Overview

Dataset statistics

Number of variables10
Number of observations71
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory85.9 B

Variable types

Categorical3
Text3
Numeric4

Dataset

Description문화재 수리업체 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=CU6VDG26R72EM0J2598S1907977&infSeq=1

Alerts

영업상태명 has constant value ""Constant
문화체육업종명 has constant value ""Constant
인허가일자 is highly overall correlated with 소재지우편번호High correlation
소재지우편번호 is highly overall correlated with 인허가일자 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 23:06:01.191262
Analysis finished2023-12-10 23:06:03.627207
Duration2.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
고양시
14 
용인시
10 
성남시
9 
수원시
8 
파주시
4 
Other values (16)
26 

Length

Max length4
Median length3
Mean length3.0140845
Min length3

Unique

Unique8 ?
Unique (%)11.3%

Sample

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

Common Values

ValueCountFrequency (%)
고양시 14
19.7%
용인시 10
14.1%
성남시 9
12.7%
수원시 8
11.3%
파주시 4
 
5.6%
평택시 3
 
4.2%
김포시 3
 
4.2%
광주시 2
 
2.8%
구리시 2
 
2.8%
부천시 2
 
2.8%
Other values (11) 14
19.7%

Length

2023-12-11T08:06:03.700533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 14
19.7%
용인시 10
14.1%
성남시 9
12.7%
수원시 8
11.3%
파주시 4
 
5.6%
평택시 3
 
4.2%
김포시 3
 
4.2%
안양시 2
 
2.8%
안성시 2
 
2.8%
화성시 2
 
2.8%
Other values (11) 14
19.7%

사업장명
Text

Distinct67
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T08:06:03.908200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.4929577
Min length2

Characters and Unicode

Total characters603
Distinct characters120
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)88.7%

Sample

1st row(주)경한
2nd row한겨레건축사사무소
3rd row시공인건축사사무소
4th row(주)고진티앤시
5th row(주)선영건축
ValueCountFrequency (%)
주식회사 15
 
17.2%
한겨레건축사사무소 2
 
2.3%
더나루 2
 
2.3%
주)함께 2
 
2.3%
북촌불교미술보존연구소 2
 
2.3%
삼영 1
 
1.1%
한옥마음 1
 
1.1%
금화 1
 
1.1%
성림종합건설(주 1
 
1.1%
배흘림 1
 
1.1%
Other values (59) 59
67.8%
2023-12-11T08:06:04.304299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 57
 
9.5%
사 44
 
7.3%
( 39
 
6.5%
) 39
 
6.5%
건 33
 
5.5%
무 18
 
3.0%
식 18
 
3.0%
회 18
 
3.0%
종 17
 
2.8%
합 17
 
2.8%
Other values (110) 303
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 508
84.2%
Open Punctuation 39
 
6.5%
Close Punctuation 39
 
6.5%
Space Separator 16
 
2.7%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 57
 
11.2%
사 44
 
8.7%
건 33
 
6.5%
무 18
 
3.5%
식 18
 
3.5%
회 18
 
3.5%
종 17
 
3.3%
합 17
 
3.3%
축 17
 
3.3%
소 17
 
3.3%
Other values (106) 252
49.6%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 509
84.4%
Common 94
 
15.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 57
 
11.2%
사 44
 
8.6%
건 33
 
6.5%
무 18
 
3.5%
식 18
 
3.5%
회 18
 
3.5%
종 17
 
3.3%
합 17
 
3.3%
축 17
 
3.3%
소 17
 
3.3%
Other values (107) 253
49.7%
Common
ValueCountFrequency (%)
( 39
41.5%
) 39
41.5%
16
17.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 508
84.2%
ASCII 94
 
15.6%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 57
 
11.2%
사 44
 
8.7%
건 33
 
6.5%
무 18
 
3.5%
식 18
 
3.5%
회 18
 
3.5%
종 17
 
3.3%
합 17
 
3.3%
축 17
 
3.3%
소 17
 
3.3%
Other values (106) 252
49.6%
ASCII
ValueCountFrequency (%)
( 39
41.5%
) 39
41.5%
16
17.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

인허가일자
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20135207
Minimum20050826
Maximum20180801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T08:06:04.453842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050826
5-th percentile20050826
Q120110404
median20150402
Q320160817
95-th percentile20180312
Maximum20180801
Range129975
Interquartile range (IQR)50413

