Overview

Dataset statistics

Number of variables9
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory81.3 B

Variable types

Text4
Categorical2
Numeric3

Dataset

Description병원평가정보(폐암) 현황
Author건강보험심사평가원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=69Y7E4Q7HW6TDYC9B0UI21283283&infSeq=1

Alerts

평가내역 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
기관명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지우편번호 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:01:12.603441
Analysis finished2023-12-10 21:01:14.305167
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct11
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T06:01:14.400051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.047619
Min length3

Characters and Unicode

Total characters64
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)23.8%

Sample

1st row수원시
2nd row의정부시
3rd row고양시
4th row성남시
5th row부천시
ValueCountFrequency (%)
고양시 5
23.8%
성남시 3
14.3%
수원시 2
 
9.5%
부천시 2
 
9.5%
안산시 2
 
9.5%
안양시 2
 
9.5%
의정부시 1
 
4.8%
화성시 1
 
4.8%
군포시 1
 
4.8%
평택시 1
 
4.8%
2023-12-11T06:01:14.677946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
32.8%
7
 
10.9%
5
 
7.8%
4
 
6.2%
4
 
6.2%
3
 
4.7%
3
 
4.7%
2
 
3.1%
2
 
3.1%
2
 
3.1%
Other values (10) 11
17.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
21
32.8%
7
 
10.9%
5
 
7.8%
4
 
6.2%
4
 
6.2%
3
 
4.7%
3
 
4.7%
2
 
3.1%
2
 
3.1%
2
 
3.1%
Other values (10) 11
17.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
21
32.8%
7
 
10.9%
5
 
7.8%
4
 
6.2%
4
 
6.2%
3
 
4.7%
3
 
4.7%
2
 
3.1%
2
 
3.1%
2
 
3.1%
Other values (10) 11
17.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
21
32.8%
7
 
10.9%
5
 
7.8%
4
 
6.2%
4
 
6.2%
3
 
4.7%
3
 
4.7%
2
 
3.1%
2
 
3.1%
2
 
3.1%
Other values (10) 11
17.2%

기관명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T06:01:14.873946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length11.238095
Min length5

Characters and Unicode

Total characters236
Distinct characters70
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row가톨릭대학교 성빈센트병원
2nd row가톨릭대학교의정부성모병원
3rd row국립암센터
4th row대진의료재단 분당제생병원
5th row순천향대학교부속부천병원
ValueCountFrequency (%)
효산의료재단 2
 
7.7%
가톨릭대학교 1
 
3.8%
굿모닝병원 1
 
3.8%
대아의료재단한도병원 1
 
3.8%
한양대학교구리병원 1
 
3.8%
한림대학교성심병원 1
 
3.8%
차의과학대학교분당차병원 1
 
3.8%
의료법인명지의료재단명지병원 1
 
3.8%
분당서울대학교병원 1
 
3.8%
동국대학교일산불교병원 1
 
3.8%
Other values (15) 15
57.7%
2023-12-11T06:01:15.433265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
8.5%
20
 
8.5%
16
 
6.8%
15
 
6.4%
14
 
5.9%
11
 
4.7%
8
 
3.4%
7
 
3.0%
6
 
2.5%
6
 
2.5%
Other values (60) 113
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 231
97.9%
Space Separator 5
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20
 
8.7%
20
 
8.7%
16
 
6.9%
15
 
6.5%
14
 
6.1%
11
 
4.8%
8
 
3.5%
7
 
3.0%
6
 
2.6%
6
 
2.6%
Other values (59) 108
46.8%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 231
97.9%
Common 5
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20
 
8.7%
20
 
8.7%
16
 
6.9%
15
 
6.5%
14
 
6.1%
11
 
4.8%
8
 
3.5%
7
 
3.0%
6
 
2.6%
6
 
2.6%
Other values (59) 108
46.8%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 231
97.9%
ASCII 5
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
20
 
8.7%
20
 
8.7%
16
 
6.9%
15
 
6.5%
14
 
6.1%
11
 
4.8%
8
 
3.5%
7
 
3.0%
6
 
2.6%
6
 
2.6%
Other values (59) 108
46.8%
ASCII
ValueCountFrequency (%)
5
100.0%

평가내역
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
폐암
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐암 21
100.0%

