Overview

Dataset statistics

Number of variables34
Number of observations395
Missing cells4070
Missing cells (%)30.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory111.6 KiB
Average record size in memory289.3 B

Variable types

Numeric4
Text7
DateTime4
Unsupported8
Categorical11

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),문화체육업종명,공사립구분명,보험가입여부코드,지도자수,건축물동수,건축물연면적,회원모집총인원,세부업종명,법인명
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16135/S/1/datasetView.do

Alerts

문화체육업종명 is highly imbalanced (61.2%)Imbalance
공사립구분명 is highly imbalanced (61.2%)Imbalance
지도자수 is highly imbalanced (54.0%)Imbalance
회원모집총인원 is highly imbalanced (90.0%)Imbalance
인허가취소일자 has 395 (100.0%) missing valuesMissing
폐업일자 has 67 (17.0%) missing valuesMissing
휴업시작일자 has 395 (100.0%) missing valuesMissing
휴업종료일자 has 395 (100.0%) missing valuesMissing
재개업일자 has 395 (100.0%) missing valuesMissing
전화번호 has 177 (44.8%) missing valuesMissing
소재지면적 has 395 (100.0%) missing valuesMissing
소재지우편번호 has 37 (9.4%) missing valuesMissing
도로명주소 has 64 (16.2%) missing valuesMissing
도로명우편번호 has 311 (78.7%) missing valuesMissing
업태구분명 has 395 (100.0%) missing valuesMissing
좌표정보(X) has 19 (4.8%) missing valuesMissing
좌표정보(Y) has 19 (4.8%) missing valuesMissing
건축물연면적 has 216 (54.7%) missing valuesMissing
세부업종명 has 395 (100.0%) missing valuesMissing
법인명 has 395 (100.0%) missing valuesMissing
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
세부업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
법인명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축물연면적 has 134 (33.9%) zerosZeros

Reproduction

Analysis started2024-05-11 06:06:55.726623
Analysis finished2024-05-11 06:06:56.593361
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct23
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3119519
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:06:56.717134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3000000
Q13050000
median3120000
Q33200000
95-th percentile3240000
Maximum3240000
Range240000
Interquartile range (IQR)150000

Descriptive statistics

Standard deviation83471.759
Coefficient of variation (CV)0.026757894
Kurtosis-1.4686423
Mean3119519
Median Absolute Deviation (MAD)80000
Skewness-0.056001032
Sum1.23221 × 109
Variance6.9675345 × 109
MonotonicityNot monotonic
2024-05-11T15:06:56.912235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3010000 40
 
10.1%
3180000 37
 
9.4%
3000000 37
 
9.4%
3200000 36
 
9.1%
3240000 33
 
8.4%
3050000 32
 
8.1%
3110000 21
 
5.3%
3230000 17
 
4.3%
3150000 17
 
4.3%
3080000 16
 
4.1%
Other values (13) 109
27.6%
ValueCountFrequency (%)
3000000 37
9.4%
3010000 40
10.1%
3020000 6
 
1.5%
3030000 12
 
3.0%
3050000 32
8.1%
3060000 9
 
2.3%
3070000 4
 
1.0%
3080000 16
 
4.1%
3090000 15
 
3.8%
3100000 4
 
1.0%
ValueCountFrequency (%)
3240000 33
8.4%
3230000 17
4.3%
3220000 11
 
2.8%
3210000 12
 
3.0%
3200000 36
9.1%
3190000 8
 
2.0%
3180000 37
9.4%
3170000 6
 
1.5%
3160000 5
 
1.3%
3150000 17
4.3%

관리번호
Text

Distinct95
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T15:06:57.251169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters7900
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

Unique29 ?
Unique (%)7.3%

Sample

1st rowCDFH3301112001000001
2nd rowCDFH3301112011000001
3rd rowCDFH3301111993000001
4th rowCDFH3301111995000001
5th rowCDFH3301111998000001
ValueCountFrequency (%)
cdfh3301112001000001 19
 
4.8%
cdfh3301111999000001 18
 
4.6%
cdfh3301112000000001 16
 
4.1%
cdfh3301112003000001 13
 
3.3%
cdfh3301111999000002 12
 
3.0%
cdfh3301111996000001 12
 
3.0%
cdfh3301111997000001 12
 
3.0%
cdfh3301111998000001 11
 
2.8%
cdfh3301112002000001 11
 
2.8%
cdfh3301111999000003 10
 
2.5%
Other values (85) 261
66.1%
2024-05-11T15:06:57.757942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2780
35.2%
1 1666
21.1%
3 876
 
11.1%
9 471
 
6.0%
C 395
 
5.0%
D 395
 
5.0%
F 395
 
5.0%
H 395
 
5.0%
2 336
 
4.3%
5 44
 
0.6%
Other values (4) 147
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6320
80.0%
Uppercase Letter 1580
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2780
44.0%
1 1666
26.4%
3 876
 
13.9%
9 471
 
7.5%
2 336
 
5.3%
5 44
 
0.7%
4 43
 
0.7%
6 37
 
0.6%
7 34
 
0.5%
8 33
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
C 395
25.0%
D 395
25.0%
F 395
25.0%
H 395
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6320
80.0%
Latin 1580
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2780
44.0%
1 1666
26.4%
3 876
 
13.9%
9 471
 
7.5%
2 336
 
5.3%
5 44
 
0.7%
4 43
 
0.7%
6 37
 
0.6%
7 34
 
0.5%
8 33
 
0.5%
Latin
ValueCountFrequency (%)
C 395
25.0%
D 395
25.0%
F 395
25.0%
H 395
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2780
35.2%
1 1666
21.1%
3 876
 
