Overview

Dataset statistics

Number of variables44
Number of observations237
Missing cells3435
Missing cells (%)32.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory88.1 KiB
Average record size in memory380.6 B

Variable types

Numeric21
Text7
DateTime6
Categorical7
Unsupported3

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),임산부정원수,영유아정원수,임산부실면적,영유아실면적,모유수유실면적,급식시설면적,세탁실면적,목욕실면적,조리원화장실면적,사무실면적,간호사수,간호조무사수,영양사수,취사부수,미화원수,기타인원수,건물층수,지상층수,지하층수
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16482/S/1/datasetView.do

Alerts

인허가취소일자 is highly imbalanced (92.4%)Imbalance
폐업일자 has 121 (51.1%) missing valuesMissing
휴업시작일자 has 194 (81.9%) missing valuesMissing
휴업종료일자 has 195 (82.3%) missing valuesMissing
재개업일자 has 237 (100.0%) missing valuesMissing
전화번호 has 48 (20.3%) missing valuesMissing
소재지면적 has 237 (100.0%) missing valuesMissing
소재지우편번호 has 106 (44.7%) missing valuesMissing
지번주소 has 33 (13.9%) missing valuesMissing
도로명주소 has 10 (4.2%) missing valuesMissing
도로명우편번호 has 61 (25.7%) missing valuesMissing
업태구분명 has 237 (100.0%) missing valuesMissing
좌표정보(X) has 11 (4.6%) missing valuesMissing
좌표정보(Y) has 11 (4.6%) missing valuesMissing
임산부정원수 has 71 (30.0%) missing valuesMissing
영유아정원수 has 71 (30.0%) missing valuesMissing
임산부실면적 has 84 (35.4%) missing valuesMissing
영유아실면적 has 83 (35.0%) missing valuesMissing
모유수유실면적 has 127 (53.6%) missing valuesMissing
급식시설면적 has 113 (47.7%) missing valuesMissing
세탁실면적 has 110 (46.4%) missing valuesMissing
목욕실면적 has 146 (61.6%) missing valuesMissing
조리원화장실면적 has 121 (51.1%) missing valuesMissing
사무실면적 has 117 (49.4%) missing valuesMissing
간호사수 has 78 (32.9%) missing valuesMissing
간호조무사수 has 79 (33.3%) missing valuesMissing
취사부수 has 109 (46.0%) missing valuesMissing
미화원수 has 117 (49.4%) missing valuesMissing
기타인원수 has 142 (59.9%) missing valuesMissing
건물층수 has 90 (38.0%) missing valuesMissing
지상층수 has 113 (47.7%) missing valuesMissing
지하층수 has 163 (68.8%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
모유수유실면적 has 14 (5.9%) zerosZeros
급식시설면적 has 6 (2.5%) zerosZeros
세탁실면적 has 5 (2.1%) zerosZeros
목욕실면적 has 15 (6.3%) zerosZeros
조리원화장실면적 has 4 (1.7%) zerosZeros
간호조무사수 has 3 (1.3%) zerosZeros
취사부수 has 5 (2.1%) zerosZeros
미화원수 has 6 (2.5%) zerosZeros
기타인원수 has 27 (11.4%) zerosZeros
건물층수 has 22 (9.3%) zerosZeros
지상층수 has 3 (1.3%) zerosZeros
지하층수 has 21 (8.9%) zerosZeros

Reproduction

Analysis started2024-05-11 00:33:36.689423
Analysis finished2024-05-11 00:33:38.376938
Duration1.69 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3151434.6
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:33:38.569929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3038000
Q13100000
median3160000
Q33220000
95-th percentile3240000
Maximum3240000
Range240000
Interquartile range (IQR)120000

Descriptive statistics

Standard deviation67218.094
Coefficient of variation (CV)0.021329364
Kurtosis-0.93541944
Mean3151434.6
Median Absolute Deviation (MAD)60000
Skewness-0.4438387
Sum7.4689 × 108
Variance4.5182722 × 109
MonotonicityNot monotonic
2024-05-11T00:33:39.074846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 29
 
12.2%
3230000 18
 
7.6%
3150000 17
 
7.2%
3240000 16
 
6.8%
3180000 13
 
5.5%
3100000 13
 
5.5%
3140000 13
 
5.5%
3110000 12
 
5.1%
3160000 11
 
4.6%
3190000 11
 
4.6%
Other values (15) 84
35.4%
ValueCountFrequency (%)
3000000 2
 
0.8%
3010000 5
2.1%
3020000 1
 
0.4%
3030000 4
1.7%
3040000 8
3.4%
3050000 7
3.0%
3060000 8
3.4%
3070000 7
3.0%
3080000 4
1.7%
3090000 6
2.5%
ValueCountFrequency (%)
3240000 16
6.8%
3230000 18
7.6%
3220000 29
12.2%
3210000 8
 
3.4%
3200000 10
 
4.2%
3190000 11
 
4.6%
3180000 13
5.5%
3170000 5
 
2.1%
3160000 11
 
4.6%
3150000 17
7.2%

관리번호
Text

UNIQUE 

Distinct237
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-11T00:33:39.802827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters5925
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

Unique237 ?
Unique (%)100.0%

Sample

1st rowPHMB120143230034042100001
2nd rowPHMB120063240033042100003
3rd rowPHMB120143200033042100001
4th rowPHMB120163050034042100002
5th rowPHMB120113150037042100002
ValueCountFrequency (%)
phmb120143230034042100001 1
 
0.4%
phmb120073190033042100002 1
 
0.4%
phmb119993190033042100001 1
 
0.4%
phmb120063190033042100001 1
 
0.4%
phmb120063190033042100002 1
 
0.4%
phmb120093190033042100001 1
 
0.4%
phmb120143190033042100001 1
 
0.4%
phmb120043190033042100001 1
 
0.4%
phmb120163190033042100001 1
 
0.4%
phmb120103200033042100001 1
 
0.4%
Other values (227) 227
95.8%
2024-05-11T00:33:40.985861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2090
35.3%
1 897
15.1%
2 686
 
11.6%
3 653
 
11.0%
4 392
 
6.6%
P 237
 
4.0%
H 237
 
4.0%
M 237
 
4.0%
B 237
 
4.0%
6 76
 
1.3%
Other values (4) 183
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4977
84.0%
Uppercase Letter 948
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2090
42.0%
1 897
18.0%
2 686
 
13.8%
3 653
 
13.1%
4 392
 
7.9%
6 76
 
1.5%
7 66
 
1.3%
5 44
 
0.9%
9 37
 
0.7%
8 36
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
P 237
25.0%
H 237
25.0%
M 237
25.0%
B 237
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4977
84.0%
Latin 948
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2090
42.0%
1 897
18.0%
2 686
 
13.8%
3 653
 
13.1%
4 392
 
7.9%
6 76
 
1.5%
7 66
 
1.3%
5 44
 
0.9%
9 37
 
0.7%
8 36
 
0.7%
Latin
ValueCountFrequency (%)
P 237
25.0%
H 237
25.0%
M 237
25.0%
B 237
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5925
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2090
35.3%
1 897
15.1%
2 686
 
11.6%
3 653
 
11.0%
4 392
 
6.6%
P 237
 
4.0%
H 237
 
4.0%
M 237
 
4.0%
B 237
 
4.0%
6 76
 
1.3%
Other values (4) 183
 
3.1%
Distinct217
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1986-12-17 00:00:00
Maximum2024-02-19 00:00:00
2024-05-11T00:33:41.864819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:33:42.577453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
232 
20140402
 
1
20140729
 
1
20090306
 
1
20160330
 
1

Length

Max length8
Median length4
Mean length4.0843882
Min length4

Unique

Unique5 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 232
97.9%
20140402 1
 
0.4%
20140729 1
 
0.4%
20090306 1
 
0.4%
20160330 1
 
0.4%
20180213 1
 
0.4%

Length

2024-05-11T00:33:43.160973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:33:43.616714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 232
97.9%
20140402 1
 
0.4%
20140729 1
 
0.4%
20090306 1
 
0.4%
20160330 1
 
0.4%
20180213 1
 
0.4%
Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3
116 
1
115 
2
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 116
48.9%
1 115
48.5%
2 6
 
2.5%

Length

2024-05-11T00:33:44.212959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:33:44.576931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 116
48.9%
1 115
48.5%
2 6
 
2.5%

영업상태명
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
폐업
116 
영업/정상
115 
휴업
 
6

Length

Max length5
Median length2
Mean length3.4556962
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 116
48.9%
영업/정상 115
48.5%
휴업 6
 
2.5%

Length

2024-05-11T00:33:45.218109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:33:45.643411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 116
48.9%
영업/정상 115
48.5%
휴업 6
 