Length

2023-12-11T06:01:15.558788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:01:15.651474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐암 21
100.0%

평가등급
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
1등급
18 
등급제외

Length

Max length4
Median length3
Mean length3.1428571
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1등급
2nd row1등급
3rd row1등급
4th row1등급
5th row1등급

Common Values

ValueCountFrequency (%)
1등급 18
85.7%
등급제외 3
 
14.3%

Length

2023-12-11T06:01:15.761757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:01:15.871843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1등급 18
85.7%
등급제외 3
 
14.3%
Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T06:01:16.052803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length18.571429
Min length14

Characters and Unicode

Total characters390
Distinct characters78
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row경기도 수원시 팔달구 중부대로 93
2nd row경기도 의정부시 천보로 271
3rd row경기도 고양시 일산동구 일산로 323
4th row경기도 성남시 분당구 서현로180번길 20
5th row경기도 부천시 조마루로 170
ValueCountFrequency (%)
경기도 21
 
21.4%
고양시 5
 
5.1%
성남시 3
 
3.1%
분당구 3
 
3.1%
일산동구 3
 
3.1%
수원시 2
 
2.0%
안양시 2
 
2.0%
170 2
 
2.0%
안산시 2
 
2.0%
부천시 2
 
2.0%
Other values (51) 53
54.1%
2023-12-11T06:01:16.430108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
19.7%
22
 
5.6%
21
 
5.4%
21
 
5.4%
21
 
5.4%
20
 
5.1%
16
 
4.1%
1 13
 
3.3%
3 10
 
2.6%
2 9
 
2.3%
Other values (68) 160
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 250
64.1%
Space Separator 77
 
19.7%
Decimal Number 63
 
16.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
22
 
8.8%
21
 
8.4%
21
 
8.4%
21
 
8.4%
20
 
8.0%
16
 
6.4%
8
 
3.2%
8
 
3.2%
6
 
2.4%
6
 
2.4%
Other values (57) 101
40.4%
Decimal Number
ValueCountFrequency (%)
1 13
20.6%
3 10
15.9%
2 9
14.3%
7 8
12.7%
0 8
12.7%
5 5
 
7.9%
9 4
 
6.3%
8 3
 
4.8%
4 2
 
3.2%
6 1
 
1.6%
Space Separator
ValueCountFrequency (%)
77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 250
64.1%
Common 140
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
22
 
8.8%
21
 
8.4%
21
 
8.4%
21
 
8.4%
20
 
8.0%
16
 
6.4%
8
 
3.2%
8
 
3.2%
6
 
2.4%
6
 
2.4%
Other values (57) 101
40.4%
Common
ValueCountFrequency (%)
77
55.0%
1 13
 
9.3%
3 10
 
7.1%
2 9
 
6.4%
7 8
 
5.7%
0 8
 
5.7%
5 5
 
3.6%
9 4
 
2.9%
8 3
 
2.1%
4 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 250
64.1%
ASCII 140
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
55.0%
1 13
 
9.3%
3 10
 
7.1%
2 9
 
6.4%
7 8
 
5.7%
0 8
 
5.7%
5 5
 
3.6%
9 4
 
2.9%
8 3
 
2.1%
4 2
 
1.4%
Hangul
ValueCountFrequency (%)
22
 
8.8%
21
 
8.4%
21
 
8.4%
21
 
8.4%
20
 
8.0%
16
 
6.4%
8
 
3.2%
8
 
3.2%
6
 
2.4%
6
 
2.4%
Other values (57) 101
40.4%
Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T06:01:16.674261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length24.095238
Min length16

Characters and Unicode

Total characters506
Distinct characters86
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

Unique21 ?
Unique (%)100.0%

Sample

1st row경기도 수원시 팔달구 지동 93-6번지
2nd row경기도 의정부시 금오동 65-1번지 의정부성모병원
3rd row경기도 고양시 일산동구 마두동 809번지
4th row경기도 성남시 분당구 서현동 255-2번지
5th row경기도 부천시 중동 1174번지
ValueCountFrequency (%)
경기도 21
 
