Overview

Dataset statistics

Number of variables9
Number of observations207
Missing cells81
Missing cells (%)4.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.3 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 (14.5%) missing valuesMissing
도로명주소2 has 30 (14.5%) missing valuesMissing
우편번호2 has 21 (10.1%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-04-20 21:11:05.241467
Analysis finished2024-04-20 21:11:07.931593
Duration2.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

UNIQUE 

Distinct207
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4214.9324
Minimum201
Maximum11703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-21T06:11:08.007810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201
5-th percentile265.9
Q11201
median3983
Q35073
95-th percentile11171
Maximum11703
Range11502
Interquartile range (IQR)3872

Descriptive statistics

Standard deviation3305.4396
Coefficient of variation (CV)0.78422127
Kurtosis-0.090537177
Mean4214.9324
Median Absolute Deviation (MAD)1920
Skewness0.79215818
Sum872491
Variance10925931
MonotonicityNot monotonic
2024-04-21T06:11:08.118935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441 1
 
0.5%
2241 1
 
0.5%
4123 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%
Other values (197) 197
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 (%)
11703 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%
11203 1
0.5%

병의원 이름
Text

Distinct206
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-21T06:11:08.312560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length6.4830918
Min length3

Characters and Unicode

Total characters1342
Distinct characters195
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

Unique205 ?
Unique (%)99.0%

Sample

1st row김영재내과의원
2nd row김승만내과의원
3rd row협동의원
4th row연세가정의학과의원
5th row서울하나의원
ValueCountFrequency (%)
제일성모내과 2
 
1.0%
한영의원 1
 
0.5%
북부성모의원 1
 
0.5%
연세중앙내과 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%
Other values (196) 196
94.7%
2024-04-21T06:11:08.618995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 169
 
12.6%
과 151
 
11.3%
원 149
 
11.1%
내 77
 
5.7%
정 44
 
3.3%
안 42
 
3.1%
가 31
 
2.3%
연 27
 
2.0%
세 26
 
1.9%
성 24
 
1.8%
Other values (185) 602
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1338
99.7%
Uppercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 169
 
12.6%
과 151
 
11.3%
원 149
 
11.1%
내 77
 
5.8%
정 44
 
3.3%
안 42
 
3.1%
가 31
 
2.3%
연 27
 
2.0%
세 26
 
1.9%
성 24
 
1.8%
Other values (182) 598
44.7%
Uppercase Letter
ValueCountFrequency (%)
H 2
50.0%
W 1
25.0%
J 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1338
99.7%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 169
 
12.6%
과 151
 
11.3%
원 149
 
11.1%
내 77
 
5.8%
정 44
 
3.3%
안 42
 
3.1%
가 31
 
2.3%
연 27
 
2.0%
세 26
 
1.9%
성 24
 
1.8%
Other values (182) 598
44.7%
Latin
ValueCountFrequency (%)
H 2
50.0%
W 1
25.0%
J 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1338
99.7%
ASCII 4
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 169
 
12.6%
과 151
 
11.3%
원 149
 
11.1%
내 77
 
5.8%
정 44
 
3.3%
안 42
 
3.1%
가 31
 
2.3%
연 27
 
2.0%
세 26
 
1.9%
성 24
 
1.8%
Other values (182) 598
44.7%
ASCII
ValueCountFrequency (%)
H 2
50.0%
W 1
25.0%
J 1
25.0%

주소1
Text

Distinct195
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-21T06:11:08.915826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length32
Mean length18.454106
Min length11

Characters and Unicode

Total characters3820
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

Unique184 ?
Unique (%)88.9%

Sample

1st row서울 강북구 수유1동 50~93
2nd row서울특별시 강북구 수유동
3rd row서울특별시 구로구 가리봉동 25-64
4th row서울특별시 성북구 정릉동 779-1
5th row서울 강북구 삼각산동 SK아파트 101~111
ValueCountFrequency (%)
서울특별시 178
 
22.1%
강북구 32
 
4.0%
서울 29
 
3.6%
도봉구 22
 
2.7%
성북구 22
 
2.7%
구로구 21
 
2.6%
관악구 15
 
1.9%
금천구 15
 
1.9%
용산구 13
 
1.6%
마포구 12
 
1.5%
Other values (276) 447
55.5%
2024-04-21T06:11:09.327293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
625
16.4%
구 241
 
