Overview

Dataset statistics

Number of variables56
Number of observations3277
Missing cells82410
Missing cells (%)44.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory484.0 B

Variable types

Numeric9
Text8
DateTime4
Categorical16
Unsupported19

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,문화사업자구분명,총층수,주변환경명,제작취급품목내용,시설면적,지상층수,지하층수,건물용도명,통로너비,조명시설조도,노래방실수,청소년실수,비상계단여부,비상구여부,자동환기여부,청소년실여부,특수조명여부,방음시설여부,비디오재생기명,조명시설유무,음향시설여부,편의시설여부,소방시설여부,총게임기수,기존게임업외업종명,제공게임물명,공연장형태구분명,품목명,최초등록시점,지역구분명
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16014/S/1/datasetView.do

Alerts

상세영업상태명 is highly imbalanced (68.2%)Imbalance
휴업시작일자 is highly imbalanced (99.5%)Imbalance
휴업종료일자 is highly imbalanced (99.5%)Imbalance
데이터갱신구분 is highly imbalanced (55.9%)Imbalance
주변환경명 is highly imbalanced (89.0%)Imbalance
건물용도명 is highly imbalanced (88.2%)Imbalance
지역구분명 is highly imbalanced (86.8%)Imbalance
인허가취소일자 has 3269 (99.8%) missing valuesMissing
폐업일자 has 2469 (75.3%) missing valuesMissing
재개업일자 has 3277 (100.0%) missing valuesMissing
전화번호 has 1910 (58.3%) missing valuesMissing
소재지면적 has 3277 (100.0%) missing valuesMissing
소재지우편번호 has 2515 (76.7%) missing valuesMissing
도로명주소 has 90 (2.7%) missing valuesMissing
도로명우편번호 has 1228 (37.5%) missing valuesMissing
업태구분명 has 3277 (100.0%) missing valuesMissing
좌표정보(X) has 84 (2.6%) missing valuesMissing
좌표정보(Y) has 84 (2.6%) missing valuesMissing
총층수 has 2281 (69.6%) missing valuesMissing
제작취급품목내용 has 641 (19.6%) missing valuesMissing
시설면적 has 1033 (31.5%) missing valuesMissing
지상층수 has 2182 (66.6%) missing valuesMissing
지하층수 has 2359 (72.0%) missing valuesMissing
비상계단여부 has 3277 (100.0%) missing valuesMissing
비상구여부 has 3277 (100.0%) missing valuesMissing
자동환기여부 has 3277 (100.0%) missing valuesMissing
청소년실여부 has 3277 (100.0%) missing valuesMissing
특수조명여부 has 3277 (100.0%) missing valuesMissing
방음시설여부 has 3277 (100.0%) missing valuesMissing
비디오재생기명 has 3277 (100.0%) missing valuesMissing
조명시설유무 has 3277 (100.0%) missing valuesMissing
음향시설여부 has 3277 (100.0%) missing valuesMissing
편의시설여부 has 3277 (100.0%) missing valuesMissing
소방시설여부 has 3277 (100.0%) missing valuesMissing
기존게임업외업종명 has 3277 (100.0%) missing valuesMissing
제공게임물명 has 3277 (100.0%) missing valuesMissing
공연장형태구분명 has 3277 (100.0%) missing valuesMissing
품목명 has 3277 (100.0%) missing valuesMissing
최초등록시점 has 3277 (100.0%) missing valuesMissing
시설면적 is highly skewed (γ1 = 32.53924839)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
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비상계단여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비상구여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
자동환기여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
청소년실여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
특수조명여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방음시설여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비디오재생기명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조명시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
음향시설여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
편의시설여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소방시설여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기존게임업외업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제공게임물명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공연장형태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
품목명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
최초등록시점 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 681 (20.8%) zerosZeros
시설면적 has 361 (11.0%) zerosZeros
지상층수 has 666 (20.3%) zerosZeros
지하층수 has 689 (21.0%) zerosZeros

Reproduction

Analysis started2024-05-11 07:47:24.987926
Analysis finished2024-05-11 07:47:29.686242
Duration4.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3158321.6
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2024-05-11T07:47:30.649515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13130000
median3180000
Q33220000
95-th percentile3220000
Maximum3240000
Range240000
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation72350.155
Coefficient of variation (CV)0.022907786
Kurtosis-0.18047434
Mean3158321.6
Median Absolute Deviation (MAD)40000
Skewness-1.08362
Sum1.034982 × 1010
Variance5.2345449 × 109
MonotonicityNot monotonic
2024-05-11T07:47:31.262749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 869
26.5%
3180000 456
13.9%
3210000 308
 
9.4%
3160000 268
 
8.2%
3010000 257
 
7.8%
3170000 208
 
6.3%
3130000 171
 
5.2%
3020000 149
 
4.5%
3230000 102
 
3.1%
3150000 77
 
2.3%
Other values (15) 412
12.6%
ValueCountFrequency (%)
3000000 42
 
1.3%
3010000 257
7.8%
3020000 149
4.5%
3030000 52
 
1.6%
3040000 38
 
1.2%
3050000 23
 
0.7%
3060000 16
 
0.5%
3070000 10
 
0.3%
3080000 24
 
0.7%
3090000 11
 
0.3%
ValueCountFrequency (%)
3240000 30
 
0.9%
3230000 102
 
3.1%
3220000 869
26.5%
3210000 308
 
9.4%
3200000 34
 
1.0%
3190000 15
 
0.5%
3180000 456
13.9%
3170000 208
 
6.3%
3160000 268
 
8.2%
3150000 77
 
2.3%
Distinct1047
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
2024-05-11T07:47:32.015486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters65540
Distinct characters13
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

Unique458 ?
Unique (%)14.0%

Sample

1st rowCDFF2241122017000016
2nd rowCDFF2241122019000032
3rd rowCDFF2241122023000002
4th rowCDFF2241122020000013
5th rowCDFF2241122017000012
ValueCountFrequency (%)
cdff2241122007000001 21
 
0.6%
cdff2241122018000001 20
 
0.6%
cdff2241122021000001 19
 
0.6%
cdff2241122006000001 19
 
0.6%
cdff2241122009000002 18
 
0.5%
cdff2241122011000002 18
 
0.5%
cdff2241122023000001 17
 
0.5%
cdff2241122022000001 17
 
0.5%
cdff2241122009000001 17
 
0.5%
cdff2241122010000001 17
 
0.5%
Other values (1037) 3094
94.4%
2024-05-11T07:47:33.275778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19812
30.2%
2 14744
22.5%
1 9955
15.2%
F 6554
 
10.0%
4 3999
 
6.1%
C 3277
 
5.0%
D 3277
 
5.0%
3 924
 
1.4%
9 777
 
1.2%
5 613
 
0.9%
Other values (3) 1608
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52432
80.0%
Uppercase Letter 13108
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19812
37.8%
2 14744
28.1%
1 9955
19.0%
4 3999
 
7.6%
3 924
 
1.8%
9 777
 
1.5%
5 613
 
1.2%
6 565
 
1.1%
7 532
 
1.0%
8 511
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
F 6554
50.0%
C 3277
25.0%
D 3277
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52432
80.0%
Latin 13108
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19812
37.8%
2 14744
28.1%
1 9955
19.0%
4 3999
 
7.6%
3 924
 
1.8%
9 777
 
1.5%
5 613
 
1.2%
6 565
 
1.1%
7 532
 
1.0%
8 511
 
1.0%
Latin
ValueCountFrequency (%)
F 6554
50.0%
C 3277
25.0%
D 3277
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65540
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19812
30.2%
2 14744
22.5%
1 9955
15.2%
F 6554
 
10.0%
4 3999
 
6.1%
C 3277
 
5.0%
D 3277
 
5.0%
3 924
 
1.4%
9 777
 
1.2%
5 613
 
0.9%
Other values (3) 1608
 
2.5%
Distinct2369
Distinct (%)72.3%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
Minimum1999-01-04 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T07:47:33.945936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:47:34.865950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)100.0%
Missing3269
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean20120530
Minimum20070625
Maximum20190311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2024-05-11T07:47:35.715554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070625
5-th percentile20070655
Q120078440
median20100672
Q320167612
95-th percentile20190245
Maximum20190311
Range119686
Interquartile range (IQR)89172.25