19.6%
고양시 5
 
4.7%
분당구 3
 
2.8%
성남시 3
 
2.8%
일산동구 3
 
2.8%
수원시 2
 
1.9%
안산시 2
 
1.9%
안양시 2
 
1.9%
부천시 2
 
1.9%
단원구 2
 
1.9%
Other values (62) 62
57.9%
2023-12-11T06:01:17.080205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
17.0%
27
 
5.3%
23
 
4.5%
21
 
4.2%
21
 
4.2%
21
 
4.2%
21
 
4.2%
21
 
4.2%
1 17
 
3.4%
16
 
3.2%
Other values (76) 232
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 333
65.8%
Space Separator 86
 
17.0%
Decimal Number 76
 
15.0%
Dash Punctuation 8
 
1.6%
Open Punctuation 1
 
0.2%
Uppercase Letter 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
27
 
8.1%
23
 
6.9%
21
 
6.3%
21
 
6.3%
21
 
6.3%
21
 
6.3%
21
 
6.3%
16
 
4.8%
12
 
3.6%
10
 
3.0%
Other values (61) 140
42.0%
Decimal Number
ValueCountFrequency (%)
1 17
22.4%
2 10
13.2%
6 9
11.8%
0 7
9.2%
4 7
9.2%
3 7
9.2%
5 5
 
6.6%
8 5
 
6.6%
9 5
 
6.6%
7 4
 
5.3%
Space Separator
ValueCountFrequency (%)
86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 333
65.8%
Common 172
34.0%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
27
 
8.1%
23
 
6.9%
21
 
6.3%
21
 
6.3%
21
 
6.3%
21
 
6.3%
21
 
6.3%
16
 
4.8%
12
 
3.6%
10
 
3.0%
Other values (61) 140
42.0%
Common
ValueCountFrequency (%)
86
50.0%
1 17
 
9.9%
2 10
 
5.8%
6 9
 
5.2%
- 8
 
4.7%
0 7
 
4.1%
4 7
 
4.1%
3 7
 
4.1%
5 5
 
2.9%
8 5
 
2.9%
Other values (4) 11
 
6.4%
Latin
ValueCountFrequency (%)
G 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 333
65.8%
ASCII 173
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
49.7%
1 17
 
9.8%
2 10
 
5.8%
6 9
 
5.2%
- 8
 
4.6%
0 7
 
4.0%
4 7
 
4.0%
3 7
 
4.0%
5 5
 
2.9%
8 5
 
2.9%
Other values (5) 12
 
6.9%
Hangul
ValueCountFrequency (%)
27
 
8.1%
23
 
6.9%
21
 
6.3%
21
 
6.3%
21
 
6.3%
21
 
6.3%
21
 
6.3%
16
 
4.8%
12
 
3.6%
10
 
3.0%
Other values (61) 140
42.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13780.333
Minimum10326
Maximum18450
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T06:01:17.258309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10326
5-th percentile10380
Q111765
median14030
Q315367
95-th percentile17874
Maximum18450
Range8124
Interquartile range (IQR)3602

Descriptive statistics

Standard deviation2523.831
Coefficient of variation (CV)0.18314731
Kurtosis-0.91763241
Mean13780.333
Median Absolute Deviation (MAD)2107
Skewness0.057070045
Sum289387
Variance6369722.9
MonotonicityNot monotonic
2023-12-11T06:01:17.407330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
16247 1
 
4.8%
11765 1
 
4.8%
14030 1
 
4.8%
15367 1
 
4.8%
11923 1
 
4.8%
14068 1
 
4.8%
13496 1
 
4.8%
10475 1
 
4.8%
13620 1
 
4.8%
10326 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
10326 1
4.8%
10380 1
4.8%
10408 1
4.8%
10444 1
4.8%
10475 1
4.8%
11765 1
4.8%
11923 1
4.8%
13496 1
4.8%
13590 1
4.8%
13620 1
4.8%
ValueCountFrequency (%)
18450 1
4.8%
17874 1
4.8%
16499 1
4.8%
16247 1
4.8%
15839 1
4.8%
15367 1
4.8%
15355 1
4.8%
14647 1
4.8%
14584 1
4.8%
14068 1
4.8%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.445636
Minimum36.990565
Maximum37.758523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T06:01:17.586241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.990565
5-th percentile37.216496
Q137.334055
median37.392894
Q337.642475
95-th percentile37.676439
Maximum37.758523
Range0.76795781
Interquartile range (IQR)0.30841927