11.1%
9 471
 
6.0%
C 395
 
5.0%
D 395
 
5.0%
F 395
 
5.0%
H 395
 
5.0%
2 336
 
4.3%
5 44
 
0.6%
Other values (4) 147
 
1.9%

인허가일자
Date

Distinct365
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum1991-11-20 00:00:00
Maximum2022-05-17 00:00:00
2024-05-11T15:06:57.963800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:58.165904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing395
Missing (%)100.0%
Memory size3.6 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3
297 
1
65 
4
33 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row4
4th row3
5th row1

Common Values

ValueCountFrequency (%)
3 297
75.2%
1 65
 
16.5%
4 33
 
8.4%

Length

2024-05-11T15:06:58.344402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:58.511593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 297
75.2%
1 65
 
16.5%
4 33
 
8.4%

영업상태명
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
폐업
297 
영업/정상
65 
취소/말소/만료/정지/중지
33 

Length

Max length14
Median length2
Mean length3.4962025
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row폐업
3rd row취소/말소/만료/정지/중지
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 297
75.2%
영업/정상 65
 
16.5%
취소/말소/만료/정지/중지 33
 
8.4%

Length

2024-05-11T15:06:58.739869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:58.925072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 297
75.2%
영업/정상 65
 
16.5%
취소/말소/만료/정지/중지 33
 
8.4%

상세영업상태코드
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3
297 
13
65 
35
33 

Length

Max length2
Median length1
Mean length1.2481013
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row3
3rd row35
4th row3
5th row13

Common Values

ValueCountFrequency (%)
3 297
75.2%
13 65
 
16.5%
35 33
 
8.4%

Length

2024-05-11T15:06:59.119363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:59.288990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 297
75.2%
13 65
 
16.5%
35 33
 
8.4%

상세영업상태명
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
폐업
297 
영업중
65 
직권말소
33 

Length

Max length4
Median length2
Mean length2.3316456
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 297
75.2%
영업중 65
 
16.5%
직권말소 33
 
8.4%

Length

2024-05-11T15:06:59.475770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:59.683047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 297
75.2%
영업중 65
 
16.5%
직권말소 33
 
8.4%

폐업일자
Date

MISSING 

Distinct284
Distinct (%)86.6%
Missing67
Missing (%)17.0%
Memory size3.2 KiB
Minimum1994-09-07 00:00:00
Maximum2023-12-31 00:00:00
2024-05-11T15:06:59.926365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:07:00.184672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing395
Missing (%)100.0%
Memory size3.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing395
Missing (%)100.0%
Memory size3.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing395
Missing (%)100.0%
Memory size3.6 KiB

전화번호
Text

MISSING 

Distinct209
Distinct (%)95.9%
Missing177
Missing (%)44.8%
Memory size3.2 KiB
2024-05-11T15:07:00.723077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length8
Mean length8.7614679
Min length8

Characters and Unicode

Total characters1910
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

Unique200 ?
Unique (%)91.7%

Sample

1st row436-0085
2nd row02-882-2467
3rd row2268-3339
4th row2279-4435
5th row2238-4631
ValueCountFrequency (%)
812-7277 2
 
0.9%
483-8844 2
 
0.9%
470-1238 2
 
0.9%
905-0303 2
 
0.9%
477-0098 2
 
0.9%
2244-4948 2
 
0.9%
434-2739 2
 
0.9%
2215-4339 2
 
0.9%
02-2274-4555 2
 
0.9%
2636-5223 1
 
0.5%
Other values (199) 199
91.3%
2024-05-11T15:07:01.487902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 250
13.1%
2 229
12.0%
4 186
9.7%
7 181
9.5%
8 174
9.1%
0 167
8.7%
3 162
8.5%
6 156
8.2%
5 146
7.6%
9 140
7.3%
Other values (2) 119
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1659
86.9%
Dash Punctuation 250
 
13.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 229
13.8%
4 186
11.2%
7 181
10.9%
8 174
10.5%
0 167
10.1%
3 162
9.8%
6 156
9.4%
5 146
8.8%
9 140
8.4%
1 118
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 250
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1910
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 250
13.1%
2 229
12.0%
4 186
9.7%
7 181
9.5%
8 174
9.1%
0 167
8.7%
3 162
8.5%
6 156
8.2%
5 146
7.6%
9 140
7.3%
Other values (2) 119
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1910
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 250
13.1%
2 229
12.0%
4 186
9.7%
7 181
9.5%
8 174
9.1%
0 167
8.7%
3 162
8.5%
6 156
8.2%
5 146
7.6%
9 140
7.3%
Other values (2) 119
6.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing395
Missing (%)100.0%
Memory size3.6 KiB

소재지우편번호
Text

MISSING 

Distinct181
Distinct (%)50.6%
Missing37
Missing (%)9.4%
Memory size3.2 KiB
2024-05-11T15:07:02.015587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.047486
Min length6

Characters and Unicode

Total characters2165
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

Unique107 ?
Unique (%)29.9%

Sample

1st row131-810
2nd row151015
3rd row100-330
4th row132-908
5th row132-898
ValueCountFrequency (%)
150033 11
 