2.5%
Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3
116 
13
115 
2
 
6

Length

Max length2
Median length1
Mean length1.4852321
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row3
3rd row13
4th row13
5th row13

Common Values

ValueCountFrequency (%)
3 116
48.9%
13 115
48.5%
2 6
 
2.5%

Length

2024-05-11T00:33:46.038569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:33:46.379729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 116
48.9%
13 115
48.5%
2 6
 
2.5%
Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
폐업
116 
영업중
115 
휴업
 
6

Length

Max length3
Median length2
Mean length2.4852321
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 116
48.9%
영업중 115
48.5%
휴업 6
 
2.5%

Length

2024-05-11T00:33:46.970841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:33:47.442774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 116
48.9%
영업중 115
48.5%
휴업 6
 
2.5%

폐업일자
Date

MISSING 

Distinct113
Distinct (%)97.4%
Missing121
Missing (%)51.1%
Memory size2.0 KiB
Minimum2007-04-11 00:00:00
Maximum2024-01-25 00:00:00
2024-05-11T00:33:47.916903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:33:48.558564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct43
Distinct (%)100.0%
Missing194
Missing (%)81.9%
Memory size2.0 KiB
Minimum2013-09-10 00:00:00
Maximum2024-04-15 00:00:00
2024-05-11T00:33:49.127927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:33:49.627479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)

휴업종료일자
Date

MISSING 

Distinct42
Distinct (%)100.0%
Missing195
Missing (%)82.3%
Memory size2.0 KiB
Minimum2013-10-27 00:00:00
Maximum2024-12-31 00:00:00
2024-05-11T00:33:50.244930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:33:50.692563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing237
Missing (%)100.0%
Memory size2.2 KiB

전화번호
Text

MISSING 

Distinct187
Distinct (%)98.9%
Missing48
Missing (%)20.3%
Memory size2.0 KiB
2024-05-11T00:33:51.372998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.560847
Min length7

Characters and Unicode

Total characters1996
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)97.9%

Sample

1st row024313535
2nd row02) 475-3350
3rd row02-889-0700
4th row02-2212-2582
5th row02-2659-0031
ValueCountFrequency (%)
02 8
 
4.1%
02-3453-4628 2
 
1.0%
02-439-5400 2
 
1.0%
02-848-3579 1
 
0.5%
884-3579 1
 
0.5%
02-533-6169 1
 
0.5%
558-2053 1
 
0.5%
541-5673 1
 
0.5%
3473-3330 1
 
0.5%
02-833-2227 1
 
0.5%
Other values (178) 178
90.4%
2024-05-11T00:33:52.446973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 328
16.4%
- 299
15.0%
2 295
14.8%
3 186
9.3%
5 171
8.6%
8 139
7.0%
6 123
 
6.2%
1 120
 
6.0%
4 108
 
5.4%
7 106
 
5.3%
Other values (6) 121
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1674
83.9%
Dash Punctuation 299
 
15.0%
Close Punctuation 12
 
0.6%
Space Separator 8
 
0.4%
Other Punctuation 2
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 328
19.6%
2 295
17.6%
3 186
11.1%
5 171
10.2%
8 139
8.3%
6 123
 
7.3%
1 120
 
7.2%
4 108
 
6.5%
7 106
 
6.3%
9 98
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/ 1
50.0%
. 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 299
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1996
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 328
16.4%
- 299
15.0%
2 295
14.8%
3 186
9.3%
5 171
8.6%
8 139
7.0%
6 123
 
6.2%
1 120
 
6.0%
4 108
 
5.4%
7 106
 
5.3%
Other values (6) 121
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 328
16.4%
- 299
15.0%
2 295
14.8%
3 186
9.3%
5 171
8.6%
8 139
7.0%
6 123
 
6.2%
1 120
 
6.0%
4 108
 
5.4%
7 106
 
5.3%
Other values (6) 121
 
6.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing237
Missing (%)100.0%
Memory size2.2 KiB

소재지우편번호
Text

MISSING 

Distinct119
Distinct (%)90.8%
Missing106
Missing (%)44.7%
Memory size2.0 KiB
2024-05-11T00:33:53.098139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0839695
Min length5

Characters and Unicode

Total characters797
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

Unique109 ?
Unique (%)83.2%

Sample

1st row134-866
2nd row157-200
3rd row122-923
4th row143959
5th row153-806
ValueCountFrequency (%)
143916 3
 
2.3%
150038 3
 
2.3%
131881 2
 
1.5%
139816 2
 
1.5%
139803 2
 
1.5%
151015 2
 
1.5%
139-816 2
 
1.5%
138190 2
 
1.5%
135842 2
 
1.5%
157030 2
 
1.5%
Other values (109) 109
83.2%
2024-05-11T00:33:54.237947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 195
24.5%
8 115
14.4%
3 112
14.1%
0 81
10.2%
5 72
 
9.0%
2 54
 
6.8%
4 46
 
5.8%
6 42
 
5.3%
9 35
 
4.4%
7 31
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 783
98.2%
Dash Punctuation 14
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 195
24.9%
8 115
14.7%
3 112
14.3%
0 81
10.3%
5 72
 
9.2%
2 54
 
6.9%
4 46
 
5.9%
6 42
 
5.4%
9 35
 
4.5%
7 31
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 797
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 195
24.5%
8 115
14.4%
3 112
14.1%
0 81
10.2%
5 72
 
9.0%
2 54
 
6.8%
4 46
 
5.8%
6 42
 
5.3%
9 35
 
4.4%
7 31
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 797
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 195
24.5%
8 115
14.4%
3 112
14.1%
0 81
10.2%
5 72
 
9.0%
2 54
 
6.8%
4 46
 
5.8%
6 42
 
5.3%
9 35
 
4.4%
7 31
 
3.9%

지번주소
Text

MISSING 

Distinct198
Distinct (%)97.1%
Missing33
Missing (%)13.9%
Memory size2.0 KiB
2024-05-11T00:33:55.038275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length26.519608
Min length12

Characters and Unicode

Total characters5410
Distinct characters243
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)94.6%

Sample

1st row서울특별시 강동구 천호1동 233번지 34호 인성빌딩 6층
2nd row서울특별시 관악구 봉천동 463-4 메카플러스
3rd row서울특별시 동대문구 답십리동 492번지 2호 9층
4th row서울특별시 강서구 가양동 1480번지 8호
5th row서울특별시 도봉구 창동 731-1 에이치큐브병원
ValueCountFrequency (%)
서울특별시 204
 
17.8%
강남구 25
 
2.2%
1호 23
 
2.0%
송파구 14
 
1.2%
강동구 14
 
1.2%
8호 13
 
1.1%
강서구 13
 
1.1%
2호 12
 
1.0%
3호 12
 
1.0%
양천구 12
 
1.0%
Other values (488) 806
70.2%
2024-05-11T00:33:56.382024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
949
 
17.5%
247
 
4.6%
236
 
4.4%
218
 
4.0%
207
 
3.8%
206
 
3.8%
204
 
3.8%
204
 
3.8%
1 190
 
3.5%
189
 
3.5%
Other values (233) 2560
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3352
62.0%
Decimal Number 1023
 
18.9%
Space Separator 949
 
17.5%
Other Punctuation 29
 
0.5%
Uppercase Letter 22
 
0.4%
Dash Punctuation 21
 
0.4%
Math Symbol 8
 
0.1%
Letter Number 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
247
 
7.4%
236
 
7.0%
218
 
6.5%
207
 
6.2%
206
 
6.1%
204
 
6.1%
204
 
6.1%
189
 
5.6%
182
 
5.4%
175
 
5.2%
Other values (202) 1284
38.3%
Uppercase Letter
ValueCountFrequency (%)
O 3
13.6%
S 3
13.6%
I 2
9.1%
C 2
9.1%
M 2
9.1%
D 2
9.1%
B 2
9.1%
R 2
9.1%
E 1
 
4.5%
W 1
 
4.5%
Other values (2) 2
9.1%
Decimal Number
ValueCountFrequency (%)
1 190
18.6%
2 139
13.6%
3 133
13.0%
6 97
9.5%
4 97
9.5%
5 86
8.4%
7 83
8.1%
8 70
 
6.8%
9 67
 
6.5%
0 61
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 22
75.9%
. 6
 
20.7%
/ 1
 
3.4%
Space Separator
ValueCountFrequency (%)
949
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3352
62.0%
Common 2034
37.6%
Latin 24
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
247
 
7.4%
236
 
7.0%
218
 
6.5%
207
 
6.2%
206
 
6.1%
204
 
6.1%
204
 
6.1%
189
 
5.6%
182
 
5.4%
175
 
5.2%
Other values (202) 1284
38.3%
Common
ValueCountFrequency (%)
949
46.7%
1 190
 
