Overview

Dataset statistics

Number of variables8
Number of observations27
Missing cells3
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory71.9 B

Variable types

Categorical1
Text4
Numeric3

Alerts

소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
소재지지번주소 has 1 (3.7%) missing valuesMissing
WGS84위도 has 1 (3.7%) missing valuesMissing
WGS84경도 has 1 (3.7%) missing valuesMissing
사업장명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-12 23:16:43.152486
Analysis finished2024-03-12 23:16:44.483325
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
광주시
7 
김포시
5 
화성시
4 
남양주시
2 
용인시
2 
Other values (7)
7 

Length

Max length4
Median length3
Mean length3.0740741
Min length3

Unique

Unique7 ?
Unique (%)25.9%

Sample

1st row고양시
2nd row광주시
3rd row광주시
4th row광주시
5th row광주시

Common Values

ValueCountFrequency (%)
광주시 7
25.9%
김포시 5
18.5%
화성시 4
14.8%
남양주시 2
 
7.4%
용인시 2
 
7.4%
고양시 1
 
3.7%
안산시 1
 
3.7%
양주시 1
 
3.7%
양평군 1
 
3.7%
이천시 1
 
3.7%
Other values (2) 2
 
7.4%

Length

2024-03-13T08:16:44.544750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
광주시 7
25.9%
김포시 5
18.5%
화성시 4
14.8%
남양주시 2
 
7.4%
용인시 2
 
7.4%
고양시 1
 
3.7%
안산시 1
 
3.7%
양주시 1
 
3.7%
양평군 1
 
3.7%
이천시 1
 
3.7%
Other values (2) 2
 
7.4%

사업장명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-03-13T08:16:44.689027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length6.1481481
Min length3

Characters and Unicode

Total characters166
Distinct characters88
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row㈜펫바라기
2nd row21그램 반려동물장례식장
3rd row㈜해피엔딩
4th row㈜펫포레스트
5th row러브펫
ValueCountFrequency (%)
포포즈 4
 
11.8%
반려동물장례식장 2
 
5.9%
21그램 2
 
5.9%
㈜펫바라기 1
 
2.9%
몽몽이엠파크 1
 
2.9%
화성점 1
 
2.9%
펫오케스트라 1
 
2.9%
스토리펫 1
 
2.9%
스타펫 1
 
2.9%
페어웰 1
 
2.9%
Other values (19) 19
55.9%
2024-03-13T08:16:44.930693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
펫 11
 
6.6%
포 11
 
6.6%
㈜ 8
 
4.8%
스 7
 
4.2%
7
 
4.2%
리 4
 
2.4%
아 4
 
2.4%
즈 4
 
2.4%
장 4
 
2.4%
동 3
 
1.8%
Other values (78) 103
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
82.5%
Other Symbol 8
 
4.8%
Uppercase Letter 8
 
4.8%
Space Separator 7
 
4.2%
Decimal Number 4
 
2.4%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
펫 11
 
8.0%
포 11
 
8.0%
스 7
 
5.1%
리 4
 
2.9%
아 4
 
2.9%
즈 4
 
2.9%
장 4
 
2.9%
동 3
 
2.2%
트 3
 
2.2%
물 3
 
2.2%
Other values (65) 83
60.6%
Uppercase Letter
ValueCountFrequency (%)
L 2
25.0%
I 1
12.5%
S 1
12.5%
H 1
12.5%
Y 1
12.5%
R 1
12.5%
O 1
12.5%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 8
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145
87.3%
Common 13
 
7.8%
Latin 8
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
펫 11
 
7.6%
포 11
 
7.6%
㈜ 8
 
5.5%
스 7
 
4.8%
리 4
 
2.8%
아 4
 
2.8%
즈 4
 
2.8%
장 4
 
2.8%
동 3
 
2.1%
트 3
 
2.1%
Other values (66) 86
59.3%
Latin
ValueCountFrequency (%)
L 2
25.0%
I 1
12.5%
S 1
12.5%
H 1
12.5%
Y 1
12.5%
R 1
12.5%
O 1
12.5%
Common
ValueCountFrequency (%)
7
53.8%
2 2
 