Descriptive statistics

Standard deviation51550.558
Coefficient of variation (CV)0.0025620875
Kurtosis-1.7571691
Mean20120530
Median Absolute Deviation (MAD)30004
Skewness0.57497027
Sum1.6096424 × 108
Variance2.65746 × 109
MonotonicityNot monotonic
2024-05-11T07:47:36.502274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20190311 1
 
< 0.1%
20160108 1
 
< 0.1%
20070625 1
 
< 0.1%
20100119 1
 
< 0.1%
20081016 1
 
< 0.1%
20070710 1
 
< 0.1%
20190123 1
 
< 0.1%
20101224 1
 
< 0.1%
(Missing) 3269
99.8%
ValueCountFrequency (%)
20070625 1
< 0.1%
20070710 1
< 0.1%
20081016 1
< 0.1%
20100119 1
< 0.1%
20101224 1
< 0.1%
20160108 1
< 0.1%
20190123 1
< 0.1%
20190311 1
< 0.1%
ValueCountFrequency (%)
20190311 1
< 0.1%
20190123 1
< 0.1%
20160108 1
< 0.1%
20101224 1
< 0.1%
20100119 1
< 0.1%
20081016 1
< 0.1%
20070710 1
< 0.1%
20070625 1
< 0.1%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
1
2455 
3
670 
5
 
86
4
 
66

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row1
4th row1
5th row5

Common Values

ValueCountFrequency (%)
1 2455
74.9%
3 670
 
20.4%
5 86
 
2.6%
4 66
 
2.0%

Length

2024-05-11T07:47:37.234264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:47:37.671411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2455
74.9%
3 670
 
20.4%
5 86
 
2.6%
4 66
 
2.0%

영업상태명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
영업/정상
2455 
폐업
670 
제외/삭제/전출
 
86
취소/말소/만료/정지/중지
 
66

Length

Max length14
Median length5
Mean length4.646628
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 2455
74.9%
폐업 670
 
20.4%
제외/삭제/전출 86
 
2.6%
취소/말소/만료/정지/중지 66
 
2.0%

Length

2024-05-11T07:47:38.291185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:47:38.834526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 2455
74.9%
폐업 670
 
20.4%
제외/삭제/전출 86
 
2.6%
취소/말소/만료/정지/중지 66
 
2.0%

상세영업상태코드
Real number (ℝ)

Distinct10
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.435764
Minimum3
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2024-05-11T07:47:39.276140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q113
median13
Q313
95-th percentile13
Maximum35
Range32
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.2222208
Coefficient of variation (CV)0.4566569
Kurtosis6.0194264
Mean11.435764
Median Absolute Deviation (MAD)0
Skewness0.87832034
Sum37475
Variance27.27159
MonotonicityNot monotonic
2024-05-11T07:47:39.996967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
13 2454
74.9%
3 670
 
20.4%
15 86
 
2.6%
35 55
 
1.7%
31 4
 
0.1%
32 2
 
0.1%
25 2
 
0.1%
33 2
 
0.1%
14 1
 
< 0.1%
30 1
 
< 0.1%
ValueCountFrequency (%)
3 670
 
20.4%
13 2454
74.9%
14 1
 
< 0.1%
15 86
 
2.6%
25 2
 
0.1%
30 1
 
< 0.1%
31 4
 
0.1%
32 2
 
0.1%
33 2
 
0.1%
35 55
 
1.7%
ValueCountFrequency (%)
35 55
 
1.7%
33 2
 
0.1%
32 2
 
0.1%
31 4
 
0.1%
30 1
 
< 0.1%
25 2
 
0.1%
15 86
 
2.6%
14 1
 
< 0.1%
13 2454
74.9%
3 670
 
20.4%

상세영업상태명
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
영업중
2454 
폐업
670 
전출
 
86
직권말소
 
55
등록취소
 
4
Other values (5)
 
8

Length

Max length4
Median length3
Mean length2.7891364
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 2454
74.9%
폐업 670
 
20.4%
전출 86
 
2.6%
직권말소 55
 
1.7%
등록취소 4
 
0.1%
신고취소 2
 
0.1%
영업정지 2
 
0.1%
지정취소 2
 
0.1%
전입 1
 
< 0.1%
허가취소 1
 
< 0.1%

Length

2024-05-11T07:47:40.668207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:47:41.312755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 2454
74.9%
폐업 670
 
20.4%
전출 86
 
2.6%
직권말소 55
 
1.7%
등록취소 4
 
0.1%
신고취소 2
 
0.1%
영업정지 2
 
0.1%
지정취소 2
 
0.1%
전입 1
 
< 0.1%
허가취소 1
 
< 0.1%

폐업일자
Date

MISSING 

Distinct683
Distinct (%)84.5%
Missing2469
Missing (%)75.3%
Memory size25.7 KiB
Minimum2005-07-06 00:00:00
Maximum2024-05-01 00:00:00
2024-05-11T07:47:41.749753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:47:42.252529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
3275 
20140201
 
1
20120225
 
1

Length

Max length8
Median length4
Mean length4.0024413
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> 3275
99.9%
20140201 1
 
< 0.1%
20120225 1
 
< 0.1%

Length

2024-05-11T07:47:42.723981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:47:43.084165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3275
99.9%
20140201 1
 
< 0.1%
20120225 1
 
< 0.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
3275 
20140302
 
1
20120325
 
1

Length

Max length8
Median length4
Mean length4.0024413
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> 3275
99.9%
20140302 1
 
< 0.1%
20120325 1
 
< 0.1%

Length

2024-05-11T07:47:43.504544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:47:44.041003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3275
99.9%
20140302 1
 
< 0.1%
20120325 1
 
< 0.1%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

전화번호
Text

MISSING 

Distinct1292
Distinct (%)94.5%
Missing1910
Missing (%)58.3%
Memory size25.7 KiB
2024-05-11T07:47:44.610133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length10.405267
Min length2

Characters and Unicode

Total characters14224
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1225 ?
Unique (%)89.6%

Sample

1st row02-869-1222
2nd row02-869-1222
3rd row02-869-1222
4th row02-869-1222
5th row02-567-5970
ValueCountFrequency (%)
2269-4206 4
 
0.3%
02-869-1222 4
 
0.3%
569-2227 3
 
0.2%
2237-3800 3
 
0.2%
585-2452 3
 
0.2%
2278-8913 3
 
0.2%
02-2141-1301 2
 
0.1%
2272-1244 2
 
0.1%
02-577-6779 2
 
0.1%
02-2155-5100 2
 
0.1%
Other values (1282) 1339
98.0%
2024-05-11T07:47:45.807843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2198
15.5%
- 2027
14.3%
2 1907
13.4%
7 1296
9.1%
5 1223
8.6%
6 1034
7.3%
3 1008
7.1%
1 992
7.0%
4 912
6.4%
8 910
6.4%
Other values (4) 717
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12188
85.7%
Dash Punctuation 2027
 
14.3%
Close Punctuation 7
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2198
18.0%
2 1907
15.6%
7 1296
10.6%
5 1223
10.0%
6 1034
8.5%
3 1008
8.3%
1 992
8.1%
4 912
7.5%
8 910
7.5%
9 708
 
5.8%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
= 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 2027
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14224
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2198
15.5%
- 2027
14.3%
2 1907
13.4%
7 1296
9.1%
5 1223
8.6%
6 1034
7.3%
3 1008
7.1%
1 992
7.0%
4 912
6.4%
8 910
6.4%
Other values (4) 717
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14224
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2198
15.5%
- 2027
14.3%
2 1907
13.4%
7 1296
9.1%
5 1223
8.6%
6 1034
7.3%
3 1008
7.1%
1 992
7.0%
4 912
6.4%
8 910
6.4%
Other values (4) 717
 
