Overview

Dataset statistics

Number of variables9
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory78.4 B

Variable types

Categorical3
Text3
Numeric3

Dataset

Description병원평가정보(위암) 현황
Author건강보험심사평가원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=ON3K7AUQNCGWX7W9WA9M21268576&infSeq=1

Alerts

평가내역 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh 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 22:30:14.792525
Analysis finished2023-12-10 22:30:16.371874
Duration1.58 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Memory size444.0 B
고양시
5 
성남시
4 
수원시
3 
안산시
3 
남양주시
3 
Other values (14)
21 

Length

Max length4
Median length3
Mean length3.1282051
Min length3

Unique

Unique8 ?
Unique (%)20.5%

Sample

1st row수원시
2nd row의정부시
3rd row고양시
4th row고양시
5th row부천시

Common Values

ValueCountFrequency (%)
고양시 5
12.8%
성남시 4
 
10.3%
수원시 3
 
7.7%
안산시 3
 
7.7%
남양주시 3
 
7.7%
부천시 3
 
7.7%
평택시 2
 
5.1%
군포시 2
 
5.1%
안양시 2
 
5.1%
오산시 2
 
5.1%
Other values (9) 10
25.6%

Length

2023-12-11T07:30:16.437083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 5
12.8%
성남시 4
 
10.3%
수원시 3
 
7.7%
안산시 3
 
7.7%
남양주시 3
 
7.7%
부천시 3
 
7.7%
안양시 2
 
5.1%
의정부시 2
 
5.1%
오산시 2
 
5.1%
군포시 2
 
5.1%
Other values (9) 10
25.6%

기관명
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-11T07:30:16.662052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length10.25641
Min length3

Characters and Unicode

Total characters400
Distinct characters106
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

Unique39 ?
Unique (%)100.0%

Sample

1st row가톨릭대학교 성빈센트병원
2nd row가톨릭대학교의정부성모병원
3rd row국립암센터
4th row동국대학교일산불교병원
5th row순천향대학교부속부천병원
ValueCountFrequency (%)
의료법인 3
 
5.9%
효산의료재단 2
 
3.9%
가톨릭대학교 1
 
2.0%
양진의료재단 1
 
2.0%
의)영문의료재단 1
 
2.0%
다보스병원 1
 
2.0%
광명성애병원 1
 
2.0%
부천세종병원 1
 
2.0%
성남중앙병원 1
 
2.0%
원광대학교 1
 
2.0%
Other values (38) 38
74.5%
2023-12-11T07:30:17.112900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 42
 
10.5%
병 38
 
9.5%
의 24
 
6.0%
료 20
 
5.0%
대 18
 
4.5%
학 16
 
4.0%
교 15
 
3.8%
단 13
 
3.2%
재 12
 
3.0%
12
 
3.0%
Other values (96) 190
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 386
96.5%
Space Separator 12
 
3.0%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 42
 
10.9%
병 38
 
9.8%
의 24
 
6.2%
료 20
 
5.2%
대 18
 
4.7%
학 16
 
4.1%
교 15
 
3.9%
단 13
 
3.4%
재 12
 
3.1%
산 10
 
2.6%
Other values (93) 178
46.1%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 386
96.5%
Common 14
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 42
 
10.9%
병 38
 
9.8%
의 24
 
6.2%
료 20
 
5.2%
대 18
 
4.7%
학 16
 
4.1%
교 15
 
3.9%
단 13
 
3.4%
재 12
 
3.1%
산 10
 
2.6%
Other values (93) 178
46.1%
Common
ValueCountFrequency (%)
12
85.7%
( 1
 
7.1%
) 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 386
96.5%
ASCII 14
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 42
 
10.9%
병 38
 
9.8%
의 24
 
6.2%
료 20
 
5.2%
대 18
 
4.7%
학 16
 
4.1%
교 15
 
3.9%
단 13
 
3.4%
재 12
 
3.1%
산 10
 
2.6%
Other values (93) 178
46.1%
ASCII
ValueCountFrequency (%)
12
85.7%
( 1
 
7.1%
) 1
 
7.1%

평가내역
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
위암
39 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위암 39
100.0%

Length

2023-12-11T07:30:17.282117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:30:17.418162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위암 39
100.0%

