Overview

Dataset statistics

Number of variables34
Number of observations5118
Missing cells51766
Missing cells (%)29.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory286.0 B

Variable types

Numeric7
Text8
DateTime5
Categorical10
Unsupported4

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-16141/S/1/datasetView.do

Alerts

인허가취소일자 is highly imbalanced (99.5%)Imbalance
상세영업상태명 is highly imbalanced (55.6%)Imbalance
공사립구분명 is highly imbalanced (54.0%)Imbalance
보험가입여부코드 is highly imbalanced (68.8%)Imbalance
폐업일자 has 2533 (49.5%) missing valuesMissing
휴업시작일자 has 5113 (99.9%) missing valuesMissing
휴업종료일자 has 5113 (99.9%) missing valuesMissing
재개업일자 has 5118 (100.0%) missing valuesMissing
전화번호 has 2084 (40.7%) missing valuesMissing
소재지면적 has 5118 (100.0%) missing valuesMissing
소재지우편번호 has 2065 (40.3%) missing valuesMissing
도로명주소 has 274 (5.4%) missing valuesMissing
도로명우편번호 has 2005 (39.2%) missing valuesMissing
좌표정보(X) has 171 (3.3%) missing valuesMissing
좌표정보(Y) has 171 (3.3%) missing valuesMissing
건축물동수 has 3684 (72.0%) missing valuesMissing
건축물연면적 has 3186 (62.3%) missing valuesMissing
회원모집총인원 has 4845 (94.7%) missing valuesMissing
세부업종명 has 5118 (100.0%) missing valuesMissing
법인명 has 5118 (100.0%) missing valuesMissing
건축물동수 is highly skewed (γ1 = 26.6822021)Skewed
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
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
건축물동수 has 1046 (20.4%) zerosZeros
건축물연면적 has 889 (17.4%) zerosZeros
회원모집총인원 has 242 (4.7%) zerosZeros

Reproduction

Analysis started2024-05-11 07:02:26.680595
Analysis finished2024-05-11 07:02:29.805185
Duration3.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3139644.4
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.1 KiB
2024-05-11T07:02:29.999108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3030000
Q13080000
median3140000
Q33200000
95-th percentile3240000
Maximum3240000
Range240000
Interquartile range (IQR)120000

Descriptive statistics

Standard deviation67851.176
Coefficient of variation (CV)0.021611102
Kurtosis-1.1184731
Mean3139644.4
Median Absolute Deviation (MAD)60000
Skewness-0.16552813
Sum1.60687 × 1010
Variance4.6037821 × 109
MonotonicityNot monotonic
2024-05-11T07:02:30.475997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3230000 396
 
7.7%
3220000 314
 
6.1%
3240000 303
 
5.9%
3140000 301
 
5.9%
3150000 299
 
5.8%
3100000 273
 
5.3%
3200000 246
 
4.8%
3110000 239
 
4.7%
3180000 212
 
4.1%
3060000 208
 
4.1%
Other values (15) 2327
45.5%
ValueCountFrequency (%)
3000000 65
 
1.3%
3010000 57
 
1.1%
3020000 70
 
1.4%
3030000 164
3.2%
3040000 155
3.0%
3050000 194
3.8%
3060000 208
4.1%
3070000 206
4.0%
3080000 167
3.3%
3090000 187
3.7%
ValueCountFrequency (%)
3240000 303
5.9%
3230000 396
7.7%
3220000 314
6.1%
3210000 195
3.8%
3200000 246
4.8%
3190000 154
 
3.0%
3180000 212
4.1%
3170000 159
3.1%
3160000 206
4.0%
3150000 299
5.8%
Distinct597
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
2024-05-11T07:02:30.977367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters102360
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

Unique118 ?
Unique (%)2.3%

Sample

1st rowCDFH3301022012000004
2nd rowCDFH3301022002000001
3rd rowCDFH3301021996000014
4th rowCDFH3301022023000011
5th rowCDFH3301022023000003
ValueCountFrequency (%)
cdfh3301021994000001 25
 
0.5%
cdfh3301022001000002 25
 
0.5%
cdfh3301022000000001 25
 
0.5%
cdfh3301022000000002 25
 
0.5%
cdfh3301022009000001 25
 
0.5%
cdfh3301022008000001 25
 
0.5%
cdfh3301022001000001 25
 
0.5%
cdfh3301022016000001 24
 
0.5%
cdfh3301022014000001 24
 
0.5%
cdfh3301022020000002 24
 
0.5%
Other values (587) 4871
95.2%
2024-05-11T07:02:31.824399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41231
40.3%
3 11533
 
11.3%
2 10689
 
10.4%
1 10061
 
9.8%
C 5118
 
5.0%
D 5118
 
5.0%
F 5118
 
5.0%
H 5118
 
5.0%
9 3552
 
3.5%
4 1231
 
1.2%
Other values (4) 3591
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81888
80.0%
Uppercase Letter 20472
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41231
50.4%
3 11533
 
14.1%
2 10689
 
13.1%
1 10061
 
12.3%
9 3552
 
4.3%
4 1231
 
1.5%
5 1037
 
1.3%
8 922
 
1.1%
7 817
 
1.0%
6 815
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 5118
25.0%
D 5118
25.0%
F 5118
25.0%
H 5118
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 81888
80.0%
Latin 20472
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41231
50.4%
3 11533
 
14.1%
2 10689
 
13.1%
1 10061
 
12.3%
9 3552
 
4.3%
4 1231
 
1.5%
5 1037
 
1.3%
8 922
 
1.1%
7 817
 
1.0%
6 815
 
1.0%
Latin
ValueCountFrequency (%)
C 5118
25.0%
D 5118
25.0%
F 5118
25.0%
H 5118
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41231
40.3%
3 11533
 
11.3%
2 10689
 
10.4%
1 10061
 
9.8%
C 5118
 
5.0%
D 5118
 
5.0%
F 5118
 
5.0%
H 5118
 
5.0%
9 3552
 
3.5%
4 1231
 
1.2%
Other values (4) 3591
 
3.5%
Distinct3659
Distinct (%)71.5%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
Minimum1971-02-04 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T07:02:32.265520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:02:32.726374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
<NA>
5114 
20150904
 
2
20171212
 
1
20120523
 
1

Length

Max length8
Median length4
Mean length4.0031262
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5114
99.9%
20150904 2
 
< 0.1%
20171212 1
 
< 0.1%
20120523 1
 
< 0.1%

Length

2024-05-11T07:02:33.192785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:02:33.627797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5114
99.9%
20150904 2
 
< 0.1%
20171212 1
 
< 0.1%
20120523 1
 
< 0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
1
2516 
3
2215 
4
378 
2
 
5
5
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 2516
49.2%
3 2215
43.3%
4 378
 
