Overview

Dataset statistics

Number of variables5
Number of observations89
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory42.5 B

Variable types

Numeric1
Text1
DateTime1
Categorical2

Dataset

Description인천광역시 서구 지하수 수질검사 결과에 관한 데이터로 연번, 관정위치, 검사일자, 검사종류, 검사결과 항목을 제공합니다.(2022년2분기 이후)
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15105183&srcSe=7661IVAWM27C61E190

Alerts

검사결과 has constant value ""Constant
연번 has unique valuesUnique
관정위치 has unique valuesUnique

Reproduction

Analysis started2024-01-28 15:51:05.247973
Analysis finished2024-01-28 15:51:05.618541
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45
Minimum1
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size933.0 B
2024-01-29T00:51:05.674954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.4
Q123
median45
Q367
95-th percentile84.6
Maximum89
Range88
Interquartile range (IQR)44

Descriptive statistics

Standard deviation25.836021
Coefficient of variation (CV)0.57413381
Kurtosis-1.2
Mean45
Median Absolute Deviation (MAD)22
Skewness0
Sum4005
Variance667.5
MonotonicityStrictly increasing
2024-01-29T00:51:05.786267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
68 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
60 1
 
1.1%
59 1
 
1.1%
Other values (79) 79
88.8%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%
81 1
1.1%
80 1
1.1%

관정위치
Text

UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2024-01-29T00:51:06.040133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length12.52809
Min length9

Characters and Unicode

Total characters1115
Distinct characters55
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

Unique89 ?
Unique (%)100.0%

Sample

1st row경서동 132번지 1호
2nd row연희동 197번지
3rd row검암동 436번지 2호
4th row석남동 산 21번지
5th row마전동 산 49번지
ValueCountFrequency (%)
1호 13
 
5.1%
연희동 9
 
3.5%
검암동 9
 
3.5%
백석동 9
 
3.5%
산 8
 
3.1%
4호 8
 
3.1%
2호 8
 
3.1%
3호 7
 
2.7%
대곡동 7
 
2.7%
경서동 7
 
2.7%
Other values (109) 171
66.8%
2024-01-29T00:51:06.393650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
238
21.3%
동 89
 
8.0%
번 89
 
8.0%
지 89
 
8.0%
1 75
 
6.7%
호 66
 
5.9%
2 48
 
4.3%
5 42
 
3.8%
4 41
 
3.7%
3 35
 
3.1%
Other values (45) 303
27.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 536
48.1%
Decimal Number 341
30.6%
Space Separator 238
21.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 89
16.6%
번 89
16.6%
지 89
16.6%
호 66
12.3%
석 14
 
2.6%
곡 14
 
2.6%
암 9
 
1.7%
검 9
 
1.7%
서 9
 
1.7%
백 9
 
1.7%
Other values (34) 139
25.9%
Decimal Number
ValueCountFrequency (%)
1 75
22.0%
2 48
14.1%
5 42
12.3%
4 41
12.0%
3 35
10.3%
7 25
 
7.3%
6 22
 
6.5%
8 21
 
6.2%
9 18
 
5.3%
0 14
 
4.1%
Space Separator
ValueCountFrequency (%)
238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 579
51.9%
Hangul 536
48.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 89
16.6%
번 89
16.6%
지 89
16.6%
호 66
12.3%
석 14
 
2.6%
곡 14
 
2.6%
암 9
 
1.7%
검 9
 
1.7%
서 9
 
1.7%
백 9
 
1.7%
Other values (34) 139
25.9%
Common
ValueCountFrequency (%)
238
41.1%
1 75
 
13.0%
2 48
 
8.3%
5 42
 
7.3%
4 41
 
7.1%
3 35
 
6.0%
7 25
 
4.3%
6 22
 
3.8%
8 21
 
3.6%
9 18
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 579
51.9%
Hangul 536
48.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
238
41.1%
1 75
 
13.0%
2 48
 
8.3%
5 42
 
7.3%
4 41
 
7.1%
3 35
 
6.0%
7 25
 
4.3%
6 22
 
3.8%
8 21
 
3.6%
9 18
 
3.1%
Hangul
ValueCountFrequency (%)
동 89
16.6%
번 89
16.6%
지 89
16.6%
호 66
12.3%
석 14
 
2.6%
곡 14
 
2.6%
암 9
 
1.7%
검 9
 
1.7%
서 9
 
1.7%
백 9
 
1.7%
Other values (34) 139
25.9%

검사일자
Date

Distinct53
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Memory size844.0 B
Minimum2022-04-05 00:00:00
Maximum2023-03-29 00:00:00
2024-01-29T00:51:06.500975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:51:06.603400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

검사종류
Categorical

Distinct5
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size844.0 B
농.어업용수
39 
생활용
23 
농·어업용
13 
생활용수
12 
음용수
 
2

Length

Max length6
Median length5
Mean length4.741573
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row농.어업용수
2nd row농.어업용수
3rd row농.어업용수
4th row음용수
5th row음용수

Common Values

ValueCountFrequency (%)
농.어업용수 39
43.8%
생활용 23
25.8%
농·어업용 13
 
14.6%
생활용수 12
 
13.5%
음용수 2
 
2.2%

Length

2024-01-29T00:51:06.707348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:51:06.803888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농.어업용수 39
43.8%
생활용 23
25.8%
농·어업용 13
 
14.6%
생활용수 12
 
13.5%
음용수 2
 
2.2%

검사결과
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size844.0 B
합격
89 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합격 89
100.0%

Length

2024-01-29T00:51:06.914346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:51:07.003440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
합격 89
100.0%

Interactions

2024-01-29T00:51:05.431214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:51:07.060632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관정위치검사일자검사종류
연번1.0001.0000.9910.790
관정위치1.0001.0001.0001.000
검사일자0.9911.0001.0000.985
검사종류0.7901.0000.9851.000
2024-01-29T00:51:07.139489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번검사종류
연번1.0000.429
검사종류0.4291.000

Missing values

2024-01-29T00:51:05.520443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:51:05.591253image/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

연번관정위치검사일자검사종류검사결과
01경서동 132번지 1호2022-04-05농.어업용수합격
12연희동 197번지2022-04-05농.어업용수합격
23검암동 436번지 2호2022-04-05농.어업용수합격
34석남동 산 21번지2022-04-11음용수합격
45마전동 산 49번지2022-04-11음용수합격
56백석동 51번지 148호2022-04-12농.어업용수합격
67연희동 127번지 1호2022-04-12농.어업용수합격
78공촌동 275번지 1호2022-04-20농.어업용수합격
89백석동 산 47번지2022-04-25생활용수합격
910심곡동 112번지2022-04-28농.어업용수합격
연번관정위치검사일자검사종류검사결과
7980오류동 1719번지 11호2023-03-03생활용수합격
8081오류동 1498번지 15호2023-02-21생활용수합격
8182원당동 1059번지2023-02-16생활용수합격
8283금곡동 536번지 7호2023-03-24농.어업용수합격
8384연희동 51번지 19호2023-03-16농.어업용수합격
8485연희동 207번지2023-03-16농.어업용수합격
8586검암동 438번지 189호2023-03-22농.어업용수합격
8687연희동 44번지 4호2023-03-29농.어업용수합격
8788대곡동 343번지2023-03-29농.어업용수합격
8889연희동 152번지2023-03-29농.어업용수합격