Overview

Dataset statistics

Number of variables9
Number of observations208
Missing cells81
Missing cells (%)4.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.4 KiB
Average record size in memory75.6 B

Variable types

Numeric3
Text5
Categorical1

Dataset

Description관리번호,병의원 이름,주소1,주소2,도로명주소1,도로명주소2,우편번호1,우편번호2,자치구 이름
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15508/S/1/datasetView.do

Alerts

도로명주소1 has 30 (14.4%) missing valuesMissing
도로명주소2 has 30 (14.4%) missing valuesMissing
우편번호2 has 21 (10.1%) missing valuesMissing
관리번호 has unique valuesUnique
병의원 이름 has unique valuesUnique

Reproduction

Analysis started2024-05-18 06:04:09.389451
Analysis finished2024-05-18 06:04:14.090270
Duration4.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

UNIQUE 

Distinct208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4251.2212
Minimum201
Maximum11743
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-18T15:04:14.304516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201
5-th percentile267.05
Q11211
median4033
Q35083.25
95-th percentile11196
Maximum11743
Range11542
Interquartile range (IQR)3872.25

Descriptive statistics

Standard deviation3338.72
Coefficient of variation (CV)0.78535552
Kurtosis-0.12623269
Mean4251.2212
Median Absolute Deviation (MAD)1971
Skewness0.78838843
Sum884254
Variance11147051
MonotonicityNot monotonic
2024-05-18T15:04:14.781753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441 1
 
0.5%
4723 1
 
0.5%
3943 1
 
0.5%
228 1
 
0.5%
643 1
 
0.5%
317 1
 
0.5%
314 1
 
0.5%
290 1
 
0.5%
504 1
 
0.5%
258 1
 
0.5%
Other values (198) 198
95.2%
ValueCountFrequency (%)
201 1
0.5%
228 1
0.5%
232 1
0.5%
233 1
0.5%
234 1
0.5%
239 1
0.5%
246 1
0.5%
251 1
0.5%
257 1
0.5%
258 1
0.5%
ValueCountFrequency (%)
11743 1
0.5%
11723 1
0.5%
11664 1
0.5%
11663 1
0.5%
11647 1
0.5%
11646 1
0.5%
11643 1
0.5%
11623 1
0.5%
11463 1
0.5%
11306 1
0.5%

병의원 이름
Text

UNIQUE 

Distinct208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-18T15:04:15.540043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length6.4807692
Min length3

Characters and Unicode

Total characters1348
Distinct characters196
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

Unique208 ?
Unique (%)100.0%

Sample

1st row김영재내과의원
2nd row박철수내과의원
3rd row최재득내과의원
4th row협동의원
5th row연세가정의학과의원
ValueCountFrequency (%)
김영재내과의원 1
 
0.5%
박철수내과의원 1
 
0.5%
북부성모의원 1
 
0.5%
정다운가정의학과 1
 
0.5%
연세곰돌이소아과 1
 
0.5%
차내과 1
 
0.5%
백제열린의원 1
 
0.5%
프렌닥터내과 1
 
0.5%
정연탁의원 1
 
0.5%
소망내과의원 1
 
0.5%
Other values (198) 198
95.2%
2024-05-18T15:04:16.834920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 171
 
12.7%
과 151
 
11.2%
원 151
 
11.2%
내 76
 
5.6%
정 44
 
3.3%
안 42
 
3.1%
가 31
 
2.3%
연 27
 
2.0%
세 26
 
1.9%
서 23
 
1.7%
Other values (186) 606
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1344
99.7%
Uppercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 171
 
12.7%
과 151
 
11.2%
원 151
 
11.2%
내 76
 
5.7%
정 44
 
3.3%
안 42
 
3.1%
가 31
 
2.3%
연 27
 
2.0%
세 26
 
1.9%
서 23
 
1.7%
Other values (183) 602
44.8%
Uppercase Letter
ValueCountFrequency (%)
H 2
50.0%
W 1
25.0%
J 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1344
99.7%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 171
 
12.7%
과 151
 
11.2%
원 151
 
11.2%
내 76
 
5.7%
정 44
 
3.3%
안 42
 
3.1%
가 31
 
2.3%
연 27
 
2.0%
세 26
 
1.9%
서 23
 
1.7%
Other values (183) 602
44.8%
Latin
ValueCountFrequency (%)
H 2
50.0%
W 1
25.0%
J 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1344
99.7%
ASCII 4
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 171
 
