Overview

Dataset statistics

Number of variables12
Number of observations28
Missing cells30
Missing cells (%)8.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory103.7 B

Variable types

Numeric2
Text7
Categorical2
Unsupported1

Dataset

Description경상남도 밀양시 재난대응용 배수펌프장 현황입니다.
Author경상남도 밀양시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15021520

Alerts

설치목적 has constant value ""Constant
연번 is highly overall correlated with 한전 전원공급방식(1회선 또는 2회선)High correlation
한전 전원공급방식(1회선 또는 2회선) is highly overall correlated with 연번High correlation
한전 전원공급방식(1회선 또는 2회선) is highly imbalanced (62.9%)Imbalance
엔진 펌프규모(kW(HP) X 대) has 28 (100.0%) missing valuesMissing
비상발전기(kW(HP) X대) has 2 (7.1%) missing valuesMissing
연번 has unique valuesUnique
펌프장명 has unique valuesUnique
주소 has unique valuesUnique
사용전력량(kWH)/년 (최대/최소, 고압/저압) has unique valuesUnique
전기요금(원)/년 (최대/최소, 고압/저압) has unique valuesUnique
엔진 펌프규모(kW(HP) X 대) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 23:51:51.024393
Analysis finished2023-12-10 23:51:52.236189
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-11T08:51:52.326837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.35
Q17.75
median14.5
Q321.25
95-th percentile26.65
Maximum28
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.2259751
Coefficient of variation (CV)0.56730863
Kurtosis-1.2
Mean14.5
Median Absolute Deviation (MAD)7
Skewness0
Sum406
Variance67.666667
MonotonicityStrictly increasing
2023-12-11T08:51:52.486184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 1
 
3.6%
16 1
 
3.6%
28 1
 
3.6%
27 1
 
3.6%
26 1
 
3.6%
25 1
 
3.6%
24 1
 
3.6%
23 1
 
3.6%
22 1
 
3.6%
21 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1 1
3.6%
2 1
3.6%
3 1
3.6%
4 1
3.6%
5 1
3.6%
6 1
3.6%
7 1
3.6%
8 1
3.6%
9 1
3.6%
10 1
3.6%
ValueCountFrequency (%)
28 1
3.6%
27 1
3.6%
26 1
3.6%
25 1
3.6%
24 1
3.6%
23 1
3.6%
22 1
3.6%
21 1
3.6%
20 1
3.6%
19 1
3.6%

펌프장명
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T08:51:52.709360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9642857
Min length2

Characters and Unicode

Total characters83
Distinct characters47
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row삼랑진
2nd row심검세
3rd row구검세
4th row외 송
5th row낙 동
ValueCountFrequency (%)
부 3
 
6.7%
은 2
 
4.4%
동 2
 
4.4%
서 2
 
4.4%
어 1
 
2.2%
산 1
 
2.2%
안 1
 
2.2%
태 1
 
2.2%
칠인전 1
 
2.2%
사 1
 
2.2%
Other values (30) 30
66.7%
2023-12-11T08:51:53.090732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
20.5%
삼 3
 
3.6%
곡 3
 
3.6%
덕 3
 
3.6%
성 3
 
3.6%
2 3
 
3.6%
부 3
 
3.6%
은 2
 
2.4%
가 2
 
2.4%
문 2
 
2.4%
Other values (37) 42
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61
73.5%
Space Separator 17
 
20.5%
Decimal Number 5
 
6.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
삼 3
 
4.9%
곡 3
 
4.9%
덕 3
 
4.9%
성 3
 
4.9%
부 3
 
4.9%
은 2
 
3.3%
가 2
 
3.3%
문 2
 
3.3%
서 2
 
3.3%
검 2
 
3.3%
Other values (34) 36
59.0%
Decimal Number
ValueCountFrequency (%)
2 3
60.0%
1 2
40.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61
73.5%
Common 22
 