5.0%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

소재지우편번호
Text

MISSING 

Distinct363
Distinct (%)47.6%
Missing2515
Missing (%)76.7%
Memory size25.7 KiB
2024-05-11T07:47:46.726973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.003937
Min length6

Characters and Unicode

Total characters4575
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

Unique238 ?
Unique (%)31.2%

Sample

1st row150-723
2nd row100192
3rd row120-709
4th row140872
5th row140869
ValueCountFrequency (%)
100340 52
 
6.8%
150042 27
 
3.5%
150723 26
 
3.4%
152848 17
 
2.2%
140879 14
 
1.8%
140847 14
 
1.8%
100848 12
 
1.6%
135924 9
 
1.2%
135840 8
 
1.0%
158050 8
 
1.0%
Other values (353) 575
75.5%
2024-05-11T07:47:48.032587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 923
20.2%
0 673
14.7%
8 578
12.6%
3 566
12.4%
5 526
11.5%
4 382
8.3%
7 361
 
7.9%
2 236
 
5.2%
9 211
 
4.6%
6 116
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4572
99.9%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 923
20.2%
0 673
14.7%
8 578
12.6%
3 566
12.4%
5 526
11.5%
4 382
8.4%
7 361
 
7.9%
2 236
 
5.2%
9 211
 
4.6%
6 116
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4575
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 923
20.2%
0 673
14.7%
8 578
12.6%
3 566
12.4%
5 526
11.5%
4 382
8.3%
7 361
 
7.9%
2 236
 
5.2%
9 211
 
4.6%
6 116
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4575
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 923
20.2%
0 673
14.7%
8 578
12.6%
3 566
12.4%
5 526
11.5%
4 382
8.3%
7 361
 
7.9%
2 236
 
5.2%
9 211
 
4.6%
6 116
 
2.5%
Distinct2499
Distinct (%)76.3%
Missing2
Missing (%)0.1%
Memory size25.7 KiB
2024-05-11T07:47:48.676541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length43
Mean length30.04458
Min length14

Characters and Unicode

Total characters98396
Distinct characters517
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

Unique2150 ?
Unique (%)65.6%

Sample

1st row서울특별시 영등포구 문래동*가 ** 문래 SK V* center
2nd row서울특별시 강남구 대치동 ***-**
3rd row서울특별시 서초구 서초동 ****-* 국제전자센터 **,**호
4th row서울특별시 영등포구 영등포동*가 **
5th row서울특별시 구로구 구로동 **-* 다인빌딩 ***호
ValueCountFrequency (%)
서울특별시 3273
18.3%
번지 2456
 
13.7%
1064
 
6.0%
강남구 870
 
4.9%
858
 
4.8%
621
 
3.5%
영등포구 456
 
2.6%
역삼동 344
 
1.9%
당산동*가 327
 
1.8%
서초구 305
 
1.7%
Other values (1868) 7288
40.8%
2024-05-11T07:47:49.663626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 19490
19.8%
16696
17.0%
3962
 
4.0%
3817
 
3.9%
3517
 
3.6%
3338
 
3.4%
3293
 
3.3%
3276
 
3.3%
3274
 
3.3%
- 2950
 
3.0%
Other values (507) 34783
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58254
59.2%
Other Punctuation 19577
 
19.9%
Space Separator 16696
 
17.0%
Dash Punctuation 2950
 
3.0%
Uppercase Letter 673
 
0.7%
Lowercase Letter 83
 
0.1%
Decimal Number 61
 
0.1%
Close Punctuation 41
 
< 0.1%
Open Punctuation 41
 
< 0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3962
 
6.8%
3817
 
6.6%
3517
 
6.0%
3338
 
5.7%
3293
 
5.7%
3276
 
5.6%
3274
 
5.6%
2736
 
4.7%
2463
 
4.2%
1355
 
2.3%
Other values (440) 27223
46.7%
Uppercase Letter
ValueCountFrequency (%)
C 67
 
10.0%
B 63
 
9.4%
S 55
 
8.2%
A 51
 
7.6%
T 50
 
7.4%
I 49
 
7.3%
E 43
 
6.4%
K 43
 
6.4%
G 29
 
4.3%
D 26
 
3.9%
Other values (16) 197
29.3%
Lowercase Letter
ValueCountFrequency (%)
e 22
26.5%
r 11
13.3%
o 8
 
9.6%
w 7
 
8.4%
n 6
 
7.2%
c 6
 
7.2%
s 6
 
7.2%
t 5
 
6.0%
b 4
 
4.8%
u 2
 
2.4%
Other values (6) 6
 
7.2%
Decimal Number
ValueCountFrequency (%)
1 15
24.6%
7 9
14.8%
8 6
 
9.8%
0 6
 
9.8%
2 5
 
8.2%
3 5
 
8.2%
5 5
 
8.2%
9 5
 
8.2%
4 3
 
4.9%
6 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
* 19490
99.6%
, 68
 
0.3%
. 7
 
< 0.1%
& 6
 
< 0.1%
/ 3
 
< 0.1%
' 1
 
< 0.1%
@ 1
 
< 0.1%
? 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
5
55.6%
4
44.4%
Space Separator
ValueCountFrequency (%)
16696
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2950
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58248
59.2%
Common 39377
40.0%
Latin 765
 
0.8%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3962
 
6.8%
3817
 
6.6%
3517
 
6.0%
3338
 
5.7%
3293
 
5.7%
3276
 
5.6%
3274
 
5.6%
2736
 
4.7%
2463
 
4.2%
1355
 
2.3%
Other values (438) 27217
46.7%
Latin
ValueCountFrequency (%)
C 67
 
8.8%
B 63
 
8.2%
S 55
 
7.2%
A 51
 
6.7%
T 50
 
6.5%
I 49
 
6.4%
E 43
 
5.6%
K 43
 
5.6%
G 29
 
3.8%
D 26
 
3.4%
Other values (34) 289
37.8%
Common
ValueCountFrequency (%)
* 19490
49.5%
16696
42.4%
- 2950
 
7.5%
, 68
 
0.2%
) 41
 
0.1%
( 41
 
0.1%
1 15
 
< 0.1%
~ 11
 
< 0.1%
7 9
 
< 0.1%
. 7
 
< 0.1%
Other values (13) 49
 
0.1%
Han
ValueCountFrequency (%)
3
50.0%
3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58248
59.2%
ASCII 40133
40.8%
Number Forms 9
 
< 0.1%
CJK 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 19490
48.6%
16696
41.6%
- 2950
 
7.4%
, 68
 
0.2%
C 67
 
0.2%
B 63
 
0.2%
S 55
 
0.1%
A 51
 
0.1%
T 50
 
0.1%
I 49
 
0.1%
Other values (55) 594
 
1.5%
Hangul
ValueCountFrequency (%)
3962
 
6.8%
3817
 
6.6%
3517
 
6.0%
3338
 
5.7%
3293
 
5.7%
3276
 
5.6%
3274
 
5.6%
2736
 
4.7%
2463
 
4.2%
1355
 
2.3%
Other values (438) 27217
46.7%
Number Forms
ValueCountFrequency (%)
5
55.6%
4
44.4%
CJK
ValueCountFrequency (%)
3
50.0%
3
50.0%

도로명주소
Text

MISSING 

Distinct2761
Distinct (%)86.6%
Missing90
Missing (%)2.7%
Memory size25.7 KiB
2024-05-11T07:47:50.390561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length53
Mean length36.998431
Min length22

Characters and Unicode

Total characters117914
Distinct characters556
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2495 ?
Unique (%)78.3%

Sample

1st row서울특별시 영등포구 선유로*길 **, 문래 SK V* center ****호 (문래동*가)
2nd row서울특별시 강남구 테헤란로**길 **, **호 (대치동)
3rd row서울특별시 서초구 효령로 ***, 국제전자센터 *층 **,**호 (서초동)
4th row서울특별시 영등포구 영신로**길 *, *층 (영등포동*가)
5th row서울특별시 구로구 구로중앙로**길 ** (구로동)
ValueCountFrequency (%)
3287
 
