Overview

Dataset statistics

Number of variables17
Number of observations97
Missing cells19
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.2 KiB
Average record size in memory150.4 B

Variable types

Numeric1
DateTime1
Text3
Categorical12

Dataset

Description김해시 안경업소 현황(사업자명, 영업상태, 전화번호, 주소, 시력표수, 표본렌즈수, 측정의자수, 동공거리측정기수, 정점굴절계기수, 조제용연마기수, 렌즈절단기수, 가열기수, 안경세척기수)
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15033412

Alerts

표본렌즈수 is highly overall correlated with 시력표수 and 10 other fieldsHigh correlation
시험테와시험렌즈세트 is highly overall correlated with 동공거리계 and 6 other fieldsHigh correlation
조제용연마기수 is highly overall correlated with 순번 and 11 other fieldsHigh correlation
렌즈절단기 is highly overall correlated with 순번 and 11 other fieldsHigh correlation
측정의자수 is highly overall correlated with 시력표수 and 10 other fieldsHigh correlation
자동굴절검사기 is highly overall correlated with 렌즈절단기 and 5 other fieldsHigh correlation
안경세척기수 is highly overall correlated with 시력표수 and 10 other fieldsHigh correlation
시력검사세트 is highly overall correlated with 렌즈절단기 and 5 other fieldsHigh correlation
시력표수 is highly overall correlated with 동공거리계 and 7 other fieldsHigh correlation
가열기수 is highly overall correlated with 순번 and 11 other fieldsHigh correlation
동공거리계 is highly overall correlated with 시력표수 and 8 other fieldsHigh correlation
렌즈정점굴절력계 is highly overall correlated with 시력표수 and 7 other fieldsHigh correlation
순번 is highly overall correlated with 렌즈절단기 and 2 other fieldsHigh correlation
시력검사세트 is highly imbalanced (68.9%)Imbalance
시험테와시험렌즈세트 is highly imbalanced (71.3%)Imbalance
자동굴절검사기 is highly imbalanced (68.9%)Imbalance
사업장전화번호 has 19 (19.6%) missing valuesMissing
순번 has unique valuesUnique
안경업소명칭 has unique valuesUnique
사업장소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:02:20.166624
Analysis finished2023-12-10 23:02:22.022073
Duration1.86 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49
Minimum1
Maximum97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-11T08:02:22.114318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.8
Q125
median49
Q373
95-th percentile92.2
Maximum97
Range96
Interquartile range (IQR)48

Descriptive statistics

Standard deviation28.145456
Coefficient of variation (CV)0.57439705
Kurtosis-1.2
Mean49
Median Absolute Deviation (MAD)24
Skewness0
Sum4753
Variance792.16667
MonotonicityStrictly increasing
2023-12-11T08:02:22.302372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
74 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
66 1
 
1.0%
65 1
 
1.0%
Other values (87) 87
89.7%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%
89 1
1.0%
88 1
1.0%

등록일자
Date

Distinct95
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size908.0 B
Minimum1993-12-13 00:00:00
Maximum2022-08-08 00:00:00
2023-12-11T08:02:22.500229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:22.634360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

안경업소명칭
Text

UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-12-11T08:02:22.902498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length8.3814433
Min length3

Characters and Unicode

Total characters813
Distinct characters157
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

Unique97 ?
Unique (%)100.0%

Sample

1st row퍼스널옵티컬
2nd row안경창고 싸군 김해구산삼계점
3rd row지니스 김해율하중앙
4th row더존안경 김해율하점
5th row지니스안경 진영신도시점
ValueCountFrequency (%)
안경원 4
 
2.8%
렌즈미 3
 
2.1%
다비치안경 3
 
2.1%
김해점 3
 
2.1%
안경 3
 
2.1%
김해율하점 3
 
2.1%
이노티안경 3
 
2.1%
부원점 2
 
1.4%
글라스미 2
 
1.4%
지니스안경 2
 
1.4%
Other values (110) 113
80.1%
2023-12-11T08:02:23.353793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 87
 