26.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
삼 3
 
4.9%
곡 3
 
4.9%
덕 3
 
4.9%
성 3
 
4.9%
부 3
 
4.9%
은 2
 
3.3%
가 2
 
3.3%
문 2
 
3.3%
서 2
 
3.3%
검 2
 
3.3%
Other values (34) 36
59.0%
Common
ValueCountFrequency (%)
17
77.3%
2 3
 
13.6%
1 2
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61
73.5%
ASCII 22
 
26.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
77.3%
2 3
 
13.6%
1 2
 
9.1%
Hangul
ValueCountFrequency (%)
삼 3
 
4.9%
곡 3
 
4.9%
덕 3
 
4.9%
성 3
 
4.9%
부 3
 
4.9%
은 2
 
3.3%
가 2
 
3.3%
문 2
 
3.3%
서 2
 
3.3%
검 2
 
3.3%
Other values (34) 36
59.0%

주소
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T08:51:53.316259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length16.428571
Min length12

Characters and Unicode

Total characters460
Distinct characters55
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

Unique28 ?
Unique (%)100.0%

Sample

1st row밀양시 삼랑진읍 검세리 658-2
2nd row밀양시 삼랑진읍 검세리 634-13
3rd row밀양시 삼랑진읍 검세리 633-9
4th row밀양시 삼랑진읍 송지리 143-10
5th row밀양시 삼랑진읍 삼랑리 58-5
ValueCountFrequency (%)
밀양시 28
26.7%
삼랑진읍 9
 
8.6%
무안면 6
 
5.7%
검세리 4
 
3.8%
송지리 3
 
2.9%
성덕리 3
 
2.9%
무안리 2
 
1.9%
가곡동 2
 
1.9%
삼문동 2
 
1.9%
외산리 2
 
1.9%
Other values (44) 44
41.9%
2023-12-11T08:51:53.654910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
 
16.7%
밀 28
 
6.1%
양 28
 
6.1%
시 28
 
6.1%
- 24
 
5.2%
리 22
 
4.8%
1 18
 
3.9%
6 14
 
3.0%
2 14
 
3.0%
8 13
 
2.8%
Other values (45) 194
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
52.8%
Decimal Number 116
25.2%
Space Separator 77
 
16.7%
Dash Punctuation 24
 
5.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
밀 28
 
11.5%
양 28
 
11.5%
시 28
 
11.5%
리 22
 
9.1%
삼 12
 
4.9%
면 11
 
4.5%
읍 10
 
4.1%
안 10
 
4.1%
랑 10
 
4.1%
무 10
 
4.1%
Other values (33) 74
30.5%
Decimal Number
ValueCountFrequency (%)
1 18
15.5%
6 14
12.1%
2 14
12.1%
8 13
11.2%
4 11
9.5%
5 11
9.5%
7 10
8.6%
3 10
8.6%
0 9
7.8%
9 6
 
5.2%
Space Separator
ValueCountFrequency (%)
77
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
52.8%
Common 217
47.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
밀 28
 
11.5%
양 28
 
11.5%
시 28
 
11.5%
리 22
 
9.1%
삼 12
 
4.9%
면 11
 
4.5%
읍 10
 
4.1%
안 10
 
4.1%
랑 10
 
4.1%
무 10
 
4.1%
Other values (33) 74
30.5%
Common
ValueCountFrequency (%)
77
35.5%
- 24
 
11.1%
1 18
 
8.3%
6 14
 
6.5%
2 14
 
6.5%
8 13
 
6.0%
4 11
 
5.1%
5 11
 
5.1%
7 10
 
4.6%
3 10
 
4.6%
Other values (2) 15
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
52.8%
ASCII 217
47.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
35.5%
- 24
 
11.1%
1 18
 
8.3%
6 14
 
6.5%
2 14
 
6.5%
8 13
 
6.0%
4 11
 
5.1%
5 11
 
5.1%
7 10
 
4.6%
3 10
 
4.6%
Other values (2) 15
 
6.9%
Hangul
ValueCountFrequency (%)
밀 28
 
11.5%
양 28
 
11.5%
시 28
 
11.5%
리 22
 
9.1%
삼 12
 
4.9%
면 11
 
4.5%
읍 10
 
4.1%
안 10
 
4.1%
랑 10
 
4.1%
무 10
 
4.1%
Other values (33) 74
30.5%

설치년도
Real number (ℝ)

