Overview

Dataset statistics

Number of variables41
Number of observations10000
Missing cells154002
Missing cells (%)37.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 MiB
Average record size in memory356.0 B

Variable types

Numeric8
Text10
DateTime6
Categorical9
Unsupported8

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),의료기관종별명,의료인수,입원실수,병상수,총면적,진료과목내용,진료과목내용명,지정취소일자,완화의료지정형태,완화의료담당부서명,구급차특수,구급차일반,총인원,구조사수,허가병상수,최초지정일자
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16480/S/1/datasetView.do

Alerts

영업상태코드 is highly imbalanced (52.9%)Imbalance
영업상태명 is highly imbalanced (52.9%)Imbalance
상세영업상태명 is highly imbalanced (57.6%)Imbalance
인허가취소일자 has 9994 (99.9%) missing valuesMissing
폐업일자 has 6034 (60.3%) missing valuesMissing
휴업시작일자 has 9899 (99.0%) missing valuesMissing
휴업종료일자 has 9900 (99.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 670 (6.7%) missing valuesMissing
소재지면적 has 10000 (100.0%) missing valuesMissing
소재지우편번호 has 5327 (53.3%) missing valuesMissing
지번주소 has 1038 (10.4%) missing valuesMissing
도로명주소 has 1839 (18.4%) missing valuesMissing
도로명우편번호 has 2293 (22.9%) missing valuesMissing
좌표정보(X) has 1995 (20.0%) missing valuesMissing
좌표정보(Y) has 1995 (20.0%) missing valuesMissing
의료인수 has 3836 (38.4%) missing valuesMissing
입원실수 has 3836 (38.4%) missing valuesMissing
병상수 has 3836 (38.4%) missing valuesMissing
총면적 has 3836 (38.4%) missing valuesMissing
진료과목내용 has 3837 (38.4%) missing valuesMissing
진료과목내용명 has 3837 (38.4%) missing valuesMissing
지정취소일자 has 10000 (100.0%) missing valuesMissing
완화의료지정형태 has 10000 (100.0%) missing valuesMissing
완화의료담당부서명 has 10000 (100.0%) missing valuesMissing
총인원 has 10000 (100.0%) missing valuesMissing
구조사수 has 10000 (100.0%) missing valuesMissing
최초지정일자 has 10000 (100.0%) missing valuesMissing
총면적 is highly skewed (γ1 = 34.96623565)Skewed
관리번호 has unique valuesUnique
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지정취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
완화의료지정형태 is an unsupported type, check if it needs cleaning or further analysisUnsupported
완화의료담당부서명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총인원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
구조사수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
최초지정일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
의료인수 has 813 (8.1%) zerosZeros
입원실수 has 5840 (58.4%) zerosZeros
병상수 has 5804 (58.0%) zerosZeros
총면적 has 976 (9.8%) zerosZeros

Reproduction

Analysis started2024-05-11 07:03:54.617471
Analysis finished2024-05-11 07:03:58.589236
Duration3.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3121823
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:03:58.676868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13070000
median3120000
Q33180000
95-th percentile3220000
Maximum3240000
Range240000
Interquartile range (IQR)110000

Descriptive statistics

Standard deviation68163.563
Coefficient of variation (CV)0.021834538
Kurtosis-1.103359
Mean3121823
Median Absolute Deviation (MAD)60000
Skewness-0.13716649
Sum3.121823 × 1010
Variance4.6462713 × 109
MonotonicityNot monotonic
2024-05-11T16:03:58.894005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3180000 890
 
8.9%
3100000 744
 
7.4%
3220000 549
 
5.5%
3150000 546
 
5.5%
3110000 515
 
5.1%
3010000 482
 
4.8%
3130000 455
 
4.5%
3050000 454
 
4.5%
3200000 414
 
4.1%
3140000 407
 
4.1%
Other values (15) 4544
45.4%
ValueCountFrequency (%)
3000000 371
3.7%
3010000 482
4.8%
3020000 218
2.2%
3030000 282
2.8%
3040000 348
3.5%
3050000 454
4.5%
3060000 326
3.3%
3070000 375
3.8%
3080000 281
2.8%
3090000 312
3.1%
ValueCountFrequency (%)
3240000 155
 
1.6%
3230000 223
 
2.2%
3220000 549
5.5%
3210000 401
4.0%
3200000 414
4.1%
3190000 384
3.8%
3180000 890
8.9%
3170000 220
 
2.2%
3160000 348
 
3.5%
3150000 546
5.5%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T16:03:59.224458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length24.9993
Min length18

Characters and Unicode

Total characters249993
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowPHMA119943100034041100021
2nd rowPHMA119873180034041100022
3rd rowPHMA119953160034041100468
4th rowPHMA120113160034041100024
5th rowPHMA120123170035041100015
ValueCountFrequency (%)
phma119943100034041100021 1
 
< 0.1%
phma120233210034041100051 1
 
< 0.1%
phma119993100034041100066 1
 
< 0.1%
phma119923200033041100007 1
 
< 0.1%
phma120103070034041100017 1
 
< 0.1%
phma120063180034041100024 1
 
< 0.1%
phma120063180034041100032 1
 
< 0.1%
phma120223100034041100009 1
 
< 0.1%
phma120123070034041100023 1
 
< 0.1%
phma120023050034041100031 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T16:03:59.804735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 80243
32.1%
1 46795
18.7%
3 28783
 
11.5%
4 17714
 
7.1%
2 15911
 
6.4%
P 10000
 
4.0%
H 10000
 
4.0%
M 10000
 
4.0%
A 10000
 
4.0%
9 6977
 
2.8%
Other values (4) 13570
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 209993
84.0%
Uppercase Letter 40000
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 80243
38.2%
1 46795
22.3%
3 28783
 
13.7%
4 17714
 
8.4%
2 15911
 
7.6%
9 6977
 
3.3%
8 3862
 
1.8%
5 3478
 
1.7%
7 3417
 
1.6%
6 2813
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
P 10000
25.0%
H 10000
25.0%
M 10000
25.0%
A 10000
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 209993
84.0%
Latin 40000
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 80243
38.2%
1 46795
22.3%
3 28783
 
13.7%
4 17714
 
8.4%
2 15911
 
7.6%
9 6977
 
3.3%
8 3862
 
1.8%
5 3478
 
1.7%
7 3417
 
1.6%
6 2813
 
1.3%
Latin
ValueCountFrequency (%)
P 10000
25.0%
H 10000
25.0%
M 10000
25.0%
A 10000
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 249993
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 80243
32.1%
1 46795
18.7%
3 28783
 
11.5%
4 17714
 
7.1%
2 15911
 
6.4%
P 10000
 
4.0%
H 10000
 
4.0%
M 10000
 
4.0%
A 10000
 
4.0%
9 6977
 
2.8%
Other values (4) 13570
 
5.4%
Distinct7285
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T16:04:00.226539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.6134
Min length8

Characters and Unicode

Total characters86134
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

Unique5308 ?
Unique (%)53.1%

Sample

1st row19940402
2nd row19870902
3rd row19950508
4th row2011-11-16
5th row20120622
ValueCountFrequency (%)
19710610 24
 
0.2%
19650830 22
 
0.2%
19000101 9
 
0.1%
19631230 8
 
0.1%
2023-02-28 7
 
0.1%
20020829 7
 
0.1%
19740305 7
 
0.1%
20070305 6
 
0.1%
19930225 6
 
0.1%
20040102 6
 
0.1%
Other values (7275) 9898
99.0%
2024-05-11T16:04:01.124116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24433
28.4%
2 15273
17.7%
1 14446
16.8%
9 7030
 
8.2%
- 6134
 
7.1%
3 3696
 
4.3%
8 3349
 
3.9%
4 3183
 
3.7%
7 2912
 
3.4%
5 2879
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80000
92.9%
Dash Punctuation 6134
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24433
30.5%
2 15273
19.1%
1 14446
18.1%
9 7030
 