10.7%
안 86
 
10.6%
점 46
 
5.7%
44
 
5.4%
원 33
 
4.1%
김 25
 
3.1%
이 25
 
3.1%
해 25
 
3.1%
스 25
 
3.1%
아 11
 
1.4%
Other values (147) 406
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 731
89.9%
Space Separator 44
 
5.4%
Decimal Number 16
 
2.0%
Uppercase Letter 9
 
1.1%
Open Punctuation 5
 
0.6%
Close Punctuation 5
 
0.6%
Other Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 87
 
11.9%
안 86
 
11.8%
점 46
 
6.3%
원 33
 
4.5%
김 25
 
3.4%
이 25
 
3.4%
해 25
 
3.4%
스 25
 
3.4%
아 11
 
1.5%
렌 9
 
1.2%
Other values (130) 359
49.1%
Uppercase Letter
ValueCountFrequency (%)
O 1
11.1%
E 1
11.1%
A 1
11.1%
L 1
11.1%
I 1
11.1%
V 1
11.1%
Y 1
11.1%
K 1
11.1%
W 1
11.1%
Decimal Number
ValueCountFrequency (%)
0 8
50.0%
1 6
37.5%
5 2
 
12.5%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 731
89.9%
Common 73
 
9.0%
Latin 9
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 87
 
11.9%
안 86
 
11.8%
점 46
 
6.3%
원 33
 
4.5%
김 25
 
3.4%
이 25
 
3.4%
해 25
 
3.4%
스 25
 
3.4%
아 11
 
1.5%
렌 9
 
1.2%
Other values (130) 359
49.1%
Latin
ValueCountFrequency (%)
O 1
11.1%
E 1
11.1%
A 1
11.1%
L 1
11.1%
I 1
11.1%
V 1
11.1%
Y 1
11.1%
K 1
11.1%
W 1
11.1%
Common
ValueCountFrequency (%)
44
60.3%
0 8
 
11.0%
1 6
 
8.2%
( 5
 
6.8%
) 5
 
6.8%
5 2
 
2.7%
& 2
 
2.7%
. 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 731
89.9%
ASCII 82
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 87
 
11.9%
안 86
 
11.8%
점 46
 
6.3%
원 33
 
4.5%
김 25
 
3.4%
이 25
 
3.4%
해 25
 
3.4%
스 25
 
3.4%
아 11
 
1.5%
렌 9
 
1.2%
Other values (130) 359
49.1%
ASCII
ValueCountFrequency (%)
44
53.7%
0 8
 
9.8%
1 6
 
7.3%
( 5
 
6.1%
) 5
 
6.1%
5 2
 
2.4%
& 2
 
2.4%
O 1
 
1.2%
. 1
 
1.2%
E 1
 
1.2%
Other values (7) 7
 
8.5%

사업장소재지(도로명)
Text

UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-12-11T08:02:23.669138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length37
Mean length27.597938
Min length18

Characters and Unicode

Total characters2677
Distinct characters144
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

Unique97 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 율하카페길 77-9, 1층 (관동동)
2nd row경상남도 김해시 가락로 278, 101호 (구산동)
3rd row경상남도 김해시 율하3로 37, 경보센텀 1층 105호 (율하동)
4th row경상남도 김해시 율하6로 64, 1층 105,106,107호 (장유동)
5th row경상남도 김해시 진영읍 장등로19번길 39, 1층 102호
ValueCountFrequency (%)
경상남도 97
 
17.4%
김해시 97
 
17.4%
1층 17
 
3.1%
진영읍 10
 
1.8%
율하동 9
 
1.6%
가락로 9
 
1.6%
외동 9
 
1.6%
어방동 8
 
1.4%
인제로 8
 
1.4%
대청동 7
 
1.3%
Other values (190) 285
51.3%
2023-12-11T08:02:24.135312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
459
 
