Overview

Dataset statistics

Number of variables9
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory79.1 B

Variable types

Text4
Categorical2
Numeric3

Dataset

Description병원평가정보(유방암) 현황
Author건강보험심사평가원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=J3SLE6B3AD9HKATJDXND21279985&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 21:57:50.710501
Analysis finished2023-12-10 21:57:51.898634
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct16
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:57:51.980625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0625
Min length3

Characters and Unicode

Total characters98
Distinct characters27
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

Unique10 ?
Unique (%)31.2%

Sample

1st row수원시
2nd row부천시
3rd row안산시
4th row고양시
5th row고양시
ValueCountFrequency (%)
고양시 6
18.8%
수원시 5
15.6%
부천시 3
9.4%
안산시 3
9.4%
성남시 3
9.4%
군포시 2
 
6.2%
평택시 1
 
3.1%
화성시 1
 
3.1%
구리시 1
 
3.1%
광명시 1
 
3.1%
Other values (6) 6
18.8%
2023-12-11T06:57:52.216454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 32
32.7%
양 8
 
8.2%
고 6
 
6.1%
수 5
 
5.1%
원 5
 
5.1%
산 4
 
4.1%
남 4
 
4.1%
성 4
 
4.1%
안 4
 
4.1%
부 4
 
4.1%
Other values (17) 22
22.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 98
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 32
32.7%
양 8
 
8.2%
고 6
 
6.1%
수 5
 
5.1%
원 5
 
5.1%
산 4
 
4.1%
남 4
 
4.1%
성 4
 
4.1%
안 4
 
4.1%
부 4
 
4.1%
Other values (17) 22
22.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 98
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 32
32.7%
양 8
 
8.2%
고 6
 
6.1%
수 5
 
5.1%
원 5
 
5.1%
산 4
 
4.1%
남 4
 
4.1%
성 4
 
4.1%
안 4
 
4.1%
부 4
 
4.1%
Other values (17) 22
22.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 98
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 32
32.7%
양 8
 
8.2%
고 6
 
6.1%
수 5
 
5.1%
원 5
 
5.1%
산 4
 
4.1%
남 4
 
4.1%
성 4
 
4.1%
안 4
 
4.1%
부 4
 
4.1%
Other values (17) 22
22.4%

기관명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:57:52.404524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length10.65625
Min length4

Characters and Unicode

Total characters341
Distinct characters99
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

Unique32 ?
Unique (%)100.0%

Sample

1st row가톨릭대학교 성빈센트병원
2nd row가톨릭대학교부천성모병원
3rd row고려대학교의과대학부속안산병원
4th row국민건강보험공단일산병원
5th row동국대학교일산불교병원
ValueCountFrequency (%)
가톨릭대학교 1
 
2.6%
의)영문의료재단 1
 
2.6%
분당제생병원 1
 
2.6%
분당서울대학교병원 1
 
2.6%
아주대학교병원 1
 
2.6%
의료법인명지의료재단명지병원 1
 
2.6%
차의과학대학교분당차병원 1
 
2.6%
한림대학교성심병원 1
 
2.6%
박희붕외과의원 1
 
2.6%
다보스병원 1
 
2.6%
Other values (29) 29
74.4%
2023-12-11T06:57:52.701521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 33
 
9.7%
병 28
 
8.2%
의 21
 
6.2%
대 18
 
5.3%
학 16
 
4.7%
교 15
 
4.4%
료 14
 
4.1%
단 10
 
2.9%
재 9
 
2.6%
산 8
 
2.3%
Other values (89) 169
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 332
97.4%
Space Separator 7
 
2.1%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 33
 
9.9%
병 28
 
8.4%
의 21
 
6.3%
대 18
 
5.4%
학 16
 
4.8%
교 15
 
4.5%
료 14
 
4.2%
단 10
 
3.0%
재 9
 
2.7%
산 8
 
2.4%
Other values (86) 160
48.2%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 332
97.4%
Common 9
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 33
 
9.9%
병 28
 
8.4%
의 21
 
6.3%
대 18
 
5.4%
학 16
 
4.8%
교 15
 
4.5%
료 14
 
4.2%
단 10
 
3.0%
재 9
 
2.7%
산 8
 
2.4%
Other values (86) 160
48.2%
Common
ValueCountFrequency (%)
7
77.8%
( 1
 
11.1%
) 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 332
97.4%
ASCII 9
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 33
 