12.7%
과 151
 
11.2%
원 151
 
11.2%
내 76
 
5.7%
정 44
 
3.3%
안 42
 
3.1%
가 31
 
2.3%
연 27
 
2.0%
세 26
 
1.9%
서 23
 
1.7%
Other values (183) 602
44.8%
ASCII
ValueCountFrequency (%)
H 2
50.0%
W 1
25.0%
J 1
25.0%

주소1
Text

Distinct197
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-18T15:04:17.861426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length32
Mean length18.480769
Min length11

Characters and Unicode

Total characters3844
Distinct characters165
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

Unique187 ?
Unique (%)89.9%

Sample

1st row서울 강북구 수유1동 50~93
2nd row서울 구로구 개봉3동 374~403
3rd row서울특별시 서초구 방배동 852-20
4th row서울특별시 구로구 가리봉동 25-64
5th row서울특별시 성북구 정릉동 779-1
ValueCountFrequency (%)
서울특별시 179
 
22.1%
강북구 32
 
3.9%
서울 29
 
3.6%
도봉구 23
 
2.8%
성북구 22
 
2.7%
구로구 21
 
2.6%
관악구 15
 
1.8%
금천구 15
 
1.8%
용산구 13
 
1.6%
미아동 12
 
1.5%
Other values (278) 450
55.5%
2024-05-18T15:04:19.596635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
629
16.4%
구 242
 
6.3%
서 231
 
6.0%
동 231
 
6.0%
울 208
 
5.4%
시 191
 
5.0%
특 179
 
4.7%
별 179
 
4.7%
1 140
 
3.6%
- 134
 
3.5%
Other values (155) 1480
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2311
60.1%
Decimal Number 750
 
19.5%
Space Separator 629
 
16.4%
Dash Punctuation 134
 
3.5%
Math Symbol 14
 
0.4%
Other Punctuation 2
 
0.1%
Uppercase Letter 2
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 242
 
10.5%
서 231
 
10.0%
동 231
 
10.0%
울 208
 
9.0%
시 191
 
8.3%
특 179
 
7.7%
별 179
 
7.7%
북 54
 
2.3%
봉 36
 
1.6%
로 35
 
1.5%
Other values (137) 725
31.4%
Decimal Number
ValueCountFrequency (%)
1 140
18.7%
3 83
11.1%
2 82
10.9%
6 72
9.6%
4 69
9.2%
0 67
8.9%
8 62
8.3%
7 61
8.1%
9 58
7.7%
5 56
 
7.5%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
629
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2311
60.1%
Common 1531
39.8%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 242
 
10.5%
서 231
 
10.0%
동 231
 
10.0%
울 208
 
9.0%
시 191
 
8.3%
특 179
 
7.7%
별 179
 
7.7%
북 54
 
2.3%
봉 36
 
1.6%
로 35
 
1.5%
Other values (137) 725
31.4%
Common
ValueCountFrequency (%)
629
41.1%
1 140
 
9.1%
- 134
 
8.8%
3 83
 
5.4%
2 82
 
5.4%
6 72
 
4.7%
4 69
 
4.5%
0 67
 
4.4%
8 62
 
4.0%
7 61
 
4.0%
Other values (6) 132
 
8.6%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2311
60.1%
ASCII 1533
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
629
41.0%
1 140
 
9.1%
- 134
 
8.7%
3 83
 
5.4%
2 82
 
5.3%
6 72
 
4.7%
4 69
 
4.5%
0 67
 
4.4%
8 62
 
4.0%
7 61
 
4.0%
Other values (8) 134
 
8.7%
Hangul
ValueCountFrequency (%)
구 242
 
10.5%
서 231
 
10.0%
동 231
 
10.0%
울 208
 
9.0%
시 191
 
8.3%
특 179
 
7.7%
별 179
 
7.7%
북 54
 
2.3%
봉 36
 
1.6%
로 35
 
1.5%
Other values (137) 725
31.4%

주소2
Text

Distinct167
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-18T15:04:20.471967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length7.9615385
Min length1

