Overview

Dataset statistics

Number of variables11
Number of observations629
Missing cells10
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory56.0 KiB
Average record size in memory91.2 B

Variable types

Categorical2
Numeric3
Text5
DateTime1

Dataset

Description보훈병원 위탁병원에 대한 위치에 대한 데이터로, 관할,기관기호, 위탁병원명, 종별, 사업자번호, 최초계약일, 우편번호, 주소, 상세주소, 위도, 경도로 되어 있음
Author한국보훈복지의료공단
URLhttps://www.data.go.kr/data/3075427/fileData.do

Alerts

기관기호 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 기관기호 and 1 other fieldsHigh correlation
관할 is highly overall correlated with 기관기호 and 1 other fieldsHigh correlation
기관기호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:51:48.827045
Analysis finished2023-12-12 04:51:51.362425
Duration2.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관할
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
중앙
218 
부산
118 
광주
113 
대구
77 
대전
77 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구
2nd row대구
3rd row대전
4th row대전
5th row대전

Common Values

ValueCountFrequency (%)
중앙 218
34.7%
부산 118
18.8%
광주 113
18.0%
대구 77
 
12.2%
대전 77
 
12.2%
인천 26
 
4.1%

Length

2023-12-12T13:51:51.434238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:51:51.594088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중앙 218
34.7%
부산 118
18.8%
광주 113
18.0%
대구 77
 
12.2%
대전 77
 
12.2%
인천 26
 
4.1%

기관기호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct629
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31592072
Minimum11100109
Maximum41387252
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-12T13:51:51.783377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11100109
5-th percentile11384007
Q131208452
median34352112
Q337331990
95-th percentile41308272
Maximum41387252
Range30287143
Interquartile range (IQR)6123538

Descriptive statistics

Standard deviation8793216.2
Coefficient of variation (CV)0.27833617
Kurtosis0.67209525
Mean31592072
Median Absolute Deviation (MAD)3005631
Skewness-1.404075
Sum1.9871413 × 1010
Variance7.7320651 × 1013
MonotonicityNot monotonic
2023-12-12T13:51:51.984399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37100041 1
 
0.2%
36309486 1
 
0.2%
37323687 1
 
0.2%
11205393 1
 
0.2%
12312908 1
 
0.2%
33322899 1
 
0.2%
36343471 1
 
0.2%
35316136 1
 
0.2%
36344737 1
 
0.2%
21328072 1
 
0.2%
Other values (619) 619
98.4%
ValueCountFrequency (%)
11100109 1
0.2%
11101407 1
0.2%
11200766 1
0.2%
11201703 1
0.2%
11204681 1
0.2%
11205016 1
0.2%
11205393 1
0.2%
11206659 1
0.2%
11206781 1
0.2%
11206811 1
0.2%
ValueCountFrequency (%)
41387252 1
0.2%
41387040 1
0.2%
41382650 1
0.2%
41379454 1
0.2%
41375530 1
0.2%
41374037 1
0.2%
41371135 1
0.2%
41368665 1
0.2%
41367154 1
0.2%
41362918 1
0.2%

위탁병원명
Text

Distinct627
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T13:51:52.342149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length7.9062003
Min length3

Characters and Unicode

Total characters4973
Distinct characters335
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique625 ?
Unique (%)99.4%

Sample

1st row포항의료원
2nd row삼성연합의원(의성)
3rd row건양대학교 부여병원
4th row괴산성모병원
5th row정민의료재단 보은한양병원
ValueCountFrequency (%)
경기도의료원 3
 
0.4%
경기도립의료원 3
 
0.4%
근로복지공단 3
 
0.4%
의)열린의료재단 3
 
0.4%
하나이비인후과의원 2
 
0.3%
제주의료원 2
 
0.3%
우리이비인후과의원 2
 
0.3%
인천광역시의료원 2
 
0.3%
우리연합의원 1
 
0.1%
손장원정형외과의원 1
 
0.1%
Other values (661) 661
96.8%
2023-12-12T13:51:52.864142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 652
 
13.1%
의 504
 
10.1%
과 304
 
6.1%
병 233
 
4.7%
내 108
 
2.2%
정 83
 
1.7%
료 80
 
1.6%
외 78
 
1.6%
성 77
 
1.5%
비 64
 
1.3%
Other values (325) 2790
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4792
96.4%
Space Separator 54
 
