Overview

Dataset statistics

Number of variables18
Number of observations122
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.5 KiB
Average record size in memory155.1 B

Variable types

Categorical8
Text2
DateTime2
Numeric6

Dataset

Description제주특별자치도 내에 소재하고 있는 중계펌프장과 관련한 데이터로 펌프장명, 위치, 가동년월일, 면적, 배수량, 양수량, 탈취설비유무 등의 정보를 제공합니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15010602/fileData.do

Alerts

우수펌프 구경(밀리미터) has constant value ""Constant
우수펌프 양수량 has constant value ""Constant
배수량및양수량단위 has constant value ""Constant
데이터기준일자 has constant value ""Constant
청천시 계획시간대최대배수량 is highly overall correlated with 강우시 계획시간대최대배수량 and 4 other fieldsHigh correlation
강우시 계획시간대최대배수량 is highly overall correlated with 청천시 계획시간대최대배수량 and 4 other fieldsHigh correlation
우수량 계획시간대최대배수량 is highly overall correlated with 청천시 계획시간대최대배수량 and 4 other fieldsHigh correlation
오수펌프 구경(밀리미터) is highly overall correlated with 청천시 계획시간대최대배수량 and 4 other fieldsHigh correlation
오수펌프 양수량 is highly overall correlated with 청천시 계획시간대최대배수량 and 3 other fieldsHigh correlation
지역구분 is highly overall correlated with 오수펌프 대수High correlation
오수펌프 대수 is highly overall correlated with 청천시 계획시간대최대배수량 and 4 other fieldsHigh correlation
우수펌프 대수 is highly imbalanced (87.9%)Imbalance
펌프장명(합류식) has unique valuesUnique
위치 has unique valuesUnique
계획배수 면적(제곱킬로미터) has 95 (77.9%) zerosZeros
우수량 계획시간대최대배수량 has 20 (16.4%) zerosZeros
오수펌프 구경(밀리미터) has 10 (8.2%) zerosZeros
오수펌프 양수량 has 10 (8.2%) zerosZeros

Reproduction

Analysis started2023-12-12 09:08:49.934642
Analysis finished2023-12-12 09:08:55.692075
Duration5.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역구분
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
서귀포시동지역
24 
성산읍
17 
제주시동지역
15 
구좌읍
11 
대정읍
11 
Other values (7)
44 

Length

Max length7
Median length3
Mean length4.1557377
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서귀포시동지역 24
19.7%
성산읍 17
13.9%
제주시동지역 15
12.3%
구좌읍 11
9.0%
대정읍 11
9.0%
애월읍 9
 
7.4%
한림읍 8
 
6.6%
한경면 8
 
6.6%
남원읍 6
 
4.9%
조천읍 5
 
4.1%
Other values (2) 8
 
6.6%

Length

2023-12-12T18:08:55.804626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서귀포시동지역 24
19.7%
성산읍 17
13.9%
제주시동지역 15
12.3%
구좌읍 11
9.0%
대정읍 11
9.0%
애월읍 9
 
7.4%
한림읍 8
 
6.6%
한경면 8
 
6.6%
남원읍 6
 
4.9%
조천읍 5
 
4.1%
Other values (2) 8
 
6.6%

펌프장명(합류식)
Text

UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T18:08:56.238606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.6557377
Min length2

Characters and Unicode

Total characters324
Distinct characters112
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)100.0%

Sample

1st row병문
2nd row화북
3rd row도두
4th row삼양2
5th row외도
ValueCountFrequency (%)
병문 1
 
0.8%
대정10 1
 
0.8%
대정6 1
 
0.8%
대정4-2 1
 
0.8%
대정4-1 1
 
0.8%
대정4 1
 
0.8%
대정3 1
 
0.8%
대정2 1
 
0.8%
대정1 1
 
0.8%
대정9 1
 
0.8%
Other values (112) 112
91.8%
2023-12-12T18:08:56.851791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
 
6.2%
2 15
 
4.6%
대 15
 
4.6%
정 14
 
4.3%
신 10
 
3.1%
산 8
 
2.5%
성 8
 
2.5%
4 7
 
2.2%
원 7
 
2.2%
포 6
 
1.9%
Other values (102) 214
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 258
79.6%
Decimal Number 61
 