Descriptive statistics

Standard deviation38071.228
Coefficient of variation (CV)0.0018907791
Kurtosis-0.21720579
Mean20135207
Median Absolute Deviation (MAD)19901
Skewness-0.94742679
Sum1.4295997 × 109
Variance1.4494184 × 109
MonotonicityNot monotonic
2023-12-11T08:06:04.593496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050826 5
 
7.0%
20150430 3
 
4.2%
20180312 3
 
4.2%
20070116 2
 
2.8%
20170831 2
 
2.8%
20090217 2
 
2.8%
20100106 1
 
1.4%
20140829 1
 
1.4%
20080414 1
 
1.4%
20100204 1
 
1.4%
Other values (50) 50
70.4%
ValueCountFrequency (%)
20050826 5
7.0%
20070116 2
 
2.8%
20071120 1
 
1.4%
20080116 1
 
1.4%
20080403 1
 
1.4%
20080414 1
 
1.4%
20090217 2
 
2.8%
20091203 1
 
1.4%
20100106 1
 
1.4%
20100204 1
 
1.4%
ValueCountFrequency (%)
20180801 1
 
1.4%
20180709 1
 
1.4%
20180328 1
 
1.4%
20180312 3
4.2%
20171226 1
 
1.4%
20171124 1
 
1.4%
20171010 1
 
1.4%
20170831 2
2.8%
20170324 1
 
1.4%
20170303 1
 
1.4%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
운영중
71 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row운영중
2nd row운영중
3rd row운영중
4th row운영중
5th row운영중

Common Values

ValueCountFrequency (%)
운영중 71
100.0%

Length

2023-12-11T08:06:04.728667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:06:04.819426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 71
100.0%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
문화재수리업
71 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row문화재수리업
2nd row문화재수리업
3rd row문화재수리업
4th row문화재수리업
5th row문화재수리업

Common Values

ValueCountFrequency (%)
문화재수리업 71
100.0%

Length

2023-12-11T08:06:04.913320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:06:05.030408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화재수리업 71
100.0%

소재지도로명주소
Text

Distinct70
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T08:06:05.292178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length38
Mean length32.71831
Min length19

Characters and Unicode

Total characters2323
Distinct characters181
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)97.2%

Sample

1st row경기도 고양시 덕양구 용현로 27-0, 403호 (행신동,행신프라자)
2nd row경기도 고양시 덕양구 고양시청로 18, 303호 (주교동)
3rd row경기도 고양시 덕양구 무원로 6, 804호 (행신동)
4th row경기도 고양시 일산동구 호수로 358-25, 922호 (백석동,동문타워II)
5th row경기도 고양시 덕양구 능곡로13번길 20, 2층 202호 (토당동)
ValueCountFrequency (%)
경기도 71
 
14.7%
고양시 14
 
2.9%
덕양구 11
 
2.3%
2층 10
 
2.1%
용인시 10
 
2.1%
성남시 9
 
1.9%
수원시 8
 
1.7%
5층 5
 
1.0%
3층 5
 
1.0%
장안구 5
 
1.0%
Other values (258) 336
69.4%
2023-12-11T08:06:05.755763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
417
 
18.0%
1 82
 
3.5%
, 80
 
3.4%
동 80
 
3.4%
기 79
 
3.4%
2 78
 
3.4%
도 76
 
3.3%
시 75
 
3.2%
경 72
 
3.1%
로 67
 
2.9%
Other values (171) 1217
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1257
54.1%
Space Separator 417
 
18.0%
Decimal Number 405
 
17.4%
Other Punctuation 81
 
3.5%
Close Punctuation 63
 
2.7%
Open Punctuation 63
 
2.7%
Dash Punctuation 28
 
1.2%
Uppercase Letter 9
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 80
 
6.4%
기 79
 
6.3%
도 76
 
6.0%
시 75
 
6.0%
경 72
 
5.7%
로 67
 
5.3%
구 52
 
4.1%
호 46
 
3.7%
양 33
 
2.6%
층 31
 
2.5%
Other values (150) 646
51.4%
Decimal Number
ValueCountFrequency (%)
1 82
20.2%
2 78
19.3%
0 62
15.3%
3 44
10.9%
4 35
8.6%
6 27
 
