Overview

Dataset statistics

Number of variables5
Number of observations100
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory43.3 B

Variable types

Text3
Numeric2

Dataset

Description인천광역시 미추홀구 공중전화 위치 현황에 대한 데이터입니다. 공중전화가 위치한 도로명주소, 위도, 경도를 제공합니다.
URLhttps://www.data.go.kr/data/15087009/fileData.do

Alerts

상호명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:09:57.234405
Analysis finished2023-12-12 13:09:58.474814
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-12T22:09:58.619442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length14.75
Min length11

Characters and Unicode

Total characters1475
Distinct characters199
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row자인의원공중전화(옥외)
2nd row미추홀구보건소사거리공중전화(옥외)
3rd row용현동금호APT상가앞공중전화(옥외)
4th row지성병원_6층공중전화(옥내)
5th row명보주유소건너공중전화(옥외)
ValueCountFrequency (%)
자인의원공중전화(옥외 1
 
1.0%
인하전문대_도서관공중전화(옥외 1
 
1.0%
동인아파트공중전화(옥외 1
 
1.0%
제일은행앞공중전화(옥외 1
 
1.0%
고려예식장앞공중전화(옥외 1
 
1.0%
항도약국앞공중전화(옥외 1
 
1.0%
남부경찰서수경동1층현관공중전화(옥내 1
 
1.0%
할렐루야빌딩_1층공중전화(옥내 1
 
1.0%
화생당약국공중전화(옥외 1
 
1.0%
인천터미널_1층_대합실공중전화(옥내 1
 
1.0%
Other values (90) 90
90.0%
2023-12-12T22:09:58.949530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
화 107
 
7.3%
전 105
 
7.1%
) 102
 
6.9%
공 102
 
6.9%
중 102
 
6.9%
( 102
 
6.9%
옥 100
 
6.8%
외 89
 
6.0%
앞 29
 
2.0%
원 17
 
1.2%
Other values (189) 620
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1199
81.3%
Close Punctuation 102
 
6.9%
Open Punctuation 102
 
6.9%
Decimal Number 35
 
2.4%
Uppercase Letter 20
 
1.4%
Connector Punctuation 16
 
1.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 107
 
8.9%
전 105
 
8.8%
공 102
 
8.5%
중 102
 
8.5%
옥 100
 
8.3%
외 89
 
7.4%
앞 29
 
2.4%
원 17
 
1.4%
주 15
 
1.3%
안 14
 
1.2%
Other values (169) 519
43.3%
Decimal Number
ValueCountFrequency (%)
1 11
31.4%
5 5
14.3%
3 4
 
11.4%
8 4
 
11.4%
2 3
 
8.6%
4 3
 
8.6%
0 2
 
5.7%
7 2
 
5.7%
6 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
T 6
30.0%
A 5
25.0%
P 5
25.0%
K 1
 
5.0%
F 1
 
5.0%
S 1
 
5.0%
G 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 102
100.0%
Open Punctuation
ValueCountFrequency (%)
( 102
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1199
81.3%
Common 256
 
17.4%
Latin 20
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 107
 
8.9%
전 105
 
8.8%
공 102
 
8.5%
중 102
 
8.5%
옥 100
 
8.3%
외 89
 
7.4%
앞 29
 
2.4%
원 17
 
1.4%
주 15
 
1.3%
안 14
 
1.2%
Other values (169) 519
43.3%
Common
ValueCountFrequency (%)
) 102
39.8%
( 102
39.8%
_ 16
 
6.2%
1 11
 
4.3%
5 5
 
2.0%
3 4
 
1.6%
8 4
 
1.6%
2 3
 
1.2%
4 3
 
1.2%
0 2
 
0.8%
Other values (3) 4
 
1.6%
Latin
ValueCountFrequency (%)
T 6
30.0%
A 5
25.0%
P 5
25.0%
K 1
 
5.0%
F 1
 
5.0%
S 1
 
5.0%
G 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1199
81.3%
ASCII 276
 
18.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
화 107
 
8.9%
전 105
 
8.8%
공 102
 
8.5%
중 102
 
8.5%
옥 100
 
8.3%
외 89
 
7.4%
앞 29
 
2.4%
원 17
 
1.4%
주 15
 
1.3%
안 14
 
1.2%
Other values (169) 519
43.3%
ASCII
ValueCountFrequency (%)
) 102
37.0%
( 102
37.0%
_ 16
 
5.8%
1 11
 
4.0%
T 6
 
2.2%
A 5
 
1.8%
5 5
 
1.8%
P 5
 
1.8%
3 4
 
1.4%
8 4
 
1.4%
Other values (10) 16
 
5.8%

지번주소
Text

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-12T22:09:59.227877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length20.1
Min length17