15.6%
서울특별시 3185
 
15.1%
1444
 
6.9%
1240
 
5.9%
강남구 866
 
4.1%
영등포구 442
 
2.1%
서초구 297
 
1.4%
영등포로 295
 
1.4%
구로구 267
 
1.3%
역삼동 255
 
1.2%
Other values (2641) 9500
45.1%
2024-05-11T07:47:51.529000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 19632
 
16.6%
19066
 
16.2%
3979
 
3.4%
3908
 
3.3%
, 3860
 
3.3%
3819
 
3.2%
3733
 
3.2%
3266
 
2.8%
) 3223
 
2.7%
( 3223
 
2.7%
Other values (546) 50205
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67463
57.2%
Other Punctuation 23510
 
19.9%
Space Separator 19066
 
16.2%
Close Punctuation 3223
 
2.7%
Open Punctuation 3223
 
2.7%
Uppercase Letter 750
 
0.6%
Dash Punctuation 473
 
0.4%
Lowercase Letter 98
 
0.1%
Decimal Number 69
 
0.1%
Math Symbol 27
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3979
 
5.9%
3908
 
5.8%
3819
 
5.7%
3733
 
5.5%
3266
 
4.8%
3212
 
4.8%
3189
 
4.7%
3186
 
4.7%
1838
 
2.7%
1635
 
2.4%
Other values (477) 35698
52.9%
Uppercase Letter
ValueCountFrequency (%)
B 85
 
11.3%
C 68
 
9.1%
A 66
 
8.8%
S 60
 
8.0%
T 53
 
7.1%
I 51
 
6.8%
E 45
 
6.0%
K 42
 
5.6%
G 30
 
4.0%
R 26
 
3.5%
Other values (16) 224
29.9%
Lowercase Letter
ValueCountFrequency (%)
e 25
25.5%
r 12
12.2%
o 9
 
9.2%
w 8
 
8.2%
b 8
 
8.2%
s 6
 
6.1%
c 6
 
6.1%
n 6
 
6.1%
t 5
 
5.1%
i 2
 
2.0%
Other values (8) 11
11.2%
Decimal Number
ValueCountFrequency (%)
1 15
21.7%
2 10
14.5%
0 10
14.5%
6 8
11.6%
3 8
11.6%
4 5
 
7.2%
7 4
 
5.8%
9 3
 
4.3%
5 3
 
4.3%
8 3
 
4.3%
Other Punctuation
ValueCountFrequency (%)
* 19632
83.5%
, 3860
 
16.4%
. 6
 
< 0.1%
& 6
 
< 0.1%
/ 3
 
< 0.1%
' 1
 
< 0.1%
@ 1
 
< 0.1%
? 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
8
66.7%
4
33.3%
Space Separator
ValueCountFrequency (%)
19066
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3223
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3223
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 473
100.0%
Math Symbol
ValueCountFrequency (%)
~ 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67457
57.2%
Common 49591
42.1%
Latin 860
 
0.7%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3979
 
5.9%
3908
 
5.8%
3819
 
5.7%
3733
 
5.5%
3266
 
4.8%
3212
 
4.8%
3189
 
4.7%
3186
 
4.7%
1838
 
2.7%
1635
 
2.4%
Other values (475) 35692
52.9%
Latin
ValueCountFrequency (%)
B 85
 
9.9%
C 68
 
7.9%
A 66
 
7.7%
S 60
 
7.0%
T 53
 
6.2%
I 51
 
5.9%
E 45
 
5.2%
K 42
 
4.9%
G 30
 
3.5%
R 26
 
3.0%
Other values (36) 334
38.8%
Common
ValueCountFrequency (%)
* 19632
39.6%
19066
38.4%
, 3860
 
7.8%
) 3223
 
6.5%
( 3223
 
6.5%
- 473
 
1.0%
~ 27
 
0.1%
1 15
 
< 0.1%
2 10
 
< 0.1%
0 10
 
< 0.1%
Other values (13) 52
 
0.1%
Han
ValueCountFrequency (%)
3
50.0%
3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67456
57.2%
ASCII 50439
42.8%
Number Forms 12
 
< 0.1%
CJK 6
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 19632
38.9%
19066
37.8%
, 3860
 
7.7%
) 3223
 
6.4%
( 3223
 
6.4%
- 473
 
0.9%
B 85
 
0.2%
C 68
 
0.1%
A 66
 
0.1%
S 60
 
0.1%
Other values (57) 683
 
1.4%
Hangul
ValueCountFrequency (%)
3979
 
5.9%
3908
 
5.8%
3819
 
5.7%
3733
 
5.5%
3266
 
4.8%
3212
 
4.8%
3189
 
4.7%
3186
 
4.7%
1838
 
2.7%
1635
 
2.4%
Other values (474) 35691
52.9%
Number Forms
ValueCountFrequency (%)
8
66.7%
4
33.3%
CJK
ValueCountFrequency (%)
3
50.0%
3
50.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Text

MISSING 

Distinct808
Distinct (%)39.4%
Missing1228
Missing (%)37.5%
Memory size25.7 KiB
2024-05-11T07:47:52.325520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0375793
Min length5

Characters and Unicode

Total characters10322
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

Unique477 ?
Unique (%)23.3%

Sample

1st row07281
2nd row06178
3rd row06720
4th row07251
5th row08302
ValueCountFrequency (%)
07264 129
 
6.3%
04545 50
 
2.4%
08390 40
 
2.0%
08381 32
 
1.6%
08378 25
 
1.2%
08389 22
 
1.1%
08506 21
 
1.0%
08377 20
 
1.0%
08504 19
 
0.9%
06159 18
 
0.9%
Other values (798) 1673
81.6%
2024-05-11T07:47:53.684071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2636
25.5%
6 1263
12.2%
8 882
 
8.5%
3 878
 
8.5%
7 858
 
8.3%
5 827
 
8.0%
1 827
 
8.0%
2 820
 
7.9%
4 814
 
7.9%
9 514
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10319
> 99.9%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2636
25.5%
6 1263
12.2%
8 882
 
8.5%
3 878
 
8.5%
7 858
 
8.3%
5 827
 
8.0%
1 827
 
8.0%
2 820
 
7.9%
4 814
 
7.9%
9 514
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10322
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2636
25.5%
6 1263
12.2%
8 882
 
8.5%
3 878
 
8.5%
7 858
 
8.3%
5 827
 
8.0%
1 827
 
8.0%
2 820
 
7.9%
4 814
 
7.9%
9 514
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10322
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2636
25.5%
6 1263
12.2%
8 882
 
8.5%
3 878
 
8.5%
7 858
 
8.3%
5 827
 
8.0%
1 827
 
8.0%
2 820
 
7.9%
4 814
 
7.9%
9 514
 
5.0%
Distinct3102
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
2024-05-11T07:47:54.488371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length29
Mean length8.1818737
Min length1

Characters and Unicode

Total characters26812
Distinct characters699
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

Unique2944 ?
Unique (%)89.8%

Sample

1st row매머드PC
2nd row주식회사 폭스게임즈
3rd row겜우리한우리
4th row우성전자
5th row(주)에스디소프트
ValueCountFrequency (%)
주식회사 546
 
13.2%
소프트 39
 
0.9%
29
 
0.7%
유한회사 25
 
0.6%
soft 13
 
0.3%
엔터테인먼트 11
 
0.3%
스튜디오 8
 
0.2%
전자 8
 
0.2%
co 8
 
0.2%
ltd 7
 
0.2%
Other values (3205) 3453
83.3%
2024-05-11T07:47:56.170006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2144
 
8.0%
) 1680
 
6.3%
( 1677
 
6.3%
899
 
3.4%
871
 
3.2%
863
 
3.2%
815
 
3.0%
644
 
2.4%
602
 
2.2%
559
 
2.1%
Other values (689) 16058
59.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21253
79.3%
Close Punctuation 1680
 
