Overview

Dataset statistics

Number of variables8
Number of observations3929
Missing cells169
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory257.2 KiB
Average record size in memory67.0 B

Variable types

Numeric3
Categorical1
DateTime3
Text1

Dataset

Description한강홍수통제소에서 요청을 받아 승인 진행 완료한 댐 방류 승인 내역 데이터입니다. 접수번호, 승인번호, 승인 일시, 방류 시작/종료 시간, 방류량 데이터를 제공합니다.
Author환경부 한강홍수통제소
URLhttps://www.data.go.kr/data/15085926/fileData.do

Alerts

관측소코드 is highly overall correlated with 접수방류량 and 1 other fieldsHigh correlation
접수방류량 is highly overall correlated with 관측소코드High correlation
관측소명 is highly overall correlated with 관측소코드High correlation
비고 has 165 (4.2%) missing valuesMissing
관측소코드 is highly skewed (γ1 = 21.98587485)Skewed
순차번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:37:58.194373
Analysis finished2023-12-12 19:37:59.959302
Duration1.76 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순차번호
Real number (ℝ)

UNIQUE 

Distinct3929
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1965
Minimum1
Maximum3929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.7 KiB
2023-12-13T04:38:00.054537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile197.4
Q1983
median1965
Q32947
95-th percentile3732.6
Maximum3929
Range3928
Interquartile range (IQR)1964

Descriptive statistics

Standard deviation1134.3489
Coefficient of variation (CV)0.57727681
Kurtosis-1.2
Mean1965
Median Absolute Deviation (MAD)982
Skewness0
Sum7720485
Variance1286747.5
MonotonicityStrictly increasing
2023-12-13T04:38:00.251201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2611 1
 
< 0.1%
2613 1
 
< 0.1%
2614 1
 
< 0.1%
2615 1
 
< 0.1%
2616 1
 
< 0.1%
2617 1
 
< 0.1%
2618 1
 
< 0.1%
2619 1
 
< 0.1%
2620 1
 
< 0.1%
Other values (3919) 3919
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3929 1
< 0.1%
3928 1
< 0.1%
3927 1
< 0.1%
3926 1
< 0.1%
3925 1
< 0.1%
3924 1
< 0.1%
3923 1
< 0.1%
3922 1
< 0.1%
3921 1
< 0.1%
3920 1
< 0.1%

관측소코드
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1012500.4
Minimum1001210
Maximum1302210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.7 KiB
2023-12-13T04:38:00.435791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001210
5-th percentile1004310
Q11007803
median1013310
Q31017310
95-th percentile1017310
Maximum1302210
Range301000
Interquartile range (IQR)9507

Descriptive statistics

Standard deviation9438.7947
Coefficient of variation (CV)0.0093222623
Kurtosis676.04498
Mean1012500.4
Median Absolute Deviation (MAD)4000
Skewness21.985875
Sum3.9781143 × 109
Variance89090846
MonotonicityNot monotonic
2023-12-13T04:38:00.555716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1017310 1194
30.4%
1004310 723
18.4%
1015310 681
17.3%
1013310 520
13.2%
1010320 352
 
9.0%
1010310 107
 
2.7%
1007803 82
 
2.1%
1007802 82
 
2.1%
1007801 81
 
2.1%
1001210 36
 
0.9%
Other values (6) 71
 
1.8%
ValueCountFrequency (%)
1001210 36
 
0.9%
1003110 15
 
0.4%
1003611 21
 
0.5%
1004310 723
18.4%
1006110 24
 
0.6%
1007801 81
 
2.1%
1007802 82
 
2.1%
1007803 82
 
2.1%
1010310 107
 
2.7%
1010320 352
9.0%
ValueCountFrequency (%)
1302210 3
 
0.1%
1021701 2
 
0.1%
1017310 1194
30.4%
1015310 681
17.3%
1013310 520
13.2%
1012110 6
 
0.2%
1010320 352
 
9.0%
1010310 107
 
2.7%
1007803 82
 
2.1%
1007802 82
 
2.1%

관측소명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
팔당댐
1194 
괴산댐
723 
청평댐
681 
의암댐
520 
춘천댐
352 
Other values (11)
459 