9.9%
병 28
 
8.4%
의 21
 
6.3%
대 18
 
5.4%
학 16
 
4.8%
교 15
 
4.5%
료 14
 
4.2%
단 10
 
3.0%
재 9
 
2.7%
산 8
 
2.4%
Other values (86) 160
48.2%
ASCII
ValueCountFrequency (%)
7
77.8%
( 1
 
11.1%
) 1
 
11.1%

평가내역
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
유방암
32 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유방암 32
100.0%

Length

2023-12-11T06:57:52.806964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:57:52.883650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유방암 32
100.0%

평가등급
Categorical

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
1등급
18 
등급제외
13 
3등급
 
1

Length

Max length4
Median length3
Mean length3.40625
Min length3

Unique

Unique1 ?
Unique (%)3.1%

Sample

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

Common Values

ValueCountFrequency (%)
1등급 18
56.2%
등급제외 13
40.6%
3등급 1
 
3.1%

Length

2023-12-11T06:57:52.981052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:57:53.062008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1등급 18
56.2%
등급제외 13
40.6%
3등급 1
 
3.1%

소재지도로명주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:57:53.240287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length18.78125
Min length14

Characters and Unicode

Total characters601
Distinct characters100
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

Unique32 ?
Unique (%)100.0%

Sample

1st row경기도 수원시 팔달구 중부대로 93
2nd row경기도 부천시 소사로 327
3rd row경기도 안산시 단원구 적금로 123
4th row경기도 고양시 일산동구 일산로 100
5th row경기도 고양시 일산동구 동국로 27
ValueCountFrequency (%)
경기도 32
 
21.6%
고양시 6
 
4.1%
수원시 5
 
3.4%
안산시 3
 
2.0%
성남시 3
 
2.0%
일산동구 3
 
2.0%
분당구 3
 
2.0%
부천시 3
 
2.0%
중부대로 2
 
1.4%
군포시 2
 
1.4%
Other values (77) 86
58.1%
2023-12-11T06:57:53.567394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
19.3%
경 34
 
5.7%
도 32
 
5.3%
기 32
 
5.3%
시 32
 
5.3%
로 31
 
5.2%
1 26
 
4.3%
구 21
 
3.5%
2 15
 
2.5%
3 14
 
2.3%
Other values (90) 248
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 382
63.6%
Space Separator 116
 
19.3%
Decimal Number 103
 
17.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 34
 
8.9%
도 32
 
8.4%
기 32
 
8.4%
시 32
 
8.4%
로 31
 
8.1%
구 21
 
5.5%
산 12
 
3.1%
길 9
 
2.4%
양 9
 
2.4%
번 8
 
2.1%
Other values (79) 162
42.4%
Decimal Number
ValueCountFrequency (%)
1 26
25.2%
2 15
14.6%
3 14
13.6%
0 9
 
8.7%
7 9
 
8.7%
5 8
 
7.8%
8 7
 
6.8%
6 6
 
5.8%
4 5
 
4.9%
9 4
 
3.9%
Space Separator
ValueCountFrequency (%)
116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 382
63.6%
Common 219
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 34
 
8.9%
도 32
 
8.4%
기 32
 
8.4%
시 32
 
8.4%
로 31
 
8.1%
구 21
 
5.5%
산 12
 
3.1%
길 9
 
2.4%
양 9
 
2.4%
번 8
 
2.1%
Other values (79) 162
42.4%
Common
ValueCountFrequency (%)
116
53.0%
1 26
 
11.9%
2 15
 
6.8%
3 14
 
6.4%
0 9
 
4.1%
7 9
 
4.1%
5 8
 
3.7%
8 7
 
3.2%
6 6
 
2.7%
4 5
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 382
63.6%
ASCII 219
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116
53.0%
1 26
 
11.9%
2 15
 
6.8%
3 14
 
6.4%
0 9
 
4.1%
7 9
 
4.1%
5 8
 
3.7%
8 7
 
3.2%
6 6
 
2.7%
4 5
 
2.3%
Hangul
ValueCountFrequency (%)
경 34
 
8.9%
도 32
 
8.4%
기 32
 
8.4%
시 32
 
8.4%
로 31
 
8.1%
구 21
 
5.5%
산 12
 
3.1%
길 9
 
2.4%
양 9
 
2.4%
번 8
 
2.1%
Other values (79) 162
42.4%

소재지지번주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:57:53.792080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length31
Mean length24.9375
Min length16

