Overview

Dataset statistics

Number of variables13
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)1.0%
Total size in memory10.6 KiB
Average record size in memory108.3 B

Variable types

Categorical4
Text4
Numeric3
DateTime2

Alerts

Dataset has 1 (1.0%) duplicate rowsDuplicates
작성부서() is highly overall correlated with 지자체명() and 1 other fieldsHigh correlation
지자체명() is highly overall correlated with 작성부서() and 1 other fieldsHigh correlation
단수시작일시() is highly overall correlated with 단수종료일시() and 2 other fieldsHigh correlation
단수종료일시() is highly overall correlated with 단수시작일시() and 2 other fieldsHigh correlation
작성일시() is highly overall correlated with 단수시작일시() and 2 other fieldsHigh correlation
주소() is highly overall correlated with 단수시작일시() and 4 other fieldsHigh correlation
주소() is highly imbalanced (52.2%)Imbalance

Reproduction

Analysis started2023-12-10 12:36:30.469570
Analysis finished2023-12-10 12:36:34.430560
Duration3.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지자체명()
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
청송군
69 
진도군
22 
단양군
 
6
완도군
 
2
장흥군
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
청송군 69
69.0%
진도군 22
 
22.0%
단양군 6
 
6.0%
완도군 2
 
2.0%
장흥군 1
 
1.0%

Length

2023-12-10T21:36:34.528300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:34.668360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청송군 69
69.0%
진도군 22
 
22.0%
단양군 6
 
6.0%
완도군 2
 
2.0%
장흥군 1
 
1.0%

단수지역()
Text

Distinct83
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:36:35.073106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length7.46
Min length3

Characters and Unicode

Total characters746
Distinct characters123
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

Unique71 ?
Unique (%)71.0%

Sample

1st row단양읍 후곡리
2nd row삼화동
3rd row장발리
4th row어상천
5th row매포읍 안동길
ValueCountFrequency (%)
진보면 27
 
13.8%
현서면 10
 
5.1%
현동면 6
 
3.1%
진도읍 6
 
3.1%
청송읍 6
 
3.1%
진보로 5
 
2.6%
주왕산면 4
 
2.1%
의신면 4
 
2.1%
부남면 4
 
2.1%
두현리 4
 
2.1%
Other values (100) 119
61.0%
2023-12-10T21:36:35.843859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
 
12.7%
면 62
 
8.3%
진 52
 
7.0%
리 38
 
5.1%
보 36
 
4.8%
길 28
 
3.8%
현 22
 
2.9%
동 17
 
2.3%
읍 17
 
2.3%
2 13
 
1.7%
Other values (113) 366
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 610
81.8%
Space Separator 95
 
12.7%
Decimal Number 27
 
3.6%
Other Punctuation 12
 
1.6%
Math Symbol 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 62
 
10.2%
진 52
 
8.5%
리 38
 
6.2%
보 36
 
5.9%
길 28
 
4.6%
현 22
 
3.6%
동 17
 
2.8%
읍 17
 
2.8%
신 13
 
2.1%
서 12
 
2.0%
Other values (105) 313
51.3%
Decimal Number
ValueCountFrequency (%)
2 13
48.1%
1 6
22.2%
3 5
 
18.5%
4 2
 
7.4%
8 1
 
3.7%
Space Separator
ValueCountFrequency (%)
95
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 610
81.8%
Common 136
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 62
 
10.2%
진 52
 
8.5%
리 38
 
6.2%
보 36
 
5.9%
길 28
 
4.6%
현 22
 
3.6%
동 17
 
2.8%
읍 17
 
2.8%
신 13
 
2.1%
서 12
 
2.0%
Other values (105) 313
51.3%
Common
ValueCountFrequency (%)
95
69.9%
2 13
 
9.6%
, 12
 
8.8%
1 6
 
4.4%
3 5
 
3.7%
~ 2
 
1.5%
4 2
 
1.5%
8 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 610
81.8%
ASCII 136
 
18.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
95
69.9%
2 13
 
9.6%
, 12
 
8.8%
1 6
 
4.4%
3 5
 
3.7%
~ 2
 
1.5%
4 2
 
1.5%
8 1
 
0.7%
Hangul
ValueCountFrequency (%)
면 62
 
10.2%
진 52
 
8.5%
리 38
 
6.2%
보 36
 
5.9%
길 28
 
4.6%
현 22
 
3.6%
동 17
 
2.8%
읍 17
 
2.8%
신 13
 
2.1%
서 12
 
2.0%
Other values (105) 313
51.3%

유형명()
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
공사
66 
복구
34 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공사
2nd row복구
3rd row공사
4th row복구
5th row복구

