Overview

Dataset statistics

Number of variables3
Number of observations2099
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.4 KiB
Average record size in memory25.1 B

Variable types

Numeric1
Text2

Dataset

Description인천광역시 연수구의 보안등 현황 데이터로서 연번, 보안등명, 지번주소의 항목으로 이루어져 있으며 보안등 위치 분석 등에 사용할 수 있습니다.
URLhttps://www.data.go.kr/data/15118896/fileData.do

Alerts

연번 has unique valuesUnique
보안등명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:06:08.928202
Analysis finished2023-12-12 12:06:09.268150
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct2099
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1050
Minimum1
Maximum2099
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.6 KiB
2023-12-12T21:06:09.338259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile105.9
Q1525.5
median1050
Q31574.5
95-th percentile1994.1
Maximum2099
Range2098
Interquartile range (IQR)1049

Descriptive statistics

Standard deviation606.07343
Coefficient of variation (CV)0.57721279
Kurtosis-1.2
Mean1050
Median Absolute Deviation (MAD)525
Skewness0
Sum2203950
Variance367325
MonotonicityStrictly increasing
2023-12-12T21:06:09.464129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1412 1
 
< 0.1%
1410 1
 
< 0.1%
1409 1
 
< 0.1%
1408 1
 
< 0.1%
1407 1
 
< 0.1%
1406 1
 
< 0.1%
1405 1
 
< 0.1%
1404 1
 
< 0.1%
1403 1
 
< 0.1%
Other values (2089) 2089
99.5%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2099 1
< 0.1%
2098 1
< 0.1%
2097 1
< 0.1%
2096 1
< 0.1%
2095 1
< 0.1%
2094 1
< 0.1%
2093 1
< 0.1%
2092 1
< 0.1%
2091 1
< 0.1%
2090 1
< 0.1%

보안등명
Text

UNIQUE 

Distinct2099
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size16.5 KiB
2023-12-12T21:06:09.680285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length14.10767
Min length11

Characters and Unicode

Total characters29612
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2099 ?
Unique (%)100.0%

Sample

1st row선학동1-9(1-1)
2nd row선학동1-2(1-2)
3rd row선학동1-3(1-3)
4th row선학동1-4(1-4)
5th row선학동1-12(1-5)
ValueCountFrequency (%)
선학동1-9(1-1 1
 
< 0.1%
청학동8-58(44-58 1
 
< 0.1%
청학동8-18(44-56 1
 
< 0.1%
청학동8-55(44-55 1
 
< 0.1%
청학동8-54(44-54 1
 
< 0.1%
청학동8-53(44-53 1
 
< 0.1%
청학동8-52(44-52 1
 
< 0.1%
청학동8-51(44-51 1
 
< 0.1%
청학동8-50(44-50 1
 
< 0.1%
청학동8-49(44-49 1
 
< 0.1%
Other values (2096) 2096
99.5%
2023-12-12T21:06:10.057320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4198
14.2%
1 3278
11.1%
동 2277
 
7.7%
2 2251
 
7.6%
( 2067
 
7.0%
) 2067
 
7.0%
4 1794
 
6.1%
3 1738
 
5.9%
5 1394
 
4.7%
7 1229
 
4.2%
Other values (15) 7319
24.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14912
50.4%
Other Letter 6297
21.3%
Dash Punctuation 4198
 
14.2%
Open Punctuation 2099
 
7.1%
Close Punctuation 2099
 
7.1%
Space Separator 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3278
22.0%
2 2251
15.1%
4 1794
12.0%
3 1738
11.7%
5 1394
9.3%
7 1229
 
8.2%
6 1047
 
7.0%
8 970
 
6.5%
9 677
 
4.5%
0 534
 
3.6%
Other Letter
ValueCountFrequency (%)
동 2277
36.2%
학 880
 
14.0%
옥 525
 
8.3%
련 525
 
8.3%
청 521
 
8.3%
연 516
 
8.2%
수 516
 
8.2%
선 359
 
5.7%
춘 178
 
2.8%
Open Punctuation
ValueCountFrequency (%)
( 2067
98.5%
[ 32
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 2067
98.5%
] 32
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 4198
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23315
78.7%
Hangul 6297
 
21.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4198
18.0%
1 3278
14.1%
2 2251
9.7%
( 2067
8.9%
) 2067
8.9%
4 1794
7.7%
3 1738
7.5%
5 1394
 
6.0%
7 1229
 
5.3%
6 1047
 
4.5%
Other values (6) 2252
9.7%
Hangul
ValueCountFrequency (%)
동 2277
36.2%
학 880
 
14.0%
옥 525
 
8.3%
련 525
 
8.3%
청 521
 
8.3%
연 516
 
8.2%
수 516
 
8.2%
선 359
 
5.7%
춘 178
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23315
78.7%
Hangul 6297
 
21.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4198
18.0%
1 3278
14.1%
2 2251
9.7%
( 2067
8.9%
) 2067
8.9%
4 1794
7.7%
3 1738
7.5%
5 1394
 
6.0%
7 1229
 
5.3%
6 1047
 
4.5%
Other values (6) 2252
9.7%
Hangul
ValueCountFrequency (%)
동 2277
36.2%
학 880
 