6.3%
Open Punctuation 1677
 
6.3%
Space Separator 871
 
3.2%
Uppercase Letter 626
 
2.3%
Lowercase Letter 519
 
1.9%
Other Punctuation 82
 
0.3%
Decimal Number 82
 
0.3%
Dash Punctuation 11
 
< 0.1%
Other Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2144
 
10.1%
899
 
4.2%
863
 
4.1%
815
 
3.8%
644
 
3.0%
602
 
2.8%
559
 
2.6%
520
 
2.4%
453
 
2.1%
413
 
1.9%
Other values (619) 13341
62.8%
Uppercase Letter
ValueCountFrequency (%)
S 64
 
10.2%
E 48
 
7.7%
T 45
 
7.2%
M 45
 
7.2%
G 36
 
5.8%
N 33
 
5.3%
O 29
 
4.6%
J 29
 
4.6%
A 29
 
4.6%
K 28
 
4.5%
Other values (16) 240
38.3%
Lowercase Letter
ValueCountFrequency (%)
e 56
10.8%
o 55
10.6%
n 53
10.2%
t 46
 
8.9%
i 41
 
7.9%
a 39
 
7.5%
s 32
 
6.2%
r 29
 
5.6%
m 22
 
4.2%
d 19
 
3.7%
Other values (14) 127
24.5%
Decimal Number
ValueCountFrequency (%)
2 17
20.7%
0 13
15.9%
1 13
15.9%
3 12
14.6%
7 8
9.8%
4 7
8.5%
8 4
 
4.9%
9 3
 
3.7%
5 3
 
3.7%
6 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 56
68.3%
& 16
 
19.5%
, 6
 
7.3%
? 4
 
4.9%
Close Punctuation
ValueCountFrequency (%)
) 1680
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1677
100.0%
Space Separator
ValueCountFrequency (%)
871
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Symbol
ValueCountFrequency (%)
10
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21259
79.3%
Common 4404
 
16.4%
Latin 1145
 
4.3%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2144
 
10.1%
899
 
4.2%
863
 
4.1%
815
 
3.8%
644
 
3.0%
602
 
2.8%
559
 
2.6%
520
 
2.4%
453
 
2.1%
413
 
1.9%
Other values (616) 13347
62.8%
Latin
ValueCountFrequency (%)
S 64
 
5.6%
e 56
 
4.9%
o 55
 
4.8%
n 53
 
4.6%
E 48
 
4.2%
t 46
 
4.0%
T 45
 
3.9%
M 45
 
3.9%
i 41
 
3.6%
a 39
 
3.4%
Other values (40) 653
57.0%
Common
ValueCountFrequency (%)
) 1680
38.1%
( 1677
38.1%
871
19.8%
. 56
 
1.3%
2 17
 
0.4%
& 16
 
0.4%
0 13
 
0.3%
1 13
 
0.3%
3 12
 
0.3%
- 11
 
0.2%
Other values (9) 38
 
0.9%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21249
79.3%
ASCII 5549
 
20.7%
None 10
 
< 0.1%
CJK 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2144
 
10.1%
899
 
4.2%
863
 
4.1%
815
 
3.8%
644
 
3.0%
602
 
2.8%
559
 
2.6%
520
 
2.4%
453
 
2.1%
413
 
1.9%
Other values (615) 13337
62.8%
ASCII
ValueCountFrequency (%)
) 1680
30.3%
( 1677
30.2%
871
15.7%
S 64
 
1.2%
. 56
 
1.0%
e 56
 
1.0%
o 55
 
1.0%
n 53
 
1.0%
E 48
 
0.9%
t 46
 
0.8%
Other values (59) 943
17.0%
None
ValueCountFrequency (%)
10
100.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct3276
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
Minimum2006-02-15 10:17:22
Maximum2024-05-09 09:42:44
2024-05-11T07:47:56.771536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:47:57.479177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
I
2663 
U
613 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 2663
81.3%
U 613
 
18.7%
D 1
 
< 0.1%

Length

2024-05-11T07:47:58.075037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:47:58.434556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2663
81.3%
u 613
 
18.7%
d 1
 
< 0.1%
Distinct728
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T07:47:58.885470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:47:59.523431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1933
Distinct (%)60.5%
Missing84
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean197867.69
Minimum180320.14
Maximum215235.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2024-05-11T07:47:59.975402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum180320.14
5-th percentile189155.73
Q1190648.45
median199526.42
Q3203271.27
95-th percentile206865.84
Maximum215235.91
Range34915.766
Interquartile range (IQR)12622.826

Descriptive statistics

Standard deviation6562.8834
Coefficient of variation (CV)0.033168039
Kurtosis-1.2458004
Mean197867.69
Median Absolute Deviation (MAD)5220.9854
Skewness-0.082331864
Sum6.3179154 × 108
Variance43071438
MonotonicityNot monotonic
2024-05-11T07:48:00.892657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190555.768991595 279
 
8.5%
199526.416139264 82
 
2.5%
199521.200809167 51
 
1.6%
189538.020935968 18
 
0.5%
189055.138252216 16
 
0.5%
190779.824680954 15
 
0.5%
190776.468544178 14
 
0.4%
199534.329650967 13
 
0.4%
191020.264430044 12
 
0.4%
190680.536850936 11
 
0.3%
Other values (1923) 2682
81.8%
(Missing) 84
 
2.6%
ValueCountFrequency (%)
180320.144698501 1
< 0.1%
182863.20722894 1
< 0.1%
183173.615351883 1
< 0.1%
183353.924328891 1
< 0.1%
183366.236140415 1
< 0.1%
183372.025068083 1
< 0.1%
183382.861571856 1
< 0.1%
183748.774951501 1
< 0.1%
183837.0 1
< 0.1%
184290.893400642 1
< 0.1%
ValueCountFrequency (%)
215235.910911 1
< 0.1%
215144.766442481 1
< 0.1%
212713.090111199 1
< 0.1%
212684.984662576 1
< 0.1%
212325.39591829 1
< 0.1%
212214.00965854 2
0.1%
212172.828537488 1
< 0.1%
211966.759282034 1
< 0.1%
211910.466972617 1
< 0.1%
211887.278139278 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1933
Distinct (%)60.5%
Missing84
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean446370.97
Minimum432911.45
Maximum464346.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2024-05-11T07:48:01.583462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum432911.45
5-th percentile441740.83
Q1443612.99
median445778.9
Q3448143.69
95-th percentile452599.63
Maximum464346.66
Range31435.212
Interquartile range (IQR)4530.7015

Descriptive statistics

Standard deviation3869.3121
Coefficient of variation (CV)0.0086683776
Kurtosis2.1230817
Mean446370.97
Median Absolute Deviation (MAD)2269.9629
Skewness1.1640077
Sum1.4252625 × 109
Variance14971576
MonotonicityNot monotonic
2024-05-11T07:48:02.217552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446698.814322782 279
 
8.5%
451693.211256949 82
 
2.5%
451751.424132583 51
 
1.6%
441982.427934953 18
 
0.5%
441958.334400683 16
 
0.5%
442527.527966789 15
 
0.5%
442370.143700207 14
 
0.4%
451608.222852119 13
 
0.4%
442460.919021593 12
 
0.4%
442392.645303533 11
 
0.3%
Other values (1923) 2682
81.8%
(Missing) 84
 
2.6%
ValueCountFrequency (%)
432911.451582184 1
 
< 0.1%
437899.830896583 1
 
< 0.1%
437914.06299827 4
0.1%
438720.679251839 1
 
< 0.1%
439205.430021381 1
 
< 0.1%
439228.931995825 1
 
< 0.1%
439255.089654051 2
0.1%
439347.273411859 1
 
< 0.1%
439569.401459017 1
 
< 0.1%
439946.302906409 1
 
< 0.1%
ValueCountFrequency (%)
464346.663669239 1
 
< 0.1%
464199.048415229 3
0.1%
464018.019728157 1
 
< 0.1%
463669.715490233 1
 
< 0.1%
462947.66303412 1
 
< 0.1%
462945.647429763 1
 
< 0.1%
462615.548659725 1
 
< 0.1%
462148.356096392 3
0.1%
462123.792297709 1
 
< 0.1%
462118.417920115 2
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
게임물배급업
2804 
<NA>
473 