3.1%
110836 9
 
2.5%
134814 8
 
2.2%
110842 8
 
2.2%
151015 8
 
2.2%
130805 7
 
2.0%
138861 7
 
2.0%
132898 7
 
2.0%
138827 6
 
1.7%
120859 6
 
1.7%
Other values (171) 281
78.5%
2024-05-11T15:07:02.796355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 525
24.2%
0 346
16.0%
8 307
14.2%
3 243
11.2%
5 177
 
8.2%
2 168
 
7.8%
9 116
 
5.4%
4 107
 
4.9%
7 89
 
4.1%
6 70
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2148
99.2%
Dash Punctuation 17
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 525
24.4%
0 346
16.1%
8 307
14.3%
3 243
11.3%
5 177
 
8.2%
2 168
 
7.8%
9 116
 
5.4%
4 107
 
5.0%
7 89
 
4.1%
6 70
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2165
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 525
24.2%
0 346
16.0%
8 307
14.2%
3 243
11.2%
5 177
 
8.2%
2 168
 
7.8%
9 116
 
5.4%
4 107
 
4.9%
7 89
 
4.1%
6 70
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 525
24.2%
0 346
16.0%
8 307
14.2%
3 243
11.2%
5 177
 
8.2%
2 168
 
7.8%
9 116
 
5.4%
4 107
 
4.9%
7 89
 
4.1%
6 70
 
3.2%

지번주소
Text

Distinct377
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T15:07:03.277267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length36
Mean length24
Min length13

Characters and Unicode

Total characters9480
Distinct characters183
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique363 ?
Unique (%)91.9%

Sample

1st row서울특별시 중랑구 망우동 563-4
2nd row서울특별시 관악구 신림동 1422-17 403호
3rd row서울특별시 중구 주교동 147-1
4th row서울특별시 도봉구 창동 333-2 한성빌디802호
5th row서울특별시 도봉구 창동 5
ValueCountFrequency (%)
서울특별시 395
 
22.5%
중구 40
 
2.3%
종로구 37
 
2.1%
영등포구 37
 
2.1%
관악구 36
 
2.0%
강동구 33
 
1.9%
동대문구 32
 
1.8%
신림동 30
 
1.7%
3층 22
 
1.3%
은평구 21
 
1.2%
Other values (539) 1074
61.1%
2024-05-11T15:07:04.368557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1722
18.2%
동 463
 
4.9%
서 452
 
4.8%
구 401
 
4.2%
시 399
 
4.2%
울 396
 
4.2%
지 395
 
4.2%
별 395
 
4.2%
특 395
 
4.2%
- 358
 
3.8%
Other values (173) 4104
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5519
58.2%
Decimal Number 1840
 
19.4%
Space Separator 1722
 
18.2%
Dash Punctuation 358
 
3.8%
Close Punctuation 13
 
0.1%
Open Punctuation 12
 
0.1%
Uppercase Letter 11
 
0.1%
Other Punctuation 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 463
 
8.4%
서 452
 
8.2%
구 401
 
7.3%
시 399
 
7.2%
울 396
 
7.2%
지 395
 
7.2%
별 395
 
7.2%
특 395
 
7.2%
번 345
 
6.3%
층 115
 
2.1%
Other values (145) 1763
31.9%
Decimal Number
ValueCountFrequency (%)
1 347
18.9%
2 260
14.1%
3 257
14.0%
4 222
12.1%
5 178
9.7%
6 139
7.6%
0 129
 
7.0%
7 104
 
5.7%
8 103
 
5.6%
9 101
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 2
18.2%
D 1
9.1%
J 1
9.1%
S 1
9.1%
A 1
9.1%
K 1
9.1%
I 1
9.1%
N 1
9.1%
G 1
9.1%
F 1
9.1%
Close Punctuation
ValueCountFrequency (%)
) 12
92.3%
] 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1722
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 358
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5519
58.2%
Common 3950
41.7%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 463
 
8.4%
서 452
 
8.2%
구 401
 
7.3%
시 399
 
7.2%
울 396
 
7.2%
지 395
 
7.2%
별 395
 
7.2%
특 395
 
7.2%
번 345
 
6.3%
층 115
 
2.1%
Other values (145) 1763
31.9%
Common
ValueCountFrequency (%)
1722
43.6%
- 358
 
9.1%
1 347
 
8.8%
2 260
 
6.6%
3 257
 
6.5%
4 222
 
5.6%
5 178
 
4.5%
6 139
 
3.5%
0 129
 
3.3%
7 104
 
2.6%
Other values (8) 234
 
5.9%
Latin
ValueCountFrequency (%)
B 2
18.2%
D 1
9.1%
J 1
9.1%
S 1
9.1%
A 1
9.1%
K 1
9.1%
I 1
9.1%
N 1
9.1%
G 1
9.1%
F 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5519
58.2%
ASCII 3961
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1722
43.5%
- 358
 
9.0%
1 347
 
8.8%
2 260
 
6.6%
3 257
 
6.5%
4 222
 
5.6%
5 178
 
4.5%
6 139
 
3.5%
0 129
 
3.3%
7 104
 
2.6%
Other values (18) 245
 
6.2%
Hangul
ValueCountFrequency (%)
동 463
 
8.4%
서 452
 
8.2%
구 401
 
7.3%
시 399
 
7.2%
울 396
 
7.2%
지 395
 
7.2%
별 395
 
7.2%
특 395
 
7.2%
번 345
 
6.3%
층 115
 
2.1%
Other values (145) 1763
31.9%

도로명주소
Text

MISSING 

Distinct317
Distinct (%)95.8%
Missing64
Missing (%)16.2%
Memory size3.2 KiB
2024-05-11T15:07:05.071363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length41
Mean length27.900302
Min length22

