Overview

Dataset statistics

Number of variables6
Number of observations243
Missing cells7
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.2 KiB
Average record size in memory51.5 B

Variable types

Numeric3
Text2
Categorical1

Dataset

Description전라남도 목포시 스마트워터미터기 현황에 대한 데이터로 순번, 도로명주소, 지번주소, 위도, 경도, 데이터 기준일자 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15104173/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
도로명주소 has 7 (2.9%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:56:18.122757
Analysis finished2023-12-12 03:56:20.018278
Duration1.9 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct243
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122
Minimum1
Maximum243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T12:56:20.131709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.1
Q161.5
median122
Q3182.5
95-th percentile230.9
Maximum243
Range242
Interquartile range (IQR)121

Descriptive statistics

Standard deviation70.292247
Coefficient of variation (CV)0.57616596
Kurtosis-1.2
Mean122
Median Absolute Deviation (MAD)61
Skewness0
Sum29646
Variance4941
MonotonicityStrictly increasing
2023-12-12T12:56:20.361288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
154 1
 
0.4%
156 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
Other values (233) 233
95.9%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%
236 1
0.4%
235 1
0.4%
234 1
0.4%

도로명주소
Text

MISSING 

Distinct231
Distinct (%)97.9%
Missing7
Missing (%)2.9%
Memory size2.0 KiB
2023-12-12T12:56:20.601037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length18.885593
Min length15

Characters and Unicode

Total characters4457
Distinct characters48
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

Unique226 ?
Unique (%)95.8%

Sample

1st row전라남도 목포시 수문로 77
2nd row전라남도 목포시 수문로 77
3rd row전라남도 목포시 수문로 79
4th row전라남도 목포시 수문로 79-1
5th row전라남도 목포시 수문로 81
ValueCountFrequency (%)
전라남도 236
25.0%
목포시 236
25.0%
수문로77번길 48
 
5.1%
불종대길21번길 36
 
3.8%
북교길 26
 
2.8%
북교길17번길 26
 
2.8%
수문로83번길 21
 
2.2%
수문로 21
 
2.2%
북교길25번길 20
 
2.1%
불종대길 13
 
1.4%
Other values (148) 261
27.6%
2023-12-12T12:56:21.076274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
708
15.9%
길 309
 
6.9%
남 238
 
5.3%
포 236
 
5.3%
라 236
 
5.3%
시 236
 
5.3%
전 236
 
5.3%
목 236
 
5.3%
도 236
 
5.3%
1 235
 
5.3%
Other values (38) 1551
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2765
62.0%
Decimal Number 855
 
19.2%
Space Separator 708
 
15.9%
Dash Punctuation 129
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 309
11.2%
남 238
8.6%
포 236
8.5%
라 236
8.5%
시 236
8.5%
전 236
8.5%
목 236
8.5%
도 236
8.5%
번 170
 
6.1%
로 97
 
3.5%
Other values (26) 535
19.3%
Decimal Number
ValueCountFrequency (%)
1 235
27.5%
7 164
19.2%
2 125
14.6%
3 96
11.2%
5 55
 
6.4%
4 53
 
6.2%
8 46
 
5.4%
6 35
 
4.1%
9 24
 
2.8%
0 22
 
2.6%
Space Separator
ValueCountFrequency (%)
708
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2765
62.0%
Common 1692
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 309
11.2%
남 238
8.6%
포 236
8.5%
라 236
8.5%
시 236
8.5%
전 236
8.5%
목 236
8.5%
도 236
8.5%
번 170
 
6.1%
로 97
 
3.5%
Other values (26) 535
19.3%
Common
ValueCountFrequency (%)
708
41.8%
1 235
 
13.9%
7 164
 
9.7%
- 129
 
7.6%
2 125
 
7.4%
3 96
 
5.7%
5 55
 
3.3%
4 53
 
3.1%
8 46
 
2.7%
6 35
 
2.1%
Other values (2) 46
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2765
62.0%
ASCII 1692
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
708
41.8%
1 235
 
13.9%
7 164
 
9.7%
- 129
 
7.6%
2 125
 
7.4%
3 96
 
5.7%
5 55
 
3.3%
4 53
 
3.1%
8 46
 
2.7%
6 35
 
2.1%
Other values (2) 46
 
2.7%
Hangul
ValueCountFrequency (%)
길 309
11.2%
남 238
8.6%
포 236
8.5%
라 236
8.5%
시 236
8.5%
전 236
8.5%
목 236
8.5%
도 236
8.5%
번 170
 