Length

Max length5
Median length3
Mean length2.9903283
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row팔당댐
2nd row청평댐
3rd row팔당댐
4th row청평댐
5th row팔당댐

Common Values

ValueCountFrequency (%)
팔당댐 1194
30.4%
괴산댐 723
18.4%
청평댐 681
17.3%
의암댐 520
13.2%
춘천댐 352
 
9.0%
화천댐 107
 
2.7%
여주보 82
 
2.1%
이포보 82
 
2.1%
강천보 81
 
2.1%
광동 36
 
0.9%
Other values (6) 71
 
1.8%

Length

2023-12-13T04:38:00.676300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
팔당댐 1194
30.4%
괴산댐 723
18.4%
청평댐 681
17.3%
의암댐 520
13.2%
춘천댐 352
 
9.0%
화천댐 107
 
2.7%
여주보 82
 
2.1%
이포보 82
 
2.1%
강천보 81
 
2.1%
광동 36
 
0.9%
Other values (6) 71
 
1.8%

승인년월일시분
Date

Distinct599
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
Minimum2010-07-16 00:00:00
Maximum2021-07-16 00:00:00
2023-12-13T04:38:00.808127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:38:00.966100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

방류시작시간
Date

Distinct2648
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
Minimum2010-07-17 05:00:00
Maximum2021-07-13 13:30:00
2023-12-13T04:38:01.101329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:38:01.243238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

접수방류량
Real number (ℝ)

HIGH CORRELATION 

Distinct2172
Distinct (%)55.3%
Missing4
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2068.2683
Minimum0
Maximum18392
Zeros16
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size34.7 KiB
2023-12-13T04:38:01.385247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile31
Q1462
median1150
Q32594
95-th percentile7367.8
Maximum18392
Range18392
Interquartile range (IQR)2132

Descriptive statistics

Standard deviation2524.8804
Coefficient of variation (CV)1.2207703
Kurtosis6.6984549
Mean2068.2683
Median Absolute Deviation (MAD)905
Skewness2.3205649
Sum8117953
Variance6375021.1
MonotonicityNot monotonic
2023-12-13T04:38:01.532778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 43
 
1.1%
100 34
 
0.9%
24 25
 
0.6%
25 25
 
0.6%
61 24
 
0.6%
500 18
 
0.5%
1100 18
 
0.5%
2000 18
 
0.5%
1500 17
 
0.4%
700 17
 
0.4%
Other values (2162) 3686
93.8%
ValueCountFrequency (%)
0 16
0.4%
4 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
8 3
 
0.1%
9 5
 
0.1%
10 1
 
< 0.1%
11 3
 
0.1%
12 1
 
< 0.1%
13 3
 
0.1%
ValueCountFrequency (%)
18392 1
< 0.1%
17992 1
< 0.1%
17393 1
< 0.1%
16992 1
< 0.1%
16900 1
< 0.1%
16492 1
< 0.1%
16393 1
< 0.1%
16391 1
< 0.1%
15992 1
< 0.1%
15991 1
< 0.1%

접수일자
Date

Distinct594
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
Minimum2010-07-16 00:00:00
Maximum2021-07-16 00:00:00
2023-12-13T04:38:01.675383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:38:01.817007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

비고
Text

MISSING 

Distinct3229
Distinct (%)85.8%
Missing165
Missing (%)4.2%
Memory size30.8 KiB
2023-12-13T04:38:02.192605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length171
Median length159
Mean length14.670298
Min length3

Characters and Unicode

Total characters55219
Distinct characters218
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2899 ?
Unique (%)77.0%

Sample

1st row초기방류
2nd row초기방류
3rd rowㅇ 댐상류 집중호우로 인한 방류시간 변경(당초 7시)
4th rowㅇ 댐상류 집중호우로 인한 방류시간 변경(당초 7시)
5th row증가방류
ValueCountFrequency (%)
감소방류 1268
 
14.4%
증가방류 1116
 
12.7%
㎥/s 325
 
3.7%
수문전폐 136
 
1.5%
방류 110
 
1.3%
탄력적 108
 
1.2%
초기수문방류 100
 
1.1%
94
 
1.1%
이내 88
 
1.0%
변경 81
 
0.9%
Other values (2640) 5363
61.0%
2023-12-13T04:38:02.820124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6602
 