8.8%
3 3696
 
4.6%
8 3349
 
4.2%
4 3183
 
4.0%
7 2912
 
3.6%
5 2879
 
3.6%
6 2799
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 6134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86134
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24433
28.4%
2 15273
17.7%
1 14446
16.8%
9 7030
 
8.2%
- 6134
 
7.1%
3 3696
 
4.3%
8 3349
 
3.9%
4 3183
 
3.7%
7 2912
 
3.4%
5 2879
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86134
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24433
28.4%
2 15273
17.7%
1 14446
16.8%
9 7030
 
8.2%
- 6134
 
7.1%
3 3696
 
4.3%
8 3349
 
3.9%
4 3183
 
3.7%
7 2912
 
3.4%
5 2879
 
3.3%

인허가취소일자
Date

MISSING 

Distinct6
Distinct (%)100.0%
Missing9994
Missing (%)99.9%
Memory size156.2 KiB
Minimum2023-02-28 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T16:04:01.311702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:04:01.503643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5714 
3
4147 
4
 
64
5
 
57
2
 
18

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row3

Common Values

ValueCountFrequency (%)
1 5714
57.1%
3 4147
41.5%
4 64
 
0.6%
5 57
 
0.6%
2 18
 
0.2%

Length

2024-05-11T16:04:01.743164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:04:01.895612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5714
57.1%
3 4147
41.5%
4 64
 
0.6%
5 57
 
0.6%
2 18
 
0.2%

영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
5714 
폐업
4147 
취소/말소/만료/정지/중지
 
64
제외/삭제/전출
 
57
휴업
 
18

Length

Max length14
Median length5
Mean length3.8252
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row폐업

Common Values

ValueCountFrequency (%)
영업/정상 5714
57.1%
폐업 4147
41.5%
취소/말소/만료/정지/중지 64
 
0.6%
제외/삭제/전출 57
 
0.6%
휴업 18
 
0.2%

Length

2024-05-11T16:04:02.074467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:04:02.249271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 5714
57.1%
폐업 4147
41.5%
취소/말소/만료/정지/중지 64
 
0.6%
제외/삭제/전출 57
 
0.6%
휴업 18
 
0.2%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9654
Minimum2
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:04:02.413257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median13
Q313
95-th percentile13
Maximum99
Range97
Interquartile range (IQR)10

Descriptive statistics

Standard deviation5.5358168
Coefficient of variation (CV)0.61746456
Kurtosis40.091489
Mean8.9654
Median Absolute Deviation (MAD)0
Skewness2.4155053
Sum89654
Variance30.645267
MonotonicityNot monotonic
2024-05-11T16:04:02.572776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
13 5714
57.1%
3 4147
41.5%
24 64
 
0.6%
15 51
 
0.5%
2 18
 
0.2%
99 6
 
0.1%
ValueCountFrequency (%)
2 18
 
0.2%
3 4147
41.5%
13 5714
57.1%
15 51
 
0.5%
24 64
 
0.6%
99 6
 
0.1%
ValueCountFrequency (%)
99 6
 
0.1%
24 64
 
0.6%
15 51
 
0.5%
13 5714
57.1%
3 4147
41.5%
2 18
 
0.2%

상세영업상태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업중
5714 
폐업
4147 
직권폐업
 
64
전출
 
51
휴업
 
18

Length

Max length4
Median length3
Mean length2.5842
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업중
2nd row영업중
3rd row영업중
4th row영업중
5th row폐업

Common Values

ValueCountFrequency (%)
영업중 5714
57.1%
폐업 4147
41.5%
직권폐업 64
 
0.6%
전출 51
 
0.5%
휴업 18
 
0.2%
삭제 6
 
0.1%

Length

2024-05-11T16:04:02.796216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:04:02.989689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 5714
57.1%
폐업 4147
41.5%
직권폐업 64
 
0.6%
전출 51
 
0.5%
휴업 18
 
0.2%
삭제 6
 
0.1%

폐업일자
Date

MISSING 

Distinct2827
Distinct (%)71.3%
Missing6034
Missing (%)60.3%
Memory size156.2 KiB
Minimum1983-01-26 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T16:04:03.201491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:04:03.527061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct100
Distinct (%)99.0%
Missing9899
Missing (%)99.0%
Memory size156.2 KiB
Minimum2008-01-01 00:00:00
Maximum2024-05-01 00:00:00
2024-05-11T16:04:03.855766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:04:04.173149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Date

MISSING 

Distinct93
Distinct (%)93.0%
Missing9900
Missing (%)99.0%
Memory size156.2 KiB
Minimum2008-06-30 00:00:00
Maximum2027-11-16 00:00:00
2024-05-11T16:04:04.404941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:04:04.628471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct8965
Distinct (%)96.1%
Missing670
Missing (%)6.7%
Memory size156.2 KiB
2024-05-11T16:04:05.128138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length10.56463
Min length3

Characters and Unicode

Total characters98568
Distinct characters19
Distinct categories7 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8644 ?
Unique (%)92.6%

Sample

1st row909-4500
2nd row02-846-1800
3rd row02-859-2887
4th row02-861-4658
5th row852-5575
ValueCountFrequency (%)
02 7
 
0.1%
979-2226 4
 
< 0.1%
909-0501 4
 
< 0.1%
02-356-0022 4
 
< 0.1%
930-7191 3
 
< 0.1%
2247-2872 3
 
< 0.1%
02-303-8234 3
 
< 0.1%
935-2879 3
 
< 0.1%
913-2275 3
 
< 0.1%
02-956-5533 3
 
< 0.1%
Other values (8955) 9295
99.6%
2024-05-11T16:04:05.855064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16307
16.5%
- 15914
16.1%
0 13487
13.7%
5 8275
8.4%
7 7899
8.0%
8 7112
7.2%
3 7106
7.2%
6 6003
 
6.1%
9 5989
 
6.1%
1 5463
 
5.5%
Other values (9) 5013
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82601
83.8%
Dash Punctuation 15914
 
16.1%
Math Symbol 23
 
< 0.1%
Other Punctuation 14
 
< 0.1%
Close Punctuation 12
 
< 0.1%
Space Separator 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 16307
19.7%
0 13487
16.3%
5 8275
10.0%
7 7899
9.6%
8 7112
8.6%
3 7106
8.6%
6 6003
 
7.3%
9 5989
 
7.3%
1 5463
 
6.6%
4 4960
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 10
71.4%
. 2
 
14.3%
* 1
 
7.1%
/ 1
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 15914
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98568
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 16307
16.5%
- 15914
16.1%
0 13487
13.7%
5 8275
8.4%
7 7899
8.0%
8 7112
7.2%
3 7106
7.2%
6 6003
 
6.1%
9 5989
 
6.1%
1 5463
 
5.5%
Other values (9) 5013
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16307
16.5%
- 15914
16.1%
0 13487
13.7%
5 8275
8.4%
7 7899
8.0%
8 7112
7.2%
3 7106
7.2%
6 6003
 
6.1%
9 5989
 
6.1%
1 5463
 
5.5%
Other values (9) 5013
 
5.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

소재지우편번호
Text

MISSING 

Distinct2110
Distinct (%)45.2%
Missing5327
Missing (%)53.3%
Memory size156.2 KiB
2024-05-11T16:04:06.426780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0528568
Min length3

Characters and Unicode

Total characters28285
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

Unique1217 ?
Unique (%)26.0%

Sample

1st row139841
2nd row150833
3rd row153813
4th row110122
5th row133-071
ValueCountFrequency (%)
130864 52
 
1.1%
139200 33
 
0.7%
130060 32
 
0.7%
139241 30
 
0.6%
139202 25
 
0.5%
139207 24
 
0.5%
139203 23
 
0.5%
139206 21
 
0.4%
121807 21
 
0.4%
139832 20
 
0.4%
Other values (2100) 4392
94.0%
2024-05-11T16:04:07.169397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6905
24.4%
0 3977
14.1%
3 3363
11.9%
8 3264
11.5%
2 2595
 