Characters and Unicode

Total characters9235
Distinct characters206
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique304 ?
Unique (%)91.8%

Sample

1st row서울특별시 중랑구 망우로 384 (망우동)
2nd row서울특별시 관악구 남부순환로 1627, 403호 (신림동)
3rd row서울특별시 도봉구 노해로65길 11 (창동,한성빌디802호)
4th row서울특별시 도봉구 마들로11가길 12 (창동)
5th row서울특별시 서초구 강남대로 621 (잠원동)
ValueCountFrequency (%)
서울특별시 331
 
19.1%
관악구 36
 
2.1%
종로구 34
 
2.0%
영등포구 32
 
1.8%
동대문구 30
 
1.7%
강동구 30
 
1.7%
신림동 25
 
1.4%
통일로 24
 
1.4%
은평구 20
 
1.2%
천호대로 18
 
1.0%
Other values (574) 1154
66.6%
2024-05-11T15:07:05.933874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1596
 
17.3%
동 420
 
4.5%
서 390
 
4.2%
로 381
 
4.1%
시 343
 
3.7%
) 340
 
3.7%
( 340
 
3.7%
구 337
 
3.6%
울 332
 
3.6%
특 331
 
3.6%
Other values (196) 4425
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5365
58.1%
Space Separator 1596
 
17.3%
Decimal Number 1358
 
14.7%
Close Punctuation 340
 
3.7%
Open Punctuation 340
 
3.7%
Other Punctuation 152
 
1.6%
Dash Punctuation 71
 
0.8%
Uppercase Letter 12
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 420
 
7.8%
서 390
 
7.3%
로 381
 
7.1%
시 343
 
6.4%
구 337
 
6.3%
울 332
 
6.2%
특 331
 
6.2%
별 331
 
6.2%
길 139
 
2.6%
대 112
 
2.1%
Other values (169) 2249
41.9%
Decimal Number
ValueCountFrequency (%)
1 269
19.8%
2 211
15.5%
3 185
13.6%
5 151
11.1%
4 129
9.5%
6 94
 
6.9%
0 92
 
6.8%
7 87
 
6.4%
8 76
 
5.6%
9 64
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 3
25.0%
J 1
 
8.3%
S 1
 
8.3%
G 1
 
8.3%
A 1
 
8.3%
N 1
 
8.3%
I 1
 
8.3%
K 1
 
8.3%
F 1
 
8.3%
D 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 151
99.3%
/ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
1596
100.0%
Close Punctuation
ValueCountFrequency (%)
) 340
100.0%
Open Punctuation
ValueCountFrequency (%)
( 340
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5365
58.1%
Common 3858
41.8%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 420
 
7.8%
서 390
 
7.3%
로 381
 
7.1%
시 343
 
6.4%
구 337
 
6.3%
울 332
 
6.2%
특 331
 
6.2%
별 331
 
6.2%
길 139
 
2.6%
대 112
 
2.1%
Other values (169) 2249
41.9%
Common
ValueCountFrequency (%)
1596
41.4%
) 340
 
8.8%
( 340
 
8.8%
1 269
 
7.0%
2 211
 
5.5%
3 185
 
4.8%
, 151
 
3.9%
5 151
 
3.9%
4 129
 
3.3%
6 94
 
2.4%
Other values (7) 392
 
10.2%
Latin
ValueCountFrequency (%)
B 3
25.0%
J 1
 
8.3%
S 1
 
8.3%
G 1
 
8.3%
A 1
 
8.3%
N 1
 
8.3%
I 1
 
8.3%
K 1
 
8.3%
F 1
 
8.3%
D 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5365
58.1%
ASCII 3870
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1596
41.2%
) 340
 
8.8%
( 340
 
8.8%
1 269
 
7.0%
2 211
 
5.5%
3 185
 
4.8%
, 151
 
3.9%
5 151
 
3.9%
4 129
 
3.3%
6 94
 
2.4%
Other values (17) 404
 
10.4%
Hangul
ValueCountFrequency (%)
동 420
 
7.8%
서 390
 
7.3%
로 381
 
7.1%
시 343
 
6.4%
구 337
 
6.3%
울 332
 
6.2%
특 331
 
6.2%
별 331
 
6.2%
길 139
 
2.6%
대 112
 
2.1%
Other values (169) 2249
41.9%

도로명우편번호
Text

MISSING 

Distinct62
Distinct (%)73.8%
Missing311
Missing (%)78.7%
Memory size3.2 KiB
2024-05-11T15:07:06.321876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2142857
Min length5

Characters and Unicode

Total characters438
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

Unique50 ?
Unique (%)59.5%

Sample

1st row02163
2nd row07250
3rd row07303
4th row03119
5th row02169
ValueCountFrequency (%)
05353 5
 
6.0%
07250 4
 
4.8%
131810 3
 
3.6%
01414 3
 
3.6%
03196 3
 
3.6%
05355 3
 
3.6%
07620 3
 
3.6%
132898 2
 
2.4%
02645 2
 
2.4%
03368 2
 
2.4%
Other values (52) 54
64.3%
2024-05-11T15:07:07.104376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 105
24.0%
3 58
13.2%
1 58
13.2%
5 40
 
9.1%
2 38
 
8.7%
7 34
 
7.8%
8 32
 
7.3%
4 29
 
6.6%
6 23
 
5.3%
9 19
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 436
99.5%
Dash Punctuation 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 105
24.1%
3 58
13.3%
1 58
13.3%
5 40
 
