigh correlation
적용종료일 is highly overall correlated with 적용시작일High correlation
하도연장 has 50 (1.6%) zerosZeros
하도폭 has 1678 (54.4%) zerosZeros
수면구배 has 34 (1.1%) zerosZeros

Reproduction

Analysis started2023-12-12 03:06:55.025010
Analysis finished2023-12-12 03:06:59.496293
Duration4.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

예보유역명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size24.2 KiB
낙동강
1165 
한강
870 
금강
347 
영산강
216 
섬진강
156 
Other values (9)
329 

Length

Max length7
Median length3
Mean length2.763542
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
낙동강 1165
37.8%
한강 870
28.2%
금강 347
 
11.3%
영산강 216
 
7.0%
섬진강 156
 
5.1%
만경 · 동진 93
 
3.0%
삽교천 59
 
1.9%
낙동강동해 37
 
1.2%
한강동해 33
 
1.1%
태화강 29
 
0.9%
Other values (4) 78
 
2.5%

Length

2023-12-12T12:06:59.613289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
낙동강 1165
35.6%
한강 870
26.6%
금강 347
 
10.6%
영산강 216
 
6.6%
섬진강 156
 
4.8%
만경 93
 
2.8%
· 93
 
2.8%
동진 93
 
2.8%
삽교천 59
 
1.8%
낙동강동해 37
 
1.1%
Other values (6) 140
 
4.3%

하도코드
Real number (ℝ)

HIGH CORRELATION 

Distinct1189
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2225957.2
Minimum1001010
Maximum5101090
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.2 KiB
2023-12-12T12:06:59.793182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001010
5-th percentile1003070
Q11022012.5
median2012150
Q33008070
95-th percentile5002120
Maximum5101090
Range4100080
Interquartile range (IQR)1986057.5

Descriptive statistics

Standard deviation1150639.3
Coefficient of variation (CV)0.51691889
Kurtosis0.31813534
Mean2225957.2
Median Absolute Deviation (MAD)993110
Skewness0.98753028
Sum6.862626 × 109
Variance1.3239708 × 1012
MonotonicityIncreasing
2023-12-12T12:07:00.006673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2016050 4
 
0.1%
2010060 4
 
0.1%
2009020 4
 
0.1%
2009030 4
 
0.1%
2009040 4
 
0.1%
2010010 4
 
0.1%
2010020 4
 
0.1%
2010030 4
 
0.1%
2010040 4
 
0.1%
2010050 4
 
0.1%
Other values (1179) 3043
98.7%
ValueCountFrequency (%)
1001010 3
0.1%
1001020 3
0.1%
1001030 3
0.1%
1001040 3
0.1%
1001050 3
0.1%
1001060 3
0.1%
1001070 3
0.1%
1001075 1
 
< 0.1%
1001078 1
 
< 0.1%
1001080 3
0.1%
ValueCountFrequency (%)
5101090 2
0.1%
5101080 2
0.1%
5101070 2
0.1%
5101060 2
0.1%
5101050 2
0.1%
5101040 2
0.1%
5101030 2
0.1%
5101020 2
0.1%
5101010 2
0.1%
5008030 1
< 0.1%

하도명칭
Text

Distinct1188
Distinct (%)38.6%
Missing3
Missing (%)0.1%
Memory size24.2 KiB
2023-12-12T12:07:00.282157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length10.92013
Min length7

Characters and Unicode

Total characters33634
Distinct characters286
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique199 ?
Unique (%)6.5%

Sample

1st row1001010광동댐
2nd row1001010광동댐
3rd row1001010광동댐
4th row1001020정선군(혈천교)
5th row1001020정선군(혈천교)
ValueCountFrequency (%)
2016040 4
 
0.1%
2010030김천시(김천교 4
 
0.1%
2004240 4
 
0.1%
2009030의성군(낙단교 4
 
0.1%
2009040구미시(일선교 4
 
0.1%
2010010 4
 
0.1%
2010020 4
 
0.1%
2008110 4
 
0.1%
2010050 4
 
0.1%
2011050성주군(성주대교 4
 
0.1%
Other values (1178) 3040
98.7%
2023-12-12T12:07:00.645967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9790
29.1%
1 4034
12.0%
2 2903
 