Common Values

ValueCountFrequency (%)
공사 66
66.0%
복구 34
34.0%

Length

2023-12-10T21:36:36.086429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:36.263864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공사 66
66.0%
복구 34
34.0%

단수사유()
Text

Distinct58
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:36:36.654478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length9.84
Min length4

Characters and Unicode

Total characters984
Distinct characters130
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)39.0%

Sample

1st row상수관로 공사에 따른 단수
2nd row상수관로 누수
3rd row상수관로 공사에 따른 단수
4th row시설물 고장
5th row단양군 우덕교 교량확장공사 손괴사고
ValueCountFrequency (%)
작업 17
 
6.9%
교체 13
 
5.3%
앵글밸브 9
 
3.7%
누수복구 9
 
3.7%
관로 9
 
3.7%
긴급누수복구 8
 
3.3%
가압장 8
 
3.3%
누수 8
 
3.3%
복구 7
 
2.8%
긴급 7
 
2.8%
Other values (90) 151
61.4%
2023-12-10T21:36:37.337690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
146
 
14.8%
수 51
 
5.2%
구 34
 
3.5%
사 34
 
3.5%
관 33
 
3.4%
로 32
 
3.3%
공 32
 
3.3%
작 30
 
3.0%
업 30
 
3.0%
교 29
 
2.9%
Other values (120) 533
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 826
83.9%
Space Separator 146
 
14.8%
Close Punctuation 4
 
0.4%
Open Punctuation 4
 
0.4%
Uppercase Letter 2
 
0.2%
Decimal Number 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 51
 
6.2%
구 34
 
4.1%
사 34
 
4.1%
관 33
 
4.0%
로 32
 
3.9%
공 32
 
3.9%
작 30
 
3.6%
업 30
 
3.6%
교 29
 
3.5%
누 29
 
3.5%
Other values (113) 492
59.6%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
146
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 826
83.9%
Common 156
 
15.9%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 51
 
6.2%
구 34
 
4.1%
사 34
 
4.1%
관 33
 
4.0%
로 32
 
3.9%
공 32
 
3.9%
작 30
 
3.6%
업 30
 
3.6%
교 29
 
3.5%
누 29
 
3.5%
Other values (113) 492
59.6%
Common
ValueCountFrequency (%)
146
93.6%
) 4
 
2.6%
( 4
 
2.6%
1 1
 
0.6%
~ 1
 
0.6%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 826
83.9%
ASCII 158
 
16.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
146
92.4%
) 4
 
2.5%
( 4
 
2.5%
1 1
 
0.6%
S 1
 
0.6%
K 1
 
0.6%
~ 1
 
0.6%
Hangul
ValueCountFrequency (%)
수 51
 
6.2%
구 34
 
4.1%
사 34
 
4.1%
관 33
 
4.0%
로 32
 
3.9%
공 32
 
3.9%
작 30
 
3.6%
업 30
 
3.6%
교 29
 
3.5%
누 29
 
3.5%
Other values (113) 492
59.6%

단수시작일시()
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190992
Minimum20190117
Maximum20191231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:37.629896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190117
5-th percentile20190321
Q120191023
median20191118
Q320191204
95-th percentile20191224
Maximum20191231
Range1114
Interquartile range (IQR)180.75

Descriptive statistics

Standard deviation311.83873
Coefficient of variation (CV)1.5444448 × 10-5
Kurtosis1.0619374
Mean20190992
Median Absolute Deviation (MAD)92.5
Skewness-1.548204
Sum2.0190992 × 109
Variance97243.391
MonotonicityNot monotonic
2023-12-10T21:36:37.865832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20191203 8
 