6.1%
로 97
 
3.5%
Other values (26) 535
19.3%

지번주소
Text

Distinct234
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T12:56:21.619501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17.016461
Min length14

Characters and Unicode

Total characters4135
Distinct characters27
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

Unique225 ?
Unique (%)92.6%

Sample

1st row전라남도 목포시 북교동 8-2
2nd row전라남도 목포시 북교동 8-2
3rd row전라남도 목포시 북교동 7
4th row전라남도 목포시 북교동 6
5th row전라남도 목포시 북교동 5-3
ValueCountFrequency (%)
전라남도 243
25.0%
목포시 243
25.0%
북교동 209
21.5%
죽교동 28
 
2.9%
산정동 5
 
0.5%
13-5 2
 
0.2%
149-2 2
 
0.2%
146-9 2
 
0.2%
20-1 2
 
0.2%
282 2
 
0.2%
Other values (229) 234
24.1%
2023-12-12T12:56:22.423744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
729
17.6%
전 243
 
5.9%
라 243
 
5.9%
남 243
 
5.9%
도 243
 
5.9%
목 243
 
5.9%
포 243
 
5.9%
시 243
 
5.9%
동 243
 
5.9%
교 237
 
5.7%
Other values (17) 1225
29.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2430
58.8%
Decimal Number 792
 
19.2%
Space Separator 729
 
17.6%
Dash Punctuation 184
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 243
10.0%
라 243
10.0%
남 243
10.0%
도 243
10.0%
목 243
10.0%
포 243
10.0%
시 243
10.0%
동 243
10.0%
교 237
9.8%
북 209
8.6%
Other values (5) 40
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 198
25.0%
2 105
13.3%
3 104
13.1%
4 73
 
9.2%
7 67
 
8.5%
6 64
 
8.1%
5 58
 
7.3%
0 44
 
5.6%
9 42
 
5.3%
8 37
 
4.7%
Space Separator
ValueCountFrequency (%)
729
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2430
58.8%
Common 1705
41.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 243
10.0%
라 243
10.0%
남 243
10.0%
도 243
10.0%
목 243
10.0%
포 243
10.0%
시 243
10.0%
동 243
10.0%
교 237
9.8%
북 209
8.6%
Other values (5) 40
 
1.6%
Common
ValueCountFrequency (%)
729
42.8%
1 198
 
11.6%
- 184
 
10.8%
2 105
 
6.2%
3 104
 
6.1%
4 73
 
4.3%
7 67
 
3.9%
6 64
 
3.8%
5 58
 
3.4%
0 44
 
2.6%
Other values (2) 79
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2430
58.8%
ASCII 1705
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
729
42.8%
1 198
 
11.6%
- 184
 
10.8%
2 105
 
6.2%
3 104
 
6.1%
4 73
 
4.3%
7 67
 
3.9%
6 64
 
3.8%
5 58
 
3.4%
0 44
 
2.6%
Other values (2) 79
 
4.6%
Hangul
ValueCountFrequency (%)
전 243
10.0%
라 243
10.0%
남 243
10.0%
도 243
10.0%
목 243
10.0%
포 243
10.0%
시 243
10.0%
동 243
10.0%
교 237
9.8%
북 209
8.6%
Other values (5) 40
 
1.6%

위도
Real number (ℝ)

Distinct238
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.794616
Minimum34.789195
Maximum34.811911
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T12:56:22.651231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.789195
5-th percentile34.792844
Q134.793853
median34.794686
Q334.795324
95-th percentile34.795774
Maximum34.811911
Range0.02271648
Interquartile range (IQR)0.00147147

Descriptive statistics

Standard deviation0.0017827964
Coefficient of variation (CV)5.1237709 × 10-5
Kurtosis50.144541
Mean34.794616
Median Absolute Deviation (MAD)0.00072767
Skewness5.2068323
Sum8455.0917
Variance3.178363 × 10-6
MonotonicityNot monotonic
2023-12-12T12:56:22.852477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.79509577 2
 
0.8%
34.79553268 2
 
0.8%
34.79572644 2
 
0.8%
34.7955892 2
 
0.8%
34.79566101 2
 
0.8%
34.79362353 1
 
0.4%
34.79387989 1
 
0.4%
34.79369755 1
 
0.4%
34.7935276 1
 
0.4%
34.79376988 1
 
0.4%
Other values (228) 228
93.8%
ValueCountFrequency (%)
34.78919489 1
0.4%
34.78931625 1
0.4%
34.79020127 1
0.4%
34.79034165 1
0.4%
34.79035681 1
0.4%
34.79256584 1
0.4%
34.79260792 1
0.4%
34.79263773 1
0.4%
34.79265541 1
0.4%
34.79267901 1
0.4%
ValueCountFrequency (%)
34.81191137 1
0.4%
34.80823269 1
0.4%
34.79613273 1
0.4%
34.79607491 1
0.4%
34.79590521 1
0.4%
34.79590052 1
0.4%
34.79586808 1
0.4%
34.79585933 1
0.4%
34.79584953 1
0.4%
34.79582943 1
0.4%