1.1%
Close Punctuation 46
 
0.9%
Open Punctuation 43
 
0.9%
Decimal Number 33
 
0.7%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 652
 
13.6%
의 504
 
10.5%
과 304
 
6.3%
병 233
 
4.9%
내 108
 
2.3%
정 83
 
1.7%
료 80
 
1.7%
외 78
 
1.6%
성 77
 
1.6%
비 64
 
1.3%
Other values (311) 2609
54.4%
Decimal Number
ValueCountFrequency (%)
5 8
24.2%
3 8
24.2%
6 7
21.2%
1 4
12.1%
8 2
 
6.1%
9 2
 
6.1%
2 2
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
J 2
40.0%
U 1
20.0%
H 1
20.0%
S 1
20.0%
Space Separator
ValueCountFrequency (%)
54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4792
96.4%
Common 176
 
3.5%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 652
 
13.6%
의 504
 
10.5%
과 304
 
6.3%
병 233
 
4.9%
내 108
 
2.3%
정 83
 
1.7%
료 80
 
1.7%
외 78
 
1.6%
성 77
 
1.6%
비 64
 
1.3%
Other values (311) 2609
54.4%
Common
ValueCountFrequency (%)
54
30.7%
) 46
26.1%
( 43
24.4%
5 8
 
4.5%
3 8
 
4.5%
6 7
 
4.0%
1 4
 
2.3%
8 2
 
1.1%
9 2
 
1.1%
2 2
 
1.1%
Latin
ValueCountFrequency (%)
J 2
40.0%
U 1
20.0%
H 1
20.0%
S 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4792
96.4%
ASCII 181
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 652
 
13.6%
의 504
 
10.5%
과 304
 
6.3%
병 233
 
4.9%
내 108
 
2.3%
정 83
 
1.7%
료 80
 
1.7%
외 78
 
1.6%
성 77
 
1.6%
비 64
 
1.3%
Other values (311) 2609
54.4%
ASCII
ValueCountFrequency (%)
54
29.8%
) 46
25.4%
( 43
23.8%
5 8
 
4.4%
3 8
 
4.4%
6 7
 
3.9%
1 4
 
2.2%
8 2
 
1.1%
9 2
 
1.1%
J 2
 
1.1%
Other values (4) 5
 
2.8%

종별
Categorical

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
의원
382 
병원
122 
종합병원
89 
요양병원
 
35
<NA>
 
1

Length

Max length4
Median length2
Mean length2.3974563
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row종합병원
2nd row의원
3rd row병원
4th row병원
5th row병원

Common Values

ValueCountFrequency (%)
의원 382
60.7%
병원 122
 
19.4%
종합병원 89
 
14.1%
요양병원 35
 
5.6%
<NA> 1
 
0.2%

Length

2023-12-12T13:51:53.043522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:51:53.162800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의원 382
60.7%
병원 122
 
19.4%
종합병원 89
 
14.1%
요양병원 35
 
5.6%
na 1
 
0.2%

사업자번호
Text

Distinct626
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T13:51:53.438491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters7548
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

Unique623 ?
Unique (%)99.0%

Sample

1st row506-82-01629
2nd row611-90-10385
3rd row308-82-07903
4th row317-82-02746
5th row302-82-06546
ValueCountFrequency (%)
506-82-01629 2
 
0.3%
113-90-34073 2
 
0.3%
616-82-03749 2
 
0.3%
364-98-01327 1
 
0.2%
483-95-00652 1
 
0.2%
217-82-05370 1
 
0.2%
803-97-01640 1
 
0.2%
610-92-08158 1
 
0.2%
615-18-90143 1
 
0.2%
229-96-00375 1
 
0.2%
Other values (616) 616
97.9%
2023-12-12T13:51:53.768380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1258
16.7%
0 1092
14.5%
1 871
11.5%
2 800
10.6%
9 682
9.0%
8 535
7.1%
3 529
7.0%
6 500
 
