Overview

Dataset statistics

Number of variables8
Number of observations153
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.3 KiB
Average record size in memory68.9 B

Variable types

Numeric4
Categorical1
Text3

Dataset

Description아산시 관내 운영중인 의원현황자료로서 전문과목, 의료기관명,주소지,전화번호,입원실 및 병상수, 총면적의 정보를 제공합니다.
Author충청남도 아산시
URLhttps://www.data.go.kr/data/15055148/fileData.do

Alerts

입원실 is highly overall correlated with 병상High correlation
병상 is highly overall correlated with 입원실High correlation
순번 has unique valuesUnique
의료기관명 has unique valuesUnique
입원실 has 135 (88.2%) zerosZeros
병상 has 135 (88.2%) zerosZeros

Reproduction

Analysis started2024-05-11 10:45:23.208816
Analysis finished2024-05-11 10:45:30.492435
Duration7.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77
Minimum1
Maximum153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T10:45:30.730026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.6
Q139
median77
Q3115
95-th percentile145.4
Maximum153
Range152
Interquartile range (IQR)76

Descriptive statistics

Standard deviation44.311398
Coefficient of variation (CV)0.5754727
Kurtosis-1.2
Mean77
Median Absolute Deviation (MAD)38
Skewness0
Sum11781
Variance1963.5
MonotonicityStrictly increasing
2024-05-11T10:45:31.294239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
106 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
105 1
 
0.7%
107 1
 
0.7%
Other values (143) 143
93.5%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
153 1
0.7%
152 1
0.7%
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%

전문과목
Categorical

Distinct19
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
내과
24 
가정의학과
20 
<NA>
20 
소아청소년과
12 
이비인후과
9 
Other values (14)
68 

Length

Max length8
Median length7
Mean length4.254902
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row마취통증의학과
3rd row소아청소년과
4th row정신건강의학과
5th row피부과

Common Values

ValueCountFrequency (%)
내과 24
15.7%
가정의학과 20
13.1%
<NA> 20
13.1%
소아청소년과 12
 
7.8%
이비인후과 9
 
5.9%
정신건강의학과 8
 
5.2%
마취통증의학과 7
 
4.6%
안과 7
 
4.6%
정형외과 7
 
4.6%
외과 7
 
4.6%
Other values (9) 32
20.9%

Length

2024-05-11T10:45:31.947224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
내과 24
15.7%
na 20
13.1%
가정의학과 20
13.1%
소아청소년과 12
 
7.8%
이비인후과 9
 
5.9%
정신건강의학과 8
 
5.2%
정형외과 7
 
4.6%
외과 7
 
4.6%
안과 7
 
4.6%
마취통증의학과 7
 
4.6%
Other values (9) 32
20.9%

의료기관명
Text

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T10:45:32.580141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.9019608
Min length4

Characters and Unicode

Total characters1209
Distinct characters207
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

Unique153 ?
Unique (%)100.0%

Sample

1st row미뉴얼의원
2nd row연세온마취통증의학과의원
3rd row탕정아이꽃소아청소년과의원
4th row함께공감정신건강의학과의원
5th row얼라이브피부과의원
ValueCountFrequency (%)
미뉴얼의원 1
 
0.6%
아산제일내과의원 1
 
0.6%
dr 1
 
0.6%
목의원 1
 
0.6%
상쾌한이비인후과의원 1
 
0.6%
연세소아청소년과의원 1
 
0.6%
아산현대의원 1
 
0.6%
청아미즈산부인과의원 1
 
0.6%
속이좋은내과의원 1
 
0.6%
봄정신건강의학과의원 1
 
0.6%
Other values (144) 144
93.5%
2024-05-11T10:45:33.707337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 176
 
14.6%
원 155
 
12.8%
과 105
 
8.7%
아 36
 
3.0%
정 28
 
2.3%
이 27
 
2.2%
내 25
 
2.1%
소 23
 
1.9%
학 22
 
1.8%
외 19
 
1.6%
Other values (197) 593
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1195
98.8%
Uppercase Letter 5
 