9.2%
2 38
 
8.7%
7 34
 
7.8%
8 32
 
7.3%
4 29
 
6.7%
6 23
 
5.3%
9 19
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 438
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 105
24.0%
3 58
13.2%
1 58
13.2%
5 40
 
9.1%
2 38
 
8.7%
7 34
 
7.8%
8 32
 
7.3%
4 29
 
6.6%
6 23
 
5.3%
9 19
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 105
24.0%
3 58
13.2%
1 58
13.2%
5 40
 
9.1%
2 38
 
8.7%
7 34
 
7.8%
8 32
 
7.3%
4 29
 
6.6%
6 23
 
5.3%
9 19
 
4.3%

사업장명
Text

Distinct331
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T15:07:07.480736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length6.4329114
Min length2

Characters and Unicode

Total characters2541
Distinct characters296
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)75.4%

Sample

1st row조이 스포츠댄스
2nd row백만불 댄스 무도학원
3rd row한국댄스무도학원
4th row대니박댄스스쿨
5th row하바나댄스스포츠학원
ValueCountFrequency (%)
댄스스포츠 15
 
3.1%
무도학원 12
 
2.5%
댄스 11
 
2.3%
서울무도학원 8
 
1.7%
스포츠댄스 7
 
1.5%
아카데미 7
 
1.5%
국제무도학원 7
 
1.5%
한국무도학원 7
 
1.5%
스포츠 5
 
1.0%
현대 4
 
0.8%
Other values (339) 397
82.7%
2024-05-11T15:07:08.150882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 257
 
10.1%
원 199
 
7.8%
학 198
 
7.8%
무 176
 
6.9%
도 176
 
6.9%
댄 131
 
5.2%
포 98
 
3.9%
츠 98
 
3.9%
85
 
3.3%
국 37
 
1.5%
Other values (286) 1086
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2356
92.7%
Space Separator 85
 
3.3%
Uppercase Letter 30
 
1.2%
Decimal Number 25
 
1.0%
Other Punctuation 12
 
0.5%
Close Punctuation 11
 
0.4%
Open Punctuation 11
 
0.4%
Lowercase Letter 11
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 257
 
10.9%
원 199
 
8.4%
학 198
 
8.4%
무 176
 
7.5%
도 176
 
7.5%
댄 131
 
5.6%
포 98
 
4.2%
츠 98
 
4.2%
국 37
 
1.6%
아 35
 
1.5%
Other values (249) 951
40.4%
Uppercase Letter
ValueCountFrequency (%)
K 6
20.0%
D 4
13.3%
C 3
10.0%
L 3
10.0%
J 2
 
6.7%
B 2
 
6.7%
E 2
 
6.7%
M 2
 
6.7%
S 2
 
6.7%
P 1
 
3.3%
Other values (3) 3
10.0%
Lowercase Letter
ValueCountFrequency (%)
d 2
18.2%
o 1
9.1%
i 1
9.1%
u 1
9.1%
t 1
9.1%
s 1
9.1%
e 1
9.1%
c 1
9.1%
n 1
9.1%
a 1
9.1%
Decimal Number
ValueCountFrequency (%)
1 8
32.0%
4 4
16.0%
0 3
 
12.0%
2 3
 
12.0%
9 2
 
8.0%
3 2
 
8.0%
5 2
 
8.0%
6 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 7
58.3%
& 4
33.3%
, 1
 
8.3%
Space Separator
ValueCountFrequency (%)
85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2356
92.7%
Common 144
 
5.7%
Latin 41
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 257
 
10.9%
원 199
 
8.4%
학 198
 
8.4%
무 176
 
7.5%
도 176
 
7.5%
댄 131
 
5.6%
포 98
 
4.2%
츠 98
 
4.2%
국 37
 
1.6%
아 35
 
1.5%
Other values (249) 951
40.4%
Latin
ValueCountFrequency (%)
K 6
14.6%
D 4
 
9.8%
C 3
 
7.3%
L 3
 
7.3%
d 2
 
4.9%
J 2
 
4.9%
B 2
 
4.9%
E 2
 
4.9%
M 2
 
4.9%
S 2
 
4.9%
Other values (13) 13
31.7%
Common
ValueCountFrequency (%)
85
59.0%
) 11
 
7.6%
( 11
 
7.6%
1 8
 
5.6%
. 7
 
4.9%
& 4
 
2.8%
4 4
 
2.8%
0 3
 
2.1%
2 3
 
2.1%
9 2
 
1.4%
Other values (4) 6
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2356
92.7%
ASCII 185
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 257
 
10.9%
원 199
 
8.4%
학 198
 
8.4%
무 176
 
7.5%
도 176
 
7.5%
댄 131
 
5.6%
포 98
 
4.2%
츠 98
 
4.2%
국 37
 
1.6%
아 35
 
1.5%
Other values (249) 951
40.4%
ASCII
ValueCountFrequency (%)
85
45.9%
) 11
 
5.9%
( 11
 
5.9%
1 8
 
4.3%
. 7
 
3.8%
K 6
 
3.2%
& 4
 
2.2%
4 4
 
2.2%
D 4
 
2.2%
C 3
 
1.6%
Other values (27) 42
22.7%

최종수정일자
Date

Distinct337
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum2003-02-06 10:45:13
Maximum2024-04-24 16:54:53
2024-05-11T15:07:08.412946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:07:08.667254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
I
318 
U
77 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 318
80.5%
U 77
 
19.5%

Length

2024-05-11T15:07:08.921599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:09.119026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 318
80.5%
u 77
 