Characters and Unicode

Total characters798
Distinct characters119
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

Unique32 ?
Unique (%)100.0%

Sample

1st row경기도 수원시 팔달구 지동 93-6번지
2nd row경기도 부천시 소사동 2번지 가톨릭대학교부천성모병원
3rd row경기도 안산시 단원구 고잔동 516번지
4th row경기도 고양시 일산동구 백석동 1232번지 백석1동 1241외1필지 4층
5th row경기도 고양시 일산동구 식사동 814번지 동국대학교일산병원
ValueCountFrequency (%)
경기도 32
 
19.6%
고양시 6
 
3.7%
수원시 5
 
3.1%
성남시 3
 
1.8%
분당구 3
 
1.8%
부천시 3
 
1.8%
일산동구 3
 
1.8%
안산시 3
 
1.8%
군포시 2
 
1.2%
일산서구 2
 
1.2%
Other values (98) 101
62.0%
2023-12-11T06:57:54.139629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
131
 
16.4%
1 39
 
4.9%
동 37
 
4.6%
지 34
 
4.3%
경 32
 
4.0%
도 32
 
4.0%
번 32
 
4.0%
기 32
 
4.0%
시 32
 
4.0%
구 21
 
2.6%
Other values (109) 376
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 499
62.5%
Decimal Number 144
 
18.0%
Space Separator 131
 
16.4%
Dash Punctuation 17
 
2.1%
Other Punctuation 4
 
0.5%
Uppercase Letter 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 37
 
7.4%
지 34
 
6.8%
경 32
 
6.4%
도 32
 
6.4%
번 32
 
6.4%
기 32
 
6.4%
시 32
 
6.4%
구 21
 
4.2%
원 19
 
3.8%
산 13
 
2.6%
Other values (93) 215
43.1%
Decimal Number
ValueCountFrequency (%)
1 39
27.1%
0 16
11.1%
2 15
 
10.4%
3 13
 
9.0%
6 12
 
8.3%
4 12
 
8.3%
7 10
 
6.9%
5 9
 
6.2%
9 9
 
6.2%
8 9
 
6.2%
Space Separator
ValueCountFrequency (%)
131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 499
62.5%
Common 298
37.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 37
 
7.4%
지 34
 
6.8%
경 32
 
6.4%
도 32
 
6.4%
번 32
 
6.4%
기 32
 
6.4%
시 32
 
6.4%
구 21
 
4.2%
원 19
 
3.8%
산 13
 
2.6%
Other values (93) 215
43.1%
Common
ValueCountFrequency (%)
131
44.0%
1 39
 
13.1%
- 17
 
5.7%
0 16
 
5.4%
2 15
 
5.0%
3 13
 
4.4%
6 12
 
4.0%
4 12
 
4.0%
7 10
 
3.4%
5 9
 
3.0%
Other values (5) 24
 
8.1%
Latin
ValueCountFrequency (%)
G 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 499
62.5%
ASCII 299
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
131
43.8%
1 39
 
13.0%
- 17
 
5.7%
0 16
 
5.4%
2 15
 
5.0%
3 13
 
4.3%
6 12
 
4.0%
4 12
 
4.0%
7 10
 
3.3%
5 9
 
3.0%
Other values (6) 25
 
8.4%
Hangul
ValueCountFrequency (%)
동 37
 
7.4%
지 34
 
6.8%
경 32
 
6.4%
도 32
 
6.4%
번 32
 
6.4%
기 32
 
6.4%
시 32
 
6.4%
구 21
 
4.2%
원 19
 
3.8%
산 13
 
2.6%
Other values (93) 215
43.1%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14158.156
Minimum10099
Maximum18450
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T06:57:54.272299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10099
5-th percentile10355.7
Q111883.5
median14615.5
Q316308.75
95-th percentile17995.5
Maximum18450
Range8351
Interquartile range (IQR)4425.25

Descriptive statistics

Standard deviation2616.3966
Coefficient of variation (CV)0.18479783
Kurtosis-1.1668424
Mean14158.156
Median Absolute Deviation (MAD)1919.5
Skewness-0.23621141
Sum453061
Variance6845530.9
MonotonicityNot monotonic
2023-12-11T06:57:54.448828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
16247 1
 