17.1%
1 133
 
5.0%
해 108
 
4.0%
김 106
 
4.0%
상 104
 
3.9%
동 100
 
3.7%
경 99
 
3.7%
시 98
 
3.7%
도 97
 
3.6%
로 97
 
3.6%
Other values (134) 1276
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1521
56.8%
Space Separator 459
 
17.1%
Decimal Number 454
 
17.0%
Open Punctuation 88
 
3.3%
Close Punctuation 88
 
3.3%
Other Punctuation 55
 
2.1%
Dash Punctuation 10
 
0.4%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 108
 
7.1%
김 106
 
7.0%
상 104
 
6.8%
동 100
 
6.6%
경 99
 
6.5%
시 98
 
6.4%
도 97
 
6.4%
로 97
 
6.4%
남 97
 
6.4%
번 31
 
2.0%
Other values (117) 584
38.4%
Decimal Number
ValueCountFrequency (%)
1 133
29.3%
2 63
13.9%
0 48
 
10.6%
3 45
 
9.9%
6 36
 
7.9%
4 31
 
6.8%
9 27
 
5.9%
5 26
 
5.7%
7 23
 
5.1%
8 22
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
459
100.0%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 88
100.0%
Other Punctuation
ValueCountFrequency (%)
, 55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1521
56.8%
Common 1154
43.1%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 108
 
7.1%
김 106
 
7.0%
상 104
 
6.8%
동 100
 
6.6%
경 99
 
6.5%
시 98
 
6.4%
도 97
 
6.4%
로 97
 
6.4%
남 97
 
6.4%
번 31
 
2.0%
Other values (117) 584
38.4%
Common
ValueCountFrequency (%)
459
39.8%
1 133
 
11.5%
( 88
 
7.6%
) 88
 
7.6%
2 63
 
5.5%
, 55
 
4.8%
0 48
 
4.2%
3 45
 
3.9%
6 36
 
3.1%
4 31
 
2.7%
Other values (5) 108
 
9.4%
Latin
ValueCountFrequency (%)
D 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1521
56.8%
ASCII 1156
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
459
39.7%
1 133
 
11.5%
( 88
 
7.6%
) 88
 
7.6%
2 63
 
5.4%
, 55
 
4.8%
0 48
 
4.2%
3 45
 
3.9%
6 36
 
3.1%
4 31
 
2.7%
Other values (7) 110
 
9.5%
Hangul
ValueCountFrequency (%)
해 108
 
7.1%
김 106
 
7.0%
상 104
 
6.8%
동 100
 
6.6%
경 99
 
6.5%
시 98
 
6.4%
도 97
 
6.4%
로 97
 
6.4%
남 97
 
6.4%
번 31
 
2.0%
Other values (117) 584
38.4%

사업장전화번호
Text

MISSING 

Distinct78
Distinct (%)100.0%
Missing19
Missing (%)19.6%
Memory size908.0 B
2023-12-11T08:02:24.387145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.012821
Min length12

Characters and Unicode

Total characters937
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

Unique78 ?
Unique (%)100.0%

Sample

1st row055-337-2022
2nd row055-337-4969
3rd row055-324-2235
4th row055-343-4969
5th row055-337-9462
ValueCountFrequency (%)
055 2
 
2.5%
055-346-0006 1
 
1.2%
055-312-1113 1
 
1.2%
055-346-1994 1
 
1.2%
055-331-2266 1
 
1.2%
055-312-2640 1
 
1.2%
055-327-7581 1
 
1.2%
055-326-2319 1
 
1.2%
055-314-9191 1
 
1.2%
055-325-3347 1
 
1.2%
Other values (70) 70
86.4%
2023-12-11T08:02:24.778795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 189
20.2%
- 153
16.3%
3 151
16.1%
0 135
14.4%
2 87
9.3%
1 50
 
5.3%
4 43
 
4.6%
6 37
 
3.9%
8 37
 
3.9%
9 27
 
2.9%
Other values (2) 28
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 781
83.4%
Dash Punctuation 153
 