평가등급
Categorical

Distinct4
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size444.0 B
1등급
18 
등급제외
18 
5등급
2 
2등급
 
1

Length

Max length4
Median length3
Mean length3.4615385
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
1등급 18
46.2%
등급제외 18
46.2%
5등급 2
 
5.1%
2등급 1
 
2.6%

Length

2023-12-11T07:30:17.527187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:30:17.648383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1등급 18
46.2%
등급제외 18
46.2%
5등급 2
 
5.1%
2등급 1
 
2.6%

소재지도로명주소
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-11T07:30:17.911382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length18.230769
Min length14

Characters and Unicode

Total characters711
Distinct characters104
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

Unique39 ?
Unique (%)100.0%

Sample

1st row경기도 수원시 팔달구 중부대로 93
2nd row경기도 의정부시 천보로 271
3rd row경기도 고양시 일산동구 일산로 323
4th row경기도 고양시 일산동구 동국로 27
5th row경기도 부천시 조마루로 170
ValueCountFrequency (%)
경기도 39
 
22.2%
고양시 5
 
2.8%
성남시 4
 
2.3%
경춘로 3
 
1.7%
안산시 3
 
1.7%
남양주시 3
 
1.7%
분당구 3
 
1.7%
일산동구 3
 
1.7%
수원시 3
 
1.7%
부천시 3
 
1.7%
Other values (96) 107
60.8%
2023-12-11T07:30:18.306915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
19.3%
경 42
 
5.9%
시 40
 
5.6%
도 40
 
5.6%
기 39
 
5.5%
로 38
 
5.3%
1 27
 
3.8%
구 20
 
2.8%
3 18
 
2.5%
2 16
 
2.3%
Other values (94) 294
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 449
63.2%
Space Separator 137
 
19.3%
Decimal Number 124
 
17.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 42
 
9.4%
시 40
 
8.9%
도 40
 
8.9%
기 39
 
8.7%
로 38
 
8.5%
구 20
 
4.5%
산 14
 
3.1%
양 11
 
2.4%
길 9
 
2.0%
번 8
 
1.8%
Other values (82) 188
41.9%
Decimal Number
ValueCountFrequency (%)
1 27
21.8%
3 18
14.5%
2 16
12.9%
0 12
9.7%
7 11
8.9%
8 9
 
7.3%
5 9
 
7.3%
4 8
 
6.5%
9 7
 
5.6%
6 7
 
5.6%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 449
63.2%
Common 262
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 42
 
9.4%
시 40
 
8.9%
도 40
 
8.9%
기 39
 
8.7%
로 38
 
8.5%
구 20
 
4.5%
산 14
 
3.1%
양 11
 
2.4%
길 9
 
2.0%
번 8
 
1.8%
Other values (82) 188
41.9%
Common
ValueCountFrequency (%)
137
52.3%
1 27
 
10.3%
3 18
 
6.9%
2 16
 
6.1%
0 12
 
4.6%
7 11
 
4.2%
8 9
 
3.4%
5 9
 
3.4%
4 8
 
3.1%
9 7
 
2.7%
Other values (2) 8
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 449
63.2%
ASCII 262
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
137
52.3%
1 27
 
10.3%
3 18
 
6.9%
2 16
 
6.1%
0 12
 
4.6%
7 11
 
4.2%
8 9
 
3.4%
5 9
 
3.4%
4 8
 
3.1%
9 7
 
2.7%
Other values (2) 8
 
3.1%
Hangul
ValueCountFrequency (%)
경 42
 
9.4%
시 40
 
8.9%
도 40
 
8.9%
기 39
 
8.7%
로 38
 
8.5%
구 20
 
4.5%
산 14
 
3.1%
양 11
 
2.4%
길 9
 
2.0%
번 8
 
1.8%
Other values (82) 188
41.9%

소재지지번주소
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-11T07:30:18.505176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length28
Mean length23.435897
Min length16

Characters and Unicode

Total characters914
Distinct characters117
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

Unique39 ?
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 고양시 일산동구 식사동 814번지 동국대학교일산병원
5th row경기도 부천시 중동 1174번지
ValueCountFrequency (%)
경기도 39
 
