Overview

Dataset statistics

Number of variables9
Number of observations113
Missing cells5
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory76.2 B

Variable types

Categorical3
Text3
Numeric3

Dataset

Description병원평가정보(질병-폐렴) 현황
Author건강보험심사평가원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=7761H8C6B4VX2NF68AGC21433947&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
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
소재지도로명주소 has 3 (2.7%) missing valuesMissing
기관명 has unique valuesUnique
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:22:42.338042
Analysis finished2023-12-10 21:22:43.882571
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
수원시
9 
남양주시
8 
평택시
8 
안산시
8 
의정부시
 
7
Other values (24)
73 

Length

Max length4
Median length3
Mean length3.1415929
Min length3

Unique

Unique5 ?
Unique (%)4.4%

Sample

1st row의정부시
2nd row안성시
3rd row의정부시
4th row안산시
5th row고양시

Common Values

ValueCountFrequency (%)
수원시 9
 
8.0%
남양주시 8
 
7.1%
평택시 8
 
7.1%
안산시 8
 
7.1%
의정부시 7
 
6.2%
고양시 7
 
6.2%
성남시 6
 
5.3%
부천시 6
 
5.3%
용인시 5
 
4.4%
화성시 5
 
4.4%
Other values (19) 44
38.9%

Length

2023-12-11T06:22:43.949130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 9
 
8.0%
평택시 8
 
7.1%
안산시 8
 
7.1%
남양주시 8
 
7.1%
의정부시 7
 
6.2%
고양시 7
 
6.2%
성남시 6
 
5.3%
부천시 6
 
5.3%
용인시 5
 
4.4%
화성시 5
 
4.4%
Other values (19) 44
38.9%

기관명
Text

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T06:22:44.182835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length9.6637168
Min length3

Characters and Unicode

Total characters1092
Distinct characters179
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

Unique113 ?
Unique (%)100.0%

Sample

1st row가톨릭대학교의정부성모병원
2nd row경기도의료원 안성병원
3rd row경기도의료원의정부병원
4th row고려대학교의과대학부속안산병원
5th row국립암센터
ValueCountFrequency (%)
의료법인 11
 
7.1%
경기도의료원 3
 
1.9%
바른병원 2
 
1.3%
효산의료재단 2
 
1.3%
부천중앙병원 1
 
0.6%
남양주 1
 
0.6%
한양병원 1
 
0.6%
대아의료재단한도병원 1
 
0.6%
동국대학교일산불교병원 1
 
0.6%
무척조은병원 1
 
0.6%
Other values (130) 130
84.4%
2023-12-11T06:22:44.545782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 130
 
11.9%
병 112
 
10.3%
의 72
 
6.6%
료 63
 
5.8%
41
 
3.8%
인 36
 
3.3%
단 35
 
3.2%
재 33
 
3.0%
법 26
 
2.4%
성 22
 
2.0%
Other values (169) 522
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1047
95.9%
Space Separator 41
 
3.8%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 130
 
12.4%
병 112
 
10.7%
의 72
 
6.9%
료 63
 
6.0%
인 36
 
3.4%
단 35
 
3.3%
재 33
 
3.2%
법 26
 
2.5%
성 22
 
2.1%
대 22
 
2.1%
Other values (166) 496
47.4%
Space Separator
ValueCountFrequency (%)
41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1047
95.9%
Common 45
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 130
 
12.4%
병 112
 
10.7%
의 72
 
6.9%
료 63
 
6.0%
인 36
 
3.4%
단 35
 
3.3%
재 33
 
3.2%
법 26
 
2.5%
성 22
 
2.1%
대 22
 
2.1%
Other values (166) 496
47.4%
Common
ValueCountFrequency (%)
41
91.1%
) 2
 
4.4%
( 2
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1047
95.9%
ASCII 45
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 130
 
12.4%
병 112
 
10.7%
의 72
 
6.9%
료 63
 
6.0%
인 36
 
3.4%
단 35
 
3.3%
재 33
 
3.2%
법 26
 
2.5%
성 22
 
2.1%
대 22
 
2.1%
Other values (166) 496
47.4%
ASCII
ValueCountFrequency (%)
41
91.1%
) 2
 
4.4%
( 2
 
4.4%

평가내역
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
폐렴
113 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐렴 113
100.0%

Length

2023-12-11T06:22:44.688583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:22:44.774362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐렴 113
100.0%