Characters and Unicode

Total characters1656
Distinct characters217
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

Unique160 ?
Unique (%)76.9%

Sample

1st row54-10 서울메디칼빌딩3층
2nd row403-162번지
3rd row레마빌딩 3층 최재득 내과의원
4th row협동의원
5th row2층
ValueCountFrequency (%)
2층 47
 
13.2%
3층 30
 
8.5%
4층 10
 
2.8%
5층 8
 
2.3%
51-1 6
 
1.7%
602호 6
 
1.7%
203호 4
 
1.1%
1층 3
 
0.8%
301호 3
 
0.8%
1 2
 
0.6%
Other values (226) 236
66.5%
2024-05-18T15:04:22.360321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
166
 
10.0%
층 116
 
7.0%
2 100
 
6.0%
3 77
 
4.6%
1 76
 
4.6%
0 56
 
3.4%
- 52
 
3.1%
과 51
 
3.1%
의 51
 
3.1%
원 46
 
2.8%
Other values (207) 865
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 931
56.2%
Decimal Number 483
29.2%
Space Separator 166
 
10.0%
Dash Punctuation 52
 
3.1%
Uppercase Letter 9
 
0.5%
Lowercase Letter 7
 
0.4%
Other Punctuation 4
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 116
 
12.5%
과 51
 
5.5%
의 51
 
5.5%
원 46
 
4.9%
빌 35
 
3.8%
호 34
 
3.7%
딩 34
 
3.7%
가 23
 
2.5%
내 22
 
2.4%
안 16
 
1.7%
Other values (176) 503
54.0%
Decimal Number
ValueCountFrequency (%)
2 100
20.7%
3 77
15.9%
1 76
15.7%
0 56
11.6%
5 38
 
7.9%
6 35
 
7.2%
4 32
 
6.6%
7 30
 
6.2%
8 22
 
4.6%
9 17
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
B 1
11.1%
Y 1
11.1%
C 1
11.1%
S 1
11.1%
W 1
11.1%
H 1
11.1%
J 1
11.1%
K 1
11.1%
A 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
d 1
14.3%
m 1
14.3%
c 1
14.3%
a 1
14.3%
s 1
14.3%
k 1
14.3%
e 1
14.3%
Space Separator
ValueCountFrequency (%)
166
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 931
56.2%
Common 709
42.8%
Latin 16
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 116
 
12.5%
과 51
 
5.5%
의 51
 
5.5%
원 46
 
4.9%
빌 35
 
3.8%
호 34
 
3.7%
딩 34
 
3.7%
가 23
 
2.5%
내 22
 
2.4%
안 16
 
1.7%
Other values (176) 503
54.0%
Latin
ValueCountFrequency (%)
B 1
 
6.2%
Y 1
 
6.2%
C 1
 
6.2%
d 1
 
6.2%
m 1
 
6.2%
c 1
 
6.2%
S 1
 
6.2%
a 1
 
6.2%
W 1
 
6.2%
H 1
 
6.2%
Other values (6) 6
37.5%
Common
ValueCountFrequency (%)
166
23.4%
2 100
14.1%
3 77
10.9%
1 76
10.7%
0 56
 
7.9%
- 52
 
7.3%
5 38
 
5.4%
6 35
 
4.9%
4 32
 
4.5%
7 30
 
4.2%
Other values (5) 47
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 931
56.2%
ASCII 725
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
166
22.9%
2 100
13.8%
3 77
10.6%
1 76
10.5%
0 56
 
7.7%
- 52
 
7.2%
5 38
 
5.2%
6 35
 
4.8%
4 32
 
4.4%
7 30
 
4.1%
Other values (21) 63
 
8.7%
Hangul
ValueCountFrequency (%)
층 116
 
12.5%
과 51
 
5.5%
의 51
 
5.5%
원 46
 
4.9%
빌 35
 
3.8%
호 34
 
3.7%
딩 34
 
3.7%
가 23
 
2.5%
내 22
 
2.4%
안 16
 
1.7%
Other values (176) 503
54.0%

도로명주소1
Text

MISSING 

Distinct175
Distinct (%)98.3%
Missing30
Missing (%)14.4%
Memory size1.8 KiB
2024-05-18T15:04:23.548232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length25.904494
Min length14