9.3%
2 139
 
6.8%
3 133
 
6.5%
6 97
 
4.8%
4 97
 
4.8%
5 86
 
4.2%
7 83
 
4.1%
8 70
 
3.4%
9 67
 
3.3%
Other values (8) 123
 
6.0%
Latin
ValueCountFrequency (%)
O 3
12.5%
S 3
12.5%
I 2
8.3%
C 2
8.3%
M 2
8.3%
D 2
8.3%
B 2
8.3%
2
8.3%
R 2
8.3%
E 1
 
4.2%
Other values (3) 3
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3352
62.0%
ASCII 2056
38.0%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
949
46.2%
1 190
 
9.2%
2 139
 
6.8%
3 133
 
6.5%
6 97
 
4.7%
4 97
 
4.7%
5 86
 
4.2%
7 83
 
4.0%
8 70
 
3.4%
9 67
 
3.3%
Other values (20) 145
 
7.1%
Hangul
ValueCountFrequency (%)
247
 
7.4%
236
 
7.0%
218
 
6.5%
207
 
6.2%
206
 
6.1%
204
 
6.1%
204
 
6.1%
189
 
5.6%
182
 
5.4%
175
 
5.2%
Other values (202) 1284
38.3%
Number Forms
ValueCountFrequency (%)
2
100.0%

도로명주소
Text

MISSING 

Distinct220
Distinct (%)96.9%
Missing10
Missing (%)4.2%
Memory size2.0 KiB
2024-05-11T00:33:57.476142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length39
Mean length30.066079
Min length17

Characters and Unicode

Total characters6825
Distinct characters281
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique213 ?
Unique (%)93.8%

Sample

1st row서울특별시 송파구 충민로2길 20 (장지동, 송파산모건강증진센터)
2nd row서울특별시 강동구 구천면로 328 (천호동)
3rd row서울특별시 관악구 양녕로 46, 메카플러스 (봉천동)
4th row서울특별시 동대문구 천호대로 317, 9층 (답십리동, 하늘병원)
5th row서울특별시 강서구 양천로 461, 5층 (가양동)
ValueCountFrequency (%)
서울특별시 227
 
16.9%
강남구 29
 
2.2%
송파구 17
 
1.3%
강동구 16
 
1.2%
3층 15
 
1.1%
강서구 14
 
1.0%
영등포구 13
 
1.0%
노원구 13
 
1.0%
은평구 12
 
0.9%
5층 12
 
0.9%
Other values (578) 979
72.7%
2024-05-11T00:33:58.884861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1123
 
16.5%
298
 
4.4%
267
 
3.9%
253
 
3.7%
252
 
3.7%
236
 
3.5%
228
 
3.3%
) 227
 
3.3%
227
 
3.3%
( 227
 
3.3%
Other values (271) 3487
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4082
59.8%
Space Separator 1123
 
16.5%
Decimal Number 916
 
13.4%
Close Punctuation 227
 
3.3%
Open Punctuation 227
 
3.3%
Other Punctuation 189
 
2.8%
Uppercase Letter 30
 
0.4%
Dash Punctuation 15
 
0.2%
Math Symbol 14
 
0.2%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
298
 
7.3%
267
 
6.5%
253
 
6.2%
252
 
6.2%
236
 
5.8%
228
 
5.6%
227
 
5.6%
227
 
5.6%
113
 
2.8%
72
 
1.8%
Other values (240) 1909
46.8%
Uppercase Letter
ValueCountFrequency (%)
D 4
13.3%
S 4
13.3%
E 3
10.0%
O 3
10.0%
M 3
10.0%
C 3
10.0%
I 2
6.7%
B 2
6.7%
H 1
 
3.3%
R 1
 
3.3%
Other values (4) 4
13.3%
Decimal Number
ValueCountFrequency (%)
1 169
18.4%
3 126
13.8%
2 106
11.6%
5 102
11.1%
4 92
10.0%
6 85
9.3%
0 72
7.9%
8 64
 
7.0%
7 62
 
6.8%
9 38
 
4.1%
Space Separator
ValueCountFrequency (%)
1123
100.0%
Close Punctuation
ValueCountFrequency (%)
) 227
100.0%
Open Punctuation
ValueCountFrequency (%)
( 227
100.0%
Other Punctuation
ValueCountFrequency (%)
, 189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4082
59.8%
Common 2711
39.7%
Latin 32
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
298
 
7.3%
267
 
6.5%
253
 
6.2%
252
 
6.2%
236
 
5.8%
228
 
5.6%
227
 
5.6%
227
 
5.6%
113
 
2.8%
72
 
1.8%
Other values (240) 1909
46.8%
Common
ValueCountFrequency (%)
1123
41.4%
) 227
 
8.4%
( 227
 
8.4%
, 189
 
7.0%
1 169
 
6.2%
3 126
 
4.6%
2 106
 
3.9%
5 102
 
3.8%
4 92
 
3.4%
6 85
 
3.1%
Other values (6) 265
 
9.8%
Latin
ValueCountFrequency (%)
D 4
12.5%
S 4
12.5%
E 3
9.4%
O 3
9.4%
M 3
9.4%
C 3
9.4%
I 2
 
6.2%
B 2
 
6.2%
2
 
6.2%
H 1
 
3.1%
Other values (5) 5
15.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4082
59.8%
ASCII 2741
40.2%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1123
41.0%
) 227
 
8.3%
( 227
 
8.3%
, 189
 
6.9%
1 169
 
6.2%
3 126
 
4.6%
2 106
 
3.9%
5 102
 
3.7%
4 92
 
3.4%
6 85
 
3.1%
Other values (20) 295
 
10.8%
Hangul
ValueCountFrequency (%)
298
 
7.3%
267
 
6.5%
253
 
6.2%
252
 
6.2%
236
 
5.8%
228
 
5.6%
227
 
5.6%
227
 
5.6%
113
 
2.8%
72
 
1.8%
Other values (240) 1909
46.8%
Number Forms
ValueCountFrequency (%)
2
100.0%

도로명우편번호
Text

MISSING 

Distinct159
Distinct (%)90.3%
Missing61
Missing (%)25.7%
Memory size2.0 KiB
2024-05-11T00:33:59.721031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0681818
Min length5

Characters and Unicode

Total characters892
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

Unique143 ?
Unique (%)81.2%

Sample

1st row05816
2nd row05309
3rd row08747
4th row02622
5th row07526
ValueCountFrequency (%)
06230 3
 
1.7%
02018 2
 
1.1%
07071 2
 
1.1%
08086 2
 
1.1%
05708 2
 
1.1%
07794 2
 
1.1%
07281 2
 
1.1%
01615 2
 
1.1%
07904 2
 
1.1%
08758 2
 
1.1%
Other values (149) 155
88.1%
2024-05-11T00:34:01.113073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 243
27.2%
5 92
 
10.3%
7 89
 
10.0%
6 82
 
9.2%
8 78
 
8.7%
3 77
 
8.6%
2 75
 
8.4%
1 74
 
8.3%
4 41
 
4.6%
9 40
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 891
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 243
27.3%
5 92
 
10.3%
7 89
 
10.0%
6 82
 
9.2%
8 78
 
8.8%
3 77
 
8.6%
2 75
 
8.4%
1 74
 
8.3%
4 41
 
4.6%
9 40
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 892
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 243
27.2%
5 92
 
10.3%
7 89
 
10.0%
6 82
 
9.2%
8 78
 
8.7%
3 77
 
8.6%
2 75
 
8.4%
1 74
 
8.3%
4 41
 
4.6%
9 40
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 892
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 243
27.2%
5 92
 
10.3%
7 89
 
10.0%
6 82
 
9.2%
8 78
 
8.7%
3 77
 
8.6%
2 75
 
8.4%
1 74
 
8.3%
4 41
 
4.6%
9 40
 
4.5%
Distinct224
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-11T00:34:01.768839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length10.590717
Min length3

Characters and Unicode

Total characters2510
Distinct characters251
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique214 ?
Unique (%)90.3%

Sample

1st row송파산모건강증진센터산후조리원
2nd row임수현 산후조리원
3rd row로얄산후조리원(봉천점)
4th row블리스산후조리원
5th row퀸즈마리 산후조리원(가양점)
ValueCountFrequency (%)
산후조리원 79
 
20.5%
주식회사 8
 
2.1%
4
 
1.0%
동그라미 4
 
1.0%
주)와이케이 4
 
1.0%
로얄사임당산후조리원 4
 
1.0%
라솜산후조리원 3
 
0.8%
vip산후조리원 3
 
0.8%
동그라미산후조리원 3
 
0.8%
행복한 3
 
0.8%
Other values (253) 271
70.2%
2024-05-11T00:34:02.750655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
259
 