19.5%

데이터갱신일자
Date

Distinct64
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:06:00
2024-05-11T15:07:09.323482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:07:09.653803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing395
Missing (%)100.0%
Memory size3.6 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct317
Distinct (%)84.3%
Missing19
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean199500.49
Minimum182970.97
Maximum213676.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:07:09.893393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182970.97
5-th percentile186436.69
Q1193731.29
median200742.62
Q3204261.26
95-th percentile211292.29
Maximum213676.32
Range30705.354
Interquartile range (IQR)10529.966

Descriptive statistics

Standard deviation6945.5349
Coefficient of variation (CV)0.034814625
Kurtosis-0.61815806
Mean199500.49
Median Absolute Deviation (MAD)5697.174
Skewness-0.097245428
Sum75012185
Variance48240456
MonotonicityNot monotonic
2024-05-11T15:07:10.122754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191908.634244893 4
 
1.0%
193755.14368469 3
 
0.8%
201493.81751023 3
 
0.8%
212111.336830711 3
 
0.8%
191376.602183978 3
 
0.8%
212127.772315316 3
 
0.8%
194917.348924087 3
 
0.8%
210935.038615054 3
 
0.8%
204750.498366411 3
 
0.8%
205018.506913318 3
 
0.8%
Other values (307) 345
87.3%
(Missing) 19
 
4.8%
ValueCountFrequency (%)
182970.965516527 1
0.3%
183027.509098842 1
0.3%
183042.639859252 2
0.5%
183119.924231899 1
0.3%
185678.592751428 1
0.3%
185716.678125288 1
0.3%
185799.527128936 1
0.3%
185800.085666831 1
0.3%
185854.99569793 1
0.3%
185945.598122621 1
0.3%
ValueCountFrequency (%)
213676.319090609 1
 
0.3%
212409.034805804 1
 
0.3%
212251.603548884 1
 
0.3%
212205.324163557 1
 
0.3%
212143.778930005 2
0.5%
212131.75626657 1
 
0.3%
212127.772315316 3
0.8%
212117.206942934 1
 
0.3%
212111.336830711 3
0.8%
212105.982273849 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct317
Distinct (%)84.3%
Missing19
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean450036.37
Minimum439007.77
Maximum461358.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:07:10.371100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439007.77
5-th percentile442295.59
Q1446098.97
median451057.53
Q3452268.13
95-th percentile459721.99
Maximum461358.97
Range22351.198
Interquartile range (IQR)6169.1638

Descriptive statistics

Standard deviation5219.7209
Coefficient of variation (CV)0.011598443
Kurtosis-0.4949193
Mean450036.37
Median Absolute Deviation (MAD)3716.6046
Skewness0.27634182
Sum1.6921367 × 108
Variance27245486
MonotonicityNot monotonic
2024-05-11T15:07:10.623630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446341.469456035 4
 
1.0%
442698.285576063 3
 
0.8%
451443.482518591 3
 
0.8%
448059.842030801 3
 
0.8%
442456.748277117 3
 
0.8%
448197.171823144 3
 
0.8%
454104.088948705 3
 
0.8%
448663.480515858 3
 
0.8%
451520.024760224 3
 
0.8%
451331.654449855 3
 
0.8%
Other values (307) 345
87.3%
(Missing) 19
 
4.8%
ValueCountFrequency (%)
439007.770863139 1
0.3%
439178.125476649 1
0.3%
439182.870671785 1
0.3%
441410.613140173 1
0.3%
441651.560578965 1
0.3%
441781.634613774 1
0.3%
441811.982687587 1
0.3%
441840.575654346 2
0.5%
442095.332266396 1
0.3%
442097.494275893 1
0.3%
ValueCountFrequency (%)
461358.969219933 1
0.3%
461342.980917319 1
0.3%
461335.356566932 1
0.3%
461328.8365 1
0.3%
461224.014056627 1
0.3%
461207.244729609 2
0.5%
461175.40204195 1
0.3%
461173.522951977 1
0.3%
461162.92 1
0.3%
461159.384486912 1
0.3%

문화체육업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
무도학원업
365 
<NA>
 
30

Length

Max length5
Median length5
Mean length4.9240506
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
무도학원업 365
92.4%
<NA> 30
 
7.6%

Length

2024-05-11T15:07:10.869611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:11.047321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무도학원업 365
92.4%
na 30
 
7.6%

공사립구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
사립
365 
<NA>
 
30

Length

Max length4
Median length2
Mean length2.1518987
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 365
92.4%
<NA> 30
 
7.6%

Length

2024-05-11T15:07:11.263491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:11.443321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 365
92.4%
na 30
 
7.6%

보험가입여부코드
Categorical

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
245 
0
122 
Y
 
23
1
 
5

Length

Max length4
Median length4
Mean length2.8607595
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> 245
62.0%
0 122
30.9%
Y 23
 
5.8%
1 5
 
1.3%

Length

2024-05-11T15:07:11.642352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:11.908041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 245
62.0%
0 122
30.9%
y 23
 
5.8%
1 5
 
1.3%

지도자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
295 
0
93 
1
 
6
2
 
1

Length

Max length4
Median length4
Mean length3.2405063
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 295
74.7%
0 93
 
23.5%
1 6
 
1.5%
2 1
 
0.3%

Length

2024-05-11T15:07:12.129454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:12.330377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 295
74.7%
0 93
 
