Overview

Dataset statistics

Number of variables7
Number of observations88
Missing cells78
Missing cells (%)12.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory60.5 B

Variable types

Categorical1
Text3
Numeric3

Dataset

Description전문도서관 현황
Author한국과학기술정보연구원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=NHAKFMCWGIWC9DC8ZU3S21463402&infSeq=1

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
소재지도로명주소 has 41 (46.6%) missing valuesMissing
소재지우편번호 has 37 (42.0%) missing valuesMissing
도서관명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:36:28.250986
Analysis finished2023-12-10 21:36:30.284292
Duration2.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size836.0 B
용인시
14 
수원시
11 
성남시
9 
안양시
8 
고양시
7 
Other values (15)
39 

Length

Max length4
Median length3
Mean length3.0113636
Min length3

Unique

Unique5 ?
Unique (%)5.7%

Sample

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

Common Values

ValueCountFrequency (%)
용인시 14
15.9%
수원시 11
12.5%
성남시 9
10.2%
안양시 8
9.1%
고양시 7
8.0%
화성시 7
8.0%
부천시 4
 
4.5%
안산시 4
 
4.5%
이천시 4
 
4.5%
평택시 3
 
3.4%
Other values (10) 17
19.3%

Length

2023-12-11T06:36:30.367433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용인시 14
15.9%
수원시 11
12.5%
성남시 9
10.2%
안양시 8
9.1%
고양시 7
8.0%
화성시 7
8.0%
부천시 4
 
4.5%
안산시 4
 
4.5%
이천시 4
 
4.5%
안성시 3
 
3.4%
Other values (10) 17
19.3%

도서관명
Text

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2023-12-11T06:36:30.602631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.2386364
Min length1

Characters and Unicode

Total characters637
Distinct characters166
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)100.0%

Sample

1st row한국건설기술연구원
2nd row한국교통연구원
3rd row국립암센터
4th row인제대학교일산백병원
5th row동국대학교일산불교병원
ValueCountFrequency (%)
한국건설기술연구원 1
 
1.1%
한국교통연구원 1
 
1.1%
강남대학교 1
 
1.1%
코오롱연구소 1
 
1.1%
삼성종합기술원 1
 
1.1%
유한양행 1
 
1.1%
삼성sdi 1
 
1.1%
주)한국야쿠르트 1
 
1.1%
주)대웅제약 1
 
1.1%
한국외국어대학교글로벌캠퍼스 1
 
1.1%
Other values (78) 78
88.6%
2023-12-11T06:36:31.020107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 51
 
8.0%
학 50
 
7.8%
교 35
 
5.5%
원 27
 
4.2%
국 20
 
3.1%
한 17
 
2.7%
연 17
 
2.7%
성 16
 
2.5%
구 16
 
2.5%
제 12
 
1.9%
Other values (156) 376
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 597
93.7%
Uppercase Letter 15
 
2.4%
Close Punctuation 9
 
1.4%
Open Punctuation 9
 
1.4%
Lowercase Letter 6
 
0.9%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 51
 
8.5%
학 50
 
8.4%
교 35
 
5.9%
원 27
 
4.5%
국 20
 
3.4%
한 17
 
2.8%
연 17
 
2.8%
성 16
 
2.7%
구 16
 
2.7%
제 12
 
2.0%
Other values (139) 336
56.3%
Uppercase Letter
ValueCountFrequency (%)
S 4
26.7%
C 2
13.3%
L 2
13.3%
D 2
13.3%
K 2
13.3%
I 1
 
6.7%
G 1
 
6.7%
J 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
p 1
16.7%
s 1
16.7%
i 1
16.7%
l 1
16.7%
a 1
16.7%
y 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 598
93.9%
Latin 21
 
3.3%
Common 18
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 51
 
8.5%
학 50
 
8.4%
교 35
 
5.9%
원 27
 
4.5%
국 20
 
3.3%
한 17
 
2.8%
연 17
 
2.8%
성 16
 
2.7%
구 16
 
2.7%
제 12
 
2.0%
Other values (140) 337
56.4%
Latin
ValueCountFrequency (%)
S 4
19.0%
C 2
9.5%
L 2
9.5%
D 2
9.5%
K 2
9.5%
p 1
 
4.8%
I 1
 
4.8%
s 1
 
4.8%
i 1
 
4.8%
l 1
 
4.8%
Other values (4) 4
19.0%
Common
ValueCountFrequency (%)
) 9
50.0%
( 9
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 597
93.7%
ASCII 39
 
