Overview

Dataset statistics

Number of variables8
Number of observations2961
Missing cells1485
Missing cells (%)6.3%
Duplicate rows5
Duplicate rows (%)0.2%
Total size in memory188.1 KiB
Average record size in memory65.0 B

Variable types

Text5
Categorical1
Numeric1
DateTime1

Dataset

Description전라남도 병의원 현황입니다. 시군별 (목포, 여수, 순천, 나주, 광양, 담양, 보성, 해남, 영암, 영광, 화순, 강진, 무안, 고흥, 함평, 장성, 장흥, 완도, 신안, 진도, 구례, 곡성) 종별(병원, 의원, 보건소, 치과, 한의원) 의료기관명 대표자 연락처 소재지 병상수 인허가일자
URLhttps://www.data.go.kr/data/15069181/fileData.do

Alerts

Dataset has 5 (0.2%) duplicate rowsDuplicates
종별 is highly imbalanced (51.6%)Imbalance
전화번호 has 233 (7.9%) missing valuesMissing
소재지_지번 has 524 (17.7%) missing valuesMissing
소재지_도로명 주소 has 709 (23.9%) missing valuesMissing
병상수 has 2642 (89.2%) zerosZeros

Reproduction

Analysis started2023-12-12 11:15:02.751305
Analysis finished2023-12-12 11:15:04.981719
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군
Text

Distinct51
Distinct (%)1.7%
Missing19
Missing (%)0.6%
Memory size23.3 KiB
2023-12-12T20:15:05.154028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length6.0183549
Min length1

Characters and Unicode

Total characters17706
Distinct characters45
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

Unique4 ?
Unique (%)0.1%

Sample

1st row전라남도 목포시 보건소
2nd row강진군
3rd row전라남도 여수시 보건소
4th row강진군
5th row강진군
ValueCountFrequency (%)
전라남도 974
19.9%
보건소 910
18.6%
여수시 498
10.2%
순천시 425
8.7%
목포시 407
8.3%
광양시 224
 
4.6%
나주시 166
 
3.4%
무안군 120
 
2.5%
영광군 101
 
2.1%
화순군 93
 
1.9%
Other values (22) 972
19.9%
2023-12-12T20:15:05.668736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1948
 
11.0%
시 1720
 
9.7%
군 1213
 
6.9%
도 1104
 
6.2%
남 1059
 
6.0%
보 1041
 
5.9%
건 974
 
5.5%
전 974
 
5.5%
라 974
 
5.5%
소 910
 
5.1%
Other values (35) 5789
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15758
89.0%
Space Separator 1948
 
11.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1720
 
10.9%
군 1213
 
7.7%
도 1104
 
7.0%
남 1059
 
6.7%
보 1041
 
6.6%
건 974
 
6.2%
전 974
 
6.2%
라 974
 
6.2%
소 910
 
5.8%
순 518
 
3.3%
Other values (34) 5271
33.4%
Space Separator
ValueCountFrequency (%)
1948
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15758
89.0%
Common 1948
 
11.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1720
 
10.9%
군 1213
 
7.7%
도 1104
 
7.0%
남 1059
 
6.7%
보 1041
 
6.6%
건 974
 
6.2%
전 974
 
6.2%
라 974
 
6.2%
소 910
 
5.8%
순 518
 
3.3%
Other values (34) 5271
33.4%
Common
ValueCountFrequency (%)
1948
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15758
89.0%
ASCII 1948
 
11.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1948
100.0%
Hangul
ValueCountFrequency (%)
시 1720
 
10.9%
군 1213
 
7.7%
도 1104
 
7.0%
남 1059
 
6.7%
보 1041
 
6.6%
건 974
 
6.2%
전 974
 
6.2%
라 974
 
6.2%
소 910
 
5.8%
순 518
 
3.3%
Other values (34) 5271
33.4%

종별
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
의원
1646 
치과의원
614 
한의원
592 
병원
 