14.0%
옥 525
 
8.3%
련 525
 
8.3%
청 521
 
8.3%
연 516
 
8.2%
수 516
 
8.2%
선 359
 
5.7%
춘 178
 
2.8%

지번주소
Text

Distinct1351
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Memory size16.5 KiB
2023-12-12T21:06:10.391868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length18.990948
Min length15

Characters and Unicode

Total characters39862
Distinct characters30
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

Unique880 ?
Unique (%)41.9%

Sample

1st row인천광역시 연수구 선학동 105-2
2nd row인천광역시 연수구 선학동 328
3rd row인천광역시 연수구 선학동 328
4th row인천광역시 연수구 선학동 126-1
5th row인천광역시 연수구 선학동 96-21
ValueCountFrequency (%)
인천광역시 2099
24.8%
연수구 2099
24.8%
옥련동 531
 
6.3%
청학동 522
 
6.2%
연수동 504
 
5.9%
선학동 354
 
4.2%
동춘동 169
 
2.0%
산 97
 
1.1%
16-1 17
 
0.2%
산52 16
 
0.2%
Other values (1286) 2072
24.4%
2023-12-12T21:06:10.845608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6383
16.0%
연 2612
 
6.6%
수 2612
 
6.6%
동 2268
 
5.7%
천 2101
 
5.3%
인 2099
 
5.3%
광 2099
 
5.3%
역 2099
 
5.3%
시 2099
 
5.3%
구 2099
 
5.3%
Other values (20) 13391
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23205
58.2%
Decimal Number 8477
 
21.3%
Space Separator 6383
 
16.0%
Dash Punctuation 1797
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 2612
11.3%
수 2612
11.3%
동 2268
9.8%
천 2101
9.1%
인 2099
9.0%
광 2099
9.0%
역 2099
9.0%
시 2099
9.0%
구 2099
9.0%
학 880
 
3.8%
Other values (8) 2237
9.6%
Decimal Number
ValueCountFrequency (%)
1 1393
16.4%
5 1255
14.8%
4 1042
12.3%
3 1006
11.9%
2 967
11.4%
6 688
8.1%
7 607
7.2%
0 554
 
6.5%
8 523
 
6.2%
9 442
 
5.2%
Space Separator
ValueCountFrequency (%)
6383
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1797
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23205
58.2%
Common 16657
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 2612
11.3%
수 2612
11.3%
동 2268
9.8%
천 2101
9.1%
인 2099
9.0%
광 2099
9.0%
역 2099
9.0%
시 2099
9.0%
구 2099
9.0%
학 880
 
3.8%
Other values (8) 2237
9.6%
Common
ValueCountFrequency (%)
6383
38.3%
- 1797
 
10.8%
1 1393
 
8.4%
5 1255
 
7.5%
4 1042
 
6.3%
3 1006
 
6.0%
2 967
 
5.8%
6 688
 
4.1%
7 607
 
3.6%
0 554
 
3.3%
Other values (2) 965
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23205
58.2%
ASCII 16657
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6383
38.3%
- 1797
 
10.8%
1 1393
 
8.4%
5 1255
 
7.5%
4 1042
 
6.3%
3 1006
 
6.0%
2 967
 
5.8%
6 688
 
4.1%
7 607
 
3.6%
0 554
 
3.3%
Other values (2) 965
 
5.8%
Hangul
ValueCountFrequency (%)
연 2612
11.3%
수 2612
11.3%
동 2268
9.8%
천 2101
9.1%
인 2099
9.0%
광 2099
9.0%
역 2099
9.0%
시 2099
9.0%
구 2099
9.0%
학 880
 
3.8%
Other values (8) 2237
9.6%

Interactions

2023-12-12T21:06:09.049664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T21:06:09.158359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:06:09.236561image/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

연번보안등명지번주소
01선학동1-9(1-1)인천광역시 연수구 선학동 105-2
12선학동1-2(1-2)인천광역시 연수구 선학동 328
23선학동1-3(1-3)인천광역시 연수구 선학동 328
34선학동1-4(1-4)인천광역시 연수구 선학동 126-1
45선학동1-12(1-5)인천광역시 연수구 선학동 96-21
56선학동1-17(1-6)인천광역시 연수구 선학동 96-7
67선학동1-35(1-7)인천광역시 연수구 선학동96-24
78선학동1-10(1-8)인천광역시 연수구 선학동 91-3
89선학동2-1(2-1)인천광역시 연수구 선학동 328
910선학동2-2(2-2)인천광역시 연수구 선학동 134-12
연번보안등명지번주소
20892090옥련2동5-2(84-2)인천광역시 연수구 옥련동 산 40-2
20902091옥련2동5-3(84-3)인천광역시 연수구 옥련동 산 40-2
20912092옥련2동5-4(84-4)인천광역시 연수구 옥련동 산 40-2
20922093옥련1동11-1(85-1)인천광역시 연수구 옥련동 405-7
20932094옥련1동11-2(85-2)인천광역시 연수구 옥련동 405-90
20942095옥련1동11-3(85-3)인천광역시 연수구 옥련동 405-71
20952096옥련1동11-4(85-4)인천광역시 연수구 옥련동 405-71
20962097옥련1동11-5(85-5)인천광역시 연수구 옥련동 405-71
20972098옥련1동11-6(85-6)인천광역시 연수구 옥련동 405-71
20982099선학동1-1(86-1)인천광역시 연수구 선학동 33-7