8.0%
20191114 5
 
5.0%
20191122 5
 
5.0%
20191224 5
 
5.0%
20191219 5
 
5.0%
20191211 4
 
4.0%
20191023 3
 
3.0%
20191202 3
 
3.0%
20191031 3
 
3.0%
20191205 3
 
3.0%
Other values (45) 56
56.0%
ValueCountFrequency (%)
20190117 1
1.0%
20190118 1
1.0%
20190122 1
1.0%
20190218 1
1.0%
20190315 1
1.0%
20190321 1
1.0%
20190404 1
1.0%
20190405 1
1.0%
20190406 1
1.0%
20190412 1
1.0%
ValueCountFrequency (%)
20191231 1
 
1.0%
20191224 5
5.0%
20191220 2
 
2.0%
20191219 5
5.0%
20191217 1
 
1.0%
20191216 1
 
1.0%
20191212 2
 
2.0%
20191211 4
4.0%
20191210 1
 
1.0%
20191205 3
3.0%

단수시작시간()
Date

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2023-12-10 00:00:00
Maximum2023-12-10 21:00:00
2023-12-10T21:36:38.039215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:38.221498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

단수종료일시()
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190992
Minimum20190117
Maximum20191231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:38.435840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190117
5-th percentile20190321
Q120191023
median20191118
Q320191204
95-th percentile20191224
Maximum20191231
Range1114
Interquartile range (IQR)180.75

Descriptive statistics

Standard deviation311.84976
Coefficient of variation (CV)1.5444994 × 10-5
Kurtosis1.0619895
Mean20190992
Median Absolute Deviation (MAD)92.5
Skewness-1.5482946
Sum2.0190992 × 109
Variance97250.275
MonotonicityNot monotonic
2023-12-10T21:36:38.658870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20191203 8
 
8.0%
20191219 5
 
5.0%
20191122 5
 
5.0%
20191224 5
 
5.0%
20191114 5
 
5.0%
20191211 4
 
4.0%
20191202 3
 
3.0%
20191128 3
 
3.0%
20191205 3
 
3.0%
20191031 3
 
3.0%
Other values (45) 56
56.0%
ValueCountFrequency (%)
20190117 1
1.0%
20190118 1
1.0%
20190122 1
1.0%
20190218 1
1.0%
20190315 1
1.0%
20190321 1
1.0%
20190404 1
1.0%
20190405 1
1.0%
20190406 1
1.0%
20190412 1
1.0%
ValueCountFrequency (%)
20191231 1
 
1.0%
20191224 5
5.0%
20191220 2
 
2.0%
20191219 5
5.0%
20191217 1
 
1.0%
20191216 1
 
1.0%
20191212 2
 
2.0%
20191211 4
4.0%
20191210 1
 
1.0%
20191205 3
3.0%

단수종료시간()
Date

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2023-12-10 00:00:00
Maximum2023-12-10 21:00:00
2023-12-10T21:36:38.827546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:39.021442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

공사명()
Text

Distinct55
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:36:39.468271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length7.92
Min length4

Characters and Unicode

Total characters792
Distinct characters96
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

Unique36 ?
Unique (%)36.0%

Sample

1st row후곡 하자보수
2nd row누수복구
3rd row상수도관로공사
4th row긴급단수
5th row단양군 우덕교 교량확장공사
ValueCountFrequency (%)
작업 17
 
8.7%
누수복구 10
 
5.1%
교체 10
 
5.1%
앵글밸브 9
 
4.6%
긴급누수복구 8
 
4.1%
가압장 8
 
4.1%
복구 7
 
3.6%
긴급 7
 
3.6%
누수 7
 
3.6%
증설 6
 
3.1%
Other values (65) 107
54.6%
2023-12-10T21:36:40.115586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
 
12.1%
수 43
 
5.4%
구 34
 
4.3%
복 31
 
3.9%
공 31
 
3.9%
사 31
 
3.9%
교 28
 
3.5%
작 28
 
3.5%
업 28
 
3.5%
누 28
 
3.5%
Other values (86) 414
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 688
86.9%
Space Separator 96
 
12.1%
Open Punctuation 4
 
0.5%
Close Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 43
 
6.2%
구 34
 
4.9%
복 31
 
4.5%
공 31
 
4.5%
사 31
 
4.5%
교 28
 
4.1%
작 28
 
4.1%
업 28
 
4.1%
누 28
 
4.1%
체 26
 
3.8%
Other values (83) 380
55.2%
Space Separator
ValueCountFrequency (%)
96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 688
86.9%
Common 104
 
