Overview

Dataset statistics

Number of variables4
Number of observations194
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory33.7 B

Variable types

Categorical2
Text1
Numeric1

Dataset

Description2022년 7월 27일 기준 대구광역시에 설치된 스마트 원격검침 계량기 전수를 동별로 집계한 데이터로 공공데이터 제공신청에 의해 제공합니다.
Author대구광역시
URLhttps://www.data.go.kr/data/15102837/fileData.do

Alerts

시 has constant value ""Constant

Reproduction

Analysis started2023-12-12 09:12:59.603897
Analysis finished2023-12-12 09:13:00.016156
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
대구광역시
194 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 194
100.0%

Length

2023-12-12T18:13:00.107657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:13:00.212749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 194
100.0%

구
Categorical

Distinct8
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
중구
55 
동구
37 
북구
31 
수성구
26 
달서구
24 
Other values (3)
21 

Length

Max length3
Median length2
Mean length2.3041237
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남구
2nd row남구
3rd row남구
4th row달서구
5th row달서구

Common Values

ValueCountFrequency (%)
중구 55
28.4%
동구 37
19.1%
북구 31
16.0%
수성구 26
13.4%
달서구 24
12.4%
달성군 9
 
4.6%
서구 9
 
4.6%
남구 3
 
1.5%

Length

2023-12-12T18:13:00.365958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:13:00.539901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 55
28.4%
동구 37
19.1%
북구 31
16.0%
수성구 26
13.4%
달서구 24
12.4%
달성군 9
 
4.6%
서구 9
 
4.6%
남구 3
 
1.5%

동
Text

Distinct192
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T18:13:00.950265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.3247423
Min length2

Characters and Unicode

Total characters645
Distinct characters126
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

Unique190 ?
Unique (%)97.9%

Sample

1st row대명동
2nd row봉덕동
3rd row이천동
4th row갈산동
5th row감삼동
ValueCountFrequency (%)
이천동 2
 
1.0%
동호동 2
 
1.0%
신매동 1
 
0.5%
대명동 1
 
0.5%
욱수동 1
 
0.5%
상동 1
 
0.5%
성동 1
 
0.5%
수성동1가 1
 
0.5%
수성동2가 1
 
0.5%
수성동3가 1
 
0.5%
Other values (182) 182
93.8%
2023-12-12T18:13:01.529923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 184
28.5%
가 41
 
6.4%
성 22
 
3.4%
로 17
 
2.6%
산 16
 
2.5%
2 14
 
2.2%
1 14
 
2.2%
대 14
 
2.2%
천 10
 
1.6%
서 10
 
1.6%
Other values (116) 303
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 607
94.1%
Decimal Number 38
 
5.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 184
30.3%
가 41
 
6.8%
성 22
 
3.6%
로 17
 
2.8%
산 16
 
2.6%
대 14
 
2.3%
천 10
 
1.6%
서 10
 
1.6%
호 9
 
1.5%
신 9
 
1.5%
Other values (112) 275
45.3%
Decimal Number
ValueCountFrequency (%)
2 14
36.8%
1 14
36.8%
3 8
21.1%
4 2
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 607
94.1%
Common 38
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 184
30.3%
가 41
 
6.8%
성 22
 
3.6%
로 17
 
2.8%
산 16
 
2.6%
대 14
 
2.3%
천 10
 
1.6%
서 10
 
1.6%
호 9
 
1.5%
신 9
 
1.5%
Other values (112) 275
45.3%
Common
ValueCountFrequency (%)
2 14
36.8%
1 14
36.8%
3 8
21.1%
4 2
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 607
94.1%
ASCII 38
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 184
30.3%
가 41
 
6.8%
성 22
 
3.6%
로 17
 
2.8%
산 16
 
2.6%
대 14
 
2.3%
천 10
 
1.6%
서 10
 
1.6%
호 9
 
1.5%
신 9
 
1.5%
Other values (112) 275
45.3%
ASCII
ValueCountFrequency (%)
2 14
36.8%
1 14
36.8%
3 8
21.1%
4 2
 
5.3%

설치전수
Real number (ℝ)

Distinct114
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.53608
Minimum1
Maximum2920
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T18:13:01.699967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.65
Q110
median38.5
Q3123
95-th percentile760.75
Maximum2920
Range2919
Interquartile range (IQR)113

Descriptive statistics

Standard deviation395.9089
Coefficient of variation (CV)2.4358216
Kurtosis22.928381
Mean162.53608
Median Absolute Deviation (MAD)34
Skewness4.5286131
Sum31532
Variance156743.86
MonotonicityNot monotonic
2023-12-12T18:13:01.873228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 9
 
4.6%
1 8
 
4.1%
3 7
 
3.6%
10 5
 
2.6%
9 5
 
2.6%
6 5
 
2.6%
17 5
 
2.6%
29 4
 
2.1%
14 4
 
2.1%
5 3
 
1.5%
Other values (104) 139
71.6%
ValueCountFrequency (%)
1 8
4.1%
2 2
 
1.0%
3 7
3.6%
4 9
4.6%
5 3
 
1.5%
6 5
2.6%
7 3
 
1.5%
8 3
 
1.5%
9 5
2.6%
10 5
2.6%
ValueCountFrequency (%)
2920 1
0.5%
2374 1
0.5%
2172 1
0.5%
2117 1
0.5%
1397 1
0.5%
1321 1
0.5%
1103 1
0.5%
1072 1
0.5%
1032 1
0.5%
868 1
0.5%

Interactions

2023-12-12T18:12:59.745560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:13:02.011775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구설치전수
구1.0000.617
설치전수0.6171.000
2023-12-12T18:13:02.469247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치전수구
설치전수1.0000.247
구0.2471.000

Missing values

2023-12-12T18:12:59.880994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:12:59.978724image/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

시구동설치전수
0대구광역시남구대명동188
1대구광역시남구봉덕동54
2대구광역시남구이천동23
3대구광역시달서구갈산동147
4대구광역시달서구감삼동17
5대구광역시달서구대곡동25
6대구광역시달서구대천동229
7대구광역시달서구도원동13
8대구광역시달서구두류동40
9대구광역시달서구본동10
시구동설치전수
184대구광역시중구전동17
185대구광역시중구종로1가14
186대구광역시중구종로2가1
187대구광역시중구태평로1가43
188대구광역시중구태평로2가47
189대구광역시중구태평로3가66
190대구광역시중구포정동80
191대구광역시중구하서동10
192대구광역시중구향촌동90
193대구광역시중구화전동54