Descriptive statistics

Standard deviation0.19087302
Coefficient of variation (CV)0.0050973369
Kurtosis-0.0044973976
Mean37.445636
Median Absolute Deviation (MAD)0.11355065
Skewness-0.28816253
Sum786.35836
Variance0.036432511
MonotonicityNot monotonic
2023-12-11T06:01:17.764055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
37.2779105554 1
 
4.8%
37.7585227082 1
 
4.8%
37.3928939479 1
 
4.8%
37.3340553037 1
 
4.8%
37.6011883667 1
 
4.8%
37.3916536825 1
 
4.8%
37.4104664747 1
 
4.8%
37.6424745722 1
 
4.8%
37.3520167812 1
 
4.8%
37.6764385211 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
36.9905649024 1
4.8%
37.2164957291 1
4.8%
37.2779105554 1
4.8%
37.2793432963 1
4.8%
37.3188593416 1
4.8%
37.3340553037 1
4.8%
37.3520167812 1
4.8%
37.3586407829 1
4.8%
37.3882075823 1
4.8%
37.3916536825 1
4.8%
ValueCountFrequency (%)
37.7585227082 1
4.8%
37.6764385211 1
4.8%
37.6742710122 1
4.8%
37.6632367324 1
4.8%
37.6454752678 1
4.8%
37.6424745722 1
4.8%
37.6011883667 1
4.8%
37.4983685015 1
4.8%
37.4872746674 1
4.8%
37.4104664747 1
4.8%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.94493
Minimum126.75038
Maximum127.13252
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T06:01:17.962777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.75038
5-th percentile126.76211
Q1126.80556
median126.9473
Q3127.07994
95-th percentile127.12583
Maximum127.13252
Range0.38213554
Interquartile range (IQR)0.27437861

Descriptive statistics

Standard deviation0.14576354
Coefficient of variation (CV)0.0011482423
Kurtosis-1.7925881
Mean126.94493
Median Absolute Deviation (MAD)0.14174084
Skewness0.045097359
Sum2665.8435
Variance0.021247008
MonotonicityNot monotonic
2023-12-11T06:01:18.131256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
127.0279830169 1
 
4.8%
127.0779287098 1
 
4.8%
126.9248195521 1
 
4.8%
126.8076211068 1
 
4.8%
127.1325173047 1
 
4.8%
126.961973707 1
 
4.8%
127.1258348309 1
 
4.8%
126.8317454892 1
 
4.8%
127.1244991912 1
 
4.8%
126.805563051 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
126.7503817665 1
4.8%
126.7621105079 1
4.8%
126.783395561 1
4.8%
126.7929631952 1
4.8%
126.7933597441 1
4.8%
126.805563051 1
4.8%
126.8076211068 1
4.8%
126.8249943518 1
4.8%
126.8317454892 1
4.8%
126.9248195521 1
4.8%
ValueCountFrequency (%)
127.1325173047 1
4.8%
127.1258348309 1
4.8%
127.1244991912 1
4.8%
127.1217770322 1
4.8%
127.1204512355 1
4.8%
127.0799416615 1
4.8%
127.0779287098 1
4.8%
127.0463045226 1
4.8%
127.0279830169 1
4.8%
126.961973707 1
4.8%

Interactions

2023-12-11T06:01:13.700099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:13.013346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:13.378402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:13.823887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:13.138954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:13.491241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:13.932358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:13.265954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:13.591455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:01:18.292022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명기관명평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0000.5271.0001.0000.9570.9860.819
기관명1.0001.0001.0001.0001.0001.0001.0001.000
평가등급0.5271.0001.0001.0001.0000.0000.2400.344
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호0.9571.0000.0001.0001.0001.0000.9400.725
WGS84위도0.9861.0000.2401.0001.0000.9401.0000.621
WGS84경도0.8191.0000.3441.0001.0000.7250.6211.000
2023-12-11T06:01:18.442714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도평가등급
소재지우편번호1.000-0.9080.3000.000
WGS84위도-0.9081.000-0.4340.132
WGS84경도0.300-0.4341.0000.171
평가등급0.0000.1320.1711.000

