Overview

Dataset statistics

Number of variables5
Number of observations101
Missing cells16
Missing cells (%)3.2%
Duplicate rows1
Duplicate rows (%)1.0%
Total size in memory4.1 KiB
Average record size in memory41.3 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description서울특별시 광진구 관내 건강검진기관(구강) 현황으로 병원명, 주소, 전화번호등 에 대한 정보( 또는 데이터)를 제공합니다.
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15052416/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (1.0%) duplicate rowsDuplicates
구분 is highly imbalanced (76.0%)Imbalance
검진기관명 has 4 (4.0%) missing valuesMissing
주소 has 4 (4.0%) missing valuesMissing
전화번호 has 4 (4.0%) missing valuesMissing
데이터기준일자 has 4 (4.0%) missing valuesMissing

Reproduction

Analysis started2024-03-14 17:48:27.377423
Analysis finished2024-03-14 17:48:28.721463
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size936.0 B
검진기관(구강)
97 
<NA>
 
4

Length

Max length8
Median length8
Mean length7.8415842
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row검진기관(구강)
2nd row검진기관(구강)
3rd row검진기관(구강)
4th row검진기관(구강)
5th row검진기관(구강)

Common Values

ValueCountFrequency (%)
검진기관(구강) 97
96.0%
<NA> 4
 
4.0%

Length

2024-03-15T02:48:28.968824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:48:29.310052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검진기관(구강 97
96.0%
na 4
 
4.0%

검진기관명
Text

MISSING 

Distinct97
Distinct (%)100.0%
Missing4
Missing (%)4.0%
Memory size936.0 B
2024-03-15T02:48:30.105127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.5876289
Min length5

Characters and Unicode

Total characters736
Distinct characters155
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)100.0%

Sample

1st row한도치과의원
2nd row소망치과의원
3rd row상아치과의원
4th row최종명치과의원
5th row김성수치과의원
ValueCountFrequency (%)
연세수치과의원 1
 
1.0%
서울앞선치과의원 1
 
1.0%
서울캐릭터치과의원 1
 
1.0%
극동치과의원 1
 
1.0%
나무치과의원 1
 
1.0%
좋은미소치과의원 1
 
1.0%
미소필치과의원 1
 
1.0%
연세안심치과의원 1
 
1.0%
봄날의미소치과의원 1
 
1.0%
미소인치과의원 1
 
1.0%
Other values (87) 87
89.7%
2024-03-15T02:48:31.301596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 99
 
13.5%
치 98
 
13.3%
과 98
 
13.3%
원 97
 
13.2%
서 16
 
2.2%
울 16
 
2.2%
이 13
 
1.8%
미 12
 
1.6%
트 11
 
1.5%
스 10
 
1.4%
Other values (145) 266
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 733
99.6%
Uppercase Letter 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 99
 
13.5%
치 98
 
13.4%
과 98
 
13.4%
원 97
 
13.2%
서 16
 
2.2%
울 16
 
2.2%
이 13
 
1.8%
미 12
 
1.6%
트 11
 
1.5%
스 10
 
1.4%
Other values (142) 263
35.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 733
99.6%
Common 2
 
0.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 99
 
13.5%
치 98
 
13.4%
과 98
 
13.4%
원 97
 
13.2%
서 16
 
2.2%
울 16
 
2.2%
이 13
 
1.8%
미 12
 
1.6%
트 11
 
1.5%
스 10
 
1.4%
Other values (142) 263
35.9%
Common
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%
Latin
ValueCountFrequency (%)
S 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 733
99.6%
ASCII 3
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 99
 
13.5%
치 98
 
13.4%
과 98
 
13.4%
원 97
 
13.2%
서 16
 
2.2%
울 16
 
2.2%
이 13
 
1.8%
미 12
 
1.6%
트 11
 
1.5%
스 10
 
1.4%
Other values (142) 263
35.9%
ASCII
ValueCountFrequency (%)
S 1
33.3%
) 1
33.3%
( 1
33.3%

주소
Text

MISSING 

Distinct97
Distinct (%)100.0%
Missing4
Missing (%)4.0%
Memory size936.0 B
2024-03-15T02:48:32.440109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length39
Mean length30.072165
Min length17

Characters and Unicode

Total characters2917
Distinct characters137
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

