Overview

Dataset statistics

Number of variables5
Number of observations1210
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory47.4 KiB
Average record size in memory40.1 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description서울특별시_송파구_의료기관에 대한 데이터로 종별, 의료기관명, 의료기관주소(도로명), 의료기관전화번호, 데이터기준일자 등에 항목으로 제공합니다.
Author서울특별시 송파구
URLhttps://www.data.go.kr/data/15052391/fileData.do

Alerts

데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2023-12-12 12:06:57.758623
Analysis finished2023-12-12 12:06:58.934093
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종별
Categorical

Distinct10
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
의원
584 
치과의원
329 
한의원
256 
병원
 
18
요양병원(일반요양병원)
 
11
Other values (5)
 
12

Length

Max length12
Median length10
Mean length2.8710744
Min length2

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
의원 584
48.3%
치과의원 329
27.2%
한의원 256
21.2%
병원 18
 
1.5%
요양병원(일반요양병원) 11
 
0.9%
한방병원 5
 
0.4%
치과병원 3
 
0.2%
종합병원 2
 
0.2%
정신병원 1
 
0.1%
요양병원(노인병원) 1
 
0.1%

Length

2023-12-12T21:06:59.024847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:06:59.206212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의원 584
48.3%
치과의원 329
27.2%
한의원 256
21.2%
병원 18
 
1.5%
요양병원(일반요양병원 11
 
0.9%
한방병원 5
 
0.4%
치과병원 3
 
0.2%
종합병원 2
 
0.2%
정신병원 1
 
0.1%
요양병원(노인병원 1
 
0.1%
Distinct1209
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2023-12-12T21:06:59.565213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length7.7
Min length3

Characters and Unicode

Total characters9317
Distinct characters447
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1208 ?
Unique (%)99.8%

Sample

1st row재단법인아산사회복지재단 서울아산병원
2nd row경찰병원
3rd row서울세계로병원
4th row새숨병원
5th row서재곤링커병원
ValueCountFrequency (%)
연세봄이비인후과의원,한의원 2
 
0.2%
한의원 2
 
0.2%
의료법인일맥의료재단 2
 
0.2%
이조은치과의원 1
 
0.1%
갤러리아치과의원 1
 
0.1%
우리가족치과의원 1
 
0.1%
그린치과의원 1
 
0.1%
서울아산병원 1
 
0.1%
재단법인아산사회복지재단 1
 
0.1%
윈스치과의원 1
 
0.1%
Other values (1211) 1211
98.9%
2023-12-12T21:07:00.173928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1286
 
13.8%
1227
 
13.2%
811
 
8.7%
348
 
3.7%
305
 
3.3%
178
 
1.9%
147
 
1.6%
121
 
1.3%
116
 
1.2%
114
 
1.2%
Other values (437) 4664
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9209
98.8%
Decimal Number 42
 
0.5%
Uppercase Letter 21
 
0.2%
Space Separator 14
 
0.2%
Other Punctuation 8
 
0.1%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%
Dash Punctuation 5
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1286
 
14.0%
1227
 
13.3%
811
 
8.8%
348
 
3.8%
305
 
3.3%
178
 
1.9%
147
 
1.6%
121
 
1.3%
116
 
1.3%
114
 
1.2%
Other values (408) 4556
49.5%
Uppercase Letter
ValueCountFrequency (%)
S 5
23.8%
E 2
 
9.5%
B 2
 
9.5%
W 2
 
9.5%
G 2
 
9.5%
M 2
 
9.5%
D 2
 
9.5%
J 1
 
4.8%
Y 1
 
4.8%
F 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
3 10
23.8%
5 8
19.0%
6 8
19.0%
2 7
16.7%
1 4
 
9.5%
0 3
 
7.1%
8 1
 
2.4%
4 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
, 3
37.5%
& 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
r 2
50.0%
n 1
25.0%
e 1
25.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9207
98.8%
Common 83
 
