Overview

Dataset statistics

Number of variables6
Number of observations111
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory51.2 B

Variable types

Text3
Numeric2
DateTime1

Dataset

Description대구광역시 북구 안경업소 현황에 대한 데이터로 업소명, 소재지도로명주소, 전화번호, 위도, 경도 등 정보를 제공합니다.
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15030482/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation

Reproduction

Analysis started2023-12-12 17:11:09.006931
Analysis finished2023-12-12 17:11:09.911924
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct109
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-13T02:11:10.075426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length7.6756757
Min length3

Characters and Unicode

Total characters852
Distinct characters184
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)96.4%

Sample

1st row룩스토어 침산점
2nd row세컨페이스 칠곡점
3rd row으뜸플러스안경 대구연경점
4th row아이씨유
5th row이분의일안경
ValueCountFrequency (%)
안경원 7
 
4.9%
동천점 3
 
2.1%
칠곡점 3
 
2.1%
아이젠트리 3
 
2.1%
침산점 3
 
2.1%
라디오아이즈 2
 
1.4%
1001안경콘택트 2
 
1.4%
씨채널 2
 
1.4%
다비치안경원 2
 
1.4%
으뜸50안경 2
 
1.4%
Other values (111) 115
79.9%
2023-12-13T02:11:10.481202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 99
 
11.6%
안 95
 
11.2%
원 46
 
5.4%
점 36
 
4.2%
33
 
3.9%
아 31
 
3.6%
이 30
 
3.5%
트 23
 
2.7%
스 17
 
2.0%
콘 15
 
1.8%
Other values (174) 427
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 768
90.1%
Space Separator 33
 
3.9%
Decimal Number 26
 
3.1%
Lowercase Letter 7
 
0.8%
Open Punctuation 6
 
0.7%
Close Punctuation 6
 
0.7%
Uppercase Letter 5
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 99
 
12.9%
안 95
 
12.4%
원 46
 
6.0%
점 36
 
4.7%
아 31
 
4.0%
이 30
 
3.9%
트 23
 
3.0%
스 17
 
2.2%
콘 15
 
2.0%
택 14
 
1.8%
Other values (155) 362
47.1%
Decimal Number
ValueCountFrequency (%)
0 12
46.2%
1 10
38.5%
5 2
 
7.7%
3 1
 
3.8%
2 1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
o 3
42.9%
k 1
 
14.3%
t 1
 
14.3%
r 1
 
14.3%
e 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
G 1
20.0%
N 1
20.0%
I 1
20.0%
L 1
20.0%
S 1
20.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 768
90.1%
Common 72
 
8.5%
Latin 12
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 99
 
12.9%
안 95
 
12.4%
원 46
 
6.0%
점 36
 
4.7%
아 31
 
4.0%
이 30
 
3.9%
트 23
 
3.0%
스 17
 
2.2%
콘 15
 
2.0%
택 14
 
1.8%
Other values (155) 362
47.1%
Latin
ValueCountFrequency (%)
o 3
25.0%
G 1
 
8.3%
N 1
 
8.3%
I 1
 
8.3%
L 1
 
8.3%
k 1
 
8.3%
S 1
 
8.3%
t 1
 
8.3%
r 1
 
8.3%
e 1
 
8.3%
Common
ValueCountFrequency (%)
33
45.8%
0 12
 
16.7%
1 10
 
13.9%
( 6
 
8.3%
) 6
 
8.3%
5 2
 
2.8%
3 1
 
1.4%
/ 1
 
1.4%
2 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 768
90.1%
ASCII 84
 
9.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 99
 
12.9%
안 95
 
12.4%
원 46
 
6.0%
점 36
 
4.7%
아 31
 
4.0%
이 30
 
3.9%
트 23
 
3.0%
스 17
 
2.2%
콘 15
 
2.0%
택 14
 
1.8%
Other values (155) 362
47.1%
ASCII
ValueCountFrequency (%)
33
39.3%
0 12
 
14.3%
1 10
 
11.9%
( 6
 
7.1%
) 6
 
7.1%
o 3
 
3.6%
5 2
 
2.4%
G 1
 
1.2%
N 1
 
1.2%
I 1
 
1.2%
Other values (9) 9
 
10.7%

소재지도로명주소
Text

Distinct110
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-13T02:11:10.814493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length27.315315
Min length20