9.2%
5 2270
 
8.0%
4 1456
 
5.1%
7 1354
 
4.8%
9 1336
 
4.7%
6 1122
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27642
97.7%
Dash Punctuation 643
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6905
25.0%
0 3977
14.4%
3 3363
12.2%
8 3264
11.8%
2 2595
 
9.4%
5 2270
 
8.2%
4 1456
 
5.3%
7 1354
 
4.9%
9 1336
 
4.8%
6 1122
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 643
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28285
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6905
24.4%
0 3977
14.1%
3 3363
11.9%
8 3264
11.5%
2 2595
 
9.2%
5 2270
 
8.0%
4 1456
 
5.1%
7 1354
 
4.8%
9 1336
 
4.7%
6 1122
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28285
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6905
24.4%
0 3977
14.1%
3 3363
11.9%
8 3264
11.5%
2 2595
 
9.2%
5 2270
 
8.0%
4 1456
 
5.1%
7 1354
 
4.8%
9 1336
 
4.7%
6 1122
 
4.0%

지번주소
Text

MISSING 

Distinct8323
Distinct (%)92.9%
Missing1038
Missing (%)10.4%
Memory size156.2 KiB
2024-05-11T16:04:07.627860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length56
Mean length25.732203
Min length3

Characters and Unicode

Total characters230612
Distinct characters588
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7827 ?
Unique (%)87.3%

Sample

1st row서울특별시 노원구 월계동 50번지 29호
2nd row서울특별시 영등포구 도림동 246번지 20호
3rd row서울특별시 구로구 구로동 141번지 5호 인성빌딩
4th row서울특별시 구로구 구로동 106번지 8호 신원빌딩
5th row서울특별시 금천구 독산동 295번지 10호 롯데빅마켓 금천점 4층
ValueCountFrequency (%)
서울특별시 8351
 
17.7%
2층 845
 
1.8%
영등포구 836
 
1.8%
1호 751
 
1.6%
3층 522
 
1.1%
강남구 472
 
1.0%
강서구 465
 
1.0%
동대문구 434
 
0.9%
노원구 429
 
0.9%
은평구 399
 
0.8%
Other values (7827) 33625
71.3%
2024-05-11T16:04:08.285417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38953
 
16.9%
10292
 
4.5%
10093
 
4.4%
1 9487
 
4.1%
9265
 
4.0%
8829
 
3.8%
8699
 
3.8%
8383
 
3.6%
8378
 
3.6%
2 7648
 
3.3%
Other values (578) 110585
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137957
59.8%
Decimal Number 48107
 
20.9%
Space Separator 38953
 
16.9%
Dash Punctuation 2817
 
1.2%
Other Punctuation 834
 
0.4%
Uppercase Letter 642
 
0.3%
Close Punctuation 555
 
0.2%
Open Punctuation 555
 
0.2%
Lowercase Letter 102
 
< 0.1%
Math Symbol 80
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10292
 
7.5%
10093
 
7.3%
9265
 
6.7%
8829
 
6.4%
8699
 
6.3%
8383
 
6.1%
8378
 
6.1%
6305
 
4.6%
6211
 
4.5%
5808
 
4.2%
Other values (508) 55694
40.4%
Uppercase Letter
ValueCountFrequency (%)
B 75
 
11.7%
A 72
 
11.2%
S 58
 
9.0%
K 51
 
7.9%
T 47
 
7.3%
D 37
 
5.8%
C 31
 
4.8%
L 29
 
4.5%
E 28
 
4.4%
W 26
 
4.0%
Other values (14) 188
29.3%
Lowercase Letter
ValueCountFrequency (%)
e 19
18.6%
a 12
11.8%
o 11
10.8%
l 7
 
6.9%
n 7
 
6.9%
v 6
 
5.9%
r 6
 
5.9%
u 5
 
4.9%
g 4
 
3.9%
i 4
 
3.9%
Other values (9) 21
20.6%
Decimal Number
ValueCountFrequency (%)
1 9487
19.7%
2 7648
15.9%
3 6217
12.9%
4 4568
9.5%
0 4165
8.7%
5 4035
8.4%
6 3711
 
7.7%
7 3144
 
6.5%
8 2618
 
5.4%
9 2514
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 725
86.9%
. 54
 
6.5%
/ 22
 
2.6%
@ 18
 
2.2%
& 9
 
1.1%
? 6
 
0.7%
Letter Number
ValueCountFrequency (%)
7
70.0%
2
 
20.0%
1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 552
99.5%
] 3
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 551
99.3%
[ 4
 
0.7%
Math Symbol
ValueCountFrequency (%)
~ 79
98.8%
+ 1
 
1.2%
Space Separator
ValueCountFrequency (%)
38953
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2817
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137957
59.8%
Common 91901
39.9%
Latin 754
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10292
 
7.5%
10093
 
7.3%
9265
 
6.7%
8829
 
6.4%
8699
 
6.3%
8383
 
6.1%
8378
 
6.1%
6305
 
4.6%
6211
 
4.5%
5808
 
4.2%
Other values (508) 55694
40.4%
Latin
ValueCountFrequency (%)
B 75
 
9.9%
A 72
 
9.5%
S 58
 
7.7%
K 51
 
6.8%
T 47
 
6.2%
D 37
 
4.9%
C 31
 
4.1%
L 29
 
3.8%
E 28
 
3.7%
W 26
 
3.4%
Other values (36) 300
39.8%
Common
ValueCountFrequency (%)
38953
42.4%
1 9487
 
10.3%
2 7648
 
8.3%
3 6217
 
6.8%
4 4568
 
5.0%
0 4165
 
4.5%
5 4035
 
4.4%
6 3711
 
4.0%
7 3144
 
3.4%
- 2817
 
3.1%
Other values (14) 7156
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137957
59.8%
ASCII 92645
40.2%
Number Forms 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38953
42.0%
1 9487
 
10.2%
2 7648
 
8.3%
3 6217
 
6.7%
4 4568
 
4.9%
0 4165
 
4.5%
5 4035
 
4.4%
6 3711
 
4.0%
7 3144
 
3.4%
- 2817
 
3.0%
Other values (57) 7900
 
8.5%
Hangul
ValueCountFrequency (%)
10292
 
7.5%
10093
 
7.3%
9265
 
6.7%
8829
 
6.4%
8699
 
6.3%
8383
 
6.1%
8378
 
6.1%
6305
 
4.6%
6211
 
4.5%
5808
 
4.2%
Other values (508) 55694
40.4%
Number Forms
ValueCountFrequency (%)
7
70.0%
2
 
20.0%
1
 
10.0%

도로명주소
Text

MISSING 

Distinct7905
Distinct (%)96.9%
Missing1839
Missing (%)18.4%
Memory size156.2 KiB
2024-05-11T16:04:08.850736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length61
Mean length32.546012
Min length14

Characters and Unicode

Total characters265608
Distinct characters632
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7677 ?
Unique (%)94.1%

Sample

1st row서울특별시 노원구 화랑로 325, 3층 (월계동, 우현빌딩)
2nd row서울특별시 영등포구 도림로 331 (도림동)
3rd row서울특별시 구로구 도림로 73, 인성빌딩 2층 (구로동)
4th row서울특별시 구로구 가마산로27길 14, 신원빌딩 2층 (구로동)
5th row서울특별시 금천구 두산로 71 (독산동, 롯데빅마켓 금천점 4층)
ValueCountFrequency (%)
서울특별시 8160
 
15.5%
2층 1628
 
3.1%
3층 982
 
1.9%
4층 548
 
1.0%
강남구 528
 
1.0%
영등포구 520
 
1.0%
강서구 507
 
1.0%
마포구 429
 
0.8%
노원구 413
 
0.8%
서초구 379
 
0.7%
Other values (7027) 38680
73.3%
2024-05-11T16:04:09.477798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44634
 