37
요양병원
 
27
Other values (6)
 
45

Length

Max length4
Median length2
Mean length2.6616008
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의원
2nd row의원
3rd row치과의원
4th row의원
5th row한의원

Common Values

ValueCountFrequency (%)
의원 1646
55.6%
치과의원 614
 
20.7%
한의원 592
 
20.0%
병원 37
 
1.2%
요양병원 27
 
0.9%
부속의원 13
 
0.4%
한방병원 13
 
0.4%
<NA> 10
 
0.3%
조산원 5
 
0.2%
종합병원 2
 
0.1%

Length

2023-12-12T20:15:05.905328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의원 1646
55.6%
치과의원 614
 
20.7%
한의원 592
 
20.0%
병원 37
 
1.2%
요양병원 27
 
0.9%
부속의원 13
 
0.4%
한방병원 13
 
0.4%
na 10
 
0.3%
조산원 5
 
0.2%
종합병원 2
 
0.1%

의료기관명
Text

Distinct2233
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
2023-12-12T20:15:06.406712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length6.6349206
Min length3

Characters and Unicode

Total characters19646
Distinct characters449
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1895 ?
Unique (%)64.0%

Sample

1st row김비뇨기과의원
2nd row주메디컬
3rd row미치과의원
4th row김안과의원
5th row동명한의원
ValueCountFrequency (%)
의원 22
 
0.7%
원광한의원 20
 
0.6%
현대의원 18
 
0.6%
중앙의원 17
 
0.5%
성심의원 15
 
0.5%
소망의원 13
 
0.4%
하나의원 13
 
0.4%
한의원 12
 
0.4%
우리의원 11
 
0.4%
한국의원 11
 
0.4%
Other values (2284) 2947
95.1%
2023-12-12T20:15:07.276506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 3010
 
15.3%
원 2984
 
15.2%
과 1398
 
7.1%
한 797
 
4.1%
치 630
 
3.2%
정 243
 
1.2%
이 229
 
1.2%
성 191
 
1.0%
인 187
 
1.0%
소 171
 
0.9%
Other values (439) 9806
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19417
98.8%
Space Separator 138
 
0.7%
Decimal Number 39
 
0.2%
Uppercase Letter 18
 
0.1%
Close Punctuation 11
 
0.1%
Open Punctuation 10
 
0.1%
Lowercase Letter 7
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 3010
 
15.5%
원 2984
 
15.4%
과 1398
 
7.2%
한 797
 
4.1%
치 630
 
3.2%
정 243
 
1.3%
이 229
 
1.2%
성 191
 
1.0%
인 187
 
1.0%
소 171
 
0.9%
Other values (412) 9577
49.3%
Uppercase Letter
ValueCountFrequency (%)
S 3
16.7%
O 2
11.1%
B 2
11.1%
G 2
11.1%
K 2
11.1%
N 2
11.1%
E 1
 
5.6%
I 1
 
5.6%
Y 1
 
5.6%
A 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
3 9
23.1%
6 9
23.1%
5 9
23.1%
2 5
12.8%
1 5
12.8%
7 1
 
2.6%
9 1
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 6
85.7%
r 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
& 1
50.0%
Space Separator
ValueCountFrequency (%)
138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19418
98.8%
Common 203
 
1.0%
Latin 25
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 3010
 
15.5%
원 2984
 
15.4%
과 1398
 
7.2%
한 797
 
4.1%
치 630
 
3.2%
정 243
 
1.3%
이 229
 
1.2%
성 191
 
1.0%
인 187
 
1.0%
소 171
 
0.9%
Other values (413) 9578
49.3%
Common
ValueCountFrequency (%)
138
68.0%
) 11
 
5.4%
( 10
 
4.9%
3 9
 
4.4%
6 9
 
4.4%
5 9
 
4.4%
2 5
 
2.5%
1 5
 
2.5%
- 3
 
1.5%
7 1
 
0.5%
Other values (3) 3
 
1.5%
Latin
ValueCountFrequency (%)
e 6
24.0%
S 3
12.0%
O 2
 
8.0%
B 2
 
8.0%
G 2
 
8.0%
K 2
 
8.0%
N 2
 
8.0%
E 1
 
4.0%
I 1
 
4.0%
Y 1
 
4.0%
Other values (3) 3
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19417
98.8%
ASCII 228
 
