Overview

Dataset statistics

Number of variables8
Number of observations142
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.6 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
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=435&beforeMenuCd=DOM_000000201001001000&publicdatapk=15055148

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
의료기관전화번호 has unique valuesUnique
입원실 has 125 (88.0%) zerosZeros
병상 has 125 (88.0%) zerosZeros

Reproduction

Analysis started2024-01-09 22:45:31.736655
Analysis finished2024-01-09 22:45:33.477909
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.5
Minimum1
Maximum142
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-01-10T07:45:33.552483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.05
Q136.25
median71.5
Q3106.75
95-th percentile134.95
Maximum142
Range141
Interquartile range (IQR)70.5

Descriptive statistics

Standard deviation41.135953
Coefficient of variation (CV)0.57532802
Kurtosis-1.2
Mean71.5
Median Absolute Deviation (MAD)35.5
Skewness0
Sum10153
Variance1692.1667
MonotonicityStrictly increasing
2024-01-10T07:45:33.696942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
99 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
100 1
 
0.7%
91 1
 
0.7%
Other values (132) 132
93.0%
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 (%)
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%

전문과목
Categorical

Distinct19
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
내과
22 
가정의학과
21 
<NA>
21 
소아청소년과
11 
이비인후과
Other values (14)
59 

Length

Max length8
Median length7
Mean length4.1971831
Min length2

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row신경외과
2nd row마취통증의학과
3rd row영상의학과
4th row정신건강의학과
5th row가정의학과

Common Values

ValueCountFrequency (%)
내과 22
15.5%
가정의학과 21
14.8%
<NA> 21
14.8%
소아청소년과 11
7.7%
이비인후과 8
 
5.6%
외과 7
 
4.9%
정형외과 7
 
4.9%
안과 7
 
4.9%
비뇨의학과 6
 
4.2%
마취통증의학과 5
 
3.5%
Other values (9) 27
19.0%

Length

2024-01-10T07:45:33.847629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
내과 22
15.5%
na 21
14.8%
가정의학과 21
14.8%
소아청소년과 11
7.7%
이비인후과 8
 
5.6%
외과 7
 
4.9%
정형외과 7
 
4.9%
안과 7
 
4.9%
비뇨의학과 6
 
4.2%
산부인과 5
 
3.5%
Other values (9) 27
19.0%

의료기관명
Text

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-10T07:45:34.033687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.7746479
Min length4

Characters and Unicode

Total characters1104
Distinct characters197
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

Unique142 ?
Unique (%)100.0%

Sample

1st row아산탑신경외과의원
2nd row신세계마취통증의학과의원
3rd row연세비에이치의원
4th row키다리정신건강의학과의원
5th row클린스의원
ValueCountFrequency (%)
아산탑신경외과의원 1
 
0.7%
아산현대의원 1
 
0.7%
속이좋은내과의원 1
 
0.7%
아산제일내과의원 1
 
0.7%
봄정신건강의학과의원 1
 
0.7%
미래메디칼의원 1
 
0.7%
박영선내과의원 1
 
0.7%
박종필성형외과의원 1
 
0.7%
청아미즈산부인과의원 1
 
0.7%
영인외과의원 1
 
0.7%
Other values (133) 133
93.0%
2024-01-10T07:45:34.335426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
 
14.7%
144
 
13.0%
97
 
8.8%
34
 
3.1%
24
 
2.2%
23
 
2.1%
23
 
2.1%
23
 
2.1%
19
 
1.7%
19
 
1.7%
Other values (187) 536
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1087
98.5%
Decimal Number 6
 
0.5%
Uppercase Letter 5
 
0.5%
Other Punctuation 2
 
0.2%
Lowercase Letter 1
 
0.1%
Space Separator 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
162
 
14.9%
144
 
13.2%
97
 
8.9%
34
 
3.1%
24
 
2.2%
23
 
2.1%
23
 
2.1%
23
 
2.1%
19
 
1.7%
19
 
1.7%
Other values (174) 519
47.7%
Uppercase Letter
ValueCountFrequency (%)
J 2
40.0%
D 1
20.0%
G 1
20.0%
E 1
20.0%
Decimal Number
ValueCountFrequency (%)
3 2
33.3%
6 2
33.3%
5 2
33.3%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
. 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
r 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1087
98.5%
Common 11
 
1.0%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
162
 
14.9%
144
 
13.2%
97
 
8.9%
34
 
3.1%
24
 
2.2%
23
 
2.1%
23
 
2.1%
23
 
2.1%
19
 
1.7%
19
 
1.7%
Other values (174) 519
47.7%
Common
ValueCountFrequency (%)
3 2
18.2%
6 2
18.2%
5 2
18.2%
& 1
9.1%
1
9.1%
) 1
9.1%
( 1
9.1%
. 1
9.1%
Latin
ValueCountFrequency (%)
J 2
33.3%
D 1
16.7%
r 1
16.7%
G 1
16.7%
E 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1087
98.5%
ASCII 17
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
162
 