15.4%
1 2
 
15.4%
( 1
 
7.7%
) 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
82.5%
ASCII 21
 
12.7%
None 8
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
펫 11
 
8.0%
포 11
 
8.0%
스 7
 
5.1%
리 4
 
2.9%
아 4
 
2.9%
즈 4
 
2.9%
장 4
 
2.9%
동 3
 
2.2%
트 3
 
2.2%
물 3
 
2.2%
Other values (65) 83
60.6%
None
ValueCountFrequency (%)
㈜ 8
100.0%
ASCII
ValueCountFrequency (%)
7
33.3%
L 2
 
9.5%
2 2
 
9.5%
1 2
 
9.5%
I 1
 
4.8%
S 1
 
4.8%
H 1
 
4.8%
Y 1
 
4.8%
R 1
 
4.8%
O 1
 
4.8%
Other values (2) 2
 
9.5%

전화번호
Text

Distinct23
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-03-13T08:16:45.074685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length10.296296
Min length9

Characters and Unicode

Total characters278
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

Unique21 ?
Unique (%)77.8%

Sample

1st row031-976-3179
2nd row1688-1240
3rd row1899-5127
4th row1577-0996
5th row031-796-4341
ValueCountFrequency (%)
1588-2888 4
 
14.8%
1577-0996 2
 
7.4%
1855-2004 1
 
3.7%
031-976-3179 1
 
3.7%
1833-5158 1
 
3.7%
031-1588-1289 1
 
3.7%
031-353-5579 1
 
3.7%
1588-9344 1
 
3.7%
031-941-3350 1
 
3.7%
031-635-2266 1
 
3.7%
Other values (13) 13
48.1%
2024-03-13T08:16:45.328535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 44
15.8%
8 40
14.4%
- 38
13.7%
0 25
9.0%
3 24
8.6%
5 23
8.3%
9 21
7.6%
4 18
6.5%
2 16
 
5.8%
7 16
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
86.3%
Dash Punctuation 38
 
13.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 44
18.3%
8 40
16.7%
0 25
10.4%
3 24
10.0%
5 23
9.6%
9 21
8.8%
4 18
7.5%
2 16
 
6.7%
7 16
 
6.7%
6 13
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 278
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 44
15.8%
8 40
14.4%
- 38
13.7%
0 25
9.0%
3 24
8.6%
5 23
8.3%
9 21
7.6%
4 18
6.5%
2 16
 
5.8%
7 16
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 278
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 44
15.8%
8 40
14.4%
- 38
13.7%
0 25
9.0%
3 24
8.6%
5 23
8.3%
9 21
7.6%
4 18
6.5%
2 16
 
5.8%
7 16
 
5.8%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13378.704
Minimum10003
Maximum18556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-03-13T08:16:45.429586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10003
5-th percentile10008
Q111072
median12728
Q316390.5
95-th percentile18524.1
Maximum18556
Range8553
Interquartile range (IQR)5318.5

Descriptive statistics

Standard deviation3043.5794
Coefficient of variation (CV)0.22749434
Kurtosis-1.0051062
Mean13378.704
Median Absolute Deviation (MAD)2476
Skewness0.66636979
Sum361225
Variance9263375.4
MonotonicityNot monotonic
2024-03-13T08:16:45.519655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
12728 2
 