18.8%
Dash Punctuation 3
 
0.9%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 15
 
5.8%
정 14
 
5.4%
신 10
 
3.9%
산 8
 
3.1%
성 8
 
3.1%
원 7
 
2.7%
포 6
 
2.3%
남 6
 
2.3%
덕 6
 
2.3%
조 5
 
1.9%
Other values (90) 173
67.1%
Decimal Number
ValueCountFrequency (%)
1 20
32.8%
2 15
24.6%
4 7
 
11.5%
5 5
 
8.2%
3 5
 
8.2%
7 3
 
4.9%
9 2
 
3.3%
0 2
 
3.3%
6 2
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 258
79.6%
Common 66
 
20.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 15
 
5.8%
정 14
 
5.4%
신 10
 
3.9%
산 8
 
3.1%
성 8
 
3.1%
원 7
 
2.7%
포 6
 
2.3%
남 6
 
2.3%
덕 6
 
2.3%
조 5
 
1.9%
Other values (90) 173
67.1%
Common
ValueCountFrequency (%)
1 20
30.3%
2 15
22.7%
4 7
 
10.6%
5 5
 
7.6%
3 5
 
7.6%
7 3
 
4.5%
- 3
 
4.5%
9 2
 
3.0%
0 2
 
3.0%
6 2
 
3.0%
Other values (2) 2
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 258
79.6%
ASCII 66
 
20.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
30.3%
2 15
22.7%
4 7
 
10.6%
5 5
 
7.6%
3 5
 
7.6%
7 3
 
4.5%
- 3
 
4.5%
9 2
 
3.0%
0 2
 
3.0%
6 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
대 15
 
5.8%
정 14
 
5.4%
신 10
 
3.9%
산 8
 
3.1%
성 8
 
3.1%
원 7
 
2.7%
포 6
 
2.3%
남 6
 
2.3%
덕 6
 
2.3%
조 5
 
1.9%
Other values (90) 173
67.1%

위치
Text

UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T18:08:57.320948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length24.245902
Min length17

Characters and Unicode

Total characters2958
Distinct characters123
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 제주시 탑동로 106
2nd row제주특별자치도 제주시 곤을길 3
3rd row제주특별자치도 제주시 도두항서길 3
4th row제주특별자치도 제주시 설촌로12길 12
5th row제주특별자치도 제주시 통물길 12
ValueCountFrequency (%)
제주특별자치도 121
21.2%
서귀포시 66
 
11.6%
제주시 56
 
9.8%
성산읍 17
 
3.0%
대정읍 12
 
2.1%
구좌읍 11
 
1.9%
애월읍 9
 
1.6%
한경면 8
 
1.4%
한림읍 8
 
1.4%
남원읍 7
 
1.2%
Other values (202) 256
44.8%
2023-12-12T18:08:57.830706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
450
 
15.2%
제 179
 
6.1%
주 178
 
6.0%
도 128
 
4.3%
시 124
 
4.2%
치 122
 
4.1%
자 122
 
4.1%
별 122
 
4.1%
특 122
 
4.1%
1 110
 
3.7%
Other values (113) 1301
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1911
64.6%
Decimal Number 513
 
17.3%
Space Separator 450
 
15.2%
Dash Punctuation 84
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 179
 
9.4%
주 178
 
9.3%
도 128
 
6.7%
시 124
 
6.5%
치 122
 
6.4%
자 122
 
6.4%
별 122
 
6.4%
특 122
 
6.4%
리 83
 
4.3%
귀 77
 
4.0%
Other values (101) 654
34.2%
Decimal Number
ValueCountFrequency (%)
1 110
21.4%
2 69
13.5%
3 52
10.1%
4 49
9.6%
0 48
9.4%
9 43
 
8.4%
6 42
 
8.2%
5 39
 
7.6%
8 38
 
7.4%
7 23
 
4.5%
Space Separator
ValueCountFrequency (%)
450
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1911
64.6%
Common 1047
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 179
 