Distinct16
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1999.2857
Minimum1981
Maximum2014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-11T08:51:53.794301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1981
5-th percentile1981
Q11992.5
median2002.5
Q32004
95-th percentile2010.6
Maximum2014
Range33
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation8.9602296
Coefficient of variation (CV)0.0044817154
Kurtosis-0.064074642
Mean1999.2857
Median Absolute Deviation (MAD)3
Skewness-0.80953756
Sum55980
Variance80.285714
MonotonicityNot monotonic
2023-12-11T08:51:53.901420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2003 4
14.3%
2004 4
14.3%
1981 3
10.7%
2002 3
10.7%
1989 2
 
7.1%
2000 2
 
7.1%
1999 1
 
3.6%
2005 1
 
3.6%
1991 1
 
3.6%
2008 1
 
3.6%
Other values (6) 6
21.4%
ValueCountFrequency (%)
1981 3
10.7%
1989 2
7.1%
1990 1
 
3.6%
1991 1
 
3.6%
1993 1
 
3.6%
1999 1
 
3.6%
2000 2
7.1%
2002 3
10.7%
2003 4
14.3%
2004 4
14.3%
ValueCountFrequency (%)
2014 1
 
3.6%
2012 1
 
3.6%
2008 1
 
3.6%
2007 1
 
3.6%
2006 1
 
3.6%
2005 1
 
3.6%
2004 4
14.3%
2003 4
14.3%
2002 3
10.7%
2000 2
7.1%

설치목적
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
내수배제
28 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
내수배제 28
100.0%

Length

2023-12-11T08:51:54.044274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:51:54.128829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
내수배제 28
100.0%

모터 펌프규모(kW(HP) X 대)
Text

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T08:51:54.275025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length11.607143
Min length8

Characters and Unicode

Total characters325
Distinct characters15
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)53.6%

Sample

1st row500(650)X2
2nd row500(650)X3
3rd row400(550)X3
4th row150(200)X2
5th row150(200)X2
ValueCountFrequency (%)
150(200)x2 5
14.7%
75(100)x2 5
14.7%
55(75)x2 4
11.8%
75(100)x1 3
 
8.8%
55(75)x1 3
 
8.8%
38(50)x1 1
 
2.9%
500(650)x2 1
 
2.9%
115(150)x2 1
 
2.9%
225(300)x1 1
 
2.9%
95(125)x2 1
 
2.9%
Other values (9) 9
26.5%
2023-12-11T08:51:54.634762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 58
17.8%
0 54
16.6%
1 38
11.7%
( 34
10.5%
) 34
10.5%
X 34
10.5%
2 30
9.2%
7 15
 
4.6%
3 8
 
2.5%
, 6
 
1.8%
Other values (5) 14
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 211
64.9%
Open Punctuation 34
 
10.5%
Close Punctuation 34
 
10.5%
Uppercase Letter 34
 
10.5%
Other Punctuation 6
 
1.8%
Space Separator 6
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 58
27.5%
0 54
25.6%
1 38
18.0%
2 30
14.2%
7 15
 
7.1%
3 8
 
3.8%
4 4
 
1.9%
6 2
 
0.9%
8 1
 
0.5%
9 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 34
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 291
89.5%
Latin 34
 
10.5%

Most frequent character per script

Common
ValueCountFrequency (%)
5 58
19.9%
0 54
18.6%
1 38
13.1%
( 34
11.7%
) 34
11.7%
2 30
10.3%
7 15
 
5.2%
3 8
 
2.7%
, 6
 
2.1%
6
 
2.1%
Other values (4) 8
 
2.7%
Latin
ValueCountFrequency (%)
X 34
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 58
17.8%
0 54
16.6%
1 38
11.7%
( 34
10.5%
) 34
10.5%
X 34
10.5%
2 30
9.2%
7 15
 