6.1%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 51
 
8.5%
학 50
 
8.4%
교 35
 
5.9%
원 27
 
4.5%
국 20
 
3.4%
한 17
 
2.8%
연 17
 
2.8%
성 16
 
2.7%
구 16
 
2.7%
제 12
 
2.0%
Other values (139) 336
56.3%
ASCII
ValueCountFrequency (%)
) 9
23.1%
( 9
23.1%
S 4
10.3%
C 2
 
5.1%
L 2
 
5.1%
D 2
 
5.1%
K 2
 
5.1%
p 1
 
2.6%
I 1
 
2.6%
s 1
 
2.6%
Other values (6) 6
15.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지도로명주소
Text

MISSING 

Distinct47
Distinct (%)100.0%
Missing41
Missing (%)46.6%
Memory size836.0 B
2023-12-11T06:36:31.359439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length19.617021
Min length14

Characters and Unicode

Total characters922
Distinct characters105
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

Unique47 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산서구 고양대로 315
2nd row경기도 고양시 일산동구 일산로 323
3rd row경기도 고양시 일산서구 주화로 170
4th row경기도 고양시 일산동구 동국로 27
5th row경기도 고양시 일산동구 일산로 100
ValueCountFrequency (%)
경기도 47
 
20.8%
용인시 12
 
5.3%
기흥구 8
 
3.5%
성남시 5
 
2.2%
고양시 5
 
2.2%
영통구 4
 
1.8%
수원시 4
 
1.8%
안양시 4
 
1.8%
의왕시 3
 
1.3%
분당구 3
 
1.3%
Other values (117) 131
58.0%
2023-12-11T06:36:31.778440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
19.4%
기 58
 
6.3%
시 49
 
5.3%
경 48
 
5.2%
도 48
 
5.2%
로 46
 
5.0%
구 32
 
3.5%
1 30
 
3.3%
2 30
 
3.3%
5 19
 
2.1%
Other values (95) 383
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 586
63.6%
Space Separator 179
 
19.4%
Decimal Number 155
 
16.8%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 58
 
9.9%
시 49
 
8.4%
경 48
 
8.2%
도 48
 
8.2%
로 46
 
7.8%
구 32
 
5.5%
인 16
 
2.7%
용 14
 
2.4%
산 12
 
2.0%
성 12
 
2.0%
Other values (83) 251
42.8%
Decimal Number
ValueCountFrequency (%)
1 30
19.4%
2 30
19.4%
5 19
12.3%
0 17
11.0%
7 15
9.7%
4 14
9.0%
3 13
8.4%
9 6
 
3.9%
8 6
 
3.9%
6 5
 
3.2%
Space Separator
ValueCountFrequency (%)
179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 586
63.6%
Common 336
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 58
 
9.9%
시 49
 
8.4%
경 48
 
8.2%
도 48
 
8.2%
로 46
 
7.8%
구 32
 
5.5%
인 16
 
2.7%
용 14
 
2.4%
산 12
 
2.0%
성 12
 
2.0%
Other values (83) 251
42.8%
Common
ValueCountFrequency (%)
179
53.3%
1 30
 
8.9%
2 30
 
8.9%
5 19
 
5.7%
0 17
 
5.1%
7 15
 
4.5%
4 14
 
4.2%
3 13
 
3.9%
9 6
 
1.8%
8 6
 
1.8%
Other values (2) 7
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 586
63.6%
ASCII 336
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
53.3%
1 30
 
8.9%
2 30
 
8.9%
5 19
 
5.7%
0 17
 
5.1%
7 15
 
4.5%
4 14
 
4.2%
3 13
 
3.9%
9 6
 
1.8%
8 6
 
1.8%
Other values (2) 7
 
2.1%
Hangul
ValueCountFrequency (%)
기 58
 
9.9%
시 49
 
8.4%
경 48
 
8.2%
도 48
 
8.2%
로 46
 
7.8%
구 32
 
5.5%
인 16
 
2.7%
용 14
 
2.4%
산 12
 
2.0%
성 12
 
2.0%
Other values (83) 251
42.8%

소재지지번주소
Text

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2023-12-11T06:36:32.028481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length37
Mean length28.522727
Min length14

Characters and Unicode

Total characters2510
Distinct characters225
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