Characters and Unicode

Total characters2010
Distinct characters35
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

Unique92 ?
Unique (%)92.0%

Sample

1st row인천광역시 미추홀구 학익동 330-10
2nd row인천광역시 미추홀구 주안동 216-14
3rd row인천광역시 미추홀구 용현동 647
4th row인천광역시 미추홀구 용현동 630-10
5th row인천광역시 미추홀구 주안동 739-1
ValueCountFrequency (%)
인천광역시 100
25.0%
미추홀구 100
25.0%
주안동 42
10.5%
용현동 20
 
5.0%
학익동 11
 
2.8%
숭의동 11
 
2.8%
도화동 8
 
2.0%
관교동 6
 
1.5%
15 2
 
0.5%
1526-5 2
 
0.5%
Other values (95) 98
24.5%
2023-12-12T22:09:59.667485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
300
 
14.9%
인 100
 
5.0%
동 100
 
5.0%
광 100
 
5.0%
역 100
 
5.0%
시 100
 
5.0%
미 100
 
5.0%
추 100
 
5.0%
홀 100
 
5.0%
구 100
 
5.0%
Other values (25) 810
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1200
59.7%
Decimal Number 422
 
21.0%
Space Separator 300
 
14.9%
Dash Punctuation 88
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 100
8.3%
동 100
8.3%
광 100
8.3%
역 100
8.3%
시 100
8.3%
미 100
8.3%
추 100
8.3%
홀 100
8.3%
구 100
8.3%
천 100
8.3%
Other values (13) 200
16.7%
Decimal Number
ValueCountFrequency (%)
1 92
21.8%
2 54
12.8%
5 50
11.8%
3 42
10.0%
4 40
9.5%
6 39
9.2%
7 29
 
6.9%
9 26
 
6.2%
0 25
 
5.9%
8 25
 
5.9%
Space Separator
ValueCountFrequency (%)
300
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1200
59.7%
Common 810
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 100
8.3%
동 100
8.3%
광 100
8.3%
역 100
8.3%
시 100
8.3%
미 100
8.3%
추 100
8.3%
홀 100
8.3%
구 100
8.3%
천 100
8.3%
Other values (13) 200
16.7%
Common
ValueCountFrequency (%)
300
37.0%
1 92
 
11.4%
- 88
 
10.9%
2 54
 
6.7%
5 50
 
6.2%
3 42
 
5.2%
4 40
 
4.9%
6 39
 
4.8%
7 29
 
3.6%
9 26
 
3.2%
Other values (2) 50
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1200
59.7%
ASCII 810
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
300
37.0%
1 92
 
11.4%
- 88
 
10.9%
2 54
 
6.7%
5 50
 
6.2%
3 42
 
5.2%
4 40
 
4.9%
6 39
 
4.8%
7 29
 
3.6%
9 26
 
3.2%
Other values (2) 50
 
6.2%
Hangul
ValueCountFrequency (%)
인 100
8.3%
동 100
8.3%
광 100
8.3%
역 100
8.3%
시 100
8.3%
미 100
8.3%
추 100
8.3%
홀 100
8.3%
구 100
8.3%
천 100
8.3%
Other values (13) 200
16.7%

도로명주소
Text

Distinct95
Distinct (%)96.0%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-12T22:10:00.001847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length18.69697
Min length16

Characters and Unicode

Total characters1851
Distinct characters75
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

Unique91 ?
Unique (%)91.9%

Sample

1st row인천광역시 미추홀구 소성로 87
2nd row인천광역시 미추홀구 주안서로 24
3rd row인천광역시 미추홀구 매소홀로 70
4th row인천광역시 미추홀구 아암대로 109
5th row인천광역시 미추홀구 인하로 212
ValueCountFrequency (%)
인천광역시 99
25.0%
미추홀구 99
25.0%
인하로 12
 
3.0%
경인로 9
 
2.3%
석정로 7
 
1.8%
미추홀대로 5
 
1.3%
매소홀로 5
 
1.3%
소성로 4
 
1.0%
독배로 3
 
0.8%
주승로 3
 
0.8%
Other values (121) 150
37.9%
2023-12-12T22:10:00.477836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
297
16.0%
인 128
 
6.9%
홀 110
 
5.9%
미 104
 
5.6%
추 104
 
5.6%
구 102
 
5.5%
천 101
 
5.5%
시 99
 
5.3%
역 99
 
5.3%
광 99
 
5.3%
Other values (65) 608
32.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1256
67.9%
Space Separator 297
 