4.6%
3 8
 
2.5%
, 6
 
1.8%
Other values (5) 14
 
4.3%

엔진 펌프규모(kW(HP) X 대)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

한전 전원공급방식(1회선 또는 2회선)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
1회선
26 
2회선
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2회선
2nd row2회선
3rd row1회선
4th row1회선
5th row1회선

Common Values

ValueCountFrequency (%)
1회선 26
92.9%
2회선 2
 
7.1%

Length

2023-12-11T08:51:54.786165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:51:54.897470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1회선 26
92.9%
2회선 2
 
7.1%

비상발전기(kW(HP) X대)
Text

MISSING 

Distinct18
Distinct (%)69.2%
Missing2
Missing (%)7.1%
Memory size356.0 B
2023-12-11T08:51:55.059601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length9.5384615
Min length1

Characters and Unicode

Total characters248
Distinct characters15
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)53.8%

Sample

1st row800(1,050)X2
2nd row375(500)X1
3rd row260(350)X1
4th row400(550)X1
5th row125(170)X1
ValueCountFrequency (%)
400(550)x1 5
19.2%
200(270)x1 3
 
11.5%
291(400)x1 2
 
7.7%
2
 
7.7%
1,364(1,800)x1 1
 
3.8%
155(200)x1 1
 
3.8%
455(600)x1 1
 
3.8%
250(330)x1 1
 
3.8%
273(350)x1 1
 
3.8%
360(480)x1 1
 
3.8%
Other values (8) 8
30.8%
2023-12-11T08:51:55.373443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 56
22.6%
1 30
12.1%
5 27
10.9%
( 24
9.7%
) 24
9.7%
X 24
9.7%
2 15
 
6.0%
4 14
 
5.6%
3 9
 
3.6%
7 7
 
2.8%
Other values (5) 18
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 171
69.0%
Open Punctuation 24
 
9.7%
Close Punctuation 24
 
9.7%
Uppercase Letter 24
 
9.7%
Other Punctuation 3
 
1.2%
Dash Punctuation 2
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 56
32.7%
1 30
17.5%
5 27
15.8%
2 15
 
8.8%
4 14
 
8.2%
3 9
 
5.3%
7 7
 
4.1%
6 7
 
4.1%
9 3
 
1.8%
8 3
 
1.8%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 224
90.3%
Latin 24
 
9.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 56
25.0%
1 30
13.4%
5 27
12.1%
( 24
10.7%
) 24
10.7%
2 15
 
6.7%
4 14
 
6.2%
3 9
 
4.0%
7 7
 
3.1%
6 7
 
3.1%
Other values (4) 11
 
4.9%
Latin
ValueCountFrequency (%)
X 24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 56
22.6%
1 30
12.1%
5 27
10.9%
( 24
9.7%
) 24
9.7%
X 24
9.7%
2 15
 
6.0%
4 14
 
5.6%
3 9
 
3.6%
7 7
 
2.8%
Other values (5) 18
 
7.3%

한전 계약전력(kW, 고압/저압)
Text

Distinct17
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T08:51:55.574208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length7.2142857
Min length6

Characters and Unicode

Total characters202
Distinct characters14
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

Unique12 ?
Unique (%)42.9%

Sample

1st row1,300(고압)
2nd row2,150(고압)
3rd row1,500(고압)
4th row500(고압)
5th row99(저압)
ValueCountFrequency (%)
250(고압 5
17.9%
500(고압 4
14.3%
350(고압 3
10.7%
55(저압 2
 
7.1%
400(고압 2
 
7.1%
300(고압 1
 
3.6%
1,300(고압 1
 
3.6%
150(고압 1
 
3.6%
200(고압 1
 
3.6%
550(고압 1
 
3.6%
Other values (7) 7
25.0%
2023-12-11T08:51:55.853960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 39
19.3%
( 28
13.9%
압 28
13.9%
) 28
13.9%
고 25
12.4%
5 22
10.9%
2 7
 
3.5%
1 6
 
3.0%
3 5
 
2.5%
, 5
 
2.5%
Other values (4) 9
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 85
42.1%
Other Letter 56
27.7%
Open Punctuation 28
 