Characters and Unicode

Total characters4611
Distinct characters252
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

Unique172 ?
Unique (%)96.6%

Sample

1st row서울특별시 서초구 방배로 177-0
2nd row서울특별시 구로구 구로동로 35 (가리봉동)
3rd row서울특별시 성북구 보국문로 168 (정릉동)
4th row서울특별시 구로구 고척로21나길 17 (개봉동)
5th row서울특별시 구로구 중앙로15길 29 (고척동)
ValueCountFrequency (%)
서울특별시 178
 
20.6%
강북구 26
 
3.0%
도봉구 23
 
2.7%
구로구 20
 
2.3%
금천구 15
 
1.7%
도봉로 13
 
1.5%
성북구 13
 
1.5%
마포구 12
 
1.4%
동대문구 11
 
1.3%
동작구 11
 
1.3%
Other values (398) 541
62.7%
2024-05-18T15:04:24.820320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
686
 
14.9%
구 216
 
4.7%
로 212
 
4.6%
시 201
 
4.4%
서 199
 
4.3%
동 189
 
4.1%
울 181
 
3.9%
특 178
 
3.9%
별 178
 
3.9%
) 146
 
3.2%
Other values (242) 2225
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2935
63.7%
Space Separator 686
 
14.9%
Decimal Number 574
 
12.4%
Close Punctuation 146
 
3.2%
Open Punctuation 146
 
3.2%
Other Punctuation 77
 
1.7%
Dash Punctuation 38
 
0.8%
Uppercase Letter 8
 
0.2%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 216
 
7.4%
로 212
 
7.2%
시 201
 
6.8%
서 199
 
6.8%
동 189
 
6.4%
울 181
 
6.2%
특 178
 
6.1%
별 178
 
6.1%
도 52
 
1.8%
봉 50
 
1.7%
Other values (219) 1279
43.6%
Decimal Number
ValueCountFrequency (%)
1 111
19.3%
2 88
15.3%
3 76
13.2%
0 58
10.1%
6 49
8.5%
4 47
8.2%
7 40
 
7.0%
5 36
 
6.3%
8 36
 
6.3%
9 33
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
K 3
37.5%
T 1
 
12.5%
I 1
 
12.5%
G 1
 
12.5%
J 1
 
12.5%
S 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 76
98.7%
& 1
 
1.3%
Space Separator
ValueCountFrequency (%)
686
100.0%
Close Punctuation
ValueCountFrequency (%)
) 146
100.0%
Open Punctuation
ValueCountFrequency (%)
( 146
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2935
63.7%
Common 1667
36.2%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 216
 
7.4%
로 212
 
7.2%
시 201
 
6.8%
서 199
 
6.8%
동 189
 
6.4%
울 181
 
6.2%
특 178
 
6.1%
별 178
 
6.1%
도 52
 
1.8%
봉 50
 
1.7%
Other values (219) 1279
43.6%
Common
ValueCountFrequency (%)
686
41.2%
) 146
 
8.8%
( 146
 
8.8%
1 111
 
6.7%
2 88
 
5.3%
, 76
 
4.6%
3 76
 
4.6%
0 58
 
3.5%
6 49
 
2.9%
4 47
 
2.8%
Other values (6) 184
 
11.0%
Latin
ValueCountFrequency (%)
K 3
33.3%
T 1
 
11.1%
I 1
 
11.1%
G 1
 
11.1%
Ⅱ 1
 
11.1%
J 1
 
11.1%
S 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2935
63.7%
ASCII 1675
36.3%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
686
41.0%
) 146
 
8.7%
( 146
 
8.7%
1 111
 
6.6%
2 88
 
5.3%
, 76
 
4.5%
3 76
 
4.5%
0 58
 
3.5%
6 49
 
2.9%
4 47
 
2.8%
Other values (12) 192
 
11.5%
Hangul
ValueCountFrequency (%)
구 216
 
7.4%
로 212
 
7.2%
시 201
 
6.8%
서 199
 
6.8%
동 189
 
6.4%
울 181
 
6.2%
특 178
 
6.1%
별 178
 
6.1%
도 52
 
1.8%
봉 50
 
1.7%
Other values (219) 1279
43.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소2
Text

