Overview

Dataset statistics

Number of variables5
Number of observations92
Missing cells3
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory43.4 B

Variable types

Numeric2
Text3

Dataset

Description부평구 안경업소 현황(안경업소명칭 사업장소재지(도로명) 사업장전화번호)예) 1,2층에 안경,인천광역시 부평구 체육관로 14, 삼산지구 복합시설 205호 (삼산동),032-724-8686
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3045124&srcSe=7661IVAWM27C61E190

Alerts

전화번호 has 3 (3.3%) missing valuesMissing
순번 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2024-03-18 02:04:23.836911
Analysis finished2024-03-18 02:04:24.842769
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.5
Minimum1
Maximum92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2024-03-18T11:04:24.903104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.55
Q123.75
median46.5
Q369.25
95-th percentile87.45
Maximum92
Range91
Interquartile range (IQR)45.5

Descriptive statistics

Standard deviation26.70206
Coefficient of variation (CV)0.57423785
Kurtosis-1.2
Mean46.5
Median Absolute Deviation (MAD)23
Skewness0
Sum4278
Variance713
MonotonicityStrictly increasing
2024-03-18T11:04:25.249938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
60 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%

안경업소명칭
Text

Distinct90
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size868.0 B
2024-03-18T11:04:25.460114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length7.9673913
Min length4

Characters and Unicode

Total characters733
Distinct characters173
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

Unique88 ?
Unique (%)95.7%

Sample

1st row으뜸플러스안경 청천점
2nd row으뜸50안경 동암역점
3rd row새로안안경 부평센터
4th row안테나안경원
5th row이목안경원
ValueCountFrequency (%)
안경 5
 
4.2%
부평점 3
 
2.5%
행복한안경 2
 
1.7%
다비치안경 2
 
1.7%
안경박사 2
 
1.7%
으뜸플러스안경 2
 
1.7%
클리어안경(clear 2
 
1.7%
렌즈미 2
 
1.7%
오렌즈 2
 
1.7%
안경콘택트 2
 
1.7%
Other values (96) 96
80.0%
2024-03-18T11:04:25.788800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 80
 
10.9%
경 78
 
10.6%
28
 
3.8%
스 23
 
3.1%
점 22
 
3.0%
이 18
 
2.5%
원 18
 
2.5%
아 17
 
2.3%
부 17
 
2.3%
평 17
 
2.3%
Other values (163) 415
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 621
84.7%
Uppercase Letter 32
 
4.4%
Space Separator 28
 
3.8%
Decimal Number 17
 
2.3%
Lowercase Letter 12
 
1.6%
Close Punctuation 11
 
1.5%
Open Punctuation 11
 
1.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 80
 
12.9%
경 78
 
12.6%
스 23
 
3.7%
점 22
 
3.5%
이 18
 
2.9%
원 18
 
2.9%
아 17
 
2.7%
부 17
 
2.7%
평 17
 
2.7%
트 15
 
2.4%
Other values (131) 316
50.9%
Uppercase Letter
ValueCountFrequency (%)
E 5
15.6%
C 5
15.6%
T 3
9.4%
O 3
9.4%
A 3
9.4%
G 2
 
6.2%
P 2
 
6.2%
R 2
 
6.2%
L 2
 
6.2%
M 1
 
3.1%
Other values (4) 4
12.5%
Lowercase Letter
ValueCountFrequency (%)
i 3
25.0%
e 2
16.7%
p 1
 
8.3%
t 1
 
8.3%
q 1
 
8.3%
u 1
 
8.3%
s 1
 
8.3%
a 1
 
8.3%
m 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
0 6
35.3%
1 6
35.3%
2 2
 
11.8%
5 2
 
11.8%
7 1
 
5.9%
Space Separator
ValueCountFrequency (%)
28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 621
84.7%
Common 68
 
