Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory566.4 KiB
Average record size in memory58.0 B

Variable types

DateTime1
Numeric2
Categorical3

Dataset

Description김해도시개발공사 진례 하수처리시설별에 대한 시간대별 가동시간 현황을 조회하는 서비스로 기준연월일, 기준시간, 하수처리장구분명, 가동시간 등의 정보를 제공
Author김해시도시개발공사
URLhttps://www.data.go.kr/data/15096562/fileData.do

Alerts

하수처리장구분명 has constant value ""Constant
태그설명 is highly overall correlated with 태그High correlation
태그 is highly overall correlated with 태그설명High correlation
기준시간 has 445 (4.5%) zerosZeros
가동시간 has 8752 (87.5%) zerosZeros

Reproduction

Analysis started2023-12-12 06:32:48.413784
Analysis finished2023-12-12 06:32:49.548658
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연월일
Date

Distinct1657
Distinct (%)16.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-02-08 00:00:00
Maximum2021-08-25 00:00:00
2023-12-12T15:32:49.634872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:32:49.820726image/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%
Mean11.4388
Minimum0
Maximum23
Zeros445
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:32:49.982769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median11
Q318
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)13

Descriptive statistics

Standard deviation6.9705031
Coefficient of variation (CV)0.60937363
Kurtosis-1.2193599
Mean11.4388
Median Absolute Deviation (MAD)6
Skewness0.0055224015
Sum114388
Variance48.587913
MonotonicityNot monotonic
2023-12-12T15:32:50.132773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 446
 
4.5%
0 445
 
4.5%
9 443
 
4.4%
5 441
 
4.4%
17 439
 
4.4%
19 438
 
4.4%
18 437
 
4.4%
13 432
 
4.3%
12 428
 
4.3%
23 428
 
4.3%
Other values (14) 5623
56.2%
ValueCountFrequency (%)
0 445
4.5%
1 446
4.5%
2 411
4.1%
3 402
4.0%
4 424
4.2%
5 441
4.4%
6 425
4.2%
7 389
3.9%
8 415
4.2%
9 443
4.4%
ValueCountFrequency (%)
23 428
4.3%
22 401
4.0%
21 406
4.1%
20 414
4.1%
19 438
4.4%
18 437
4.4%
17 439
4.4%
16 381
3.8%
15 374
3.7%
14 412
4.1%

하수처리장구분명
Categorical

CONSTANT 

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

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진례 하수처리장 10000
100.0%

Length

2023-12-12T15:32:50.261252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:32:50.367059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진례 10000
50.0%
하수처리장 10000
50.0%

태그설명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
역세펌프
8332 
약품펌프
1668 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
역세펌프 8332
83.3%
약품펌프 1668
 
16.7%

Length

2023-12-12T15:32:50.466841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:32:50.590381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
역세펌프 8332
83.3%
약품펌프 1668
 
16.7%

태그
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M-101B
4180 
M-101A
4152 
M-102A
1668 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM-101B
2nd rowM-101A
3rd rowM-101B
4th rowM-101A
5th rowM-101B

Common Values

ValueCountFrequency (%)
M-101B 4180
41.8%
M-101A 4152
41.5%
M-102A 1668
 
16.7%

Length

2023-12-12T15:32:50.700807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:32:50.807792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m-101b 4180
41.8%
m-101a 4152
41.5%
m-102a 1668
 
16.7%

가동시간
Real number (ℝ)

ZEROS 

Distinct50
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.15
Minimum0
Maximum60
Zeros8752
Zeros (%)87.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:32:50.956784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum60
Range60
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.3859348
Coefficient of variation (CV)3.8138563
Kurtosis63.957205
Mean1.15
Median Absolute Deviation (MAD)0
Skewness6.7685676
Sum11500
Variance19.236424
MonotonicityNot monotonic
2023-12-12T15:32:51.117544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8752
87.5%
4 255
 
2.5%
3 150
 
1.5%
5 97
 
1.0%
6 86
 
0.9%
8 60
 
0.6%
2 58
 
0.6%
7 56
 
0.6%
13 54
 
0.5%
10 52
 
0.5%
Other values (40) 380
 
3.8%
ValueCountFrequency (%)
0 8752
87.5%
1 17
 
0.2%
2 58
 
0.6%
3 150
 
1.5%
4 255
 
2.5%
5 97
 
1.0%
6 86
 
0.9%
7 56
 
0.6%
8 60
 
0.6%
9 48
 
0.5%
ValueCountFrequency (%)
60 10
0.1%
59 1
 
< 0.1%
57 1
 
< 0.1%
55 1
 
< 0.1%
53 1
 
< 0.1%
52 1
 
< 0.1%
49 4
 
< 0.1%
47 2
 
< 0.1%
45 1
 
< 0.1%
43 1
 
< 0.1%

Interactions

2023-12-12T15:32:49.094587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:32:48.826960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:32:49.181188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:32:48.932613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:32:51.206610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준시간태그설명태그가동시간
기준시간1.0000.0440.0450.000
태그설명0.0441.0001.0000.152
태그0.0451.0001.0000.208
가동시간0.0000.1520.2081.000
2023-12-12T15:32:51.323298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
태그설명태그
태그설명1.0001.000
태그1.0001.000
2023-12-12T15:32:51.412402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준시간가동시간태그설명태그
기준시간1.0000.0180.0330.027
가동시간0.0181.0000.1070.123
태그설명0.0330.1071.0001.000
태그0.0270.1231.0001.000

Missing values

2023-12-12T15:32:49.326219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:32:49.487342image/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

기준연월일기준시간하수처리장구분명태그설명태그가동시간
401122017-02-208진례 하수처리장역세펌프M-101B0
262017-02-092진례 하수처리장역세펌프M-101A0
741252021-01-0813진례 하수처리장역세펌프M-101B0
76142017-12-236진례 하수처리장역세펌프M-101A0
669652020-03-165진례 하수처리장역세펌프M-101B0
790322021-08-010진례 하수처리장역세펌프M-101B0
119232018-06-2019진례 하수처리장역세펌프M-101A3
98602018-03-2620진례 하수처리장역세펌프M-101A0
112612018-05-245진례 하수처리장역세펌프M-101A9
861562017-11-0720진례 하수처리장약품펌프M-102A0
기준연월일기준시간하수처리장구분명태그설명태그가동시간
355482021-03-014진례 하수처리장역세펌프M-101A0
839172017-08-0613진례 하수처리장약품펌프M-102A0
918752018-07-043진례 하수처리장약품펌프M-102A0
436962017-07-2016진례 하수처리장역세펌프M-101B0
99872018-04-013진례 하수처리장역세펌프M-101A8
327482020-11-0412진례 하수처리장역세펌프M-101A0
695822020-07-036진례 하수처리장역세펌프M-101B4
256732020-01-1417진례 하수처리장역세펌프M-101A0
622732019-09-0217진례 하수처리장역세펌프M-101B0
922702018-07-2014진례 하수처리장약품펌프M-102A0