Overview

Dataset statistics

Number of variables59
Number of observations197
Missing cells5891
Missing cells (%)50.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory99.0 KiB
Average record size in memory514.7 B

Variable types

Numeric12
Categorical14
Text6
Unsupported26
DateTime1

Dataset

Description6270000_대구광역시_03_05_02_P_게임물제작업_9월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000068365&dataSetDetailId=DDI_0000068383&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
문화체육업종명 has constant value ""Constant
문화사업자구분명 has constant value ""Constant
인허가취소일자 is highly imbalanced (87.9%)Imbalance
상세영업상태코드 is highly imbalanced (53.5%)Imbalance
상세영업상태명 is highly imbalanced (53.5%)Imbalance
데이터갱신구분 is highly imbalanced (59.4%)Imbalance
주변환경명 is highly imbalanced (57.7%)Imbalance
지하층수 is highly imbalanced (82.0%)Imbalance
건물용도명 is highly imbalanced (54.2%)Imbalance
폐업일자 has 153 (77.7%) missing valuesMissing
휴업시작일자 has 197 (100.0%) missing valuesMissing
휴업종료일자 has 197 (100.0%) missing valuesMissing
재개업일자 has 197 (100.0%) missing valuesMissing
소재지전화 has 92 (46.7%) missing valuesMissing
소재지면적 has 197 (100.0%) missing valuesMissing
소재지우편번호 has 152 (77.2%) missing valuesMissing
도로명전체주소 has 6 (3.0%) missing valuesMissing
도로명우편번호 has 67 (34.0%) missing valuesMissing
업태구분명 has 197 (100.0%) missing valuesMissing
좌표정보(X) has 5 (2.5%) missing valuesMissing
좌표정보(Y) has 5 (2.5%) missing valuesMissing
총층수 has 131 (66.5%) missing valuesMissing
시설면적 has 37 (18.8%) missing valuesMissing
지상층수 has 121 (61.4%) missing valuesMissing
통로너비 has 197 (100.0%) missing valuesMissing
조명시설조도 has 197 (100.0%) missing valuesMissing
노래방실수 has 197 (100.0%) missing valuesMissing
청소년실수 has 197 (100.0%) missing valuesMissing
비상계단여부 has 197 (100.0%) missing valuesMissing
비상구여부 has 197 (100.0%) missing valuesMissing
자동환기여부 has 197 (100.0%) missing valuesMissing
청소년실여부 has 197 (100.0%) missing valuesMissing
특수조명여부 has 197 (100.0%) missing valuesMissing
방음시설여부 has 197 (100.0%) missing valuesMissing
비디오재생기명 has 197 (100.0%) missing valuesMissing
조명시설유무 has 197 (100.0%) missing valuesMissing
음향시설여부 has 197 (100.0%) missing valuesMissing
편의시설여부 has 197 (100.0%) missing valuesMissing
소방시설여부 has 197 (100.0%) missing valuesMissing
총게임기수 has 197 (100.0%) missing valuesMissing
기존게임업외업종명 has 197 (100.0%) missing valuesMissing
제공게임물명 has 197 (100.0%) missing valuesMissing
공연장형태구분명 has 197 (100.0%) missing valuesMissing
품목명 has 197 (100.0%) missing valuesMissing
최초등록시점 has 197 (100.0%) missing valuesMissing
번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
통로너비 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조명시설조도 is an unsupported type, check if it needs cleaning or further analysisUnsupported
노래방실수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
청소년실수 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
총게임기수 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
시설면적 has 3 (1.5%) zerosZeros

Reproduction

Analysis started2024-04-19 05:56:22.972206
Analysis finished2024-04-19 05:56:23.832615
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct197
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99
Minimum1
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:23.899671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.8
Q150
median99
Q3148
95-th percentile187.2
Maximum197
Range196
Interquartile range (IQR)98

Descriptive statistics

Standard deviation57.013156
Coefficient of variation (CV)0.57589047
Kurtosis-1.2
Mean99
Median Absolute Deviation (MAD)49
Skewness0
Sum19503
Variance3250.5
MonotonicityStrictly increasing
2024-04-19T14:56:24.044963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
125 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
Other values (187) 187
94.9%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
게임물제작업
197 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
게임물제작업 197
100.0%

Length

2024-04-19T14:56:24.178126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:24.270879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
게임물제작업 197
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
03_05_02_P
197 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_05_02_P
2nd row03_05_02_P
3rd row03_05_02_P
4th row03_05_02_P
5th row03_05_02_P