10.3%
241
 
9.6%
233
 
9.3%
227
 
9.0%
226
 
9.0%
149
 
5.9%
45
 
1.8%
) 42
 
1.7%
( 42
 
1.7%
41
 
1.6%
Other values (241) 1005
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2244
89.4%
Space Separator 149
 
5.9%
Close Punctuation 42
 
1.7%
Open Punctuation 42
 
1.7%
Uppercase Letter 14
 
0.6%
Lowercase Letter 11
 
0.4%
Decimal Number 4
 
0.2%
Other Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
259
 
11.5%
241
 
10.7%
233
 
10.4%
227
 
10.1%
226
 
10.1%
45
 
2.0%
41
 
1.8%
38
 
1.7%
33
 
1.5%
31
 
1.4%
Other values (217) 870
38.8%
Lowercase Letter
ValueCountFrequency (%)
s 2
18.2%
a 2
18.2%
k 2
18.2%
i 1
9.1%
r 1
9.1%
t 1
9.1%
p 1
9.1%
n 1
9.1%
Uppercase Letter
ValueCountFrequency (%)
I 3
21.4%
P 3
21.4%
V 3
21.4%
M 2
14.3%
H 1
 
7.1%
S 1
 
7.1%
J 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 3
75.0%
1 1
 
25.0%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
149
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2245
89.4%
Common 240
 
9.6%
Latin 25
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
259
 
11.5%
241
 
10.7%
233
 
10.4%
227
 
10.1%
226
 
10.1%
45
 
2.0%
41
 
1.8%
38
 
1.7%
33
 
1.5%
31
 
1.4%
Other values (218) 871
38.8%
Latin
ValueCountFrequency (%)
I 3
12.0%
P 3
12.0%
V 3
12.0%
s 2
 
8.0%
M 2
 
8.0%
a 2
 
8.0%
k 2
 
8.0%
i 1
 
4.0%
H 1
 
4.0%
r 1
 
4.0%
Other values (5) 5
20.0%
Common
ValueCountFrequency (%)
149
62.1%
) 42
 
17.5%
( 42
 
17.5%
2 3
 
1.2%
& 1
 
0.4%
. 1
 
0.4%
- 1
 
0.4%
1 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2244
89.4%
ASCII 265
 
10.6%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
259
 
11.5%
241
 
10.7%
233
 
10.4%
227
 
10.1%
226
 
10.1%
45
 
2.0%
41
 
1.8%
38
 
1.7%
33
 
1.5%
31
 
1.4%
Other values (217) 870
38.8%
ASCII
ValueCountFrequency (%)
149
56.2%
) 42
 
15.8%
( 42
 
15.8%
I 3
 
1.1%
P 3
 
1.1%
2 3
 
1.1%
V 3
 
1.1%
s 2
 
0.8%
M 2
 
0.8%
a 2
 
0.8%
Other values (13) 14
 
5.3%
None
ValueCountFrequency (%)
1
100.0%

최종수정일자
Date

UNIQUE 

Distinct237
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2008-12-22 17:11:39
Maximum2024-05-03 16:32:02
2024-05-11T00:34:03.171536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:34:03.600267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
U
147 
I
89 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
U 147
62.0%
I 89
37.6%
D 1
 
0.4%

Length

2024-05-11T00:34:03.957419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:34:04.254441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 147
62.0%
i 89
37.6%
d 1
 
0.4%
Distinct144
Distinct (%)60.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T00:34:04.699697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:34:05.205641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing237
Missing (%)100.0%
Memory size2.2 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct202
Distinct (%)89.4%
Missing11
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean199295.79
Minimum183902.04
Maximum215379.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:05.642634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183902.04
5-th percentile185968.07
Q1191803.8
median201780.34
Q3205874.82
95-th percentile211773.97
Maximum215379.1
Range31477.057
Interquartile range (IQR)14071.015

Descriptive statistics

Standard deviation8397.0339
Coefficient of variation (CV)0.042133524
Kurtosis-1.2709585
Mean199295.79
Median Absolute Deviation (MAD)7266.9017
Skewness-0.13665015
Sum45040849
Variance70510179
MonotonicityNot monotonic
2024-05-11T00:34:06.103060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204004.328388149 3
 
1.3%
191628.281133809 3
 
1.3%
193284.940671202 2
 
0.8%
185538.386473543 2
 
0.8%
195537.269534163 2
 
0.8%
211338.114281843 2
 
0.8%
205903.645088343 2
 
0.8%
210251.590527245 2
 
0.8%
206381.496427374 2
 
0.8%
206936.570187916 2
 
0.8%
Other values (192) 204
86.1%
(Missing) 11
 
4.6%
ValueCountFrequency (%)
183902.043509212 1
0.4%
184806.911534822 2
0.8%
185538.386473543 2
0.8%
185663.269533644 1
0.4%
185721.912026 1
0.4%
185818.005782408 1
0.4%
185851.053632398 1
0.4%
185937.652818807 1
0.4%
185950.696438517 1
0.4%
185962.809546697 1
0.4%
ValueCountFrequency (%)
215379.100058 1
0.4%
215186.099366286 1
0.4%
212631.968657493 1
0.4%
212603.194992637 1
0.4%
212383.514068572 1
0.4%
212241.599163626 1
0.4%
212103.610058511 1
0.4%
211997.374303563 1
0.4%
211955.138746228 1
0.4%
211907.685267696 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct202
Distinct (%)89.4%
Missing11
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean449262.33
Minimum438699.77
Maximum464597.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:06.641674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438699.77
5-th percentile442289.02
Q1444916.9
median448165.88
Q3452602.47
95-th percentile460906.44
Maximum464597.2
Range25897.428
Interquartile range (IQR)7685.5706

Descriptive statistics

Standard deviation5620.3109
Coefficient of variation (CV)0.012510087
Kurtosis-0.33640155
Mean449262.33
Median Absolute Deviation (MAD)3634.2821
Skewness0.67348943
Sum1.0153329 × 108
Variance31587894
MonotonicityNot monotonic
2024-05-11T00:34:07.569244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443597.980050957 3
 
1.3%
447397.380617328 3
 
1.3%
456206.224350641 2
 
0.8%
451080.469903239 2
 
0.8%
442122.202180318 2
 
0.8%
450358.802980111 2
 
0.8%
449506.049065503 2
 
0.8%
444061.408532921 2
 
0.8%
457994.001705713 2
 
0.8%
455280.600452321 2
 
0.8%
Other values (192) 204
86.1%
(Missing) 11
 
4.6%
ValueCountFrequency (%)
438699.77460936 1
0.4%
439241.805170218 1
0.4%
440964.438480712 1
0.4%
441091.373561528 2
0.8%
441093.949862979 1
0.4%
441832.716970491 1
0.4%
442122.202180318 2
0.8%
442204.012875284 1
0.4%
442205.889843962 1
0.4%
442230.03574985 1
0.4%
ValueCountFrequency (%)
464597.202705501 1
0.4%
463189.712552985 2
0.8%
461771.054429344 1
0.4%
461683.780241427 1
0.4%
461640.694067429 2
0.8%
461624.554924461 1
0.4%
461557.310544671 1
0.4%
461375.864695799 2
0.8%
461046.100244717 1
0.4%
460487.443375594 1
0.4%

임산부정원수
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)18.7%
Missing71
Missing (%)30.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum0
Maximum60
Zeros2
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:08.056327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q113
median16
Q319
95-th percentile26.75
Maximum60
Range60
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.948948
Coefficient of variation (CV)0.42114837
Kurtosis10.28397
Mean16.5
Median Absolute Deviation (MAD)3
Skewness1.8359673
Sum2739
Variance48.287879
MonotonicityNot monotonic
2024-05-11T00:34:08.591477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
15 20
 
8.4%
19 18
 
7.6%
16 14
 
5.9%
13 12
 
5.1%
17 11
 
4.6%
14 10
 
4.2%
18 10
 
4.2%
12 9
 
3.8%
10 7
 
3.0%
23 7
 
3.0%
Other values (21) 48
20.3%
(Missing) 71
30.0%
ValueCountFrequency (%)
0 2
 
0.8%
1 1
 
0.4%
2 1
 
0.4%
3 1
 
0.4%
6 1
 
0.4%
7 5
2.1%
8 2
 
0.8%
9 4
1.7%
10 7
3.0%
11 2
 
0.8%
ValueCountFrequency (%)
60 1
 
0.4%
44 1
 
0.4%
39 1
 
0.4%
29 3
1.3%
28 1
 
0.4%
27 2
 
0.8%
26 1
 
0.4%
25 2
 
0.8%
24 2
 
0.8%
23 7
3.0%

영유아정원수
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)18.7%
Missing71
Missing (%)30.0%
Infinite0
Infinite (%)0.0%
Mean16.572289
Minimum0
Maximum60
Zeros2
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:09.000116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q113
median16
Q319
95-th percentile26.75
Maximum60
Range60
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.9720796
Coefficient of variation (CV)0.42070709
Kurtosis10.038918
Mean16.572289
Median Absolute Deviation (MAD)3
Skewness1.7946309
Sum2751
Variance48.609894
MonotonicityNot monotonic
2024-05-11T00:34:09.382138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
15 19
 