16.8%
10428
 
3.9%
10183
 
3.8%
, 9836
 
3.7%
9208
 
3.5%
8863
 
3.3%
8504
 
3.2%
) 8277
 
3.1%
( 8276
 
3.1%
8232
 
3.1%
Other values (622) 139167
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151994
57.2%
Space Separator 44634
 
16.8%
Decimal Number 40596
 
15.3%
Other Punctuation 9887
 
3.7%
Close Punctuation 8277
 
3.1%
Open Punctuation 8276
 
3.1%
Uppercase Letter 864
 
0.3%
Dash Punctuation 678
 
0.3%
Math Symbol 259
 
0.1%
Lowercase Letter 133
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10428
 
6.9%
10183
 
6.7%
9208
 
6.1%
8863
 
5.8%
8504
 
5.6%
8232
 
5.4%
8168
 
5.4%
8160
 
5.4%
5228
 
3.4%
2584
 
1.7%
Other values (550) 72436
47.7%
Uppercase Letter
ValueCountFrequency (%)
B 124
14.4%
A 92
 
10.6%
S 71
 
8.2%
C 58
 
6.7%
T 53
 
6.1%
K 51
 
5.9%
E 43
 
5.0%
L 43
 
5.0%
I 39
 
4.5%
M 37
 
4.3%
Other values (15) 253
29.3%
Lowercase Letter
ValueCountFrequency (%)
e 31
23.3%
a 11
 
8.3%
o 11
 
8.3%
n 10
 
7.5%
r 9
 
6.8%
l 9
 
6.8%
u 6
 
4.5%
i 5
 
3.8%
g 5
 
3.8%
v 5
 
3.8%
Other values (10) 31
23.3%
Decimal Number
ValueCountFrequency (%)
2 7713
19.0%
1 7288
18.0%
3 5674
14.0%
0 4196
10.3%
4 4021
9.9%
5 3127
7.7%
6 2610
 
6.4%
7 2231
 
5.5%
8 1919
 
4.7%
9 1817
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 9836
99.5%
. 27
 
0.3%
& 9
 
0.1%
/ 5
 
0.1%
* 4
 
< 0.1%
? 3
 
< 0.1%
@ 2
 
< 0.1%
: 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
6
60.0%
2
 
20.0%
2
 
20.0%
Math Symbol
ValueCountFrequency (%)
~ 258
99.6%
+ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
44634
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8277
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8276
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 678
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151994
57.2%
Common 112607
42.4%
Latin 1007
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10428
 
6.9%
10183
 
6.7%
9208
 
6.1%
8863
 
5.8%
8504
 
5.6%
8232
 
5.4%
8168
 
5.4%
8160
 
5.4%
5228
 
3.4%
2584
 
1.7%
Other values (550) 72436
47.7%
Latin
ValueCountFrequency (%)
B 124
 
12.3%
A 92
 
9.1%
S 71
 
7.1%
C 58
 
5.8%
T 53
 
5.3%
K 51
 
5.1%
E 43
 
4.3%
L 43
 
4.3%
I 39
 
3.9%
M 37
 
3.7%
Other values (38) 396
39.3%
Common
ValueCountFrequency (%)
44634
39.6%
, 9836
 
8.7%
) 8277
 
7.4%
( 8276
 
7.3%
2 7713
 
6.8%
1 7288
 
6.5%
3 5674
 
5.0%
0 4196
 
3.7%
4 4021
 
3.6%
5 3127
 
2.8%
Other values (14) 9565
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151994
57.2%
ASCII 113604
42.8%
Number Forms 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44634
39.3%
, 9836
 
8.7%
) 8277
 
7.3%
( 8276
 
7.3%
2 7713
 
6.8%
1 7288
 
6.4%
3 5674
 
5.0%
0 4196
 
3.7%
4 4021
 
3.5%
5 3127
 
2.8%
Other values (59) 10562
 
9.3%
Hangul
ValueCountFrequency (%)
10428
 
6.9%
10183
 
6.7%
9208
 
6.1%
8863
 
5.8%
8504
 
5.6%
8232
 
5.4%
8168
 
5.4%
8160
 
5.4%
5228
 
3.4%
2584
 
1.7%
Other values (550) 72436
47.7%
Number Forms
ValueCountFrequency (%)
6
60.0%
2
 
20.0%
2
 
20.0%

도로명우편번호
Text

MISSING 

Distinct2777
Distinct (%)36.0%
Missing2293
Missing (%)22.9%
Memory size156.2 KiB
2024-05-11T16:04:09.857920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.075386
Min length5

Characters and Unicode

Total characters39116
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

Unique1264 ?
Unique (%)16.4%

Sample

1st row01904
2nd row07374
3rd row08312
4th row08298
5th row153813
ValueCountFrequency (%)
01751 42
 
0.5%
07803 29
 
0.4%
07008 27
 
0.4%
07639 26
 
0.3%
02570 26
 
0.3%
06612 25
 
0.3%
01762 24
 
0.3%
07946 24
 
0.3%
04050 21
 
0.3%
06035 20
 
0.3%
Other values (2767) 7443
96.6%
2024-05-11T16:04:10.404893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10167
26.0%
1 3860
 
9.9%
7 3815
 
9.8%
3 3695
 
9.4%
2 3174
 
8.1%
6 3152
 
8.1%
4 3138
 
8.0%
5 3116
 
8.0%
8 3102
 
7.9%
9 1894
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39113
> 99.9%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10167
26.0%
1 3860
 
9.9%
7 3815
 
9.8%
3 3695
 
9.4%
2 3174
 
8.1%
6 3152
 
8.1%
4 3138
 
8.0%
5 3116
 
8.0%
8 3102
 
7.9%
9 1894
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39116
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10167
26.0%
1 3860
 
9.9%
7 3815
 
9.8%
3 3695
 
9.4%
2 3174
 
8.1%
6 3152
 
8.1%
4 3138
 
8.0%
5 3116
 
8.0%
8 3102
 
7.9%
9 1894
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39116
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10167
26.0%
1 3860
 
9.9%
7 3815
 
9.8%
3 3695
 
9.4%
2 3174
 
8.1%
6 3152
 
8.1%
4 3138
 
8.0%
5 3116
 
8.0%
8 3102
 
7.9%
9 1894
 
4.8%
Distinct8250
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T16:04:10.702181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length7.3614
Min length3

Characters and Unicode

Total characters73614
Distinct characters744
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7256 ?
Unique (%)72.6%

Sample

1st row문비뇨기과의원
2nd row도림한의원
3rd row엠케이(MK)비뇨기과의원
4th row(의)열린의료재단오경식의원
5th row연세베스트의원
ValueCountFrequency (%)
경희한의원 17
 
0.2%
한의원 16
 
0.2%
치과의원 15
 
0.1%
서울의원 14
 
0.1%
연세이비인후과의원 12
 
0.1%
의원 12
 
0.1%
이사랑치과의원 11
 
0.1%
의료법인 11
 
0.1%
우리의원 10
 
0.1%
연세치과의원 10
 
0.1%
Other values (8324) 10077
98.7%
2024-05-11T16:04:11.180403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10736
 
14.6%
10209
 
13.9%
5975
 
8.1%
2788
 
3.8%
2563
 
3.5%
1315
 
1.8%
1030
 
1.4%
1000
 
1.4%
905
 
1.2%
840
 
1.1%
Other values (734) 36253
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72661
98.7%
Decimal Number 270
 
0.4%
Space Separator 205
 
0.3%
Uppercase Letter 147
 
0.2%
Close Punctuation 114
 
0.2%
Open Punctuation 111
 
0.2%
Lowercase Letter 61
 
0.1%
Other Punctuation 34
 
< 0.1%
Dash Punctuation 9
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10736
 