MISSING 

Distinct132
Distinct (%)74.2%
Missing30
Missing (%)14.4%
Memory size1.8 KiB
2024-05-18T15:04:25.403979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length6.752809
Min length2

Characters and Unicode

Total characters1202
Distinct characters184
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

Unique123 ?
Unique (%)69.1%

Sample

1st row레마빌딩 3층 최재득 내과의원
2nd row협동의원
3rd row2층
4th row2층
5th row고척성모의원
ValueCountFrequency (%)
2층 45
 
16.0%
3층 26
 
9.3%
4층 11
 
3.9%
5층 9
 
3.2%
문정빌딩 4
 
1.4%
602호 4
 
1.4%
203호 4
 
1.4%
상가 4
 
1.4%
1층 3
 
1.1%
301호 3
 
1.1%
Other values (159) 168
59.8%
2024-05-18T15:04:26.389771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
114
 
9.5%
층 109
 
9.1%
2 80
 
6.7%
3 51
 
4.2%
과 48
 
4.0%
의 46
 
3.8%
0 39
 
3.2%
원 38
 
3.2%
호 33
 
2.7%
1 30
 
2.5%
Other values (174) 614
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 784
65.2%
Decimal Number 268
 
22.3%
Space Separator 114
 
9.5%
Dash Punctuation 9
 
0.7%
Uppercase Letter 9
 
0.7%
Other Punctuation 6
 
0.5%
Lowercase Letter 6
 
0.5%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 109
 
13.9%
과 48
 
6.1%
의 46
 
5.9%
원 38
 
4.8%
호 33
 
4.2%
빌 28
 
3.6%
딩 28
 
3.6%
가 20
 
2.6%
내 19
 
2.4%
정 18
 
2.3%
Other values (145) 397
50.6%
Decimal Number
ValueCountFrequency (%)
2 80
29.9%
3 51
19.0%
0 39
14.6%
1 30
 
11.2%
5 22
 
8.2%
4 16
 
6.0%
9 10
 
3.7%
6 9
 
3.4%
8 6
 
2.2%
7 5
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
W 2
22.2%
C 1
11.1%
Y 1
11.1%
B 1
11.1%
J 1
11.1%
S 1
11.1%
A 1
11.1%
H 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
c 1
16.7%
m 1
16.7%
d 1
16.7%
a 1
16.7%
s 1
16.7%
k 1
16.7%
Space Separator
ValueCountFrequency (%)
114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 784
65.2%
Common 403
33.5%
Latin 15
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 109
 
13.9%
과 48
 
6.1%
의 46
 
5.9%
원 38
 
4.8%
호 33
 
4.2%
빌 28
 
3.6%
딩 28
 
3.6%
가 20
 
2.6%
내 19
 
2.4%
정 18
 
2.3%
Other values (145) 397
50.6%
Common
ValueCountFrequency (%)
114
28.3%
2 80
19.9%
3 51
12.7%
0 39
 
9.7%
1 30
 
7.4%
5 22
 
5.5%
4 16
 
4.0%
9 10
 
2.5%
- 9
 
2.2%
6 9
 
2.2%
Other values (5) 23
 
5.7%
Latin
ValueCountFrequency (%)
W 2
13.3%
c 1
 
6.7%
m 1
 
6.7%
d 1
 
6.7%
C 1
 
6.7%
Y 1
 
6.7%
B 1
 
6.7%
J 1
 
6.7%
S 1
 
6.7%
A 1
 
6.7%
Other values (4) 4
26.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 784
65.2%
ASCII 418
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
114
27.3%
2 80
19.1%
3 51
12.2%
0 39
 
9.3%
1 30
 
7.2%
5 22
 
5.3%
4 16
 
3.8%
9 10
 
2.4%
- 9
 
2.2%
6 9
 
2.2%
Other values (19) 38
 
9.1%
Hangul
ValueCountFrequency (%)
층 109
 
13.9%
과 48
 
6.1%
의 46
 
5.9%
원 38
 
4.8%
호 33
 
4.2%
빌 28
 
3.6%
딩 28
 
3.6%
가 20
 
2.6%
내 19
 
2.4%
정 18
 
2.3%
Other values (145) 397
50.6%

우편번호1
Real number (ℝ)