1.2%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 3010
 
15.5%
원 2984
 
15.4%
과 1398
 
7.2%
한 797
 
4.1%
치 630
 
3.2%
정 243
 
1.3%
이 229
 
1.2%
성 191
 
1.0%
인 187
 
1.0%
소 171
 
0.9%
Other values (412) 9577
49.3%
ASCII
ValueCountFrequency (%)
138
60.5%
) 11
 
4.8%
( 10
 
4.4%
3 9
 
3.9%
6 9
 
3.9%
5 9
 
3.9%
e 6
 
2.6%
2 5
 
2.2%
1 5
 
2.2%
S 3
 
1.3%
Other values (16) 23
 
10.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

전화번호
Text

MISSING 

Distinct2348
Distinct (%)86.1%
Missing233
Missing (%)7.9%
Memory size23.3 KiB
2023-12-12T20:15:07.783012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.018695
Min length11

Characters and Unicode

Total characters32787
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2093 ?
Unique (%)76.7%

Sample

1st row061-244-0942
2nd row061-691-0350
3rd row061-432-1532
4th row061-434-3186
5th row061-433-3819
ValueCountFrequency (%)
010-0000-0000 50
 
1.8%
061-281-2800 5
 
0.2%
010-000-0000 5
 
0.2%
061-281-7588 5
 
0.2%
061-842-7500 4
 
0.1%
061-394-9200 4
 
0.1%
061-271-7583 4
 
0.1%
061-277-8600 4
 
0.1%
061-432-1100 4
 
0.1%
061-393-7582 4
 
0.1%
Other values (2340) 2641
96.7%
2023-12-12T20:15:08.537288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 5449
16.6%
0 5037
15.4%
6 4002
12.2%
1 3951
12.1%
7 2780
8.5%
2 2615
8.0%
5 2524
7.7%
3 2200
6.7%
8 1935
 
5.9%
4 1416
 
4.3%
Other values (3) 878
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27334
83.4%
Dash Punctuation 5449
 
16.6%
Other Punctuation 2
 
< 0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5037
18.4%
6 4002
14.6%
1 3951
14.5%
7 2780
10.2%
2 2615
9.6%
5 2524
9.2%
3 2200
8.0%
8 1935
 
7.1%
4 1416
 
5.2%
9 874
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 5449
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32787
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 5449
16.6%
0 5037
15.4%
6 4002
12.2%
1 3951
12.1%
7 2780
8.5%
2 2615
8.0%
5 2524
7.7%
3 2200
6.7%
8 1935
 
5.9%
4 1416
 
4.3%
Other values (3) 878
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32787
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 5449
16.6%
0 5037
15.4%
6 4002
12.2%
1 3951
12.1%
7 2780
8.5%
2 2615
8.0%
5 2524
7.7%
3 2200
6.7%
8 1935
 
5.9%
4 1416
 
4.3%
Other values (3) 878
 
2.7%

소재지_지번
Text

MISSING 

Distinct2062
Distinct (%)84.6%
Missing524
Missing (%)17.7%
Memory size23.3 KiB
2023-12-12T20:15:09.047569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length22.522364
Min length6

Characters and Unicode

Total characters54887
Distinct characters313
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1803 ?
Unique (%)74.0%

Sample

1st row전라남도 목포시 명륜동 17번지
2nd row전남 여수시 신기동 109-7
3rd row전라남도 강진군 강진읍 남성리 47-34
4th row전라남도 강진군 강진읍 동성리 325
5th row전라남도목포시무안동 13-15
ValueCountFrequency (%)
전라남도 2256
 