13.9%
Close Punctuation 28
 
13.9%
Other Punctuation 5
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 39
45.9%
5 22
25.9%
2 7
 
8.2%
1 6
 
7.1%
3 5
 
5.9%
4 3
 
3.5%
9 2
 
2.4%
8 1
 
1.2%
Other Letter
ValueCountFrequency (%)
압 28
50.0%
고 25
44.6%
저 3
 
5.4%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 146
72.3%
Hangul 56
 
27.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 39
26.7%
( 28
19.2%
) 28
19.2%
5 22
15.1%
2 7
 
4.8%
1 6
 
4.1%
3 5
 
3.4%
, 5
 
3.4%
4 3
 
2.1%
9 2
 
1.4%
Hangul
ValueCountFrequency (%)
압 28
50.0%
고 25
44.6%
저 3
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 146
72.3%
Hangul 56
 
27.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 39
26.7%
( 28
19.2%
) 28
19.2%
5 22
15.1%
2 7
 
4.8%
1 6
 
4.1%
3 5
 
3.4%
, 5
 
3.4%
4 3
 
2.1%
9 2
 
1.4%
Hangul
ValueCountFrequency (%)
압 28
50.0%
고 25
44.6%
저 3
 
5.4%

사용전력량(kWH)/년 (최대/최소, 고압/저압)
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T08:51:56.053248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15.5
Mean length14.214286
Min length9

Characters and Unicode

Total characters398
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row21,859(6,019/0)
2nd row46,818(12,258/0)
3rd row29,484(8,652/0)
4th row22,256(4,421/0)
5th row796(248/0)
ValueCountFrequency (%)
21,859(6,019/0 1
 
3.6%
46,818(12,258/0 1
 
3.6%
11,736(2,688/0 1
 
3.6%
4,203(1,218/0 1
 
3.6%
16,207(4,432/0 1
 
3.6%
50,693(17,155/0 1
 
3.6%
27,506(8,611/0 1
 
3.6%
21,800(4,159/0 1
 
3.6%
9,463(1,589/0 1
 
3.6%
13,150(3,380/0 1
 
3.6%
Other values (18) 18
64.3%
2023-12-11T08:51:56.369747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 49
12.3%
0 49
12.3%
1 45
11.3%
2 32
8.0%
( 28
 
7.0%
/ 28
 
7.0%
) 28
 
7.0%
5 23
 
5.8%
8 22
 
5.5%
4 21
 
5.3%
Other values (4) 73
18.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 265
66.6%
Other Punctuation 77
 
19.3%
Open Punctuation 28
 
7.0%
Close Punctuation 28
 
7.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
18.5%
1 45
17.0%
2 32
12.1%
5 23
8.7%
8 22
8.3%
4 21
7.9%
3 20
7.5%
9 19
 
7.2%
6 19
 
7.2%
7 15
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 49
63.6%
/ 28
36.4%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 398
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 49
12.3%
0 49
12.3%
1 45
11.3%
2 32
8.0%
( 28
 
7.0%
/ 28
 
7.0%
) 28
 
7.0%
5 23
 
5.8%
8 22
 
5.5%
4 21
 
5.3%
Other values (4) 73
18.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 398
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 49
12.3%
0 49
12.3%
1 45
11.3%
2 32
8.0%
( 28
 
7.0%
/ 28
 
7.0%
) 28
 
7.0%
5 23
 
5.8%
8 22
 
5.5%
4 21
 
5.3%
Other values (4) 73
18.3%

전기요금(원)/년 (최대/최소, 고압/저압)
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T08:51:56.558199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length19.285714
Min length17

Characters and Unicode

Total characters540
Distinct characters15
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row1,554,390(334,180/0)
2nd row3,468,430(759,970/0)
3rd row1,816,820(393,460/0)
4th row3,675,350(864,790/0)
5th row811,380(181,190/0)
ValueCountFrequency (%)
1,554,390(334,180/0 1
 