7.4%
2 5
 
0.1%
5 4
 
0.1%

Length

2024-05-11T07:02:33.996199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:02:34.388967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2516
49.2%
3 2215
43.3%
4 378
 
7.4%
2 5
 
0.1%
5 4
 
0.1%

영업상태명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
영업/정상
2516 
폐업
2215 
취소/말소/만료/정지/중지
378 
휴업
 
5
제외/삭제/전출
 
4

Length

Max length14
Median length8
Mean length4.3657679
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 2516
49.2%
폐업 2215
43.3%
취소/말소/만료/정지/중지 378
 
7.4%
휴업 5
 
0.1%
제외/삭제/전출 4
 
0.1%

Length

2024-05-11T07:02:34.877651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:02:35.296205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 2516
49.2%
폐업 2215
43.3%
취소/말소/만료/정지/중지 378
 
7.4%
휴업 5
 
0.1%
제외/삭제/전출 4
 
0.1%

상세영업상태코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.284095
Minimum2
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.1 KiB
2024-05-11T07:02:35.659283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median13
Q313
95-th percentile35
Maximum35
Range33
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.4637997
Coefficient of variation (CV)0.82299895
Kurtosis2.5859156
Mean10.284095
Median Absolute Deviation (MAD)10
Skewness1.5701674
Sum52634
Variance71.635905
MonotonicityNot monotonic
2024-05-11T07:02:36.315385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
13 2516
49.2%
3 2215
43.3%
35 373
 
7.3%
2 5
 
0.1%
15 4
 
0.1%
31 2
 
< 0.1%
32 2
 
< 0.1%
30 1
 
< 0.1%
ValueCountFrequency (%)
2 5
 
0.1%
3 2215
43.3%
13 2516
49.2%
15 4
 
0.1%
30 1
 
< 0.1%
31 2
 
< 0.1%
32 2
 
< 0.1%
35 373
 
7.3%
ValueCountFrequency (%)
35 373
 
7.3%
32 2
 
< 0.1%
31 2
 
< 0.1%
30 1
 
< 0.1%
15 4
 
0.1%
13 2516
49.2%
3 2215
43.3%
2 5
 
0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
영업중
2516 
폐업
2215 
직권말소
373 
휴업
 
5
전출
 
4
Other values (3)
 
5

Length

Max length4
Median length3
Mean length2.6393122
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 2516
49.2%
폐업 2215
43.3%
직권말소 373
 
7.3%
휴업 5
 
0.1%
전출 4
 
0.1%
등록취소 2
 
< 0.1%
신고취소 2
 
< 0.1%
허가취소 1
 
< 0.1%

Length

2024-05-11T07:02:36.861703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:02:37.271288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 2516
49.2%
폐업 2215
43.3%
직권말소 373
 
7.3%
휴업 5
 
0.1%
전출 4
 
0.1%
등록취소 2
 
< 0.1%
신고취소 2
 
< 0.1%
허가취소 1
 
< 0.1%

폐업일자
Text

MISSING 

Distinct1822
Distinct (%)70.5%
Missing2533
Missing (%)49.5%
Memory size40.1 KiB
2024-05-11T07:02:38.018722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.0796905
Min length8

Characters and Unicode

Total characters20886
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

Unique1465 ?
Unique (%)56.7%

Sample

1st row2023-01-31
2nd row2021-07-10
3rd row2023-03-06
4th row20220329
5th row20220405
ValueCountFrequency (%)
20211215 30
 
1.2%
20200207 23
 
0.9%
20200722 23
 
0.9%
20200618 22
 
0.9%
20210108 21
 
0.8%
20151106 21
 
0.8%
20190806 18
 
0.7%
20141020 17
 
0.7%
20200522 17
 
0.7%
20200625 16
 
0.6%
Other values (1812) 2377
92.0%
2024-05-11T07:02:39.812525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6777
32.4%
2 4765
22.8%
1 3685
17.6%
9 1054
 
5.0%
3 903
 
4.3%
7 730
 
3.5%
8 723
 
3.5%
5 696
 
3.3%
6 677
 
3.2%
4 670
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20680
99.0%
Dash Punctuation 206
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6777
32.8%
2 4765
23.0%
1 3685
17.8%
9 1054
 
5.1%
3 903
 
4.4%
7 730
 
3.5%
8 723
 
3.5%
5 696
 
3.4%
6 677
 
3.3%
4 670
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 206
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6777
32.4%
2 4765
22.8%
1 3685
17.6%
9 1054
 
5.0%
3 903
 
4.3%
7 730
 
3.5%
8 723
 
3.5%
5 696
 
3.3%
6 677
 
3.2%
4 670
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6777
32.4%
2 4765
22.8%
1 3685
17.6%
9 1054
 
5.0%
3 903
 
4.3%
7 730
 
3.5%
8 723
 
3.5%
5 696
 
3.3%
6 677
 
3.2%
4 670
 
3.2%

휴업시작일자
Date

MISSING 

Distinct5
Distinct (%)100.0%
Missing5113
Missing (%)99.9%
Memory size40.1 KiB
Minimum2013-11-18 00:00:00
Maximum2023-06-24 00:00:00
2024-05-11T07:02:40.707724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:02:41.116754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

휴업종료일자
Date

MISSING 

Distinct5
Distinct (%)100.0%
Missing5113
Missing (%)99.9%
Memory size40.1 KiB
Minimum2015-12-30 00:00:00
Maximum2025-12-08 00:00:00
2024-05-11T07:02:41.587465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:02:42.216765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5118
Missing (%)100.0%
Memory size45.1 KiB

전화번호
Text

MISSING 

Distinct2831
Distinct (%)93.3%
Missing2084
Missing (%)40.7%
Memory size40.1 KiB
2024-05-11T07:02:43.025024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length9.3223467
Min length1

Characters and Unicode

Total characters28284
Distinct characters17
Distinct categories7 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2643 ?
Unique (%)87.1%

Sample

1st row02-835-8253
2nd row02-858-6585
3rd row02-2653-8882
4th row417-8512
5th row2604-6565
ValueCountFrequency (%)
02 24
 
0.8%
302-9583 3
 
0.1%
2611-4786 3
 
0.1%
2642-8533 3
 
0.1%
430-1126 3
 
0.1%
566-4881 3
 
0.1%
02-2293-8770 3
 
0.1%
02-3417-0321 3
 
0.1%
964-6523 3
 
0.1%
993-1716 3
 
0.1%
Other values (2839) 3027
98.3%
2024-05-11T07:02:44.729450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 3952
14.0%
2 3768
13.3%
0 2987
10.6%
3 2415
8.5%
4 2377
8.4%
6 2245
7.9%
8 2235
7.9%
7 2114
7.5%
5 2077
7.3%
9 2055
7.3%
Other values (7) 2059
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24222
85.6%
Dash Punctuation 3952
 