Unique97 ?
Unique (%)100.0%

Sample

1st row서울 광진구 구의동 55-14/21
2nd row서울특별시 광진구 아차산로 634 205호 (광장동, 대오빌딩)
3rd row서울특별시 광진구 용마산로 57 (중곡동)
4th row서울특별시 광진구 광나루로56길 32 302호 (구의동, 현대아파트2단지상가)
5th row서울특별시 광진구 천호대로 525, (중곡동)
ValueCountFrequency (%)
광진구 97
 
15.8%
서울특별시 89
 
14.5%
2층 38
 
6.2%
3층 23
 
3.7%
자양동 22
 
3.6%
중곡동 21
 
3.4%
구의동 16
 
2.6%
아차산로 16
 
2.6%
능동로 13
 
2.1%
천호대로 13
 
2.1%
Other values (183) 267
43.4%
2024-03-15T02:48:34.234472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
527
 
18.1%
광 121
 
4.1%
구 120
 
4.1%
동 119
 
4.1%
진 102
 
3.5%
서 97
 
3.3%
울 97
 
3.3%
시 90
 
3.1%
로 90
 
3.1%
2 90
 
3.1%
Other values (127) 1464
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1688
57.9%
Space Separator 527
 
18.1%
Decimal Number 461
 
15.8%
Close Punctuation 89
 
3.1%
Open Punctuation 89
 
3.1%
Other Punctuation 41
 
1.4%
Dash Punctuation 11
 
0.4%
Uppercase Letter 10
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 121
 
7.2%
구 120
 
7.1%
동 119
 
7.0%
진 102
 
6.0%
서 97
 
5.7%
울 97
 
5.7%
시 90
 
5.3%
로 90
 
5.3%
별 89
 
5.3%
특 89
 
5.3%
Other values (102) 674
39.9%
Decimal Number
ValueCountFrequency (%)
2 90
19.5%
3 72
15.6%
1 56
12.1%
5 55
11.9%
4 47
10.2%
6 38
8.2%
0 38
8.2%
9 25
 
5.4%
7 21
 
4.6%
8 19
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
A 3
30.0%
C 2
20.0%
S 1
 
10.0%
P 1
 
10.0%
L 1
 
10.0%
Z 1
 
10.0%
B 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 38
92.7%
. 2
 
4.9%
/ 1
 
2.4%
Space Separator
ValueCountFrequency (%)
527
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 89
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1688
57.9%
Common 1219
41.8%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 121
 
7.2%
구 120
 
7.1%
동 119
 
7.0%
진 102
 
6.0%
서 97
 
5.7%
울 97
 
5.7%
시 90
 
5.3%
로 90
 
5.3%
별 89
 
5.3%
특 89
 
5.3%
Other values (102) 674
39.9%
Common
ValueCountFrequency (%)
527
43.2%
2 90
 
7.4%
) 89
 
7.3%
( 89
 
7.3%
3 72
 
5.9%
1 56
 
4.6%
5 55
 
4.5%
4 47
 
3.9%
6 38
 
3.1%
, 38
 
3.1%
Other values (8) 118
 
9.7%
Latin
ValueCountFrequency (%)
A 3
30.0%
C 2
20.0%
S 1
 
10.0%
P 1
 
10.0%
L 1
 
10.0%
Z 1
 
10.0%
B 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1688
57.9%
ASCII 1229
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
527
42.9%
2 90
 
7.3%
) 89
 
7.2%
( 89
 
7.2%
3 72
 
5.9%
1 56
 
4.6%
5 55
 
4.5%
4 47
 
3.8%
6 38
 
3.1%
, 38
 
3.1%
Other values (15) 128
 
10.4%
Hangul
ValueCountFrequency (%)
광 121
 
7.2%
구 120
 
7.1%
동 119
 
7.0%
진 102
 
6.0%
서 97
 
5.7%
울 97
 
5.7%
시 90
 
5.3%
로 90
 
5.3%
별 89
 
5.3%
특 89
 
5.3%
Other values (102) 674
39.9%

전화번호
Text

MISSING 

Distinct97
Distinct (%)100.0%
Missing4
Missing (%)4.0%
Memory size936.0 B
2024-03-15T02:48:35.585100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.257732
Min length11

Characters and Unicode

Total characters1092
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

Unique97 ?
Unique (%)100.0%

Sample

1st row02-453-6607
2nd row02-3436-4513
3rd row02-455-0385
4th row02-458-2275
5th row02-464-8336
ValueCountFrequency (%)
02-2201-5536 1
 