3.6%
3,468,430(759,970/0 1
 
3.6%
814,510(166,630/0 1
 
3.6%
350,280(82,650/0 1
 
3.6%
1,072,160(227,380/0 1
 
3.6%
2,042,300(524,910/0 1
 
3.6%
1,016,300(259,320/0 1
 
3.6%
919,880(156,290/0 1
 
3.6%
445,580(70,630/0 1
 
3.6%
783,240(180,820/0 1
 
3.6%
Other values (18) 18
64.3%
2023-12-11T08:51:56.874914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 106
19.6%
, 74
13.7%
1 38
 
7.0%
3 33
 
6.1%
8 32
 
5.9%
5 31
 
5.7%
4 31
 
5.7%
2 30
 
5.6%
7 29
 
5.4%
( 28
 
5.2%
Other values (5) 108
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 381
70.6%
Other Punctuation 103
 
19.1%
Open Punctuation 28
 
5.2%
Close Punctuation 28
 
5.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 106
27.8%
1 38
 
10.0%
3 33
 
8.7%
8 32
 
8.4%
5 31
 
8.1%
4 31
 
8.1%
2 30
 
7.9%
7 29
 
7.6%
6 28
 
7.3%
9 23
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 74
71.8%
/ 28
 
27.2%
. 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 540
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 106
19.6%
, 74
13.7%
1 38
 
7.0%
3 33
 
6.1%
8 32
 
5.9%
5 31
 
5.7%
4 31
 
5.7%
2 30
 
5.6%
7 29
 
5.4%
( 28
 
5.2%
Other values (5) 108
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 540
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 106
19.6%
, 74
13.7%
1 38
 
7.0%
3 33
 
6.1%
8 32
 
5.9%
5 31
 
5.7%
4 31
 
5.7%
2 30
 
5.6%
7 29
 
5.4%
( 28
 
5.2%
Other values (5) 108
20.0%

Interactions

2023-12-11T08:51:51.662957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:51:51.456490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:51:51.769279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:51:51.563857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:51:57.287341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번펌프장명주소설치년도모터 펌프규모(kW(HP) X 대)한전 전원공급방식(1회선 또는 2회선)비상발전기(kW(HP) X대)한전 계약전력(kW, 고압/저압)사용전력량(kWH)/년 (최대/최소, 고압/저압)전기요금(원)/년 (최대/최소, 고압/저압)
연번1.0001.0001.0000.4240.7380.8540.8450.7611.0001.000
펌프장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설치년도0.4241.0001.0001.0000.5280.0000.8620.6431.0001.000
모터 펌프규모(kW(HP) X 대)0.7381.0001.0000.5281.0001.0000.3180.9301.0001.000
한전 전원공급방식(1회선 또는 2회선)0.8541.0001.0000.0001.0001.000NaN1.0001.0001.000
비상발전기(kW(HP) X대)0.8451.0001.0000.8620.318NaN1.0000.8991.0001.000
한전 계약전력(kW, 고압/저압)0.7611.0001.0000.6430.9301.0000.8991.0001.0001.000
사용전력량(kWH)/년 (최대/최소, 고압/저압)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전기요금(원)/년 (최대/최소, 고압/저압)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-11T08:51:57.419984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치년도한전 전원공급방식(1회선 또는 2회선)
연번1.0000.3020.565
설치년도0.3021.0000.000
한전 전원공급방식(1회선 또는 2회선)0.5650.0001.000

Missing values

2023-12-11T08:51:51.924921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:51:52.148847image/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