3.1%
10408 1
 
3.1%
15839 1
 
3.1%
12013 1
 
3.1%
10099 1
 
3.1%
16494 1
 
3.1%
18144 1
 
3.1%
10386 1
 
3.1%
17063 1
 
3.1%
16571 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
10099 1
3.1%
10326 1
3.1%
10380 1
3.1%
10386 1
3.1%
10408 1
3.1%
10444 1
3.1%
10475 1
3.1%
11765 1
3.1%
11923 1
3.1%
12013 1
3.1%
ValueCountFrequency (%)
18450 1
3.1%
18144 1
3.1%
17874 1
3.1%
17063 1
3.1%
16580 1
3.1%
16571 1
3.1%
16499 1
3.1%
16494 1
3.1%
16247 1
3.1%
15865 1
3.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.43041
Minimum36.990565
Maximum37.758523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T06:57:54.571003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.990565
5-th percentile37.182651
Q137.279048
median37.389931
Q337.635369
95-th percentile37.693987
Maximum37.758523
Range0.76795781
Interquartile range (IQR)0.35632167

Descriptive statistics

Standard deviation0.19191425
Coefficient of variation (CV)0.0051272282
Kurtosis-0.70626505
Mean37.43041
Median Absolute Deviation (MAD)0.12015159
Skewness-0.026272489
Sum1197.7731
Variance0.036831081
MonotonicityNot monotonic
2023-12-11T06:57:54.696643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
37.2779105554 1
 
3.1%
37.6632367324 1
 
3.1%
37.3586407829 1
 
3.1%
37.7154360459 1
 
3.1%
37.6330010089 1
 
3.1%
37.2781610499 1
 
3.1%
37.1412846971 1
 
3.1%
37.669807677 1
 
3.1%
37.2315458776 1
 
3.1%
37.261647536 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
36.9905649024 1
3.1%
37.1412846971 1
3.1%
37.2164957291 1
3.1%
37.2315458776 1
3.1%
37.2555463591 1
3.1%
37.261647536 1
3.1%
37.2779105554 1
3.1%
37.2781610499 1
3.1%
37.2793432963 1
3.1%
37.3071016672 1
3.1%
ValueCountFrequency (%)
37.7585227082 1
3.1%
37.7154360459 1
3.1%
37.6764385211 1
3.1%
37.6742710122 1
3.1%
37.669807677 1
3.1%
37.6632367324 1
3.1%
37.6454752678 1
3.1%
37.6424745722 1
3.1%
37.6330010089 1
3.1%
37.6011883667 1
3.1%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.94965
Minimum126.71055
Maximum127.21142
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T06:57:54.819637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.71055
5-th percentile126.75683
Q1126.80251
median126.95464
Q3127.07843
95-th percentile127.15387
Maximum127.21142
Range0.50086457
Interquartile range (IQR)0.27591972

Descriptive statistics

Standard deviation0.15183536
Coefficient of variation (CV)0.0011960282
Kurtosis-1.5004982
Mean126.94965
Median Absolute Deviation (MAD)0.14804672
Skewness0.04397829
Sum4062.3889
Variance0.023053977
MonotonicityNot monotonic
2023-12-11T06:57:55.189410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
127.0279830169 1
 
3.1%
126.783395561 1
 
3.1%
126.9473038902 1
 
3.1%
127.1799591601 1
 
3.1%
126.7105517913 1
 
3.1%
127.0343321487 1
 
3.1%
127.0755950189 1
 
3.1%
126.762967568 1
 
3.1%
127.2114163575 1
 
3.1%
127.0297761731 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
126.7105517913 1
3.1%
126.7503817665 1
3.1%
126.7621105079 1
3.1%
126.762967568 1
3.1%
126.783395561 1
3.1%
126.7911902926 1
3.1%
126.7929631952 1
3.1%
126.7933597441 1
3.1%
126.805563051 1
3.1%
126.8076211068 1
3.1%
ValueCountFrequency (%)
127.2114163575 1
3.1%
127.1799591601 1
3.1%
127.1325173047 1
3.1%
127.1258348309 1
3.1%
127.1244991912 1
3.1%
127.1217770322 1
3.1%
127.1204512355 1
3.1%
127.0799416615 1
3.1%
127.0779287098 1
3.1%
127.0755950189 1
3.1%