Unique88 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산서구 시민대로 1190
2nd row경기도 고양시 일산서구 대화동 2311번지 한국교통연구원
3rd row경기도 고양시 일산동구 마두1동 국립암센터
4th row경기도 고양시 일산서구 대화동 2240번지
5th row경기도 고양시 일산동구 식사동 동국대일산불교종합병원
ValueCountFrequency (%)
경기도 88
 
17.6%
용인시 14
 
2.8%
수원시 11
 
2.2%
기흥구 10
 
2.0%
성남시 9
 
1.8%
중앙도서관 9
 
1.8%
안양시 8
 
1.6%
도서관 8
 
1.6%
고양시 7
 
1.4%
화성시 7
 
1.4%
Other values (259) 330
65.9%
2023-12-11T06:36:32.417663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
413
 
16.5%
도 118
 
4.7%
기 110
 
4.4%
경 94
 
3.7%
시 91
 
3.6%
동 87
 
3.5%
1 87
 
3.5%
구 74
 
2.9%
학 46
 
1.8%
대 45
 
1.8%
Other values (215) 1345
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1720
68.5%
Space Separator 413
 
16.5%
Decimal Number 289
 
11.5%
Dash Punctuation 39
 
1.6%
Uppercase Letter 28
 
1.1%
Open Punctuation 7
 
0.3%
Close Punctuation 7
 
0.3%
Lowercase Letter 6
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 118
 
6.9%
기 110
 
6.4%
경 94
 
5.5%
시 91
 
5.3%
동 87
 
5.1%
구 74
 
4.3%
학 46
 
2.7%
대 45
 
2.6%
서 38
 
2.2%
안 36
 
2.1%
Other values (181) 981
57.0%
Uppercase Letter
ValueCountFrequency (%)
D 4
14.3%
C 3
10.7%
K 3
10.7%
L 3
10.7%
I 3
10.7%
S 3
10.7%
R 2
7.1%
A 2
7.1%
G 1
 
3.6%
N 1
 
3.6%
Other values (3) 3
10.7%
Decimal Number
ValueCountFrequency (%)
1 87
30.1%
2 43
14.9%
4 28
 
9.7%
3 27
 
9.3%
5 24
 
8.3%
0 21
 
7.3%
6 21
 
7.3%
8 14
 
4.8%
7 14
 
4.8%
9 10
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
s 1
16.7%
i 1
16.7%
l 1
16.7%
p 1
16.7%
a 1
16.7%
y 1
16.7%
Space Separator
ValueCountFrequency (%)
413
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1720
68.5%
Common 756
30.1%
Latin 34
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 118
 
6.9%
기 110
 
6.4%
경 94
 
5.5%
시 91
 
5.3%
동 87
 
5.1%
구 74
 
4.3%
학 46
 
2.7%
대 45
 
2.6%
서 38
 
2.2%
안 36
 
2.1%
Other values (181) 981
57.0%
Latin
ValueCountFrequency (%)
D 4
11.8%
C 3
 
8.8%
K 3
 
8.8%
L 3
 
8.8%
I 3
 
8.8%
S 3
 
8.8%
R 2
 
5.9%
A 2
 
5.9%
G 1
 
2.9%
s 1
 
2.9%
Other values (9) 9
26.5%
Common
ValueCountFrequency (%)
413
54.6%
1 87
 
11.5%
2 43
 
5.7%
- 39
 
5.2%
4 28
 
3.7%
3 27
 
3.6%
5 24
 
3.2%
0 21
 
2.8%
6 21
 
2.8%
8 14
 
1.9%
Other values (5) 39
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1720
68.5%
ASCII 790
31.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
413
52.3%
1 87
 
11.0%
2 43
 
5.4%
- 39
 
4.9%
4 28
 
3.5%
3 27
 
3.4%
5 24
 
3.0%
0 21
 
2.7%
6 21
 
2.7%
8 14
 
1.8%
Other values (24) 73
 
9.2%
Hangul
ValueCountFrequency (%)
도 118
 
6.9%
기 110
 
6.4%
경 94
 
5.5%
시 91
 
5.3%
동 87
 
5.1%
구 74
 
4.3%
학 46
 
2.7%
대 45
 
2.6%
서 38
 
2.2%
안 36
 
2.1%
Other values (181) 981
57.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct50
Distinct (%)98.0%
Missing37
Missing (%)42.0%
Infinite0
Infinite (%)0.0%
Mean15400.941
Minimum10223
Maximum18364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2023-12-11T06:36:32.589668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10223
5-th percentile10394
Q114059
median16227
Q317085
95-th percentile18110
Maximum18364
Range8141
Interquartile range (IQR)3026