Common Values

ValueCountFrequency (%)
03_05_02_P 197
100.0%

Length

2024-04-19T14:56:24.376070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:24.464415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_05_02_p 197
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3440507.6
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:24.552357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13420000
median3440000
Q33460000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation21635.812
Coefficient of variation (CV)0.0062885523
Kurtosis-1.2855992
Mean3440507.6
Median Absolute Deviation (MAD)20000
Skewness-0.087405973
Sum6.7778 × 108
Variance4.6810836 × 108
MonotonicityIncreasing
2024-04-19T14:56:24.672887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3440000 43
21.8%
3410000 40
20.3%
3470000 30
15.2%
3460000 28
14.2%
3420000 25
12.7%
3450000 25
12.7%
3430000 3
 
1.5%
3480000 3
 
1.5%
ValueCountFrequency (%)
3410000 40
20.3%
3420000 25
12.7%
3430000 3
 
1.5%
3440000 43
21.8%
3450000 25
12.7%
3460000 28
14.2%
3470000 30
15.2%
3480000 3
 
1.5%
ValueCountFrequency (%)
3480000 3
 
1.5%
3470000 30
15.2%
3460000 28
14.2%
3450000 25
12.7%
3440000 43
21.8%
3430000 3
 
1.5%
3420000 25
12.7%
3410000 40
20.3%
Distinct87
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-19T14:56:24.884792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters3940
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

Unique37 ?
Unique (%)18.8%

Sample

1st rowCDFF2241082003000001
2nd rowCDFF2241082019000003
3rd rowCDFF2241082016000003
4th rowCDFF2241082002000003
5th rowCDFF2241082011000002
ValueCountFrequency (%)
cdff2241082014000001 7
 
3.6%
cdff2241082009000001 6
 
3.0%
cdff2241082019000001 6
 
3.0%
cdff2241082015000001 6
 
3.0%
cdff2241082019000002 5
 
2.5%
cdff2241082018000002 5
 
2.5%
cdff2241082018000001 5
 
2.5%
cdff2241082008000001 5
 
2.5%
cdff2241082016000002 5
 
2.5%
cdff2241082017000001 5
 
2.5%
Other values (77) 142
72.1%
2024-04-19T14:56:25.214596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1468
37.3%
2 655
16.6%
1 414
 
10.5%
F 394
 
10.0%
4 230
 
5.8%
8 228
 
5.8%
C 197
 
5.0%
D 197
 
5.0%
3 42
 
1.1%
9 32
 
0.8%
Other values (3) 83
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3152
80.0%
Uppercase Letter 788
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1468
46.6%
2 655
20.8%
1 414
 
13.1%
4 230
 
7.3%
8 228
 
7.2%
3 42
 
1.3%
9 32
 
1.0%
5 30
 
1.0%
7 30
 
1.0%
6 23
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
F 394
50.0%
C 197
25.0%
D 197
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3152
80.0%
Latin 788
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1468
46.6%
2 655
20.8%
1 414
 
13.1%
4 230
 
7.3%
8 228
 
7.2%
3 42
 
1.3%
9 32
 
1.0%
5 30
 
1.0%
7 30
 
1.0%
6 23
 
0.7%
Latin
ValueCountFrequency (%)
F 394
50.0%
C 197
25.0%
D 197
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1468
37.3%
2 655
16.6%
1 414
 
10.5%
F 394
 
10.0%
4 230
 
5.8%
8 228
 
5.8%
C 197
 
5.0%
D 197
 
5.0%
3 42
 
1.1%
9 32
 
0.8%
Other values (3) 83
 
2.1%

인허가일자
Real number (ℝ)

Distinct190
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20109876
Minimum19990706
Maximum20190902
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:25.390961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19990706
5-th percentile20011129
Q120070209
median20110624
Q320160616
95-th percentile20182747
Maximum20190902
Range200196
Interquartile range (IQR)90407

Descriptive statistics

Standard deviation56540.578
Coefficient of variation (CV)0.0028115826
Kurtosis-1.1164194
Mean20109876
Median Absolute Deviation (MAD)49900
Skewness-0.26506662
Sum3.9616456 × 109
Variance3.1968369 × 109
MonotonicityNot monotonic
2024-04-19T14:56:25.586101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20100409 2
 
1.0%
20160504 2
 
1.0%
20050614 2
 
1.0%
20170228 2
 
1.0%
20011129 2
 
1.0%
20080411 2
 
1.0%
20161228 2
 
1.0%
20070913 1
 
0.5%
20170719 1
 
0.5%
20171108 1
 
0.5%
Other values (180) 180
91.4%
ValueCountFrequency (%)
19990706 1
0.5%
19990730 1
0.5%
20000104 1
0.5%
20000415 1
0.5%
20000613 1
0.5%
20000807 1
0.5%
20010111 1
0.5%
20010419 1
0.5%
20010817 1
0.5%
20011129 2
1.0%
ValueCountFrequency (%)
20190902 1
0.5%
20190719 1
0.5%
20190712 1
0.5%
20190620 1
0.5%
20190501 1
0.5%
20190402 1
0.5%
20190307 1
0.5%
20190305 1
0.5%
20190208 1
0.5%
20190108 1
0.5%