Interactions

2023-12-11T06:57:51.505570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:51.071382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:51.278926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:51.569003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:51.134159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:51.346411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:51.643147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:51.209998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:51.431520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:57:55.317734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명기관명평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0000.0001.0001.0001.0000.9930.972
기관명1.0001.0001.0001.0001.0001.0001.0001.000
평가등급0.0001.0001.0001.0001.0000.0000.0000.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0001.0000.0001.0001.0001.0000.9220.819
WGS84위도0.9931.0000.0001.0001.0000.9221.0000.861
WGS84경도0.9721.0000.0001.0001.0000.8190.8611.000
2023-12-11T06:57:55.450686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도평가등급
소재지우편번호1.000-0.9230.4380.000
WGS84위도-0.9231.000-0.4330.000
WGS84경도0.438-0.4331.0000.000
평가등급0.0000.0000.0001.000

Missing values

2023-12-11T06:57:51.743395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:57:51.857339image/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 성빈센트병원유방암1등급경기도 수원시 팔달구 중부대로 93경기도 수원시 팔달구 지동 93-6번지1624737.277911127.027983
1부천시가톨릭대학교부천성모병원유방암1등급경기도 부천시 소사로 327경기도 부천시 소사동 2번지 가톨릭대학교부천성모병원1464737.487275126.79336
2안산시고려대학교의과대학부속안산병원유방암1등급경기도 안산시 단원구 적금로 123경기도 안산시 단원구 고잔동 516번지1535537.318859126.824994
3고양시국민건강보험공단일산병원유방암1등급경기도 고양시 일산동구 일산로 100경기도 고양시 일산동구 백석동 1232번지 백석1동 1241외1필지 4층1044437.645475126.792963
4고양시동국대학교일산불교병원유방암1등급경기도 고양시 일산동구 동국로 27경기도 고양시 일산동구 식사동 814번지 동국대학교일산병원1032637.676439126.805563
5부천시순천향대학교부속부천병원유방암1등급경기도 부천시 조마루로 170경기도 부천시 중동 1174번지1458437.498369126.762111
6평택시의료법인백송의료재단 굿모닝병원유방암1등급경기도 평택시 중앙로 338경기도 평택시 합정동 883번지1787436.990565127.120451
7고양시인제대학교일산백병원유방암1등급경기도 고양시 일산서구 주화로 170경기도 고양시 일산서구 대화동 2240번지1038037.674271126.750382
8화성시한림대학교동탄성심병원유방암1등급경기도 화성시 큰재봉길 7경기도 화성시 석우동 40번지1845037.216496127.079942
9구리시한양대학교구리병원유방암1등급경기도 구리시 경춘로 153경기도 구리시 교문동 249-1번지1192337.601188127.132517
시군명기관명평가내역평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
22성남시차의과학대학교분당차병원유방암1등급경기도 성남시 분당구 야탑로 59경기도 성남시 분당구 야탑동 351번지1349637.410466127.125835
23안양시한림대학교성심병원유방암1등급경기도 안양시 동안구 관평로170번길 22경기도 안양시 동안구 평촌동 896번지1406837.391654126.961974
24수원시박희붕외과의원유방암3등급경기도 수원시 권선구 효원로256번길 7경기도 수원시 권선구 권선동 1013번지 105-108,111,113,114,203-206호1657137.261648127.029776
25용인시(의)영문의료재단 다보스병원유방암등급제외경기도 용인시 처인구 백옥대로1082번길 18경기도 용인시 처인구 김량장동 18-4번지 다보스종합병원1706337.231546127.211416
26고양시박세호여성외과의원유방암등급제외경기도 고양시 일산서구 중앙로 1416경기도 고양시 일산서구 주엽동 71-2번지 한사랑빌딩 401호1038637.669808126.762968
27오산시오산한국병원유방암등급제외경기도 오산시 밀머리로1번길 16경기도 오산시 원동 560-70번지1814437.141285127.075595
28수원시의료법인 녹산의료재단동수원병원유방암등급제외경기도 수원시 팔달구 중부대로 165경기도 수원시 팔달구 우만동 157-7번지1649437.278161127.034332
29김포시의료법인우리의료재단김포우리병원유방암등급제외경기도 김포시 감암로 11경기도 김포시 걸포동 389-15번지 김포우리병원1009937.633001126.710552
30남양주시현대병원유방암등급제외경기도 남양주시 진접읍 봉현로 21경기도 남양주시 진접읍 장현리 663번지1201337.715436127.179959
31군포시효산의료재단 지샘병원유방암등급제외경기도 군포시 군포로 591경기도 군포시 당동 730번지 (G샘병원)군포샘병원1583937.358641126.947304