0.9%
Latin 25
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1286
 
14.0%
1227
 
13.3%
811
 
8.8%
348
 
3.8%
305
 
3.3%
178
 
1.9%
147
 
1.6%
121
 
1.3%
116
 
1.3%
114
 
1.2%
Other values (407) 4554
49.5%
Common
ValueCountFrequency (%)
14
16.9%
3 10
12.0%
5 8
9.6%
6 8
9.6%
2 7
8.4%
( 7
8.4%
) 7
8.4%
- 5
 
6.0%
. 4
 
4.8%
1 4
 
4.8%
Other values (5) 9
10.8%
Latin
ValueCountFrequency (%)
S 5
20.0%
E 2
 
8.0%
B 2
 
8.0%
W 2
 
8.0%
G 2
 
8.0%
M 2
 
8.0%
r 2
 
8.0%
D 2
 
8.0%
J 1
 
4.0%
n 1
 
4.0%
Other values (4) 4
16.0%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9207
98.8%
ASCII 108
 
1.2%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1286
 
14.0%
1227
 
13.3%
811
 
8.8%
348
 
3.8%
305
 
3.3%
178
 
1.9%
147
 
1.6%
121
 
1.3%
116
 
1.3%
114
 
1.2%
Other values (407) 4554
49.5%
ASCII
ValueCountFrequency (%)
14
13.0%
3 10
 
9.3%
5 8
 
7.4%
6 8
 
7.4%
2 7
 
6.5%
( 7
 
6.5%
) 7
 
6.5%
S 5
 
4.6%
- 5
 
4.6%
. 4
 
3.7%
Other values (19) 33
30.6%
CJK
ValueCountFrequency (%)
2
100.0%
Distinct1184
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2023-12-12T21:07:00.490583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length53
Mean length35.11405
Min length22

Characters and Unicode

Total characters42488
Distinct characters342
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1160 ?
Unique (%)95.9%

Sample

1st row서울특별시 송파구 올림픽로43길 88, 서울아산병원 (풍납동)
2nd row서울특별시 송파구 송이로 123, 국립경찰병원 (가락동)
3rd row서울특별시 송파구 위례서로 248, 지하1층, 5~12층 (거여동)
4th row서울특별시 송파구 정의로8길 4, KDG70타워 2,3,4층 (문정동)
5th row서울특별시 송파구 백제고분로 436 (송파동, 서재곤링커병원)
ValueCountFrequency (%)
서울특별시 1210
 
14.5%
송파구 1210
 
14.5%
2층 259
 
3.1%
잠실동 218
 
2.6%
올림픽로 188
 
2.3%
3층 163
 
2.0%
가락동 158
 
1.9%
송파대로 141
 
1.7%
문정동 137
 
1.6%
방이동 114
 
1.4%
Other values (1291) 4525
54.4%
2023-12-12T21:07:00.957207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7123
 
16.8%
, 1704
 
4.0%
1625
 
3.8%
1523
 
3.6%
1437
 
3.4%
1269
 
3.0%
2 1268
 
3.0%
1 1233
 
2.9%
1230
 
2.9%
1223
 
2.9%
Other values (332) 22853
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24206
57.0%
Space Separator 7123
 
16.8%
Decimal Number 6631
 
15.6%
Other Punctuation 1717
 
4.0%
Open Punctuation 1218
 
2.9%
Close Punctuation 1218
 
2.9%
Uppercase Letter 261
 
0.6%
Dash Punctuation 58
 
0.1%
Math Symbol 49
 
0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1625
 
6.7%
1523
 
6.3%
1437
 
5.9%
1269
 
5.2%
1230
 
5.1%
1223
 
5.1%
1217
 
5.0%
1210
 
5.0%
1210
 
5.0%
1210
 
5.0%
Other values (280) 11052
45.7%
Uppercase Letter
ValueCountFrequency (%)
A 80
30.7%
B 71
27.2%
C 20
 