16.3%
Space Separator 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 189
24.2%
3 151
19.3%
0 135
17.3%
2 87
11.1%
1 50
 
6.4%
4 43
 
5.5%
6 37
 
4.7%
8 37
 
4.7%
9 27
 
3.5%
7 25
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 153
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 937
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 189
20.2%
- 153
16.3%
3 151
16.1%
0 135
14.4%
2 87
9.3%
1 50
 
5.3%
4 43
 
4.6%
6 37
 
3.9%
8 37
 
3.9%
9 27
 
2.9%
Other values (2) 28
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 937
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 189
20.2%
- 153
16.3%
3 151
16.1%
0 135
14.4%
2 87
9.3%
1 50
 
5.3%
4 43
 
4.6%
6 37
 
3.9%
8 37
 
3.9%
9 27
 
2.9%
Other values (2) 28
 
3.0%

시력표수
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
1
61 
0
27 
2
7 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 61
62.9%
0 27
27.8%
2 7
 
7.2%
3 2
 
2.1%

Length

2023-12-11T08:02:24.947765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:25.054570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 61
62.9%
0 27
27.8%
2 7
 
7.2%
3 2
 
2.1%

시력검사세트
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
<NA>
88 
1
 
8
2
 
1

Length

Max length4
Median length4
Mean length3.7216495
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
<NA> 88
90.7%
1 8
 
8.2%
2 1
 
1.0%

Length

2023-12-11T08:02:25.158522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:25.265641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
90.7%
1 8
 
8.2%
2 1
 
1.0%

시험테와시험렌즈세트
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
<NA>
89 
1
 
7
2
 
1

Length

Max length4
Median length4
Mean length3.7525773
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row1
2nd row1
3rd row<NA>
4th row2
5th row1

Common Values

ValueCountFrequency (%)
<NA> 89
91.8%
1 7
 
7.2%
2 1
 
1.0%

Length

2023-12-11T08:02:25.392353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:25.496567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
91.8%
1 7
 
7.2%
2 1
 
1.0%

동공거리계
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
1
64 
0
27 
2
 
5
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row1
2nd row1
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 64
66.0%
0 27
27.8%
2 5
 
5.2%
5 1
 
1.0%

Length

2023-12-11T08:02:25.664729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:25.762755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 64
66.0%
0 27
27.8%
2 5
 
5.2%
5 1
 
1.0%

자동굴절검사기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
<NA>
88 
1
 
8
2
 
1

Length

Max length4
Median length4
Mean length3.7216495
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
<NA> 88
90.7%
1 8
 
8.2%
2 1
 
1.0%

Length

2023-12-11T08:02:25.874311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:25.974904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
90.7%
1 8
 
8.2%
2 1
 
1.0%

렌즈정점굴절력계
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size908.0 B
1
48 
0
27 
2
17 
3
 
4
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row2
2nd row1
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 48
49.5%
0 27
27.8%
2 17
 
17.5%
3 4
 
4.1%
4 1
 
1.0%

Length

2023-12-11T08:02:26.081754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:26.204106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 48
49.5%
0 27
27.8%
2 17
 
17.5%
3 4
 
4.1%
4 1
 
1.0%

렌즈절단기
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
1
62 
0
27 
<NA>
8 

Length

Max length4
Median length1
Mean length1.2474227
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
1 62
63.9%
0 27
27.8%
<NA> 8
 
8.2%

Length

2023-12-11T08:02:26.355997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:26.503164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 62
63.9%
0 27
27.8%
na 8
 
8.2%

표본렌즈수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size908.0 B
1
58 
0
27 
<NA>
7 
2
 
4
5
 
1

Length

Max length4
Median length1
Mean length1.2164948
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
1 58
59.8%
0 27
27.8%
<NA> 7
 