경도
Real number (ℝ)

Distinct237
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.37858
Minimum126.37076
Maximum126.43671
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T12:56:23.056359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.37076
5-th percentile126.37693
Q1126.37745
median126.37794
Q3126.37848
95-th percentile126.37907
Maximum126.43671
Range0.0659494
Interquartile range (IQR)0.00102435

Descriptive statistics

Standard deviation0.0049901344
Coefficient of variation (CV)3.9485603 × 10-5
Kurtosis85.015613
Mean126.37858
Median Absolute Deviation (MAD)0.0004996
Skewness8.5418146
Sum30709.995
Variance2.4901442 × 10-5
MonotonicityNot monotonic
2023-12-12T12:56:23.257843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.3784291 3
 
1.2%
126.3788695 2
 
0.8%
126.3770454 2
 
0.8%
126.3776888 2
 
0.8%
126.3776463 2
 
0.8%
126.3774422 1
 
0.4%
126.3775245 1
 
0.4%
126.3774604 1
 
0.4%
126.3774106 1
 
0.4%
126.3776381 1
 
0.4%
Other values (227) 227
93.4%
ValueCountFrequency (%)
126.3707632 1
0.4%
126.3766097 1
0.4%
126.3766802 1
0.4%
126.3766808 1
0.4%
126.3767691 1
0.4%
126.3767853 1
0.4%
126.3767874 1
0.4%
126.3767957 1
0.4%
126.3768152 1
0.4%
126.3768532 1
0.4%
ValueCountFrequency (%)
126.4367126 1
0.4%
126.4045218 1
0.4%
126.4040465 1
0.4%
126.4038884 1
0.4%
126.3992519 1
0.4%
126.3804009 1
0.4%
126.3800759 1
0.4%
126.3797183 1
0.4%
126.3791491 1
0.4%
126.3791438 1
0.4%

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-07-19
243 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-19
2nd row2023-07-19
3rd row2023-07-19
4th row2023-07-19
5th row2023-07-19

Common Values

ValueCountFrequency (%)
2023-07-19 243
100.0%

Length

2023-12-12T12:56:23.488202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:56:23.628959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-19 243
100.0%

Interactions

2023-12-12T12:56:19.317906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:56:18.415390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:56:18.871932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:56:19.472616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:56:18.548340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:56:19.027833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:56:19.632542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:56:18.710108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:56:19.159261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:56:23.739058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도
순번1.0000.5910.685
위도0.5911.0000.758
경도0.6850.7581.000
2023-12-12T12:56:24.276513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도
순번1.000-0.444-0.220
위도-0.4441.000-0.248
경도-0.220-0.2481.000

Missing values

2023-12-12T12:56:19.799935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:56:19.954592image/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

순번도로명주소지번주소위도경도데이터 기준일자
01전라남도 목포시 수문로 77전라남도 목포시 북교동 8-234.795096126.3788692023-07-19
12전라남도 목포시 수문로 77전라남도 목포시 북교동 8-234.795096126.3788692023-07-19
23전라남도 목포시 수문로 79전라남도 목포시 북교동 734.795205126.3788482023-07-19
34전라남도 목포시 수문로 79-1전라남도 목포시 북교동 634.795314126.3788412023-07-19
45전라남도 목포시 수문로 81전라남도 목포시 북교동 5-334.795401126.3787922023-07-19
56전라남도 목포시 수문로 81-1전라남도 목포시 북교동 5-234.79546126.3787132023-07-19
67전라남도 목포시 수문로83번길 1전라남도 목포시 북교동 5-434.795509126.3786762023-07-19
78전라남도 목포시 수문로83번길 1-1전라남도 목포시 북교동 13-734.795493126.3785952023-07-19
89전라남도 목포시 수문로83번길 3전라남도 목포시 북교동 13-534.795533126.3784292023-07-19
910전라남도 목포시 수문로83번길 3전라남도 목포시 북교동 13-534.795533126.3784292023-07-19
순번도로명주소지번주소위도경도데이터 기준일자
233234전라남도 목포시 북교길17번길 20-2전라남도 목포시 죽교동 145-134.79575126.376922023-07-19
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