12.0%
류 3547
 
6.4%
방 3540
 
6.4%
s 3389
 
6.1%
( 2980
 
5.4%
) 2980
 
5.4%
/ 2650
 
4.8%
㎥ 2523
 
4.6%
0 2477
 
4.5%
1 1818
 
3.3%
Other values (208) 22713
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18492
33.5%
Decimal Number 12169
22.0%
Space Separator 6602
 
12.0%
Lowercase Letter 5148
 
9.3%
Other Punctuation 2994
 
5.4%
Open Punctuation 2982
 
5.4%
Close Punctuation 2982
 
5.4%
Other Symbol 2523
 
4.6%
Dash Punctuation 1182
 
2.1%
Math Symbol 127
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 3547
19.2%
방 3540
19.1%
소 1789
9.7%
감 1780
9.6%
가 1434
 
7.8%
증 1433
 
7.7%
수 367
 
2.0%
문 336
 
1.8%
초 294
 
1.6%
기 284
 
1.5%
Other values (165) 3688
19.9%
Decimal Number
ValueCountFrequency (%)
0 2477
20.4%
1 1818
14.9%
2 1348
11.1%
3 1104
9.1%
5 1043
8.6%
4 1009
8.3%
6 874
 
7.2%
9 867
 
7.1%
7 829
 
6.8%
8 800
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
s 3389
65.8%
m 877
 
17.0%
c 865
 
16.8%
b 5
 
0.1%
r 5
 
0.1%
t 4
 
0.1%
g 2
 
< 0.1%
l 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2650
88.5%
: 213
 
7.1%
. 119
 
4.0%
* 4
 
0.1%
& 3
 
0.1%
; 3
 
0.1%
" 2
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 93
73.2%
+ 13
 
10.2%
> 9
 
7.1%
< 6
 
4.7%
→ 5
 
3.9%
= 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
S 4
22.2%
L 4
22.2%
E 4
22.2%
M 3
16.7%
C 3
16.7%
Open Punctuation
ValueCountFrequency (%)
( 2980
99.9%
[ 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 2980
99.9%
] 2
 
0.1%
Space Separator
ValueCountFrequency (%)
6602
100.0%
Other Symbol
ValueCountFrequency (%)
㎥ 2523
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31561
57.2%
Hangul 18492
33.5%
Latin 5166
 
9.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 3547
19.2%
방 3540
19.1%
소 1789
9.7%
감 1780
9.6%
가 1434
 
7.8%
증 1433
 
7.7%
수 367
 
2.0%
문 336
 
1.8%
초 294
 
1.6%
기 284
 
1.5%
Other values (165) 3688
19.9%
Common
ValueCountFrequency (%)
6602
20.9%
( 2980
9.4%
) 2980
9.4%
/ 2650
8.4%
㎥ 2523
 
8.0%
0 2477
 
7.8%
1 1818
 
5.8%
2 1348
 
4.3%
- 1182
 
3.7%
3 1104
 
3.5%
Other values (20) 5897
18.7%
Latin
ValueCountFrequency (%)
s 3389
65.6%
m 877
 
17.0%
c 865
 
16.7%
b 5
 
0.1%
r 5
 
0.1%
t 4
 
0.1%
S 4
 
0.1%
L 4
 
0.1%
E 4
 
0.1%
M 3
 
0.1%
Other values (3) 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34199
61.9%
Hangul 18486
33.5%
CJK Compat 2523
 
4.6%
Compat Jamo 6
 
< 0.1%
Arrows 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6602
19.3%
s 3389
9.9%
( 2980
 
8.7%
) 2980
 
8.7%
/ 2650
 
7.7%
0 2477
 
7.2%
1 1818
 
5.3%
2 1348
 
3.9%
- 1182
 
3.5%
3 1104
 
3.2%
Other values (31) 7669
22.4%
Hangul
ValueCountFrequency (%)
류 3547
19.2%
방 3540
19.1%
소 1789
9.7%
감 1780
9.6%
가 1434
 
7.8%
증 1433
 
7.8%
수 367
 
2.0%
문 336
 
1.8%
초 294
 
1.6%
기 284
 
1.5%
Other values (164) 3682
19.9%
CJK Compat
ValueCountFrequency (%)
㎥ 2523
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 6
100.0%
Arrows
ValueCountFrequency (%)
→ 5
100.0%