인허가취소일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
191 
20070726
 
3
20110302
 
2
20101102
 
1

Length

Max length8
Median length4
Mean length4.1218274
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row20101102
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 191
97.0%
20070726 3
 
1.5%
20110302 2
 
1.0%
20101102 1
 
0.5%

Length

2024-04-19T14:56:25.812245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:25.953304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 191
97.0%
20070726 3
 
1.5%
20110302 2
 
1.0%
20101102 1
 
0.5%
Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1
147 
3
40 
4
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 147
74.6%
3 40
 
20.3%
4 10
 
5.1%

Length

2024-04-19T14:56:26.066278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:26.156449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 147
74.6%
3 40
 
20.3%
4 10
 
5.1%

영업상태명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
영업/정상
147 
폐업
40 
취소/말소/만료/정지/중지
 
10

Length

Max length14
Median length5
Mean length4.8477157
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 147
74.6%
폐업 40
 
20.3%
취소/말소/만료/정지/중지 10
 
5.1%

Length

2024-04-19T14:56:26.266589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:26.372138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 147
74.6%
폐업 40
 
20.3%
취소/말소/만료/정지/중지 10
 
5.1%

상세영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
13
147 
3
40 
35
 
4
31
 
3
30
 
3

Length

Max length2
Median length2
Mean length1.7969543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row31
2nd row13
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
13 147
74.6%
3 40
 
20.3%
35 4
 
2.0%
31 3
 
1.5%
30 3
 
1.5%

Length

2024-04-19T14:56:26.489609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:26.590609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 147
74.6%
3 40
 
20.3%
35 4
 
2.0%
31 3
 
1.5%
30 3
 
1.5%

상세영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
영업중
147 
폐업
40 
직권말소
 
4
등록취소
 
3
허가취소
 
3

Length

Max length4
Median length3
Mean length2.8477157
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 147
74.6%
폐업 40
 
20.3%
직권말소 4
 
2.0%
등록취소 3
 
1.5%
허가취소 3
 
1.5%

Length

2024-04-19T14:56:26.996091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:27.119400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 147
74.6%
폐업 40
 
20.3%
직권말소 4
 
2.0%
등록취소 3
 
1.5%
허가취소 3
 
1.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)90.9%
Missing153
Missing (%)77.7%
Infinite0
Infinite (%)0.0%
Mean20112713
Minimum20050912
Maximum20181224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:27.239796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050912
5-th percentile20050912
Q120078068
median20105679
Q320142779
95-th percentile20180703
Maximum20181224
Range130312
Interquartile range (IQR)64711.5

Descriptive statistics

Standard deviation41495.306
Coefficient of variation (CV)0.0020631382
Kurtosis-1.0526733
Mean20112713
Median Absolute Deviation (MAD)34594.5
Skewness0.21412915
Sum8.8495936 × 108
Variance1.7218604 × 109
MonotonicityNot monotonic
2024-04-19T14:56:27.367694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
20050912 5
 
2.5%
20130426 1
 
0.5%
20181224 1
 
0.5%
20130123 1
 
0.5%
20131217 1
 
0.5%
20101123 1
 
0.5%
20110127 1
 
0.5%
20180802 1
 
0.5%
20100927 1
 
0.5%
20101231 1
 
0.5%
Other values (30) 30
 
15.2%
(Missing) 153
77.7%
ValueCountFrequency (%)
20050912 5
2.5%
20070126 1
 
0.5%
20070208 1
 
0.5%
20070313 1
 
0.5%
20070430 1
 
0.5%
20070703 1
 
0.5%
20071016 1
 
0.5%
20080418 1
 
0.5%
20090323 1
 
0.5%
20090330 1
 
0.5%
ValueCountFrequency (%)
20181224 1
0.5%
20180802 1
0.5%
20180720 1
0.5%
20180604 1
0.5%
20180403 1
0.5%
20171107 1
0.5%
20170327 1
0.5%
20161123 1
0.5%
20160329 1
0.5%
20150723 1
0.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

소재지전화
Text

MISSING 

Distinct104
Distinct (%)99.0%
Missing92
Missing (%)46.7%
Memory size1.7 KiB
2024-04-19T14:56:27.603331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.009524
Min length8

Characters and Unicode

Total characters1156
Distinct characters16
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