6.3%
서 230
 
6.0%
동 229
 
6.0%
울 207
 
5.4%
시 190
 
5.0%
특 178
 
4.7%
별 178
 
4.7%
1 139
 
3.6%
- 133
 
3.5%
Other values (155) 1470
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2300
60.2%
Decimal Number 742
 
19.4%
Space Separator 625
 
16.4%
Dash Punctuation 133
 
3.5%
Math Symbol 14
 
0.4%
Other Punctuation 2
 
0.1%
Uppercase Letter 2
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 241
 
10.5%
서 230
 
10.0%
동 229
 
10.0%
울 207
 
9.0%
시 190
 
8.3%
특 178
 
7.7%
별 178
 
7.7%
북 54
 
2.3%
로 35
 
1.5%
강 35
 
1.5%
Other values (137) 723
31.4%
Decimal Number
ValueCountFrequency (%)
1 139
18.7%
3 82
11.1%
2 82
11.1%
6 72
9.7%
4 68
9.2%
0 64
8.6%
8 61
8.2%
7 61
8.2%
9 57
7.7%
5 56
7.5%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
625
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 133
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2300
60.2%
Common 1518
39.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 241
 
10.5%
서 230
 
10.0%
동 229
 
10.0%
울 207
 
9.0%
시 190
 
8.3%
특 178
 
7.7%
별 178
 
7.7%
북 54
 
2.3%
로 35
 
1.5%
강 35
 
1.5%
Other values (137) 723
31.4%
Common
ValueCountFrequency (%)
625
41.2%
1 139
 
9.2%
- 133
 
8.8%
3 82
 
5.4%
2 82
 
5.4%
6 72
 
4.7%
4 68
 
4.5%
0 64
 
4.2%
8 61
 
4.0%
7 61
 
4.0%
Other values (6) 131
 
8.6%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2300
60.2%
ASCII 1520
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
625
41.1%
1 139
 
9.1%
- 133
 
8.8%
3 82
 
5.4%
2 82
 
5.4%
6 72
 
4.7%
4 68
 
4.5%
0 64
 
4.2%
8 61
 
4.0%
7 61
 
4.0%
Other values (8) 133
 
8.8%
Hangul
ValueCountFrequency (%)
구 241
 
10.5%
서 230
 
10.0%
동 229
 
10.0%
울 207
 
9.0%
시 190
 
8.3%
특 178
 
7.7%
별 178
 
7.7%
북 54
 
2.3%
로 35
 
1.5%
강 35
 
1.5%
Other values (137) 723
31.4%

주소2
Text

Distinct165
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-21T06:11:09.550653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length7.9227053
Min length1

Characters and Unicode

Total characters1640
Distinct characters212
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

Unique158 ?
Unique (%)76.3%

Sample

1st row54-10 서울메디칼빌딩3층
2nd row58-8
3rd row협동의원
4th row2층
5th row주상가 108호
ValueCountFrequency (%)
2층 47
 
13.4%
3층 30
 
8.5%
4층 10
 
2.8%
5층 8
 
2.3%
51-1 7
 
2.0%
602호 7
 
2.0%
203호 4
 
1.1%
1층 3
 
0.9%
301호 3
 
0.9%
205호 2
 
0.6%
Other values (222) 231
65.6%
2024-04-21T06:11:09.904076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
164
 
10.0%
층 116
 
7.1%
2 101
 
6.2%
1 78
 
4.8%
3 75
 
4.6%
0 57
 
3.5%
- 53
 
3.2%
과 51
 
3.1%
의 50
 
3.0%
원 45
 
2.7%
Other values (202) 850
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 914
55.7%
Decimal Number 485
29.6%
Space Separator 164
 
10.0%
Dash Punctuation 53
 
3.2%
Uppercase Letter 9
 
0.5%
Lowercase Letter 7
 
0.4%
Other Punctuation 4
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 116
 
12.7%
과 51
 
5.6%
의 50
 
5.5%
원 45
 
4.9%
빌 35
 
3.8%
호 35
 
3.8%
딩 34
 
3.7%
가 23
 
2.5%
내 22
 
2.4%
안 16
 
1.8%
Other values (171) 487
53.3%
Decimal Number
ValueCountFrequency (%)
2 101
20.8%
1 78
16.1%
3 75
15.5%
0 57
11.8%
5 39
 