18.0%
여수시 406
 
3.2%
목포시 345
 
2.8%
순천시 336
 
2.7%
1호 251
 
2.0%
광양시 223
 
1.8%
2층 209
 
1.7%
2호 162
 
1.3%
나주시 130
 
1.0%
3호 120
 
1.0%
Other values (2041) 8073
64.5%
2023-12-12T20:15:09.837043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10074
 
18.4%
남 2640
 
4.8%
도 2464
 
4.5%
전 2406
 
4.4%
1 2347
 
4.3%
라 2292
 
4.2%
지 2014
 
3.7%
번 1940
 
3.5%
호 1590
 
2.9%
2 1570
 
2.9%
Other values (303) 25550
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33482
61.0%
Decimal Number 10403
 
19.0%
Space Separator 10074
 
18.4%
Dash Punctuation 419
 
0.8%
Open Punctuation 179
 
0.3%
Close Punctuation 172
 
0.3%
Other Punctuation 125
 
0.2%
Uppercase Letter 18
 
< 0.1%
Math Symbol 8
 
< 0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 2640
 
7.9%
도 2464
 
7.4%
전 2406
 
7.2%
라 2292
 
6.8%
지 2014
 
6.0%
번 1940
 
5.8%
호 1590
 
4.7%
시 1467
 
4.4%
동 1420
 
4.2%
리 1174
 
3.5%
Other values (270) 14075
42.0%
Decimal Number
ValueCountFrequency (%)
1 2347
22.6%
2 1570
15.1%
3 1057
10.2%
4 891
 
8.6%
5 838
 
8.1%
8 813
 
7.8%
6 792
 
7.6%
7 786
 
7.6%
9 678
 
6.5%
0 631
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
S 5
27.8%
M 3
16.7%
B 3
16.7%
A 3
16.7%
G 2
 
11.1%
L 1
 
5.6%
D 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
a 2
28.6%
p 1
14.3%
c 1
14.3%
e 1
14.3%
n 1
14.3%
o 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 114
91.2%
@ 5
 
4.0%
. 5
 
4.0%
/ 1
 
0.8%
Math Symbol
ValueCountFrequency (%)
~ 7
87.5%
～ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
10074
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 419
100.0%
Open Punctuation
ValueCountFrequency (%)
( 179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33482
61.0%
Common 21380
39.0%
Latin 25
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 2640
 
7.9%
도 2464
 
7.4%
전 2406
 
7.2%
라 2292
 
6.8%
지 2014
 
6.0%
번 1940
 
5.8%
호 1590
 
4.7%
시 1467
 
4.4%
동 1420
 
4.2%
리 1174
 
3.5%
Other values (270) 14075
42.0%
Common
ValueCountFrequency (%)
10074
47.1%
1 2347
 
11.0%
2 1570
 
7.3%
3 1057
 
4.9%
4 891
 
4.2%
5 838
 
3.9%
8 813
 
3.8%
6 792
 
3.7%
7 786
 
3.7%
9 678
 
3.2%
Other values (10) 1534
 
7.2%
Latin
ValueCountFrequency (%)
S 5
20.0%
M 3
12.0%
B 3
12.0%
A 3
12.0%
a 2
 
8.0%
G 2
 
8.0%
L 1
 
4.0%
D 1
 
4.0%
p 1
 
4.0%
c 1
 
4.0%
Other values (3) 3
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33482
61.0%
ASCII 21404
39.0%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10074
47.1%
1 2347
 