0.4%
Decimal Number 3
 
0.2%
Other Punctuation 2
 
0.2%
Lowercase Letter 1
 
0.1%
Space Separator 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 176
 
14.7%
원 155
 
13.0%
과 105
 
8.8%
아 36
 
3.0%
정 28
 
2.3%
이 27
 
2.3%
내 25
 
2.1%
소 23
 
1.9%
학 22
 
1.8%
외 19
 
1.6%
Other values (184) 579
48.5%
Uppercase Letter
ValueCountFrequency (%)
J 2
40.0%
D 1
20.0%
G 1
20.0%
E 1
20.0%
Decimal Number
ValueCountFrequency (%)
5 1
33.3%
6 1
33.3%
3 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
& 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
r 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1195
98.8%
Common 8
 
0.7%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 176
 
14.7%
원 155
 
13.0%
과 105
 
8.8%
아 36
 
3.0%
정 28
 
2.3%
이 27
 
2.3%
내 25
 
2.1%
소 23
 
1.9%
학 22
 
1.8%
외 19
 
1.6%
Other values (184) 579
48.5%
Common
ValueCountFrequency (%)
. 1
12.5%
1
12.5%
& 1
12.5%
( 1
12.5%
) 1
12.5%
5 1
12.5%
6 1
12.5%
3 1
12.5%
Latin
ValueCountFrequency (%)
J 2
33.3%
r 1
16.7%
D 1
16.7%
G 1
16.7%
E 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1195
98.8%
ASCII 14
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 176
 
14.7%
원 155
 
13.0%
과 105
 
8.8%
아 36
 
3.0%
정 28
 
2.3%
이 27
 
2.3%
내 25
 
2.1%
소 23
 
1.9%
학 22
 
1.8%
외 19
 
1.6%
Other values (184) 579
48.5%
ASCII
ValueCountFrequency (%)
J 2
14.3%
r 1
 
7.1%
. 1
 
7.1%
1
 
7.1%
D 1
 
7.1%
& 1
 
7.1%
G 1
 
7.1%
E 1
 
7.1%
( 1
 
7.1%
) 1
 
7.1%
Other values (3) 3
21.4%

의료기관주소(도로명)
Text

Distinct148
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T10:45:34.444241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length42
Mean length29.411765
Min length19

Characters and Unicode

Total characters4500
Distinct characters162
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

Unique143 ?
Unique (%)93.5%

Sample

1st row충청남도 아산시 탕정면 한들물빛5로 5, 606,607,608호
2nd row충청남도 아산시 탕정면 한들물빛5로 5, 젤존메디컬 5층 502,503,504호
3rd row충청남도 아산시 탕정면 한들물빛5로 5, 2층 203호
4th row충청남도 아산시 탕정면 한들물빛5로 5, 젤존메디컬시티 6층 603호
5th row충청남도 아산시 탕정면 한들물빛6로 32, KJ타워 5층
ValueCountFrequency (%)
충청남도 153
 
16.0%
아산시 153
 
16.0%
온천동 47
 
4.9%
배방읍 32
 
3.4%
탕정면 21
 
2.2%
충무로 20
 
2.1%
3층 18
 
1.9%
모종동 17
 
1.8%
2층 17
 
1.8%
온천대로 15
 
1.6%
Other values (261) 462
48.4%
2024-05-11T10:45:35.819045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
802
 
17.8%
시 179
 
4.0%
산 174
 
3.9%
충 173
 
3.8%
아 169
 
3.8%
도 159
 
3.5%
남 158
 
3.5%
청 155
 
3.4%
로 142
 
3.2%
2 139
 
3.1%
Other values (152) 2250
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2541
56.5%
Space Separator 802
 
17.8%
Decimal Number 768
 
17.1%
Other Punctuation 139
 
3.1%
Open Punctuation 101
 
2.2%
Close Punctuation 101
 
2.2%
Dash Punctuation 23
 
0.5%
Math Symbol 15
 
0.3%
Uppercase Letter 10
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 179
 