8.0%
19 16
 
6.8%
16 14
 
5.9%
13 11
 
4.6%
14 11
 
4.6%
18 11
 
4.6%
17 10
 
4.2%
12 9
 
3.8%
20 9
 
3.8%
23 7
 
3.0%
Other values (21) 49
20.7%
(Missing) 71
30.0%
ValueCountFrequency (%)
0 2
 
0.8%
1 1
 
0.4%
2 1
 
0.4%
3 1
 
0.4%
6 1
 
0.4%
7 5
2.1%
8 2
 
0.8%
9 4
1.7%
10 7
3.0%
11 2
 
0.8%
ValueCountFrequency (%)
60 1
 
0.4%
44 1
 
0.4%
39 1
 
0.4%
29 3
1.3%
28 1
 
0.4%
27 2
 
0.8%
26 1
 
0.4%
25 2
 
0.8%
24 3
1.3%
23 7
3.0%

임산부실면적
Real number (ℝ)

MISSING 

Distinct148
Distinct (%)96.7%
Missing84
Missing (%)35.4%
Infinite0
Infinite (%)0.0%
Mean276.77333
Minimum6.3
Maximum2622.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:10.015100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.3
5-th percentile10.7
Q1127.1
median236.39
Q3361.2
95-th percentile648.65
Maximum2622.62
Range2616.32
Interquartile range (IQR)234.1

Descriptive statistics

Standard deviation280.43505
Coefficient of variation (CV)1.01323
Kurtosis32.904644
Mean276.77333
Median Absolute Deviation (MAD)117.01
Skewness4.4741089
Sum42346.32
Variance78643.817
MonotonicityNot monotonic
2024-05-11T00:34:10.626293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.0 2
 
0.8%
148.0 2
 
0.8%
258.0 2
 
0.8%
302.09 2
 
0.8%
13.9 2
 
0.8%
19.25 1
 
0.4%
284.2 1
 
0.4%
369.0 1
 
0.4%
135.0 1
 
0.4%
581.4 1
 
0.4%
Other values (138) 138
58.2%
(Missing) 84
35.4%
ValueCountFrequency (%)
6.3 1
0.4%
6.5 1
0.4%
7.1 1
0.4%
7.13 1
0.4%
7.53 1
0.4%
7.66 1
0.4%
8.4 1
0.4%
8.75 1
0.4%
12.0 2
0.8%
12.1 1
0.4%
ValueCountFrequency (%)
2622.62 1
0.4%
1393.0 1
0.4%
970.7 1
0.4%
791.71 1
0.4%
773.96 1
0.4%
723.33 1
0.4%
669.0 1
0.4%
650.0 1
0.4%
647.75 1
0.4%
621.26 1
0.4%

영유아실면적
Real number (ℝ)

MISSING 

Distinct141
Distinct (%)91.6%
Missing83
Missing (%)35.0%
Infinite0
Infinite (%)0.0%
Mean43.011818
Minimum2.74
Maximum279.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:11.144543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.74
5-th percentile18.267
Q127.405
median36.18
Q350.47
95-th percentile83.153
Maximum279.69
Range276.95
Interquartile range (IQR)23.065

Descriptive statistics

Standard deviation30.956199
Coefficient of variation (CV)0.71971379
Kurtosis27.550942
Mean43.011818
Median Absolute Deviation (MAD)10.47
Skewness4.3868818
Sum6623.82
Variance958.28624
MonotonicityNot monotonic
2024-05-11T00:34:11.663673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28.0 3
 
1.3%
42.9 3
 
1.3%
39.0 3
 
1.3%
32.0 3
 
1.3%
40.0 2
 
0.8%
63.38 2
 
0.8%
35.17 2
 
0.8%
31.4 2
 
0.8%
21.5 2
 
0.8%
29.7 1
 
0.4%
Other values (131) 131
55.3%
(Missing) 83
35.0%
ValueCountFrequency (%)
2.74 1
0.4%
11.42 1
0.4%
12.6 1
0.4%
15.0 1
0.4%
15.6 1
0.4%
16.8 1
0.4%
17.15 1
0.4%
18.02 1
0.4%
18.4 1
0.4%
18.5 1
0.4%
ValueCountFrequency (%)
279.69 1
0.4%
214.0 1
0.4%
127.06 1
0.4%
125.36 1
0.4%
104.32 1
0.4%
87.21 1
0.4%
84.9 1
0.4%
83.4 1
0.4%
83.02 1
0.4%
80.0 1
0.4%

모유수유실면적
Real number (ℝ)

MISSING  ZEROS 

Distinct88
Distinct (%)80.0%
Missing127
Missing (%)53.6%
Infinite0
Infinite (%)0.0%
Mean12.285545
Minimum0
Maximum149.75
Zeros14
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:12.120445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.91
median9.1
Q314.45
95-th percentile28.672
Maximum149.75
Range149.75
Interquartile range (IQR)8.54

Descriptive statistics

Standard deviation16.268335
Coefficient of variation (CV)1.324185
Kurtosis47.269942
Mean12.285545
Median Absolute Deviation (MAD)4.59
Skewness5.9588636
Sum1351.41
Variance264.65873
MonotonicityNot monotonic
2024-05-11T00:34:12.618641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 14
 
5.9%
6.1 2
 
0.8%
12.0 2
 
0.8%
19.25 2
 
0.8%
5.4 2
 
0.8%
6.0 2
 
0.8%
14.0 2
 
0.8%
6.6 2
 
0.8%
4.5 2
 
0.8%
16.0 2
 
0.8%
Other values (78) 78
32.9%
(Missing) 127
53.6%
ValueCountFrequency (%)
0.0 14
5.9%
3.34 1
 
0.4%
3.4 1
 
0.4%
3.63 1
 
0.4%
3.99 1
 
0.4%
4.0 1
 
0.4%
4.48 1
 
0.4%
4.5 2
 
0.8%
4.55 1
 
0.4%
5.2 1
 
0.4%
ValueCountFrequency (%)
149.75 1
0.4%
56.0 1
0.4%
43.5 1
0.4%
43.44 1
0.4%
39.92 1
0.4%
30.04 1
0.4%
27.0 1
0.4%
26.8 1
0.4%
24.33 1
0.4%
23.65 1
0.4%

급식시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct114
Distinct (%)91.9%
Missing113
Missing (%)47.7%
Infinite0
Infinite (%)0.0%
Mean35.469839
Minimum0
Maximum192.13
Zeros6
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:13.121888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.2475
Q122.725
median28.95
Q343.7325
95-th percentile70.582
Maximum192.13
Range192.13
Interquartile range (IQR)21.0075

Descriptive statistics

Standard deviation29.505805
Coefficient of variation (CV)0.8318562
Kurtosis13.729622
Mean35.469839
Median Absolute Deviation (MAD)11.55
Skewness3.1715006
Sum4398.26
Variance870.59253
MonotonicityNot monotonic
2024-05-11T00:34:13.707919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6
 
2.5%
23.7 2
 
0.8%
33.23 2
 
0.8%
30.0 2
 
0.8%
29.4 2
 
0.8%
40.0 2
 
0.8%
24.44 1
 
0.4%
56.6 1
 
0.4%
30.54 1
 
0.4%
20.0 1
 
0.4%
Other values (104) 104
43.9%
(Missing) 113
47.7%
ValueCountFrequency (%)
0.0 6
2.5%
5.0 1
 
0.4%
6.65 1
 
0.4%
7.2 1
 
0.4%
8.0 1
 
0.4%
8.54 1
 
0.4%
8.68 1
 
0.4%
11.0 1
 
0.4%
11.4 1
 
0.4%
12.19 1
 
0.4%
ValueCountFrequency (%)
192.13 1
0.4%
187.11 1
0.4%
167.25 1
0.4%
103.5 1
0.4%
95.3 1
0.4%
74.24 1
0.4%
71.02 1
0.4%
68.1 1
0.4%
66.2 1
0.4%
62.1 1
0.4%

세탁실면적
Real number (ℝ)