20.4%
고양시 5
 
2.6%
성남시 4
 
2.1%
부천시 3
 
1.6%
수원시 3
 
1.6%
안산시 3
 
1.6%
일산동구 3
 
1.6%
분당구 3
 
1.6%
남양주시 3
 
1.6%
안양시 2
 
1.0%
Other values (117) 123
64.4%
2023-12-11T07:30:18.840445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
152
 
16.6%
동 43
 
4.7%
경 41
 
4.5%
도 41
 
4.5%
시 41
 
4.5%
지 41
 
4.5%
기 40
 
4.4%
번 39
 
4.3%
1 28
 
3.1%
원 22
 
2.4%
Other values (107) 426
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 592
64.8%
Space Separator 152
 
16.6%
Decimal Number 147
 
16.1%
Dash Punctuation 20
 
2.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 43
 
7.3%
경 41
 
6.9%
도 41
 
6.9%
시 41
 
6.9%
지 41
 
6.9%
기 40
 
6.8%
번 39
 
6.6%
원 22
 
3.7%
구 20
 
3.4%
산 14
 
2.4%
Other values (92) 250
42.2%
Decimal Number
ValueCountFrequency (%)
1 28
19.0%
3 19
12.9%
2 16
10.9%
6 15
10.2%
4 15
10.2%
9 14
9.5%
5 11
 
7.5%
8 10
 
6.8%
0 10
 
6.8%
7 9
 
6.1%
Space Separator
ValueCountFrequency (%)
152
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 592
64.8%
Common 321
35.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 43
 
7.3%
경 41
 
6.9%
도 41
 
6.9%
시 41
 
6.9%
지 41
 
6.9%
기 40
 
6.8%
번 39
 
6.6%
원 22
 
3.7%
구 20
 
3.4%
산 14
 
2.4%
Other values (92) 250
42.2%
Common
ValueCountFrequency (%)
152
47.4%
1 28
 
8.7%
- 20
 
6.2%
3 19
 
5.9%
2 16
 
5.0%
6 15
 
4.7%
4 15
 
4.7%
9 14
 
4.4%
5 11
 
3.4%
8 10
 
3.1%
Other values (4) 21
 
6.5%
Latin
ValueCountFrequency (%)
G 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 592
64.8%
ASCII 322
35.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
152
47.2%
1 28
 
8.7%
- 20
 
6.2%
3 19
 
5.9%
2 16
 
5.0%
6 15
 
4.7%
4 15
 
4.7%
9 14
 
4.3%
5 11
 
3.4%
8 10
 
3.1%
Other values (5) 22
 
6.8%
Hangul
ValueCountFrequency (%)
동 43
 
7.3%
경 41
 
6.9%
도 41
 
6.9%
시 41
 
6.9%
지 41
 
6.9%
기 40
 
6.8%
번 39
 
6.6%
원 22
 
3.7%
구 20
 
3.4%
산 14
 
2.4%
Other values (92) 250
42.2%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14038.128
Minimum10099
Maximum18450
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T07:30:19.002640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10099
5-th percentile10374.6
Q111968
median14068
Q315852
95-th percentile18136.8
Maximum18450
Range8351
Interquartile range (IQR)3884

Descriptive statistics

Standard deviation2528.5208
Coefficient of variation (CV)0.18011809
Kurtosis-1.0600821
Mean14038.128
Median Absolute Deviation (MAD)2055
Skewness0.060584667
Sum547487
Variance6393417.5
MonotonicityNot monotonic
2023-12-11T07:30:19.167912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
16247 1
 
2.6%
11765 1
 
2.6%
17063 1
 
2.6%
14241 1
 
2.6%
14754 1
 
2.6%
13161 1
 
2.6%
15865 1
 
2.6%
12179 1
 
2.6%
17825 1
 
2.6%
18136 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
10099 1
2.6%
10326 1
2.6%
10380 1
2.6%
10408 1
2.6%
10444 1
2.6%
10475 1
2.6%
10922 1
2.6%
11686 1
2.6%
11765 1
2.6%
11923 1
2.6%
ValueCountFrequency (%)
18450 1
2.6%
18144 1
2.6%
18136 1
2.6%
17874 1
2.6%
17825 1
2.6%
17063 1
2.6%
16499 1
2.6%
16494 1
2.6%
16247 1
2.6%
15865 1
2.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.439625
Minimum36.990565
Maximum37.758523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T07:30:19.314617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.990565
5-th percentile37.127994
Q137.312981
median37.410466
Q337.638013
95-th percentile37.750286
Maximum37.758523
Range0.76795781
Interquartile range (IQR)0.32503295