Distinct37
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean706.96635
Minimum12
Maximum8716
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-18T15:04:26.702115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile121
Q1132
median142
Q3152
95-th percentile6737.3
Maximum8716
Range8704
Interquartile range (IQR)20

Descriptive statistics

Standard deviation1943.0711
Coefficient of variation (CV)2.7484634
Kurtosis10.409332
Mean706.96635
Median Absolute Deviation (MAD)10
Skewness3.4434076
Sum147049
Variance3775525.3
MonotonicityNot monotonic
2024-05-18T15:04:27.086192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
142 28
13.5%
132 22
10.6%
136 19
 
9.1%
153 15
 
7.2%
152 13
 
6.2%
151 13
 
6.2%
140 12
 
5.8%
121 12
 
5.8%
130 11
 
5.3%
156 11
 
5.3%
Other values (27) 52
25.0%
ValueCountFrequency (%)
12 1
 
0.5%
100 9
4.3%
121 12
5.8%
130 11
5.3%
131 1
 
0.5%
132 22
10.6%
136 19
9.1%
137 9
4.3%
138 1
 
0.5%
140 12
5.8%
ValueCountFrequency (%)
8716 1
0.5%
8701 1
0.5%
8324 1
0.5%
8322 1
0.5%
8305 1
0.5%
8282 1
0.5%
8251 1
0.5%
8241 1
0.5%
8235 1
0.5%
8222 1
0.5%

우편번호2
Real number (ℝ)

MISSING 

Distinct114
Distinct (%)61.0%
Missing21
Missing (%)10.1%
Infinite0
Infinite (%)0.0%
Mean719.6631
Minimum15
Maximum932
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-18T15:04:27.462071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile51.9
Q1789
median827
Q3860.5
95-th percentile896
Maximum932
Range917
Interquartile range (IQR)71.5

Descriptive statistics

Standard deviation273.58066
Coefficient of variation (CV)0.38015101
Kurtosis1.6230317
Mean719.6631
Median Absolute Deviation (MAD)36
Skewness-1.8314383
Sum134577
Variance74846.375
MonotonicityNot monotonic
2024-05-18T15:04:27.721916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
858 6
 
2.9%
823 6
 
2.9%
854 4
 
1.9%
805 4
 
1.9%
859 4
 
1.9%
867 4
 
1.9%
807 3
 
1.4%
810 3
 
1.4%
130 3
 
1.4%
836 3
 
1.4%
Other values (104) 147
70.7%
(Missing) 21
 
10.1%
ValueCountFrequency (%)
15 1
0.5%
20 1
0.5%
30 1
0.5%
31 1
0.5%
32 1
0.5%
36 1
0.5%
45 2
1.0%
50 1
0.5%
51 1
0.5%
54 1
0.5%
ValueCountFrequency (%)
932 3
1.4%
916 1
 
0.5%
913 1
 
0.5%
907 1
 
0.5%
905 1
 
0.5%
903 1
 
0.5%
896 3
1.4%
893 1
 
0.5%
892 1
 
0.5%
890 2
1.0%

자치구 이름
Categorical

Distinct15
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
강북구
32 
도봉구
23 
성북구
22 
구로구
21 
관악구
15 
Other values (10)
95 

Length

Max length4
Median length3
Mean length3.0096154
Min length2

Unique

Unique2 ?
Unique (%)1.0%

Sample

1st row강북구
2nd row구로구
3rd row서초구
4th row구로구
5th row성북구

Common Values

ValueCountFrequency (%)
강북구 32
15.4%
도봉구 23
11.1%
성북구 22
10.6%
구로구 21
10.1%
관악구 15
7.2%
금천구 15
7.2%
용산구 13
6.2%
서초구 12
 
5.8%
마포구 12
 
5.8%
동작구 11
 
5.3%
Other values (5) 32
15.4%

Length

2024-05-18T15:04:27.978537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강북구 32
15.4%
도봉구 23
11.1%
성북구 22
10.6%
구로구 21
10.1%
관악구 15
7.2%
금천구 15
7.2%
용산구 13
6.2%
서초구 12
 