16.0%
Decimal Number 292
 
15.8%
Dash Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 128
10.2%
홀 110
8.8%
미 104
8.3%
추 104
8.3%
구 102
8.1%
천 101
8.0%
시 99
7.9%
역 99
7.9%
광 99
7.9%
로 98
7.8%
Other values (53) 212
16.9%
Decimal Number
ValueCountFrequency (%)
1 54
18.5%
3 44
15.1%
2 42
14.4%
4 30
10.3%
7 23
7.9%
9 23
7.9%
0 21
 
7.2%
8 20
 
6.8%
5 20
 
6.8%
6 15
 
5.1%
Space Separator
ValueCountFrequency (%)
297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1256
67.9%
Common 595
32.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 128
10.2%
홀 110
8.8%
미 104
8.3%
추 104
8.3%
구 102
8.1%
천 101
8.0%
시 99
7.9%
역 99
7.9%
광 99
7.9%
로 98
7.8%
Other values (53) 212
16.9%
Common
ValueCountFrequency (%)
297
49.9%
1 54
 
9.1%
3 44
 
7.4%
2 42
 
7.1%
4 30
 
5.0%
7 23
 
3.9%
9 23
 
3.9%
0 21
 
3.5%
8 20
 
3.4%
5 20
 
3.4%
Other values (2) 21
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1256
67.9%
ASCII 595
32.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
297
49.9%
1 54
 
9.1%
3 44
 
7.4%
2 42
 
7.1%
4 30
 
5.0%
7 23
 
3.9%
9 23
 
3.9%
0 21
 
3.5%
8 20
 
3.4%
5 20
 
3.4%
Other values (2) 21
 
3.5%
Hangul
ValueCountFrequency (%)
인 128
10.2%
홀 110
8.8%
미 104
8.3%
추 104
8.3%
구 102
8.1%
천 101
8.0%
시 99
7.9%
역 99
7.9%
광 99
7.9%
로 98
7.8%
Other values (53) 212
16.9%

위도
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.455398
Minimum37.436545
Maximum37.47759
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T22:10:00.672641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.436545
5-th percentile37.44119
Q137.44817
median37.455786
Q337.46358
95-th percentile37.468484
Maximum37.47759
Range0.041045244
Interquartile range (IQR)0.015409599

Descriptive statistics

Standard deviation0.0093954156
Coefficient of variation (CV)0.00025084276
Kurtosis-0.96684347
Mean37.455398
Median Absolute Deviation (MAD)0.0077149641
Skewness-0.066827767
Sum3745.5398
Variance8.8273833 × 10-5
MonotonicityNot monotonic
2023-12-12T22:10:00.843898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4520508681165 2
 
2.0%
37.448046993126 2
 
2.0%
37.4514480321002 2
 
2.0%
37.4425062298688 2
 
2.0%
37.4452728717404 1
 
1.0%
37.4598185467648 1
 
1.0%
37.4680359048114 1
 
1.0%
37.4654273249409 1
 
1.0%
37.4659832106032 1
 
1.0%
37.4625901310756 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
37.4365451636913 1
1.0%
37.43721955612 1
1.0%
37.4385186411793 1
1.0%
37.4397546747602 1
1.0%
37.4405463321377 1
1.0%
37.4412235986512 1
1.0%
37.4417008858307 1
1.0%
37.4419049500121 1
1.0%
37.4423446873032 1
1.0%
37.4423612994612 1
1.0%
ValueCountFrequency (%)
37.4775904080537 1
1.0%
37.4701268096077 1
1.0%
37.4692945656698 1
1.0%
37.469018717232 1
1.0%
37.4685215114069 1
1.0%
37.4684819837938 1
1.0%
37.4682489436581 1
1.0%
37.4681943967769 1
1.0%
37.4680359048114 1
1.0%
37.4679810013875 1
1.0%

경도
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.6692
Minimum126.63226
Maximum126.70152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T22:10:01.021224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63226
5-th percentile126.63678
Q1126.65411
median126.66998
Q3126.68416
95-th percentile126.69482
Maximum126.70152
Range0.069255116
Interquartile range (IQR)0.03004544

Descriptive statistics

Standard deviation0.018555456
Coefficient of variation (CV)0.00014648751
Kurtosis-1.0043834
Mean126.6692
Median Absolute Deviation (MAD)0.015405866
Skewness-0.25409098
Sum12666.92
Variance0.00034430494
MonotonicityNot monotonic
2023-12-12T22:10:01.175275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.63226354014 2
 