6.7%
5 24
 
5.9%
7 22
 
5.4%
8 18
 
4.4%
9 13
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
A 2
22.2%
I 2
22.2%
C 1
 
11.1%
Y 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 80
98.8%
· 1
 
1.2%
Space Separator
ValueCountFrequency (%)
417
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1257
54.1%
Common 1057
45.5%
Latin 9
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 80
 
6.4%
기 79
 
6.3%
도 76
 
6.0%
시 75
 
6.0%
경 72
 
5.7%
로 67
 
5.3%
구 52
 
4.1%
호 46
 
3.7%
양 33
 
2.6%
층 31
 
2.5%
Other values (150) 646
51.4%
Common
ValueCountFrequency (%)
417
39.5%
1 82
 
7.8%
, 80
 
7.6%
2 78
 
7.4%
) 63
 
6.0%
( 63
 
6.0%
0 62
 
5.9%
3 44
 
4.2%
4 35
 
3.3%
- 28
 
2.6%
Other values (6) 105
 
9.9%
Latin
ValueCountFrequency (%)
B 3
33.3%
A 2
22.2%
I 2
22.2%
C 1
 
11.1%
Y 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1257
54.1%
ASCII 1065
45.8%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
417
39.2%
1 82
 
7.7%
, 80
 
7.5%
2 78
 
7.3%
) 63
 
5.9%
( 63
 
5.9%
0 62
 
5.8%
3 44
 
4.1%
4 35
 
3.3%
- 28
 
2.6%
Other values (10) 113
 
10.6%
Hangul
ValueCountFrequency (%)
동 80
 
6.4%
기 79
 
6.3%
도 76
 
6.0%
시 75
 
6.0%
경 72
 
5.7%
로 67
 
5.3%
구 52
 
4.1%
호 46
 
3.7%
양 33
 
2.6%
층 31
 
2.5%
Other values (150) 646
51.4%
None
ValueCountFrequency (%)
· 1
100.0%

소재지지번주소
Text

Distinct68
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T08:06:06.053087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length27.605634
Min length14

Characters and Unicode

Total characters1960
Distinct characters163
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)91.5%

Sample

1st row경기도 고양시 덕양구 행신동 757 - 2 행신프라자 403호
2nd row경기도 고양시 덕양구 주교동 603 - 2 303호
3rd row경기도 고양시 덕양구 행신동 709 - 1 804호
4th row경기도 고양시 일산동구 백석동 1324 - 0 동문타워II 922호
5th row경기도 고양시 덕양구 토당동 344 - 73 202호
ValueCountFrequency (%)
경기도 71
 
13.1%
61
 
11.2%
1 16
 
2.9%
고양시 13
 
2.4%
2 12
 
2.2%
덕양구 11
 
2.0%
용인시 10
 
1.8%
성남시 9
 
1.7%
수원시 8
 
1.5%
장안구 5
 
0.9%
Other values (237) 328
60.3%
2023-12-11T08:06:06.549501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
473
24.1%
1 81
 
4.1%
동 79
 
4.0%
기 76
 
3.9%
도 74
 
3.8%
시 72
 
3.7%
경 71
 
3.6%
2 64
 
3.3%
3 63
 
3.2%
- 61
 
3.1%
Other values (153) 846
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 990
50.5%
Space Separator 473
24.1%
Decimal Number 426
21.7%
Dash Punctuation 61
 
3.1%
Uppercase Letter 8
 
0.4%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 79
 
8.0%
기 76
 
7.7%
도 74
 
7.5%
시 72
 
7.3%
경 71
 
7.2%
구 48
 
4.8%
호 42
 
4.2%
양 30
 
3.0%
수 18
 
1.8%
남 15
 
1.5%
Other values (135) 465
47.0%
Decimal Number
ValueCountFrequency (%)
1 81
19.0%
2 64
15.0%
3 63
14.8%
0 57
13.4%
4 42
9.9%
7 40
9.4%
6 27
 
6.3%
5 19
 
4.5%
8 18
 
4.2%
9 15
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
A 2
25.0%
I 2
25.0%
B 2
25.0%
Y 1
12.5%
C 1
12.5%
Space Separator
ValueCountFrequency (%)
473
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 990
50.5%
Common 962
49.1%
Latin 8
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 79
 