5.8%
마포구 12
 
5.8%
동작구 11
 
5.3%
Other values (5) 32
15.4%

Interactions

2024-05-18T15:04:12.345778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:04:10.881141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:04:11.634228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:04:12.595935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:04:11.190542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:04:11.874953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:04:12.863279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:04:11.412694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:04:12.104619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T15:04:28.179175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호우편번호1우편번호2자치구 이름
관리번호1.0000.1790.3310.726
우편번호10.1791.000NaN0.575
우편번호20.331NaN1.0000.648
자치구 이름0.7260.5750.6481.000
2024-05-18T15:04:28.433121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호우편번호1우편번호2자치구 이름
관리번호1.000-0.3520.0840.366
우편번호1-0.3521.0000.0810.304
우편번호20.0840.0811.0000.354
자치구 이름0.3660.3040.3541.000

Missing values

2024-05-18T15:04:13.201609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T15:04:13.645680image/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.
2024-05-18T15:04:13.943329image/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

관리번호병의원 이름주소1주소2도로명주소1도로명주소2우편번호1우편번호2자치구 이름
0441김영재내과의원서울 강북구 수유1동 50~9354-10 서울메디칼빌딩3층<NA><NA>142874강북구
11901박철수내과의원서울 구로구 개봉3동 374~403403-162번지<NA><NA>152816구로구
22921최재득내과의원서울특별시 서초구 방배동 852-20레마빌딩 3층 최재득 내과의원서울특별시 서초구 방배로 177-0레마빌딩 3층 최재득 내과의원137837서초구
3462협동의원서울특별시 구로구 가리봉동 25-64협동의원서울특별시 구로구 구로동로 35 (가리봉동)협동의원8322<NA>구로구
4641연세가정의학과의원서울특별시 성북구 정릉동 779-12층서울특별시 성북구 보국문로 168 (정릉동)2층2701<NA>성북구
5741서울하나의원서울 강북구 삼각산동 SK아파트 101~111주상가 108호<NA><NA>142777강북구
6823김동일내과서울 성북구 동소문동6가1<NA><NA>13636성북구
7922오형태내과서울특별시 구로구 개봉동 33-30 현대빌딩2층서울특별시 구로구 고척로21나길 17 (개봉동)2층8251<NA>구로구
8941연세가정의학과서울 서초구 서초동1319-11 두산베어스텔301<NA><NA>13770서초구
9303정릉제일정형외과서울 성북구 정릉1동 14~7216-174<NA><NA>136841성북구
관리번호병의원 이름주소1주소2도로명주소1도로명주소2우편번호1우편번호2자치구 이름
19811131동안비전내과의원서울특별시 동대문구 이문동 324-102층 동안비전내과의원서울특별시 동대문구 이문로 88 (이문동,민족통일 대통령 빌딩)2층130831동대문구
19911643서울삼성안과서울특별시 광진구 구의동 75-1썬타워빌딩 1층서울특별시 광진구 천호대로 670 (구의동,썬-타워빌딩)썬타워빌딩 1층143819광진구
20011646타임안과서울특별시 구로구 고척동 72-49스카이타워 5층서울특별시 구로구 경인로 387 (고척동)스카이타워 5층152826구로구
20111647정가정의학과의원서울특별시 구로구 개봉동 476서울특별시 구로구 경인로382서울특별시 구로구 경인로 382 (개봉동,한마을아파트)한마을 아파트 상가 206호152752구로구
20211663연세정형외과의원서울특별시 구로구 구로동 103-9구로오네뜨시티 301호서울특별시 구로구 가마산로 271 (구로동,대륙빌딩)구로오네뜨시티 301호152842구로구
203544열린연세정형외과서울특별시 구로구 개봉동 126-22 서정빌딩4층 열린연세정형외과서울특별시 구로구 고척로 132 (개봉동)4층 열린연세정형외과8235<NA>구로구
20411664진가정의학과의원서울특별시 구로구 구로동에이스테크노타워8차 201호 진가정의학과의원서울특별시 구로구 디지털로33길 11-0201호 진가정의학과의원152780구로구
20511743새서울외과의원서울특별시 동대문구 장안동 309-10서울특별시 서초구 서초대로74길 33서울특별시 동대문구 장한로 144 (장안동,새서울병원)문정빌딩 602호130839동대문구
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