평가등급
Categorical

Distinct6
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
1등급
50 
4등급
26 
3등급
20 
2등급
10 
5등급
 
4

Length

Max length4
Median length3
Mean length3.0265487
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1등급 50
44.2%
4등급 26
23.0%
3등급 20
 
17.7%
2등급 10
 
8.8%
5등급 4
 
3.5%
등급제외 3
 
2.7%

Length

2023-12-11T06:22:44.863485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:22:44.964660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1등급 50
44.2%
4등급 26
23.0%
3등급 20
 
17.7%
2등급 10
 
8.8%
5등급 4
 
3.5%
등급제외 3
 
2.7%

소재지도로명주소
Text

MISSING 

Distinct110
Distinct (%)100.0%
Missing3
Missing (%)2.7%
Memory size1.0 KiB
2023-12-11T06:22:45.300558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length18.272727
Min length13

Characters and Unicode

Total characters2010
Distinct characters153
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

Unique110 ?
Unique (%)100.0%

Sample

1st row경기도 의정부시 천보로 271
2nd row경기도 안성시 남파로 95
3rd row경기도 의정부시 흥선로 142
4th row경기도 안산시 단원구 적금로 123
5th row경기도 고양시 일산동구 일산로 323
ValueCountFrequency (%)
경기도 110
 
22.1%
수원시 9
 
1.8%
안산시 8
 
1.6%
평택시 8
 
1.6%
남양주시 7
 
1.4%
의정부시 7
 
1.4%
고양시 7
 
1.4%
부천시 6
 
1.2%
성남시 6
 
1.2%
용인시 5
 
1.0%
Other values (246) 324
65.2%
2023-12-11T06:22:45.842741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
387
19.3%
경 117
 
5.8%
기 112
 
5.6%
시 112
 
5.6%
도 111
 
5.5%
로 105
 
5.2%
1 67
 
3.3%
3 46
 
2.3%
구 46
 
2.3%
2 44
 
2.2%
Other values (143) 863
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1267
63.0%
Space Separator 387
 
19.3%
Decimal Number 347
 
17.3%
Dash Punctuation 9
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 117
 
9.2%
기 112
 
8.8%
시 112
 
8.8%
도 111
 
8.8%
로 105
 
8.3%
구 46
 
3.6%
양 27
 
2.1%
안 25
 
2.0%
길 24
 
1.9%
산 24
 
1.9%
Other values (131) 564
44.5%
Decimal Number
ValueCountFrequency (%)
1 67
19.3%
3 46
13.3%
2 44
12.7%
6 33
9.5%
5 32
9.2%
7 32
9.2%
9 27
7.8%
4 23
 
6.6%
0 22
 
6.3%
8 21
 
6.1%
Space Separator
ValueCountFrequency (%)
387
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1267
63.0%
Common 743
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 117
 
9.2%
기 112
 
8.8%
시 112
 
8.8%
도 111
 
8.8%
로 105
 
8.3%
구 46
 
3.6%
양 27
 
2.1%
안 25
 
2.0%
길 24
 
1.9%
산 24
 
1.9%
Other values (131) 564
44.5%
Common
ValueCountFrequency (%)
387
52.1%
1 67
 
9.0%
3 46
 
6.2%
2 44
 
5.9%
6 33
 
4.4%
5 32
 
4.3%
7 32
 
4.3%
9 27
 
3.6%
4 23
 
3.1%
0 22
 
3.0%
Other values (2) 30
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1267
63.0%
ASCII 743
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
387
52.1%
1 67
 
9.0%
3 46
 
6.2%
2 44
 
5.9%
6 33
 
4.4%
5 32
 
4.3%
7 32
 
4.3%
9 27
 
3.6%
4 23
 
3.1%
0 22
 
3.0%
Other values (2) 30
 
4.0%
Hangul
ValueCountFrequency (%)
경 117
 
9.2%
기 112
 
8.8%
시 112
 
8.8%
도 111
 
8.8%
로 105
 
8.3%
구 46
 
3.6%
양 27
 
2.1%
안 25
 
2.0%
길 24
 
1.9%
산 24
 
1.9%
Other values (131) 564
44.5%

소재지지번주소
Text

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T06:22:46.142358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length35
Mean length24.80531
Min length16

Characters and Unicode

Total characters2803
Distinct characters190
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