7.0%
산 174
 
6.8%
충 173
 
6.8%
아 169
 
6.7%
도 159
 
6.3%
남 158
 
6.2%
청 155
 
6.1%
로 142
 
5.6%
동 89
 
3.5%
층 72
 
2.8%
Other values (130) 1071
42.1%
Decimal Number
ValueCountFrequency (%)
2 139
18.1%
1 121
15.8%
3 104
13.5%
4 96
12.5%
0 85
11.1%
5 82
10.7%
8 43
 
5.6%
6 42
 
5.5%
7 29
 
3.8%
9 27
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
J 4
40.0%
S 3
30.0%
K 1
 
10.0%
G 1
 
10.0%
A 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 138
99.3%
. 1
 
0.7%
Space Separator
ValueCountFrequency (%)
802
100.0%
Open Punctuation
ValueCountFrequency (%)
( 101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2541
56.5%
Common 1949
43.3%
Latin 10
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 179
 
7.0%
산 174
 
6.8%
충 173
 
6.8%
아 169
 
6.7%
도 159
 
6.3%
남 158
 
6.2%
청 155
 
6.1%
로 142
 
5.6%
동 89
 
3.5%
층 72
 
2.8%
Other values (130) 1071
42.1%
Common
ValueCountFrequency (%)
802
41.1%
2 139
 
7.1%
, 138
 
7.1%
1 121
 
6.2%
3 104
 
5.3%
( 101
 
5.2%
) 101
 
5.2%
4 96
 
4.9%
0 85
 
4.4%
5 82
 
4.2%
Other values (7) 180
 
9.2%
Latin
ValueCountFrequency (%)
J 4
40.0%
S 3
30.0%
K 1
 
10.0%
G 1
 
10.0%
A 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2541
56.5%
ASCII 1959
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
802
40.9%
2 139
 
7.1%
, 138
 
7.0%
1 121
 
6.2%
3 104
 
5.3%
( 101
 
5.2%
) 101
 
5.2%
4 96
 
4.9%
0 85
 
4.3%
5 82
 
4.2%
Other values (12) 190
 
9.7%
Hangul
ValueCountFrequency (%)
시 179
 
7.0%
산 174
 
6.8%
충 173
 
6.8%
아 169
 
6.7%
도 159
 
6.3%
남 158
 
6.2%
청 155
 
6.1%
로 142
 
5.6%
동 89
 
3.5%
층 72
 
2.8%
Other values (130) 1071
42.1%

의료기관전화번호
Text

Distinct152
Distinct (%)100.0%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2024-05-11T10:45:36.655450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1824
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)100.0%

Sample

1st row041-424-2024
2nd row041-572-2221
3rd row041-424-7501
4th row041-910-9900
5th row041-424-7570
ValueCountFrequency (%)
041-424-2220 1
 
0.7%
041-533-0087 1
 
0.7%
041-548-5775 1
 
0.7%
041-541-9753 1
 
0.7%
041-548-5275 1
 
0.7%
041-531-7525 1
 
0.7%
041-547-2020 1
 
0.7%
041-545-6388 1
 
0.7%
041-548-3191 1
 
0.7%
041-532-6838 1
 
0.7%
Other values (142) 142
93.4%
2024-05-11T10:45:38.212394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 304
16.7%
4 302
16.6%
0 272
14.9%
1 238
13.0%
5 236
12.9%
3 110
 
6.0%
7 100
 
5.5%
2 88
 
4.8%
8 70
 
3.8%
9 59
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1520
83.3%
Dash Punctuation 304
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 302
19.9%
0 272
17.9%
1 238
15.7%
5 236
15.5%
3 110
 
7.2%
7 100
 
6.6%
2 88
 
5.8%
8 70
 
4.6%
9 59
 
3.9%
6 45
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 304
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1824
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 304
16.7%
4 302
16.6%
0 272
14.9%
1 238
13.0%
5 236
12.9%
3 110
 
6.0%
7 100
 
5.5%
2 88
 
4.8%
8 70
 
3.8%
9 59
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1824
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 304
16.7%
4 302
16.6%
0 272
14.9%
1 238
13.0%
5 236
12.9%
3 110
 
