Overview

Dataset statistics

Number of variables8
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory71.3 B

Variable types

Categorical5
Numeric2
Text1

Dataset

Description문경시 상수도 요금에 대한 데이터로 구분, 업종별, 단게별, 사용량별, 단가, 관리기관 전화번호, 관리기관명 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15091500/fileData.do

Alerts

구분 has constant value ""Constant
관리기관 전화번호 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
단계 is highly overall correlated with 단가(원)High correlation
단가(원) is highly overall correlated with 단계High correlation

Reproduction

Analysis started2023-12-12 12:25:47.632441
Analysis finished2023-12-12 12:25:48.558709
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
상수도
25 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도 25
100.0%

Length

2023-12-12T21:25:48.657749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:48.809539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도 25
100.0%

업종
Categorical

Distinct6
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
가정용
6 
업무용
5 
영업용
4 
욕탕1종
4 
욕탕2종
4 

Length

Max length5
Median length3
Mean length3.48
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가정용 6
24.0%
업무용 5
20.0%
영업용 4
16.0%
욕탕1종 4
16.0%
욕탕2종 4
16.0%
전용공업용 2
 
8.0%

Length

2023-12-12T21:25:48.953515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:49.145625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가정용 6
24.0%
업무용 5
20.0%
영업용 4
16.0%
욕탕1종 4
16.0%
욕탕2종 4
16.0%
전용공업용 2
 
8.0%

단계
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.76
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T21:25:49.281048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4514361
Coefficient of variation (CV)0.52588263
Kurtosis-0.61747216
Mean2.76
Median Absolute Deviation (MAD)1
Skewness0.4554444
Sum69
Variance2.1066667
MonotonicityNot monotonic
2023-12-12T21:25:49.430937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 6
24.0%
2 6
24.0%
3 5
20.0%
4 5
20.0%
5 2
 
8.0%
6 1
 
4.0%
ValueCountFrequency (%)
1 6
24.0%
2 6
24.0%
3 5
20.0%
4 5
20.0%
5 2
 
8.0%
6 1
 
4.0%
ValueCountFrequency (%)
6 1
 
4.0%
5 2
 
8.0%
4 5
20.0%
3 5
20.0%
2 6
24.0%
1 6
24.0%

사용량(톤)
Text

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T21:25:49.650254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.52
Min length6

Characters and Unicode

Total characters213
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)64.0%

Sample

1st row 0 ~ 10
2nd row 11 ~ 20
3rd row 21 ~ 30
4th row 31 ~ 40
5th row 41 ~ 50
ValueCountFrequency (%)
16
23.5%
0 6
 
8.8%
이상 5
 
7.4%
200 3
 
4.4%
∼ 3
 
4.4%
50 3
 
4.4%
300 3
 
4.4%
21 2
 
2.9%
20 2
 
2.9%
30 2
 
2.9%
Other values (16) 23
33.8%
2023-12-12T21:25:50.001321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74
34.7%
0 45
21.1%
1 25
 
11.7%
~ 16
 
7.5%
2 10
 
4.7%
3 10
 
4.7%
5 10
 
4.7%
톤 6
 
2.8%
이 6
 
2.8%
상 6
 
2.8%
Other values (2) 5
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102
47.9%
Space Separator 74
34.7%
Math Symbol 19
 
8.9%
Other Letter 18
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
44.1%
1 25
24.5%
2 10
 
9.8%
3 10
 
9.8%
5 10
 
9.8%
4 2
 
2.0%
Other Letter
ValueCountFrequency (%)
톤 6
33.3%
이 6
33.3%
상 6
33.3%
Math Symbol
ValueCountFrequency (%)
~ 16
84.2%
∼ 3
 
15.8%
Space Separator
ValueCountFrequency (%)
74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 195
91.5%
Hangul 18
 
8.5%

Most frequent character per script

Common
ValueCountFrequency (%)
74
37.9%
0 45
23.1%
1 25
 
12.8%
~ 16
 
8.2%
2 10
 
5.1%
3 10
 
5.1%
5 10
 
5.1%
∼ 3
 
1.5%
4 2
 
1.0%
Hangul
ValueCountFrequency (%)
톤 6
33.3%
이 6
33.3%
상 6
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 192
90.1%
Hangul 18
 
8.5%
Math Operators 3
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
74
38.5%
0 45
23.4%
1 25
 
13.0%
~ 16
 
8.3%
2 10
 
5.2%
3 10
 
5.2%
5 10
 
5.2%
4 2
 
1.0%
Hangul
ValueCountFrequency (%)
톤 6
33.3%
이 6
33.3%
상 6
33.3%
Math Operators
ValueCountFrequency (%)
∼ 3
100.0%