11.0%
2 1570
 
7.3%
3 1057
 
4.9%
4 891
 
4.2%
5 838
 
3.9%
8 813
 
3.8%
6 792
 
3.7%
7 786
 
3.7%
9 678
 
3.2%
Other values (22) 1558
 
7.3%
Hangul
ValueCountFrequency (%)
남 2640
 
7.9%
도 2464
 
7.4%
전 2406
 
7.2%
라 2292
 
6.8%
지 2014
 
6.0%
번 1940
 
5.8%
호 1590
 
4.7%
시 1467
 
4.4%
동 1420
 
4.2%
리 1174
 
3.5%
Other values (270) 14075
42.0%
None
ValueCountFrequency (%)
～ 1
100.0%

소재지_도로명 주소
Text

MISSING 

Distinct1997
Distinct (%)88.7%
Missing709
Missing (%)23.9%
Memory size23.3 KiB
2023-12-12T20:15:10.419609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length46
Mean length23.945382
Min length17

Characters and Unicode

Total characters53925
Distinct characters374
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1790 ?
Unique (%)79.5%

Sample

1st row전라남도 목포시 노적봉길 6 (명륜동)
2nd row전라남도 강진군 강진읍 평동2길 30, 2층 202호 (지스퀘어2층)
3rd row전라남도 강진군 강진읍 보은로2길 33
4th row전라남도 강진군 마량면 마량4길 11, 1층
5th row전라남도 강진군 강진읍 영랑로 36
ValueCountFrequency (%)
전라남도 2252
 
18.1%
2층 390
 
3.1%
순천시 340
 
2.7%
여수시 335
 
2.7%
목포시 304
 
2.4%
광양시 201
 
1.6%
나주시 146
 
1.2%
중앙로 128
 
1.0%
3층 124
 
1.0%
조례동 107
 
0.9%
Other values (1802) 8146
65.3%
2023-12-12T20:15:11.262750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10221
 
19.0%
남 2582
 
4.8%
도 2471
 
4.6%
전 2286
 
4.2%
라 2283
 
4.2%
로 1714
 
3.2%
1 1711
 
3.2%
2 1428
 
2.6%
시 1387
 
2.6%
동 1317
 
2.4%
Other values (364) 26525
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32198
59.7%
Space Separator 10221
 
19.0%
Decimal Number 7551
 
14.0%
Close Punctuation 1200
 
2.2%
Open Punctuation 1199
 
2.2%
Other Punctuation 1075
 
2.0%
Dash Punctuation 420
 
0.8%
Uppercase Letter 29
 
0.1%
Math Symbol 26
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 2582
 
8.0%
도 2471
 
7.7%
전 2286
 
7.1%
라 2283
 
7.1%
로 1714
 
5.3%
시 1387
 
4.3%
동 1317
 
4.1%
군 935
 
2.9%
층 811
 
2.5%
읍 746
 
2.3%
Other values (328) 15666
48.7%
Uppercase Letter
ValueCountFrequency (%)
A 8
27.6%
S 4
13.8%
M 3
 
10.3%
L 3
 
10.3%
G 3
 
10.3%
B 2
 
6.9%
E 2
 
6.9%
D 1
 
3.4%
P 1
 
3.4%
N 1
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 1711
22.7%
2 1428
18.9%
3 908
12.0%
4 633
 
8.4%
5 569
 
7.5%
0 509
 
6.7%
6 494
 
6.5%
7 467
 
6.2%
8 429
 
5.7%
9 403
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
p 1
16.7%
c 1
16.7%
s 1
16.7%
e 1
16.7%
n 1
16.7%
o 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 1067
99.3%
. 5
 
0.5%
@ 2
 
0.2%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
10221
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1200
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1199
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 420
100.0%
Math Symbol
ValueCountFrequency (%)
~ 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32198
59.7%
Common 21692
40.2%
Latin 35
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 2582
 
8.0%
도 2471
 
7.7%
전 2286
 
7.1%
라 2283
 
7.1%
로 1714
 
5.3%
시 1387
 
4.3%
동 1317
 
4.1%
군 935
 
2.9%
층 811
 
2.5%
읍 746
 
2.3%
Other values (328) 15666
48.7%
Common
ValueCountFrequency (%)
10221
47.1%
1 1711
 