Unique103 ?
Unique (%)98.1%

Sample

1st row(053)427-0500
2nd row(053)422-6030
3rd row07041381580
4th row053-254-8380
5th row(053)254-7253
ValueCountFrequency (%)
053 4
 
3.7%
053)423-1839 2
 
1.8%
623-0531 1
 
0.9%
285-1700 1
 
0.9%
053-752-0456 1
 
0.9%
053-745-1907 1
 
0.9%
053-744-7777 1
 
0.9%
0536558055 1
 
0.9%
0532160623 1
 
0.9%
053-939-0340 1
 
0.9%
Other values (95) 95
87.2%
2024-04-19T14:56:28.008829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 171
14.8%
5 141
12.2%
3 137
11.9%
- 134
11.6%
2 104
9.0%
1 91
7.9%
7 84
7.3%
4 82
7.1%
6 65
 
5.6%
8 61
 
5.3%
Other values (6) 86
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 984
85.1%
Dash Punctuation 134
 
11.6%
Open Punctuation 16
 
1.4%
Close Punctuation 16
 
1.4%
Space Separator 4
 
0.3%
Math Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 171
17.4%
5 141
14.3%
3 137
13.9%
2 104
10.6%
1 91
9.2%
7 84
8.5%
4 82
8.3%
6 65
 
6.6%
8 61
 
6.2%
9 48
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1156
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 171
14.8%
5 141
12.2%
3 137
11.9%
- 134
11.6%
2 104
9.0%
1 91
7.9%
7 84
7.3%
4 82
7.1%
6 65
 
5.6%
8 61
 
5.3%
Other values (6) 86
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 171
14.8%
5 141
12.2%
3 137
11.9%
- 134
11.6%
2 104
9.0%
1 91
7.9%
7 84
7.3%
4 82
7.1%
6 65
 
5.6%
8 61
 
5.3%
Other values (6) 86
7.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)73.3%
Missing152
Missing (%)77.2%
Infinite0
Infinite (%)0.0%
Mean702879.36
Minimum700060
Maximum706840
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:28.141835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700060
5-th percentile700170
Q1700412
median700811
Q3705816
95-th percentile706831.8
Maximum706840
Range6780
Interquartile range (IQR)5404

Descriptive statistics

Standard deviation2748.5167
Coefficient of variation (CV)0.0039103676
Kurtosis-1.6987427
Mean702879.36
Median Absolute Deviation (MAD)751
Skewness0.33950691
Sum31629571
Variance7554344
MonotonicityNot monotonic
2024-04-19T14:56:28.266953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
700170 6
 
3.0%
700423 3
 
1.5%
700804 2
 
1.0%
704833 2
 
1.0%
706808 2
 
1.0%
700180 2
 
1.0%
700412 2
 
1.0%
700413 1
 
0.5%
706840 1
 
0.5%
704937 1
 
0.5%
Other values (23) 23
 
11.7%
(Missing) 152
77.2%
ValueCountFrequency (%)
700060 1
 
0.5%
700113 1
 
0.5%
700170 6
3.0%
700180 2
 
1.0%
700412 2
 
1.0%
700413 1
 
0.5%
700421 1
 
0.5%
700423 3
1.5%
700743 1
 
0.5%
700802 1
 
0.5%
ValueCountFrequency (%)
706840 1
0.5%
706836 1
0.5%
706834 1
0.5%
706823 1
0.5%
706822 1
0.5%
706808 2
1.0%
706800 1
0.5%
706170 1
0.5%
706160 1
0.5%
705817 1
0.5%
Distinct179
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-19T14:56:28.624134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length26.690355
Min length13

Characters and Unicode

Total characters5258
Distinct characters185
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique168 ?
Unique (%)85.3%

Sample

1st row대구광역시 중구 동문동 9-21번지
2nd row대구광역시 중구 상서동 23-1번지 대구YMCA청소년회관
3rd row대구광역시 중구 남산동 2466-24번지 3층
4th row대구광역시 중구 완전동 1-55번지
5th row대구광역시 중구 동인동1가 116번지 78태평아파트 2동 102호
ValueCountFrequency (%)
대구광역시 197
 
20.1%
남구 42
 
4.3%
중구 41
 
4.2%
대명동 34
 
3.5%
달서구 30
 
3.1%
수성구 28
 
2.9%
북구 25
 
2.5%
동구 25
 
2.5%
신천동 20
 
2.0%
2139번지 14
 
1.4%
Other values (331) 525
53.5%
2024-04-19T14:56:29.129532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
954
18.1%
421
 
8.0%
279
 
5.3%
247
 
4.7%
1 247
 
4.7%
219
 
4.2%
205
 
3.9%
200
 
3.8%
199
 
3.8%
195
 
3.7%
Other values (175) 2092
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3047
57.9%
Decimal Number 1064
 