6.6%
5 456
 
6.0%
4 441
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6290
83.3%
Dash Punctuation 1258
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1092
17.4%
1 871
13.8%
2 800
12.7%
9 682
10.8%
8 535
8.5%
3 529
8.4%
6 500
7.9%
5 456
7.2%
4 441
7.0%
7 384
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 1258
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7548
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1258
16.7%
0 1092
14.5%
1 871
11.5%
2 800
10.6%
9 682
9.0%
8 535
7.1%
3 529
7.0%
6 500
 
6.6%
5 456
 
6.0%
4 441
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1258
16.7%
0 1092
14.5%
1 871
11.5%
2 800
10.6%
9 682
9.0%
8 535
7.1%
3 529
7.0%
6 500
 
6.6%
5 456
 
6.0%
4 441
 
5.8%

최초계약일
Date

Distinct220
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum1987-04-01 00:00:00
Maximum2023-10-01 00:00:00
2023-12-12T13:51:53.892084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:54.010897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

우편번호
Text

Distinct597
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T13:51:54.293376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0317965
Min length5

Characters and Unicode

Total characters3165
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

Unique567 ?
Unique (%)90.1%

Sample

1st row37688
2nd row37313
3rd row33169
4th row28027
5th row28949
ValueCountFrequency (%)
59140 3
 
0.5%
57535 3
 
0.5%
32804 2
 
0.3%
50132 2
 
0.3%
32143 2
 
0.3%
12179 2
 
0.3%
37688 2
 
0.3%
63585 2
 
0.3%
02165 2
 
0.3%
17909 2
 
0.3%
Other values (587) 607
96.5%
2023-12-12T13:51:54.695340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 420
13.3%
2 393
12.4%
1 377
11.9%
3 370
11.7%
4 351
11.1%
0 323
10.2%
6 269
8.5%
7 249
7.9%
8 204
6.4%
9 199
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3155
99.7%
Dash Punctuation 10
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 420
13.3%
2 393
12.5%
1 377
11.9%
3 370
11.7%
4 351
11.1%
0 323
10.2%
6 269
8.5%
7 249
7.9%
8 204
6.5%
9 199
6.3%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3165
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 420
13.3%
2 393
12.4%
1 377
11.9%
3 370
11.7%
4 351
11.1%
0 323
10.2%
6 269
8.5%
7 249
7.9%
8 204
6.4%
9 199
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 420
13.3%
2 393
12.4%
1 377
11.9%
3 370
11.7%
4 351
11.1%
0 323
10.2%
6 269
8.5%
7 249
7.9%
8 204
6.4%
9 199
6.3%

주소
Text

Distinct229
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T13:51:55.014213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.5198728
Min length6

Characters and Unicode

Total characters4101
Distinct characters133
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)5.2%

Sample

1st row경북 포항시
2nd row경북 의성군
3rd row충남 부여군
4th row충북 괴산군
5th row충북 보은군
ValueCountFrequency (%)
경기도 97
 
7.7%
서울시 84
 
6.7%
전남 63
 
5.0%
경북 57
 
4.5%
경남 56
 
4.5%
강원도 46
 
3.7%
전북 41
 
3.3%
부산시 35
 
2.8%
충남 33
 
2.6%
충북 25
 
2.0%
Other values (213) 721
57.3%
2023-12-12T13:51:55.436029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
630
 
15.4%
시 468
 
11.4%
경 221
 
5.4%
구 217
 
5.3%
남 188
 
4.6%
군 182
 
4.4%
도 172
 
4.2%
북 139
 
3.4%
전 124
 
3.0%
서 120
 
2.9%
Other values (123) 1640
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3471
84.6%
Space Separator 630
 
15.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 468
 
13.5%
경 221
 
6.4%
구 217
 
6.3%
남 188
 
5.4%
군 182
 
5.2%
도 172
 
5.0%
북 139
 
4.0%
전 124
 
3.6%
서 120
 
3.5%
울 104
 
3.0%
Other values (122) 1536
44.3%
Space Separator
ValueCountFrequency (%)
630
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3471
84.6%
Common 630
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 468
 
13.5%
경 221
 
6.4%
구 217
 
6.3%
남 188
 
5.4%
군 182
 
5.2%
도 172
 
5.0%
북 139
 
4.0%
전 124
 
3.6%
서 120
 
3.5%
울 104
 
3.0%
Other values (122) 1536
44.3%
Common
ValueCountFrequency (%)
630
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3471
84.6%
ASCII 630
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
630
100.0%
Hangul
ValueCountFrequency (%)
시 468
 