8.6%
3 1364
 
4.1%
) 1278
 
3.8%
( 1278
 
3.8%
교 1029
 
3.1%
4 907
 
2.7%
5 839
 
2.5%
시 653
 
1.9%
Other values (276) 9559
28.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21734
64.6%
Other Letter 9100
27.1%
Close Punctuation 1348
 
4.0%
Open Punctuation 1348
 
4.0%
Lowercase Letter 55
 
0.2%
Math Symbol 18
 
0.1%
Currency Symbol 15
 
< 0.1%
Other Punctuation 15
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 1029
 
11.3%
시 653
 
7.2%
군 613
 
6.7%
천 428
 
4.7%
주 324
 
3.6%
대 243
 
2.7%
산 203
 
2.2%
양 189
 
2.1%
리 185
 
2.0%
성 163
 
1.8%
Other values (255) 5070
55.7%
Decimal Number
ValueCountFrequency (%)
0 9790
45.0%
1 4034
18.6%
2 2903
 
13.4%
3 1364
 
6.3%
4 907
 
4.2%
5 839
 
3.9%
8 558
 
2.6%
6 474
 
2.2%
7 472
 
2.2%
9 393
 
1.8%
Other Punctuation
ValueCountFrequency (%)
@ 9
60.0%
· 4
26.7%
# 2
 
13.3%
Close Punctuation
ValueCountFrequency (%)
) 1278
94.8%
] 70
 
5.2%
Open Punctuation
ValueCountFrequency (%)
( 1278
94.8%
[ 70
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
c 55
100.0%
Math Symbol
ValueCountFrequency (%)
+ 18
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 15
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24479
72.8%
Hangul 9100
 
27.1%
Latin 55
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 1029
 
11.3%
시 653
 
7.2%
군 613
 
6.7%
천 428
 
4.7%
주 324
 
3.6%
대 243
 
2.7%
산 203
 
2.2%
양 189
 
2.1%
리 185
 
2.0%
성 163
 
1.8%
Other values (255) 5070
55.7%
Common
ValueCountFrequency (%)
0 9790
40.0%
1 4034
16.5%
2 2903
 
11.9%
3 1364
 
5.6%
) 1278
 
5.2%
( 1278
 
5.2%
4 907
 
3.7%
5 839
 
3.4%
8 558
 
2.3%
6 474
 
1.9%
Other values (10) 1054
 
4.3%
Latin
ValueCountFrequency (%)
c 55
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24530
72.9%
Hangul 9100
 
27.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9790
39.9%
1 4034
16.4%
2 2903
 
11.8%
3 1364
 
5.6%
) 1278
 
5.2%
( 1278
 
5.2%
4 907
 
3.7%
5 839
 
3.4%
8 558
 
2.3%
6 474
 
1.9%
Other values (10) 1105
 
4.5%
Hangul
ValueCountFrequency (%)
교 1029
 
11.3%
시 653
 
7.2%
군 613
 
6.7%
천 428
 
4.7%
주 324
 
3.6%
대 243
 
2.7%
산 203
 
2.2%
양 189
 
2.1%
리 185
 
2.0%
성 163
 
1.8%
Other values (255) 5070
55.7%
None
ValueCountFrequency (%)
· 4
100.0%

적용시작일
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size24.2 KiB
2021-01-01
1086 
2000-01-01
1010 
2018-01-01
289 
2017-06-01
281 
2017-07-17
276 
Other values (2)
141 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2000-01-01
2nd row2017-07-17
3rd row2021-01-01
4th row2000-01-01
5th row2017-07-17

Common Values

ValueCountFrequency (%)
2021-01-01 1086
35.2%
2000-01-01 1010
32.8%
2018-01-01 289
 
9.4%
2017-06-01 281
 
9.1%
2017-07-17 276
 
9.0%
2013-01-01 71
 
2.3%
2011-01-01 70
 
2.3%

Length

2023-12-12T12:07:00.798329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:07:00.932564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-01-01 1086
35.2%
2000-01-01 1010
32.8%
2018-01-01 289
 