20.2%
Space Separator 954
 
18.1%
Dash Punctuation 149
 
2.8%
Uppercase Letter 26
 
0.5%
Open Punctuation 6
 
0.1%
Close Punctuation 6
 
0.1%
Other Punctuation 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
421
13.8%
279
 
9.2%
247
 
8.1%
219
 
7.2%
205
 
6.7%
200
 
6.6%
199
 
6.5%
195
 
6.4%
52
 
1.7%
51
 
1.7%
Other values (146) 979
32.1%
Uppercase Letter
ValueCountFrequency (%)
I 4
15.4%
A 4
15.4%
D 3
11.5%
C 3
11.5%
T 2
7.7%
F 2
7.7%
P 2
7.7%
B 1
 
3.8%
U 1
 
3.8%
H 1
 
3.8%
Other values (3) 3
11.5%
Decimal Number
ValueCountFrequency (%)
1 247
23.2%
2 159
14.9%
3 127
11.9%
0 120
11.3%
5 80
 
7.5%
8 80
 
7.5%
9 77
 
7.2%
6 66
 
6.2%
7 54
 
5.1%
4 54
 
5.1%
Space Separator
ValueCountFrequency (%)
954
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 149
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3047
57.9%
Common 2185
41.6%
Latin 26
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
421
13.8%
279
 
9.2%
247
 
8.1%
219
 
7.2%
205
 
6.7%
200
 
6.6%
199
 
6.5%
195
 
6.4%
52
 
1.7%
51
 
1.7%
Other values (146) 979
32.1%
Common
ValueCountFrequency (%)
954
43.7%
1 247
 
11.3%
2 159
 
7.3%
- 149
 
6.8%
3 127
 
5.8%
0 120
 
5.5%
5 80
 
3.7%
8 80
 
3.7%
9 77
 
3.5%
6 66
 
3.0%
Other values (6) 126
 
5.8%
Latin
ValueCountFrequency (%)
I 4
15.4%
A 4
15.4%
D 3
11.5%
C 3
11.5%
T 2
7.7%
F 2
7.7%
P 2
7.7%
B 1
 
3.8%
U 1
 
3.8%
H 1
 
3.8%
Other values (3) 3
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3047
57.9%
ASCII 2211
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
954
43.1%
1 247
 
11.2%
2 159
 
7.2%
- 149
 
6.7%
3 127
 
5.7%
0 120
 
5.4%
5 80
 
3.6%
8 80
 
3.6%
9 77
 
3.5%
6 66
 
3.0%
Other values (19) 152
 
6.9%
Hangul
ValueCountFrequency (%)
421
13.8%
279
 
9.2%
247
 
8.1%
219
 
7.2%
205
 
6.7%
200
 
6.6%
199
 
6.5%
195
 
6.4%
52
 
1.7%
51
 
1.7%
Other values (146) 979
32.1%

도로명전체주소
Text

MISSING 

Distinct186
Distinct (%)97.4%
Missing6
Missing (%)3.0%
Memory size1.7 KiB
2024-04-19T14:56:29.550200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length47
Mean length32.706806
Min length21

Characters and Unicode

Total characters6247
Distinct characters230
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique182 ?
Unique (%)95.3%

Sample

1st row대구광역시 중구 교동4길 33-21 (동문동)
2nd row대구광역시 중구 국채보상로 541, 대구YMCA청소년회관 6층 5호 (상서동)
3rd row대구광역시 중구 남산로 43-1, 3층 (남산동)
4th row대구광역시 중구 교동4길 25-8 (완전동)
5th row대구광역시 중구 태평로 225, 2동 102호 (동인동1가, 태평아파트)
ValueCountFrequency (%)
대구광역시 191
 
15.8%
남구 40
 
3.3%
중구 39
 
3.2%
달서구 29
 
2.4%
대명동 29
 
2.4%
수성구 27
 
2.2%
동구 25
 
2.1%
북구 25
 
2.1%
2층 21
 
1.7%
명덕로 21
 
1.7%
Other values (441) 761
63.0%
2024-04-19T14:56:30.150150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1074
 
17.2%
442
 
7.1%
325
 
5.2%
293
 
4.7%
1 214
 
3.4%
200
 
3.2%
196
 
3.1%
195
 
3.1%
) 190
 
3.0%
( 190
 
3.0%
Other values (220) 2928
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3518
56.3%
Space Separator 1074
 