13.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 43
 
6.2%
구 34
 
4.9%
복 31
 
4.5%
공 31
 
4.5%
사 31
 
4.5%
교 28
 
4.1%
작 28
 
4.1%
업 28
 
4.1%
누 28
 
4.1%
체 26
 
3.8%
Other values (83) 380
55.2%
Common
ValueCountFrequency (%)
96
92.3%
( 4
 
3.8%
) 4
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 688
86.9%
ASCII 104
 
13.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
92.3%
( 4
 
3.8%
) 4
 
3.8%
Hangul
ValueCountFrequency (%)
수 43
 
6.2%
구 34
 
4.9%
복 31
 
4.5%
공 31
 
4.5%
사 31
 
4.5%
교 28
 
4.1%
작 28
 
4.1%
업 28
 
4.1%
누 28
 
4.1%
체 26
 
3.8%
Other values (83) 380
55.2%

공사개요()
Text

Distinct59
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:36:40.651203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length9.26
Min length4

Characters and Unicode

Total characters926
Distinct characters123
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)41.0%

Sample

1st row단양군 하자보수로 인한 단수(후곡리)
2nd row배수관로 누수
3rd row상수도관로공사
4th row긴급단수
5th row단양군 우덕교 교량확장공사
ValueCountFrequency (%)
작업 17
 
7.5%
교체 11
 
4.9%
누수복구 9
 
4.0%
앵글밸브 9
 
4.0%
가압장 8
 
3.5%
긴급누수복구 8
 
3.5%
누수 8
 
3.5%
관로 7
 
3.1%
복구 7
 
3.1%
긴급 7
 
3.1%
Other values (86) 135
59.7%
2023-12-10T21:36:41.351813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
13.6%
수 47
 
5.1%
구 36
 
3.9%
사 31
 
3.3%
작 31
 
3.3%
업 31
 
3.3%
공 30
 
3.2%
복 30
 
3.2%
관 29
 
3.1%
누 29
 
3.1%
Other values (113) 506
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 771
83.3%
Space Separator 126
 
13.6%
Decimal Number 13
 
1.4%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%
Lowercase Letter 3
 
0.3%
Other Punctuation 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 47
 
6.1%
구 36
 
4.7%
사 31
 
4.0%
작 31
 
4.0%
업 31
 
4.0%
공 30
 
3.9%
복 30
 
3.9%
관 29
 
3.8%
누 29
 
3.8%
로 27
 
3.5%
Other values (101) 450
58.4%
Decimal Number
ValueCountFrequency (%)
1 5
38.5%
0 4
30.8%
2 1
 
7.7%
9 1
 
7.7%
5 1
 
7.7%
3 1
 
7.7%
Space Separator
ValueCountFrequency (%)
126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 771
83.3%
Common 152
 
16.4%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 47
 
6.1%
구 36
 
4.7%
사 31
 
4.0%
작 31
 
4.0%
업 31
 
4.0%
공 30
 
3.9%
복 30
 
3.9%
관 29
 
3.8%
누 29
 
3.8%
로 27
 
3.5%
Other values (101) 450
58.4%
Common
ValueCountFrequency (%)
126
82.9%
1 5
 
3.3%
) 5
 
3.3%
( 5
 
3.3%
0 4
 
2.6%
. 2
 
1.3%
2 1
 
0.7%
9 1
 
0.7%
5 1
 
0.7%
~ 1
 
0.7%
Latin
ValueCountFrequency (%)
m 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 771
83.3%
ASCII 155
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
81.3%
1 5
 
3.2%
) 5
 
3.2%
( 5
 
3.2%
0 4
 
2.6%
m 3
 
1.9%
. 2
 
1.3%
2 1
 
0.6%
9 1
 
0.6%
5 1
 
0.6%
Other values (2) 2
 
1.3%
Hangul
ValueCountFrequency (%)
수 47
 
6.1%
구 36
 
4.7%
사 31
 
4.0%
작 31
 
4.0%
업 31
 
4.0%
공 30
 
3.9%
복 30
 
3.9%
관 29
 
3.8%
누 29
 
3.8%
로 27
 
3.5%
Other values (101) 450
58.4%

작성부서()
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
청송권지사
69 
진도수도지사
22 
충주권지사
 