1.0%
02-452-7522 1
 
1.0%
02-455-2875 1
 
1.0%
02-3437-2333 1
 
1.0%
02-452-2223 1
 
1.0%
02-6462-2828 1
 
1.0%
02-6482-2875 1
 
1.0%
02-452-2275 1
 
1.0%
02-3437-2828 1
 
1.0%
02-456-2204 1
 
1.0%
Other values (87) 87
89.7%
2024-03-15T02:48:37.235065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 230
21.1%
- 194
17.8%
0 141
12.9%
4 124
11.4%
5 99
9.1%
8 80
 
7.3%
7 68
 
6.2%
6 63
 
5.8%
3 42
 
3.8%
1 27
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 898
82.2%
Dash Punctuation 194
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 230
25.6%
0 141
15.7%
4 124
13.8%
5 99
11.0%
8 80
 
8.9%
7 68
 
7.6%
6 63
 
7.0%
3 42
 
4.7%
1 27
 
3.0%
9 24
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 194
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1092
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 230
21.1%
- 194
17.8%
0 141
12.9%
4 124
11.4%
5 99
9.1%
8 80
 
7.3%
7 68
 
6.2%
6 63
 
5.8%
3 42
 
3.8%
1 27
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1092
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 230
21.1%
- 194
17.8%
0 141
12.9%
4 124
11.4%
5 99
9.1%
8 80
 
7.3%
7 68
 
6.2%
6 63
 
5.8%
3 42
 
3.8%
1 27
 
2.5%

데이터기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)1.0%
Missing4
Missing (%)4.0%
Memory size936.0 B
Minimum2024-02-07 00:00:00
Maximum2024-02-07 00:00:00
2024-03-15T02:48:37.762586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:48:38.012347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-03-15T02:48:38.222615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
검진기관명주소전화번호
검진기관명1.0001.0001.000
주소1.0001.0001.000
전화번호1.0001.0001.000

Missing values

2024-03-15T02:48:27.903139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:48:28.232662image/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.
2024-03-15T02:48:28.539866image/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

구분검진기관명주소전화번호데이터기준일자
0검진기관(구강)한도치과의원서울 광진구 구의동 55-14/2102-453-66072024-02-07
1검진기관(구강)소망치과의원서울특별시 광진구 아차산로 634 205호 (광장동, 대오빌딩)02-3436-45132024-02-07
2검진기관(구강)상아치과의원서울특별시 광진구 용마산로 57 (중곡동)02-455-03852024-02-07
3검진기관(구강)최종명치과의원서울특별시 광진구 광나루로56길 32 302호 (구의동, 현대아파트2단지상가)02-458-22752024-02-07
4검진기관(구강)김성수치과의원서울특별시 광진구 천호대로 525, (중곡동)02-464-83362024-02-07
5검진기관(구강)박현수치과의원서울 광진구 중곡1동 241번지 34호 2층02-465-51112024-02-07
6검진기관(구강)우리들치과의원서울 광진구 군자동 478-5 중앙빌딩 302호02-464-28722024-02-07
7검진기관(구강)서울미소치과의원서울 광진구 구의3동 199번지1호 만택빌딩 2층02-452-97002024-02-07
8검진기관(구강)스타시티치과의원서울특별시 광진구 아차산로 244 3층 (자양동)02-462-82752024-02-07
9검진기관(구강)미소치과의원서울특별시 광진구 능동로 420 2층 (중곡동)02-3409-28792024-02-07
구분검진기관명주소전화번호데이터기준일자
91검진기관(구강)루트웰치과의원서울특별시 광진구 뚝섬로 533 3층 (자양동)02-2205-22752024-02-07
92검진기관(구강)라라치과의원서울특별시 광진구 동일로 116 2층 2호 (화양동)02-457-20072024-02-07
93검진기관(구강)연세나루치과의원서울특별시 광진구 아차산로 502 4층 403호 (광장동, 진넥스오딧세이)02-454-28042024-02-07
94검진기관(구강)서울미니플란트치과의원서울특별시 광진구 천호대로 653 5층 (중곡동)02-455-20802024-02-07
95검진기관(구강)헤이사랑치과의원서울특별시 광진구 천호대로 559 아스하임 4층 401호 (중곡동)02-2201-22752024-02-07
96검진기관(구강)군자플란트치과의원서울특별시 광진구 능동로 294 3층 (능동)02-466-01212024-02-07
97<NA><NA><NA><NA><NA>
98<NA><NA><NA><NA><NA>
99<NA><NA><NA><NA><NA>
100<NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

구분검진기관명주소전화번호데이터기준일자# duplicates
0<NA><NA><NA><NA><NA>4