단가(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1352.4
Minimum580
Maximum1980
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T21:25:50.164267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum580
5-th percentile704
Q11000
median1310
Q31680
95-th percentile1942
Maximum1980
Range1400
Interquartile range (IQR)680

Descriptive statistics

Standard deviation405.69159
Coefficient of variation (CV)0.29997899
Kurtosis-0.99584382
Mean1352.4
Median Absolute Deviation (MAD)330
Skewness-0.17198266
Sum33810
Variance164585.67
MonotonicityNot monotonic
2023-12-12T21:25:50.313785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1190 2
 
8.0%
1000 2
 
8.0%
580 1
 
4.0%
1800 1
 
4.0%
960 1
 
4.0%
800 1
 
4.0%
1810 1
 
4.0%
1690 1
 
4.0%
1570 1
 
4.0%
1310 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
580 1
4.0%
680 1
4.0%
800 1
4.0%
950 1
4.0%
960 1
4.0%
1000 2
8.0%
1110 1
4.0%
1180 1
4.0%
1190 2
8.0%
1290 1
4.0%
ValueCountFrequency (%)
1980 1
4.0%
1960 1
4.0%
1870 1
4.0%
1810 1
4.0%
1800 1
4.0%
1690 1
4.0%
1680 1
4.0%
1640 1
4.0%
1580 1
4.0%
1570 1
4.0%

관리기관 전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
054-550-8319
25 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row054-550-8319
2nd row054-550-8319
3rd row054-550-8319
4th row054-550-8319
5th row054-550-8319

Common Values

ValueCountFrequency (%)
054-550-8319 25
100.0%

Length

2023-12-12T21:25:50.494398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:50.624267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
054-550-8319 25
100.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
문경시청
25 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문경시청 25
100.0%

Length

2023-12-12T21:25:50.730321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:50.855908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문경시청 25
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-08-09
25 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-09
2nd row2023-08-09
3rd row2023-08-09
4th row2023-08-09
5th row2023-08-09

Common Values

ValueCountFrequency (%)
2023-08-09 25
100.0%

Length

2023-12-12T21:25:50.990523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:51.125623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-09 25
100.0%

Interactions

2023-12-12T21:25:48.065537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.845915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:48.176626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.963451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:25:51.200518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종단계사용량(톤)단가(원)
업종1.0000.0000.0000.000
단계0.0001.0001.0000.000
사용량(톤)0.0001.0001.0000.000
단가(원)0.0000.0000.0001.000
2023-12-12T21:25:51.333680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단계단가(원)업종
단계1.0000.6590.000
단가(원)0.6591.0000.000
업종0.0000.0001.000

Missing values

2023-12-12T21:25:48.341973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:25:48.492859image/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

구분업종단계사용량(톤)단가(원)관리기관 전화번호관리기관명데이터기준일자
0상수도가정용10 ~ 10580054-550-8319문경시청2023-08-09
1상수도가정용211 ~ 20680054-550-8319문경시청2023-08-09
2상수도가정용321 ~ 30950054-550-8319문경시청2023-08-09
3상수도가정용431 ~ 401190054-550-8319문경시청2023-08-09
4상수도가정용541 ~ 501580054-550-8319문경시청2023-08-09
5상수도가정용651톤 이상1870054-550-8319문경시청2023-08-09
6상수도업무용10 ~ 201000054-550-8319문경시청2023-08-09
7상수도업무용221 ~ 501180054-550-8319문경시청2023-08-09
8상수도업무용351 ~ 1001480054-550-8319문경시청2023-08-09
9상수도업무용4101 ~ 3001680054-550-8319문경시청2023-08-09
구분업종단계사용량(톤)단가(원)관리기관 전화번호관리기관명데이터기준일자
15상수도욕탕1종10 ~ 2001000054-550-8319문경시청2023-08-09
16상수도욕탕1종2201 ~ 3001110054-550-8319문경시청2023-08-09
17상수도욕탕1종3301 ~ 5001190054-550-8319문경시청2023-08-09
18상수도욕탕1종4501톤 이상1290054-550-8319문경시청2023-08-09
19상수도욕탕2종10 ~ 2001310054-550-8319문경시청2023-08-09
20상수도욕탕2종2201 ~ 3001570054-550-8319문경시청2023-08-09
21상수도욕탕2종3301 ~ 5001690054-550-8319문경시청2023-08-09
22상수도욕탕2종4501톤 이상1810054-550-8319문경시청2023-08-09
23상수도전용공업용10 ~ 200800054-550-8319문경시청2023-08-09
24상수도전용공업용2201톤 이상960054-550-8319문경시청2023-08-09