9.3%
Latin 44
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 80
 
12.9%
경 78
 
12.6%
스 23
 
3.7%
점 22
 
3.5%
이 18
 
2.9%
원 18
 
2.9%
아 17
 
2.7%
부 17
 
2.7%
평 17
 
2.7%
트 15
 
2.4%
Other values (131) 316
50.9%
Latin
ValueCountFrequency (%)
E 5
 
11.4%
C 5
 
11.4%
i 3
 
6.8%
T 3
 
6.8%
O 3
 
6.8%
A 3
 
6.8%
G 2
 
4.5%
P 2
 
4.5%
R 2
 
4.5%
e 2
 
4.5%
Other values (13) 14
31.8%
Common
ValueCountFrequency (%)
28
41.2%
) 11
 
16.2%
( 11
 
16.2%
0 6
 
8.8%
1 6
 
8.8%
2 2
 
2.9%
5 2
 
2.9%
. 1
 
1.5%
7 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 621
84.7%
ASCII 112
 
15.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 80
 
12.9%
경 78
 
12.6%
스 23
 
3.7%
점 22
 
3.5%
이 18
 
2.9%
원 18
 
2.9%
아 17
 
2.7%
부 17
 
2.7%
평 17
 
2.7%
트 15
 
2.4%
Other values (131) 316
50.9%
ASCII
ValueCountFrequency (%)
28
25.0%
) 11
 
9.8%
( 11
 
9.8%
0 6
 
5.4%
1 6
 
5.4%
E 5
 
4.5%
C 5
 
4.5%
i 3
 
2.7%
T 3
 
2.7%
O 3
 
2.7%
Other values (22) 31
27.7%

소재지(도로명)
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2024-03-18T11:04:26.149999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length41.5
Mean length31.01087
Min length22

Characters and Unicode

Total characters2853
Distinct characters150
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

Unique92 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 산청로 60, 상가2동 209호 (산곡동, 부평캐슬&더샵퍼스트)
2nd row인천광역시 부평구 열우물로 40-1, 1층 (십정동)
3rd row인천광역시 부평구 부평대로 55, 국천빌딩 901 일부호 (부평동)
4th row인천광역시 부평구 경인로 947, 태성메디칼 110호, 111호 (부평동)
5th row인천광역시 부평구 주부토로 236, A동 134호, 135호 (갈산동)
ValueCountFrequency (%)
인천광역시 92
 
15.9%
부평구 92
 
15.9%
부평동 35
 
6.0%
1층 17
 
2.9%
삼산동 14
 
2.4%
산곡동 12
 
2.1%
부개동 12
 
2.1%
부평대로 10
 
1.7%
경원대로 8
 
1.4%
청천동 7
 
1.2%
Other values (206) 281
48.4%
2024-03-18T11:04:26.670011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
489
 
17.1%
부 177
 
6.2%
평 148
 
5.2%
1 114
 
4.0%
동 107
 
3.8%
천 102
 
3.6%
시 98
 
3.4%
인 98
 
3.4%
광 96
 
3.4%
역 95
 
3.3%
Other values (140) 1329
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1653
57.9%
Space Separator 489
 
17.1%
Decimal Number 427
 
15.0%
Open Punctuation 93
 
3.3%
Close Punctuation 93
 
3.3%
Other Punctuation 85
 
3.0%
Dash Punctuation 8
 
0.3%
Uppercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 177
 
10.7%
평 148
 
9.0%
동 107
 
6.5%
천 102
 
6.2%
시 98
 
5.9%
인 98
 
5.9%
광 96
 
5.8%
역 95
 
5.7%
구 93
 
5.6%
로 92
 
5.6%
Other values (120) 547
33.1%
Decimal Number
ValueCountFrequency (%)
1 114
26.7%
2 66
15.5%
0 48
11.2%
4 46
10.8%
3 43
 
10.1%
5 36
 
8.4%
6 25
 
5.9%
8 20
 
4.7%
7 16
 
3.7%
9 13
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
C 1
25.0%
B 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 84
98.8%
& 1
 
1.2%
Space Separator
ValueCountFrequency (%)
489
100.0%
Open Punctuation
ValueCountFrequency (%)
( 93
100.0%
Close Punctuation
ValueCountFrequency (%)
) 93
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1653
57.9%
Common 1196
41.9%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 177
 