Unique113 ?
Unique (%)100.0%

Sample

1st row경기도 의정부시 금오동 65-1번지 의정부성모병원
2nd row경기도 안성시 당왕동 585번지
3rd row경기도 의정부시 의정부동 433번지
4th row경기도 안산시 단원구 고잔동 516번지
5th row경기도 고양시 일산동구 마두동 809번지
ValueCountFrequency (%)
경기도 113
 
19.8%
수원시 9
 
1.6%
안산시 8
 
1.4%
남양주시 8
 
1.4%
평택시 8
 
1.4%
고양시 7
 
1.2%
의정부시 7
 
1.2%
부천시 6
 
1.0%
성남시 6
 
1.0%
용인시 5
 
0.9%
Other values (323) 395
69.1%
2023-12-11T06:22:46.590921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
459
 
16.4%
지 129
 
4.6%
기 117
 
4.2%
경 115
 
4.1%
도 115
 
4.1%
시 114
 
4.1%
번 114
 
4.1%
동 104
 
3.7%
1 100
 
3.6%
- 80
 
2.9%
Other values (180) 1356
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1720
61.4%
Decimal Number 512
 
18.3%
Space Separator 459
 
16.4%
Dash Punctuation 80
 
2.9%
Other Punctuation 17
 
0.6%
Math Symbol 7
 
0.2%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 129
 
7.5%
기 117
 
6.8%
경 115
 
6.7%
도 115
 
6.7%
시 114
 
6.6%
번 114
 
6.6%
동 104
 
6.0%
원 51
 
3.0%
구 44
 
2.6%
양 34
 
2.0%
Other values (161) 783
45.5%
Decimal Number
ValueCountFrequency (%)
1 100
19.5%
4 59
11.5%
2 59
11.5%
3 57
11.1%
5 45
8.8%
9 43
8.4%
6 41
8.0%
0 40
 
7.8%
8 34
 
6.6%
7 34
 
6.6%
Other Punctuation
ValueCountFrequency (%)
, 16
94.1%
/ 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
459
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1720
61.4%
Common 1081
38.6%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 129
 
7.5%
기 117
 
6.8%
경 115
 
6.7%
도 115
 
6.7%
시 114
 
6.6%
번 114
 
6.6%
동 104
 
6.0%
원 51
 
3.0%
구 44
 
2.6%
양 34
 
2.0%
Other values (161) 783
45.5%
Common
ValueCountFrequency (%)
459
42.5%
1 100
 
9.3%
- 80
 
7.4%
4 59
 
5.5%
2 59
 
5.5%
3 57
 
5.3%
5 45
 
4.2%
9 43
 
4.0%
6 41
 
3.8%
0 40
 
3.7%
Other values (7) 98
 
9.1%
Latin
ValueCountFrequency (%)
G 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1720
61.4%
ASCII 1083
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
459
42.4%
1 100
 
9.2%
- 80
 
7.4%
4 59
 
5.4%
2 59
 
5.4%
3 57
 
5.3%
5 45
 
4.2%
9 43
 
4.0%
6 41
 
3.8%
0 40
 
3.7%
Other values (9) 100
 
9.2%
Hangul
ValueCountFrequency (%)
지 129
 
7.5%
기 117
 
6.8%
경 115
 
6.7%
도 115
 
6.7%
시 114
 
6.6%
번 114
 
6.6%
동 104
 
6.0%
원 51
 
3.0%
구 44
 
2.6%
양 34
 
2.0%
Other values (161) 783
45.5%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct110
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14199.664
Minimum10086
Maximum18592
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T06:22:46.764185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10086
5-th percentile10396.8
Q111918
median14096
Q316499
95-th percentile18139.2
Maximum18592
Range8506
Interquartile range (IQR)4581

Descriptive statistics

Standard deviation2616.754
Coefficient of variation (CV)0.18428282
Kurtosis-1.3647122
Mean14199.664
Median Absolute Deviation (MAD)2331
Skewness0.087549947
Sum1604562
Variance6847401.6
MonotonicityNot monotonic
2023-12-11T06:22:46.898994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11686 3
 