7.2%
2 4
 
4.1%
5 1
 
1.0%

Length

2023-12-11T08:02:26.628519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:26.751720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 58
59.8%
0 27
27.8%
na 7
 
7.2%
2 4
 
4.1%
5 1
 
1.0%

측정의자수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size908.0 B
1
57 
0
27 
<NA>
7 
2
 
5
12
 
1

Length

Max length4
Median length1
Mean length1.2268041
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
1 57
58.8%
0 27
27.8%
<NA> 7
 
7.2%
2 5
 
5.2%
12 1
 
1.0%

Length

2023-12-11T08:02:26.898868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:27.000970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 57
58.8%
0 27
27.8%
na 7
 
7.2%
2 5
 
5.2%
12 1
 
1.0%

안경세척기수
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size908.0 B
1
41 
0
27 
2
18 
<NA>
8 
3
 
2

Length

Max length4
Median length1
Mean length1.2474227
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
1 41
42.3%
0 27
27.8%
2 18
18.6%
<NA> 8
 
8.2%
3 2
 
2.1%
5 1
 
1.0%

Length

2023-12-11T08:02:27.369368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:27.471756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 41
42.3%
0 27
27.8%
2 18
18.6%
na 8
 
8.2%
3 2
 
2.1%
5 1
 
1.0%

가열기수
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
1
48 
0
27 
2
14 
<NA>
8 

Length

Max length4
Median length1
Mean length1.2474227
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
1 48
49.5%
0 27
27.8%
2 14
 
14.4%
<NA> 8
 
8.2%

Length

2023-12-11T08:02:27.595343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:27.706513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 48
49.5%
0 27
27.8%
2 14
 
14.4%
na 8
 
8.2%

조제용연마기수
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
1
62 
0
27 
<NA>
8 

Length

Max length4
Median length1
Mean length1.2474227
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
1 62
63.9%
0 27
27.8%
<NA> 8
 
8.2%

Length

2023-12-11T08:02:27.814497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:27.921139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 62
63.9%
0 27
27.8%
na 8
 