14.0%
Space Separator 67
 
0.2%
Close Punctuation 27
 
0.1%
Other Punctuation 10
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3768
15.6%
0 2987
12.3%
3 2415
10.0%
4 2377
9.8%
6 2245
9.3%
8 2235
9.2%
7 2114
8.7%
5 2077
8.6%
9 2055
8.5%
1 1949
8.0%
Other Punctuation
ValueCountFrequency (%)
. 7
70.0%
, 3
30.0%
Dash Punctuation
ValueCountFrequency (%)
- 3952
100.0%
Space Separator
ValueCountFrequency (%)
67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28284
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 3952
14.0%
2 3768
13.3%
0 2987
10.6%
3 2415
8.5%
4 2377
8.4%
6 2245
7.9%
8 2235
7.9%
7 2114
7.5%
5 2077
7.3%
9 2055
7.3%
Other values (7) 2059
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28284
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 3952
14.0%
2 3768
13.3%
0 2987
10.6%
3 2415
8.5%
4 2377
8.4%
6 2245
7.9%
8 2235
7.9%
7 2114
7.5%
5 2077
7.3%
9 2055
7.3%
Other values (7) 2059
7.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5118
Missing (%)100.0%
Memory size45.1 KiB

소재지우편번호
Text

MISSING 

Distinct1570
Distinct (%)51.4%
Missing2065
Missing (%)40.3%
Memory size40.1 KiB
2024-05-11T07:02:45.930015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0488045
Min length6

Characters and Unicode

Total characters18467
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

Unique895 ?
Unique (%)29.3%

Sample

1st row156-844
2nd row152-802
3rd row138-845
4th row152-873
5th row140887
ValueCountFrequency (%)
138200 18
 
0.6%
158070 18
 
0.6%
151015 16
 
0.5%
151050 14
 
0.5%
138854 12
 
0.4%
158861 12
 
0.4%
157280 11
 
0.4%
158827 10
 
0.3%
138862 10
 
0.3%
138220 9
 
0.3%
Other values (1560) 2923
95.7%
2024-05-11T07:02:47.603184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4331
23.5%
8 3200
17.3%
3 2327
12.6%
5 1820
9.9%
0 1630
 
8.8%
2 1488
 
8.1%
4 987
 
5.3%
7 937
 
5.1%
9 821
 
4.4%
6 777
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18318
99.2%
Dash Punctuation 149
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4331
23.6%
8 3200
17.5%
3 2327
12.7%
5 1820
9.9%
0 1630
 
8.9%
2 1488
 
8.1%
4 987
 
5.4%
7 937
 
5.1%
9 821
 
4.5%
6 777
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18467
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4331
23.5%
8 3200
17.3%
3 2327
12.6%
5 1820
9.9%
0 1630
 
8.8%
2 1488
 
8.1%
4 987
 
5.3%
7 937
 
5.1%
9 821
 
4.4%
6 777
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18467
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4331
23.5%
8 3200
17.3%
3 2327
12.6%
5 1820
9.9%
0 1630
 
8.8%
2 1488
 
8.1%
4 987
 
5.3%
7 937
 
5.1%
9 821
 
4.4%
6 777
 
4.2%
Distinct4902
Distinct (%)96.7%
Missing50
Missing (%)1.0%
Memory size40.1 KiB
2024-05-11T07:02:48.355226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length51
Mean length25.375493
Min length13

Characters and Unicode

Total characters128603
Distinct characters458
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4749 ?
Unique (%)93.7%

Sample

1st row서울특별시 동작구 상도동 259-41 4층
2nd row서울특별시 서대문구 북가좌동 286-18 2층
3rd row서울특별시 강서구 가양동 1474 대림경동아파트 상가동 304호
4th row서울특별시 서초구 잠원동 10-48 명성빌딩
5th row서울특별시 영등포구 신길동 4397
ValueCountFrequency (%)
서울특별시 5068
 
20.7%
2층 493
 
2.0%
3층 398
 
1.6%
송파구 392
 
1.6%
강남구 313
 
1.3%
강동구 303
 
1.2%
양천구 303
 
1.2%
강서구 299
 
1.2%
노원구 273
 
1.1%
관악구 246
 
1.0%
Other values (6383) 16355
66.9%
2024-05-11T07:02:49.657429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23166
 
18.0%
6248
 
4.9%
5816
 
4.5%
5403
 
4.2%
5192
 
4.0%
5080
 
4.0%
5068
 
3.9%
5068
 
3.9%
1 4842
 
3.8%
- 4246
 
3.3%
Other values (448) 58474
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74824
58.2%
Decimal Number 25525
 
19.8%
Space Separator 23166
 
18.0%
Dash Punctuation 4246
 
3.3%
Other Punctuation 213
 
0.2%
Uppercase Letter 200
 
0.2%
Close Punctuation 194
 
0.2%
Open Punctuation 189
 
0.1%
Math Symbol 32
 
< 0.1%
Lowercase Letter 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6248
 
8.4%
5816
 
7.8%
5403
 
7.2%
5192
 
6.9%
5080
 
6.8%
5068
 
6.8%
5068
 
6.8%
3872
 
5.2%
3304
 
4.4%
1682
 
2.2%
Other values (396) 28091
37.5%
Uppercase Letter
ValueCountFrequency (%)
B 80
40.0%
A 49
24.5%
K 13
 
6.5%
S 13
 
6.5%
M 5
 
2.5%
D 5
 
2.5%
C 4
 
2.0%
T 4
 
2.0%
P 4
 
2.0%
I 3
 
1.5%
Other values (12) 20
 
10.0%
Decimal Number
ValueCountFrequency (%)
1 4842
19.0%
2 3805
14.9%
3 3316
13.0%
4 2453
9.6%
0 2279
8.9%
5 2118
8.3%
6 1949
7.6%
7 1732
 
6.8%
8 1543
 
6.0%
9 1485
 
5.8%
Other values (3) 3
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 6
42.9%
c 2
 
14.3%
b 2
 
14.3%
a 1
 
7.1%
o 1
 
7.1%
w 1
 
7.1%
r 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 189
88.7%
@ 14
 
6.6%
. 4
 
1.9%
/ 4
 
1.9%
? 2
 
0.9%
Space Separator
ValueCountFrequency (%)
23166
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4246
100.0%
Close Punctuation
ValueCountFrequency (%)
) 194
100.0%
Open Punctuation
ValueCountFrequency (%)
( 189
100.0%
Math Symbol
ValueCountFrequency (%)
~ 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74823
58.2%
Common 53565
41.7%
Latin 214
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6248
 