8.0%
기 76
 
7.7%
도 74
 
7.5%
시 72
 
7.3%
경 71
 
7.2%
구 48
 
4.8%
호 42
 
4.2%
양 30
 
3.0%
수 18
 
1.8%
남 15
 
1.5%
Other values (135) 465
47.0%
Common
ValueCountFrequency (%)
473
49.2%
1 81
 
8.4%
2 64
 
6.7%
3 63
 
6.5%
- 61
 
6.3%
0 57
 
5.9%
4 42
 
4.4%
7 40
 
4.2%
6 27
 
2.8%
5 19
 
2.0%
Other values (3) 35
 
3.6%
Latin
ValueCountFrequency (%)
A 2
25.0%
I 2
25.0%
B 2
25.0%
Y 1
12.5%
C 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 990
50.5%
ASCII 970
49.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
473
48.8%
1 81
 
8.4%
2 64
 
6.6%
3 63
 
6.5%
- 61
 
6.3%
0 57
 
5.9%
4 42
 
4.3%
7 40
 
4.1%
6 27
 
2.8%
5 19
 
2.0%
Other values (8) 43
 
4.4%
Hangul
ValueCountFrequency (%)
동 79
 
8.0%
기 76
 
7.7%
도 74
 
7.5%
시 72
 
7.3%
경 71
 
7.2%
구 48
 
4.8%
호 42
 
4.2%
양 30
 
3.0%
수 18
 
1.8%
남 15
 
1.5%
Other values (135) 465
47.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123194.37
Minimum10108
Maximum477804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T08:06:06.703641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10108
5-th percentile10229.5
Q110910.5
median15856
Q3215320
95-th percentile463832
Maximum477804
Range467696
Interquartile range (IQR)204409.5

Descriptive statistics

Standard deviation189903.56
Coefficient of variation (CV)1.5414955
Kurtosis-0.649903
Mean123194.37
Median Absolute Deviation (MAD)4975
Skewness1.1647279
Sum8746800
Variance3.6063363 × 1010
MonotonicityNot monotonic
2023-12-11T08:06:06.828640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10526 2
 
2.8%
11938 2
 
2.8%
10881 2
 
2.8%
17058 2
 
2.8%
10460 2
 
2.8%
16360 2
 
2.8%
10108 2
 
2.8%
16339 2
 
2.8%
437836 2
 
2.8%
10594 2
 
2.8%
Other values (51) 51
71.8%
ValueCountFrequency (%)
10108 2
2.8%
10126 1
1.4%
10223 1
1.4%
10236 1
1.4%
10437 1
1.4%
10460 2
2.8%
10486 1
1.4%
10508 1
1.4%
10523 1
1.4%
10526 2
2.8%
ValueCountFrequency (%)
477804 1
1.4%
469805 1
1.4%
464802 1
1.4%
463836 1
1.4%
463828 1
1.4%
461855 1
1.4%
456833 1
1.4%
445976 1
1.4%
443370 1
1.4%
440820 1
1.4%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.427532
Minimum37.003286
Maximum37.895779
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T08:06:06.943908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.003286
5-th percentile37.054497
Q137.295374
median37.414162
Q337.616888
95-th percentile37.707065
Maximum37.895779
Range0.89249296
Interquartile range (IQR)0.32151342

Descriptive statistics

Standard deviation0.20345477
Coefficient of variation (CV)0.0054359653
Kurtosis-0.64838276
Mean37.427532
Median Absolute Deviation (MAD)0.17368191
Skewness-0.10896258
Sum2657.3548
Variance0.041393842
MonotonicityNot monotonic
2023-12-11T08:06:07.067865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2990523831 2
 