8.0%
6 36
 
7.4%
4 31
 
6.4%
7 29
 
6.0%
8 22
 
4.5%
9 17
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
W 1
11.1%
H 1
11.1%
J 1
11.1%
C 1
11.1%
Y 1
11.1%
B 1
11.1%
K 1
11.1%
S 1
11.1%
A 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
c 1
14.3%
m 1
14.3%
d 1
14.3%
a 1
14.3%
s 1
14.3%
k 1
14.3%
e 1
14.3%
Space Separator
ValueCountFrequency (%)
164
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 914
55.7%
Common 710
43.3%
Latin 16
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 116
 
12.7%
과 51
 
5.6%
의 50
 
5.5%
원 45
 
4.9%
빌 35
 
3.8%
호 35
 
3.8%
딩 34
 
3.7%
가 23
 
2.5%
내 22
 
2.4%
안 16
 
1.8%
Other values (171) 487
53.3%
Latin
ValueCountFrequency (%)
W 1
 
6.2%
H 1
 
6.2%
J 1
 
6.2%
c 1
 
6.2%
m 1
 
6.2%
d 1
 
6.2%
C 1
 
6.2%
Y 1
 
6.2%
B 1
 
6.2%
a 1
 
6.2%
Other values (6) 6
37.5%
Common
ValueCountFrequency (%)
164
23.1%
2 101
14.2%
1 78
11.0%
3 75
10.6%
0 57
 
8.0%
- 53
 
7.5%
5 39
 
5.5%
6 36
 
5.1%
4 31
 
4.4%
7 29
 
4.1%
Other values (5) 47
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 914
55.7%
ASCII 726
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
164
22.6%
2 101
13.9%
1 78
10.7%
3 75
10.3%
0 57
 
7.9%
- 53
 
7.3%
5 39
 
5.4%
6 36
 
5.0%
4 31
 
4.3%
7 29
 
4.0%
Other values (21) 63
 
8.7%
Hangul
ValueCountFrequency (%)
층 116
 
12.7%
과 51
 
5.6%
의 50
 
5.5%
원 45
 
4.9%
빌 35
 
3.8%
호 35
 
3.8%
딩 34
 
3.7%
가 23
 
2.5%
내 22
 
2.4%
안 16
 
1.8%
Other values (171) 487
53.3%

도로명주소1
Text

MISSING 

Distinct173
Distinct (%)97.7%
Missing30
Missing (%)14.5%
Memory size1.7 KiB
2024-04-21T06:11:10.171856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length25.779661
Min length14

Characters and Unicode

Total characters4563
Distinct characters250
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

Unique169 ?
Unique (%)95.5%

Sample

1st row서울특별시 강북구 삼양로 294-0
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 177
 
20.7%
강북구 26
 
3.0%
도봉구 22
 
2.6%
구로구 20
 
2.3%
금천구 15
 
1.8%
도봉로 13
 
1.5%
성북구 13
 
1.5%
마포구 12
 
1.4%
동작구 11
 
1.3%
동대문구 10
 
1.2%
Other values (393) 538
62.8%
2024-04-21T06:11:10.546579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
681
 
14.9%
구 215
 
4.7%
로 211
 
4.6%
시 200
 
4.4%
서 197
 
4.3%
동 185
 
4.1%
울 179
 
3.9%
별 177
 
3.9%
특 177
 
3.9%
) 144
 
3.2%
Other values (240) 2197
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2904
63.6%
Space Separator 681
 
14.9%
Decimal Number 568
 
12.4%
Close Punctuation 144
 
3.2%
Open Punctuation 144
 
3.2%
Other Punctuation 75
 
1.6%
Dash Punctuation 38
 
0.8%
Uppercase Letter 8
 
0.2%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 215
 
7.4%
로 211
 
7.3%
시 200
 
6.9%
서 197
 
6.8%
동 185
 
6.4%
울 179
 
6.2%
별 177
 
6.1%
특 177
 
6.1%
도 51
 
1.8%
봉 49
 
1.7%
Other values (217) 1263
43.5%
Decimal Number
ValueCountFrequency (%)
1 109
19.2%
2 88
15.5%
3 75
13.2%
0 58
10.2%
6 47
8.3%
4 45
7.9%
7 40
 