8.4%
5816
 
7.8%
5403
 
7.2%
5192
 
6.9%
5080
 
6.8%
5068
 
6.8%
5068
 
6.8%
3872
 
5.2%
3304
 
4.4%
1682
 
2.2%
Other values (395) 28090
37.5%
Latin
ValueCountFrequency (%)
B 80
37.4%
A 49
22.9%
K 13
 
6.1%
S 13
 
6.1%
e 6
 
2.8%
M 5
 
2.3%
D 5
 
2.3%
C 4
 
1.9%
T 4
 
1.9%
P 4
 
1.9%
Other values (19) 31
 
14.5%
Common
ValueCountFrequency (%)
23166
43.2%
1 4842
 
9.0%
- 4246
 
7.9%
2 3805
 
7.1%
3 3316
 
6.2%
4 2453
 
4.6%
0 2279
 
4.3%
5 2118
 
4.0%
6 1949
 
3.6%
7 1732
 
3.2%
Other values (13) 3659
 
6.8%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74823
58.2%
ASCII 53776
41.8%
None 3
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23166
43.1%
1 4842
 
9.0%
- 4246
 
7.9%
2 3805
 
7.1%
3 3316
 
6.2%
4 2453
 
4.6%
0 2279
 
4.2%
5 2118
 
3.9%
6 1949
 
3.6%
7 1732
 
3.2%
Other values (39) 3870
 
7.2%
Hangul
ValueCountFrequency (%)
6248
 
8.4%
5816
 
7.8%
5403
 
7.2%
5192
 
6.9%
5080
 
6.8%
5068
 
6.8%
5068
 
6.8%
3872
 
5.2%
3304
 
4.4%
1682
 
2.2%
Other values (395) 28090
37.5%
None
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
CJK
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct4711
Distinct (%)97.3%
Missing274
Missing (%)5.4%
Memory size40.1 KiB
2024-05-11T07:02:50.618178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length55
Mean length30.698183
Min length21

Characters and Unicode

Total characters148702
Distinct characters505
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4582 ?
Unique (%)94.6%

Sample

1st row서울특별시 동작구 성대로10가길 5, 4층 (상도동)
2nd row서울특별시 서대문구 증가로 201, 2층 (북가좌동)
3rd row서울특별시 강서구 허준로 121, 304호 (가양동, 대림경동아파트 상가동)
4th row서울특별시 서초구 강남대로101안길 12, 명성빌딩 (잠원동)
5th row서울특별시 영등포구 여의대방로 93, 지층 (신길동)
ValueCountFrequency (%)
서울특별시 4844
 
16.9%
2층 527
 
1.8%
3층 471
 
1.6%
송파구 387
 
1.4%
강남구 309
 
1.1%
양천구 295
 
1.0%
강서구 286
 
1.0%
강동구 285
 
1.0%
노원구 263
 
0.9%
지하1층 238
 
0.8%
Other values (5315) 20746
72.4%
2024-05-11T07:02:52.113406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25035
 
16.8%
6431
 
4.3%
5767
 
3.9%
5264
 
3.5%
5044
 
3.4%
5029
 
3.4%
) 4965
 
3.3%
( 4962
 
3.3%
4868
 
3.3%
4845
 
3.3%
Other values (495) 76492
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86950
58.5%
Space Separator 25035
 
16.8%
Decimal Number 21980
 
14.8%
Close Punctuation 4965
 
3.3%
Open Punctuation 4962
 
3.3%
Other Punctuation 4071
 
2.7%
Dash Punctuation 431
 
0.3%
Uppercase Letter 238
 
0.2%
Math Symbol 46
 
< 0.1%
Lowercase Letter 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6431
 
7.4%
5767
 
6.6%
5264
 
6.1%
5044
 
5.8%
5029
 
5.8%
4868
 
5.6%
4845
 
5.6%
4844
 
5.6%
2503
 
2.9%
2500
 
2.9%
Other values (439) 39855
45.8%
Uppercase Letter
ValueCountFrequency (%)
B 114
47.9%
A 39
 
16.4%
S 19
 
8.0%
K 12
 
5.0%
M 8
 
3.4%
D 7
 
2.9%
C 7
 
2.9%
G 5
 
2.1%
L 4
 
1.7%
I 3
 
1.3%
Other values (12) 20
 
8.4%
Lowercase Letter
ValueCountFrequency (%)
e 7
30.4%
b 4
17.4%
i 2
 
8.7%
c 2
 
8.7%
o 1
 
4.3%
g 1
 
4.3%
n 1
 
4.3%
d 1
 
4.3%
l 1
 
4.3%
u 1
 
4.3%
Other values (2) 2
 
8.7%
Decimal Number
ValueCountFrequency (%)
1 4273
19.4%
2 3840
17.5%
3 3127
14.2%
4 2144
9.8%
0 1955
8.9%
5 1731
7.9%
6 1465
 
6.7%
7 1244
 
5.7%
8 1133
 
5.2%
9 1068
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 4061
99.8%
? 3
 
0.1%
/ 3
 
0.1%
@ 2
 
< 0.1%
! 1
 
< 0.1%
. 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
25035
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4965
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4962
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 431
100.0%
Math Symbol
ValueCountFrequency (%)
~ 46
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86950
58.5%
Common 61490
41.4%
Latin 261
 
0.2%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6431
 
7.4%
5767
 
6.6%
5264
 
6.1%
5044
 
5.8%
5029
 
5.8%
4868
 
5.6%
4845
 
5.6%
4844
 
5.6%
2503
 
2.9%
2500
 
2.9%
Other values (439) 39855
45.8%
Latin
ValueCountFrequency (%)
B 114
43.7%
A 39
 
14.9%
S 19
 
7.3%
K 12
 
4.6%
M 8
 
3.1%
D 7
 
2.7%
C 7
 
2.7%
e 7
 
2.7%
G 5
 
1.9%
b 4
 
1.5%
Other values (24) 39
 
14.9%
Common
ValueCountFrequency (%)
25035
40.7%
) 4965
 
8.1%
( 4962
 
8.1%
1 4273
 
6.9%
, 4061
 
6.6%
2 3840
 
6.2%
3 3127
 
5.1%
4 2144
 
3.5%
0 1955
 
3.2%
5 1731
 
2.8%
Other values (11) 5397
 
8.8%
Greek
ValueCountFrequency (%)
Ι 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86950
58.5%
ASCII 61750
41.5%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25035
40.5%
) 4965
 