7.4%
10008 2
 
7.4%
10010 2
 
7.4%
10252 1
 
3.7%
12540 1
 
3.7%
18556 1
 
3.7%
18525 1
 
3.7%
18284 1
 
3.7%
18522 1
 
3.7%
11190 1
 
3.7%
Other values (14) 14
51.9%
ValueCountFrequency (%)
10003 1
3.7%
10008 2
7.4%
10010 2
7.4%
10252 1
3.7%
10954 1
3.7%
11190 1
3.7%
11424 1
3.7%
12192 1
3.7%
12199 1
3.7%
12540 1
3.7%
ValueCountFrequency (%)
18556 1
3.7%
18525 1
3.7%
18522 1
3.7%
18284 1
3.7%
17383 1
3.7%
17172 1
3.7%
17123 1
3.7%
15658 1
3.7%
12798 1
3.7%
12774 1
3.7%

소재지지번주소
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing1
Missing (%)3.7%
Memory size348.0 B
2024-03-13T08:16:45.731973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length22.807692
Min length19

Characters and Unicode

Total characters593
Distinct characters90
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

Unique26 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산동구 설문동 515-1번지
2nd row경기도 광주시 초월읍 지월리 134번지
3rd row경기도 광주시 문형동 749-5번지
4th row경기도 광주시 초월읍 지월리 712-10번지
5th row경기도 광주시 초월읍 신월리 592-19번지
ValueCountFrequency (%)
경기도 26
 
19.5%
광주시 6
 
4.5%
김포시 5
 
3.8%
화성시 4
 
3.0%
초월읍 4
 
3.0%
용인시 2
 
1.5%
처인구 2
 
1.5%
화도읍 2
 
1.5%
남양주시 2
 
1.5%
귀전리 2
 
1.5%
Other values (74) 78
58.6%
2024-03-13T08:16:46.014307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
107
18.0%
지 29
 
4.9%
도 28
 
4.7%
경 26
 
4.4%
번 26
 
4.4%
기 26
 
4.4%
시 25
 
4.2%
리 23
 
3.9%
5 20
 
3.4%
1 20
 
3.4%
Other values (80) 263
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 373
62.9%
Space Separator 107
 
18.0%
Decimal Number 96
 
16.2%
Dash Punctuation 17
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 29
 
7.8%
도 28
 
7.5%
경 26
 
7.0%
번 26
 
7.0%
기 26
 
7.0%
시 25
 
6.7%
리 23
 
6.2%
면 13
 
3.5%
읍 10
 
2.7%
주 10
 
2.7%
Other values (68) 157
42.1%
Decimal Number
ValueCountFrequency (%)
5 20
20.8%
1 20
20.8%
2 11
11.5%
8 9
9.4%
6 9
9.4%
3 9
9.4%
9 5
 
5.2%
7 5
 
5.2%
4 4
 
4.2%
0 4
 
4.2%
Space Separator
ValueCountFrequency (%)
107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 373
62.9%
Common 220
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 29
 
7.8%
도 28
 
7.5%
경 26
 
7.0%
번 26
 
7.0%
기 26
 
7.0%
시 25
 
6.7%
리 23
 
6.2%
면 13
 
3.5%
읍 10
 
2.7%
주 10
 
2.7%
Other values (68) 157
42.1%
Common
ValueCountFrequency (%)
107
48.6%
5 20
 
9.1%
1 20
 
9.1%
- 17
 
7.7%
2 11
 
5.0%
8 9
 
4.1%
6 9
 
4.1%
3 9
 
4.1%
9 5
 
2.3%
7 5
 
2.3%
Other values (2) 8
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 373
62.9%
ASCII 220
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
107
48.6%
5 20
 
9.1%
1 20
 
9.1%
- 17
 
7.7%
2 11
 
5.0%
8 9
 
4.1%
6 9
 
4.1%
3 9
 
4.1%
9 5
 
2.3%
7 5
 
2.3%
Other values (2) 8
 
3.6%
Hangul
ValueCountFrequency (%)
지 29
 
7.8%
도 28
 
7.5%
경 26
 
7.0%
번 26
 
7.0%
기 26
 
7.0%
시 25
 
6.7%
리 23
 
6.2%
면 13
 
3.5%
읍 10
 
2.7%
주 10
 
2.7%
Other values (68) 157
42.1%

소재지도로명주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-03-13T08:16:46.224038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length23
Mean length21.888889
Min length18