7.7%
S 10
 
3.8%
D 10
 
3.8%
I 8
 
3.1%
N 8
 
3.1%
G 7
 
2.7%
T 6
 
2.3%
K 5
 
1.9%
Other values (12) 36
13.8%
Decimal Number
ValueCountFrequency (%)
2 1268
19.1%
1 1233
18.6%
3 880
13.3%
0 769
11.6%
4 718
10.8%
5 569
8.6%
6 379
 
5.7%
8 323
 
4.9%
7 258
 
3.9%
9 234
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 1704
99.2%
@ 5
 
0.3%
. 4
 
0.2%
? 1
 
0.1%
* 1
 
0.1%
/ 1
 
0.1%
& 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
t 1
16.7%
i 1
16.7%
u 1
16.7%
c 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 1217
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1217
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
7123
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Math Symbol
ValueCountFrequency (%)
~ 49
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24206
57.0%
Common 18015
42.4%
Latin 267
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1625
 
6.7%
1523
 
6.3%
1437
 
5.9%
1269
 
5.2%
1230
 
5.1%
1223
 
5.1%
1217
 
5.0%
1210
 
5.0%
1210
 
5.0%
1210
 
5.0%
Other values (280) 11052
45.7%
Latin
ValueCountFrequency (%)
A 80
30.0%
B 71
26.6%
C 20
 
7.5%
S 10
 
3.7%
D 10
 
3.7%
I 8
 
3.0%
N 8
 
3.0%
G 7
 
2.6%
T 6
 
2.2%
K 5
 
1.9%
Other values (17) 42
15.7%
Common
ValueCountFrequency (%)
7123
39.5%
, 1704
 
9.5%
2 1268
 
7.0%
1 1233
 
6.8%
( 1217
 
6.8%
) 1217
 
6.8%
3 880
 
4.9%
0 769
 
4.3%
4 718
 
4.0%
5 569
 
3.2%
Other values (15) 1317
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24206
57.0%
ASCII 18282
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7123
39.0%
, 1704
 
9.3%
2 1268
 
6.9%
1 1233
 
6.7%
( 1217
 
6.7%
) 1217
 
6.7%
3 880
 
4.8%
0 769
 
4.2%
4 718
 
3.9%
5 569
 
3.1%
Other values (42) 1584
 
8.7%
Hangul
ValueCountFrequency (%)
1625
 
6.7%
1523
 
6.3%
1437
 
5.9%
1269
 
5.2%
1230
 
5.1%
1223
 
5.1%
1217
 
5.0%
1210
 
5.0%
1210
 
5.0%
1210
 
5.0%
Other values (280) 11052
45.7%
Distinct1202
Distinct (%)99.5%
Missing2
Missing (%)0.2%
Memory size9.6 KiB
2023-12-12T21:07:01.272839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length11
Mean length11.255795
Min length9

Characters and Unicode

Total characters13597
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1196 ?
Unique (%)99.0%

Sample

1st row02-3010-3114
2nd row02-3400-1114
3rd row02-1670-9111
4th row02-449-7588
5th row02-2284-2001
ValueCountFrequency (%)
02-3445-3475 2
 
0.2%
02-6959-2075 2
 
0.2%
02-412-1175 2
 
0.2%
02-2202-7528 2
 
0.2%
02-408-0022 2
 
0.2%
02-443-7575 2
 
0.2%
02-2145-0028 1
 
0.1%
02-400-4701 1
 
0.1%
02-412-2288 1
 
0.1%
02-401-0275 1
 
0.1%
Other values (1197) 1197
98.7%
2023-12-12T21:07:01.817451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2413
17.7%
2 2409
17.7%
0 2375
17.5%
4 1418
10.4%
1 913
 
6.7%
5 886
 
6.5%
7 856
 
6.3%
8 715
 
5.3%
3 700
 
5.1%
9 451
 
3.3%
Other values (4) 461
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11171
82.2%
Dash Punctuation 2413
 
17.7%
Other Punctuation 6
 
< 0.1%
Space Separator 5
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2409
21.6%
0 2375
21.3%
4 1418
12.7%
1 913
 