7.0%
5 36
 
6.3%
8 36
 
6.3%
9 34
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
K 3
37.5%
J 1
 
12.5%
G 1
 
12.5%
I 1
 
12.5%
T 1
 
12.5%
S 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 74
98.7%
& 1
 
1.3%
Space Separator
ValueCountFrequency (%)
681
100.0%
Close Punctuation
ValueCountFrequency (%)
) 144
100.0%
Open Punctuation
ValueCountFrequency (%)
( 144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2904
63.6%
Common 1650
36.2%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 215
 
7.4%
로 211
 
7.3%
시 200
 
6.9%
서 197
 
6.8%
동 185
 
6.4%
울 179
 
6.2%
별 177
 
6.1%
특 177
 
6.1%
도 51
 
1.8%
봉 49
 
1.7%
Other values (217) 1263
43.5%
Common
ValueCountFrequency (%)
681
41.3%
) 144
 
8.7%
( 144
 
8.7%
1 109
 
6.6%
2 88
 
5.3%
3 75
 
4.5%
, 74
 
4.5%
0 58
 
3.5%
6 47
 
2.8%
4 45
 
2.7%
Other values (6) 185
 
11.2%
Latin
ValueCountFrequency (%)
K 3
33.3%
J 1
 
11.1%
G 1
 
11.1%
I 1
 
11.1%
T 1
 
11.1%
Ⅱ 1
 
11.1%
S 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2904
63.6%
ASCII 1658
36.3%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
681
41.1%
) 144
 
8.7%
( 144
 
8.7%
1 109
 
6.6%
2 88
 
5.3%
3 75
 
4.5%
, 74
 
4.5%
0 58
 
3.5%
6 47
 
2.8%
4 45
 
2.7%
Other values (12) 193
 
11.6%
Hangul
ValueCountFrequency (%)
구 215
 
7.4%
로 211
 
7.3%
시 200
 
6.9%
서 197
 
6.8%
동 185
 
6.4%
울 179
 
6.2%
별 177
 
6.1%
특 177
 
6.1%
도 51
 
1.8%
봉 49
 
1.7%
Other values (217) 1263
43.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소2
Text

MISSING 

Distinct131
Distinct (%)74.0%
Missing30
Missing (%)14.5%
Memory size1.7 KiB
2024-04-21T06:11:10.756729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length6.7514124
Min length2

Characters and Unicode

Total characters1195
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

Unique122 ?
Unique (%)68.9%

Sample

1st row김승만내과
2nd row협동의원
3rd row2층
4th row2층
5th row고척성모의원
ValueCountFrequency (%)
2층 45
 
16.1%
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 3
 
1.1%
301호 3
 
1.1%
1층 3
 
1.1%
Other values (158) 167
59.9%
2024-04-21T06:11:11.069030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
 
9.5%
층 109
 
9.1%
2 79
 
6.6%
3 51
 
4.3%
과 48
 
4.0%
의 46
 
3.8%
원 38
 
3.2%
0 38
 
3.2%
호 32
 
2.7%
1 30
 
2.5%
Other values (174) 611
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 781
65.4%
Decimal Number 265
 
22.2%
Space Separator 113
 
9.5%
Dash Punctuation 9
 
0.8%
Uppercase Letter 9
 
0.8%
Other Punctuation 6
 
0.5%
Lowercase Letter 6
 
0.5%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 109
 
14.0%
과 48
 
6.1%
의 46
 
5.9%
원 38
 
4.9%
호 32
 
4.1%
빌 28
 
3.6%
딩 28
 
3.6%
가 19
 
2.4%
내 19
 
2.4%
정 18
 
2.3%
Other values (145) 396
50.7%
Decimal Number
ValueCountFrequency (%)
2 79
29.8%
3 51
19.2%
0 38
14.3%
1 30
 
11.3%
5 22
 
8.3%
4 15
 
5.7%
9 10
 
3.8%
6 9
 
3.4%
8 6
 
2.3%
7 5
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
W 2
22.2%
C 1
11.1%
Y 1
11.1%
B 1
11.1%
A 1
11.1%
H 1
11.1%
J 1
11.1%
S 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
c 1
16.7%
m 1
16.7%
d 1
16.7%
a 1
16.7%
k 1
16.7%
s 1
16.7%
Space Separator
ValueCountFrequency (%)
113
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 781
65.4%
Common 399
33.4%
Latin 15
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 109
 