2.7%
11918 2
 
1.8%
10326 1
 
0.9%
10355 1
 
0.9%
10099 1
 
0.9%
10475 1
 
0.9%
18592 1
 
0.9%
17909 1
 
0.9%
15034 1
 
0.9%
16995 1
 
0.9%
Other values (100) 100
88.5%
ValueCountFrequency (%)
10086 1
0.9%
10099 1
0.9%
10113 1
0.9%
10326 1
0.9%
10355 1
0.9%
10380 1
0.9%
10408 1
0.9%
10444 1
0.9%
10475 1
0.9%
10518 1
0.9%
ValueCountFrequency (%)
18592 1
0.9%
18450 1
0.9%
18356 1
0.9%
18270 1
0.9%
18256 1
0.9%
18144 1
0.9%
18136 1
0.9%
17936 1
0.9%
17909 1
0.9%
17874 1
0.9%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct112
Distinct (%)100.0%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean37.441498
Minimum36.98405
Maximum37.911037
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T06:22:47.030883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.98405
5-th percentile37.007219
Q137.278098
median37.407102
Q337.650558
95-th percentile37.821558
Maximum37.911037
Range0.92698761
Interquartile range (IQR)0.37245969

Descriptive statistics

Standard deviation0.24284208
Coefficient of variation (CV)0.0064859072
Kurtosis-0.89281088
Mean37.441498
Median Absolute Deviation (MAD)0.19556303
Skewness-0.020076774
Sum4193.4478
Variance0.058972278
MonotonicityNot monotonic
2023-12-11T06:22:47.181241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7585227082 1
 
0.9%
37.0052394653 1
 
0.9%
37.6330010089 1
 
0.9%
37.6424745722 1
 
0.9%
37.1313495282 1
 
0.9%
36.9930565731 1
 
0.9%
37.3499087489 1
 
0.9%
37.2707754145 1
 
0.9%
37.2793432963 1
 
0.9%
37.4528318807 1
 
0.9%
Other values (102) 102
90.3%
ValueCountFrequency (%)
36.9840497212 1
0.9%
36.9905649024 1
0.9%
36.9930565731 1
0.9%
37.0034226893 1
0.9%
37.0052394653 1
0.9%
37.0058059754 1
0.9%
37.0083742374 1
0.9%
37.0173057984 1
0.9%
37.0482621367 1
0.9%
37.0797779061 1
0.9%
ValueCountFrequency (%)
37.9110373304 1
0.9%
37.9030934888 1
0.9%
37.8848827889 1
0.9%
37.8639614261 1
0.9%
37.854250207 1
0.9%
37.8274877024 1
0.9%
37.8167055283 1
0.9%
37.7585227082 1
0.9%
37.7580480392 1
0.9%
37.7548777512 1
0.9%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct112
Distinct (%)100.0%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean127.02914
Minimum126.66026
Maximum127.63292
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T06:22:47.326342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.66026
5-th percentile126.74801
Q1126.83493
median127.04294
Q3127.14168
95-th percentile127.44093
Maximum127.63292
Range0.97266839
Interquartile range (IQR)0.30675746

Descriptive statistics

Standard deviation0.21049524
Coefficient of variation (CV)0.0016570626
Kurtosis0.40939439
Mean127.02914
Median Absolute Deviation (MAD)0.15702541
Skewness0.6537764
Sum14227.264
Variance0.044308247
MonotonicityNot monotonic
2023-12-11T06:22:47.480384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0779287098 1
 
0.9%
127.266797905 1
 
0.9%
126.7105517913 1
 
0.9%
126.8317454892 1
 
0.9%
126.9107734239 1
 
0.9%
127.0890739281 1
 
0.9%
126.7370103825 1
 
0.9%
127.1482844761 1
 
0.9%
127.0463045226 1
 
0.9%
127.1620415598 1
 
0.9%
Other values (102) 102
90.3%
ValueCountFrequency (%)
126.660255538 1
0.9%
126.7105517913 1
0.9%
126.7284520798 1
0.9%
126.7347224643 1
0.9%
126.7370103825 1
0.9%
126.7451220069 1
0.9%
126.7503817665 1
0.9%
126.7621105079 1
0.9%
126.7694862939 1
0.9%
126.774853086 1
0.9%
ValueCountFrequency (%)
127.6329239251 1
0.9%
127.6253165893 1
0.9%
127.6121106081 1
0.9%
127.5213805697 1
0.9%
127.5034843038 1
0.9%
127.4503587588 1
0.9%
127.4332171305 1
0.9%
127.3516963281 1
0.9%
127.3043775936 1
0.9%
127.2707076272 1
0.9%