Characters and Unicode

Total characters3032
Distinct characters136
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)98.2%

Sample

1st row대구광역시 북구 침산로 100, 상가동 1층 126호 (칠성동2가, 오페라삼정그린코아더베스트)
2nd row대구광역시 북구 학정로 436, DN트윈스 2차 빌딩 1층 102호 (구암동)
3rd row대구광역시 북구 연경중앙로 3, 대성플라자 2층 201호 (연경동)
4th row대구광역시 북구 태암남로11길 27-1, 1층 (구암동)
5th row대구광역시 북구 침산로 163, 상가동 2층 201호 (침산동, 현대아파트)
ValueCountFrequency (%)
대구광역시 111
 
17.1%
북구 111
 
17.1%
산격동 25
 
3.8%
1층 23
 
3.5%
침산동 15
 
2.3%
동천동 15
 
2.3%
태전동 14
 
2.2%
동북로 13
 
2.0%
칠곡중앙대로 11
 
1.7%
복현동 9
 
1.4%
Other values (206) 303
46.6%
2023-12-13T02:11:11.341817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
539
17.8%
구 231
 
7.6%
동 161
 
5.3%
대 145
 
4.8%
북 129
 
4.3%
1 125
 
4.1%
시 112
 
3.7%
로 112
 
3.7%
역 112
 
3.7%
) 111
 
3.7%
Other values (126) 1255
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1745
57.6%
Space Separator 539
 
17.8%
Decimal Number 452
 
14.9%
Close Punctuation 111
 
3.7%
Open Punctuation 111
 
3.7%
Other Punctuation 56
 
1.8%
Dash Punctuation 11
 
0.4%
Uppercase Letter 6
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 231
13.2%
동 161
 
9.2%
대 145
 
8.3%
북 129
 
7.4%
시 112
 
6.4%
로 112
 
6.4%
역 112
 
6.4%
광 111
 
6.4%
산 56
 
3.2%
층 34
 
1.9%
Other values (103) 542
31.1%
Decimal Number
ValueCountFrequency (%)
1 125
27.7%
2 72
15.9%
3 51
11.3%
0 43
 
9.5%
6 33
 
7.3%
4 32
 
7.1%
5 31
 
6.9%
7 24
 
5.3%
8 22
 
4.9%
9 19
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
D 1
16.7%
N 1
16.7%
B 1
16.7%
S 1
16.7%
K 1
16.7%
Y 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 55
98.2%
/ 1
 
1.8%
Space Separator
ValueCountFrequency (%)
539
100.0%
Close Punctuation
ValueCountFrequency (%)
) 111
100.0%
Open Punctuation
ValueCountFrequency (%)
( 111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1745
57.6%
Common 1281
42.2%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 231
13.2%
동 161
 
9.2%
대 145
 
8.3%
북 129
 
7.4%
시 112
 
6.4%
로 112
 
6.4%
역 112
 
6.4%
광 111
 
6.4%
산 56
 
3.2%
층 34
 
1.9%
Other values (103) 542
31.1%
Common
ValueCountFrequency (%)
539
42.1%
1 125
 
9.8%
) 111
 
8.7%
( 111
 
8.7%
2 72
 
5.6%
, 55
 
4.3%
3 51
 
4.0%
0 43
 
3.4%
6 33
 
2.6%
4 32
 
2.5%
Other values (7) 109
 
8.5%
Latin
ValueCountFrequency (%)
D 1
16.7%
N 1
16.7%
B 1
16.7%
S 1
16.7%
K 1
16.7%
Y 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1745
57.6%
ASCII 1287
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
539
41.9%
1 125
 
9.7%
) 111
 
8.6%
( 111
 
8.6%
2 72
 
5.6%
, 55
 
4.3%
3 51
 
4.0%
0 43
 
3.3%
6 33
 
2.6%
4 32
 
2.5%
Other values (13) 115
 
8.9%
Hangul
ValueCountFrequency (%)
구 231
13.2%
동 161
 
9.2%
대 145
 
8.3%
북 129
 
7.4%
시 112
 
6.4%
로 112
 
6.4%
역 112
 
6.4%
광 111
 
6.4%
산 56
 
3.2%
층 34
 
1.9%
Other values (103) 542
31.1%

전화번호
Text

Distinct74
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-13T02:11:11.591434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1332
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)65.8%