7.9%
2 1428
 
6.6%
) 1200
 
5.5%
( 1199
 
5.5%
, 1067
 
4.9%
3 908
 
4.2%
4 633
 
2.9%
5 569
 
2.6%
0 509
 
2.3%
Other values (9) 2247
 
10.4%
Latin
ValueCountFrequency (%)
A 8
22.9%
S 4
11.4%
M 3
 
8.6%
L 3
 
8.6%
G 3
 
8.6%
B 2
 
5.7%
E 2
 
5.7%
p 1
 
2.9%
c 1
 
2.9%
D 1
 
2.9%
Other values (7) 7
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32198
59.7%
ASCII 21727
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10221
47.0%
1 1711
 
7.9%
2 1428
 
6.6%
) 1200
 
5.5%
( 1199
 
5.5%
, 1067
 
4.9%
3 908
 
4.2%
4 633
 
2.9%
5 569
 
2.6%
0 509
 
2.3%
Other values (26) 2282
 
10.5%
Hangul
ValueCountFrequency (%)
남 2582
 
8.0%
도 2471
 
7.7%
전 2286
 
7.1%
라 2283
 
7.1%
로 1714
 
5.3%
시 1387
 
4.3%
동 1317
 
4.1%
군 935
 
2.9%
층 811
 
2.5%
읍 746
 
2.3%
Other values (328) 15666
48.7%

병상수
Real number (ℝ)

ZEROS 

Distinct91
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8257345
Minimum0
Maximum496
Zeros2642
Zeros (%)89.2%
Negative0
Negative (%)0.0%
Memory size26.2 KiB
2023-12-12T20:15:11.494246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile28
Maximum496
Range496
Interquartile range (IQR)0

Descriptive statistics

Standard deviation25.195788
Coefficient of variation (CV)5.2211301
Kurtosis126.61956
Mean4.8257345
Median Absolute Deviation (MAD)0
Skewness9.7598067
Sum14289
Variance634.82773
MonotonicityNot monotonic
2023-12-12T20:15:11.732798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2642
89.2%
29 61
 
2.1%
2 16
 
0.5%
1 16
 
0.5%
27 15
 
0.5%
28 14
 
0.5%
23 9
 
0.3%
25 9
 
0.3%
4 9
 
0.3%
26 9
 
0.3%
Other values (81) 161
 
5.4%
ValueCountFrequency (%)
0 2642
89.2%
1 16
 
0.5%
2 16
 
0.5%
3 6
 
0.2%
4 9
 
0.3%
5 4
 
0.1%
6 6
 
0.2%
7 2
 
0.1%
8 5
 
0.2%
9 4
 
0.1%
ValueCountFrequency (%)
496 1
 
< 0.1%
418 1
 
< 0.1%
397 1
 
< 0.1%
299 1
 
< 0.1%
270 1
 
< 0.1%
264 2
0.1%
224 1
 
< 0.1%
202 1
 
< 0.1%
200 3
0.1%
199 2
0.1%

인허가일자
Date

Distinct2318
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size23.3 KiB
Minimum1900-01-01 00:00:00
Maximum2020-08-14 00:00:00
2023-12-12T20:15:12.005689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:15:12.267564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T20:15:04.110945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:15:12.437608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군종별병상수
시군1.0000.3040.193
종별0.3041.0000.627
병상수0.1930.6271.000
2023-12-12T20:15:12.598914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
병상수종별
병상수1.0000.346
종별0.3461.000

Missing values

2023-12-12T20:15:04.356775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:15:04.625713image/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.
2023-12-12T20:15:04.859140image/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

