Overview

Dataset statistics

Number of variables7
Number of observations125
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory59.1 B

Variable types

Numeric2
Categorical4
Text1

Dataset

Description전라남도 화순군 상수도 원격검침기에 관한 데이터로 시도, 시군구, 읍면동, 도로명주소, 상수도 원격검침기의 대수, 데이터 기준일 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15103397/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 읍면동High correlation
읍면동 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:40:56.037305
Analysis finished2023-12-12 21:40:56.797347
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct125
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63
Minimum1
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T06:40:56.889265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.2
Q132
median63
Q394
95-th percentile118.8
Maximum125
Range124
Interquartile range (IQR)62

Descriptive statistics

Standard deviation36.228442
Coefficient of variation (CV)0.57505463
Kurtosis-1.2
Mean63
Median Absolute Deviation (MAD)31
Skewness0
Sum7875
Variance1312.5
MonotonicityStrictly increasing
2023-12-13T06:40:57.053900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
80 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
Other values (115) 115
92.0%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
전라남도
125 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 125
100.0%

Length

2023-12-13T06:40:57.216505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:40:57.311080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 125
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
화순군
125 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화순군 125
100.0%

Length

2023-12-13T06:40:57.407049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:40:57.505609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화순군 125
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
화순읍
73 
능주면
50 
도곡면
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화순읍 73
58.4%
능주면 50
40.0%
도곡면 2
 
1.6%

Length

2023-12-13T06:40:57.597707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:40:57.707640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화순읍 73
58.4%
능주면 50
40.0%
도곡면 2
 
1.6%

도로명주소
Text

UNIQUE 

Distinct125
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T06:40:58.042582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.344
Min length2

Characters and Unicode

Total characters418
Distinct characters120
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)100.0%

Sample

1st row계량길
2nd row계소리
3rd row광덕로
4th row광덕리
5th row광덕중앙길
ValueCountFrequency (%)
계량길 1
 
0.8%
하주길 1
 
0.8%
백암1길 1
 
0.8%
만인리 1
 
0.8%
만수리 1
 
0.8%
만세동길 1
 
0.8%
만년동길 1
 
0.8%
능주종방길 1
 
0.8%
능주시장길 1
 
0.8%
능주농공길 1
 
0.8%
Other values (115) 115
92.0%
2023-12-13T06:40:58.562976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 86
 
20.6%
리 26
 
6.2%
로 16
 
3.8%
동 15
 
3.6%
덕 8
 
1.9%
정 7
 
1.7%
만 7
 
1.7%
1 7
 
1.7%
곡 7
 
1.7%
교 6
 
1.4%
Other values (110) 233
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 406
97.1%
Decimal Number 12
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 86
 
21.2%
리 26
 
6.4%
로 16
 
3.9%
동 15
 
3.7%
덕 8
 
2.0%
정 7
 
1.7%
만 7
 
1.7%
곡 7
 
1.7%
교 6
 
1.5%
중 6
 
1.5%
Other values (108) 222
54.7%
Decimal Number
ValueCountFrequency (%)
1 7
58.3%
2 5
41.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 406
97.1%
Common 12
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 86
 
21.2%
리 26
 
6.4%
로 16
 
3.9%
동 15
 
3.7%
덕 8
 
2.0%
정 7
 
1.7%
만 7
 
1.7%
곡 7
 
1.7%
교 6
 
1.5%
중 6
 
1.5%
Other values (108) 222
54.7%
Common
ValueCountFrequency (%)
1 7
58.3%
2 5
41.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 406
97.1%
ASCII 12
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 86
 
21.2%
리 26
 
6.4%
로 16
 
3.9%
동 15
 
3.7%
덕 8
 
2.0%
정 7
 
1.7%
만 7
 
1.7%
곡 7
 
1.7%
교 6
 
1.5%
중 6
 
1.5%
Other values (108) 222
54.7%
ASCII
ValueCountFrequency (%)
1 7
58.3%
2 5
41.7%

상수도원격검침기수
Real number (ℝ)

Distinct61
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.44
Minimum1
Maximum199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T06:40:58.732329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q110
median23
Q346
95-th percentile83.2
Maximum199
Range198
Interquartile range (IQR)36

Descriptive statistics

Standard deviation29.173121
Coefficient of variation (CV)0.9583811
Kurtosis8.7785606
Mean30.44
Median Absolute Deviation (MAD)16
Skewness2.2784943
Sum3805
Variance851.07097
MonotonicityNot monotonic
2023-12-13T06:40:58.916122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 9
 
7.2%
21 5
 
4.0%
23 5
 
4.0%
47 5
 
4.0%
12 4
 
3.2%
2 4
 
3.2%
5 4
 
3.2%
14 4
 
3.2%
7 3
 
2.4%
8 3
 
2.4%
Other values (51) 79
63.2%
ValueCountFrequency (%)
1 9
7.2%
2 4
3.2%
3 1
 
0.8%
4 3
 
2.4%
5 4
3.2%
6 2
 
1.6%
7 3
 
2.4%
8 3
 
2.4%
9 2
 
1.6%
10 1
 
0.8%
ValueCountFrequency (%)
199 1
0.8%
120 1
0.8%
114 1
0.8%
97 1
0.8%
93 1
0.8%
88 1
0.8%
84 1
0.8%
80 1
0.8%
73 1
0.8%
72 1
0.8%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2022-08-08
125 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-08
2nd row2022-08-08
3rd row2022-08-08
4th row2022-08-08
5th row2022-08-08

Common Values

ValueCountFrequency (%)
2022-08-08 125
100.0%

Length

2023-12-13T06:40:59.080036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:40:59.191917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-08 125
100.0%

Interactions

2023-12-13T06:40:56.437120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:56.224641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:56.523930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:56.341829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:40:59.248324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동상수도원격검침기수
연번1.0000.8290.000
읍면동0.8291.0000.000
상수도원격검침기수0.0000.0001.000
2023-12-13T06:40:59.356206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상수도원격검침기수읍면동
연번1.000-0.0330.712
상수도원격검침기수-0.0331.0000.000
읍면동0.7120.0001.000

Missing values

2023-12-13T06:40:56.648302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:40:56.755574image/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

연번시도시군구읍면동도로명주소상수도원격검침기수데이터기준일
01전라남도화순군화순읍계량길582022-08-08
12전라남도화순군화순읍계소리72022-08-08
23전라남도화순군화순읍광덕로12022-08-08
34전라남도화순군화순읍광덕리82022-08-08
45전라남도화순군화순읍광덕중앙길842022-08-08
56전라남도화순군화순읍교동1길412022-08-08
67전라남도화순군화순읍교동2길292022-08-08
78전라남도화순군화순읍교동길402022-08-08
89전라남도화순군화순읍교리72022-08-08
910전라남도화순군화순읍대교로802022-08-08
연번시도시군구읍면동도로명주소상수도원격검침기수데이터기준일
115116전라남도화순군능주면지석로122022-08-08
116117전라남도화순군능주면지평길62022-08-08
117118전라남도화순군능주면천년동길472022-08-08
118119전라남도화순군능주면천덕리22022-08-08
119120전라남도화순군능주면초당길252022-08-08
120121전라남도화순군능주면통사물길282022-08-08
121122전라남도화순군능주면학샘길192022-08-08
122123전라남도화순군능주면학포로602022-08-08
123124전라남도화순군능주면회덕길402022-08-08
124125전라남도화순군능주면효죽로12022-08-08