9.4%
2017-06-01 281
 
9.1%
2017-07-17 276
 
9.0%
2013-01-01 71
 
2.3%
2011-01-01 70
 
2.3%

적용종료일
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size24.2 KiB
9999-12-31
1188 
2020-12-31
989 
2017-12-31
281 
2017-05-31
280 
2017-07-16
276 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-07-16
2nd row2020-12-31
3rd row9999-12-31
4th row2017-07-16
5th row2020-12-31

Common Values

ValueCountFrequency (%)
9999-12-31 1188
38.5%
2020-12-31 989
32.1%
2017-12-31 281
 
9.1%
2017-05-31 280
 
9.1%
2017-07-16 276
 
9.0%
2012-12-31 69
 
2.2%

Length

2023-12-12T12:07:01.072340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:07:01.197341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9999-12-31 1188
38.5%
2020-12-31 989
32.1%
2017-12-31 281
 
9.1%
2017-05-31 280
 
9.1%
2017-07-16 276
 
9.0%
2012-12-31 69
 
2.2%

계산순서
Real number (ℝ)

Distinct318
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.68343
Minimum1
Maximum318
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.2 KiB
2023-12-12T12:07:01.363231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q134
median94
Q3181
95-th percentile269
Maximum318
Range317
Interquartile range (IQR)147

Descriptive statistics

Standard deviation87.171084
Coefficient of variation (CV)0.77359278
Kurtosis-0.97849971
Mean112.68343
Median Absolute Deviation (MAD)68
Skewness0.50108153
Sum347403
Variance7598.7979
MonotonicityNot monotonic
2023-12-12T12:07:01.534245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 28
 
0.9%
2 28
 
0.9%
3 28
 
0.9%
4 28
 
0.9%
5 28
 
0.9%
6 28
 
0.9%
7 28
 
0.9%
8 28
 
0.9%
9 28
 
0.9%
10 25
 
0.8%
Other values (308) 2806
91.0%
ValueCountFrequency (%)
1 28
0.9%
2 28
0.9%
3 28
0.9%
4 28
0.9%
5 28
0.9%
6 28
0.9%
7 28
0.9%
8 28
0.9%
9 28
0.9%
10 25
0.8%
ValueCountFrequency (%)
318 1
< 0.1%
317 1
< 0.1%
316 1
< 0.1%
315 2
0.1%
314 2
0.1%
313 2
0.1%
312 2
0.1%
311 2
0.1%
310 2
0.1%
309 2
0.1%

관측소유형
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size24.2 KiB
수위관측소
3083 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수위관측소 3083
100.0%

Length

2023-12-12T12:07:02.346157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:07:02.558942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수위관측소 3083
100.0%

하도연장
Real number (ℝ)

ZEROS 

Distinct847
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.5868829
Minimum0
Maximum72.01
Zeros50
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size27.2 KiB
2023-12-12T12:07:02.703013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.89
Q13.06
median5.69
Q310.41
95-th percentile19.42
Maximum72.01
Range72.01
Interquartile range (IQR)7.35

Descriptive statistics

Standard deviation6.8639904
Coefficient of variation (CV)0.90471811
Kurtosis12.898264
Mean7.5868829
Median Absolute Deviation (MAD)3.22
Skewness2.6446802
Sum23390.36
Variance47.114364
MonotonicityNot monotonic
2023-12-12T12:07:02.922177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 50
 
1.6%
7.29 16
 
0.5%
2.81 15
 
0.5%
3.11 13
 
0.4%
4.4 13
 
0.4%
0.98 12
 
0.4%
4.46 12
 
0.4%
4.32 12
 
0.4%
4.5 12
 
0.4%
5.64 11
 
0.4%
Other values (837) 2917
94.6%
ValueCountFrequency (%)
0.0 50
1.6%
0.09 2
 
0.1%
0.14 1
 
< 0.1%
0.15 3
 
0.1%
0.2 1
 
< 0.1%
0.24 3
 
0.1%
0.28 1
 
< 0.1%
0.29 1
 
< 0.1%
0.34 8
 
0.3%
0.36 4
 
0.1%
ValueCountFrequency (%)
72.01 3
0.1%
49.65 3
0.1%
44.23 3
0.1%
43.69 3
0.1%
43.19 3
0.1%
42.17 2
0.1%
40.83 1
 