14.0%
과 48
 
6.1%
의 46
 
5.9%
원 38
 
4.9%
호 32
 
4.1%
빌 28
 
3.6%
딩 28
 
3.6%
가 19
 
2.4%
내 19
 
2.4%
정 18
 
2.3%
Other values (145) 396
50.7%
Common
ValueCountFrequency (%)
113
28.3%
2 79
19.8%
3 51
12.8%
0 38
 
9.5%
1 30
 
7.5%
5 22
 
5.5%
4 15
 
3.8%
9 10
 
2.5%
6 9
 
2.3%
- 9
 
2.3%
Other values (5) 23
 
5.8%
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%
A 1
 
6.7%
a 1
 
6.7%
H 1
 
6.7%
Other values (4) 4
26.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 781
65.4%
ASCII 414
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
27.3%
2 79
19.1%
3 51
12.3%
0 38
 
9.2%
1 30
 
7.2%
5 22
 
5.3%
4 15
 
3.6%
9 10
 
2.4%
6 9
 
2.2%
- 9
 
2.2%
Other values (19) 38
 
9.2%
Hangul
ValueCountFrequency (%)
층 109
 
14.0%
과 48
 
6.1%
의 46
 
5.9%
원 38
 
4.9%
호 32
 
4.1%
빌 28
 
3.6%
딩 28
 
3.6%
가 19
 
2.4%
내 19
 
2.4%
정 18
 
2.3%
Other values (145) 396
50.7%

우편번호1
Real number (ℝ)

Distinct37
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean709.78261
Minimum12
Maximum8716
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-21T06:11:11.187095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile121
Q1132
median142
Q3152
95-th percentile6737.4
Maximum8716
Range8704
Interquartile range (IQR)20

Descriptive statistics

Standard deviation1947.3561
Coefficient of variation (CV)2.7435951
Kurtosis10.337412
Mean709.78261
Median Absolute Deviation (MAD)10
Skewness3.4332438
Sum146925
Variance3792195.8
MonotonicityNot monotonic
2024-04-21T06:11:11.285498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
142 28
13.5%
132 21
 
10.1%
136 19
 
9.2%
153 15
 
7.2%
151 13
 
6.3%
152 13
 
6.3%
140 12
 
5.8%
121 12
 
5.8%
156 11
 
5.3%
130 10
 
4.8%
Other values (27) 53
25.6%
ValueCountFrequency (%)
12 1
 
0.5%
100 9
4.3%
121 12
5.8%
130 10
4.8%
131 1
 
0.5%
132 21
10.1%
136 19
9.2%
137 9
4.3%
138 2
 
1.0%
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 

Distinct113
Distinct (%)60.8%
Missing21
Missing (%)10.1%
Infinite0
Infinite (%)0.0%
Mean715.88172
Minimum15
Maximum932
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-21T06:11:11.390618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile51.75
Q1788
median826.5
Q3860.75
95-th percentile896
Maximum932
Range917
Interquartile range (IQR)72.75

Descriptive statistics

Standard deviation276.76154
Coefficient of variation (CV)0.38660232
Kurtosis1.4055161
Mean715.88172
Median Absolute Deviation (MAD)36
Skewness-1.7739212
Sum133154
Variance76596.948
MonotonicityNot monotonic
2024-04-21T06:11:11.496516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
858 6
 
2.9%
823 6
 
2.9%
200 4
 
1.9%
859 4
 
1.9%
805 4
 
1.9%
867 4
 
1.9%
854 4
 
1.9%
836 3
 
1.4%
830 3
 
1.4%
896 3
 
1.4%
Other values (103) 145
70.0%
(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 size1.7 KiB
강북구
32 
구로구
22 
성북구
22 
도봉구
22 
관악구
15 
Other values (10)
94 

Length

Max length4
Median length3
Mean length3.0048309
Min length2

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
강북구 32
15.5%
구로구 22
10.6%
성북구 22
10.6%
도봉구 22
10.6%
관악구 15
7.2%
금천구 15
7.2%
용산구 13
6.3%
서초구 12
 
5.8%
마포구 12
 
5.8%
동작구 11
 
5.3%
Other values (5) 31
15.0%

Length

2024-04-21T06:11:11.607561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강북구 32
15.5%
구로구 22
10.6%
성북구 22
10.6%
도봉구 22
10.6%
관악구 15
7.2%
금천구 15
7.2%
용산구 13
6.3%
서초구 12
 