14.8%
10209
 
14.1%
5975
 
8.2%
2788
 
3.8%
2563
 
3.5%
1315
 
1.8%
1030
 
1.4%
1000
 
1.4%
905
 
1.2%
840
 
1.2%
Other values (670) 35300
48.6%
Uppercase Letter
ValueCountFrequency (%)
S 28
19.0%
M 14
 
9.5%
K 12
 
8.2%
D 12
 
8.2%
C 10
 
6.8%
U 6
 
4.1%
L 6
 
4.1%
N 6
 
4.1%
T 6
 
4.1%
W 5
 
3.4%
Other values (13) 42
28.6%
Lowercase Letter
ValueCountFrequency (%)
e 26
42.6%
m 7
 
11.5%
r 6
 
9.8%
o 3
 
4.9%
a 2
 
3.3%
n 2
 
3.3%
y 2
 
3.3%
s 2
 
3.3%
c 2
 
3.3%
w 2
 
3.3%
Other values (7) 7
 
11.5%
Decimal Number
ValueCountFrequency (%)
3 73
27.0%
5 69
25.6%
6 68
25.2%
1 17
 
6.3%
2 11
 
4.1%
0 10
 
3.7%
4 9
 
3.3%
8 7
 
2.6%
7 4
 
1.5%
9 2
 
0.7%
Other Punctuation
ValueCountFrequency (%)
& 11
32.4%
. 9
26.5%
? 8
23.5%
, 4
 
11.8%
1
 
2.9%
: 1
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 113
99.1%
] 1
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 110
99.1%
[ 1
 
0.9%
Space Separator
ValueCountFrequency (%)
205
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72655
98.7%
Common 745
 
1.0%
Latin 208
 
0.3%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10736
 
14.8%
10209
 
14.1%
5975
 
8.2%
2788
 
3.8%
2563
 
3.5%
1315
 
1.8%
1030
 
1.4%
1000
 
1.4%
905
 
1.2%
840
 
1.2%
Other values (665) 35294
48.6%
Latin
ValueCountFrequency (%)
S 28
 
13.5%
e 26
 
12.5%
M 14
 
6.7%
K 12
 
5.8%
D 12
 
5.8%
C 10
 
4.8%
m 7
 
3.4%
U 6
 
2.9%
L 6
 
2.9%
N 6
 
2.9%
Other values (30) 81
38.9%
Common
ValueCountFrequency (%)
205
27.5%
) 113
15.2%
( 110
14.8%
3 73
 
9.8%
5 69
 
9.3%
6 68
 
9.1%
1 17
 
2.3%
2 11
 
1.5%
& 11
 
1.5%
0 10
 
1.3%
Other values (14) 58
 
7.8%
Han
ValueCountFrequency (%)
2
33.3%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72655
98.7%
ASCII 951
 
1.3%
CJK 6
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
10736
 
14.8%
10209
 
14.1%
5975
 
8.2%
2788
 
3.8%
2563
 
3.5%
1315
 
1.8%
1030
 
1.4%
1000
 
1.4%
905
 
1.2%
840
 
1.2%
Other values (665) 35294
48.6%
ASCII
ValueCountFrequency (%)
205
21.6%
) 113
11.9%
( 110
11.6%
3 73
 
7.7%
5 69
 
7.3%
6 68
 
7.2%
S 28
 
2.9%
e 26
 
2.7%
1 17
 
1.8%
M 14
 
1.5%
Other values (52) 228
24.0%
CJK
ValueCountFrequency (%)
2
33.3%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
None
ValueCountFrequency (%)
1
50.0%
´ 1
50.0%
Distinct8232
Distinct (%)82.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2008-07-31 13:47:43
Maximum2024-05-09 23:43:40
2024-05-11T16:04:11.323878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:04:11.463993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
U
5605 
I
4392 
D
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowU
3rd rowI
4th rowU
5th rowI

Common Values

ValueCountFrequency (%)
U 5605
56.0%
I 4392
43.9%
D 3
 
< 0.1%

Length

2024-05-11T16:04:11.595493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:04:11.690703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 5605
56.0%
i 4392
43.9%
d 3
 
< 0.1%
Distinct1224
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T16:04:12.081571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:04:12.246578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
의원
5157 
치과의원
2490 
한의원
2333 
보건소
 
10
보건지소
 
6

Length

Max length4
Median length2
Mean length2.7339
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
의원 5157
51.6%
치과의원 2490
24.9%
한의원 2333
23.3%
보건소 10
 
0.1%
보건지소 6
 
0.1%
조산원 4
 
< 0.1%

Length

2024-05-11T16:04:12.422033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:04:12.548599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의원 5157
51.6%
치과의원 2490
24.9%
한의원 2333
23.3%
보건소 10
 
0.1%
보건지소 6
 
0.1%
조산원 4
 
< 0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct5542
Distinct (%)69.2%
Missing1995
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean198158.88
Minimum182141.21
Maximum273347.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:04:12.682342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile186147.36
Q1192526.78
median198637.35
Q3203634.62
95-th percentile208112.86
Maximum273347.08
Range91205.871
Interquartile range (IQR)11107.839

Descriptive statistics

Standard deviation7068.6427
Coefficient of variation (CV)0.035671592
Kurtosis0.60396633
Mean198158.88
Median Absolute Deviation (MAD)5658.4338
Skewness0.0043654749
Sum1.5862618 × 109
Variance49965710
MonotonicityNot monotonic
2024-05-11T16:04:12.847359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202173.486849488 10
 
0.1%
204089.817117361 10
 
0.1%
198150.300374121 10
 
0.1%
193306.330043669 9
 
0.1%
190005.132500398 9
 
0.1%
205489.761880316 8
 
0.1%
190125.564768858 8
 
0.1%
195196.693652181 8
 
0.1%
190858.649482406 8
 
0.1%
208051.884671132 8
 
0.1%
Other values (5532) 7917
79.2%
(Missing) 1995
 
20.0%
ValueCountFrequency (%)
182141.205465089 1
< 0.1%
182524.823835629 1
< 0.1%
182876.367858149 2
< 0.1%
182908.975451896 1
< 0.1%
183039.073279899 1
< 0.1%
183039.079934909 1
< 0.1%
183110.235307185 1
< 0.1%
183166.343309141 1
< 0.1%
183215.243871182 2
< 0.1%
183227.963853126 1
< 0.1%
ValueCountFrequency (%)
273347.076619373 1
 
< 0.1%
215487.94428281 1
 
< 0.1%
215466.920457331 1
 
< 0.1%
215401.064224577 1
 
< 0.1%
215314.746342111 1
 
< 0.1%
215257.766510608 1
 
< 0.1%
215178.151836179 1
 
< 0.1%
214860.734709632 2
< 0.1%
214859.432267306 1
 
< 0.1%
214695.292858761 4
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct5541
Distinct (%)69.2%
Missing1995
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean449861.92
Minimum390832.68
Maximum465103.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:04:12.987797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum390832.68
5-th percentile442035.58
Q1445445.19
median449695.09
Q3453227.28
95-th percentile460644.64
Maximum465103.76
Range74271.071
Interquartile range (IQR)7782.0944

Descriptive statistics

Standard deviation5584.5884
Coefficient of variation (CV)0.012414006
Kurtosis1.0035087
Mean449861.92
Median Absolute Deviation (MAD)3942.8695
Skewness0.22282384
Sum3.6011447 × 109
Variance31187628
MonotonicityNot monotonic
2024-05-11T16:04:13.175390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444369.925403887 10
 