6
완도수도지사
 
2
장흥수도관리단
 
1

Length

Max length7
Median length5
Mean length5.26
Min length5

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
청송권지사 69
69.0%
진도수도지사 22
 
22.0%
충주권지사 6
 
6.0%
완도수도지사 2
 
2.0%
장흥수도관리단 1
 
1.0%

Length

2023-12-10T21:36:41.599162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:41.777319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청송권지사 69
69.0%
진도수도지사 22
 
22.0%
충주권지사 6
 
6.0%
완도수도지사 2
 
2.0%
장흥수도관리단 1
 
1.0%

주소()
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct27
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경상북도 청송군 안덕면 성덕댐로 1191
69 
충청북도 충주시 사래실길 20-49
 
6
전라남도 진도군 진도읍 남동1길 62-28
 
1
전라남도 진도군 진도읍 남동1길 62-18
 
1
전라남도 진도군 진도읍 남동1길 62-19
 
1
Other values (22)
22 

Length

Max length23
Median length22
Mean length22.03
Min length19

Unique

Unique25 ?
Unique (%)25.0%

Sample

1st row충청북도 충주시 사래실길 20-49
2nd row충청북도 충주시 사래실길 20-49
3rd row충청북도 충주시 사래실길 20-49
4th row충청북도 충주시 사래실길 20-49
5th row충청북도 충주시 사래실길 20-49

Common Values

ValueCountFrequency (%)
경상북도 청송군 안덕면 성덕댐로 1191 69
69.0%
충청북도 충주시 사래실길 20-49 6
 
6.0%
전라남도 진도군 진도읍 남동1길 62-28 1
 
1.0%
전라남도 진도군 진도읍 남동1길 62-18 1
 
1.0%
전라남도 진도군 진도읍 남동1길 62-19 1
 
1.0%
전라남도 진도군 진도읍 남동1길 62-20 1
 
1.0%
전라남도 진도군 진도읍 남동1길 62-21 1
 
1.0%
전라남도 진도군 진도읍 남동1길 62-22 1
 
1.0%
전라남도 진도군 진도읍 남동1길 62-23 1
 
1.0%
전라남도 진도군 진도읍 남동1길 62-24 1
 
1.0%
Other values (17) 17
 
17.0%

Length

2023-12-10T21:36:41.992873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상북도 69
14.0%
청송군 69
14.0%
안덕면 69
14.0%
성덕댐로 69
14.0%
1191 69
14.0%
전라남도 25
 
5.1%
진도군 22
 
4.5%
진도읍 22
 
4.5%
남동1길 22
 
4.5%
충청북도 6
 
1.2%
Other values (34) 52
10.5%

작성일시()
Real number (ℝ)

HIGH CORRELATION 

Distinct54
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190990
Minimum20190116
Maximum20191231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:42.207831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190116
5-th percentile20190321
Q120191022
median20191116
Q320191203
95-th percentile20191223
Maximum20191231
Range1115
Interquartile range (IQR)180.75

Descriptive statistics

Standard deviation310.65306
Coefficient of variation (CV)1.5385727 × 10-5
Kurtosis1.0781378
Mean20190990
Median Absolute Deviation (MAD)92.5
Skewness-1.5523975
Sum2.019099 × 109
Variance96505.322
MonotonicityNot monotonic
2023-12-10T21:36:42.483273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20191122 7
 
7.0%
20191219 7
 
7.0%
20191202 6
 
6.0%
20191223 5
 
5.0%
20191211 4
 
4.0%
20191030 4
 
4.0%
20191104 4
 
4.0%
20191114 4
 
4.0%
20191128 3
 
3.0%
20191129 3
 
3.0%
Other values (44) 53
53.0%
ValueCountFrequency (%)
20190116 1
1.0%
20190117 1
1.0%
20190121 1
1.0%
20190218 1
1.0%
20190315 1
1.0%
20190321 1
1.0%
20190402 1
1.0%
20190404 1
1.0%
20190406 1
1.0%
20190412 1
1.0%
ValueCountFrequency (%)
20191231 1
 