Missing values

2023-12-11T06:01:14.094906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:01:14.249899image/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

시군명기관명평가내역평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0수원시가톨릭대학교 성빈센트병원폐암1등급경기도 수원시 팔달구 중부대로 93경기도 수원시 팔달구 지동 93-6번지1624737.277911127.027983
1의정부시가톨릭대학교의정부성모병원폐암1등급경기도 의정부시 천보로 271경기도 의정부시 금오동 65-1번지 의정부성모병원1176537.758523127.077929
2고양시국립암센터폐암1등급경기도 고양시 일산동구 일산로 323경기도 고양시 일산동구 마두동 809번지1040837.663237126.783396
3성남시대진의료재단 분당제생병원폐암1등급경기도 성남시 분당구 서현로180번길 20경기도 성남시 분당구 서현동 255-2번지1359037.388208127.121777
4부천시순천향대학교부속부천병원폐암1등급경기도 부천시 조마루로 170경기도 부천시 중동 1174번지1458437.498369126.762111
5수원시아주대학교병원폐암1등급경기도 수원시 영통구 월드컵로 164경기도 수원시 영통구 원천동 산26-6번지1649937.279343127.046305
6고양시인제대학교일산백병원폐암1등급경기도 고양시 일산서구 주화로 170경기도 고양시 일산서구 대화동 2240번지1038037.674271126.750382
7화성시한림대학교동탄성심병원폐암1등급경기도 화성시 큰재봉길 7경기도 화성시 석우동 40번지1845037.216496127.079942
8군포시효산의료재단 지샘병원폐암1등급경기도 군포시 군포로 591경기도 군포시 당동 730번지 (G샘병원)군포샘병원1583937.358641126.947304
9평택시의료법인백송의료재단 굿모닝병원폐암등급제외경기도 평택시 중앙로 338경기도 평택시 합정동 883번지1787436.990565127.120451
시군명기관명평가내역평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
11안산시고려대학교의과대학부속안산병원폐암1등급경기도 안산시 단원구 적금로 123경기도 안산시 단원구 고잔동 516번지1535537.318859126.824994
12고양시국민건강보험공단일산병원폐암1등급경기도 고양시 일산동구 일산로 100경기도 고양시 일산동구 백석동 1232번지 백석1동 1241외1필지 4층1044437.645475126.792963
13고양시동국대학교일산불교병원폐암1등급경기도 고양시 일산동구 동국로 27경기도 고양시 일산동구 식사동 814번지 동국대학교일산병원1032637.676439126.805563
14성남시분당서울대학교병원폐암1등급경기도 성남시 분당구 구미로173번길 82경기도 성남시 분당구 구미동 300번지 분당서울대학교병원1362037.352017127.124499
15고양시의료법인명지의료재단명지병원폐암1등급경기도 고양시 덕양구 화수로14번길 55경기도 고양시 덕양구 화정동 697-1번지1047537.642475126.831745
16성남시차의과학대학교분당차병원폐암1등급경기도 성남시 분당구 야탑로 59경기도 성남시 분당구 야탑동 351번지1349637.410466127.125835
17안양시한림대학교성심병원폐암1등급경기도 안양시 동안구 관평로170번길 22경기도 안양시 동안구 평촌동 896번지1406837.391654126.961974
18구리시한양대학교구리병원폐암1등급경기도 구리시 경춘로 153경기도 구리시 교문동 249-1번지1192337.601188127.132517
19안산시대아의료재단한도병원폐암등급제외경기도 안산시 단원구 선부광장로 103경기도 안산시 단원구 선부동 1071-1번지1536737.334055126.807621
20안양시효산의료재단 안양샘병원폐암등급제외경기도 안양시 만안구 삼덕로 9경기도 안양시 만안구 안양동 613-6번지 안양샘병원1403037.392894126.92482