< 0.1%
40.0 1
 
< 0.1%
39.02 3
0.1%
37.84 3
0.1%

하도폭
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct560
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202.82802
Minimum0
Maximum2510.84
Zeros1678
Zeros (%)54.4%
Negative0
Negative (%)0.0%
Memory size27.2 KiB
2023-12-12T12:07:03.211030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3323.455
95-th percentile859.241
Maximum2510.84
Range2510.84
Interquartile range (IQR)323.455

Descriptive statistics

Standard deviation312.5775
Coefficient of variation (CV)1.5410962
Kurtosis5.7725766
Mean202.82802
Median Absolute Deviation (MAD)0
Skewness2.118018
Sum625318.8
Variance97704.695
MonotonicityNot monotonic
2023-12-12T12:07:03.446534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1678
54.4%
234.46 5
 
0.2%
112.24 5
 
0.2%
165.01 5
 
0.2%
307.35 5
 
0.2%
375.13 5
 
0.2%
342.9 5
 
0.2%
357.27 5
 
0.2%
560.5 5
 
0.2%
252.29 4
 
0.1%
Other values (550) 1361
44.1%
ValueCountFrequency (%)
0.0 1678
54.4%
25.25 2
 
0.1%
30.0 2
 
0.1%
35.0 1
 
< 0.1%
41.29 2
 
0.1%
41.88 1
 
< 0.1%
43.75 1
 
< 0.1%
48.82 1
 
< 0.1%
49.0 1
 
< 0.1%
50.0 2
 
0.1%
ValueCountFrequency (%)
2510.84 2
0.1%
2009.23 2
0.1%
1982.14 1
 
< 0.1%
1824.0 1
 
< 0.1%
1728.21 3
0.1%
1544.8 3
0.1%
1534.74 4
0.1%
1486.59 4
0.1%
1463.39 3
0.1%
1401.13 3
0.1%

수면구배
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct521
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0026165488
Minimum0
Maximum0.05957
Zeros34
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size27.2 KiB
2023-12-12T12:07:03.688859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0001
Q10.00025
median0.0012
Q30.00325
95-th percentile0.009723
Maximum0.05957
Range0.05957
Interquartile range (IQR)0.003

Descriptive statistics

Standard deviation0.0039142075
Coefficient of variation (CV)1.4959429
Kurtosis27.514801
Mean0.0026165488
Median Absolute Deviation (MAD)0.00108
Skewness3.9267487
Sum8.06682
Variance1.5321021 × 10-5
MonotonicityNot monotonic
2023-12-12T12:07:03.979266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0001 404
 
13.1%
0.00022 36
 
1.2%
0.00024 34
 
1.1%
0.00016 34
 
1.1%
0.0 34
 
1.1%
0.00011 31
 
1.0%
0.00014 28
 
0.9%
0.00013 24
 
0.8%
0.00015 24
 
0.8%
0.00018 23
 
0.7%
Other values (511) 2411
78.2%
ValueCountFrequency (%)
0.0 34
 
1.1%
0.0001 404
13.1%
0.00011 31
 
1.0%
0.00012 21
 
0.7%
0.00013 24
 
0.8%
0.00014 28
 
0.9%
0.00015 24
 
0.8%
0.00016 34
 
1.1%
0.00017 22
 
0.7%
0.00018 23
 
0.7%
ValueCountFrequency (%)
0.05957 1
 
< 0.1%
0.03269 4
0.1%
0.02957 4
0.1%
0.02858 2
0.1%
0.02728 1
 
< 0.1%
0.02588 4
0.1%
0.02293 4
0.1%
0.02291 2
0.1%
0.02195 2
0.1%
0.01935 4
0.1%

조도계수
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size24.2 KiB
0
3083 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3083
100.0%

Length

2023-12-12T12:07:04.180386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:07:04.309306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3083
100.0%

1시간최대허용변동량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size24.2 KiB
3
3083 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 3083
100.0%

Length

2023-12-12T12:07:04.460657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:07:04.606201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3083
100.0%