Length

Max length6
Median length6
Mean length5.7113213
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 (%)
게임물배급업 2804
85.6%
<NA> 473
 
14.4%

Length

2024-05-11T07:48:02.839243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:03.308208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
게임물배급업 2804
85.6%
na 473
 
14.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
유통관련업
2804 
<NA>
473 

Length

Max length5
Median length5
Mean length4.8556607
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 (%)
유통관련업 2804
85.6%
<NA> 473
 
14.4%

Length

2024-05-11T07:48:03.752182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:04.083910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통관련업 2804
85.6%
na 473
 
14.4%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct34
Distinct (%)3.4%
Missing2281
Missing (%)69.6%
Infinite0
Infinite (%)0.0%
Mean3.7971888
Minimum0
Maximum43
Zeros681
Zeros (%)20.8%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2024-05-11T07:48:04.593725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile18
Maximum43
Range43
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.8919173
Coefficient of variation (CV)1.8150052
Kurtosis3.9977967
Mean3.7971888
Median Absolute Deviation (MAD)0
Skewness2.0061138
Sum3782
Variance47.498525
MonotonicityNot monotonic
2024-05-11T07:48:05.022242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 681
 
20.8%
15 31
 
0.9%
5 30
 
0.9%
14 27
 
0.8%
10 24
 
0.7%
4 23
 
0.7%
6 19
 
0.6%
7 18
 
0.5%
18 17
 
0.5%
8 15
 
0.5%
Other values (24) 111
 
3.4%
(Missing) 2281
69.6%
ValueCountFrequency (%)
0 681
20.8%
1 3
 
0.1%
2 7
 
0.2%
3 7
 
0.2%
4 23
 
0.7%
5 30
 
0.9%
6 19
 
0.6%
7 18
 
0.5%
8 15
 
0.5%
9 14
 
0.4%
ValueCountFrequency (%)
43 1
 
< 0.1%
39 1
 
< 0.1%
37 1
 
< 0.1%
36 1
 
< 0.1%
35 1
 
< 0.1%
30 2
0.1%
28 1
 
< 0.1%
27 1
 
< 0.1%
26 4
0.1%
25 4
0.1%

주변환경명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
3152 
기타
 
91
주택가주변
 
16
아파트지역
 
10
유흥업소밀집지역
 
5

Length

Max length8
Median length4
Mean length3.9621605
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 (%)
<NA> 3152
96.2%
기타 91
 
2.8%
주택가주변 16
 
0.5%
아파트지역 10
 
0.3%
유흥업소밀집지역 5
 
0.2%
학교정화(상대) 3
 
0.1%

Length

2024-05-11T07:48:05.488251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:05.966441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3152
96.2%
기타 91
 
2.8%
주택가주변 16
 
0.5%
아파트지역 10
 
0.3%
유흥업소밀집지역 5
 
0.2%
학교정화(상대 3
 
0.1%
Distinct619
Distinct (%)23.5%
Missing641
Missing (%)19.6%
Memory size25.7 KiB
2024-05-11T07:48:06.561747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length37
Mean length5.9040212
Min length2

Characters and Unicode

Total characters15563
Distinct characters284
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique517 ?
Unique (%)19.6%

Sample

1st row경품게임기및오락기
2nd row소프트웨어 공급
3rd row게임물
4th row게임물
5th row게임물
ValueCountFrequency (%)
게임물 1052
30.5%
모바일게임 247
 
7.2%
게임 206
 
6.0%
온라인게임 176
 
5.1%
온라인 115
 
3.3%
모바일 111
 
3.2%
소프트웨어 96
 
2.8%
게임기 92
 
2.7%
79
 
2.3%
아케이드 65
 
1.9%
Other values (497) 1214
35.2%
2024-05-11T07:48:07.815498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2575
16.5%
2572
16.5%
1238
 
8.0%
818
 
5.3%
503
 
3.2%
503
 
3.2%
499
 
3.2%
494
 
3.2%
475
 
3.1%
468
 
3.0%
Other values (274) 5418
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13708
88.1%
Space Separator 818
 
5.3%
Other Punctuation 442
 
2.8%
Uppercase Letter 342
 
2.2%
Lowercase Letter 85
 
0.5%
Open Punctuation 76
 
0.5%
Close Punctuation 76
 
0.5%
Decimal Number 15
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2575
18.8%
2572
18.8%
1238
 
9.0%
503
 
3.7%
503
 
3.7%
499
 
3.6%
494
 
3.6%
475
 
3.5%
468
 
3.4%
276
 
2.0%
Other values (222) 4105
29.9%
Uppercase Letter
ValueCountFrequency (%)
P 83
24.3%
C 75
21.9%
R 51
14.9%
V 31
 
9.1%
M 23
 
6.7%
G 14
 
4.1%
D 12
 
3.5%
O 12
 
3.5%
A 11
 
3.2%
S 7
 
2.0%
Other values (10) 23
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
o 13
15.3%
p 11
12.9%
m 10
11.8%
r 9
10.6%
g 6
7.1%
a 6
7.1%
s 6
7.1%
c 5
 
5.9%
e 4
 
4.7%
i 3
 
3.5%
Other values (6) 12
14.1%
Other Punctuation
ValueCountFrequency (%)
, 409
92.5%
/ 22
 
5.0%
? 4
 
0.9%
. 3
 
0.7%
: 2
 
0.5%
& 1
 
0.2%
1
 
0.2%
Decimal Number
ValueCountFrequency (%)
3 7
46.7%
2 3
20.0%
4 2
 
13.3%
8 2
 
13.3%
1 1
 
6.7%
Space Separator
ValueCountFrequency (%)
818
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13708
88.1%
Common 1428
 
9.2%
Latin 427
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2575
18.8%
2572
18.8%
1238
 
9.0%
503
 
3.7%
503
 
3.7%
499
 
3.6%
494
 
3.6%
475
 
3.5%
468
 
3.4%
276
 
2.0%
Other values (222) 4105
29.9%
Latin
ValueCountFrequency (%)
P 83
19.4%
C 75
17.6%
R 51
11.9%
V 31
 
7.3%
M 23
 
5.4%
G 14
 
3.3%
o 13
 
3.0%
D 12
 
2.8%
O 12
 
2.8%
A 11
 
2.6%
Other values (26) 102
23.9%
Common
ValueCountFrequency (%)
818
57.3%
, 409
28.6%
( 76
 
5.3%
) 76
 
5.3%
/ 22
 
1.5%
3 7
 
0.5%
? 4
 
0.3%
2 3
 
0.2%
. 3
 
0.2%
: 2
 
0.1%
Other values (6) 8
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13708
88.1%
ASCII 1854
 
11.9%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2575
18.8%
2572
18.8%
1238
 
9.0%
503
 
3.7%
503
 
3.7%
499
 
3.6%
494
 
3.6%
475
 
3.5%
468
 
3.4%
276
 
2.0%
Other values (222) 4105
29.9%
ASCII
ValueCountFrequency (%)
818
44.1%
, 409
22.1%
P 83
 
4.5%
( 76
 
4.1%
) 76
 
4.1%
C 75
 
4.0%
R 51
 
2.8%
V 31
 
1.7%
M 23
 
1.2%
/ 22
 
1.2%
Other values (41) 190
 
10.2%
None
ValueCountFrequency (%)
1
100.0%

시설면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1096
Distinct (%)48.8%
Missing1033
Missing (%)31.5%
Infinite0
Infinite (%)0.0%
Mean1073.4218
Minimum0
Maximum883014
Zeros361
Zeros (%)11.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2024-05-11T07:48:08.571039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.3
median33.3
Q3128.095
95-th percentile613.1065
Maximum883014
Range883014
Interquartile range (IQR)124.795