Characters and Unicode

Total characters591
Distinct characters96
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산동구 은마길63번길 25-2
2nd row경기도 광주시 오포읍 매자리길 185
3rd row경기도 광주시 초월읍 지월로100번길 18
4th row경기도 광주시 오포읍 오포안로 77
5th row경기도 광주시 초월읍 현산로361번길 12
ValueCountFrequency (%)
경기도 27
 
19.3%
광주시 7
 
5.0%
김포시 5
 
3.6%
화성시 4
 
2.9%
초월읍 4
 
2.9%
용인시 2
 
1.4%
처인구 2
 
1.4%
화도읍 2
 
1.4%
남양주시 2
 
1.4%
통진읍 2
 
1.4%
Other values (80) 83
59.3%
2024-03-13T08:16:46.529822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
19.1%
도 29
 
4.9%
기 29
 
4.9%
경 27
 
4.6%
시 26
 
4.4%
1 21
 
3.6%
로 19
 
3.2%
길 16
 
2.7%
2 15
 
2.5%
면 14
 
2.4%
Other values (86) 282
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 365
61.8%
Space Separator 113
 
19.1%
Decimal Number 106
 
17.9%
Dash Punctuation 6
 
1.0%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 29
 
7.9%
기 29
 
7.9%
경 27
 
7.4%
시 26
 
7.1%
로 19
 
5.2%
길 16
 
4.4%
면 14
 
3.8%
주 11
 
3.0%
읍 11
 
3.0%
양 9
 
2.5%
Other values (73) 174
47.7%
Decimal Number
ValueCountFrequency (%)
1 21
19.8%
2 15
14.2%
3 13
12.3%
0 12
11.3%
6 10
9.4%
5 9
8.5%
8 8
 
7.5%
4 8
 
7.5%
7 6
 
5.7%
9 4
 
3.8%
Space Separator
ValueCountFrequency (%)
113
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 365
61.8%
Common 226
38.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 29
 
7.9%
기 29
 
7.9%
경 27
 
7.4%
시 26
 
7.1%
로 19
 
5.2%
길 16
 
4.4%
면 14
 
3.8%
주 11
 
3.0%
읍 11
 
3.0%
양 9
 
2.5%
Other values (73) 174
47.7%
Common
ValueCountFrequency (%)
113
50.0%
1 21
 
9.3%
2 15
 
6.6%
3 13
 
5.8%
0 12
 
5.3%
6 10
 
4.4%
5 9
 
4.0%
8 8
 
3.5%
4 8
 
3.5%
- 6
 
2.7%
Other values (3) 11
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 365
61.8%
ASCII 226
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
50.0%
1 21
 
9.3%
2 15
 
6.6%
3 13
 
5.8%
0 12
 
5.3%
6 10
 
4.4%
5 9
 
4.0%
8 8
 
3.5%
4 8
 
3.5%
- 6
 
2.7%
Other values (3) 11
 
4.9%
Hangul
ValueCountFrequency (%)
도 29
 
7.9%
기 29
 
7.9%
경 27
 
7.4%
시 26
 
7.1%
로 19
 
5.2%
길 16
 
4.4%
면 14
 
3.8%
주 11
 
3.0%
읍 11
 
3.0%
양 9
 
2.5%
Other values (73) 174
47.7%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)100.0%
Missing1
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean37.475047
Minimum37.107319
Maximum37.815513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-03-13T08:16:46.654214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.107319
5-th percentile37.152996
Q137.283565
median37.413612
Q337.726289
95-th percentile37.79837
Maximum37.815513
Range0.70819358
Interquartile range (IQR)0.44272319