1.0%
20191223 5
5.0%
20191219 7
7.0%
20191217 1
 
1.0%
20191216 1
 
1.0%
20191212 1
 
1.0%
20191211 4
4.0%
20191210 1
 
1.0%
20191209 1
 
1.0%
20191205 2
 
2.0%

Interactions

2023-12-10T21:36:33.375926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.562016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.990665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.531116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.712117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.122675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.683641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.856035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.243697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:36:42.666109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체명()단수지역()유형명()단수사유()단수시작일시()단수시작시간()단수종료일시()단수종료시간()공사명()공사개요()작성부서()주소()작성일시()
지자체명()1.0001.0000.1601.0000.6880.5370.6880.4210.9971.0001.0001.0000.688
단수지역()1.0001.0000.8000.9950.9950.8510.9950.8210.9930.9951.0001.0000.995
유형명()0.1600.8001.0001.0000.1510.5650.1510.5471.0001.0000.1600.0000.151
단수사유()1.0000.9951.0001.0000.9980.9530.9980.9720.9991.0001.0000.9990.998
단수시작일시()0.6880.9950.1510.9981.0000.3591.0000.5660.9900.9980.6880.9701.000
단수시작시간()0.5370.8510.5650.9530.3591.0000.3590.9360.9590.9570.5370.0000.359
단수종료일시()0.6880.9950.1510.9981.0000.3591.0000.5660.9900.9980.6880.9701.000
단수종료시간()0.4210.8210.5470.9720.5660.9360.5661.0000.9700.9720.4210.0000.566
공사명()0.9970.9931.0000.9990.9900.9590.9900.9701.0001.0000.9970.9920.990
공사개요()1.0000.9951.0001.0000.9980.9570.9980.9721.0001.0001.0000.9990.998
작성부서()1.0001.0000.1601.0000.6880.5370.6880.4210.9971.0001.0001.0000.688
주소()1.0001.0000.0000.9990.9700.0000.9700.0000.9920.9991.0001.0000.970
작성일시()0.6880.9950.1510.9981.0000.3591.0000.5660.9900.9980.6880.9701.000
2023-12-10T21:36:42.929540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형명()작성부서()지자체명()주소()
유형명()1.0000.1920.1920.000
작성부서()0.1921.0001.0000.877
지자체명()0.1921.0001.0000.877
주소()0.0000.8770.8771.000
2023-12-10T21:36:43.085873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단수시작일시()단수종료일시()작성일시()지자체명()유형명()작성부서()주소()
단수시작일시()1.0001.0000.9980.4810.1610.4810.743
단수종료일시()1.0001.0000.9980.4810.1610.4810.743
작성일시()0.9980.9981.0000.4810.1610.4810.743
지자체명()0.4810.4810.4811.0000.1921.0000.877
유형명()0.1610.1610.1610.1921.0000.1920.000
작성부서()0.4810.4810.4811.0000.1921.0000.877
주소()0.7430.7430.7430.8770.0000.8771.000

Missing values

2023-12-10T21:36:33.881700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:36:34.215375image/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