9.4%
주 178
 
9.3%
도 128
 
6.7%
시 124
 
6.5%
치 122
 
6.4%
자 122
 
6.4%
별 122
 
6.4%
특 122
 
6.4%
리 83
 
4.3%
귀 77
 
4.0%
Other values (101) 654
34.2%
Common
ValueCountFrequency (%)
450
43.0%
1 110
 
10.5%
- 84
 
8.0%
2 69
 
6.6%
3 52
 
5.0%
4 49
 
4.7%
0 48
 
4.6%
9 43
 
4.1%
6 42
 
4.0%
5 39
 
3.7%
Other values (2) 61
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1911
64.6%
ASCII 1047
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
450
43.0%
1 110
 
10.5%
- 84
 
8.0%
2 69
 
6.6%
3 52
 
5.0%
4 49
 
4.7%
0 48
 
4.6%
9 43
 
4.1%
6 42
 
4.0%
5 39
 
3.7%
Other values (2) 61
 
5.8%
Hangul
ValueCountFrequency (%)
제 179
 
9.4%
주 178
 
9.3%
도 128
 
6.7%
시 124
 
6.5%
치 122
 
6.4%
자 122
 
6.4%
별 122
 
6.4%
특 122
 
6.4%
리 83
 
4.3%
귀 77
 
4.0%
Other values (101) 654
34.2%

가동년월일
Date

Distinct18
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1983-08-01 00:00:00
Maximum2015-04-01 00:00:00
2023-12-12T18:08:57.944238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:58.365068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

계획배수 면적(제곱킬로미터)
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6352459
Minimum0
Maximum12.6
Zeros95
Zeros (%)77.9%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T18:08:58.528208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.635
Maximum12.6
Range12.6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.9763445
Coefficient of variation (CV)3.1111487
Kurtosis21.500404
Mean0.6352459
Median Absolute Deviation (MAD)0
Skewness4.3871373
Sum77.5
Variance3.9059375
MonotonicityNot monotonic
2023-12-12T18:08:58.689236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 95
77.9%
0.7 4
 
3.3%
0.9 2
 
1.6%
3.4 2
 
1.6%
0.2 2
 
1.6%
0.5 1
 
0.8%
4.7 1
 
0.8%
12.3 1
 
0.8%
7.7 1
 
0.8%
12.6 1
 
0.8%
Other values (12) 12
 
9.8%
ValueCountFrequency (%)
0.0 95
77.9%
0.1 1
 
0.8%
0.2 2
 
1.6%
0.3 1
 
0.8%
0.5 1
 
0.8%
0.7 4
 
3.3%
0.8 1
 
0.8%
0.9 2
 
1.6%
1.0 1
 
0.8%
1.3 1
 
0.8%
ValueCountFrequency (%)
12.6 1
0.8%
12.3 1
0.8%
7.7 1
0.8%
5.5 1
0.8%
5.0 1
0.8%
4.8 1
0.8%
4.7 1
0.8%
3.4 2
1.6%
2.9 1
0.8%
2.6 1
0.8%

청천시 계획시간대최대배수량
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)81.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188.22131
Minimum1
Maximum2979
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T18:08:58.849662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.05
Q126.25
median72
Q3194.75
95-th percentile639.65
Maximum2979
Range2978
Interquartile range (IQR)168.5

Descriptive statistics

Standard deviation354.75387
Coefficient of variation (CV)1.8847699
Kurtosis35.853366
Mean188.22131
Median Absolute Deviation (MAD)60
Skewness5.3094284
Sum22963
Variance125850.31
MonotonicityNot monotonic
2023-12-12T18:08:59.035381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 3
 
2.5%
18 3
 
2.5%
60 3
 
2.5%
35 3
 
2.5%
31 2
 
1.6%
2 2
 
1.6%
16 2
 
1.6%
1 2
 
1.6%
27 2
 
1.6%
99 2
 
1.6%
Other values (89) 98
80.3%
ValueCountFrequency (%)
1 2
1.6%
2 2
1.6%
4 3
2.5%
5 1
 
0.8%
6 1
 
0.8%
8 1
 
0.8%
9 1
 
0.8%
10 1
 
0.8%
11 1
 
0.8%
12 2
1.6%
ValueCountFrequency (%)
2979 1
0.8%
1944 1
0.8%
1010 1
0.8%
706 1
0.8%
648 1
0.8%
642 1
0.8%
640 1
0.8%
633 1
0.8%
625 1
0.8%
600 1
0.8%