5.8%
마포구 12
 
5.8%
동작구 11
 
5.3%
Other values (5) 31
15.0%

Interactions

2024-04-21T06:11:07.361399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:11:06.910856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:11:07.168416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:11:07.439525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:11:07.027996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:11:07.235486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:11:07.528078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:11:07.102083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:11:07.297197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T06:11:11.679703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호우편번호1우편번호2자치구 이름
관리번호1.0000.1770.3360.728
우편번호10.1771.000NaN0.567
우편번호20.336NaN1.0000.631
자치구 이름0.7280.5670.6311.000
2024-04-21T06:11:11.762414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호우편번호1우편번호2자치구 이름
관리번호1.000-0.3370.0800.367
우편번호1-0.3371.0000.0800.299
우편번호20.0800.0801.0000.339
자치구 이름0.3670.2990.3391.000

Missing values

2024-04-21T06:11:07.637495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T06:11:07.782608image/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.
2024-04-21T06:11:07.874846image/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
12241김승만내과의원서울특별시 강북구 수유동58-8서울특별시 강북구 삼양로 294-0김승만내과142874강북구
2462협동의원서울특별시 구로구 가리봉동 25-64협동의원서울특별시 구로구 구로동로 35 (가리봉동)협동의원8322<NA>구로구
3641연세가정의학과의원서울특별시 성북구 정릉동 779-12층서울특별시 성북구 보국문로 168 (정릉동)2층2701<NA>성북구
4741서울하나의원서울 강북구 삼각산동 SK아파트 101~111주상가 108호<NA><NA>142777강북구
5823김동일내과서울 성북구 동소문동6가1<NA><NA>13636성북구
6922오형태내과서울특별시 구로구 개봉동 33-30 현대빌딩2층서울특별시 구로구 고척로21나길 17 (개봉동)2층8251<NA>구로구
7941연세가정의학과서울 서초구 서초동1319-11 두산베어스텔301<NA><NA>13770서초구
8303정릉제일정형외과서울 성북구 정릉1동 14~7216-174<NA><NA>136841성북구
9308오가정의학과의원서울 성북구 정릉3동 890~962892-7<NA><NA>136856성북구
관리번호병의원 이름주소1주소2도로명주소1도로명주소2우편번호1우편번호2자치구 이름
19711131동안비전내과의원서울특별시 동대문구 이문동 324-102층 동안비전내과의원서울특별시 동대문구 이문로 88 (이문동,민족통일 대통령 빌딩)2층130831동대문구
19811643서울삼성안과서울특별시 광진구 구의동 75-1썬타워빌딩 1층서울특별시 광진구 천호대로 670 (구의동,썬-타워빌딩)썬타워빌딩 1층143819광진구
19911646타임안과서울특별시 구로구 고척동 72-49스카이타워 5층서울특별시 구로구 경인로 387 (고척동)스카이타워 5층152826구로구
20011647정가정의학과의원서울특별시 구로구 개봉동 476서울특별시 구로구 경인로382서울특별시 구로구 경인로 382 (개봉동,한마을아파트)한마을 아파트 상가 206호152752구로구
20111663연세정형외과의원서울특별시 구로구 구로동 103-9구로오네뜨시티 301호서울특별시 구로구 가마산로 271 (구로동,대륙빌딩)구로오네뜨시티 301호152842구로구
202544열린연세정형외과서울특별시 구로구 개봉동 126-22 서정빌딩4층 열린연세정형외과서울특별시 구로구 고척로 132 (개봉동)4층 열린연세정형외과8235<NA>구로구
20311664진가정의학과의원서울특별시 구로구 구로동에이스테크노타워8차 201호 진가정의학과의원서울특별시 구로구 디지털로33길 11-0201호 진가정의학과의원152780구로구
20411703제일성모내과서울특별시 송파구 문정동51-1 602호서울특별시 송파구 문정로 9문정빌딩 602호138200구로구
20511123윤명진윤나리내과서울특별시 동대문구 휘경동 150-132층서울특별시 동대문구 휘경로 49 (휘경동)2층130875동대문구
20611103강북삼성의원서울특별시 강북구 수유동 482-653층서울특별시 강북구 삼양로77가길 9 (수유동,삼보빌딩)3층142875강북구