Descriptive statistics

Standard deviation23056.558
Coefficient of variation (CV)21.479494
Kurtosis1138.5657
Mean1073.4218
Median Absolute Deviation (MAD)33.3
Skewness32.539248
Sum2408758.6
Variance5.3160485 × 108
MonotonicityNot monotonic
2024-05-11T07:48:09.164948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 361
 
11.0%
1.0 125
 
3.8%
18.0 62
 
1.9%
3.3 51
 
1.6%
10.0 38
 
1.2%
33.0 34
 
1.0%
15.0 31
 
0.9%
30.0 30
 
0.9%
20.0 17
 
0.5%
50.0 16
 
0.5%
Other values (1086) 1479
45.1%
(Missing) 1033
31.5%
ValueCountFrequency (%)
0.0 361
11.0%
1.0 125
 
3.8%
1.1 1
 
< 0.1%
1.29 1
 
< 0.1%
1.3 4
 
0.1%
1.35 1
 
< 0.1%
1.44 2
 
0.1%
1.64 1
 
< 0.1%
1.65 1
 
< 0.1%
2.0 5
 
0.2%
ValueCountFrequency (%)
883014.0 1
< 0.1%
583737.0 1
< 0.1%
157835.0 1
< 0.1%
147349.0 1
< 0.1%
133811.0 1
< 0.1%
84990.0 1
< 0.1%
41598.11 1
< 0.1%
13015.0 1
< 0.1%
12574.0 1
< 0.1%
11933.41 1
< 0.1%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct29
Distinct (%)2.6%
Missing2182
Missing (%)66.6%
Infinite0
Infinite (%)0.0%
Mean2.9251142
Minimum0
Maximum40
Zeros666
Zeros (%)20.3%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2024-05-11T07:48:09.600242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile15
Maximum40
Range40
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.1464707
Coefficient of variation (CV)1.7594085
Kurtosis7.8607898
Mean2.9251142
Median Absolute Deviation (MAD)0
Skewness2.4785995
Sum3203
Variance26.48616
MonotonicityNot monotonic
2024-05-11T07:48:10.086139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 666
 
20.3%
4 61
 
1.9%
3 56
 
1.7%
5 44
 
1.3%
2 38
 
1.2%
6 38
 
1.2%
8 30
 
0.9%
7 21
 
0.6%
15 19
 
0.6%
10 15
 
0.5%
Other values (19) 107
 
3.3%
(Missing) 2182
66.6%
ValueCountFrequency (%)
0 666
20.3%
1 15
 
0.5%
2 38
 
1.2%
3 56
 
1.7%
4 61
 
1.9%
5 44
 
1.3%
6 38
 
1.2%
7 21
 
0.6%
8 30
 
0.9%
9 13
 
0.4%
ValueCountFrequency (%)
40 1
 
< 0.1%
35 1
 
< 0.1%
34 1
 
< 0.1%
30 1
 
< 0.1%
28 1
 
< 0.1%
25 2
 
0.1%
22 1
 
< 0.1%
21 3
0.1%
20 7
0.2%
19 4
0.1%

지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.9%
Missing2359
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean0.4869281
Minimum0
Maximum7
Zeros689
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2024-05-11T07:48:10.669899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0439331
Coefficient of variation (CV)2.1439162
Kurtosis9.2538574
Mean0.4869281
Median Absolute Deviation (MAD)0
Skewness2.7869963
Sum447
Variance1.0897962
MonotonicityNot monotonic
2024-05-11T07:48:11.019500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 689
 
21.0%
1 104
 
3.2%
2 76
 
2.3%
3 24
 
0.7%
4 14
 
0.4%
5 6
 
0.2%
7 3
 
0.1%
6 2
 
0.1%
(Missing) 2359
72.0%
ValueCountFrequency (%)
0 689
21.0%
1 104
 
3.2%
2 76
 
2.3%
3 24
 
0.7%
4 14
 
0.4%
5 6
 
0.2%
6 2
 
0.1%
7 3
 
0.1%
ValueCountFrequency (%)
7 3
 
0.1%
6 2
 
0.1%
5 6
 
0.2%
4 14
 
0.4%
3 24
 
0.7%
2 76
 
2.3%
1 104
 
3.2%
0 689
21.0%

건물용도명
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
3100 
근린생활시설
 
108
사무실
 
45
판매시설
 
11
아파트
 
4
Other values (5)
 
9

Length

Max length15
Median length4
Mean length4.0570644
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3100
94.6%
근린생활시설 108
 
3.3%
사무실 45
 
1.4%
판매시설 11
 
0.3%
아파트 4
 
0.1%
기타 3
 
0.1%
교육연구시설 3
 
0.1%
다중주택(공동주택적용) 1
 
< 0.1%
다가구용 주택(공동주택적용) 1
 
< 0.1%
다세대주택 1
 
< 0.1%

Length

2024-05-11T07:48:11.488200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:11.920952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3100
94.6%
근린생활시설 108
 
3.3%
사무실 45
 
1.4%
판매시설 11
 
0.3%
아파트 4
 
0.1%
기타 3
 
0.1%
교육연구시설 3
 
0.1%
다중주택(공동주택적용 1
 
< 0.1%
다가구용 1
 
< 0.1%
주택(공동주택적용 1
 
< 0.1%

통로너비
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
2554 
0
723 

Length

Max length4
Median length4
Mean length3.3381141
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> 2554
77.9%
0 723
 
22.1%

Length

2024-05-11T07:48:12.503044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:12.949291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2554
77.9%
0 723
 
22.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
2554 
0
723 

Length

Max length4
Median length4
Mean length3.3381141
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> 2554
77.9%
0 723
 
22.1%

Length

2024-05-11T07:48:13.339964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:13.720874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2554
77.9%
0 723
 
22.1%

노래방실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
2554 
0
723 

Length

Max length4
Median length4
Mean length3.3381141
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> 2554
77.9%
0 723
 
22.1%

Length

2024-05-11T07:48:14.263583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:14.710906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2554
77.9%
0 723
 
22.1%

청소년실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
2554 
0
723 

Length

Max length4
Median length4
Mean length3.3381141
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> 2554
77.9%
0 723
 
22.1%

Length

2024-05-11T07:48:15.101257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:15.422606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2554
77.9%
0 723
 
22.1%

비상계단여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

비상구여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

자동환기여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

청소년실여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

특수조명여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

방음시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

비디오재생기명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

조명시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

음향시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

편의시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

소방시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

총게임기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
2554 
0
723 

Length

Max length4
Median length4
Mean length3.3381141
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> 2554
77.9%
0 723
 
22.1%

Length

2024-05-11T07:48:15.873737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:48:16.225239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2554
77.9%
0 723
 
22.1%

기존게임업외업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

제공게임물명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

공연장형태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

품목명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

최초등록시점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3277
Missing (%)100.0%
Memory size28.9 KiB

지역구분명
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
3080 
준공업지역
 
68
일반상업지역
 
37
일반주거지역
 
35
주거지역
 
17
Other values (8)
 
40

Length

Max length6
Median length4
Mean length4.0765944
Min length4

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3080
94.0%
준공업지역 68
 
2.1%
일반상업지역 37
 
1.1%
일반주거지역 35
 
1.1%
주거지역 17
 
0.5%
준주거지역 15
 
0.5%
상업지역 12
 
0.4%
근린상업지역 6
 
0.2%
전용주거지역 2
 
0.1%
중심상업지역 2
 
0.1%
Other values (3) 3
 
0.1%

Length

2024-05-11T07:48:16.663781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3080
94.0%
준공업지역 68
 