강우시 계획시간대최대배수량
Real number (ℝ)

HIGH CORRELATION 

Distinct105
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean413.00164
Minimum2
Maximum5316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T18:08:59.193902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile10.05
Q143.25
median183
Q3481.75
95-th percentile1396.8
Maximum5316
Range5314
Interquartile range (IQR)438.5

Descriptive statistics

Standard deviation677.65831
Coefficient of variation (CV)1.6408126
Kurtosis25.271541
Mean413.00164
Median Absolute Deviation (MAD)156.5
Skewness4.3136647
Sum50386.2
Variance459220.78
MonotonicityNot monotonic
2023-12-12T18:08:59.377978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
142.0 4
 
3.3%
6.0 3
 
2.5%
408.0 3
 
2.5%
36.0 2
 
1.6%
65.0 2
 
1.6%
13.0 2
 
1.6%
30.0 2
 
1.6%
57.0 2
 
1.6%
105.0 2
 
1.6%
29.0 2
 
1.6%
Other values (95) 98
80.3%
ValueCountFrequency (%)
2.0 1
 
0.8%
3.0 1
 
0.8%
4.0 1
 
0.8%
6.0 3
2.5%
10.0 1
 
0.8%
11.0 1
 
0.8%
13.0 2
1.6%
14.0 1
 
0.8%
16.0 1
 
0.8%
18.0 1
 
0.8%
ValueCountFrequency (%)
5316.0 1
0.8%
3487.0 1
0.8%
1944.0 1
0.8%
1926.0 1
0.8%
1921.0 1
0.8%
1440.0 1
0.8%
1404.0 1
0.8%
1260.0 1
0.8%
1258.0 1
0.8%
1098.0 1
0.8%

우수량 계획시간대최대배수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct82
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean224.56721
Minimum0
Maximum2337
Zeros20
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T18:08:59.532150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.25
median77
Q3273.75
95-th percentile931.2
Maximum2337
Range2337
Interquartile range (IQR)266.5

Descriptive statistics

Standard deviation361.21236
Coefficient of variation (CV)1.6084822
Kurtosis11.149249
Mean224.56721
Median Absolute Deviation (MAD)77
Skewness2.9373711
Sum27397.2
Variance130474.37
MonotonicityNot monotonic
2023-12-12T18:08:59.720645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 20
 
16.4%
2.0 4
 
3.3%
16.0 3
 
2.5%
73.0 3
 
2.5%
214.0 2
 
1.6%
309.0 2
 
1.6%
1.0 2
 
1.6%
11.0 2
 
1.6%
107.0 2
 
1.6%
18.0 2
 
1.6%
Other values (72) 80
65.6%
ValueCountFrequency (%)
0.0 20
16.4%
1.0 2
 
1.6%
2.0 4
 
3.3%
3.0 2
 
1.6%
5.0 1
 
0.8%
6.0 1
 
0.8%
7.0 1
 
0.8%
8.0 2
 
1.6%
10.0 1
 
0.8%
11.0 2
 
1.6%
ValueCountFrequency (%)
2337.0 1
0.8%
1543.0 1
0.8%
1296.0 1
0.8%
1284.0 1
0.8%
1281.0 1
0.8%
960.0 1
0.8%
936.0 1
0.8%
840.0 1
0.8%
732.0 1
0.8%
696.0 1
0.8%

오수펌프 대수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3
47 
2
39 
4
25 
0
10 
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row5
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
3 47
38.5%
2 39
32.0%
4 25
20.5%
0 10
 
8.2%
5 1
 
0.8%

Length

2023-12-12T18:08:59.864313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:08:59.999537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 47
38.5%
2 39
32.0%
4 25
20.5%
0 10
 
8.2%
5 1
 
0.8%

오수펌프 구경(밀리미터)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean149.43443
Minimum0
Maximum400
Zeros10
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T18:09:00.155657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1100
median150
Q3200
95-th percentile300
Maximum400
Range400
Interquartile range (IQR)100