시군종별의료기관명전화번호소재지_지번소재지_도로명 주소병상수인허가일자
0전라남도 목포시 보건소의원김비뇨기과의원061-244-0942전라남도 목포시 명륜동 17번지전라남도 목포시 노적봉길 6 (명륜동)01973-05-01
1강진군의원주메디컬<NA><NA><NA>02014-04-15
2전라남도 여수시 보건소치과의원미치과의원061-691-0350전남 여수시 신기동 109-7<NA>01990-04-21
3강진군의원김안과의원061-432-1532<NA>전라남도 강진군 강진읍 평동2길 30, 2층 202호 (지스퀘어2층)02013-10-01
4강진군한의원동명한의원061-434-3186전라남도 강진군 강진읍 남성리 47-34전라남도 강진군 강진읍 보은로2길 3301996-02-01
5전라남도 강진군 보건소의원강진의원061-433-3819전라남도 강진군 강진읍 동성리 325<NA>02002-01-04
6전라남도 목포시 보건소한의원백제한의원061-242-5501전라남도목포시무안동 13-15<NA>01985-05-04
7전라남도 목포시 보건소의원경원치과의원061-281-2737전라남도목포시상동 867번지<NA>01987-05-02
8전라남도 여수시 보건소의원동인의원061-663-3415전라남도 여수시 충무동 550<NA>01975-06-11
9강진군의원마량의원061-434-9933전라남도 강진군 마량면 마량리 987번지 43호 마량공용버스터미널전라남도 강진군 마량면 마량4길 11, 1층02017-11-06
시군종별의료기관명전화번호소재지_지번소재지_도로명 주소병상수인허가일자
2951화순군의원예닮의원061-371-2235전라남도 화순군 화순읍 만연리 242번지 4호전라남도 화순군 화순읍 광덕로 185, 동인빌딩 1동 3층02018-06-18
2952화순군의원한양 미 의원061-371-0016<NA>전라남도 화순군 화순읍 자치샘로 36, 3층02017-07-27
2953화순군의원사평제일의원061-371-6611<NA>전라남도 화순군 남면 사평길 1702017-09-28
2954화순군한의원능주한의원061-371-7501전라남도 화순군 능주면 관영리 89번지 1호전라남도 화순군 능주면 죽수길 9402002-03-19
2955화순군한의원조영복한의원061-371-7510전라남도 화순군 화순읍 만연리 241번지 3호 숙인빌딩전라남도 화순군 화순읍 광덕로 177, 숙인빌딩02001-10-10
2956화순군치과의원더바른치과의원061-371-7582전라남도 화순군 화순읍 삼천리 630번지 2호전라남도 화순군 화순읍 칠충로 12302019-05-08
2957화순군의원푸른소아청소년과의원061-372-1122<NA>전라남도 화순군 화순읍 중앙로 9802016-02-03
2958화순군의원차산부인과의원061-371-2100전라남도 화순군 화순읍 만연리 240번지 8호전라남도 화순군 화순읍 중앙로 8902007-01-15
2959화순군치과의원한양화이트 치과의원061-371-2727전라남도 화순군 화순읍 향청리 85번지 2호전라남도 화순군 화순읍 자치샘로 36, 4층02020-04-10
2960화순군한의원인성한의원061-373-2288전라남도 화순군 화순읍 교리 222번지 1호전라남도 화순군 화순읍 도서관길 2301988-12-22

Duplicate rows

Most frequently occurring

시군종별의료기관명전화번호소재지_지번소재지_도로명 주소병상수인허가일자# duplicates
0무안군한의원원광한의원061-454-1075<NA>전라남도 무안군 무안읍 무안중앙로 23, 1층02010-04-302
1전라남도 강진군 보건소의원우리의원019-000-0000전라남도 강진군 마량면 마량리 987번지 43호<NA>02009-09-072
2전라남도 강진군 보건소의원작천한국의원061-432-1100전라남도 강진군 작천면 평리 172번지 28호<NA>02009-04-062
3전라남도 보성군 보건소의원미래의원061-858-9000전라남도 보성군 벌교읍 벌교리 889번지 1호<NA>292010-01-192
4전라남도 여수시 보건소의원밝은안과의원<NA>전라남도 여수시 학동 11번지 12호<NA>02004-04-232