Interactions

2023-12-12T12:06:58.311357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:55.783581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:56.297800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:56.874757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:57.572774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:58.445556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:55.877782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:56.415069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:57.002933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:57.718716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:58.595803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:55.980535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:56.529271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:57.152239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:57.867159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:58.775184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:56.093778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:56.664329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:57.267023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:58.020722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:58.921875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:56.180397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:56.752844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:57.420894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:06:58.161200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:07:04.703986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예보유역명하도코드적용시작일적용종료일계산순서하도연장하도폭수면구배
예보유역명1.0001.0000.8950.6860.5280.1750.2930.171
하도코드1.0001.0000.8610.5900.4570.1520.2140.171
적용시작일0.8950.8611.0000.8350.3060.0890.0870.082
적용종료일0.6860.5900.8351.0000.2640.0850.0890.000
계산순서0.5280.4570.3060.2641.0000.1510.3510.144
하도연장0.1750.1520.0890.0850.1511.0000.1260.000
하도폭0.2930.2140.0870.0890.3510.1261.0000.176
수면구배0.1710.1710.0820.0000.1440.0000.1761.000
2023-12-12T12:07:04.868000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적용종료일적용시작일예보유역명
적용종료일1.0000.6860.424
적용시작일0.6861.0000.560
예보유역명0.4240.5601.000
2023-12-12T12:07:05.024175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
하도코드계산순서하도연장하도폭수면구배예보유역명적용시작일적용종료일
하도코드1.000-0.213-0.1590.180-0.1180.9990.4720.402
계산순서-0.2131.0000.0840.120-0.1880.2440.1600.142
하도연장-0.1590.0841.000-0.1800.1870.0780.0470.047
하도폭0.1800.120-0.1801.000-0.5370.1220.0440.047
수면구배-0.118-0.1880.187-0.5371.0000.0640.0290.000
예보유역명0.9990.2440.0780.1220.0641.0000.5600.424
적용시작일0.4720.1600.0470.0440.0290.5601.0000.686
적용종료일0.4020.1420.0470.0470.0000.4240.6861.000

Missing values

2023-12-12T12:06:59.146236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:06:59.394644image/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

예보유역명하도코드하도명칭적용시작일적용종료일계산순서관측소유형하도연장하도폭수면구배조도계수1시간최대허용변동량
0한강10010101001010광동댐2000-01-012017-07-161수위관측소29.570.00.0056203
1한강10010101001010광동댐2017-07-172020-12-311수위관측소29.570.00.0056203
2한강10010101001010광동댐2021-01-019999-12-311수위관측소29.570.00.0056203
3한강10010201001020정선군(혈천교)2000-01-012017-07-162수위관측소1.970.00.0048103
4한강10010201001020정선군(혈천교)2017-07-172020-12-312수위관측소1.970.00.0048103
5한강10010201001020정선군(혈천교)2021-01-019999-12-312수위관측소1.970.00.0048103
6한강10010301001030정선군(송계교)2000-01-012017-07-163수위관측소3.220.00.0055503
7한강10010301001030정선군(송계교)2017-07-172020-12-313수위관측소3.220.00.0055503
8한강10010301001030정선군(송계교)2021-01-019999-12-313수위관측소3.220.00.0055503
9한강100104010010402000-01-012017-07-164수위관측소25.110.00.0041403
예보유역명하도코드하도명칭적용시작일적용종료일계산순서관측소유형하도연장하도폭수면구배조도계수1시간최대허용변동량
3073탐진강51010505101050장흥군(감천교)2000-01-012020-12-315수위관측소0.74121.320.0003103
3074탐진강51010505101050장흥군(감천교)2021-01-019999-12-315수위관측소0.74121.320.0003103
3075탐진강510106051010602000-01-012020-12-316수위관측소2.0270.150.0008503
3076탐진강510106051010602021-01-019999-12-316수위관측소2.0270.150.0008503
3077탐진강51010705101070풍동2000-01-012020-12-317수위관측소5.5260.50.0011103
3078탐진강51010705101070풍동2021-01-019999-12-317수위관측소5.5260.50.0011103
3079탐진강51010805101080강진군(석교교)2000-01-012020-12-318수위관측소4.5236.880.0007703
3080탐진강51010805101080강진군(석교교)2021-01-019999-12-318수위관측소4.5236.880.0007703
3081탐진강510109051010902000-01-012020-12-319수위관측소0.00.00.003
3082탐진강510109051010902021-01-019999-12-319수위관측소0.00.00.003