연번펌프장명주소설치년도설치목적모터 펌프규모(kW(HP) X 대)엔진 펌프규모(kW(HP) X 대)한전 전원공급방식(1회선 또는 2회선)비상발전기(kW(HP) X대)한전 계약전력(kW, 고압/저압)사용전력량(kWH)/년 (최대/최소, 고압/저압)전기요금(원)/년 (최대/최소, 고압/저압)
01삼랑진밀양시 삼랑진읍 검세리 658-22003내수배제500(650)X2<NA>2회선<NA>1,300(고압)21,859(6,019/0)1,554,390(334,180/0)
12심검세밀양시 삼랑진읍 검세리 634-132003내수배제500(650)X3<NA>2회선<NA>2,150(고압)46,818(12,258/0)3,468,430(759,970/0)
23구검세밀양시 삼랑진읍 검세리 633-91991내수배제400(550)X3<NA>1회선800(1,050)X21,500(고압)29,484(8,652/0)1,816,820(393,460/0)
34외 송밀양시 삼랑진읍 송지리 143-102004내수배제150(200)X2<NA>1회선375(500)X1500(고압)22,256(4,421/0)3,675,350(864,790/0)
45낙 동밀양시 삼랑진읍 삼랑리 58-51990내수배제150(200)X2<NA>1회선260(350)X199(저압)796(248/0)811,380(181,190/0)
56죽 곡밀양시 삼랑진읍 송지리 677-22003내수배제75(100)X1, 150(200)X1<NA>1회선400(550)X1500(고압)11,313(2,610/0)735,690(146,330/0)
67신 천밀양시 삼랑진읍 송지리 541-32000내수배제55(75)X2<NA>1회선125(170)X155(저압)236(79/0)435,010(77,050/0)
78평 지밀양시 하남읍 명례리 1296-161999내수배제55(75)X1, 25(30)X1<NA>1회선200(270)X155(저압)239(90/0)2,089,970(371,890/0)
89동 부밀양시 무안면 무안리 909-52003내수배제55(75)X2<NA>1회선200(270)X1350(고압)11,752(2,314/0)596,520(114,450/0)
910서 부밀양시 무안면 무안리 7782005내수배제55(75)X2<NA>1회선200(270)X1250(고압)7,855(1,574/0)397,930(85,570/0)
연번펌프장명주소설치년도설치목적모터 펌프규모(kW(HP) X 대)엔진 펌프규모(kW(HP) X 대)한전 전원공급방식(1회선 또는 2회선)비상발전기(kW(HP) X대)한전 계약전력(kW, 고압/저압)사용전력량(kWH)/년 (최대/최소, 고압/저압)전기요금(원)/년 (최대/최소, 고압/저압)
1819칠인전밀양시 삼랑진읍 용성리 857-12002내수배제55(75)X1, 38(50)X1<NA>1회선291(400)X1150(고압)23,625(10,003/0)790,150(272,880/0)
1920사 포밀양시 부북면 전사포리 838-1852004내수배제150(200)X2<NA>1회선545(730)X1400(고압)13,150(3,380/0)783,240(180,820/0)
2021어 은밀양시 상남면 외산리 외산리 756-22007내수배제75(100)X2<NA>1회선273(350)X1250(고압)9,463(1,589/0)445,580(70,630/0)
2122서 은밀양시 초동면 오방리 6862004내수배제75(100)X1, 115(150)X1<NA>1회선291(400)X1350(고압)21,800(4,159/0)919,880(156,290/0)
2223성 덕밀양시 무안면 성덕리 793-22004내수배제95(125)X2<NA>1회선250(330)X1300(고압)27,506(8,611/0)1,016,300(259,320/0)
2324성덕2밀양시 무안면 성덕리 11032000내수배제75(100)X2, 225(300)X1<NA>1회선455(600)X1550(고압)50,693(17,155/0)2,042,300(524,910/0)
2425성덕원밀양시 무안면 성덕리 479-22002내수배제150(200)X2<NA>1회선-50(고압)16,207(4,432/0)1,072,160(227,380/0)
2526부 로밀양시 무안면무안리 682-11993내수배제55(75)X2<NA>1회선155(200)X1200(고압)4,203(1,218/0)350,280(82,650/0)
2627연 상밀양시 무안면 연상리 8152006내수배제150(200)X2<NA>1회선495(660)X1500(고압)11,736(2,688/0)814,510(166,630/0)
2728차현밀양시 교동 234-22014내수배제345(450)X2<NA>1회선-1,000(고압)9,510(4,723/0)1,015,580(242,670/0)