0.1%
452019.212642931 10
 
0.1%
453314.135663101 10
 
0.1%
446582.782311218 9
 
0.1%
445250.538868558 9
 
0.1%
453764.706268517 8
 
0.1%
450884.0 8
 
0.1%
447246.938313599 8
 
0.1%
440808.541334678 8
 
0.1%
447994.805558304 8
 
0.1%
Other values (5531) 7917
79.2%
(Missing) 1995
 
20.0%
ValueCountFrequency (%)
390832.684562684 1
 
< 0.1%
436946.358720615 1
 
< 0.1%
437689.38449215 1
 
< 0.1%
437777.824339474 1
 
< 0.1%
437792.713058127 1
 
< 0.1%
437914.06299827 1
 
< 0.1%
438012.1279662 1
 
< 0.1%
438307.022609784 2
< 0.1%
438418.0 1
 
< 0.1%
438460.667319682 3
< 0.1%
ValueCountFrequency (%)
465103.755134816 1
< 0.1%
464973.884141836 1
< 0.1%
464964.284423079 1
< 0.1%
464959.058464501 2
< 0.1%
464814.717432497 1
< 0.1%
464638.133327247 1
< 0.1%
464633.761055876 2
< 0.1%
464597.202705501 1
< 0.1%
464591.516973411 1
< 0.1%
464448.684446374 2
< 0.1%
Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
3836 
의원
3091 
치과의원
1734 
한의원
1325 
보건소
 
8
Other values (2)
 
6

Length

Max length4
Median length4
Mean length3.2483
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의원
2nd row한의원
3rd row의원
4th row<NA>
5th row의원

Common Values

ValueCountFrequency (%)
<NA> 3836
38.4%
의원 3091
30.9%
치과의원 1734
17.3%
한의원 1325
 
13.2%
보건소 8
 
0.1%
보건지소 4
 
< 0.1%
조산원 2
 
< 0.1%

Length

2024-05-11T16:04:13.360356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:04:13.533663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3836
38.4%
의원 3091
30.9%
치과의원 1734
17.3%
한의원 1325
 
13.2%
보건소 8
 
0.1%
보건지소 4
 
< 0.1%
조산원 2
 
< 0.1%

의료인수
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)0.3%
Missing3836
Missing (%)38.4%
Infinite0
Infinite (%)0.0%
Mean1.1022064
Minimum0
Maximum38
Zeros813
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:04:13.690828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum38
Range38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2185761
Coefficient of variation (CV)1.1055789
Kurtosis338.38247
Mean1.1022064
Median Absolute Deviation (MAD)0
Skewness14.512091
Sum6794
Variance1.4849278
MonotonicityNot monotonic
2024-05-11T16:04:13.847123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 4498
45.0%
0 813
 
8.1%
2 651
 
6.5%
3 113
 
1.1%
4 40
 
0.4%
5 12
 
0.1%
6 11
 
0.1%
7 6
 
0.1%
9 3
 
< 0.1%
8 3
 
< 0.1%
Other values (11) 14
 
0.1%
(Missing) 3836
38.4%
ValueCountFrequency (%)
0 813
 
8.1%
1 4498
45.0%
2 651
 
6.5%
3 113
 
1.1%
4 40
 
0.4%
5 12
 
0.1%
6 11
 
0.1%
7 6
 
0.1%
8 3
 
< 0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
38 1
< 0.1%
36 1
< 0.1%
26 1
< 0.1%
24 1
< 0.1%
22 1
< 0.1%
21 1
< 0.1%
18 1
< 0.1%
16 2
< 0.1%
14 1
< 0.1%
12 1
< 0.1%

입원실수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)0.3%
Missing3836
Missing (%)38.4%
Infinite0
Infinite (%)0.0%
Mean0.22615185
Minimum0
Maximum27
Zeros5840
Zeros (%)58.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:04:14.011504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum27
Range27
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2999547
Coefficient of variation (CV)5.7481498
Kurtosis99.375912
Mean0.22615185
Median Absolute Deviation (MAD)0
Skewness8.5337798
Sum1394
Variance1.6898823
MonotonicityNot monotonic
2024-05-11T16:04:14.159994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 5840
58.4%
1 101
 
1.0%
2 36
 
0.4%
3 34
 
0.3%
4 31
 
0.3%
8 25
 
0.2%
5 24
 
0.2%
6 20
 
0.2%
7 17
 
0.2%
10 10
 
0.1%
Other values (9) 26
 
0.3%
(Missing) 3836
38.4%
ValueCountFrequency (%)
0 5840
58.4%
1 101
 
1.0%
2 36
 
0.4%
3 34
 
0.3%
4 31
 
0.3%
5 24
 
0.2%
6 20
 
0.2%
7 17
 
0.2%
8 25
 
0.2%
9 9
 
0.1%
ValueCountFrequency (%)
27 1
 
< 0.1%
25 1
 
< 0.1%
20 1
 
< 0.1%
18 1
 
< 0.1%
15 3
 
< 0.1%
13 4
 
< 0.1%
12 2
 
< 0.1%
11 4
 
< 0.1%
10 10
0.1%
9 9
0.1%

병상수
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)0.6%
Missing3836
Missing (%)38.4%
Infinite0
Infinite (%)0.0%
Mean0.64617132
Minimum0
Maximum90
Zeros5804
Zeros (%)58.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:04:14.323283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum90
Range90
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.9320304
Coefficient of variation (CV)6.0851206
Kurtosis101.28165
Mean0.64617132
Median Absolute Deviation (MAD)0
Skewness8.633596
Sum3983
Variance15.460863
MonotonicityNot monotonic
2024-05-11T16:04:14.480412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 5804
58.0%
1 75
 
0.8%
29 43
 
0.4%
2 40
 
0.4%
3 30
 
0.3%
4 30
 
0.3%
6 14
 
0.1%
5 11
 
0.1%
10 10
 
0.1%
7 10
 
0.1%
Other values (25) 97
 
1.0%
(Missing) 3836
38.4%
ValueCountFrequency (%)
0 5804
58.0%
1 75
 
0.8%
2 40
 
0.4%
3 30
 
0.3%
4 30
 
0.3%
5 11
 
0.1%
6 14
 
0.1%
7 10
 
0.1%
8 9
 
0.1%
9 6
 
0.1%
ValueCountFrequency (%)
90 1
 
< 0.1%
70 1
 
< 0.1%
49 2
 
< 0.1%
48 1
 
< 0.1%
45 1
 
< 0.1%
42 1
 
< 0.1%
29 43
0.4%
28 6
 
0.1%
27 3
 
< 0.1%
26 6
 
0.1%

총면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct3682
Distinct (%)59.7%
Missing3836
Missing (%)38.4%
Infinite0
Infinite (%)0.0%
Mean127.74114
Minimum0
Maximum16891
Zeros976
Zeros (%)9.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:04:14.650982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q156.1575
median97.175
Q3148
95-th percentile329.8
Maximum16891
Range16891
Interquartile range (IQR)91.8425

Descriptive statistics

Standard deviation328.39166
Coefficient of variation (CV)2.5707589
Kurtosis1537.061
Mean127.74114
Median Absolute Deviation (MAD)45.825
Skewness34.966236
Sum787396.36
Variance107841.08
MonotonicityNot monotonic
2024-05-11T16:04:14.833453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 976
 
9.8%
30.0 64
 
0.6%
50.0 32
 
0.3%
66.0 26
 
0.3%
132.0 21
 
0.2%
100.0 15
 
0.1%
60.0 15
 
0.1%
165.0 14
 
0.1%
99.0 14
 
0.1%
105.0 14
 
0.1%
Other values (3672) 4973
49.7%
(Missing) 3836
38.4%
ValueCountFrequency (%)
0.0 976
9.8%
1.0 3
 
< 0.1%
7.2 1
 
< 0.1%
10.0 1
 
< 0.1%
10.97 1
 
< 0.1%
12.54 1
 
< 0.1%
12.6 1
 
< 0.1%
14.35 1
 
< 0.1%
15.5 2
 
< 0.1%
17.0 1
 
< 0.1%
ValueCountFrequency (%)
16891.0 1
< 0.1%
12501.0 1
< 0.1%
9162.0 1
< 0.1%
5587.0 1
< 0.1%
3896.95 1
< 0.1%
2822.0 1
< 0.1%
2433.64 1
< 0.1%
1796.21 1
< 0.1%
1739.38 1
< 0.1%
1400.94 1
< 0.1%