17.2%
Decimal Number 1035
 
16.6%
Close Punctuation 190
 
3.0%
Open Punctuation 190
 
3.0%
Other Punctuation 189
 
3.0%
Dash Punctuation 29
 
0.5%
Uppercase Letter 19
 
0.3%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
442
 
12.6%
325
 
9.2%
293
 
8.3%
200
 
5.7%
196
 
5.6%
195
 
5.5%
178
 
5.1%
86
 
2.4%
78
 
2.2%
76
 
2.2%
Other values (195) 1449
41.2%
Decimal Number
ValueCountFrequency (%)
1 214
20.7%
2 158
15.3%
0 134
12.9%
4 120
11.6%
3 113
10.9%
5 72
 
7.0%
8 68
 
6.6%
7 61
 
5.9%
6 54
 
5.2%
9 41
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
A 5
26.3%
I 4
21.1%
T 3
15.8%
F 2
 
10.5%
P 1
 
5.3%
D 1
 
5.3%
C 1
 
5.3%
M 1
 
5.3%
Y 1
 
5.3%
Space Separator
ValueCountFrequency (%)
1074
100.0%
Close Punctuation
ValueCountFrequency (%)
) 190
100.0%
Open Punctuation
ValueCountFrequency (%)
( 190
100.0%
Other Punctuation
ValueCountFrequency (%)
, 189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3518
56.3%
Common 2710
43.4%
Latin 19
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
442
 
12.6%
325
 
9.2%
293
 
8.3%
200
 
5.7%
196
 
5.6%
195
 
5.5%
178
 
5.1%
86
 
2.4%
78
 
2.2%
76
 
2.2%
Other values (195) 1449
41.2%
Common
ValueCountFrequency (%)
1074
39.6%
1 214
 
7.9%
) 190
 
7.0%
( 190
 
7.0%
, 189
 
7.0%
2 158
 
5.8%
0 134
 
4.9%
4 120
 
4.4%
3 113
 
4.2%
5 72
 
2.7%
Other values (6) 256
 
9.4%
Latin
ValueCountFrequency (%)
A 5
26.3%
I 4
21.1%
T 3
15.8%
F 2
 
10.5%
P 1
 
5.3%
D 1
 
5.3%
C 1
 
5.3%
M 1
 
5.3%
Y 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3518
56.3%
ASCII 2729
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1074
39.4%
1 214
 
7.8%
) 190
 
7.0%
( 190
 
7.0%
, 189
 
6.9%
2 158
 
5.8%
0 134
 
4.9%
4 120
 
4.4%
3 113
 
4.1%
5 72
 
2.6%
Other values (15) 275
 
10.1%
Hangul
ValueCountFrequency (%)
442
 
12.6%
325
 
9.2%
293
 
8.3%
200
 
5.7%
196
 
5.6%
195
 
5.5%
178
 
5.1%
86
 
2.4%
78
 
2.2%
76
 
2.2%
Other values (195) 1449
41.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct76
Distinct (%)58.5%
Missing67
Missing (%)34.0%
Infinite0
Infinite (%)0.0%
Mean77686.431
Minimum41028
Maximum711822
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:30.327788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41028
5-th percentile41256
Q141566
median42136.5
Q342429.75
95-th percentile404761.1
Maximum711822
Range670794
Interquartile range (IQR)863.75

Descriptive statistics

Standard deviation150162.18
Coefficient of variation (CV)1.9329267
Kurtosis14.216884
Mean77686.431
Median Absolute Deviation (MAD)475.5
Skewness3.9996916
Sum10099236
Variance2.254868 × 1010
MonotonicityNot monotonic
2024-04-19T14:56:30.486097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42403 18
 
9.1%
41256 9
 
4.6%
41260 8
 
4.1%
41566 6
 
3.0%
41585 5
 
2.5%
41937 3
 
1.5%
41484 3
 
1.5%
41956 3
 
1.5%
41912 3
 
1.5%
42612 2
 
1.0%
Other values (66) 70
35.5%
(Missing) 67
34.0%
ValueCountFrequency (%)
41028 1
 
0.5%
41108 1
 
0.5%
41125 1
 
0.5%
41167 1
 
0.5%
41227 1
 
0.5%
41244 1
 
0.5%
41256 9
4.6%
41260 8
4.1%
41401 1
 
0.5%
41474 1
 
0.5%
ValueCountFrequency (%)
711822 1
0.5%
705831 1
0.5%
705819 1
0.5%
705039 1
0.5%
702812 1
0.5%
700836 1
0.5%
700754 1
0.5%
42992 1
0.5%
42930 1
0.5%
42818 2
1.0%
Distinct194
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-19T14:56:30.735238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length15
Mean length7.0507614
Min length2

Characters and Unicode

Total characters1389
Distinct characters278
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)97.0%