8.0%
( 4962
 
8.0%
1 4273
 
6.9%
, 4061
 
6.6%
2 3840
 
6.2%
3 3127
 
5.1%
4 2144
 
3.5%
0 1955
 
3.2%
5 1731
 
2.8%
Other values (44) 5657
 
9.2%
Hangul
ValueCountFrequency (%)
6431
 
7.4%
5767
 
6.6%
5264
 
6.1%
5044
 
5.8%
5029
 
5.8%
4868
 
5.6%
4845
 
5.6%
4844
 
5.6%
2503
 
2.9%
2500
 
2.9%
Other values (439) 39855
45.8%
None
ValueCountFrequency (%)
Ι 1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Text

MISSING 

Distinct2067
Distinct (%)66.4%
Missing2005
Missing (%)39.2%
Memory size40.1 KiB
2024-05-11T07:02:53.185073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0697077
Min length5

Characters and Unicode

Total characters15782
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

Unique1389 ?
Unique (%)44.6%

Sample

1st row07044
2nd row03685
3rd row07525
4th row06525
5th row07433
ValueCountFrequency (%)
06325 9
 
0.3%
08365 7
 
0.2%
05211 7
 
0.2%
07295 7
 
0.2%
07599 6
 
0.2%
07946 6
 
0.2%
05257 6
 
0.2%
07343 6
 
0.2%
06971 6
 
0.2%
04735 6
 
0.2%
Other values (2057) 3047
97.9%
2024-05-11T07:02:54.757339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4039
25.6%
3 1549
 
9.8%
7 1478
 
9.4%
1 1420
 
9.0%
5 1419
 
9.0%
2 1306
 
8.3%
6 1300
 
8.2%
8 1254
 
7.9%
4 1125
 
7.1%
9 883
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15773
99.9%
Dash Punctuation 9
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4039
25.6%
3 1549
 
9.8%
7 1478
 
9.4%
1 1420
 
9.0%
5 1419
 
9.0%
2 1306
 
8.3%
6 1300
 
8.2%
8 1254
 
8.0%
4 1125
 
7.1%
9 883
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15782
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4039
25.6%
3 1549
 
9.8%
7 1478
 
9.4%
1 1420
 
9.0%
5 1419
 
9.0%
2 1306
 
8.3%
6 1300
 
8.2%
8 1254
 
7.9%
4 1125
 
7.1%
9 883
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15782
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4039
25.6%
3 1549
 
9.8%
7 1478
 
9.4%
1 1420
 
9.0%
5 1419
 
9.0%
2 1306
 
8.3%
6 1300
 
8.2%
8 1254
 
7.9%
4 1125
 
7.1%
9 883
 
5.6%
Distinct4346
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
2024-05-11T07:02:55.546921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length7.8528722
Min length1

Characters and Unicode

Total characters40191
Distinct characters625
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3900 ?
Unique (%)76.2%

Sample

1st row제이칼리쿠(태권도)
2nd row해솔태권도장
3rd row부부 용인대 TOP 태권도장
4th row마이 복싱 짐
5th rowTS국가대표MVP태권도장
ValueCountFrequency (%)
태권도 445
 
5.8%
태권도장 232
 
3.0%
용인대 173
 
2.2%
경희대 139
 
1.8%
체육관 125
 
1.6%
복싱 84
 
1.1%
한국체대 74
 
1.0%
합기도 55
 
0.7%
국가대표 53
 
0.7%
복싱클럽 39
 
0.5%
Other values (4224) 6305
81.6%
2024-05-11T07:02:56.777529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3246
 
8.1%
2649
 
6.6%
2610
 
6.5%
2598
 
6.5%
1867
 
4.6%
1500
 
3.7%
1390
 
3.5%
1090
 
2.7%
863
 
2.1%
524
 
1.3%
Other values (615) 21854
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33935
84.4%
Space Separator 2610
 
6.5%
Uppercase Letter 1399
 
3.5%
Decimal Number 620
 
1.5%
Open Punctuation 525
 
1.3%
Close Punctuation 525
 
1.3%
Lowercase Letter 453
 
1.1%
Other Punctuation 110
 
0.3%
Dash Punctuation 13
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3246
 
9.6%
2649
 
7.8%
2598
 
7.7%
1867
 
5.5%
1500
 
4.4%
1390
 
4.1%
1090
 
3.2%
863
 
2.5%
524
 
1.5%
509
 
1.5%
Other values (539) 17699
52.2%
Uppercase Letter
ValueCountFrequency (%)
T 171
12.2%
M 168
12.0%
A 133
 
9.5%
S 121
 
8.6%
B 79
 
5.6%
G 78
 
5.6%
K 78
 
5.6%
I 56
 
4.0%
Y 52
 
3.7%
O 50
 
3.6%
Other values (15) 413
29.5%
Lowercase Letter
ValueCountFrequency (%)
e 49
 
10.8%
o 42
 
9.3%
n 37
 
8.2%
i 36
 
7.9%
a 29
 
6.4%
m 29
 
6.4%
g 26
 
5.7%
r 26
 
5.7%
s 25
 
5.5%
y 22
 
4.9%
Other values (14) 132
29.1%
Decimal Number
ValueCountFrequency (%)
2 168
27.1%
1 116
18.7%
3 60
 
9.7%
8 41
 
6.6%
5 40
 
6.5%
7 40
 
6.5%
9 39
 
6.3%
4 39
 
6.3%
0 39
 
6.3%
6 38
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 42
38.2%
& 34
30.9%
, 12
 
10.9%
' 10
 
9.1%
? 5
 
4.5%
: 2
 
1.8%
/ 2
 
1.8%
1
 
0.9%
! 1
 
0.9%
1
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 502
95.6%
[ 23
 
4.4%
Close Punctuation
ValueCountFrequency (%)
) 502
95.6%
] 23
 
4.4%
Space Separator
ValueCountFrequency (%)
2610
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33929
84.4%
Common 4403
 
11.0%
Latin 1853
 
4.6%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3246
 
9.6%
2649
 
7.8%
2598
 
7.7%
1867
 
5.5%
1500
 
4.4%
1390
 
4.1%
1090
 
3.2%
863
 
2.5%
524
 
1.5%
509
 
1.5%
Other values (535) 17693
52.1%
Latin
ValueCountFrequency (%)
T 171
 
9.2%
M 168
 
9.1%
A 133
 
7.2%
S 121
 
6.5%
B 79
 
4.3%
G 78
 
4.2%
K 78
 
4.2%
I 56
 
3.0%
Y 52
 
2.8%
O 50
 
2.7%
Other values (40) 867
46.8%
Common
ValueCountFrequency (%)
2610
59.3%
( 502
 
11.4%
) 502
 
11.4%
2 168
 
3.8%
1 116
 
2.6%
3 60
 
1.4%
. 42
 
1.0%
8 41
 
0.9%
5 40
 
0.9%
7 40
 
0.9%
Other values (16) 282
 
6.4%
Han
ValueCountFrequency (%)
2
33.3%
2
33.3%
1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33928
84.4%
ASCII 6253
 