MISSING  ZEROS 

Distinct101
Distinct (%)79.5%
Missing110
Missing (%)46.4%
Infinite0
Infinite (%)0.0%
Mean11.538976
Minimum0
Maximum53.94
Zeros5
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:14.186954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.075
Q16.06
median9
Q315.2
95-th percentile26.232
Maximum53.94
Range53.94
Interquartile range (IQR)9.14

Descriptive statistics

Standard deviation8.5805646
Coefficient of variation (CV)0.74361575
Kurtosis4.8317423
Mean11.538976
Median Absolute Deviation (MAD)4
Skewness1.7613335
Sum1465.45
Variance73.626089
MonotonicityNot monotonic
2024-05-11T00:34:14.748478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.0 5
 
2.1%
0.0 5
 
2.1%
10.5 3
 
1.3%
20.0 3
 
1.3%
5.0 3
 
1.3%
9.0 2
 
0.8%
13.5 2
 
0.8%
10.0 2
 
0.8%
9.1 2
 
0.8%
6.0 2
 
0.8%
Other values (91) 98
41.4%
(Missing) 110
46.4%
ValueCountFrequency (%)
0.0 5
2.1%
1.9 1
 
0.4%
2.0 1
 
0.4%
2.25 1
 
0.4%
2.56 1
 
0.4%
2.7 1
 
0.4%
2.78 1
 
0.4%
2.94 1
 
0.4%
2.95 1
 
0.4%
3.0 1
 
0.4%
ValueCountFrequency (%)
53.94 1
0.4%
39.3 1
0.4%
35.9 1
0.4%
35.0 1
0.4%
30.03 1
0.4%
28.12 1
0.4%
26.4 1
0.4%
25.84 1
0.4%
25.2 1
0.4%
24.3 1
0.4%

목욕실면적
Real number (ℝ)

MISSING  ZEROS 

Distinct73
Distinct (%)80.2%
Missing146
Missing (%)61.6%
Infinite0
Infinite (%)0.0%
Mean20.827582
Minimum0
Maximum387.3
Zeros15
Zeros (%)6.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:15.266942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.8
median6
Q325.41
95-th percentile68.4
Maximum387.3
Range387.3
Interquartile range (IQR)22.61

Descriptive statistics

Standard deviation44.985903
Coefficient of variation (CV)2.1599196
Kurtosis49.641727
Mean20.827582
Median Absolute Deviation (MAD)6
Skewness6.3463123
Sum1895.31
Variance2023.7314
MonotonicityNot monotonic
2024-05-11T00:34:15.841895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 15
 
6.3%
2.8 2
 
0.8%
5.0 2
 
0.8%
6.1 2
 
0.8%
4.0 2
 
0.8%
3.0 1
 
0.4%
5.52 1
 
0.4%
79.2 1
 
0.4%
15.0 1
 
0.4%
3.7 1
 
0.4%
Other values (63) 63
26.6%
(Missing) 146
61.6%
ValueCountFrequency (%)
0.0 15
6.3%
1.48 1
 
0.4%
1.82 1
 
0.4%
2.0 1
 
0.4%
2.1 1
 
0.4%
2.5 1
 
0.4%
2.54 1
 
0.4%
2.7 1
 
0.4%
2.8 2
 
0.8%
3.0 1
 
0.4%
ValueCountFrequency (%)
387.3 1
0.4%
109.33 1
0.4%
102.0 1
0.4%
89.29 1
0.4%
79.2 1
0.4%
57.6 1
0.4%
56.0 1
0.4%
53.2 1
0.4%
48.2 1
0.4%
43.9 1
0.4%

조리원화장실면적
Real number (ℝ)

MISSING  ZEROS 

Distinct110
Distinct (%)94.8%
Missing121
Missing (%)51.1%
Infinite0
Infinite (%)0.0%
Mean34.013534
Minimum0
Maximum203.85
Zeros4
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:16.642726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.905
Q17.4175
median23.26
Q353.8575
95-th percentile97.5375
Maximum203.85
Range203.85
Interquartile range (IQR)46.44

Descriptive statistics

Standard deviation34.520113
Coefficient of variation (CV)1.0148934
Kurtosis4.2594778
Mean34.013534
Median Absolute Deviation (MAD)19.7
Skewness1.6583317
Sum3945.57
Variance1191.6382
MonotonicityNot monotonic
2024-05-11T00:34:17.200803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4
 
1.7%
4.5 2
 
0.8%
48.2 2
 
0.8%
36.0 2
 
0.8%
3.38 1
 
0.4%
3.18 1
 
0.4%
41.66 1
 
0.4%
24.81 1
 
0.4%
3.08 1
 
0.4%
34.0 1
 
0.4%
Other values (100) 100
42.2%
(Missing) 121
51.1%
ValueCountFrequency (%)
0.0 4
1.7%
1.3 1
 
0.4%
1.32 1
 
0.4%
2.1 1
 
0.4%
2.7 1
 
0.4%
2.76 1
 
0.4%
2.8 1
 
0.4%
2.85 1
 
0.4%
2.86 1
 
0.4%
3.0 1
 
0.4%
ValueCountFrequency (%)
203.85 1
0.4%
122.3 1
0.4%
120.0 1
0.4%
109.83 1
0.4%
108.1 1
0.4%
99.75 1
0.4%
96.8 1
0.4%
90.0 1
0.4%
89.0 1
0.4%
88.55 1
0.4%

사무실면적
Real number (ℝ)

MISSING 

Distinct107
Distinct (%)89.2%
Missing117
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean13.478083
Minimum0
Maximum73.8
Zeros2
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:18.153589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.9925
Q17.27
median10.9
Q316.08
95-th percentile30.832
Maximum73.8
Range73.8
Interquartile range (IQR)8.81

Descriptive statistics

Standard deviation9.8914658
Coefficient of variation (CV)0.73389262
Kurtosis11.210777
Mean13.478083
Median Absolute Deviation (MAD)4.3
Skewness2.5538476
Sum1617.37
Variance97.841096
MonotonicityNot monotonic
2024-05-11T00:34:18.711191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.0 2
 
0.8%
22.8 2
 
0.8%
10.0 2
 
0.8%
14.0 2
 
0.8%
10.8 2
 
0.8%
7.0 2
 
0.8%
10.41 2
 
0.8%
6.6 2
 
0.8%
10.2 2
 
0.8%
18.0 2
 
0.8%
Other values (97) 100
42.2%
(Missing) 117
49.4%
ValueCountFrequency (%)
0.0 2
0.8%
3.03 1
0.4%
3.12 1
0.4%
3.8 1
0.4%
3.85 1
0.4%
4.0 2
0.8%
4.07 1
0.4%
4.1 1
0.4%
4.4 1
0.4%
4.62 1
0.4%
ValueCountFrequency (%)
73.8 1
0.4%
43.29 1
0.4%
38.5 1
0.4%
33.7 1
0.4%
33.0 1
0.4%
32.2 1
0.4%
30.76 1
0.4%
30.0 1
0.4%
27.86 1
0.4%
26.7 1
0.4%

간호사수
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)8.2%
Missing78
Missing (%)32.9%
Infinite0
Infinite (%)0.0%
Mean3.9559748
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:19.252131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile8
Maximum26
Range25
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.7010216
Coefficient of variation (CV)0.68277017
Kurtosis32.155256
Mean3.9559748
Median Absolute Deviation (MAD)1
Skewness4.7976251
Sum629
Variance7.2955179
MonotonicityNot monotonic
2024-05-11T00:34:19.647187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3 67
28.3%
4 37
15.6%
2 21
 
8.9%
5 12
 
5.1%
6 5
 
2.1%
8 4
 
1.7%
7 4
 
1.7%
1 3
 
1.3%
9 2
 
0.8%
26 1
 
0.4%
Other values (3) 3
 
1.3%
(Missing) 78
32.9%
ValueCountFrequency (%)
1 3
 
1.3%
2 21
 
8.9%
3 67
28.3%
4 37
15.6%
5 12
 
5.1%
6 5
 
2.1%
7 4
 
1.7%
8 4
 
1.7%
9 2
 
0.8%
11 1
 
0.4%
ValueCountFrequency (%)
26 1
 
0.4%
18 1
 
0.4%
12 1
 
0.4%
11 1
 
0.4%
9 2
 
0.8%
8 4
 
1.7%
7 4
 
1.7%
6 5
 
2.1%
5 12
 
5.1%
4 37
15.6%

간호조무사수
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)11.4%
Missing79
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean5.8481013
Minimum0
Maximum45
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:19.980238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q13
median5
Q37
95-th percentile11.15
Maximum45
Range45
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.4837672
Coefficient of variation (CV)0.76670478
Kurtosis36.771522
Mean5.8481013
Median Absolute Deviation (MAD)2
Skewness4.6326414
Sum924
Variance20.104168
MonotonicityNot monotonic
2024-05-11T00:34:20.526298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
3 28
 