23.5%
1 6
 
1.5%
2 1
 
0.3%

건축물동수
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
239 
0
138 
1
 
18

Length

Max length4
Median length4
Mean length2.8151899
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> 239
60.5%
0 138
34.9%
1 18
 
4.6%

Length

2024-05-11T15:07:12.542406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:12.748870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 239
60.5%
0 138
34.9%
1 18
 
4.6%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct43
Distinct (%)24.0%
Missing216
Missing (%)54.7%
Infinite0
Infinite (%)0.0%
Mean563.54084
Minimum0
Maximum10469.08
Zeros134
Zeros (%)33.9%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T15:07:12.968343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q334.65
95-th percentile3354.75
Maximum10469.08
Range10469.08
Interquartile range (IQR)34.65

Descriptive statistics

Standard deviation1781.541
Coefficient of variation (CV)3.1613344
Kurtosis17.673514
Mean563.54084
Median Absolute Deviation (MAD)0
Skewness4.1857504
Sum100873.81
Variance3173888.5
MonotonicityNot monotonic
2024-05-11T15:07:13.234223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.0 134
33.9%
7586.0 3
 
0.8%
832.75 2
 
0.5%
1701.19 1
 
0.3%
1018.21 1
 
0.3%
683.62 1
 
0.3%
10169.63 1
 
0.3%
10469.08 1
 
0.3%
866.52 1
 
0.3%
680.28 1
 
0.3%
Other values (33) 33
 
8.4%
(Missing) 216
54.7%
ValueCountFrequency (%)
0.0 134
33.9%
69.3 1
 
0.3%
91.54 1
 
0.3%
129.92 1
 
0.3%
196.43 1
 
0.3%
226.2 1
 
0.3%
255.94 1
 
0.3%
283.3 1
 
0.3%
398.42 1
 
0.3%
418.0 1
 
0.3%
ValueCountFrequency (%)
10469.08 1
 
0.3%
10169.63 1
 
0.3%
9905.44 1
 
0.3%
7628.12 1
 
0.3%
7586.0 3
0.8%
3942.0 1
 
0.3%
3865.5 1
 
0.3%
3298.0 1
 
0.3%
3091.45 1
 
0.3%
2686.7 1
 
0.3%

회원모집총인원
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
383 
0
 
9
250
 
1
30
 
1
20
 
1

Length

Max length4
Median length4
Mean length3.9189873
Min length1

Unique

Unique3 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 383
97.0%
0 9
 
2.3%
250 1
 
0.3%
30 1
 
0.3%
20 1
 
0.3%

Length

2024-05-11T15:07:13.476363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:07:13.667459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 383
97.0%
0 9
 