Sample

1st row한양전자
2nd row어바웃 게임즈(ABOUT GAMES)
3rd row스타터 유한책임회사
4th row대경실업
5th row사이드빌(SIDEVIL)
ValueCountFrequency (%)
주식회사 20
 
8.4%
다모아 2
 
0.8%
조이위드 2
 
0.8%
휴즈넷 2
 
0.8%
소프트 2
 
0.8%
누리 1
 
0.4%
쓰리에프팩토리(3f 1
 
0.4%
factory 1
 
0.4%
inc 1
 
0.4%
스마트이 1
 
0.4%
Other values (204) 204
86.1%
2024-04-19T14:56:31.126948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
6.2%
( 71
 
5.1%
) 71
 
5.1%
54
 
3.9%
47
 
3.4%
41
 
3.0%
40
 
2.9%
31
 
2.2%
30
 
2.2%
26
 
1.9%
Other values (268) 892
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1090
78.5%
Open Punctuation 71
 
5.1%
Close Punctuation 71
 
5.1%
Uppercase Letter 60
 
4.3%
Space Separator 40
 
2.9%
Lowercase Letter 36
 
2.6%
Decimal Number 12
 
0.9%
Other Punctuation 8
 
0.6%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
86
 
7.9%
54
 
5.0%
47
 
4.3%
41
 
3.8%
31
 
2.8%
30
 
2.8%
26
 
2.4%
26
 
2.4%
25
 
2.3%
20
 
1.8%
Other values (216) 704
64.6%
Uppercase Letter
ValueCountFrequency (%)
S 7
 
11.7%
I 5
 
8.3%
E 4
 
6.7%
T 4
 
6.7%
D 4
 
6.7%
O 4
 
6.7%
Y 3
 
5.0%
B 3
 
5.0%
M 3
 
5.0%
A 3
 
5.0%
Other values (12) 20
33.3%
Lowercase Letter
ValueCountFrequency (%)
o 5
13.9%
t 5
13.9%
c 3
8.3%
a 3
8.3%
e 3
8.3%
f 2
 
5.6%
i 2
 
5.6%
k 2
 
5.6%
r 2
 
5.6%
s 2
 
5.6%
Other values (7) 7
19.4%
Decimal Number
ValueCountFrequency (%)
0 5
41.7%
8 2
 
16.7%
3 2
 
16.7%
1 1
 
8.3%
4 1
 
8.3%
2 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 6
75.0%
, 1
 
12.5%
& 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1090
78.5%
Common 203
 
14.6%
Latin 96
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
86
 
7.9%
54
 
5.0%
47
 
4.3%
41
 
3.8%
31
 
2.8%
30
 
2.8%
26
 
2.4%
26
 
2.4%
25
 
2.3%
20
 
1.8%
Other values (216) 704
64.6%
Latin
ValueCountFrequency (%)
S 7
 
7.3%
o 5
 
5.2%
I 5
 
5.2%
t 5
 
5.2%
E 4
 
4.2%
T 4
 
4.2%
D 4
 
4.2%
O 4
 
4.2%
Y 3
 
3.1%
c 3
 
3.1%
Other values (29) 52
54.2%
Common
ValueCountFrequency (%)
( 71
35.0%
) 71
35.0%
40
19.7%
. 6
 
3.0%
0 5
 
2.5%
8 2
 
1.0%
3 2
 
1.0%
- 1
 
0.5%
1 1
 
0.5%
4 1
 
0.5%
Other values (3) 3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1090
78.5%
ASCII 299
 
21.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
86
 
7.9%
54
 
5.0%
47
 
4.3%
41
 
3.8%
31
 
2.8%
30
 
2.8%
26
 
2.4%
26
 
2.4%
25
 
2.3%
20
 
1.8%
Other values (216) 704
64.6%
ASCII
ValueCountFrequency (%)
( 71
23.7%
) 71
23.7%
40
13.4%
S 7
 
2.3%
. 6
 
2.0%
0 5
 
1.7%
o 5
 
1.7%
I 5
 
1.7%
t 5
 
1.7%
E 4
 
1.3%
Other values (42) 80
26.8%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct197
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.013705 × 1013
Minimum2.007043 × 1013
Maximum2.0190927 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:31.285752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.007043 × 1013
5-th percentile2.0070808 × 1013
Q12.0110103 × 1013
median2.0140724 × 1013
Q32.0171109 × 1013
95-th percentile2.0190703 × 1013
Maximum2.0190927 × 1013
Range1.2049702 × 1011
Interquartile range (IQR)6.1005977 × 1010

Descriptive statistics

Standard deviation4.044978 × 1010
Coefficient of variation (CV)0.0020087242
Kurtosis-1.1882816
Mean2.013705 × 1013
Median Absolute Deviation (MAD)3.0597006 × 1010
Skewness-0.33650337
Sum3.9669988 × 1015
Variance1.6361847 × 1021
MonotonicityNot monotonic
2024-04-19T14:56:31.452259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20101104132359 1
 