11.8%
5 21
 
8.9%
6 19
 
8.0%
4 17
 
7.2%
7 15
 
6.3%
2 13
 
5.5%
8 12
 
5.1%
9 9
 
3.8%
11 5
 
2.1%
1 4
 
1.7%
Other values (8) 15
 
6.3%
(Missing) 79
33.3%
ValueCountFrequency (%)
0 3
 
1.3%
1 4
 
1.7%
2 13
5.5%
3 28
11.8%
4 17
7.2%
5 21
8.9%
6 19
8.0%
7 15
6.3%
8 12
5.1%
9 9
 
3.8%
ValueCountFrequency (%)
45 1
 
0.4%
20 1
 
0.4%
16 1
 
0.4%
15 1
 
0.4%
14 1
 
0.4%
12 3
 
1.3%
11 5
2.1%
10 4
 
1.7%
9 9
3.8%
8 12
5.1%

영양사수
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
167 
0
42 
1
26 
2
 
2

Length

Max length4
Median length4
Mean length3.1139241
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 167
70.5%
0 42
 
17.7%
1 26
 
11.0%
2 2
 
0.8%

Length

2024-05-11T00:34:21.062441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:34:21.462754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 167
70.5%
0 42
 
17.7%
1 26
 
11.0%
2 2
 
0.8%

취사부수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)6.2%
Missing109
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean1.7890625
Minimum0
Maximum10
Zeros5
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:21.895932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q32
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2273289
Coefficient of variation (CV)0.68601788
Kurtosis15.857581
Mean1.7890625
Median Absolute Deviation (MAD)1
Skewness2.9822002
Sum229
Variance1.5063361
MonotonicityNot monotonic
2024-05-11T00:34:22.255333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 54
22.8%
2 50
21.1%
3 10
 
4.2%
4 6
 
2.5%
0 5
 
2.1%
10 1
 
0.4%
5 1
 
0.4%
6 1
 
0.4%
(Missing) 109
46.0%
ValueCountFrequency (%)
0 5
 
2.1%
1 54
22.8%
2 50
21.1%
3 10
 
4.2%
4 6
 
2.5%
5 1
 
0.4%
6 1
 
0.4%
10 1
 
0.4%
ValueCountFrequency (%)
10 1
 
0.4%
6 1
 
0.4%
5 1
 
0.4%
4 6
 
2.5%
3 10
 
4.2%
2 50
21.1%
1 54
22.8%
0 5
 
2.1%

미화원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)5.0%
Missing117
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean1.3833333
Minimum0
Maximum6
Zeros6
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:22.549589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.95
Q11
median1
Q32
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.83195965
Coefficient of variation (CV)0.60141662
Kurtosis7.6863665
Mean1.3833333
Median Absolute Deviation (MAD)0
Skewness2.0259943
Sum166
Variance0.69215686
MonotonicityNot monotonic
2024-05-11T00:34:22.917666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 76
32.1%
2 28
 
11.8%
3 8
 
3.4%
0 6
 
2.5%
4 1
 
0.4%
6 1
 
0.4%
(Missing) 117
49.4%
ValueCountFrequency (%)
0 6
 
2.5%
1 76
32.1%
2 28
 
11.8%
3 8
 
3.4%
4 1
 
0.4%
6 1
 
0.4%
ValueCountFrequency (%)
6 1
 
0.4%
4 1
 
0.4%
3 8
 
3.4%
2 28
 
11.8%
1 76
32.1%
0 6
 
2.5%

기타인원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)9.5%
Missing142
Missing (%)59.9%
Infinite0
Infinite (%)0.0%
Mean1.7473684
Minimum0
Maximum21
Zeros27
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:23.303834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4.3
Maximum21
Range21
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.5051794
Coefficient of variation (CV)1.433687
Kurtosis37.017796
Mean1.7473684
Median Absolute Deviation (MAD)1
Skewness5.1124714
Sum166
Variance6.2759239
MonotonicityNot monotonic
2024-05-11T00:34:23.666822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 28
 
11.8%
0 27
 
11.4%
2 17
 
7.2%
3 13
 
5.5%
4 5
 
2.1%
6 2
 
0.8%
21 1
 
0.4%
5 1
 
0.4%
7 1
 
0.4%
(Missing) 142
59.9%
ValueCountFrequency (%)
0 27
11.4%
1 28
11.8%
2 17
7.2%
3 13
5.5%
4 5
 
2.1%
5 1
 
0.4%
6 2
 
0.8%
7 1
 
0.4%
21 1
 
0.4%
ValueCountFrequency (%)
21 1
 
0.4%
7 1
 
0.4%
6 2
 
0.8%
5 1
 
0.4%
4 5
 
2.1%
3 13
5.5%
2 17
7.2%
1 28
11.8%
0 27
11.4%

건물층수
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)14.3%
Missing90
Missing (%)38.0%
Infinite0
Infinite (%)0.0%
Mean6.0612245
Minimum0
Maximum44
Zeros22
Zeros (%)9.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:24.361760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median6
Q38
95-th percentile14.7
Maximum44
Range44
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.6921293
Coefficient of variation (CV)0.9391055
Kurtosis14.197014
Mean6.0612245
Median Absolute Deviation (MAD)3
Skewness2.8361505
Sum891
Variance32.400335
MonotonicityNot monotonic
2024-05-11T00:34:24.816380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
6 24
 
10.1%
0 22
 
9.3%
3 16
 
6.8%
5 14
 
5.9%
7 13
 
5.5%
8 10
 
4.2%
2 8
 
3.4%
11 8
 
3.4%
4 7
 
3.0%
9 7
 
3.0%
Other values (11) 18
 
7.6%
(Missing) 90
38.0%
ValueCountFrequency (%)
0 22
9.3%
1 4
 
1.7%
2 8
 
3.4%
3 16
6.8%
4 7
 
3.0%
5 14
5.9%
6 24
10.1%
7 13
5.5%
8 10
4.2%
9 7
 
3.0%
ValueCountFrequency (%)
44 1
 
0.4%
26 1
 
0.4%
25 1
 
0.4%
22 1
 
0.4%
18 2
 
0.8%
17 1
 
0.4%
15 1
 
0.4%
14 2
 
0.8%
13 2
 
0.8%
11 8
3.4%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)13.7%
Missing113
Missing (%)47.7%
Infinite0
Infinite (%)0.0%
Mean9.0725806
Minimum0
Maximum456
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:25.313402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median5
Q36
95-th percentile14.25
Maximum456
Range456
Interquartile range (IQR)3

Descriptive statistics

Standard deviation40.747522
Coefficient of variation (CV)4.4912824
Kurtosis120.47337
Mean9.0725806
Median Absolute Deviation (MAD)2
Skewness10.90522
Sum1125
Variance1660.3605
MonotonicityNot monotonic
2024-05-11T00:34:25.633150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
5 24
 
10.1%
6 18
 
7.6%
2 17
 
7.2%
4 14
 
5.9%
3 13
 
5.5%
7 11
 
4.6%
1 7
 
3.0%
10 5
 
2.1%
0 3
 
1.3%
8 3
 
1.3%
Other values (7) 9
 
3.8%
(Missing) 113
47.7%
ValueCountFrequency (%)
0 3
 
1.3%
1 7
 
3.0%
2 17
7.2%
3 13
5.5%
4 14
5.9%
5 24
10.1%
6 18
7.6%
7 11
4.6%
8 3
 
1.3%
9 2
 
0.8%
ValueCountFrequency (%)
456 1
 
0.4%
39 1
 
0.4%
23 1
 
0.4%
21 1
 
0.4%
19 2
 
0.8%
15 1
 
0.4%
10 5
2.1%
9 2
 
0.8%
8 3
 
1.3%
7 11
4.6%

지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)10.8%
Missing163
Missing (%)68.8%
Infinite0
Infinite (%)0.0%
Mean1.5675676
Minimum0
Maximum7
Zeros21
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T00:34:25.933957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5969241
Coefficient of variation (CV)1.0187274
Kurtosis1.8686355
Mean1.5675676
Median Absolute Deviation (MAD)1
Skewness1.3672905
Sum116
Variance2.5501666
MonotonicityNot monotonic
2024-05-11T00:34:26.363129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 22
 
9.3%
0 21
 
8.9%
2 16
 
6.8%
3 7
 
3.0%
4 3
 
1.3%
5 2
 
0.8%
6 2
 
0.8%
7 1
 
0.4%
(Missing) 163
68.8%
ValueCountFrequency (%)
0 21
8.9%
1 22
9.3%
2 16
6.8%
3 7
 