진료과목내용
Text

MISSING 

Distinct1436
Distinct (%)23.3%
Missing3837
Missing (%)38.4%
Memory size156.2 KiB
2024-05-11T16:04:15.082166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length103
Median length91
Mean length13.651631
Min length3

Characters and Unicode

Total characters84135
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1171 ?
Unique (%)19.0%

Sample

1st row115 114
2nd row308 307 306 305 304 303 302 301
3rd row115 114
4th row101 111 122 114 105
5th row401
ValueCountFrequency (%)
101 2032
 
9.0%
401 1235
 
5.5%
114 1183
 
5.2%
301 1178
 
5.2%
111 1028
 
4.6%
302 959
 
4.2%
303 950
 
4.2%
308 938
 
4.2%
304 898
 
4.0%
305 890
 
3.9%
Other values (89) 11280
50.0%
2024-05-11T16:04:15.674210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20571
24.4%
0 17550
20.9%
16409
19.5%
3 9944
11.8%
4 7499
 
8.9%
2 4305
 
5.1%
5 2427
 
2.9%
8 1800
 
2.1%
6 1562
 
1.9%
7 1222
 
1.5%
Other values (2) 846
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67725
80.5%
Space Separator 16409
 
19.5%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20571
30.4%
0 17550
25.9%
3 9944
14.7%
4 7499
 
11.1%
2 4305
 
6.4%
5 2427
 
3.6%
8 1800
 
2.7%
6 1562
 
2.3%
7 1222
 
1.8%
9 845
 
1.2%
Space Separator
ValueCountFrequency (%)
16409
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84135
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20571
24.4%
0 17550
20.9%
16409
19.5%
3 9944
11.8%
4 7499
 
8.9%
2 4305
 
5.1%
5 2427
 
2.9%
8 1800
 
2.1%
6 1562
 
1.9%
7 1222
 
1.5%
Other values (2) 846
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20571
24.4%
0 17550
20.9%
16409
19.5%
3 9944
11.8%
4 7499
 
8.9%
2 4305
 
5.1%
5 2427
 
2.9%
8 1800
 
2.1%
6 1562
 
1.9%
7 1222
 
1.5%
Other values (2) 846
 
1.0%

진료과목내용명
Text

MISSING 

Distinct888
Distinct (%)14.4%
Missing3837
Missing (%)38.4%
Memory size156.2 KiB
2024-05-11T16:04:15.942315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length168
Median length141
Mean length22.176375
Min length2

Characters and Unicode

Total characters136673
Distinct characters73
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique623 ?
Unique (%)10.1%

Sample

1st row피부과, 비뇨의학과
2nd row한방내과, 한방부인과, 한방소아과, 한방안?이비인후?피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과
3rd row피부과, 비뇨의학과
4th row내과, 정형외과, 소아청소년과, 피부과, 가정의학과
5th row치과
ValueCountFrequency (%)
내과 2032
 
9.0%
치과 1255
 
5.6%
피부과 1182
 
5.3%
한방내과 1176
 
5.2%
소아청소년과 1028
 
4.6%
한방부인과 957
 
4.3%
한방소아과 948
 
4.2%
침구과 935
 
4.2%
한방안?이비인후?피부과 894
 
4.0%
한방신경정신과 888
 
3.9%
Other values (41) 11194
49.8%
2024-05-11T16:04:16.420446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23765
17.4%
, 16326
 
11.9%
16326
 
11.9%
6357
 
4.7%
5829
 
4.3%
4245
 
3.1%
3601
 
2.6%
3443
 
2.5%
3417
 
2.5%
3150
 
2.3%
Other values (63) 50214
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102233
74.8%
Other Punctuation 18114
 
13.3%
Space Separator 16326
 
11.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
23765
23.2%
6357
 
6.2%
5829
 
5.7%
4245
 
4.2%
3601
 
3.5%
3443
 
3.4%
3417
 
3.3%
3150
 
3.1%
3140
 
3.1%
2980
 
2.9%
Other values (60) 42306
41.4%
Other Punctuation
ValueCountFrequency (%)
, 16326
90.1%
? 1788
 
9.9%
Space Separator
ValueCountFrequency (%)
16326
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102233
74.8%
Common 34440
 
25.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
23765
23.2%
6357
 
6.2%
5829
 
5.7%
4245
 
4.2%
3601
 
3.5%
3443
 
3.4%
3417
 
3.3%
3150
 
3.1%
3140
 
3.1%
2980
 
2.9%
Other values (60) 42306
41.4%
Common
ValueCountFrequency (%)
, 16326
47.4%
16326
47.4%
? 1788
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102233
74.8%
ASCII 34440
 
25.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
23765
23.2%
6357
 
6.2%
5829
 
5.7%
4245
 
4.2%
3601
 
3.5%
3443
 
3.4%
3417
 
3.3%
3150
 
3.1%
3140
 
3.1%
2980
 
2.9%
Other values (60) 42306
41.4%
ASCII
ValueCountFrequency (%)
, 16326
47.4%
16326
47.4%
? 1788
 
5.2%

지정취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

완화의료지정형태
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

완화의료담당부서명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

구급차특수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6164 
<NA>
3836 

Length

Max length4
Median length1
Mean length2.1508
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 6164
61.6%
<NA> 3836
38.4%

Length

2024-05-11T16:04:16.592069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:04:16.731652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6164
61.6%
na 3836
38.4%

구급차일반
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6164 
<NA>
3836 

Length

Max length4
Median length1
Mean length2.1508
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 6164
61.6%
<NA> 3836
38.4%

Length

2024-05-11T16:04:16.871086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:04:17.001024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6164
61.6%
na 3836
38.4%

총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

구조사수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

허가병상수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6164 
<NA>
3836 

Length

Max length4
Median length1
Mean length2.1508
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 6164
61.6%
<NA> 3836
38.4%

Length

2024-05-11T16:04:17.143526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:04:17.300787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6164
61.6%
na 3836
38.4%