10.7%
평 148
 
9.0%
동 107
 
6.5%
천 102
 
6.2%
시 98
 
5.9%
인 98
 
5.9%
광 96
 
5.8%
역 95
 
5.7%
구 93
 
5.6%
로 92
 
5.6%
Other values (120) 547
33.1%
Common
ValueCountFrequency (%)
489
40.9%
1 114
 
9.5%
( 93
 
7.8%
) 93
 
7.8%
, 84
 
7.0%
2 66
 
5.5%
0 48
 
4.0%
4 46
 
3.8%
3 43
 
3.6%
5 36
 
3.0%
Other values (7) 84
 
7.0%
Latin
ValueCountFrequency (%)
A 2
50.0%
C 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1653
57.9%
ASCII 1200
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
489
40.8%
1 114
 
9.5%
( 93
 
7.8%
) 93
 
7.8%
, 84
 
7.0%
2 66
 
5.5%
0 48
 
4.0%
4 46
 
3.8%
3 43
 
3.6%
5 36
 
3.0%
Other values (10) 88
 
7.3%
Hangul
ValueCountFrequency (%)
부 177
 
10.7%
평 148
 
9.0%
동 107
 
6.5%
천 102
 
6.2%
시 98
 
5.9%
인 98
 
5.9%
광 96
 
5.8%
역 95
 
5.7%
구 93
 
5.6%
로 92
 
5.6%
Other values (120) 547
33.1%

전화번호
Text

MISSING 

Distinct88
Distinct (%)98.9%
Missing3
Missing (%)3.3%
Memory size868.0 B
2024-03-18T11:04:26.877944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.775281
Min length1

Characters and Unicode

Total characters1048
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)97.8%

Sample

1st row032-501-4669
2nd row032-432-5050
3rd row032-508-1002
4th row
5th row032-330-9001
ValueCountFrequency (%)
032-503-0853 1
 
1.1%
032-525-3330 1
 
1.1%
032-501-4669 1
 
1.1%
032-511-0818 1
 
1.1%
032-513-0101 1
 
1.1%
032-270-2950 1
 
1.1%
032-527-5339 1
 
1.1%
032-515-0801 1
 
1.1%
032-525-2491 1
 
1.1%
032-521-1100 1
 
1.1%
Other values (77) 77
88.5%
2024-03-18T11:04:27.241023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 200
19.1%
- 174
16.6%
2 158
15.1%
3 140
13.4%
5 113
10.8%
1 77
 
7.3%
7 54
 
5.2%
8 37
 
3.5%
6 33
 
3.1%
4 31
 
3.0%
Other values (2) 31
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 872
83.2%
Dash Punctuation 174
 
16.6%
Space Separator 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 200
22.9%
2 158
18.1%
3 140
16.1%
5 113
13.0%
1 77
 
8.8%
7 54
 
6.2%
8 37
 
4.2%
6 33
 
3.8%
4 31
 
3.6%
9 29
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1048
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 200
19.1%
- 174
16.6%
2 158
15.1%
3 140
13.4%
5 113
10.8%
1 77
 
7.3%
7 54
 
5.2%
8 37
 
3.5%
6 33
 
3.1%
4 31
 
3.0%
Other values (2) 31
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1048
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 200
19.1%
- 174
16.6%
2 158
15.1%
3 140
13.4%
5 113
10.8%
1 77
 
7.3%
7 54
 
5.2%
8 37
 
3.5%
6 33
 
3.1%
4 31
 
3.0%
Other values (2) 31
 
3.0%

우편번호
Real number (ℝ)

Distinct50
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21377.804
Minimum21302
Maximum21452
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2024-03-18T11:04:27.391983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21302
5-th percentile21312.55
Q121344
median21389
Q321404
95-th percentile21433.15
Maximum21452
Range150
Interquartile range (IQR)60

Descriptive statistics

Standard deviation38.234165
Coefficient of variation (CV)0.0017884982
Kurtosis-0.7890398
Mean21377.804
Median Absolute Deviation (MAD)25.5
Skewness-0.32185048
Sum1966758
Variance1461.8514
MonotonicityNot monotonic
2024-03-18T11:04:27.510076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21344 8
 