지자체명()단수지역()유형명()단수사유()단수시작일시()단수시작시간()단수종료일시()단수종료시간()공사명()공사개요()작성부서()주소()작성일시()
0단양군단양읍 후곡리공사상수관로 공사에 따른 단수201911269:402019112616:00후곡 하자보수단양군 하자보수로 인한 단수(후곡리)충주권지사충청북도 충주시 사래실길 20-4920191126
1단양군삼화동복구상수관로 누수2019111914:002019111915:00누수복구배수관로 누수충주권지사충청북도 충주시 사래실길 20-4920191118
2단양군장발리공사상수관로 공사에 따른 단수201911070:00201911070:00상수도관로공사상수도관로공사충주권지사충청북도 충주시 사래실길 20-4920191107
3단양군어상천복구시설물 고장2019090213:002019090218:00긴급단수긴급단수충주권지사충청북도 충주시 사래실길 20-4920190902
4단양군매포읍 안동길복구단양군 우덕교 교량확장공사 손괴사고2019081512:302019081516:30단양군 우덕교 교량확장공사단양군 우덕교 교량확장공사충주권지사충청북도 충주시 사래실길 20-4920190815
5단양군매포읍 평동 3리공사계량기함 이설2019041214:002019041214:30계량기함 이설계량기함 이설충주권지사충청북도 충주시 사래실길 20-4920190412
6장흥군진목,이회진,삭금마을공사회진1가압장 펌프점검 및 교체2019111513:002019111515:00가압장펌프교체2019.11.15장흥수도관리단전라남도 장흥군 장흥읍 남부관광로 1220191115
7완도군약산면득암리,사동리복구수위저하201909250:00201909250:00수위저하수위저하완도수도지사전라남도 완도군 완도읍 농공단지7길 3920190925
8완도군금일읍 하화전리복구원관누수복구2019040611:002019040616:00원관보수작업원관누수복구완도수도지사전라남도 완도군 완도읍 농공단지7길 4020190406
9진도군의신면 정지리공사의신천 교량공사중 급수관로 중첩으로 인한 이설2019120514:002019120517:00의신천 정비공사100mm 급수관로 30m 매설 후 연결작업 시행진도수도지사전라남도 진도군 진도읍 남동1길 62-1820191204
지자체명()단수지역()유형명()단수사유()단수시작일시()단수시작시간()단수종료일시()단수종료시간()공사명()공사개요()작성부서()주소()작성일시()
90청송군청송읍 청운리공사청송군 소화전 설치작업201910319:302019103111:30청송군 소화전 설치작업청송군 소화전 설치작업청송권지사경상북도 청송군 안덕면 성덕댐로 119120191030
91청송군진보면 광덕세장길공사청송군 소화전 설치작업2019103013:302019103014:30청송군 소화전 설치작업청송군 소화전 설치작업청송권지사경상북도 청송군 안덕면 성덕댐로 119120191030
92청송군진보면 신한1, 2길공사청송군 소화전 설치작업2019103013:302019103014:30청송군 소화전 설치작업청송군 소화전 설치작업청송권지사경상북도 청송군 안덕면 성덕댐로 119120191030
93청송군청송읍 논시골로공사논시골 가압장 설비교체2019102514:002019102516:00논시골 가압장 설비교체논시골 가압장 설비교체청송권지사경상북도 청송군 안덕면 성덕댐로 119120191024
94청송군청송읍 논시길공사논시골 가압장 설비교체2019102514:002019102516:00논시골 가압장 설비교체논시골 가압장 설비교체청송권지사경상북도 청송군 안덕면 성덕댐로 119120191024
95청송군청송읍 망미정3길복구긴급 누수복구 공사2019102313:302019102315:30긴급 누수복구 공사긴급 누수복구 공사청송권지사경상북도 청송군 안덕면 성덕댐로 119120191023
96청송군진보면 진안1, 4리복구경동택배 앞 긴급 누수복구 공사2019102313:302019102317:00경동택배 앞 긴급 누수복구 공사경동택배 앞 긴급 누수복구 공사청송권지사경상북도 청송군 안덕면 성덕댐로 119120191023
97청송군진보면 이촌1,2리복구경동택배 앞 긴급 누수복구 공사2019102313:302019102317:00경동택배 앞 긴급 누수복구 공사경동택배 앞 긴급 누수복구 공사청송권지사경상북도 청송군 안덕면 성덕댐로 119120191023
98청송군주왕산면 마평로공사계량기 교체공사201910229:302019102211:00계량기 교체공사계량기 교체공사청송권지사경상북도 청송군 안덕면 성덕댐로 119120191021
99청송군현서면 새터길공사이토변 설치공사2019102113:102019102115:00이토변 설치공사이토변 설치공사청송권지사경상북도 청송군 안덕면 성덕댐로 119120191021

Duplicate rows

Most frequently occurring

지자체명()단수지역()유형명()단수사유()단수시작일시()단수시작시간()단수종료일시()단수종료시간()공사명()공사개요()작성부서()주소()작성일시()# duplicates
0청송군주왕산면 신점2리복구누수복구2019112710:002019112711:30누수복구누수복구청송권지사경상북도 청송군 안덕면 성덕댐로 1191201911272