6.0%
7 100
 
5.5%
2 88
 
4.8%
8 70
 
3.8%
9 59
 
3.2%

입원실
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.84313725
Minimum0
Maximum20
Zeros135
Zeros (%)88.2%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T10:45:38.735593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7.4
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.8310256
Coefficient of variation (CV)3.357728
Kurtosis19.171571
Mean0.84313725
Median Absolute Deviation (MAD)0
Skewness4.1400766
Sum129
Variance8.0147059
MonotonicityNot monotonic
2024-05-11T10:45:39.306221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 135
88.2%
3 4
 
2.6%
10 3
 
2.0%
4 3
 
2.0%
8 2
 
1.3%
14 1
 
0.7%
1 1
 
0.7%
7 1
 
0.7%
12 1
 
0.7%
5 1
 
0.7%
ValueCountFrequency (%)
0 135
88.2%
1 1
 
0.7%
3 4
 
2.6%
4 3
 
2.0%
5 1
 
0.7%
7 1
 
0.7%
8 2
 
1.3%
10 3
 
2.0%
12 1
 
0.7%
14 1
 
0.7%
ValueCountFrequency (%)
20 1
 
0.7%
14 1
 
0.7%
12 1
 
0.7%
10 3
2.0%
8 2
1.3%
7 1
 
0.7%
5 1
 
0.7%
4 3
2.0%
3 4
2.6%
1 1
 
0.7%

병상
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5163399
Minimum0
Maximum29
Zeros135
Zeros (%)88.2%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T10:45:39.848875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10.8
Maximum29
Range29
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.2966034
Coefficient of variation (CV)3.4930186
Kurtosis16.033047
Mean1.5163399
Median Absolute Deviation (MAD)0
Skewness4.0184048
Sum232
Variance28.054008
MonotonicityNot monotonic
2024-05-11T10:45:40.272496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 135
88.2%
3 2
 
1.3%
29 2
 
1.3%
6 2
 
1.3%
4 2
 
1.3%
22 1
 
0.7%
9 1
 
0.7%
12 1
 
0.7%
23 1
 
0.7%
1 1
 
0.7%
Other values (5) 5
 
3.3%
ValueCountFrequency (%)
0 135
88.2%
1 1
 
0.7%
3 2
 
1.3%
4 2
 
1.3%
6 2
 
1.3%
8 1
 
0.7%
9 1
 
0.7%
10 1
 
0.7%
12 1
 
0.7%
15 1
 
0.7%
ValueCountFrequency (%)
29 2
1.3%
28 1
0.7%
23 1
0.7%
22 1
0.7%
20 1
0.7%
15 1
0.7%
12 1
0.7%
10 1
0.7%
9 1
0.7%
8 1
0.7%

총면적
Real number (ℝ)

Distinct151
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean351.22569
Minimum55.18
Maximum1905.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T10:45:40.754567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum55.18
5-th percentile93.844
Q1146.53
median216.71
Q3398.01
95-th percentile1364.756
Maximum1905.81
Range1850.63
Interquartile range (IQR)251.48

Descriptive statistics

Standard deviation373.69652
Coefficient of variation (CV)1.0639783
Kurtosis6.3052239
Mean351.22569
Median Absolute Deviation (MAD)90.11
Skewness2.5588815
Sum53737.53
Variance139649.09
MonotonicityNot monotonic
2024-05-11T10:45:41.336919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165.6 2
 
1.3%
143.0 2
 
1.3%
398.01 1
 
0.7%
632.66 1
 
0.7%
157.3 1
 
0.7%
126.81 1
 
0.7%
1649.94 1
 
0.7%
162.5 1
 
0.7%
422.67 1
 
0.7%
97.61 1
 
0.7%
Other values (141) 141
92.2%
ValueCountFrequency (%)
55.18 1
0.7%
60.39 1
0.7%
69.75 1
0.7%
70.81 1
0.7%
75.46 1
0.7%
87.78 1
0.7%
89.0 1
0.7%
92.41 1
0.7%
94.8 1
0.7%
96.5 1
0.7%
ValueCountFrequency (%)
1905.81 1
0.7%
1829.04 1
0.7%
1738.6 1
0.7%
1649.94 1
0.7%
1643.8 1
0.7%
1457.2 1
0.7%
1415.0 1
0.7%
1376.0 1
0.7%
1357.26 1
0.7%
1322.26 1
0.7%