8.7%
21394 7
 
7.6%
21404 7
 
7.6%
21405 4
 
4.3%
21388 4
 
4.3%
21377 4
 
4.3%
21419 3
 
3.3%
21389 3
 
3.3%
21312 2
 
2.2%
21445 2
 
2.2%
Other values (40) 48
52.2%
ValueCountFrequency (%)
21302 1
1.1%
21304 1
1.1%
21305 1
1.1%
21312 2
2.2%
21313 1
1.1%
21316 1
1.1%
21317 1
1.1%
21318 2
2.2%
21319 1
1.1%
21321 1
1.1%
ValueCountFrequency (%)
21452 1
 
1.1%
21450 1
 
1.1%
21445 2
2.2%
21437 1
 
1.1%
21430 1
 
1.1%
21426 2
2.2%
21424 1
 
1.1%
21419 3
3.3%
21416 1
 
1.1%
21415 1
 
1.1%

Interactions

2024-03-18T11:04:24.567172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:04:24.446053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:04:24.633121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:04:24.501047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T11:04:27.597402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번안경업소명칭소재지(도로명)전화번호우편번호
순번1.0000.8701.0000.9310.404
안경업소명칭0.8701.0001.0000.9960.672
소재지(도로명)1.0001.0001.0001.0001.000
전화번호0.9310.9961.0001.0000.963
우편번호0.4040.6721.0000.9631.000
2024-03-18T11:04:27.678410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번우편번호
순번1.0000.004
우편번호0.0041.000

Missing values

2024-03-18T11:04:24.730214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T11:04:24.810473image/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

순번안경업소명칭소재지(도로명)전화번호우편번호
01으뜸플러스안경 청천점인천광역시 부평구 산청로 60, 상가2동 209호 (산곡동, 부평캐슬&더샵퍼스트)032-501-466921305
12으뜸50안경 동암역점인천광역시 부평구 열우물로 40-1, 1층 (십정동)032-432-505021445
23새로안안경 부평센터인천광역시 부평구 부평대로 55, 국천빌딩 901 일부호 (부평동)032-508-100221388
34안테나안경원인천광역시 부평구 경인로 947, 태성메디칼 110호, 111호 (부평동)<NA>21407
45이목안경원인천광역시 부평구 주부토로 236, A동 134호, 135호 (갈산동)21330
56으뜸플러스인천삼산점인천광역시 부평구 충선로203번길 24, 삼산프라자 3층 304호 (삼산동)032-330-900121344
67으뜸50안경인천부평역점인천광역시 부평구 부평대로 24, 가나빌딩 2층 202호 (부평동)032-565-011021394
78바른안경인천광역시 부평구 부흥로 416, 1층 102일부호, 103호 (부개동, 골드마운틴)032-502-555221398
89글라스윈드안경인천광역시 부평구 마장로272번길 76, 상가동 103호 (산곡동, 경남아파트)032-507-100121376
910제임스옵티크(James Optique)인천광역시 부평구 시장로 13-1, 2동 1,2층 (부평동)032-511-897721394
순번안경업소명칭소재지(도로명)전화번호우편번호
8283한일안경인천광역시 부평구 부평대로 12 (부평동)032-515-722021394
8384한국안경인천광역시 부평구 경인로1024번길 42 (부개동)032-519-732921426
8485아이아트안경인천광역시 부평구 대정로 45 (부평동)032-503-318121391
8586탑클래스 안경체인(동암역점)인천광역시 부평구 열우물로 29 (십정동)032-432-010021452
8687연세안경인천광역시 부평구 경인로1104번길 6 (부개동)032-511-948921419
8788안경상회부평 갈산점인천광역시 부평구 주부토로 260 (갈산동)<NA>21317
88891001안경원인천광역시 부평구 부평문화로 216, 상가1층 4,5,6호 (부개동, 부개역 코오롱 하늘채)032-524-100121401
8990엘림안경원인천광역시 부평구 배곶로 59 (십정동)032-431-480521450
9091클리어안경(CLEAR OPTiC)부평청천점인천광역시 부평구 청중로 66 (청천동)032-502-147321312
9192아이디안경인천광역시 부평구 부평대로 25 (부평동)032-502-337721389