Descriptive statistics

Standard deviation2368.6543
Coefficient of variation (CV)0.15379932
Kurtosis-0.2408243
Mean15400.941
Median Absolute Deviation (MAD)1511
Skewness-0.85702887
Sum785448
Variance5610523
MonotonicityNot monotonic
2023-12-11T06:36:32.788399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17084 2
 
2.3%
17074 1
 
1.1%
18119 1
 
1.1%
16890 1
 
1.1%
16911 1
 
1.1%
17092 1
 
1.1%
17035 1
 
1.1%
17028 1
 
1.1%
17086 1
 
1.1%
16979 1
 
1.1%
Other values (40) 40
45.5%
(Missing) 37
42.0%
ValueCountFrequency (%)
10223 1
1.1%
10326 1
1.1%
10380 1
1.1%
10408 1
1.1%
10444 1
1.1%
11618 1
1.1%
12773 1
1.1%
13120 1
1.1%
13281 1
1.1%
13494 1
1.1%
ValueCountFrequency (%)
18364 1
1.1%
18332 1
1.1%
18119 1
1.1%
18101 1
1.1%
17956 1
1.1%
17870 1
1.1%
17738 1
1.1%
17546 1
1.1%
17520 1
1.1%
17384 1
1.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.349231
Minimum36.981609
Maximum37.87404
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2023-12-11T06:36:33.020358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.981609
5-th percentile37.056391
Q137.249469
median37.314845
Q337.41892
95-th percentile37.67558
Maximum37.87404
Range0.8924311
Interquartile range (IQR)0.1694513

Descriptive statistics

Standard deviation0.17789505
Coefficient of variation (CV)0.0047630177
Kurtosis0.86246474
Mean37.349231
Median Absolute Deviation (MAD)0.08288675
Skewness0.66150013
Sum3286.7323
Variance0.031646648
MonotonicityNot monotonic
2023-12-11T06:36:33.153916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6692721 1
 
1.1%
37.3739002 1
 
1.1%
37.2429722 1
 
1.1%
37.2759651 1
 
1.1%
37.3009153 1
 
1.1%
37.2319001 1
 
1.1%
37.314942 1
 
1.1%
37.2371342 1
 
1.1%
37.2226398 1
 
1.1%
37.2832043 1
 
1.1%
Other values (78) 78
88.6%
ValueCountFrequency (%)
36.9816092 1
1.1%
36.9952372 1
1.1%
37.0033066 1
1.1%
37.0113537 1
1.1%
37.0514867 1
1.1%
37.0655002 1
1.1%
37.1555966 1
1.1%
37.1563661 1
1.1%
37.1932815 1
1.1%
37.1937772 1
1.1%
ValueCountFrequency (%)
37.8740403 1
1.1%
37.812251 1
1.1%
37.746462 1
1.1%
37.7446571 1
1.1%
37.6763735 1
1.1%
37.674105 1
1.1%
37.6722719 1
1.1%
37.6692721 1
1.1%
37.6631658 1
1.1%
37.6455064 1
1.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.01336
Minimum126.54945
Maximum127.48672
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2023-12-11T06:36:33.280064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54945
5-th percentile126.74488
Q1126.91727
median127.0257
Q3127.12248
95-th percentile127.3251
Maximum127.48672
Range0.9372711
Interquartile range (IQR)0.20520915

Descriptive statistics

Standard deviation0.17341351
Coefficient of variation (CV)0.0013653171
Kurtosis0.33398408
Mean127.01336
Median Absolute Deviation (MAD)0.1006767
Skewness0.16573266
Sum11177.175
Variance0.030072245
MonotonicityNot monotonic
2023-12-11T06:36:33.444040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.739102 1
 
1.1%
126.9488614 1
 
1.1%
127.0800536 1
 
1.1%
127.1338748 1
 
1.1%
127.1271371 1
 
1.1%
127.0851659 1
 
1.1%
126.989372 1
 
1.1%
127.1108588 1
 
1.1%
127.1052074 1
 
1.1%
127.2405624 1
 
1.1%
Other values (78) 78
88.6%
ValueCountFrequency (%)
126.5494537 1
1.1%
126.7332601 1
1.1%
126.7375677 1
1.1%
126.739102 1
1.1%
126.741929 1
1.1%
126.75035 1
1.1%
126.761234 1
1.1%
126.7788147 1
1.1%
126.7833772 1
1.1%
126.791157 1
1.1%
ValueCountFrequency (%)
127.4867248 1
1.1%
127.4221104 1
1.1%
127.41272 1
1.1%
127.359601 1
1.1%
127.3547011 1
1.1%
127.2701284 1
1.1%
127.2651287 1
1.1%
127.2405624 1
1.1%
127.2312927 1
1.1%
127.1883291 1
1.1%