Interactions

2024-05-11T10:45:28.367817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:24.728634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:25.852030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:26.937070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:28.682938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:24.994421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:26.130759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:27.201982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:29.092294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:25.276084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:26.409333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:27.473516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:29.412544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:25.576672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:26.659426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:45:27.845097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T10:45:41.616710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번전문과목입원실병상총면적
순번1.0000.2360.0480.1730.228
전문과목0.2361.0000.4440.6440.603
입원실0.0480.4441.0000.9780.879
병상0.1730.6440.9781.0000.860
총면적0.2280.6030.8790.8601.000
2024-05-11T10:45:41.991467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번입원실병상총면적전문과목
순번1.000-0.104-0.103-0.3040.062
입원실-0.1041.0001.0000.3850.156
병상-0.1031.0001.0000.3850.257
총면적-0.3040.3850.3851.0000.232
전문과목0.0620.1560.2570.2321.000

Missing values

2024-05-11T10:45:29.845767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:45:30.303455image/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

순번전문과목의료기관명의료기관주소(도로명)의료기관전화번호입원실병상총면적
01<NA>미뉴얼의원충청남도 아산시 탕정면 한들물빛5로 5, 606,607,608호<NA>00398.01
12마취통증의학과연세온마취통증의학과의원충청남도 아산시 탕정면 한들물빛5로 5, 젤존메디컬 5층 502,503,504호041-424-202400359.91
23소아청소년과탕정아이꽃소아청소년과의원충청남도 아산시 탕정면 한들물빛5로 5, 2층 203호041-572-222100165.6
34정신건강의학과함께공감정신건강의학과의원충청남도 아산시 탕정면 한들물빛5로 5, 젤존메디컬시티 6층 603호041-424-750100165.6
45피부과얼라이브피부과의원충청남도 아산시 탕정면 한들물빛6로 32, KJ타워 5층041-910-990000308.49
56이비인후과탕정미래이비인후과의원충청남도 아산시 탕정면 탕정면로 54-3, 2층 203,204호041-424-757000228.12
67피부과바라던피부과의원충청남도 아산시 탕정면 한들물빛5로 25, 주1동 4층 407,408,409호041-424-500100270.4
78정신건강의학과마음동행정신건강의학과의원충청남도 아산시 탕정면 한들물빛6로 46, 703호041-548-750000137.35
89산부인과청담유의원충청남도 아산시 탕정면 한들물빛6로 16, 501~505호041-424-222000216.71
910성형외과압구정메디컬의원충청남도 아산시 온천대로 1538, 3층 (온천동)041-533-777710221376.0
순번전문과목의료기관명의료기관주소(도로명)의료기관전화번호입원실병상총면적
143144안과EG임안과의원충청남도 아산시 충무로 22, 306호 (온천동, 유엘시티)041-544-221100412.8
144145비뇨의학과수비뇨기과의원충청남도 아산시 충무로 14 (온천동)041-545-113000119.06
145146<NA>도고성모의원충청남도 아산시 도고면 아산만로 177041-544-839400104.0
146147<NA>경희의원충청남도 아산시 온천대로 1474 (온천동)041-546-405100149.18
147148내과김병모내과의원충청남도 아산시 충무로 26 (온천동)041-542-812100358.45
148149안과김안과의원충청남도 아산시 충무로 14 (온천동)041-544-13230060.39
149150신경외과온양신경외과의원충청남도 아산시 시민로 424 (온천동)041-544-010000176.8
150151<NA>제일내과의원충청남도 아산시 충무로 16 (온천동)041-545-373300140.3
151152가정의학과서울의원충청남도 아산시 둔포면 둔포중앙로137번길 7-5041-531-456700113.92
152153외과성모외과의원충청남도 아산시 온천대로 1542-5 (온천동)041-545-460000255.22