Descriptive statistics

Standard deviation86.239527
Coefficient of variation (CV)0.57710615
Kurtosis0.16323402
Mean149.43443
Median Absolute Deviation (MAD)50
Skewness0.41425671
Sum18231
Variance7437.256
MonotonicityNot monotonic
2023-12-12T18:09:00.281329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
150 23
18.9%
200 22
18.0%
100 21
17.2%
250 12
9.8%
80 12
9.8%
0 10
8.2%
300 7
 
5.7%
125 7
 
5.7%
32 3
 
2.5%
400 2
 
1.6%
Other values (2) 3
 
2.5%
ValueCountFrequency (%)
0 10
8.2%
32 3
 
2.5%
50 2
 
1.6%
80 12
9.8%
100 21
17.2%
125 7
 
5.7%
150 23
18.9%
200 22
18.0%
250 12
9.8%
300 7
 
5.7%
ValueCountFrequency (%)
400 2
 
1.6%
350 1
 
0.8%
300 7
 
5.7%
250 12
9.8%
200 22
18.0%
150 23
18.9%
125 7
 
5.7%
100 21
17.2%
80 12
9.8%
50 2
 
1.6%

오수펌프 양수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct79
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean216.7377
Minimum0
Maximum1740
Zeros10
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T18:09:00.452358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q138.25
median157.5
Q3285.75
95-th percentile639.65
Maximum1740
Range1740
Interquartile range (IQR)247.5

Descriptive statistics

Standard deviation264.23208
Coefficient of variation (CV)1.219133
Kurtosis14.450811
Mean216.7377
Median Absolute Deviation (MAD)121.5
Skewness3.2028028
Sum26442
Variance69818.592
MonotonicityNot monotonic
2023-12-12T18:09:00.605624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
8.2%
36 6
 
4.9%
60 5
 
4.1%
78 4
 
3.3%
186 3
 
2.5%
216 3
 
2.5%
144 3
 
2.5%
240 3
 
2.5%
6 3
 
2.5%
180 3
 
2.5%
Other values (69) 79
64.8%
ValueCountFrequency (%)
0 10
8.2%
6 3
 
2.5%
13 1
 
0.8%
15 1
 
0.8%
18 2
 
1.6%
24 1
 
0.8%
30 1
 
0.8%
31 2
 
1.6%
32 1
 
0.8%
33 1
 
0.8%
ValueCountFrequency (%)
1740 1
0.8%
1620 1
0.8%
900 1
0.8%
738 1
0.8%
648 1
0.8%
642 1
0.8%
640 1
0.8%
633 1
0.8%
625 1
0.8%
624 1
0.8%

우수펌프 대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
120 
1
 
2

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 (%)
0 120
98.4%
1 2
 
1.6%

Length

2023-12-12T18:09:00.792241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:09:00.893350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 120
98.4%
1 2
 
1.6%

우수펌프 구경(밀리미터)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
122 

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 (%)
0 122
100.0%

Length

2023-12-12T18:09:01.015795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:09:01.158080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 122
100.0%

우수펌프 양수량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
122 

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 (%)
0 122
100.0%

Length

2023-12-12T18:09:01.288159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:09:01.402089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 122
100.0%

탈취설비유무
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
무
95 
유
27 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row무
2nd row유
3rd row무
4th row무
5th row무

Common Values

ValueCountFrequency (%)
무 95
77.9%
유 27
 
22.1%

Length

2023-12-12T18:09:01.538621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:09:01.673061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 95
77.9%
유 27
 
22.1%

자가발전유무
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
무
103 
유
19 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
무 103
84.4%
유 19
 
15.6%

Length

2023-12-12T18:09:01.810514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:09:01.952658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 103
84.4%
유 19
 
15.6%

배수량및양수량단위
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
㎥/hr
122 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row㎥/hr
2nd row㎥/hr
3rd row㎥/hr
4th row㎥/hr
5th row㎥/hr