13.5%
경 221
 
6.4%
구 217
 
6.3%
남 188
 
5.4%
군 182
 
5.2%
도 172
 
5.0%
북 139
 
4.0%
전 124
 
3.6%
서 120
 
3.5%
울 104
 
3.0%
Other values (122) 1536
44.3%

상세주소
Text

Distinct628
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T13:51:55.761883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length32
Mean length14.90938
Min length5

Characters and Unicode

Total characters9378
Distinct characters394
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique627 ?
Unique (%)99.7%

Sample

1st row북구 용흥로 36
2nd row안계면 안계길 171
3rd row부여읍 계백로 200
4th row괴산읍 임꺽정로 116
5th row보은읍 보은로 102
ValueCountFrequency (%)
2층 36
 
1.7%
3층 33
 
1.6%
중앙로 27
 
1.3%
4층 17
 
0.8%
5층 14
 
0.7%
5 8
 
0.4%
11 7
 
0.3%
1층 7
 
0.3%
10 7
 
0.3%
9 7
 
0.3%
Other values (1523) 1935
92.2%
2023-12-12T13:51:56.288436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1485
 
15.8%
로 567
 
6.0%
1 487
 
5.2%
2 320
 
3.4%
3 292
 
3.1%
동 258
 
2.8%
5 215
 
2.3%
) 198
 
2.1%
( 198
 
2.1%
0 182
 
1.9%
Other values (384) 5176
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5030
53.6%
Decimal Number 2245
23.9%
Space Separator 1485
 
15.8%
Close Punctuation 198
 
2.1%
Open Punctuation 198
 
2.1%
Other Punctuation 115
 
1.2%
Dash Punctuation 67
 
0.7%
Uppercase Letter 21
 
0.2%
Math Symbol 19
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 567
 
11.3%
동 258
 
5.1%
읍 180
 
3.6%
층 158
 
3.1%
원 138
 
2.7%
길 123
 
2.4%
대 119
 
2.4%
산 89
 
1.8%
의 85
 
1.7%
구 84
 
1.7%
Other values (354) 3229
64.2%
Uppercase Letter
ValueCountFrequency (%)
S 4
19.0%
B 4
19.0%
J 2
9.5%
A 2
9.5%
G 2
9.5%
I 1
 
4.8%
L 1
 
4.8%
X 1
 
4.8%
T 1
 
4.8%
C 1
 
4.8%
Other values (2) 2
9.5%
Decimal Number
ValueCountFrequency (%)
1 487
21.7%
2 320
14.3%
3 292
13.0%
5 215
9.6%
0 182
 
8.1%
4 168
 
7.5%
6 168
 
7.5%
7 151
 
6.7%
9 133
 
5.9%
8 129
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 109
94.8%
. 3
 
2.6%
· 3
 
2.6%
Space Separator
ValueCountFrequency (%)
1485
100.0%
Close Punctuation
ValueCountFrequency (%)
) 198
100.0%
Open Punctuation
ValueCountFrequency (%)
( 198
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5030
53.6%
Common 4327
46.1%
Latin 21
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 567
 
11.3%
동 258
 
5.1%
읍 180
 
3.6%
층 158
 
3.1%
원 138
 
2.7%
길 123
 
2.4%
대 119
 
2.4%
산 89
 
1.8%
의 85
 
1.7%
구 84
 
1.7%
Other values (354) 3229
64.2%
Common
ValueCountFrequency (%)
1485
34.3%
1 487
 
11.3%
2 320
 
7.4%
3 292
 
6.7%
5 215
 
5.0%
) 198
 
4.6%
( 198
 
4.6%
0 182
 
4.2%
4 168
 
3.9%
6 168
 
3.9%
Other values (8) 614
14.2%
Latin
ValueCountFrequency (%)
S 4
19.0%
B 4
19.0%
J 2
9.5%
A 2
9.5%
G 2
9.5%
I 1
 
4.8%
L 1
 
4.8%
X 1
 
4.8%
T 1
 
4.8%
C 1
 
4.8%
Other values (2) 2
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5030
53.6%
ASCII 4345
46.3%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1485
34.2%
1 487
 