Interactions

2023-12-13T04:37:59.283416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:58.619494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:58.972184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:59.384890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:58.745205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:59.075458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:59.479157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:58.867112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:59.173677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:38:02.948166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순차번호관측소코드관측소명접수방류량
순차번호1.0000.0900.3710.284
관측소코드0.0901.0001.0000.000
관측소명0.3711.0001.0000.357
접수방류량0.2840.0000.3571.000
2023-12-13T04:38:03.067264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순차번호관측소코드접수방류량관측소명
순차번호1.000-0.0140.0660.155
관측소코드-0.0141.0000.6130.998
접수방류량0.0660.6131.0000.148
관측소명0.1550.9980.1481.000

Missing values

2023-12-13T04:37:59.626088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:37:59.776633image/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.
2023-12-13T04:37:59.898357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순차번호관측소코드관측소명승인년월일시분방류시작시간접수방류량접수일자비고
011017310팔당댐2010-07-162010-07-17 05:009582010-07-16초기방류
121015310청평댐2010-07-162010-07-17 07:004462010-07-16초기방류
231017310팔당댐2010-07-172010-07-17 05:009582010-07-17ㅇ 댐상류 집중호우로 인한 방류시간 변경(당초 7시)
341015310청평댐2010-07-172010-07-17 05:004462010-07-17ㅇ 댐상류 집중호우로 인한 방류시간 변경(당초 7시)
451017310팔당댐2010-07-172010-07-17 06:1011252010-07-17증가방류
561015310청평댐2010-07-172010-07-17 06:104182010-07-17감소방류
671017310팔당댐2010-07-172010-07-17 07:2017992010-07-17674 cms 증가 방류
781017310팔당댐2010-07-172010-07-17 11:5022302010-07-17증가방류 776
891015310청평댐2010-07-172010-07-17 18:004292010-07-17<NA>
9101017310팔당댐2010-07-172010-07-17 15:3019692010-07-17<NA>
순차번호관측소코드관측소명승인년월일시분방류시작시간접수방류량접수일자비고
391939201017310팔당댐2021-07-092021-07-09 16:207902021-07-09(수문전폐 -260㎥/s)
392039211017310팔당댐2021-07-112021-07-11 22:009702021-07-11(증가방류 260㎥/s)팔당댐 초기방류
392139221017310팔당댐2021-07-112021-07-11 22:1020252021-07-11(증가방류 1055㎥/s)팔당댐 증가방류
392239231017310팔당댐2021-07-122021-07-12 01:4017902021-07-12(감소방류 -235㎥/s)
392339241017310팔당댐2021-07-122021-07-12 13:409902021-07-12(감소방류 -800㎥/s)
392439251017310팔당댐2021-07-122021-07-12 21:008702021-07-12(감소방류 -120㎥/s)
392539261017310팔당댐2021-07-132021-07-13 13:307392021-07-13(수문전폐 -131㎥/s)
392639271007801강천보2021-07-162021-07-03 06:009002021-07-16방류기간 (당초) 07/03 06:00 ~ 07/16 18:00 (변경) 07/03 06:00 ~ 07/23 18:00 방류량(당초) 3000㎥/s(강천보) 3100㎥/s(여주보) 3200㎥/s(이포보)(변경) 900㎥/s(강천보) 1000㎥/s(여주보) 1100㎥/s(이포보)
392739281007802여주보2021-07-162021-07-03 06:0010002021-07-16방류기간 (당초) 07/03 06:00 ~ 07/16 18:00 (변경) 07/03 06:00 ~ 07/23 18:00 방류량(당초) 3000㎥/s(강천보) 3100㎥/s(여주보) 3200㎥/s(이포보)(변경) 900㎥/s(강천보) 1000㎥/s(여주보) 1100㎥/s(이포보)
392839291007803이포보2021-07-162021-07-03 06:0011002021-07-16방류기간 (당초) 07/03 06:00 ~ 07/16 18:00 (변경) 07/03 06:00 ~ 07/23 18:00 방류량(당초) 3000㎥/s(강천보) 3100㎥/s(여주보) 3200㎥/s(이포보)(변경) 900㎥/s(강천보) 1000㎥/s(여주보) 1100㎥/s(이포보)