Interactions

2023-12-11T06:22:43.263222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:42.796589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:43.029168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:43.346367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:42.869663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:43.109951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:43.440374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:42.950738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:43.185128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:22:47.574028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명평가등급소재지우편번호WGS84위도WGS84경도
시군명1.0000.0000.9930.9650.952
평가등급0.0001.0000.0000.3420.000
소재지우편번호0.9930.0001.0000.9130.846
WGS84위도0.9650.3420.9131.0000.658
WGS84경도0.9520.0000.8460.6581.000
2023-12-11T06:22:47.662847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명평가등급
시군명1.0000.000
평가등급0.0001.000
2023-12-11T06:22:47.737800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명평가등급
소재지우편번호1.000-0.9200.1760.8530.000
WGS84위도-0.9201.000-0.1330.7170.182
WGS84경도0.176-0.1331.0000.6700.000
시군명0.8530.7170.6701.0000.000
평가등급0.0000.1820.0000.0001.000

Missing values

2023-12-11T06:22:43.543412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:22:43.741758image/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.
2023-12-11T06:22:43.834983image/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

시군명기관명평가내역평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0의정부시가톨릭대학교의정부성모병원폐렴1등급경기도 의정부시 천보로 271경기도 의정부시 금오동 65-1번지 의정부성모병원1176537.758523127.077929
1안성시경기도의료원 안성병원폐렴1등급경기도 안성시 남파로 95경기도 안성시 당왕동 585번지1756837.017306127.260297
2의정부시경기도의료원의정부병원폐렴1등급경기도 의정부시 흥선로 142경기도 의정부시 의정부동 433번지1167137.741076127.042514
3안산시고려대학교의과대학부속안산병원폐렴1등급경기도 안산시 단원구 적금로 123경기도 안산시 단원구 고잔동 516번지1535537.318859126.824994
4고양시국립암센터폐렴1등급경기도 고양시 일산동구 일산로 323경기도 고양시 일산동구 마두동 809번지1040837.663237126.783396
5안산시근로복지공단안산병원폐렴1등급경기도 안산시 상록구 구룡로 87경기도 안산시 상록구 일동 95번지 근로복지공단안산병원1532437.316767126.873993
6성남시대진의료재단 분당제생병원폐렴1등급경기도 성남시 분당구 서현로180번길 20경기도 성남시 분당구 서현동 255-2번지1359037.388208127.121777
7파주시메디인병원폐렴1등급경기도 파주시 시청로 6경기도 파주시 금촌동 948-3번지 메디인병원1092437.758048126.774853
8부천시부천세종병원폐렴1등급경기도 부천시 호현로489번길 28경기도 부천시 소사본동 91-121번지 세종병원1475437.481042126.79119
9성남시분당서울대학교병원폐렴1등급경기도 성남시 분당구 구미로173번길 82경기도 성남시 분당구 구미동 300번지 분당서울대학교병원1362037.352017127.124499
시군명기관명평가내역평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
103남양주시원병원폐렴3등급경기도 남양주시 화도읍 경춘로 1943-16경기도 남양주시 화도읍 창현리 495-3번지1217937.651911127.304378
104의정부시의료법인 영동의료재단 의정부백병원폐렴3등급경기도 의정부시 금신로 322경기도 의정부시 신곡동 519-11번지1177837.745306127.062136
105이천시이천엘리야병원폐렴3등급경기도 이천시 장호원읍 서동대로 8793경기도 이천시 장호원읍 장호원리 341번지 이천엘리야병원1742137.115895127.612111
106의정부시호원병원폐렴3등급경기도 의정부시 신흥로 145-1경기도 의정부시 호원동 345-6번지 B2-5층1162737.729038127.043359
107김포시히즈메디병원폐렴3등급경기도 김포시 김포대로 681경기도 김포시 풍무동 258-26번지1011337.611222126.734722
108하남시더 바른병원폐렴4등급경기도 하남시 신장로 93-1경기도 하남시 신장동 432-17번지1296437.536771127.207369
109이천시바른병원폐렴4등급경기도 이천시 경충대로 2543경기도 이천시 진리동 9-11번지 바른병원1738137.273757127.450359
110평택시서울제일병원폐렴4등급경기도 평택시 지산로 70경기도 평택시 지산동 1078번지 2-7층1776337.079778127.062381
111여주시세종여주병원폐렴4등급경기도 여주시 청심로 39경기도 여주시 하동 435번지 세종여주병원1261837.301482127.625317
112수원시수원한국병원폐렴4등급경기도 수원시 장안구 경수대로 969경기도 수원시 장안구 송죽동 495-4번지1630437.303947127.004745