3.0%
4 3
 
1.3%
5 2
 
0.8%
6 2
 
0.8%
7 1
 
0.4%
ValueCountFrequency (%)
7 1
 
0.4%
6 2
 
0.8%
5 2
 
0.8%
4 3
 
1.3%
3 7
 
3.0%
2 16
6.8%
1 22
9.3%
0 21
8.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)임산부정원수영유아정원수임산부실면적영유아실면적모유수유실면적급식시설면적세탁실면적목욕실면적조리원화장실면적사무실면적간호사수간호조무사수영양사수취사부수미화원수기타인원수건물층수지상층수지하층수
03230000PHMB1201432300340421000012014-02-27<NA>1영업/정상13영업중<NA><NA><NA><NA>024313535<NA><NA><NA>서울특별시 송파구 충민로2길 20 (장지동, 송파산모건강증진센터)05816송파산모건강증진센터산후조리원2023-04-18 11:16:05U2022-12-03 22:00:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13240000PHMB1200632400330421000032006-12-08<NA>3폐업3폐업2023-04-03<NA><NA><NA>02) 475-3350<NA>134-866서울특별시 강동구 천호1동 233번지 34호 인성빌딩 6층서울특별시 강동구 구천면로 328 (천호동)05309임수현 산후조리원2023-05-02 17:17:37U2022-12-05 00:04:00.0<NA>211955.138746449582.786229<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23200000PHMB1201432000330421000012014-05-01<NA>1영업/정상13영업중<NA>2023-04-132023-05-15<NA>02-889-0700<NA><NA>서울특별시 관악구 봉천동 463-4 메카플러스서울특별시 관악구 양녕로 46, 메카플러스 (봉천동)08747로얄산후조리원(봉천점)2023-06-27 11:58:39U2022-12-05 22:09:00.0<NA>195274.343266442663.498607<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33050000PHMB1201630500340421000022016-11-10<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2212-2582<NA><NA>서울특별시 동대문구 답십리동 492번지 2호 9층서울특별시 동대문구 천호대로 317, 9층 (답십리동, 하늘병원)02622블리스산후조리원2023-05-08 17:21:11U2022-12-04 23:00:00.0<NA>204831.461306451444.505953<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43150000PHMB1201131500370421000022011-03-17<NA>1영업/정상13영업중<NA>2023-06-052023-06-30<NA>02-2659-0031<NA>157-200서울특별시 강서구 가양동 1480번지 8호서울특별시 강서구 양천로 461, 5층 (가양동)07526퀸즈마리 산후조리원(가양점)2023-06-29 11:19:23U2022-12-07 00:01:00.0<NA>186875.994185451205.835119<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53090000PHMB1200830900330421000012008-08-26<NA>1영업/정상13영업중<NA>2023-05-032023-05-31<NA><NA><NA><NA>서울특별시 도봉구 창동 731-1 에이치큐브병원서울특별시 도봉구 도봉로 604, 에이치큐브병원 7-8층 (창동)01401에이치큐브 산후조리원2023-05-25 09:24:16U2022-12-04 22:07:00.0<NA>203556.661563461771.054429<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63110000PHMB1200731100320421000022007-02-01<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6010-0702<NA>122-923서울특별시 은평구 응암동 578번지 16호 4,5층서울특별시 은평구 응암로 235 (응암동)03457라솜 산후조리원 은평점2023-05-24 15:41:19U2022-12-04 22:07:00.0<NA>192652.478015454524.979326<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
73140000PHMB12015314003304210000120150807<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6491-1001<NA><NA>서울특별시 양천구 목동 406번지 21호서울특별시 양천구 오목로 325 (목동)08000㈜레피리움시그니쳐2022-04-12 15:56:45U2021-12-03 23:04:00.0<NA>188767.584299446998.232039<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
83220000PHMB1201432200330421000042014-09-05<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 삼성동 21 한섬빌딩서울특별시 강남구 삼성로 635, 한섬빌딩 (삼성동)06091(주)헤리티지산후조리원2024-01-26 11:17:22U2023-11-30 22:08:00.0<NA>204436.97085446036.981493<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93040000PHMB12007304003304210000120070620<NA>1영업/정상13영업중<NA><NA><NA><NA>02-457-6020<NA>143959서울특별시 광진구 구의동 223번지 65호서울특별시 광진구 구의로 28 (구의동)<NA>예그리나 산후조리원2022-10-26 13:28:45U2021-10-30 22:08:00.0<NA>207866.804669448680.6447<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)임산부정원수영유아정원수임산부실면적영유아실면적모유수유실면적급식시설면적세탁실면적목욕실면적조리원화장실면적사무실면적간호사수간호조무사수영양사수취사부수미화원수기타인원수건물층수지상층수지하층수
2273070000PHMB12011307003404210000120110307<NA>3폐업3폐업202205302018071620180731<NA>02-2039-0000<NA>136820서울특별시 성북구 석관동 349번지 1호서울특별시 성북구 화랑로 248, 장위뉴타워 8층 (석관동)02787동그라미산후조리원 성북점2022-05-30 14:31:37U2021-12-06 00:01:00.0<NA>204958.405518456443.387226<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2283240000PHMB1200632400330421000022006-10-17<NA>1영업/정상13영업중<NA><NA><NA><NA>02) 485-2151<NA><NA>서울특별시 강동구 천호동 447 정산타워빌딩서울특별시 강동구 천호대로 1099, 정산타워빌딩 6층 (천호동)05339강동맘스 산후조리원(주)2023-12-14 12:38:22U2022-11-01 23:06:00.0<NA>211785.062144448178.173809<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2293240000PHMB1200632400330421000012006-12-08<NA>1영업/정상13영업중<NA><NA><NA><NA>02) 485-0087<NA><NA>서울특별시 강동구 성내동 378 웰빙메디컬빌딩서울특별시 강동구 천호대로 1128, 웰빙메디컬빌딩 6~7층 (성내동)05373가율 산후조리원2023-05-12 10:04:17U2022-12-04 23:04:00.0<NA>211997.374304447998.814231<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2303210000PHMB12022321003404210000120220701<NA>1영업/정상13영업중<NA><NA><NA><NA>02-592-0020<NA><NA>서울특별시 서초구 방배동 783-24 왕실빌딩서울특별시 서초구 동작대로 172, 왕실빌딩 3층 50호 (방배동)06559sk산후조리원2022-07-20 14:46:32I2021-12-06 22:02:00.0<NA>198448.680593443312.729013<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2313180000PHMB12008318003404210000120080229<NA>1영업/정상13영업중<NA>2019010120190228<NA>02-848-3579<NA><NA><NA>서울특별시 영등포구 도신로 116, 대웅빌딩 (신길동)07383메르디앙 산후조리원2022-09-08 10:33:17U2021-12-08 23:00:00.0<NA>191534.963963445094.612873<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2323240000PHMB12016324003304210000120160104<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>05239<NA>서울특별시 강동구 올림픽로 833, 매일우리아이센타 (암사동)05239(주)라파엘산후조리원2022-10-12 10:54:11U2021-10-30 23:04:00.0<NA>211338.114282450358.80298<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2333220000PHMB12006322003304210000320061207<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3412-0101<NA><NA>서울특별시 강남구 개포동 1239번지 17호 문화빌딩 5,6층서울특별시 강남구 논현로 98, 문화빌딩 5,6층 (개포동)06303한아름산후조리원2022-09-28 08:47:10U2021-12-08 21:00:00.0<NA>203889.694313441832.71697<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2343140000PHMB12011314003304210000120110117<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2601-3588<NA><NA>서울특별시 양천구 신월동 550번지 3호 승일뷰티타워2서울특별시 양천구 신월로 164, 승일뷰티타워2 7층 (신월동)08064팰리스산후조리원2022-10-05 17:18:19U2021-10-31 00:07:00.0<NA>185962.809547446176.170953<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2353150000PHMB1201531500370421000012015-06-16<NA>1영업/정상13영업중<NA>2017-02-072017-02-15<NA>02-2664-6999<NA><NA><NA>서울특별시 강서구 마곡중앙5로 81, 에스비타운 (마곡동)07599리베 산후조리원(마곡점)2023-07-19 14:21:48U2022-12-06 22:01:00.0<NA>183902.043509451664.251457<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2363110000PHMB1200631100320421000012006-12-07<NA>1영업/정상13영업중<NA>2022-04-082022-07-08<NA>02-309-7535<NA>122-924서울특별시 은평구 응암동 603번지 24호 연송빌딩 4,5층서울특별시 은평구 응암로 164 (응암동,연송빌딩 4,5층)<NA>인정산후조리원2024-01-30 15:30:11U2023-12-02 00:01:00.0<NA>192562.859527453813.903417<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>