14.9%
144
 
13.2%
97
 
8.9%
34
 
3.1%
24
 
2.2%
23
 
2.1%
23
 
2.1%
23
 
2.1%
19
 
1.7%
19
 
1.7%
Other values (174) 519
47.7%
ASCII
ValueCountFrequency (%)
3 2
11.8%
6 2
11.8%
J 2
11.8%
5 2
11.8%
& 1
 
5.9%
D 1
 
5.9%
r 1
 
5.9%
G 1
 
5.9%
E 1
 
5.9%
1
 
5.9%
Other values (3) 3
17.6%
Distinct137
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-10T07:45:34.606517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length43
Mean length28.788732
Min length19

Characters and Unicode

Total characters4088
Distinct characters159
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

Unique132 ?
Unique (%)93.0%

Sample

1st row충청남도 아산시 배방읍 배방로 25, 장호빌딩 4층
2nd row충청남도 아산시 온궁로 33, 3층 (온천동)
3rd row충청남도 아산시 배방읍 고속철대로 83, 5층
4th row충청남도 아산시 배방읍 광장로 210, 202동 A214호 (요진 와이시티)
5th row충청남도 아산시 탕정면 한들물빛도시로 88, 거산타워 403~406호
ValueCountFrequency (%)
충청남도 142
 
16.2%
아산시 142
 
16.2%
온천동 48
 
5.5%
배방읍 33
 
3.8%
충무로 22
 
2.5%
3층 19
 
2.2%
모종동 17
 
1.9%
2층 16
 
1.8%
온천대로 14
 
1.6%
5층 9
 
1.0%
Other values (241) 414
47.3%
2024-01-10T07:45:35.248917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
734
 
18.0%
166
 
4.1%
164
 
4.0%
161
 
3.9%
158
 
3.9%
147
 
3.6%
146
 
3.6%
144
 
3.5%
2 133
 
3.3%
131
 
3.2%
Other values (149) 2004
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2329
57.0%
Space Separator 734
 
18.0%
Decimal Number 663
 
16.2%
Other Punctuation 117
 
2.9%
Open Punctuation 101
 
2.5%
Close Punctuation 101
 
2.5%
Dash Punctuation 22
 
0.5%
Math Symbol 13
 
0.3%
Uppercase Letter 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
166
 
7.1%
164
 
7.0%
161
 
6.9%
158
 
6.8%
147
 
6.3%
146
 
6.3%
144
 
6.2%
131
 
5.6%
88
 
3.8%
68
 
2.9%
Other values (128) 956
41.0%
Decimal Number
ValueCountFrequency (%)
2 133
20.1%
1 116
17.5%
3 95
14.3%
4 85
12.8%
0 63
9.5%
5 58
8.7%
8 34
 
5.1%
6 31
 
4.7%
7 25
 
3.8%
9 23
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
37.5%
J 3
37.5%
G 1
 
12.5%
A 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 116
99.1%
. 1
 
0.9%
Space Separator
ValueCountFrequency (%)
734
100.0%
Open Punctuation
ValueCountFrequency (%)
( 101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2329
57.0%
Common 1751
42.8%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
166
 
7.1%
164
 
7.0%
161
 
6.9%
158
 
6.8%
147
 
6.3%
146
 
6.3%
144
 
6.2%
131
 
5.6%
88
 
3.8%
68
 
2.9%
Other values (128) 956
41.0%
Common
ValueCountFrequency (%)
734
41.9%
2 133
 
7.6%
, 116
 
6.6%
1 116
 
6.6%
( 101
 
5.8%
) 101
 
5.8%
3 95
 
5.4%
4 85
 
4.9%
0 63
 
3.6%
5 58
 
3.3%
Other values (7) 149
 
8.5%
Latin
ValueCountFrequency (%)
S 3
37.5%
J 3
37.5%
G 1
 
12.5%
A 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2329
57.0%
ASCII 1759
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
734
41.7%
2 133
 
7.6%
, 116
 
6.6%
1 116
 
6.6%
( 101
 
5.7%
) 101
 
5.7%
3 95
 
5.4%
4 85
 
4.8%
0 63
 
3.6%
5 58
 
3.3%
Other values (11) 157
 
8.9%
Hangul
ValueCountFrequency (%)
166
 
7.1%
164
 
7.0%
161
 
6.9%
158
 
6.8%
147
 
6.3%
146
 
6.3%
144
 
6.2%
131
 
5.6%
88
 
3.8%
68
 
2.9%
Other values (128) 956
41.0%
Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-10T07:45:35.497307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1704
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

Unique142 ?
Unique (%)100.0%

Sample

1st row041-427-0175
2nd row041-534-6939
3rd row041-532-9988
4th row041-555-3255
5th row041-427-0075
ValueCountFrequency (%)
041-427-0175 1
 
0.7%
041-547-3375 1
 
0.7%
041-547-0707 1
 
0.7%
041-545-6388 1
 
0.7%
041-548-3191 1
 
0.7%
041-533-0087 1
 
0.7%
041-545-7588 1
 
0.7%
041-532-6838 1
 
0.7%
041-531-7525 1
 
0.7%
041-548-5275 1
 
0.7%
Other values (132) 132
93.0%
2024-01-10T07:45:35.829189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/