8.2%
5 886
 
7.9%
7 856
 
7.7%
8 715
 
6.4%
3 700
 
6.3%
9 451
 
4.0%
6 448
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 2413
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13597
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2413
17.7%
2 2409
17.7%
0 2375
17.5%
4 1418
10.4%
1 913
 
6.7%
5 886
 
6.5%
7 856
 
6.3%
8 715
 
5.3%
3 700
 
5.1%
9 451
 
3.3%
Other values (4) 461
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13597
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2413
17.7%
2 2409
17.7%
0 2375
17.5%
4 1418
10.4%
1 913
 
6.7%
5 886
 
6.5%
7 856
 
6.3%
8 715
 
5.3%
3 700
 
5.1%
9 451
 
3.3%
Other values (4) 461
 
3.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
Minimum2021-09-10 00:00:00
Maximum2021-09-10 00:00:00
2023-12-12T21:07:01.966245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:02.109359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2023-12-12T21:06:58.740439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:06:58.878631image/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

종별의료기관명의료기관주소(도로명)의료기관전화번호데이터기준일자
0종합병원재단법인아산사회복지재단 서울아산병원서울특별시 송파구 올림픽로43길 88, 서울아산병원 (풍납동)02-3010-31142021-09-10
1종합병원경찰병원서울특별시 송파구 송이로 123, 국립경찰병원 (가락동)02-3400-11142021-09-10
2병원서울세계로병원서울특별시 송파구 위례서로 248, 지하1층, 5~12층 (거여동)02-1670-91112021-09-10
3병원새숨병원서울특별시 송파구 정의로8길 4, KDG70타워 2,3,4층 (문정동)02-449-75882021-09-10
4병원서재곤링커병원서울특별시 송파구 백제고분로 436 (송파동, 서재곤링커병원)02-2284-20012021-09-10
5병원민트병원서울특별시 송파구 정의로8길 7, 한스 (문정동)02-2088-30002021-09-10
6병원혜민안과병원서울특별시 송파구 중대로 122 (가락동)02-3012-18002021-09-10
7병원염창환병원서울특별시 송파구 오금로 296, 재정빌딩 지하1층~지상5층 (가락동)02-514-12492021-09-10
8병원서울석병원서울특별시 송파구 송이로 148 (가락동)02-403-75852021-09-10
9병원빠른병원서울특별시 송파구 백제고분로 405, 유니온테크송파빌딩 (송파동)02-423-82882021-09-10
종별의료기관명의료기관주소(도로명)의료기관전화번호데이터기준일자
1200한의원평강한의원서울특별시 송파구 위례광장로 136, 에비뉴상가D동 205~206호 (장지동, 위례아이파크)02-457-79402021-09-10
1201한의원김공수한의원서울특별시 송파구 석촌호수로 70, 건양빌딩 (잠실동)02-415-67062021-09-10
1202한의원강덕수한의원서울특별시 송파구 올림픽로 212, A동 212호 (잠실동, 갤러리아팰리스)02-416-14892021-09-10
1203한의원고경석한의원서울특별시 송파구 양재대로 1164, 홍일빌딩동 3층 1,2호 (오금동)02-408-69692021-09-10
1204한의원남해한의원서울특별시 송파구 오금로 251, 207호 (방이동, 한양A상가)02-412-08322021-09-10
1205한의원양서현한의원서울특별시 송파구 바람드리길 51 (풍납동)02-473-52252021-09-10
1206한의원이충섭한의원서울특별시 송파구 가락로 74, 2층 (석촌동, 송일상가)02-415-39592021-09-10
1207한의원경희한의원서울특별시 송파구 삼학사로19길 28 (삼전동)02-415-12772021-09-10
1208한의원세제한의원서울특별시 송파구 올림픽로 491, 세제빌딩 8층 (풍납동)02-486-85252021-09-10
1209한의원동양한의원서울특별시 송파구 석촌호수로 114 (잠실동)02-422-87632021-09-10