Common Values

ValueCountFrequency (%)
㎥/hr 122
100.0%

Length

2023-12-12T18:09:02.094109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:09:02.199162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
㎥/hr 122
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-02-20 00:00:00
Maximum2023-02-20 00:00:00
2023-12-12T18:09:02.287083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:09:02.439969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T18:08:54.442934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:50.692667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:51.375920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:52.107876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:52.907451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:53.633035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:54.561766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:50.786411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:51.498580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:52.257021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:53.039523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:53.763616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:54.663851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:50.899247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:51.628676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:52.399182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:53.159207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:53.895468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:54.784957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:51.012140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:51.722162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:52.516896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:53.273670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:54.017563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:54.904627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:51.127528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:51.837718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:52.631228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:53.376606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:54.141046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:55.027778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:51.263499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:51.977789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:52.771091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:53.487201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:08:54.289384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:09:02.586714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역구분가동년월일계획배수 면적(제곱킬로미터)청천시 계획시간대최대배수량강우시 계획시간대최대배수량우수량 계획시간대최대배수량오수펌프 대수오수펌프 구경(밀리미터)오수펌프 양수량우수펌프 대수탈취설비유무자가발전유무
지역구분1.0000.8690.3970.5360.6580.7310.7450.7050.4640.3770.5470.499
가동년월일0.8691.0000.3150.5930.5290.4170.6230.6430.7420.0000.7070.696
계획배수 면적(제곱킬로미터)0.3970.3151.0000.6200.0000.0000.0000.1880.6930.0000.4440.338
청천시 계획시간대최대배수량0.5360.5930.6201.0000.9770.8840.7310.8690.7960.0000.2150.604
강우시 계획시간대최대배수량0.6580.5290.0000.9771.0000.9670.7330.8900.7680.0000.1910.474
우수량 계획시간대최대배수량0.7310.4170.0000.8840.9671.0000.7660.8310.7310.0000.2840.330
오수펌프 대수0.7450.6230.0000.7310.7330.7661.0000.8410.6570.0000.1650.232
오수펌프 구경(밀리미터)0.7050.6430.1880.8690.8900.8310.8411.0000.6770.0000.2810.416
오수펌프 양수량0.4640.7420.6930.7960.7680.7310.6570.6771.0000.0000.2660.462
우수펌프 대수0.3770.0000.0000.0000.0000.0000.0000.0000.0001.0000.2150.000
탈취설비유무0.5470.7070.4440.2150.1910.2840.1650.2810.2660.2151.0000.418
자가발전유무0.4990.6960.3380.6040.4740.3300.2320.4160.4620.0000.4181.000
2023-12-12T18:09:02.774150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자가발전유무탈취설비유무우수펌프 대수지역구분오수펌프 대수
자가발전유무1.0000.2750.0000.3720.280
탈취설비유무0.2751.0000.1380.4080.199
우수펌프 대수0.0000.1381.0000.2790.000
지역구분0.3720.4080.2791.0000.517
오수펌프 대수0.2800.1990.0000.5171.000
2023-12-12T18:09:02.903913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계획배수 면적(제곱킬로미터)청천시 계획시간대최대배수량강우시 계획시간대최대배수량우수량 계획시간대최대배수량오수펌프 구경(밀리미터)오수펌프 양수량지역구분오수펌프 대수우수펌프 대수탈취설비유무자가발전유무
계획배수 면적(제곱킬로미터)1.0000.1830.009-0.3810.0810.2070.1990.0000.0000.4660.354
청천시 계획시간대최대배수량0.1831.0000.9470.6020.8900.8660.2310.5980.0000.1510.431
강우시 계획시간대최대배수량0.0090.9471.0000.7950.9030.8690.3090.6000.0000.1340.336
우수량 계획시간대최대배수량-0.3810.6020.7951.0000.6750.6310.4070.6020.0000.2070.241
오수펌프 구경(밀리미터)0.0810.8900.9030.6751.0000.9010.4050.6750.0000.2730.404
오수펌프 양수량0.2070.8660.8690.6310.9011.0000.2400.4950.0000.2780.484
지역구분0.1990.2310.3090.4070.4050.2401.0000.5170.2790.4080.372
오수펌프 대수0.0000.5980.6000.6020.6750.4950.5171.0000.0000.1990.280
우수펌프 대수0.0000.0000.0000.0000.0000.0000.2790.0001.0000.1380.000
탈취설비유무0.4660.1510.1340.2070.2730.2780.4080.1990.1381.0000.275
자가발전유무0.3540.4310.3360.2410.4040.4840.3720.2800.0000.2751.000