최초지정일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료기관종별명의료인수입원실수병상수총면적진료과목내용진료과목내용명지정취소일자완화의료지정형태완화의료담당부서명구급차특수구급차일반총인원구조사수허가병상수최초지정일자
149843100000PHMA11994310003404110002119940402<NA>1영업/정상13영업중<NA><NA><NA><NA>909-4500<NA>139841서울특별시 노원구 월계동 50번지 29호서울특별시 노원구 화랑로 325, 3층 (월계동, 우현빌딩)01904문비뇨기과의원2017-09-05 18:39:08I2018-08-31 23:59:59.0의원205585.595613456954.147371의원100185.0115 114피부과, 비뇨의학과<NA><NA><NA>00<NA><NA>0<NA>
223463180000PHMA11987318003404110002219870902<NA>1영업/정상13영업중<NA><NA><NA><NA>02-846-1800<NA>150833서울특별시 영등포구 도림동 246번지 20호서울특별시 영등포구 도림로 331 (도림동)07374도림한의원2021-12-24 13:37:17U2021-12-26 02:40:00.0한의원191158.211744444991.766553한의원100137.9308 307 306 305 304 303 302 301한방내과, 한방부인과, 한방소아과, 한방안?이비인후?피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과<NA><NA><NA>00<NA><NA>0<NA>
201903160000PHMA11995316003404110046819950508<NA>1영업/정상13영업중<NA><NA><NA><NA>02-859-2887<NA><NA>서울특별시 구로구 구로동 141번지 5호 인성빌딩서울특별시 구로구 도림로 73, 인성빌딩 2층 (구로동)08312엠케이(MK)비뇨기과의원2018-07-26 16:10:35I2018-08-31 23:59:59.0의원190342.202865443095.731206의원100115.5115 114피부과, 비뇨의학과<NA><NA><NA>00<NA><NA>0<NA>
21543160000PHMA1201131600340411000242011-11-16<NA>1영업/정상13영업중<NA><NA><NA><NA>02-861-4658<NA><NA>서울특별시 구로구 구로동 106번지 8호 신원빌딩서울특별시 구로구 가마산로27길 14, 신원빌딩 2층 (구로동)08298(의)열린의료재단오경식의원2024-05-03 01:13:20U2023-12-05 00:05:00.0의원190368.667231443952.558148<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
204973170000PHMA12012317003504110001520120622<NA>3폐업3폐업20130124<NA><NA><NA>852-5575<NA>153813서울특별시 금천구 독산동 295번지 10호 롯데빅마켓 금천점 4층서울특별시 금천구 두산로 71 (독산동, 롯데빅마켓 금천점 4층)153813연세베스트의원2013-01-24 17:00:48I2018-08-31 23:59:59.0의원190704.904313440940.384414의원200109.5101 111 122 114 105내과, 정형외과, 소아청소년과, 피부과, 가정의학과<NA><NA><NA>00<NA><NA>0<NA>
82343200000PHMA1202032000330411000022020-01-28<NA>1영업/정상13영업중<NA><NA><NA><NA>02-882-9998<NA><NA>서울특별시 관악구 봉천동 858번지 6호서울특별시 관악구 관악로 186, 5층 (봉천동)08738서울대입구정형외과의원2024-04-26 03:13:23U2023-12-03 22:08:00.0의원195820.484507442141.851087<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
155953110000PHMA12003311003204110001920030310<NA>3폐업3폐업20031230<NA><NA><NA>02-387-7255<NA><NA>서울특별시 은평구 역촌1동 44번지 33호<NA><NA>한보연치과의원2008-12-15 13:30:48I2018-08-31 23:59:59.0치과의원<NA><NA>치과의원0000.0401치과<NA><NA><NA>00<NA><NA>0<NA>
60463000000PHMA12014300003404110002320140929<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3492-7775<NA><NA>서울특별시 종로구 견지동 110번지 종로1가 대성 스카이렉스서울특별시 종로구 삼봉로 95, 종로1가 대성 스카이렉스 207호 (견지동)03150김산한의원2020-04-06 09:24:07U2020-04-08 02:40:00.0한의원198386.829871452237.303785한의원100125.0301 304 307 308 305 302 303 306 309한방내과, 한방부인과, 한방소아과, 한방안?이비인후?피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과, 한방응급과<NA><NA><NA>00<NA><NA>0<NA>
57843000000PHMA11999300003404110000519990419<NA>1영업/정상13영업중<NA><NA><NA><NA>02-739-9011<NA>110122서울특별시 종로구 종로2가 8번지 4호 2층서울특별시 종로구 종로 65, 2층 (종로2가)03164벨치과의원2017-09-05 18:39:19I2018-08-31 23:59:59.0치과의원198572.839145452022.373156치과의원10047.62401치과<NA><NA><NA>00<NA><NA>0<NA>
89183030000PHMA1201030300330411000152010-10-07<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2282-2080<NA>133-071서울특별시 성동구 행당동 349번지 외 1필지 행당한신아파트상가 305호, 306호, 307호의 일부서울특별시 성동구 고산자로 164, 305, 306, 307(일부)호 (행당동, 행당한신아파트상가)04746서울민트치과의원2023-11-24 00:13:37U2022-10-31 22:06:00.0치과의원203133.802372450318.17446<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료기관종별명의료인수입원실수병상수총면적진료과목내용진료과목내용명지정취소일자완화의료지정형태완화의료담당부서명구급차특수구급차일반총인원구조사수허가병상수최초지정일자
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145963100000PHMA12007310003404110001420070406<NA>3폐업3폐업20150531<NA><NA><NA>903-5647<NA>139848서울특별시 노원구 월계동 600번지 월계주공상가 203호서울특별시 노원구 월계로49길 5 (월계동)139848한양웰빙의원2015-06-03 16:25:30I2018-08-31 23:59:59.0의원204872.498746458540.446276의원100133.08101 106 114 120 109내과, 신경외과, 마취통증의학과, 피부과, 재활의학과<NA><NA><NA>00<NA><NA>0<NA>
151203100000PHMA12017310003404110000820170419<NA>1영업/정상13영업중<NA><NA><NA><NA>02-930-4942<NA><NA>서울특별시 노원구 상계동 746번지 1호서울특별시 노원구 동일로 1371, 302호 (상계동, 현대프라자빌딩)01763박상근신경외과의원2017-09-05 18:39:11I2018-08-31 23:59:59.0의원205324.316308460953.875995의원10043.6122 120 115 114 109 106 105 104 103 102 101내과, 신경과, 정신건강의학과, 외과, 정형외과, 신경외과, 마취통증의학과, 피부과, 비뇨의학과, 재활의학과, 가정의학과<NA><NA><NA>00<NA><NA>0<NA>
64303090000PHMA1199930900330411000231999-08-21<NA>1영업/정상13영업중<NA><NA><NA><NA>02-902-0082<NA><NA><NA>서울특별시 도봉구 도봉로 484, 5,6층 (창동)01454서울정인한의원2023-09-07 17:42:09U2022-12-09 00:09:00.0한의원203023.886823460695.381113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
111073050000PHMA12000305003404110000920000615<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3295-4031<NA><NA>서울특별시 동대문구 이문동 305번지 151호서울특별시 동대문구 휘경로 15, 4층 (이문동)02419정이비인후과의원2017-09-05 18:36:39I2018-08-31 23:59:59.0의원205403.44476454846.056613의원11167.0111 113 108성형외과, 소아청소년과, 이비인후과<NA><NA><NA>00<NA><NA>0<NA>
101553050000PHMA12005305003404110006220050916<NA>3폐업3폐업20090102<NA><NA><NA>02-967-3323<NA>130060서울특별시 동대문구 왕산로 269(제기2동 1051-1)<NA><NA>동명한의원2009-01-02 11:22:57I2018-08-31 23:59:59.0한의원<NA><NA>한의원10042.95301한방내과<NA><NA><NA>00<NA><NA>0<NA>
206163170000PHMA12006317003504110001020060628<NA>1영업/정상13영업중<NA><NA><NA><NA>2027-2875<NA>153776서울특별시 금천구 가산동 680번지 우림라이온스밸리2차 223,224호서울특별시 금천구 가산디지털1로 2, 223,224호 (가산동, 우림라이온스밸리2차)08591서울이안치과의원2021-10-21 20:43:13U2021-10-23 02:40:00.0치과의원190050.903573440523.497478치과의원200135.27401치과<NA><NA><NA>00<NA><NA>0<NA>
192813150000PHMA1200331500370411000072003-03-11<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2696-9119<NA>157-901서울특별시 강서구 화곡동 836번지 5호서울특별시 강서구 곰달래로 223 (화곡동)07749힘찬부성정형외과의원2024-03-22 04:43:24U2023-12-02 22:04:00.0의원187352.4263447743.546305<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
227193190000PHMA12008319003304110001020080312<NA>3폐업3폐업20150302<NA><NA><NA>02-814-0055<NA>156801서울특별시 동작구 노량진동 114번지 5호서울특별시 동작구 노량진로 162 (노량진동)156801미지음성형외과의원2015-03-25 14:42:03I2018-08-31 23:59:59.0의원194972.424068445686.158478의원10098.18108 114성형외과, 피부과<NA><NA><NA>00<NA><NA>0<NA>
52773000000PHMA12004300003404110000120040109<NA>3폐업3폐업20100520<NA><NA><NA>02-742-5612<NA>110850서울특별시 종로구 효제동 89번지 1호서울특별시 종로구 김상옥로 45-1 (효제동)<NA>지성한의원2010-05-20 16:34:05I2018-08-31 23:59:59.0한의원200186.870197452359.774223한의원10078.9301 302 303 304 305 306 307 308한방내과, 한방부인과, 한방소아과, 한방안?이비인후?피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과<NA><NA><NA>00<NA><NA>0<NA>