Sample

1st row000-000-0000
2nd row053-241-7900
3rd row053-981-1125
4th row000-000-0000
5th row000-000-0000
ValueCountFrequency (%)
000-000-0000 38
34.2%
053-958-1002 1
 
0.9%
053-323-9692 1
 
0.9%
053-959-0195 1
 
0.9%
053-959-0052 1
 
0.9%
053-954-2235 1
 
0.9%
053-942-5292 1
 
0.9%
053-323-0760 1
 
0.9%
053-359-1110 1
 
0.9%
053-341-3007 1
 
0.9%
Other values (64) 64
57.7%
2023-12-13T02:11:12.039334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 517
38.8%
- 222
16.7%
3 151
 
11.3%
5 148
 
11.1%
1 61
 
4.6%
2 52
 
3.9%
9 52
 
3.9%
4 48
 
3.6%
8 34
 
2.6%
6 25
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1110
83.3%
Dash Punctuation 222
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 517
46.6%
3 151
 
13.6%
5 148
 
13.3%
1 61
 
5.5%
2 52
 
4.7%
9 52
 
4.7%
4 48
 
4.3%
8 34
 
3.1%
6 25
 
2.3%
7 22
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 222
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1332
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 517
38.8%
- 222
16.7%
3 151
 
11.3%
5 148
 
11.1%
1 61
 
4.6%
2 52
 
3.9%
9 52
 
3.9%
4 48
 
3.6%
8 34
 
2.6%
6 25
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 517
38.8%
- 222
16.7%
3 151
 
11.3%
5 148
 
11.1%
1 61
 
4.6%
2 52
 
3.9%
9 52
 
3.9%
4 48
 
3.6%
8 34
 
2.6%
6 25
 
1.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct110
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.909164
Minimum35.875885
Maximum35.952218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T02:11:12.322844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.875885
5-th percentile35.880583
Q135.892452
median35.899748
Q335.930524
95-th percentile35.943597
Maximum35.952218
Range0.0763335
Interquartile range (IQR)0.0380722

Descriptive statistics

Standard deviation0.022115287
Coefficient of variation (CV)0.00061586751
Kurtosis-1.2954728
Mean35.909164
Median Absolute Deviation (MAD)0.0141182
Skewness0.42696014
Sum3985.9172
Variance0.00048908594
MonotonicityNot monotonic
2023-12-13T02:11:12.532963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8989134 2
 
1.8%
35.885196 1
 
0.9%
35.9440358 1
 
0.9%
35.8937782 1
 
0.9%
35.9004708 1
 
0.9%
35.9095238 1
 
0.9%
35.9215373 1
 
0.9%
35.8848858 1
 
0.9%
35.9423757 1
 
0.9%
35.8888084 1
 
0.9%
Other values (100) 100
90.1%
ValueCountFrequency (%)
35.8758849 1
0.9%
35.877907 1
0.9%
35.8784563 1
0.9%
35.8785065 1
0.9%
35.8800682 1
0.9%
35.8802748 1
0.9%
35.8808912 1
0.9%
35.8810081 1
0.9%
35.8814815 1
0.9%
35.8836868 1
0.9%
ValueCountFrequency (%)
35.9522184 1
0.9%
35.9448499 1
0.9%
35.9440358 1
0.9%
35.943942 1
0.9%
35.9437659 1
0.9%
35.9436336 1
0.9%
35.9435612 1
0.9%
35.9434732 1
0.9%
35.9434625 1
0.9%
35.9433567 1
0.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct109
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.58578
Minimum128.51455
Maximum128.62569
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T02:11:12.762369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.51455
5-th percentile128.54705
Q1128.56162
median128.59028
Q3128.6095
95-th percentile128.61866
Maximum128.62569
Range0.1111407
Interquartile range (IQR)0.04788705

Descriptive statistics

Standard deviation0.026394603
Coefficient of variation (CV)0.00020526844
Kurtosis-1.1113568
Mean128.58578
Median Absolute Deviation (MAD)0.022373
Skewness-0.34407425
Sum14273.022
Variance0.00069667505
MonotonicityNot monotonic
2023-12-13T02:11:12.975681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.612519 2
 