11.2%
2 320
 
7.4%
3 292
 
6.7%
5 215
 
4.9%
) 198
 
4.6%
( 198
 
4.6%
0 182
 
4.2%
4 168
 
3.9%
6 168
 
3.9%
Other values (19) 632
14.5%
Hangul
ValueCountFrequency (%)
로 567
 
11.3%
동 258
 
5.1%
읍 180
 
3.6%
층 158
 
3.1%
원 138
 
2.7%
길 123
 
2.4%
대 119
 
2.4%
산 89
 
1.8%
의 85
 
1.7%
구 84
 
1.7%
Other values (354) 3229
64.2%
None
ValueCountFrequency (%)
· 3
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct620
Distinct (%)99.4%
Missing5
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean36.354148
Minimum32.2676
Maximum38.447513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-12T13:51:56.441097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.2676
5-th percentile34.724451
Q135.316791
median36.36035
Q337.483929
95-th percentile37.792419
Maximum38.447513
Range6.1799128
Interquartile range (IQR)2.1671381

Descriptive statistics

Standard deviation1.141371
Coefficient of variation (CV)0.031395894
Kurtosis-0.72234395
Mean36.354148
Median Absolute Deviation (MAD)1.0946541
Skewness-0.35230408
Sum22684.989
Variance1.3027277
MonotonicityNot monotonic
2023-12-12T13:51:56.570945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6587474 2
 
0.3%
36.8986377 2
 
0.3%
37.5467114 2
 
0.3%
36.0350941 2
 
0.3%
36.1852219 1
 
0.2%
35.21220024 1
 
0.2%
35.96796834 1
 
0.2%
37.64575094 1
 
0.2%
37.48346328 1
 
0.2%
36.17448877 1
 
0.2%
Other values (610) 610
97.0%
(Missing) 5
 
0.8%
ValueCountFrequency (%)
32.2676 1
0.2%
33.2488 1
0.2%
33.2523213 1
0.2%
33.2560963 1
0.2%
33.4138347 1
0.2%
33.4452709 1
0.2%
33.44549764 1
0.2%
33.44972751 1
0.2%
33.4670429 1
0.2%
33.48442499 1
0.2%
ValueCountFrequency (%)
38.4475128 1
0.2%
38.2164098 1
0.2%
38.20665514 1
0.2%
38.19508437 1
0.2%
38.1911274 1
0.2%
38.18955666 1
0.2%
38.1502529 1
0.2%
38.12876051 1
0.2%
38.1075314 1
0.2%
38.1045016 1
0.2%

경도
Real number (ℝ)

Distinct619
Distinct (%)99.2%
Missing5
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean127.61805
Minimum124.71827
Maximum130.89852
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-12T13:51:56.695609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124.71827
5-th percentile126.56395
Q1126.93286
median127.27798
Q3128.46055
95-th percentile129.17016
Maximum130.89852
Range6.1802498
Interquartile range (IQR)1.5276906

Descriptive statistics

Standard deviation0.89815965
Coefficient of variation (CV)0.0070378729
Kurtosis-0.66390193
Mean127.61805
Median Absolute Deviation (MAD)0.5026532
Skewness0.54191243
Sum79633.666
Variance0.80669076
MonotonicityNot monotonic
2023-12-12T13:51:56.879224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0635414 2
 
0.3%
126.7398 2
 
0.3%
126.6329937 2
 
0.3%
126.9328565 2
 
0.3%
129.3544868 2
 
0.3%
126.833862 1
 
0.2%
127.4648269 1
 
0.2%
129.4160865 1
 
0.2%
127.0333662 1
 
0.2%
126.9537656 1
 
0.2%
Other values (609) 609
96.8%
(Missing) 5
 
0.8%
ValueCountFrequency (%)
124.718271 1
0.2%
125.4458703 1
0.2%
125.9330008 1
0.2%
126.0466575 1
0.2%
126.2115923 1
0.2%
126.262921 1
0.2%
126.2652077 1
0.2%
126.3019893 1
0.2%
126.303575 1
0.2%
126.3136328 1
0.2%
ValueCountFrequency (%)
130.8985208 1
0.2%
129.4309036 1
0.2%
129.4282505 1
0.2%
129.4264937 1
0.2%
129.4160865 1
0.2%
129.4100665 1
0.2%
129.4023434 1
0.2%
129.3835139 1
0.2%
129.3803 1
0.2%
129.3717967 1
0.2%

