Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory644.5 KiB
Average record size in memory66.0 B

Variable types

DateTime1
Numeric2
Categorical4

Dataset

Description김해도시개발공사 생림 하수처리시설별에 대한 시간대별 계측 현황을 조회하는 서비스로 기준연월일, 기준시간, 하수처리장구분명, 계측구분명, 계측값 등의 정보를 제공
Author김해시도시개발공사
URLhttps://www.data.go.kr/data/15096558/fileData.do

Alerts

하수처리장구분명 has constant value ""Constant
계측태그명 is highly overall correlated with 계측값 and 2 other fieldsHigh correlation
계측구분명 is highly overall correlated with 계측값 and 2 other fieldsHigh correlation
계측단위 is highly overall correlated with 계측값 and 2 other fieldsHigh correlation
계측값 is highly overall correlated with 계측구분명 and 2 other fieldsHigh correlation
기준시간 has 436 (4.4%) zerosZeros
계측값 has 329 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-12 19:11:35.005940
Analysis finished2023-12-12 19:11:36.343349
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연월일
Date

Distinct1119
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-01-01 00:00:00
Maximum2021-02-13 00:00:00
2023-12-13T04:11:36.439703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:36.610808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

기준시간
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.4215
Minimum0
Maximum23
Zeros436
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:11:37.095253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median11
Q317
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.9210568
Coefficient of variation (CV)0.60596742
Kurtosis-1.2119816
Mean11.4215
Median Absolute Deviation (MAD)6
Skewness-0.0020251178
Sum114215
Variance47.901028
MonotonicityNot monotonic
2023-12-13T04:11:37.232155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
16 478
 
4.8%
4 447
 
4.5%
18 444
 
4.4%
2 443
 
4.4%
0 436
 
4.4%
10 433
 
4.3%
12 432
 
4.3%
5 420
 
4.2%
13 419
 
4.2%
3 413
 
4.1%
Other values (14) 5635
56.4%
ValueCountFrequency (%)
0 436
4.4%
1 412
4.1%
2 443
4.4%
3 413
4.1%
4 447
4.5%
5 420
4.2%
6 409
4.1%
7 403
4.0%
8 406
4.1%
9 376
3.8%
ValueCountFrequency (%)
23 380
3.8%
22 413
4.1%
21 409
4.1%
20 409
4.1%
19 408
4.1%
18 444
4.4%
17 403
4.0%
16 478
4.8%
15 401
4.0%
14 401
4.0%

하수처리장구분명
Categorical

CONSTANT 

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

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생림 하수처리장
2nd row생림 하수처리장
3rd row생림 하수처리장
4th row생림 하수처리장
5th row생림 하수처리장

Common Values

ValueCountFrequency (%)
생림 하수처리장 10000
100.0%

Length

2023-12-13T04:11:37.410452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:11:37.517698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생림 10000
50.0%
하수처리장 10000
50.0%

계측구분명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
유량조정소 수위
5611 
긴급차단 개도
2801 
유량조정조(PH)
1588 

Length

Max length9
Median length8
Mean length7.8787
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row긴급차단 개도
2nd row유량조정소 수위
3rd row유량조정조(PH)
4th row유량조정조(PH)
5th row유량조정소 수위

Common Values

ValueCountFrequency (%)
유량조정소 수위 5611
56.1%
긴급차단 개도 2801
28.0%
유량조정조(PH) 1588
 
15.9%

Length

2023-12-13T04:11:37.679790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:11:37.824610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유량조정소 5611
30.5%
수위 5611
30.5%
긴급차단 2801
15.2%
개도 2801
15.2%
유량조정조(ph 1588
 
8.6%

계측태그명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
LT-104
2815 
M-111
2801 
LT-103
2796 
PHT-101
1588 

Length

Max length7
Median length6
Mean length5.8787
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM-111
2nd rowLT-103
3rd rowPHT-101
4th rowPHT-101
5th rowLT-104

Common Values

ValueCountFrequency (%)
LT-104 2815
28.1%
M-111 2801
28.0%
LT-103 2796
28.0%
PHT-101 1588
15.9%

Length

2023-12-13T04:11:38.012539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:11:38.173028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
lt-104 2815
28.1%
m-111 2801
28.0%
lt-103 2796
28.0%
pht-101 1588
15.9%

계측단위
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
5611 
%
2801 
<NA>
1588 

Length

Max length4
Median length1
Mean length1.4764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 5611
56.1%
% 2801
28.0%
<NA> 1588
 
15.9%

Length

2023-12-13T04:11:38.337119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:11:38.470559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 5611
56.1%
2801
28.0%
na 1588
 