2.3%
250 1
 
0.3%
30 1
 
0.3%
20 1
 
0.3%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing395
Missing (%)100.0%
Memory size3.6 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing395
Missing (%)100.0%
Memory size3.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03060000CDFH33011120010000012001-08-16<NA>1영업/정상13영업중<NA><NA><NA><NA>436-0085<NA>131-810서울특별시 중랑구 망우동 563-4서울특별시 중랑구 망우로 384 (망우동)02163조이 스포츠댄스2023-03-30 21:31:38U2022-12-04 00:01:00.0<NA>208311.301971455130.240271<NA><NA><NA><NA><NA><NA><NA><NA><NA>
13200000CDFH330111201100000120110725<NA>3폐업3폐업20220420<NA><NA><NA>02-882-2467<NA>151015서울특별시 관악구 신림동 1422-17 403호서울특별시 관악구 남부순환로 1627, 403호 (신림동)<NA>백만불 댄스 무도학원2022-04-20 14:33:49U2021-12-03 22:02:00.0<NA>193859.537538442511.026089<NA><NA><NA><NA><NA><NA><NA><NA><NA>
23010000CDFH33011119930000011993-01-14<NA>4취소/말소/만료/정지/중지35직권말소2023-03-29<NA><NA><NA><NA><NA>100-330서울특별시 중구 주교동 147-1<NA><NA>한국댄스무도학원2023-03-30 10:23:04U2022-12-04 00:01:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33090000CDFH33011119950000011995-08-31<NA>3폐업3폐업2007-12-04<NA><NA><NA><NA><NA>132-908서울특별시 도봉구 창동 333-2 한성빌디802호서울특별시 도봉구 노해로65길 11 (창동,한성빌디802호)<NA>대니박댄스스쿨2023-06-22 18:02:44U2022-12-05 22:04:00.0<NA>204004.945535461048.885009<NA><NA><NA><NA><NA><NA><NA><NA><NA>
43090000CDFH33011119980000011998-09-11<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>132-898서울특별시 도봉구 창동 5서울특별시 도봉구 마들로11가길 12 (창동)<NA>하바나댄스스포츠학원2023-06-26 09:55:32U2022-12-05 22:08:00.0<NA>204238.333861461159.384487<NA><NA><NA><NA><NA><NA><NA><NA><NA>
53010000CDFH33011120070000012007-09-21<NA>4취소/말소/만료/정지/중지35직권말소2023-07-28<NA><NA><NA>2268-3339<NA>100-230서울특별시 중구 수표동 11-7<NA><NA>탑 댄스스포츠2023-07-31 13:44:38U2022-12-08 00:02:00.0<NA>199049.025989451709.766105<NA><NA><NA><NA><NA><NA><NA><NA><NA>
63010000CDFH33011120040000012004-09-15<NA>4취소/말소/만료/정지/중지35직권말소2023-07-28<NA><NA><NA>2279-4435<NA>100-411서울특별시 중구 광희동1가 98<NA><NA>국제스포츠댄스학원2023-07-31 13:43:42U2022-12-08 00:02:00.0<NA>200411.522051451397.541418<NA><NA><NA><NA><NA><NA><NA><NA><NA>
73010000CDFH33011120030000012003-12-06<NA>4취소/말소/만료/정지/중지35직권말소2023-07-28<NA><NA><NA>2238-4631<NA>100-868서울특별시 중구 황학동 1<NA><NA>한국댄스학원2023-07-31 13:43:03U2022-12-08 00:02:00.0<NA>201628.053846452025.526057<NA><NA><NA><NA><NA><NA><NA><NA><NA>
83210000CDFH33011119960000011996-10-18<NA>3폐업3폐업2023-09-19<NA><NA><NA>542-9521<NA>137-902서울특별시 서초구 잠원동 12-25서울특별시 서초구 강남대로 621 (잠원동)<NA>이해동댄스스포츠아카데미2023-09-19 14:49:31U2022-12-08 22:01:00.0<NA>201591.166842446100.917106<NA><NA><NA><NA><NA><NA><NA><NA><NA>
93180000CDFH33011120210000012021-04-12<NA>1영업/정상13영업중<NA><NA><NA><NA>02-703-4679<NA><NA>서울특별시 영등포구 영등포동5가 6-3서울특별시 영등포구 영등포로 231-1, 3층 (영등포동5가)07250이동석댄스스포츠스쿨2024-02-14 11:04:42U2023-12-01 23:06:00.0<NA>191732.892901446390.542846<NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
3853240000CDFH330111201100000120110706<NA>4취소/말소/만료/정지/중지35직권말소20211215<NA><NA><NA><NA><NA>134864서울특별시 강동구 천호동 452-3 지층서울특별시 강동구 천호대로 1041-8 (천호동,지층)<NA>천궁무도학원2021-12-16 10:43:01U2021-12-18 02:40:00.0<NA>211261.468606448409.006712무도학원업사립<NA>001632.220<NA><NA>
3863240000CDFH330111200500000420050725<NA>4취소/말소/만료/정지/중지35직권말소20211215<NA><NA><NA>484-0073<NA><NA>서울특별시 강동구 길동 458-3서울특별시 강동구 진황도로 110 (길동)05355아사모댄스스쿨2021-12-16 10:42:38U2021-12-18 02:40:00.0<NA>212131.756267448108.629965무도학원업사립Y01196.430<NA><NA>
3873240000CDFH33011120080000012008-01-11<NA>3폐업3폐업2023-03-07<NA><NA><NA>3427-2054<NA><NA>서울특별시 강동구 길동 413-50 3층서울특별시 강동구 천호대로177길 34 (길동)05353쉘위 댄스 학원2023-03-07 11:09:12U2022-12-02 23:00:00.0<NA>212127.772315448197.171823<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3883240000CDFH330111200700000120071204<NA>4취소/말소/만료/정지/중지35직권말소20180223<NA><NA><NA>477-0098<NA><NA>서울특별시 강동구 길동 414-4번지 강동 와이시티서울특별시 강동구 천호대로175길 42 (길동, 강동 와이시티)05353홍미애댄스스포츠아카데미2018-02-23 11:02:08I2018-08-31 23:59:59.0<NA>212078.284279448257.541434무도학원업사립<NA><NA>13298.0<NA><NA><NA>
3893240000CDFH330111201300000120130520<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 천호동 454-15 동원천호빌딩서울특별시 강동구 천호대로 1027 (천호동)05329하바나 댄스 스튜디오2022-03-28 13:08:58U2021-12-02 21:00:00.0<NA>211096.952458448450.575808<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3903050000CDFH330111202200000120220517<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 465-2서울특별시 동대문구 장한로2길 36, 2,3층 (장안동)02645더오페라2022-05-17 10:49:09I2021-12-04 23:09:00.0<NA>205851.797111451057.528462<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3913150000CDFH330111201200000120121019<NA>3폐업3폐업20220607<NA><NA><NA><NA><NA>157812서울특별시 강서구 공항동 72-30 2층서울특별시 강서구 공항대로 14-1, 2층 (공항동)07622공항댄스스포츠2022-06-07 21:09:52U2021-12-06 00:09:00.0<NA>183042.639859451015.8183<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3923090000CDFH330111201500000220150415<NA>1영업/정상13영업중<NA><NA><NA><NA>02-900-8877<NA>132898서울특별시 도봉구 창동 3-3 콤마프라자 지층서울특별시 도봉구 마들로11길 73, 지층층 7,8,9,1,15호 (창동)01414탑댄스 아카데미2022-06-30 09:15:04U2021-12-07 00:02:00.0<NA>204263.706546461207.24473<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3933200000CDFH330111199900000319990212<NA>3폐업3폐업20220805<NA><NA><NA><NA><NA>151899서울특별시 관악구 신림동 1568-1서울특별시 관악구 난곡로 302 (신림동)<NA>난곡무도학원2022-08-05 14:44:25U2021-12-08 00:07:00.0<NA>192403.860741442095.332266<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3943000000CDFH33011120110000012011-03-31<NA>1영업/정상13영업중<NA><NA><NA><NA>02-764-9788<NA>110-825서울특별시 종로구 숭인동 200-8서울특별시 종로구 종로66길 10 (숭인동)03115김동완 댄스학원2024-04-24 16:53:58U2023-12-03 22:06:00.0<NA>201834.95408452450.347246<NA><NA><NA><NA><NA><NA><NA><NA><NA>