15.6%
CJK 6
 
< 0.1%
None 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3246
 
9.6%
2649
 
7.8%
2598
 
7.7%
1867
 
5.5%
1500
 
4.4%
1390
 
4.1%
1090
 
3.2%
863
 
2.5%
524
 
1.5%
509
 
1.5%
Other values (534) 17692
52.1%
ASCII
ValueCountFrequency (%)
2610
41.7%
( 502
 
8.0%
) 502
 
8.0%
T 171
 
2.7%
2 168
 
2.7%
M 168
 
2.7%
A 133
 
2.1%
S 121
 
1.9%
1 116
 
1.9%
B 79
 
1.3%
Other values (63) 1683
26.9%
CJK
ValueCountFrequency (%)
2
33.3%
2
33.3%
1
16.7%
1
16.7%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct4752
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
Minimum2002-10-22 17:59:13
Maximum2024-05-09 14:37:20
2024-05-11T07:02:57.369107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:02:57.828554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
I
2899 
U
2218 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 2899
56.6%
U 2218
43.3%
D 1
 
< 0.1%

Length

2024-05-11T07:02:58.357126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:02:58.823989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2899
56.6%
u 2218
43.3%
d 1
 
< 0.1%
Distinct1051
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T07:02:59.316932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:02:59.839506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
<NA>
2765 
태권도
1401 
권투
494 
합기도
 
143
검도
 
130
Other values (3)
 
185

Length

Max length4
Median length4
Mean length3.3901915
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row태권도
2nd row태권도
3rd row태권도
4th row권투
5th row태권도

Common Values

ValueCountFrequency (%)
<NA> 2765
54.0%
태권도 1401
27.4%
권투 494
 
9.7%
합기도 143
 
2.8%
검도 130
 
2.5%
유도 122
 
2.4%
레슬링 41
 
0.8%
우슈 22
 
0.4%

Length

2024-05-11T07:03:00.404804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:00.919256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2765
54.0%
태권도 1401
27.4%
권투 494
 
9.7%
합기도 143
 
2.8%
검도 130
 
2.5%
유도 122
 
2.4%
레슬링 41
 
0.8%
우슈 22
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4180
Distinct (%)84.5%
Missing171
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean199385.01
Minimum182882.61
Maximum216029.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.1 KiB
2024-05-11T07:03:01.516193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182882.61
5-th percentile185839.54
Q1192187.72
median201422.08
Q3205949.91
95-th percentile212011.27
Maximum216029.39
Range33146.778
Interquartile range (IQR)13762.192

Descriptive statistics

Standard deviation8292.7872
Coefficient of variation (CV)0.04159183
Kurtosis-1.1309701
Mean199385.01
Median Absolute Deviation (MAD)6884.3997
Skewness-0.13228445
Sum9.8635763 × 108
Variance68770320
MonotonicityNot monotonic
2024-05-11T07:03:02.267394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207373.50021477 7
 
0.1%
210045.748264305 6
 
0.1%
193989.272586157 5
 
0.1%
203196.800963466 5
 
0.1%
200841.726990037 5
 
0.1%
204992.451561361 5
 
0.1%
195766.388348198 5
 
0.1%
188317.369539448 4
 
0.1%
205588.636016926 4
 
0.1%
192458.239757393 4
 
0.1%
Other values (4170) 4897
95.7%
(Missing) 171
 
3.3%
ValueCountFrequency (%)
182882.61020059 1
< 0.1%
182968.796339956 1
< 0.1%
182983.398791677 1
< 0.1%
183017.198989475 1
< 0.1%
183046.848238676 1
< 0.1%
183049.525160207 1
< 0.1%
183094.694866371 1
< 0.1%
183096.228020098 1
< 0.1%
183116.294494255 1
< 0.1%
183138.257688198 1
< 0.1%
ValueCountFrequency (%)
216029.388021 1
< 0.1%
215875.024969 1
< 0.1%
215784.2264 2
< 0.1%
215527.721278 1
< 0.1%
215512.97537469 1
< 0.1%
215487.94428281 1
< 0.1%
215426.028109 1
< 0.1%
215422.746119624 1
< 0.1%
215401.064224577 2
< 0.1%
215379.100058 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4182
Distinct (%)84.5%
Missing171
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean449633.58
Minimum436946.36
Maximum465253.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.1 KiB
2024-05-11T07:03:02.998100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436946.36
5-th percentile441597.8
Q1444495.7
median449022.26
Q3453970.38
95-th percentile461206.29
Maximum465253.15
Range28306.793
Interquartile range (IQR)9474.6803

Descriptive statistics

Standard deviation6022.2502
Coefficient of variation (CV)0.013393684
Kurtosis-0.64800001
Mean449633.58
Median Absolute Deviation (MAD)4634.4557
Skewness0.44932031
Sum2.2243373 × 109
Variance36267498
MonotonicityNot monotonic
2024-05-11T07:03:03.433300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445545.656024061 7
 
0.1%
442930.687284628 6
 
0.1%
446346.562230998 5
 
0.1%
455429.846270094 5
 
0.1%
454721.505180141 5
 
0.1%
443183.576115254 5
 
0.1%
444020.397472042 5
 
0.1%
446299.352775446 4
 
0.1%
459964.099651861 4
 
0.1%
441774.679423362 4
 
0.1%
Other values (4172) 4897
95.7%
(Missing) 171
 
3.3%
ValueCountFrequency (%)
436946.358720615 1
 
< 0.1%
437647.525127383 1
 
< 0.1%
437689.38449215 1
 
< 0.1%
437753.206548839 1
 
< 0.1%
437799.809089881 2
< 0.1%
438294.344091932 1
 
< 0.1%
438307.022609784 3
0.1%
438307.423372216 2
< 0.1%
438356.170313032 1
 
< 0.1%
438367.332881743 1
 
< 0.1%
ValueCountFrequency (%)
465253.152004 1
< 0.1%
464959.058464501 1
< 0.1%
464941.802561026 1
< 0.1%
464814.717432497 2
< 0.1%
464788.229274616 1
< 0.1%
464638.133327247 1
< 0.1%
464598.721765819 1
< 0.1%
464597.202705501 2
< 0.1%
464498.162404483 1
< 0.1%
464448.684446374 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
체육도장업
4083 
<NA>
1035 

Length

Max length5
Median length5
Mean length4.7977726
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 (%)
체육도장업 4083
79.8%
<NA> 1035
 
20.2%

Length

2024-05-11T07:03:03.850711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:04.393284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체육도장업 4083
79.8%
na 1035
 
20.2%

공사립구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
사립
4082 
<NA>
1035 
공립
 
1

Length

Max length4
Median length2
Mean length2.4044549
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
사립 4082
79.8%
<NA> 1035
 