Interactions

2023-12-12T13:51:50.455437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:49.684382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:50.081596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:50.590803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:49.812261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:50.212152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:50.728079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:49.944799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:51:50.322916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:51:56.969162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할기관기호종별위도경도
관할1.0000.9120.0950.8190.688
기관기호0.9121.0000.3370.7730.633
종별0.0950.3371.0000.1580.000
위도0.8190.7730.1581.0000.553
경도0.6880.6330.0000.5531.000
2023-12-12T13:51:57.051680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할종별
관할1.0000.061
종별0.0611.000
2023-12-12T13:51:57.133127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관기호위도경도관할종별
기관기호1.000-0.5150.2200.5760.219
위도-0.5151.000-0.1640.6130.094
경도0.220-0.1641.0000.4250.000
관할0.5760.6130.4251.0000.061
종별0.2190.0940.0000.0611.000

Missing values

2023-12-12T13:51:50.925861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:51:51.155630image/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.
2023-12-12T13:51:51.302673image/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

관할기관기호위탁병원명종별사업자번호최초계약일우편번호주소상세주소위도경도
0대구37100041포항의료원종합병원506-82-016291993-03-3137688경북 포항시북구 용흥로 3636.035094129.354487
1대구37336398삼성연합의원(의성)의원611-90-103852012-06-1437313경북 의성군안계면 안계길 17136.386302128.434615
2대전34201700건양대학교 부여병원병원308-82-079032003-02-0133169충남 부여군부여읍 계백로 20036.275721126.90107
3대전33200998괴산성모병원병원317-82-027462011-01-0328027충북 괴산군괴산읍 임꺽정로 11636.815414127.784238
4대전33201081정민의료재단 보은한양병원병원302-82-065462002-09-0128949충북 보은군보은읍 보은로 10236.483278127.718287
5대전33200726영동병원병원302-82-043442008-12-0529134충북 영동군영동읍 대학로 10636.185222127.781006
6대전34201645예산명지병원병원311-90-387842006-09-1132423충남 예산군예산읍 신례원로 2636.712916126.833862
7대전34201289예일병원병원312-91-878682008-11-2431174충남 천안시서북구 충무로 12936.793017127.121754
8대전34201297서해병원병원313-82-026522003-02-0133635충남 서천군서천읍 서천로 18436.08448126.687631
9대전33100233(의)건명의료재단 중앙제일병원종합병원301-90-241482002-03-0127832충북 진천군진천읍 중앙북로 3636.858312127.44062
관할기관기호위탁병원명종별사업자번호최초계약일우편번호주소상세주소위도경도
619인천31101488인천적십자병원종합병원131-82-009172003-03-1021935인천시 연수구원인재로 26337.418596126.688837
620대구37323865하나이비인후과의원의원513-90-893082023-08-2939225경북 구미시구미중앙로 11136.1278128.3345
621광주36329614정의원의원416-90-833192023-09-0159347전남 장흥군관산읍 관산로 92-634.5634126.9387
622인천31376771박현수정형외과의원의원122-35-280902023-10-0121416인천시 부평구수변로 8, 파워프라자 2층37.4872126.7398
623인천41362497손발척척정형외과의원의원390-92-004412023-10-0110113경기도 김포시양도로 23, 오성프라자 6차 5층37.6067126.7251
624중앙41387040평촌연세365내과의원의원364-98-013272023-09-0114072경기도 안양시동안구 평촌대로 217번길 27, 3~4층37.3903126.954
625중앙41387252다산이엠365의원의원639-18-019902023-09-0112249경기도 남양주시다산중앙로 82번길 78, 2~3층37.6197127.1633
626중앙41351134구리백내과의원의원527-91-001052023-09-0111932경기도 구리시검배로 42, 3~4층37.5975127.1436
627대구37283251좋은선린요양병원요양병원126-82-204162019-11-0137726경북 포항시북구 대신로 27 (대신동) 좋은선린요양병원36.046507129.366696
628부산38350289가온내과의원의원839-95-004382021-10-1551490경남 창원시성산구 가음로 88 (가음동)35.205527128.702992