Interactions

2023-12-11T06:36:29.309927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:28.661194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:28.982354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:29.450750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:28.754313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:29.080290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:29.528941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:28.858748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:29.196375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:36:33.568835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명도서관명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0001.0001.0000.9870.9820.950
도서관명1.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.000
소재지우편번호0.9871.0001.0001.0001.0000.8830.656
WGS84위도0.9821.0001.0001.0000.8831.0000.759
WGS84경도0.9501.0001.0001.0000.6560.7591.000
2023-12-11T06:36:33.666670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명
소재지우편번호1.000-0.9350.3840.867
WGS84위도-0.9351.000-0.4220.725
WGS84경도0.384-0.4221.0000.606
시군명0.8670.7250.6061.000

Missing values

2023-12-11T06:36:29.661997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:36:29.821471image/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.
2023-12-11T06:36:30.231567image/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

시군명도서관명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0고양시한국건설기술연구원<NA>경기도 고양시 일산서구 시민대로 1190<NA>37.669272126.739102
1고양시한국교통연구원경기도 고양시 일산서구 고양대로 315경기도 고양시 일산서구 대화동 2311번지 한국교통연구원1022337.672272126.741929
2고양시국립암센터경기도 고양시 일산동구 일산로 323경기도 고양시 일산동구 마두1동 국립암센터1040837.663166126.783377
3고양시인제대학교일산백병원경기도 고양시 일산서구 주화로 170경기도 고양시 일산서구 대화동 2240번지1038037.674105126.75035
4고양시동국대학교일산불교병원경기도 고양시 일산동구 동국로 27경기도 고양시 일산동구 식사동 동국대일산불교종합병원1032637.676373126.806399
5고양시한국항공대학교<NA>경기도 고양시 덕양구 화전동 200-1한국항공대학교 중앙도서관 학술정보팀<NA>37.598099126.864409
6고양시국민건강보험공단일산병원경기도 고양시 일산동구 일산로 100경기도 고양시 일산동구 백석동 12321044437.645506126.793014
7과천시정보통신정책연구원<NA>경기도 과천시 주암동 정보통신정책연구원1-1<NA>37.464137127.031457
8과천시서울시보건환경연구원<NA>경기도 과천시 용머리2길 18(주암동1)<NA>37.464376127.032187
9광주시에피밸리경기도 광주시 오포읍 오포로 240경기도 광주시 오포읍 능평리51-2번지1277337.348893127.188329
시군명도서관명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
78평택시평택대학교<NA>경기도 평택시 용이동 111번지 평택대학교 도서관1787036.995237127.133443
79평택시동우화인켐주식회사경기도 평택시 포승읍 포승공단로117번길 35경기도 평택시 포승읍 원정리 1177동우화인켐(주) 지적재산팀1795636.981609126.842866
80포천시대진대학교<NA>경기도 포천시 선단동 산 11-1대진대학교 중앙도서관<NA>37.87404127.157478
81화성시중외제약(주)<NA>경기도 화성시 안녕동 146-141(주)중외제약 중앙연구소<NA>37.199005126.9994
82화성시C경기도 화성시 안녕남로 171경기도 화성시 안녕동 146-1411836437.198766126.999485
83화성시수원대학교<NA>경기도 화성시 봉담읍 와우리 산2-2수원대학교 중앙도서관<NA>37.208627126.975764
84화성시현대자동차남양연구소<NA>경기도 화성시 장덕동 현대자동차,기아자동차남양연구소연구개발교육팀<NA>37.155597126.81643
85화성시일동제약<NA>경기도 화성시 석우동 23-9일동제약 연구지원팀<NA>37.220607127.075038
86화성시협성대학교<NA>경기도 화성시 봉담읍 상리 14협성대학교 학술정보관<NA>37.212938126.952786
87화성시수원가톨릭대학교경기도 화성시 봉담읍 왕림1길 67경기도 화성시 봉담읍 왕림리 220-1번지1833237.193777126.933761