1.8%
128.5839734 2
 
1.8%
128.591318 1
 
0.9%
128.5620488 1
 
0.9%
128.5846254 1
 
0.9%
128.6163378 1
 
0.9%
128.5964084 1
 
0.9%
128.6139043 1
 
0.9%
128.5630877 1
 
0.9%
128.5918725 1
 
0.9%
Other values (99) 99
89.2%
ValueCountFrequency (%)
128.5145507 1
0.9%
128.5427833 1
0.9%
128.5445607 1
0.9%
128.546309 1
0.9%
128.54678 1
0.9%
128.5469143 1
0.9%
128.5471951 1
0.9%
128.5472647 1
0.9%
128.5474021 1
0.9%
128.5474827 1
0.9%
ValueCountFrequency (%)
128.6256914 1
0.9%
128.6228761 1
0.9%
128.6226033 1
0.9%
128.6216143 1
0.9%
128.6212532 1
0.9%
128.61873 1
0.9%
128.6185908 1
0.9%
128.6181001 1
0.9%
128.617999 1
0.9%
128.6179646 1
0.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
Minimum2022-10-19 00:00:00
Maximum2022-10-19 00:00:00
2023-12-13T02:11:13.130642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:13.273803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T02:11:09.509830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:09.314627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:09.639665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:11:09.419384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:11:13.372038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전화번호위도경도
전화번호1.0000.0000.721
위도0.0001.0000.797
경도0.7210.7971.000
2023-12-13T02:11:13.467767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.507
경도-0.5071.000

Missing values

2023-12-13T02:11:09.765915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:11:09.869989image/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

업소명소재지도로명주소전화번호위도경도데이터기준일자
0룩스토어 침산점대구광역시 북구 침산로 100, 상가동 1층 126호 (칠성동2가, 오페라삼정그린코아더베스트)000-000-000035.885196128.5913182022-10-19
1세컨페이스 칠곡점대구광역시 북구 학정로 436, DN트윈스 2차 빌딩 1층 102호 (구암동)053-241-790035.943473128.5641612022-10-19
2으뜸플러스안경 대구연경점대구광역시 북구 연경중앙로 3, 대성플라자 2층 201호 (연경동)053-981-112535.942993128.6179652022-10-19
3아이씨유대구광역시 북구 태암남로11길 27-1, 1층 (구암동)000-000-000035.927498128.5539622022-10-19
4이분의일안경대구광역시 북구 침산로 163, 상가동 2층 201호 (침산동, 현대아파트)000-000-000035.890477128.5898412022-10-19
5아이아대구광역시 북구 구암로60길 3-7, 1층 101호 (구암동)000-000-000035.937576128.5679882022-10-19
6눈플러스안경원대구광역시 북구 학남로3길 39, 1층 (학정동)000-000-000035.952218128.5675482022-10-19
7스펙트럼안경원대구광역시 북구 침산로 93, 스펙트럼시티 2층 305호 (칠성동2가)053-213-230535.885226128.589792022-10-19
81001안경콘택트대구광역시 북구 동북로 158, 1층 (산격동)053-954-100135.899521128.6098752022-10-19
9바른눈안경대구광역시 북구 연경중앙로 5, 중앙플라자 1층 105호, 106호 (연경동)000-000-000035.943273128.6179992022-10-19
업소명소재지도로명주소전화번호위도경도데이터기준일자
101애체안경타운대구광역시 북구 검단로 23 (산격동)053-958-280035.900061128.6150892022-10-19
102명안경원대구광역시 북구 동북로 186 (산격동)053-957-800835.898396128.6126562022-10-19
103우성 안경원대구광역시 북구 산격로 90-1 (산격동)053-471-542235.898167128.6069072022-10-19
104아이피아안경원대구광역시 북구 칠곡중앙대로 463 (관음동)053-312-338535.937199128.5488362022-10-19
105보보당안경원대구광역시 북구 고성로 154 (고성동2가)053-352-646835.881008128.5825312022-10-19
106새신용사안경원대구광역시 북구 칠곡중앙대로 529 (읍내동)053-312-243735.942979128.5504732022-10-19
107귀빈당 안경원대구광역시 북구 동북로 246 (복현동)053-952-022235.895059128.6177572022-10-19
108서독안경원대구광역시 북구 팔달로 173-1 (노원동3가)053-352-284735.888918128.5691912022-10-19
109윤 안경원대구광역시 북구 신암로 63 (대현동)053-941-414635.877907128.6073062022-10-19
110소보안경원대구광역시 북구 성북로 3 (침산동)053-355-125135.890214128.5839732022-10-19