20.2%
공립 1
 
< 0.1%

Length

2024-05-11T07:03:04.893372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:05.248235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 4082
79.8%
na 1035
 
20.2%
공립 1
 
< 0.1%

보험가입여부코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
<NA>
4358 
0
748 
Y
 
11
1
 
1

Length

Max length4
Median length4
Mean length3.5545135
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4358
85.2%
0 748
 
14.6%
Y 11
 
0.2%
1 1
 
< 0.1%

Length

2024-05-11T07:03:05.648563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:06.151987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4358
85.2%
0 748
 
14.6%
y 11
 
0.2%
1 1
 
< 0.1%

지도자수
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size40.1 KiB
<NA>
3312 
1
1097 
0
696 
2
 
12
11
 
1

Length

Max length4
Median length4
Mean length2.9415787
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3312
64.7%
1 1097
 
21.4%
0 696
 
13.6%
2 12
 
0.2%
11 1
 
< 0.1%

Length

2024-05-11T07:03:06.763354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:03:07.159866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3312
64.7%
1 1097
 
21.4%
0 696
 
13.6%
2 12
 
0.2%
11 1
 
< 0.1%

건축물동수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct7
Distinct (%)0.5%
Missing3684
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean0.69804742
Minimum0
Maximum305
Zeros1046
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size45.1 KiB
2024-05-11T07:03:07.649279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum305
Range305
Interquartile range (IQR)1

Descriptive statistics

Standard deviation11.311372
Coefficient of variation (CV)16.204303
Kurtosis712.17952
Mean0.69804742
Median Absolute Deviation (MAD)0
Skewness26.682202
Sum1001
Variance127.94714
MonotonicityNot monotonic
2024-05-11T07:03:08.170905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1046
 
20.4%
1 380
 
7.4%
2 4
 
0.1%
305 1
 
< 0.1%
301 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
(Missing) 3684
72.0%
ValueCountFrequency (%)
0 1046
20.4%
1 380
 
7.4%
2 4
 
0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
301 1
 
< 0.1%
305 1
 
< 0.1%
ValueCountFrequency (%)
305 1
 
< 0.1%
301 1
 
< 0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%
2 4
 
0.1%
1 380
 
7.4%
0 1046
20.4%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct988
Distinct (%)51.1%
Missing3186
Missing (%)62.3%
Infinite0
Infinite (%)0.0%
Mean1362.4623
Minimum0
Maximum135170.79
Zeros889
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size45.1 KiB
2024-05-11T07:03:08.943973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median149.8
Q3947.0625
95-th percentile4832.844
Maximum135170.79
Range135170.79
Interquartile range (IQR)947.0625

Descriptive statistics

Standard deviation5381.128
Coefficient of variation (CV)3.9495612
Kurtosis239.24552
Mean1362.4623
Median Absolute Deviation (MAD)149.8
Skewness12.585111
Sum2632277.1
Variance28956539
MonotonicityNot monotonic
2024-05-11T07:03:09.645036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 889
 
17.4%
17516.44 3
 
0.1%
867.65 3
 
0.1%
1130.94 3
 
0.1%
792.71 3
 
0.1%
492.0 3
 
0.1%
609.45 3
 
0.1%
903.95 3
 
0.1%
467.28 2
 
< 0.1%
2316.17 2
 
< 0.1%
Other values (978) 1018
 
19.9%
(Missing) 3186
62.3%
ValueCountFrequency (%)
0.0 889
17.4%
66.82 1
 
< 0.1%
67.29 1
 
< 0.1%
69.0 1
 
< 0.1%
70.34 1
 
< 0.1%
71.73 1
 
< 0.1%
73.0 1
 
< 0.1%
78.48 1
 
< 0.1%
78.5 1
 
< 0.1%
80.51 1
 
< 0.1%
ValueCountFrequency (%)
135170.79 1
< 0.1%
76448.64 1
< 0.1%
63860.73 1
< 0.1%
45768.27 1
< 0.1%
43457.0 1
< 0.1%
43215.07 1
< 0.1%
39190.94 2
< 0.1%
37349.05 1
< 0.1%
31759.58 1
< 0.1%
30645.75 2
< 0.1%

회원모집총인원
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)5.9%
Missing4845
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean12.263736
Minimum0
Maximum800
Zeros242
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size45.1 KiB
2024-05-11T07:03:10.284545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile72
Maximum800
Range800
Interquartile range (IQR)0

Descriptive statistics

Standard deviation61.719688
Coefficient of variation (CV)5.0326986
Kurtosis111.89877
Mean12.263736
Median Absolute Deviation (MAD)0
Skewness9.7648739
Sum3348
Variance3809.3199
MonotonicityNot monotonic
2024-05-11T07:03:10.864398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 242
 