Missing values

2023-12-12T18:08:55.229876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:08:55.571697image/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

지역구분펌프장명(합류식)위치가동년월일계획배수 면적(제곱킬로미터)청천시 계획시간대최대배수량강우시 계획시간대최대배수량우수량 계획시간대최대배수량오수펌프 대수오수펌프 구경(밀리미터)오수펌프 양수량우수펌프 대수우수펌프 구경(밀리미터)우수펌프 양수량탈취설비유무자가발전유무배수량및양수량단위데이터기준일자
0제주시동지역병문제주특별자치도 제주시 탑동로 1061993-12-310.029795316.02337.054001740000무유㎥/hr2023-02-20
1제주시동지역화북제주특별자치도 제주시 곤을길 31993-12-310.019443487.01543.04350624000유유㎥/hr2023-02-20
2제주시동지역도두제주특별자치도 제주시 도두항서길 31999-12-270.0436783.0347.04300900000무유㎥/hr2023-02-20
3제주시동지역삼양2제주특별자치도 제주시 설촌로12길 121999-12-270.07061258.0552.04250420000무유㎥/hr2023-02-20
4제주시동지역외도제주특별자치도 제주시 통물길 121999-12-270.0194346.0152.04200116000무유㎥/hr2023-02-20
5제주시동지역용담제주특별자치도 제주시 서해안로 6041993-12-310.093166.073.0320078000무유㎥/hr2023-02-20
6제주시동지역이호1제주특별자치도 제주시 이호2동 1613-11999-12-270.0436532.096.0215036000무무㎥/hr2023-02-20
7제주시동지역이호2제주특별자치도 제주시 서해안로 991999-12-270.0911.02.0210036000무무㎥/hr2023-02-20
8제주시동지역현사제주특별자치도 제주시 이호1동 1781-31999-12-270.0810.02.0210036000무무㎥/hr2023-02-20
9제주시동지역내도제주특별자치도 제주시 테우해안로 31999-12-270.01013.03.0210036000무무㎥/hr2023-02-20
지역구분펌프장명(합류식)위치가동년월일계획배수 면적(제곱킬로미터)청천시 계획시간대최대배수량강우시 계획시간대최대배수량우수량 계획시간대최대배수량오수펌프 대수오수펌프 구경(밀리미터)오수펌프 양수량우수펌프 대수우수펌프 구경(밀리미터)우수펌프 양수량탈취설비유무자가발전유무배수량및양수량단위데이터기준일자
112성산읍성산2제주특별자치도 서귀포시 성산읍 성산리 234-292005-04-010.035143.0108.0310093000유무㎥/hr2023-02-20
113성산읍성산5제주특별자치도 서귀포시 성산읍 고성리 352-72005-04-010.01457.043.0210039000무무㎥/hr2023-02-20
114성산읍시흥1제주특별자치도 서귀포시 성산읍 시흥리 1008-22005-04-010.026.05.03326000무무㎥/hr2023-02-20
115성산읍시흥4제주특별자치도 서귀포시 성산읍 시흥리 980-342005-04-010.01665.049.0210042000무무㎥/hr2023-02-20
116성산읍고성1제주특별자치도 서귀포시 성산읍 고성리 1152-62005-04-010.0518.013.02326000무무㎥/hr2023-02-20
117성산읍고성2제주특별자치도 서귀포시 성산읍 고성리 1138-12005-04-010.02698.073.0210060000유무㎥/hr2023-02-20
118성산읍오조1제주특별자치도 서귀포시 성산읍 오조리 90-232005-04-010.01457.043.0210078000무무㎥/hr2023-02-20
119성산읍오조2제주특별자치도 서귀포시 성산읍 오조리 2582005-04-010.0416.012.033260000무무㎥/hr2023-02-20
120성산읍오조4제주특별자치도 서귀포시 성산읍 오조리 2-12005-04-010.01554.039.035015000무무㎥/hr2023-02-20
121성산읍오조3제주특별자치도 서귀포시 성산읍 오조리 8702006-09-090.01554.039.028018000무무㎥/hr2023-02-20