Descriptive statistics

Standard deviation0.24281526
Coefficient of variation (CV)0.0064793852
Kurtosis-1.58983
Mean37.475047
Median Absolute Deviation (MAD)0.2511895
Skewness0.0091479002
Sum974.35121
Variance0.058959251
MonotonicityNot monotonic
2024-03-13T08:16:46.760054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
37.7137643378 1
 
3.7%
37.2953164569 1
 
3.7%
37.1547701222 1
 
3.7%
37.1750591167 1
 
3.7%
37.2192801412 1
 
3.7%
37.1524039978 1
 
3.7%
37.8155129225 1
 
3.7%
37.7657256863 1
 
3.7%
37.2796484224 1
 
3.7%
37.1700757091 1
 
3.7%
Other values (16) 16
59.3%
ValueCountFrequency (%)
37.1073193395 1
3.7%
37.1524039978 1
3.7%
37.1547701222 1
3.7%
37.1700757091 1
3.7%
37.1750591167 1
3.7%
37.2192801412 1
3.7%
37.2796484224 1
3.7%
37.2953164569 1
3.7%
37.3525341412 1
3.7%
37.3538817494 1
3.7%
ValueCountFrequency (%)
37.8155129225 1
3.7%
37.8092519779 1
3.7%
37.7657256863 1
3.7%
37.7365160779 1
3.7%
37.7308397669 1
3.7%
37.7301908786 1
3.7%
37.7267816569 1
3.7%
37.7248095289 1
3.7%
37.7137643378 1
3.7%
37.681379783 1
3.7%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)100.0%
Missing1
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean127.04804
Minimum126.57553
Maximum127.78336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-03-13T08:16:46.856162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.57553
5-th percentile126.60432
Q1126.78155
median127.06289
Q3127.30764
95-th percentile127.39355
Maximum127.78336
Range1.2078285
Interquartile range (IQR)0.52608117

Descriptive statistics

Standard deviation0.32757033
Coefficient of variation (CV)0.0025783186
Kurtosis-0.86596397
Mean127.04804
Median Absolute Deviation (MAD)0.25619781
Skewness0.1589393
Sum3303.249
Variance0.10730232
MonotonicityNot monotonic
2024-03-13T08:16:46.952851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
126.8059296044 1
 
3.7%
126.7734292216 1
 
3.7%
126.7414983445 1
 
3.7%
126.8947537044 1
 
3.7%
126.8685443166 1
 
3.7%
126.9535383272 1
 
3.7%
127.2126007184 1
 
3.7%
126.8470440221 1
 
3.7%
127.3906476273 1
 
3.7%
127.3749233219 1
 
3.7%
Other values (16) 16
59.3%
ValueCountFrequency (%)
126.5755341521 1
3.7%
126.6010982759 1
3.7%
126.6139652518 1
3.7%
126.6275574053 1
3.7%
126.6297379058 1
3.7%
126.7414983445 1
3.7%
126.7734292216 1
3.7%
126.8059296044 1
3.7%
126.8470440221 1
3.7%
126.8685443166 1
3.7%
ValueCountFrequency (%)
127.7833627001 1
3.7%
127.3945146508 1
3.7%
127.3906476273 1
3.7%
127.3749233219 1
3.7%
127.3646908715 1
3.7%
127.3183252193 1
3.7%
127.3100014023 1
3.7%
127.3005377241 1
3.7%
127.2903026619 1
3.7%
127.2844682374 1
3.7%

Interactions

2024-03-13T08:16:43.835368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:16:43.445020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:16:43.635801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:16:43.893575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:16:43.501320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:16:43.699799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:16:43.962687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:16:43.565511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:16:43.767476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:16:47.028008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명전화번호소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0000.8961.0001.0001.0000.8950.875
사업장명1.0001.0001.0001.0001.0001.0001.0001.000
전화번호0.8961.0001.0000.8231.0001.0000.8460.909
소재지우편번호1.0001.0000.8231.0001.0001.0000.8700.721
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도0.8951.0000.8460.8701.0001.0001.0000.626
WGS84경도0.8751.0000.9090.7211.0001.0000.6261.000
2024-03-13T08:16:47.113466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명
소재지우편번호1.000-0.9100.3940.866
WGS84위도-0.9101.000-0.3200.559
WGS84경도0.394-0.3201.0000.523
시군명0.8660.5590.5231.000