Descriptive statistics

Standard deviation0.20409374
Coefficient of variation (CV)0.0054512764
Kurtosis-0.58724101
Mean37.439625
Median Absolute Deviation (MAD)0.13255592
Skewness-0.20744982
Sum1460.1454
Variance0.041654255
MonotonicityNot monotonic
2023-12-11T07:30:19.707639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
37.2779105554 1
 
2.6%
37.7585227082 1
 
2.6%
37.2315458776 1
 
2.6%
37.4736631727 1
 
2.6%
37.4810423491 1
 
2.6%
37.4528318807 1
 
2.6%
37.3594142404 1
 
2.6%
37.6519114852 1
 
2.6%
37.0083742374 1
 
2.6%
37.154202255 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
36.9905649024 1
2.6%
37.0083742374 1
2.6%
37.1412846971 1
2.6%
37.154202255 1
2.6%
37.2164957291 1
2.6%
37.2315458776 1
2.6%
37.2779105554 1
2.6%
37.2781610499 1
2.6%
37.2793432963 1
2.6%
37.3071016672 1
2.6%
ValueCountFrequency (%)
37.7585227082 1
2.6%
37.7548777512 1
2.6%
37.7497753415 1
2.6%
37.7154360459 1
2.6%
37.6764385211 1
2.6%
37.6742710122 1
2.6%
37.6632367324 1
2.6%
37.6519114852 1
2.6%
37.6454752678 1
2.6%
37.6424745722 1
2.6%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.97784
Minimum126.71055
Maximum127.30438
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T07:30:19.831771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.71055
5-th percentile126.74904
Q1126.80659
median127.02798
Q3127.12111
95-th percentile127.21627
Maximum127.30438
Range0.5938258
Interquartile range (IQR)0.31452205

Descriptive statistics

Standard deviation0.16884372
Coefficient of variation (CV)0.0013297101
Kurtosis-1.2799058
Mean126.97784
Median Absolute Deviation (MAD)0.15197614
Skewness0.047993177
Sum4952.1359
Variance0.028508203
MonotonicityNot monotonic
2023-12-11T07:30:19.960411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
127.0279830169 1
 
2.6%
127.0779287098 1
 
2.6%
127.2114163575 1
 
2.6%
126.8713299326 1
 
2.6%
126.7911902926 1
 
2.6%
127.1620415598 1
 
2.6%
126.933600771 1
 
2.6%
127.3043775936 1
 
2.6%
127.0743680813 1
 
2.6%
127.0681914802 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
126.7105517913 1
2.6%
126.7370103825 1
2.6%
126.7503817665 1
2.6%
126.7621105079 1
2.6%
126.7796405014 1
2.6%
126.783395561 1
2.6%
126.7911902926 1
2.6%
126.7929631952 1
2.6%
126.7933597441 1
2.6%
126.805563051 1
2.6%
ValueCountFrequency (%)
127.3043775936 1
2.6%
127.2599526938 1
2.6%
127.2114163575 1
2.6%
127.2052107223 1
2.6%
127.1799591601 1
2.6%
127.1620415598 1
2.6%
127.1325173047 1
2.6%
127.1258348309 1
2.6%
127.1244991912 1
2.6%
127.1217770322 1
2.6%