8.2%

Interactions

2023-12-11T08:02:21.501309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:02:28.024717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번등록일자안경업소명칭사업장소재지(도로명)사업장전화번호시력표수시력검사세트시험테와시험렌즈세트동공거리계자동굴절검사기렌즈정점굴절력계렌즈절단기표본렌즈수측정의자수안경세척기수가열기수조제용연마기수
순번1.0001.0001.0001.0001.0000.6980.0000.0000.6610.0000.7180.9320.6390.6680.7570.7280.932
등록일자1.0001.0001.0001.0001.0000.0001.0001.0000.0001.0000.9150.5580.0000.0000.9820.9360.558
안경업소명칭1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사업장소재지(도로명)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사업장전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시력표수0.6980.0001.0001.0001.0001.0000.4550.3960.9180.4550.6671.0000.9720.9800.7460.6701.000
시력검사세트0.0001.0001.0001.0001.0000.4551.0000.3960.0000.4550.000NaNNaNNaNNaNNaNNaN
시험테와시험렌즈세트0.0001.0001.0001.0001.0000.3960.3961.000NaN0.3960.000NaNNaNNaNNaNNaNNaN
동공거리계0.6610.0001.0001.0001.0000.9180.000NaN1.0000.0000.6621.0000.9170.9400.6380.6681.000
자동굴절검사기0.0001.0001.0001.0001.0000.4550.4550.3960.0001.0000.000NaNNaNNaNNaNNaNNaN
렌즈정점굴절력계0.7180.9151.0001.0001.0000.6670.0000.0000.6620.0001.0001.0000.7280.7150.9490.7581.000
렌즈절단기0.9320.5581.0001.0001.0001.000NaNNaN1.000NaN1.0001.0001.0001.0001.0001.0000.999
표본렌즈수0.6390.0001.0001.0001.0000.972NaNNaN0.917NaN0.7281.0001.0000.9940.8370.6761.000
측정의자수0.6680.0001.0001.0001.0000.980NaNNaN0.940NaN0.7151.0000.9941.0000.8360.6681.000
안경세척기수0.7570.9821.0001.0001.0000.746NaNNaN0.638NaN0.9491.0000.8370.8361.0000.8581.000
가열기수0.7280.9361.0001.0001.0000.670NaNNaN0.668NaN0.7581.0000.6760.6680.8581.0001.000
조제용연마기수0.9320.5581.0001.0001.0001.000NaNNaN1.000NaN1.0000.9991.0001.0001.0001.0001.000
2023-12-11T08:02:28.206247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표본렌즈수시험테와시험렌즈세트조제용연마기수렌즈절단기측정의자수자동굴절검사기안경세척기수시력검사세트시력표수가열기수동공거리계렌즈정점굴절력계
표본렌즈수1.0001.0000.9880.9880.8941.0000.8051.0000.7720.7030.6210.665
시험테와시험렌즈세트1.0001.0001.0001.0001.0000.2181.0000.2180.2181.0001.0000.000
조제용연마기수0.9881.0001.0000.9730.9881.0000.9831.0000.9880.9940.9880.983
렌즈절단기0.9881.0000.9731.0000.9881.0000.9831.0000.9880.9940.9880.983
측정의자수0.8941.0000.9880.9881.0001.0000.8041.0000.8070.6920.6740.649
자동굴절검사기1.0000.2181.0001.0001.0001.0001.0000.2750.2751.0000.0000.000
안경세척기수0.8051.0000.9830.9830.8041.0001.0001.0000.6860.8880.5640.681
시력검사세트1.0000.2181.0001.0001.0000.2751.0001.0000.2751.0000.0000.000
시력표수0.7720.2180.9880.9880.8070.2750.6860.2751.0000.6950.6210.596
가열기수0.7031.0000.9940.9940.6921.0000.8881.0000.6951.0000.6920.753
동공거리계0.6211.0000.9880.9880.6740.0000.5640.0000.6210.6921.0000.590
렌즈정점굴절력계0.6650.0000.9830.9830.6490.0000.6810.0000.5960.7530.5901.000
2023-12-11T08:02:28.343602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시력표수시력검사세트시험테와시험렌즈세트동공거리계자동굴절검사기렌즈정점굴절력계렌즈절단기표본렌즈수측정의자수안경세척기수가열기수조제용연마기수
순번1.0000.4830.0000.0000.4460.0000.3670.7440.4240.4510.4000.5670.744
시력표수0.4831.0000.2750.2180.6210.2750.5960.9880.7720.8070.6860.6950.988
시력검사세트0.0000.2751.0000.2180.0000.2750.0001.0001.0001.0001.0001.0001.000
시험테와시험렌즈세트0.0000.2180.2181.0001.0000.2180.0001.0001.0001.0001.0001.0001.000
동공거리계0.4460.6210.0001.0001.0000.0000.5900.9880.6210.6740.5640.6920.988
자동굴절검사기0.0000.2750.2750.2180.0001.0000.0001.0001.0001.0001.0001.0001.000
렌즈정점굴절력계0.3670.5960.0000.0000.5900.0001.0000.9830.6650.6490.6810.7530.983
렌즈절단기0.7440.9881.0001.0000.9881.0000.9831.0000.9880.9880.9830.9940.973
표본렌즈수0.4240.7721.0001.0000.6211.0000.6650.9881.0000.8940.8050.7030.988
측정의자수0.4510.8071.0001.0000.6741.0000.6490.9880.8941.0000.8040.6920.988
안경세척기수0.4000.6861.0001.0000.5641.0000.6810.9830.8050.8041.0000.8880.983
가열기수0.5670.6951.0001.0000.6921.0000.7530.9940.7030.6920.8881.0000.994
조제용연마기수0.7440.9881.0001.0000.9881.0000.9830.9730.9880.9880.9830.9941.000