Missing values

2024-03-13T08:16:44.259429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:16:44.351702image/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.
2024-03-13T08:16:44.429345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명사업장명전화번호소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
0고양시㈜펫바라기031-976-317910252경기도 고양시 일산동구 설문동 515-1번지경기도 고양시 일산동구 은마길63번길 25-237.713764126.80593
1광주시21그램 반려동물장례식장1688-124012798<NA>경기도 광주시 오포읍 매자리길 185<NA><NA>
2광주시㈜해피엔딩1899-512712728경기도 광주시 초월읍 지월리 134번지경기도 광주시 초월읍 지월로100번길 1837.412711127.300538
3광주시㈜펫포레스트1577-099612774경기도 광주시 문형동 749-5번지경기도 광주시 오포읍 오포안로 7737.352534127.198161
4광주시러브펫031-796-434112728경기도 광주시 초월읍 지월리 712-10번지경기도 광주시 초월읍 현산로361번길 1237.416802127.284468
5광주시포포즈 경기광주1588-288812729경기도 광주시 초월읍 신월리 592-19번지경기도 광주시 초월읍 산수로 409-1137.397187127.310001
6광주시백꽃사랑하이빛1811-965012723경기도 광주시 곤지암읍 부항리 236번지경기도 광주시 곤지암읍 신만로 30537.353882127.394515
7광주시하늘강아지1577-442812732경기도 광주시 초월읍 선동리 386-5번지경기도 광주시 초월읍 선장동길 31-337.388988127.318325
8김포시㈜위디안(엔젤스톤)031-981-027110008경기도 김포시 하성면 양택리 251-6번지경기도 김포시 하성면 하성로 72037.736516126.629738
9김포시펫포레스트1577-099610010경기도 김포시 통진읍 귀전리 167번지경기도 김포시 통진읍 고정로 30837.72481126.601098
시군명사업장명전화번호소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
17양평군ROYHILLS1855-200412540경기도 양평군 양동면 삼산리 18번지경기도 양평군 양동면 양동금곡4길 1037.414514127.783363
18용인시리멤버080-200-500417123경기도 용인시 처인구 남사읍 방아리 883-3번지경기도 용인시 처인구 남사면 원암로 53537.107319127.172238
19용인시씨엘로펫1577-733217172경기도 용인시 처인구 백암면 백암리 220번지경기도 용인시 처인구 백암면 죽양대로 120637.170076127.374923
20이천시㈜아리아펫031-635-226617383경기도 이천시 마장면 장암리 525-1번지경기도 이천시 마장면 이장로 329-237.279648127.390648
21파주시페어웰031-941-335010954경기도 파주시 광탄면 분수리 458번지경기도 파주시 광탄면 수레길 30237.765726126.847044
22포천시스타펫1588-934411190경기도 포천시 내촌면 진목리 225번지경기도 포천시 내촌면 진금로 3437.815513127.212601
23화성시스토리펫031-353-557918522경기도 화성시 정남면 문학리 663번지경기도 화성시 정남면 서봉로851번길 8337.152404126.953538
24화성시펫오케스트라031-1588-128918284경기도 화성시 비봉면 양노리 755-5번지경기도 화성시 비봉면 양노남길 10837.21928126.868544
25화성시포포즈 반려동물장례식장 화성점1588-288818525경기도 화성시 팔탄면 창곡리 925-6번지경기도 화성시 팔탄면 독곡길 24-4237.175059126.894754
26화성시㈜우리반려동물문화원1899-641518556경기도 화성시 서신면 사곳리 5-18번지경기도 화성시 서신면 안벼슬길102번길 16537.15477126.741498