2.1%
일반상업지역 37
 
1.1%
일반주거지역 35
 
1.1%
주거지역 17
 
0.5%
준주거지역 15
 
0.5%
상업지역 12
 
0.4%
근린상업지역 6
 
0.2%
전용주거지역 2
 
0.1%
중심상업지역 2
 
0.1%
Other values (3) 3
 
0.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명총층수주변환경명제작취급품목내용시설면적지상층수지하층수건물용도명통로너비조명시설조도노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부비디오재생기명조명시설유무음향시설여부편의시설여부소방시설여부총게임기수기존게임업외업종명제공게임물명공연장형태구분명품목명최초등록시점지역구분명
03180000CDFF22411220170000162017-06-28<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 문래동*가 ** 문래 SK V* center서울특별시 영등포구 선유로*길 **, 문래 SK V* center ****호 (문래동*가)07281매머드PC2023-02-28 14:45:06U2022-12-03 00:03:00.0<NA>190555.768992446698.814323<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13220000CDFF22411220190000322018-05-30<NA>3폐업3폐업2023-03-02<NA><NA><NA><NA><NA><NA>서울특별시 강남구 대치동 ***-**서울특별시 강남구 테헤란로**길 **, **호 (대치동)06178주식회사 폭스게임즈2023-03-02 15:33:00U2022-12-03 00:04:00.0<NA>205079.418138444869.834721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23210000CDFF22411220230000022023-03-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 ****-* 국제전자센터 **,**호서울특별시 서초구 효령로 ***, 국제전자센터 *층 **,**호 (서초동)06720겜우리한우리2023-03-06 09:24:22I2022-12-03 00:08:00.0<NA>201501.67266442505.573143<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33180000CDFF22411220200000132020-11-16<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동*가 **서울특별시 영등포구 영신로**길 *, *층 (영등포동*가)07251우성전자2023-03-07 14:16:40U2022-12-03 00:09:00.0<NA>191279.885047446536.965434<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43160000CDFF22411220170000122017-11-08<NA>5제외/삭제/전출15전출2023-03-07<NA><NA><NA>02-869-1222<NA><NA>서울특별시 구로구 구로동 **-* 다인빌딩 ***호서울특별시 구로구 구로중앙로**길 ** (구로동)08302(주)에스디소프트2023-03-07 13:14:39U2022-12-03 00:09:00.0<NA>190418.759352443803.304336<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53180000CDFF22411220230000022017-11-08<NA>1영업/정상13영업중<NA><NA><NA><NA>02-869-1222<NA><NA>서울특별시 영등포구 대림동 ***-* 대림하우스서울특별시 영등포구 대림로 ***, 대림하우스 ***호 (대림동)07410(주)에스디소프트2023-03-07 13:26:17I2022-12-03 00:09:00.0<NA>191008.421514443923.872118<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63180000CDFF22411220230000032013-10-02<NA>1영업/정상13영업중<NA><NA><NA><NA>02-869-1222<NA><NA>서울특별시 영등포구 대림동 ***-* 대림하우스서울특별시 영등포구 대림로 ***, 대림하우스 ***호 (대림동)07410(주)에스엠게임즈2023-03-07 14:17:05I2022-12-03 00:09:00.0<NA>191008.421514443923.872118<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
73160000CDFF22411220130000332013-10-02<NA>5제외/삭제/전출15전출2023-03-07<NA><NA><NA>02-869-1222<NA><NA>서울특별시 구로구 구로동 **-* 다인빌딩 ***호서울특별시 구로구 구로중앙로**길 **, ***호 (구로동, 다인빌딩)08302(주)에스엠게임즈2023-03-07 13:13:45U2022-12-03 00:09:00.0<NA>190418.759352443803.304336<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
83220000CDFF22411220230000072023-03-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 역삼동 ***-** 새롬빌딩서울특별시 강남구 선릉로 ***, 새롬빌딩 지하*층 (역삼동)06145(주)빅게임스튜디오2023-03-08 15:07:32I2022-12-02 23:00:00.0<NA>203923.219525445068.877037<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93220000CDFF22411220140000562012-11-15<NA>5제외/삭제/전출15전출2023-03-09<NA><NA><NA><NA><NA><NA>서울특별시 강남구 삼성동 ***-*서울특별시 강남구 삼성로 *** (삼성동)06168(주)인터파크2023-03-09 17:40:04U2022-12-02 23:01:00.0<NA>204914.532476445103.936441<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명총층수주변환경명제작취급품목내용시설면적지상층수지하층수건물용도명통로너비조명시설조도노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부비디오재생기명조명시설유무음향시설여부편의시설여부소방시설여부총게임기수기존게임업외업종명제공게임물명공연장형태구분명품목명최초등록시점지역구분명
32673220000CDFF224112202200002920220930<NA>5제외/삭제/전출15전출20221213<NA><NA><NA><NA><NA><NA>서울특별시 강남구 삼성동 77-11 랜드마크빌딩서울특별시 강남구 영동대로 607, 랜드마크빌딩 6층 (삼성동)06087주식회사 한컴링크2022-12-13 13:53:12U2021-11-01 23:05:00.0<NA>205189.161136445818.673205<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
32683180000CDFF224112201400001820141030<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동*가 **-*서울특별시 영등포구 영등포로 ***, *층 가열 **호 (당산동*가, 영등포유통상가)07264지니어스2022-05-19 14:20:57U2021-12-04 22:01:00.0<NA>190555.768992446698.814323<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
32693210000CDFF224112201900001220170308<NA>5제외/삭제/전출15전출20220823<NA><NA><NA>02-518-5923<NA><NA>서울특별시 서초구 서초동 ****-* (주)삼성출판사 사옥서울특별시 서초구 명달로 ** (주)삼성출판사 사옥 *층 (서초동)06668(주)미디어프론트2022-08-23 09:12:56U2021-12-07 22:05:00.0<NA>200313.23433442609.514493<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
32703170000CDFF224112202200000720221005<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 ***-*** 가산 더블유센터서울특별시 금천구 가산디지털*로 ***, 가산 더블유센터 ***호 (가산동)08503요스타홍콩리미티드(영업소)2022-10-05 10:12:14I2021-10-31 00:07:00.0<NA>189350.592435442143.206055<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
32713220000CDFF22411220220000282020-11-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 삼성동 ***-**서울특별시 강남구 테헤란로**길 **-**, **층 (삼성동)06159(주)핏펀즈2023-10-12 16:04:09U2022-10-30 23:04:00.0<NA>204671.159363444985.87312<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
32723220000CDFF224112202200002520220823<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 논현동 ***-*서울특별시 강남구 학동로**길 **, *층,*층 (논현동)06113(주)이츠블록2022-10-05 10:31:23U2021-10-31 00:07:00.0<NA>202415.313775445490.091003<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
32733220000CDFF224112201600001320160321<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6207-7112<NA><NA>서울특별시 강남구 청담동 **-* 파모소빌딩서울특별시 강남구 도산대로 ***, 파모소빌딩 *층 (청담동)06016(주)아이톡시2023-01-09 14:55:46U2022-11-30 23:01:00.0<NA>203693.316311446862.339555<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
32743220000CDFF22411220210000112021-03-22<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 삼성동 ***-*서울특별시 강남구 삼성로**길 ** (삼성동)06157에이시티게임즈(주)2024-02-23 16:52:02U2023-12-01 22:05:00.0<NA>204725.410822445186.845406<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
32753160000CDFF22411220220000072012-10-26<NA>1영업/정상13영업중<NA><NA><NA><NA>070-4658-9405<NA><NA>서울특별시 구로구 구로동 ***-** 에이스테크노타워*차 ****-호서울특별시 구로구 디지털로**길 **, 에이스테크노타워*차 ****-*,****,****,****호 (구로동)08380(주)팡스카이2024-05-03 15:47:05U2023-12-05 00:05:00.0<NA>190571.928128442598.144799<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
32763100000CDFF224112202200000220221013<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 노원구 공릉동 ***-** 노원 프레미어스 엠코 ***동 ***C호서울특별시 노원구 동일로 ***, ***동 ***C호 (공릉동, 노원 프레미어스 엠코)01849(주)머니웹2022-10-13 13:42:46I2021-10-30 23:05:00.0<NA>206659.562561457357.219231<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>