2.8%
37.6490702916 2
 
2.8%
37.6576076788 2
 
2.8%
37.2218111476 2
 
2.8%
37.7070650257 2
 
2.8%
37.3008702874 2
 
2.8%
37.6135331586 2
 
2.8%
37.013970811 1
 
1.4%
37.206294069 1
 
1.4%
37.3049789928 1
 
1.4%
Other values (54) 54
76.1%
ValueCountFrequency (%)
37.0032860743 1
1.4%
37.013970811 1
1.4%
37.0369384976 1
1.4%
37.0514365142 1
1.4%
37.0575571716 1
1.4%
37.1094720021 1
1.4%
37.1262372445 1
1.4%
37.206294069 1
1.4%
37.2218111476 2
2.8%
37.2253682916 1
1.4%
ValueCountFrequency (%)
37.8957790377 1
1.4%
37.7510366335 1
1.4%
37.7250014414 1
1.4%
37.7070650257 2
2.8%
37.6933063617 1
1.4%
37.6746400996 1
1.4%
37.6663348381 1
1.4%
37.6576076788 2
2.8%
37.6490702916 2
2.8%
37.6399272494 1
1.4%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.01245
Minimum126.68576
Maximum127.66012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T08:06:07.183357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.68576
5-th percentile126.71607
Q1126.835
median127.00059
Q3127.12701
95-th percentile127.29771
Maximum127.66012
Range0.97435663
Interquartile range (IQR)0.29201485

Descriptive statistics

Standard deviation0.21178256
Coefficient of variation (CV)0.0016674157
Kurtosis1.1818614
Mean127.01245
Median Absolute Deviation (MAD)0.1444602
Skewness0.79719722
Sum9017.884
Variance0.044851853
MonotonicityNot monotonic
2023-12-11T08:06:07.295952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9693926501 2
 
2.8%
126.9019008596 2
 
2.8%
126.8317119067 2
 
2.8%
127.190183634 2
 
2.8%
126.6857616057 2
 
2.8%
126.9913149393 2
 
2.8%
126.8349958107 2
 
2.8%
126.8797231239 1
 
1.4%
126.9887837318 1
 
1.4%
127.0123433784 1
 
1.4%
Other values (54) 54
76.1%
ValueCountFrequency (%)
126.6857616057 2
2.8%
126.6989664826 1
1.4%
126.7140457467 1
1.4%
126.718100668 1
1.4%
126.7418505989 1
1.4%
126.7517214118 1
1.4%
126.7565370124 1
1.4%
126.7689012552 1
1.4%
126.7728472713 1
1.4%
126.7752713673 1
1.4%
ValueCountFrequency (%)
127.6601182336 1
1.4%
127.6522591063 1
1.4%
127.5723367672 1
1.4%
127.3037707252 1
1.4%
127.2916423441 1
1.4%
127.2636231114 1
1.4%
127.2569824921 1
1.4%
127.2279573324 1
1.4%
127.203519761 1
1.4%
127.190183634 2
2.8%

Interactions

2023-12-11T08:06:02.824004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:01.862759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:02.166117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:02.453459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:03.150348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:01.943292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:02.245905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:02.528008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:03.216109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:02.013678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:02.317026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:02.617997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:03.289497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:02.091150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:02.384627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:06:02.695089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:06:07.377526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명인허가일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0000.4721.0001.0000.4210.9620.916
사업장명1.0001.0000.9680.9940.9941.0001.0001.000
인허가일자0.4720.9681.0000.7650.9360.9270.0000.215
소재지도로명주소1.0000.9940.7651.0001.0000.7081.0001.000
소재지지번주소1.0000.9940.9361.0001.0000.9471.0001.000
소재지우편번호0.4211.0000.9270.7080.9471.0000.0000.119
WGS84위도0.9621.0000.0001.0001.0000.0001.0000.607
WGS84경도0.9161.0000.2151.0001.0000.1190.6071.000
2023-12-11T08:06:07.478265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자소재지우편번호WGS84위도WGS84경도시군명
인허가일자1.000-0.5910.298-0.0160.243
소재지우편번호-0.5911.000-0.7220.4330.205
WGS84위도0.298-0.7221.000-0.5360.722
WGS84경도-0.0160.433-0.5361.0000.623
시군명0.2430.2050.7220.6231.000

Missing values

2023-12-11T08:06:03.427088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:06:03.577978image/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