Interactions

2023-12-11T07:30:15.806547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:30:15.191176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:30:15.475031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:30:15.895414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:30:15.275465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:30:15.570502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:30:15.993552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:30:15.365064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:30:15.683417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:30:20.079134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명기관명평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0000.0001.0001.0000.9900.9690.876
기관명1.0001.0001.0001.0001.0001.0001.0001.000
평가등급0.0001.0001.0001.0001.0000.0890.0000.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호0.9901.0000.0891.0001.0001.0000.9420.894
WGS84위도0.9691.0000.0001.0001.0000.9421.0000.525
WGS84경도0.8761.0000.0001.0001.0000.8940.5251.000
2023-12-11T07:30:20.200748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가등급시군명
평가등급1.0000.000
시군명0.0001.000
2023-12-11T07:30:20.279916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명평가등급
소재지우편번호1.000-0.9140.2110.7850.096
WGS84위도-0.9141.000-0.2150.6910.000
WGS84경도0.211-0.2151.0000.4670.000
시군명0.7850.6910.4671.0000.000
평가등급0.0960.0000.0000.0001.000

Missing values

2023-12-11T07:30:16.175082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:30:16.308034image/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 성빈센트병원위암1등급경기도 수원시 팔달구 중부대로 93경기도 수원시 팔달구 지동 93-6번지1624737.277911127.027983
1의정부시가톨릭대학교의정부성모병원위암1등급경기도 의정부시 천보로 271경기도 의정부시 금오동 65-1번지 의정부성모병원1176537.758523127.077929
2고양시국립암센터위암1등급경기도 고양시 일산동구 일산로 323경기도 고양시 일산동구 마두동 809번지1040837.663237126.783396
3고양시동국대학교일산불교병원위암1등급경기도 고양시 일산동구 동국로 27경기도 고양시 일산동구 식사동 814번지 동국대학교일산병원1032637.676439126.805563
4부천시순천향대학교부속부천병원위암1등급경기도 부천시 조마루로 170경기도 부천시 중동 1174번지1458437.498369126.762111
5고양시의료법인명지의료재단명지병원위암1등급경기도 고양시 덕양구 화수로14번길 55경기도 고양시 덕양구 화정동 697-1번지1047537.642475126.831745
6고양시인제대학교일산백병원위암1등급경기도 고양시 일산서구 주화로 170경기도 고양시 일산서구 대화동 2240번지1038037.674271126.750382
7화성시한림대학교동탄성심병원위암1등급경기도 화성시 큰재봉길 7경기도 화성시 석우동 40번지1845037.216496127.079942
8구리시한양대학교구리병원위암1등급경기도 구리시 경춘로 153경기도 구리시 교문동 249-1번지1192337.601188127.132517
9안산시대아의료재단한도병원위암2등급경기도 안산시 단원구 선부광장로 103경기도 안산시 단원구 선부동 1071-1번지1536737.334055126.807621
시군명기관명평가내역평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
29오산시조은오산병원위암등급제외경기도 오산시 오산로 307경기도 오산시 오산동 399번지1813637.154202127.068191
30의정부시추병원위암등급제외경기도 의정부시 평화로 650경기도 의정부시 의정부동 234-2번지1168637.749775127.045207
31군포시효산의료재단 지샘병원위암등급제외경기도 군포시 군포로 591경기도 군포시 당동 730번지 (G샘병원)군포샘병원1583937.358641126.947304
32부천시가톨릭대학교부천성모병원위암1등급경기도 부천시 소사로 327경기도 부천시 소사동 2번지 가톨릭대학교부천성모병원1464737.487275126.79336
33안산시고려대학교의과대학부속안산병원위암1등급경기도 안산시 단원구 적금로 123경기도 안산시 단원구 고잔동 516번지1535537.318859126.824994
34고양시국민건강보험공단일산병원위암1등급경기도 고양시 일산동구 일산로 100경기도 고양시 일산동구 백석동 1232번지 백석1동 1241외1필지 4층1044437.645475126.792963
35성남시분당서울대학교병원위암1등급경기도 성남시 분당구 구미로173번길 82경기도 성남시 분당구 구미동 300번지 분당서울대학교병원1362037.352017127.124499
36수원시아주대학교병원위암1등급경기도 수원시 영통구 월드컵로 164경기도 수원시 영통구 원천동 산26-6번지1649937.279343127.046305
37김포시의료법인우리의료재단김포우리병원위암1등급경기도 김포시 감암로 11경기도 김포시 걸포동 389-15번지 김포우리병원1009937.633001126.710552
38성남시차의과학대학교분당차병원위암1등급경기도 성남시 분당구 야탑로 59경기도 성남시 분당구 야탑동 351번지1349637.410466127.125835