4.7%
100 6
 
0.1%
50 6
 
0.1%
80 3
 
0.1%
30 2
 
< 0.1%
70 2
 
< 0.1%
20 2
 
< 0.1%
40 2
 
< 0.1%
60 1
 
< 0.1%
65 1
 
< 0.1%
Other values (6) 6
 
0.1%
(Missing) 4845
94.7%
ValueCountFrequency (%)
0 242
4.7%
20 2
 
< 0.1%
30 2
 
< 0.1%
38 1
 
< 0.1%
40 2
 
< 0.1%
50 6
 
0.1%
60 1
 
< 0.1%
65 1
 
< 0.1%
70 2
 
< 0.1%
75 1
 
< 0.1%
ValueCountFrequency (%)
800 1
 
< 0.1%
500 1
 
< 0.1%
200 1
 
< 0.1%
150 1
 
< 0.1%
100 6
0.1%
80 3
0.1%
75 1
 
< 0.1%
70 2
 
< 0.1%
65 1
 
< 0.1%
60 1
 
< 0.1%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5118
Missing (%)100.0%
Memory size45.1 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5118
Missing (%)100.0%
Memory size45.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03190000CDFH33010220120000042012-07-25<NA>3폐업3폐업2023-01-31<NA><NA><NA><NA><NA>156-844서울특별시 동작구 상도동 259-41 4층서울특별시 동작구 성대로10가길 5, 4층 (상도동)07044제이칼리쿠(태권도)2023-02-28 11:04:37U2022-12-03 00:03:00.0태권도194132.733697443909.975049<NA><NA><NA><NA><NA><NA><NA><NA><NA>
13120000CDFH33010220020000012002-03-13<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 북가좌동 286-18 2층서울특별시 서대문구 증가로 201, 2층 (북가좌동)03685해솔태권도장2023-02-28 13:39:12U2022-12-03 00:03:00.0태권도192503.770166453078.703665<NA><NA><NA><NA><NA><NA><NA><NA><NA>
23150000CDFH33010219960000141996-12-27<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 가양동 1474 대림경동아파트 상가동 304호서울특별시 강서구 허준로 121, 304호 (가양동, 대림경동아파트 상가동)07525부부 용인대 TOP 태권도장2023-02-28 13:53:08U2022-12-03 00:03:00.0태권도187034.317305451572.87705<NA><NA><NA><NA><NA><NA><NA><NA><NA>
33210000CDFH33010220230000112023-11-09<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 잠원동 10-48 명성빌딩서울특별시 서초구 강남대로101안길 12, 명성빌딩 (잠원동)06525마이 복싱 짐2023-11-09 11:25:43I2022-10-31 23:01:00.0권투201508.13815446036.074661<NA><NA><NA><NA><NA><NA><NA><NA><NA>
43180000CDFH33010220230000032023-03-02<NA>1영업/정상13영업중<NA><NA><NA><NA>02-835-8253<NA><NA>서울특별시 영등포구 신길동 4397서울특별시 영등포구 여의대방로 93, 지층 (신길동)07433TS국가대표MVP태권도장2023-03-02 10:56:37I2022-12-03 00:04:00.0태권도192581.012004443927.696666<NA><NA><NA><NA><NA><NA><NA><NA><NA>
53160000CDFH33010220230000022023-03-02<NA>1영업/정상13영업중<NA><NA><NA><NA>02-858-6585<NA><NA>서울특별시 구로구 구로동 507-6서울특별시 구로구 구로동로42길 56, 3층 (구로동)08280용인대 예도 태권도2023-03-02 13:03:41I2022-12-03 00:04:00.0태권도189694.937489443991.086756<NA><NA><NA><NA><NA><NA><NA><NA><NA>
63160000CDFH33010220000000022000-03-07<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>152-802서울특별시 구로구 개봉동 38-10서울특별시 구로구 고척로21나길 42 (개봉동)08251행복한 백호 태권도2024-01-13 13:21:47U2023-11-30 23:05:00.0태권도186079.519104444482.948611<NA><NA><NA><NA><NA><NA><NA><NA><NA>
73070000CDFH33010220230000022023-03-03<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 성북구 동소문동2가 227 애산빌딩서울특별시 성북구 동소문로 18-1, 애산빌딩 B1층 (동소문동2가)02860민앤마이노(한성대점)2023-03-03 09:52:08I2022-12-03 00:05:00.0유도200662.617378454094.531353<NA><NA><NA><NA><NA><NA><NA><NA><NA>
83140000CDFH33010220200000132020-07-20<NA>3폐업3폐업2021-07-10<NA><NA><NA>02-2653-8882<NA><NA>서울특별시 양천구 목동 725-3서울특별시 양천구 목동중앙남로9길 38, 3층 (목동)07958공도관 제8관2023-03-03 13:00:44U2022-12-03 00:05:00.0합기도187950.024484448432.130157<NA><NA><NA><NA><NA><NA><NA><NA><NA>
93140000CDFH33010220200000092020-06-03<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 174-1서울특별시 양천구 목동남로4길 38, 예인빌딩 4층 403호 (신정동)08104숭무관2023-03-03 17:58:51U2022-12-03 00:05:00.0합기도188131.296204445197.198551<NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
51083200000CDFH330102201500000420150520<NA>1영업/정상13영업중<NA><NA><NA><NA>02-876-1282<NA>151849서울특별시 관악구 봉천동 1680-29서울특별시 관악구 남부순환로 1901 (봉천동)08742더블B복싱클럽2022-07-05 08:49:32U2021-12-07 00:07:00.0권투196462.120645441809.435132<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51093060000CDFH330102199900000519990708<NA>4취소/말소/만료/정지/중지35직권말소20220627<NA><NA><NA>2209-1365<NA>131820서울특별시 중랑구 면목동 177-38 2층서울특별시 중랑구 겸재로3길 30 (면목동,2층)<NA>행복한 동행 한국체대 점프태권도2022-06-30 11:34:22U2021-12-07 00:02:00.0태권도206707.400663453893.266555<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51103060000CDFH330102199700000819970327<NA>4취소/말소/만료/정지/중지35직권말소20220627<NA><NA><NA>493-7497<NA>131814서울특별시 중랑구 면목동 413-3 2층서울특별시 중랑구 면목로 362 (면목동)02205경일체육관2022-06-30 11:21:36U2021-12-07 00:02:00.0태권도207757.111159453557.753876<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51113060000CDFH330102199500000119950126<NA>4취소/말소/만료/정지/중지35직권말소20220627<NA><NA><NA><NA><NA>131831서울특별시 중랑구 면목동 605-6서울특별시 중랑구 사가정로 365 (면목동)02228대성체육관2022-06-30 11:01:30U2021-12-07 00:02:00.0태권도207469.526789453213.812538<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51123060000CDFH330102199000000219900212<NA>4취소/말소/만료/정지/중지35직권말소20220627<NA><NA><NA>02-433-6601<NA>131809서울특별시 중랑구 망우동서울특별시 중랑구 봉우재로 203-1 (망우동)02171청도태권도2022-06-30 13:02:28U2021-12-07 00:02:00.0태권도208346.878674454725.307336<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51133020000CDFH330102202200000120220706<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 서계동 266-73 힐타워 8층서울특별시 용산구 만리재로 134, 힐타워 8층 (서계동)04305WS복싱클럽2022-07-06 09:14:07I2021-12-07 00:08:00.0권투196621.810303449898.051124<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51143210000CDFH330102201700000320170704<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 방배로 244 (방배동, 지하1층)06584킹스복싱짐2022-07-07 09:36:49U2021-12-07 00:09:00.0권투198998.136903443628.4328<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51153210000CDFH330102201500001220151012<NA>1영업/정상13영업중<NA><NA><NA><NA>02-573-4100<NA><NA>서울특별시 서초구 우면동 721-1 우면프라자1서울특별시 서초구 태봉로 70, 지층 제비101,102호 (우면동, 우면프라자Ι)06764케이탑2022-07-07 09:36:07U2021-12-07 00:09:00.0권투202190.137341440262.270869<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51163210000CDFH330102201500001020150915<NA>1영업/정상13영업중<NA><NA><NA><NA>02-576-5200<NA><NA>서울특별시 서초구 우면동 757 서초타워서울특별시 서초구 중앙로 582, A동 2층 202호 (우면동, 서초타워)06767용인대STA태권도장2022-07-07 09:35:32U2021-12-07 00:09:00.0태권도201286.184985439441.292545<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51173230000CDFH330102202200000520220621<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 송파구 거여동 605-4 1003~1006호서울특별시 송파구 위례송파로 77, 1003~1006호 (거여동)05790선비태권도장2022-07-08 10:05:16U2021-12-06 23:00:00.0태권도<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>