Missing values

2023-12-11T08:02:21.662564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:02:21.939136image/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

순번등록일자안경업소명칭사업장소재지(도로명)사업장전화번호시력표수시력검사세트시험테와시험렌즈세트동공거리계자동굴절검사기렌즈정점굴절력계렌즈절단기표본렌즈수측정의자수안경세척기수가열기수조제용연마기수
012022-08-08퍼스널옵티컬경상남도 김해시 율하카페길 77-9, 1층 (관동동)055-337-2022111112<NA><NA><NA><NA><NA><NA>
122022-05-04안경창고 싸군 김해구산삼계점경상남도 김해시 가락로 278, 101호 (구산동)<NA>111111<NA><NA><NA><NA><NA><NA>
232022-01-12지니스 김해율하중앙경상남도 김해시 율하3로 37, 경보센텀 1층 105호 (율하동)055-337-496911<NA>211<NA><NA><NA><NA><NA><NA>
342022-01-11더존안경 김해율하점경상남도 김해시 율하6로 64, 1층 105,106,107호 (장유동)055-324-2235222122<NA><NA><NA><NA><NA><NA>
452021-08-23지니스안경 진영신도시점경상남도 김해시 진영읍 장등로19번길 39, 1층 102호055-343-4969111112<NA><NA><NA><NA><NA><NA>
562021-08-04이노티안경 김해주촌점경상남도 김해시 주촌면 천곡로 16055-337-9462111111<NA><NA><NA><NA><NA><NA>
672020-10-23Y플러스안경경상남도 김해시 분성로 168 (외동)<NA>111111<NA><NA><NA><NA><NA><NA>
782019-10-11으뜸플러스 김해율하점경상남도 김해시 율하2로 50, 1층 (율하동)055-338-27881<NA><NA>1<NA>2111111
892019-06-19참 좋은 안경원 진영점경상남도 김해시 진영읍 진산대로 61, 220동 104호 (진영 이진 캐스빌)055-342-78561<NA><NA>1<NA>1111111
9102019-04-29더존안경경상남도 김해시 진영읍 김해대로 428, 1층055-346-22342<NA><NA>1<NA>1111111
순번등록일자안경업소명칭사업장소재지(도로명)사업장전화번호시력표수시력검사세트시험테와시험렌즈세트동공거리계자동굴절검사기렌즈정점굴절력계렌즈절단기표본렌즈수측정의자수안경세척기수가열기수조제용연마기수
87882000-11-01으뜸안경부원점경상남도 김해시 분성로 321, 골든에비뉴 107호 (서상동)055-320-82041<NA><NA>1<NA>4111321
88891999-10-15안경만들기안경원경상남도 김해시 삼안로 229 (삼방동)055-333-94840<NA><NA>0<NA>0000000
89901998-10-20알로뷰(ALO VIEW)경상남도 김해시 김해대로 2078, 삼성홈플러스 (내동)<NA>1<NA><NA>1<NA>1111111
90911998-09-28김해안경사랑안경원경상남도 김해시 분성로 346 (동상동)055-327-52330<NA><NA>0<NA>0000000
91921998-05-08밝은눈안경경상남도 김해시 가락로 98-1 (서상동)055-333-25800<NA><NA>0<NA>0000000
92931997-08-19으뜸50안경 김해구산점경상남도 김해시 구산로 40 (구산동)055-323-34360<NA><NA>0<NA>0000000
93941997-02-21아이센스안경원경상남도 김해시 인제로 183 (어방동)055-322-62580<NA><NA>0<NA>0000000
94951995-02-10안경본데이경상남도 김해시 인제로 171 (어방동)<NA>0<NA><NA>0<NA>0000000
95961993-12-30제일안경원경상남도 김해시 가락로 92-1 (서상동)055-336-95860<NA><NA>0<NA>0000000
96971993-12-13세일안경원경상남도 김해시 진영읍 진영로 208-2055-342-11570<NA><NA>0<NA>0000000