2.0%
126.689657616872 2
 
2.0%
126.651542258118 2
 
2.0%
126.701518656221 2
 
2.0%
126.658924242638 1
 
1.0%
126.649033860157 1
 
1.0%
126.646371768058 1
 
1.0%
126.682584385481 1
 
1.0%
126.657157444678 1
 
1.0%
126.680774516939 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
126.63226354014 2
2.0%
126.633278038555 1
1.0%
126.636241781781 1
1.0%
126.636745389227 1
1.0%
126.636779769382 1
1.0%
126.637550634942 1
1.0%
126.638152026208 1
1.0%
126.639058274496 1
1.0%
126.642624556053 1
1.0%
126.645288095029 1
1.0%
ValueCountFrequency (%)
126.701518656221 2
2.0%
126.699690868667 1
1.0%
126.696268088598 1
1.0%
126.695005886277 1
1.0%
126.694811300122 1
1.0%
126.694774928269 1
1.0%
126.692878809393 1
1.0%
126.692331534887 1
1.0%
126.692069140179 1
1.0%
126.691526516186 1
1.0%

Interactions

2023-12-12T22:09:58.076477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:09:57.592201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:09:58.153665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:09:57.680260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:10:01.280684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호명지번주소도로명주소위도경도
상호명1.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.000
위도1.0001.0001.0001.0000.597
경도1.0001.0001.0000.5971.000
2023-12-12T22:10:01.377670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.123
경도-0.1231.000

Missing values

2023-12-12T22:09:58.303965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:09:58.436581image/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

상호명지번주소도로명주소위도경도
0자인의원공중전화(옥외)인천광역시 미추홀구 학익동 330-10인천광역시 미추홀구 소성로 8737.445273126.658924
1미추홀구보건소사거리공중전화(옥외)인천광역시 미추홀구 주안동 216-14인천광역시 미추홀구 주안서로 2437.460852126.677899
2용현동금호APT상가앞공중전화(옥외)인천광역시 미추홀구 용현동 647인천광역시 미추홀구 매소홀로 7037.449307126.633278
3지성병원_6층공중전화(옥내)인천광역시 미추홀구 용현동 630-10인천광역시 미추홀구 아암대로 10937.452051126.632264
4명보주유소건너공중전화(옥외)인천광역시 미추홀구 주안동 739-1인천광역시 미추홀구 인하로 21237.448387126.671532
5현대,기아부품대리점공중전화(옥외)인천광역시 미추홀구 주안동 722-28인천광역시 미추홀구 인주대로320번길 237.451663126.671682
6공단5호매점공중전화(옥외)인천광역시 미추홀구 주안동 6-1인천광역시 미추홀구 염전로 34437.470127126.678026
7간석역_뉴스타빌딩앞공중전화(옥외)인천광역시 미추홀구 주안동 49-1인천광역시 미추홀구 석산로 1237.463578126.694775
8인하전문대_2호관공중전화(옥외)인천광역시 미추홀구 용현동 253인천광역시 미추홀구 인하로 10037.451448126.651542
9주안축협공중전화(옥외)인천광역시 미추홀구 주안동 894-3인천광역시 미추홀구 경인로 49937.460386126.694811
상호명지번주소도로명주소위도경도
90명진컴퓨터학원앞공중전화(옥외)인천광역시 미추홀구 숭의동 63-8인천광역시 미추홀구 경인로 11337.466462126.655204
91숭의깡시장공중전화(옥외)인천광역시 미추홀구 숭의동 82-1인천광역시 미추홀구 석정로 10437.467981126.647205
92사랑병원응급실공중전화(옥내)인천광역시 미추홀구 주안동 144-2인천광역시 미추홀구 미추홀대로 72637.462198126.680684
931호선_도화역공중전화(옥내)인천광역시 미추홀구 도화동 668인천광역시 미추홀구 숙골로24번길 937.466111126.668376
94인천터미널_주차장공중전화(옥외)인천광역시 미추홀구 관교동 15인천광역시 미추홀구 연남로 3537.442506126.701519
95로얄백화점공중전화(옥외)인천광역시 미추홀구 용현동 139-2인천광역시 미추홀구 인주대로 17837.455525126.656596
96학익동아풍림후문공중전화(옥외)인천광역시 미추홀구 학익동 719인천광역시 미추홀구 소성로 12037.441701126.66218
97주안현광아파트공중전화(옥외)인천광역시 미추홀구 주안동 32-1인천광역시 미추홀구 염창로 9237.465309126.683948
98원다방앞공중전화(옥외)인천광역시 미추홀구 주안동 1499-26인천광역시 미추홀구 인하로 33337.448194126.685284
99주안미도APT공중전화(옥외)인천광역시 미추홀구 주안동 18-2인천광역시 미추홀구 주염로 3437.468249126.682459