15.9%

계측값
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1091
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.27227
Minimum0
Maximum46.15
Zeros329
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:11:38.635827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.98
Q11.57
median2.22
Q311.4425
95-th percentile32.98
Maximum46.15
Range46.15
Interquartile range (IQR)9.8725

Descriptive statistics

Standard deviation11.902633
Coefficient of variation (CV)1.2836806
Kurtosis-0.12405114
Mean9.27227
Median Absolute Deviation (MAD)1.12
Skewness1.2560518
Sum92722.7
Variance141.67268
MonotonicityNot monotonic
2023-12-13T04:11:38.849263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 329
 
3.3%
6.26 63
 
0.6%
6.29 56
 
0.6%
6.3 56
 
0.6%
6.25 55
 
0.5%
1.16 53
 
0.5%
2.05 53
 
0.5%
30.01 53
 
0.5%
1.23 50
 
0.5%
1.98 50
 
0.5%
Other values (1081) 9182
91.8%
ValueCountFrequency (%)
0.0 329
3.3%
0.31 1
 
< 0.1%
0.56 1
 
< 0.1%
0.58 1
 
< 0.1%
0.59 1
 
< 0.1%
0.62 1
 
< 0.1%
0.75 3
 
< 0.1%
0.76 4
 
< 0.1%
0.78 3
 
< 0.1%
0.8 2
 
< 0.1%
ValueCountFrequency (%)
46.15 1
< 0.1%
46.09 1
< 0.1%
46.06 1
< 0.1%
39.88 1
< 0.1%
38.12 1
< 0.1%
38.04 1
< 0.1%
37.96 2
< 0.1%
37.94 1
< 0.1%
37.93 2
< 0.1%
37.92 1
< 0.1%

Interactions

2023-12-13T04:11:35.795038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:35.556012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:35.940356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:35.665717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:11:38.947781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준시간계측구분명계측태그명계측단위계측값
기준시간1.0000.0000.0000.0000.000
계측구분명0.0001.0001.0001.0000.955
계측태그명0.0001.0001.0001.0000.897
계측단위0.0001.0001.0001.0000.998
계측값0.0000.9550.8970.9981.000
2023-12-13T04:11:39.073544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계측태그명계측구분명계측단위
계측태그명1.0001.0001.000
계측구분명1.0001.0001.000
계측단위1.0001.0001.000
2023-12-13T04:11:39.206086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준시간계측값계측구분명계측태그명계측단위
기준시간1.0000.0180.0000.0000.000
계측값0.0181.0000.9510.7770.961
계측구분명0.0000.9511.0001.0001.000
계측태그명0.0000.7771.0001.0001.000
계측단위0.0000.9611.0001.0001.000

Missing values

2023-12-13T04:11:36.104163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:11:36.271178image/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

기준연월일기준시간하수처리장구분명계측구분명계측태그명계측단위계측값
221742020-08-0122생림 하수처리장긴급차단 개도M-111%25.53
485772020-07-131생림 하수처리장유량조정소 수위LT-103M1.54
865802018-09-0712생림 하수처리장유량조정조(PH)PHT-101<NA>6.2
868872018-09-207생림 하수처리장유량조정조(PH)PHT-101<NA>6.07
790242020-12-0816생림 하수처리장유량조정소 수위LT-104M1.16
554922018-03-144생림 하수처리장유량조정소 수위LT-104M1.15
714052020-01-115생림 하수처리장유량조정소 수위LT-104M2.38
55412018-08-2121생림 하수처리장긴급차단 개도M-111%25.84
99842019-02-240생림 하수처리장긴급차단 개도M-111%32.71
351802018-12-1420생림 하수처리장유량조정소 수위LT-103M1.89
기준연월일기준시간하수처리장구분명계측구분명계측태그명계측단위계측값
927002019-05-2112생림 하수처리장유량조정조(PH)PHT-101<NA>6.32
756342020-07-2010생림 하수처리장유량조정소 수위LT-104M1.82
364492019-02-0517생림 하수처리장유량조정소 수위LT-103M1.35
7122018-01-3016생림 하수처리장긴급차단 개도M-111%17.07
468852020-04-1813생림 하수처리장유량조정소 수위LT-103M1.75
404302019-07-2314생림 하수처리장유량조정소 수위LT-103M1.31
28842018-05-014생림 하수처리장긴급차단 개도M-111%37.43
519112020-11-2823생림 하수처리장유량조정소 수위LT-103M1.79
296852018-04-2721생림 하수처리장유량조정소 수위LT-103M1.72
271102018-01-1014생림 하수처리장유량조정소 수위LT-103M1.39