시군명사업장명인허가일자영업상태명문화체육업종명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0고양시(주)경한20150430운영중문화재수리업경기도 고양시 덕양구 용현로 27-0, 403호 (행신동,행신프라자)경기도 고양시 덕양구 행신동 757 - 2 행신프라자 403호1052637.615222126.835627
1고양시한겨레건축사사무소20141215운영중문화재수리업경기도 고양시 덕양구 고양시청로 18, 303호 (주교동)경기도 고양시 덕양구 주교동 603 - 2 303호1046037.657608126.831712
2고양시시공인건축사사무소20140704운영중문화재수리업경기도 고양시 덕양구 무원로 6, 804호 (행신동)경기도 고양시 덕양구 행신동 709 - 1 804호1052337.613439126.832651
3고양시(주)고진티앤시20091203운영중문화재수리업경기도 고양시 일산동구 호수로 358-25, 922호 (백석동,동문타워II)경기도 고양시 일산동구 백석동 1324 - 0 동문타워II 922호41282737.639927126.78617
4고양시(주)선영건축20150430운영중문화재수리업경기도 고양시 덕양구 능곡로13번길 20, 2층 202호 (토당동)경기도 고양시 덕양구 토당동 344 - 73 202호1050837.622418126.820355
5고양시(주)현영종합건설20070116운영중문화재수리업경기도 고양시 덕양구 용현로5번길 24, 202호 (행신동)경기도 고양시 덕양구 행신동 763 - 2 202호43783637.613533126.834996
6고양시북촌불교미술보존연구소20161027운영중문화재수리업경기도 고양시 덕양구 통일로 140, A동 2층 221호 (동산동)경기도 고양시 덕양구 동산동 376 A동 221호1059437.64907126.901901
7고양시도화원(주)20150713운영중문화재수리업경기도 고양시 덕양구 호수로 76-14, 지층 (토당동)경기도 고양시 덕양구 토당동 647 - 98 지층1043737.623927126.808545
8고양시북촌불교미술보존연구소20160908운영중문화재수리업경기도 고양시 덕양구 통일로 140, A동 2층 21호 (동산동)경기도 고양시 덕양구 동산동 376 A동 21호1059437.64907126.901901
9고양시(주)넥스트앤파트너스20151021운영중문화재수리업경기도 고양시 덕양구 서정마을1로 20-10, 5층 504호 (행신동,근영타워)경기도 고양시 덕양구 행신동 1079 - 2 근영타워 504호1048637.618553126.846214
시군명사업장명인허가일자영업상태명문화체육업종명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
61파주시예담문화재(주)20160328운영중문화재수리업경기도 파주시 조리읍 장곡로 139경기도 파주시 조리읍 장곡리 1311094037.751037126.840987
62파주시주식회사 더나루20170324운영중문화재수리업경기도 파주시 문발로 141, 4층 403호 (문발동)경기도 파주시 문발동 530 - 1 403호1088137.707065126.685762
63파주시대헌주식회사20160513운영중문화재수리업경기도 파주시 지목로 70-25, 9동 202호 (문발동,파비뇽)경기도 파주시 문발동 263 - 31 파비뇽 9동 202호1088037.725001126.698966
64파주시주식회사 더나루20180312운영중문화재수리업경기도 파주시 문발로 141-0, 403호 (문발동)경기도 파주시 문발동 530 - 1 403호1088137.707065126.685762
65평택시창성그린개발20140314운영중문화재수리업경기도 평택시 산단로 54-0, 4층 1호 (모곡동,은혜빌딩)경기도 평택시 모곡동 442 - 2 은혜빌딩 401호1774637.036938127.076289
66평택시경안종합건설(주)20050826운영중문화재수리업경기도 평택시 상리길 27 (도일동)경기도 평택시 도일동 9546980537.057557127.119735
67평택시주식회사 광야20160726운영중문화재수리업경기도 평택시 포승읍 포승장안로 393-1경기도 평택시 포승읍 홍원리 142 - 01781337.013971126.879723
68포천시푸른나무병원20141208운영중문화재수리업경기도 포천시 중앙로78번길 39, B102호 (신읍동)경기도 포천시 신읍동 28 - 351114537.895779127.20352
69화성시그린종합조경20050826운영중문화재수리업경기도 화성시 향남읍 백토관리길 113-112, 2층경기도 화성시 향남읍 관리 246 - 344082037.126237126.944101
70화성시금세기종합건설(주)20050826운영중문화재수리업경기도 화성시 효행로 508-4, 1·2층 (안녕동)경기도 화성시 안녕동 186 - 17044597637.206294126.988784