0.5%
20150127091114 1
 
0.5%
20170125104406 1
 
0.5%
20180730104355 1
 
0.5%
20180619102403 1
 
0.5%
20171108170141 1
 
0.5%
20170405180737 1
 
0.5%
20160616083210 1
 
0.5%
20160503172254 1
 
0.5%
20160315133709 1
 
0.5%
Other values (187) 187
94.9%
ValueCountFrequency (%)
20070430150436 1
0.5%
20070703163054 1
0.5%
20070726130927 1
0.5%
20070726131009 1
0.5%
20070726131051 1
0.5%
20070808132538 1
0.5%
20070808140707 1
0.5%
20070808143412 1
0.5%
20070808144901 1
0.5%
20070808145628 1
0.5%
ValueCountFrequency (%)
20190927175435 1
0.5%
20190926162127 1
0.5%
20190902135619 1
0.5%
20190813155135 1
0.5%
20190719103737 1
0.5%
20190718175218 1
0.5%
20190712090528 1
0.5%
20190711162838 1
0.5%
20190711101934 1
0.5%
20190703160136 1
0.5%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
I
181 
U
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 181
91.9%
U 16
 
8.1%

Length

2024-04-19T14:56:31.572881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:31.669053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 181
91.9%
u 16
 
8.1%
Distinct26
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2018-08-31 23:59:59
Maximum2019-09-29 02:40:00
2024-04-19T14:56:31.761071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:56:31.906228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct140
Distinct (%)72.9%
Missing5
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean343577.97
Minimum330188.03
Maximum355268.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:32.067738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330188.03
5-th percentile336778.76
Q1342464.62
median344098.07
Q3345694.93
95-th percentile348177.76
Maximum355268.65
Range25080.629
Interquartile range (IQR)3230.314

Descriptive statistics

Standard deviation3716.4949
Coefficient of variation (CV)0.010817035
Kurtosis1.8132164
Mean343577.97
Median Absolute Deviation (MAD)1607.6375
Skewness-0.51212146
Sum65966970
Variance13812334
MonotonicityNot monotonic
2024-04-19T14:56:32.242268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
342774.766132 14
 
7.1%
346675.629423 8
 
4.1%
346671.596784 7
 
3.6%
342632.844135 4
 
2.0%
345687.898519 4
 
2.0%
343918.932727 3
 
1.5%
344686.259338 3
 
1.5%
339767.711751 3
 
1.5%
343908.47526 3
 
1.5%
348665.873375 3
 
1.5%
Other values (130) 140
71.1%
(Missing) 5
 
2.5%
ValueCountFrequency (%)
330188.025284 1
0.5%
332041.965348 1
0.5%
333405.043635 1
0.5%
333415.217405 1
0.5%
335106.257743 1
0.5%
335696.726933 1
0.5%
335724.138822 1
0.5%
335914.193392 1
0.5%
336249.114209 1
0.5%
336768.382972 1
0.5%
ValueCountFrequency (%)
355268.654288 1
 
0.5%
354755.033317 1
 
0.5%
353862.969131 1
 
0.5%
352725.021343 1
 
0.5%
348898.124525 1
 
0.5%
348665.873375 3
1.5%
348375.293645 1
 
0.5%
348227.45681 1
 
0.5%
348137.09344 1
 
0.5%
348086.799192 1
 
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct140
Distinct (%)72.9%
Missing5
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean263471.78
Minimum239240.09
Maximum273228.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:32.388519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum239240.09
5-th percentile259673.79
Q1261962.41
median263190.74
Q3264814.12
95-th percentile267501.33
Maximum273228.66
Range33988.573
Interquartile range (IQR)2851.7117

Descriptive statistics

Standard deviation3078.0217
Coefficient of variation (CV)0.011682548
Kurtosis19.783141
Mean263471.78
Median Absolute Deviation (MAD)1571.7963
Skewness-2.1785056
Sum50586581
Variance9474217.4
MonotonicityNot monotonic
2024-04-19T14:56:32.588667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
262912.887933 14
 
7.1%
264755.079985 8
 
4.1%
264994.226366 7
 
3.6%
262643.902173 4
 
2.0%
266987.666828 4
 
2.0%
266015.581633 3
 
1.5%
263958.880864 3
 
1.5%
269135.246601 3
 
1.5%
264557.544338 3
 
1.5%
262623.706996 3
 
1.5%
Other values (130) 140
71.1%
(Missing) 5
 
2.5%
ValueCountFrequency (%)
239240.086699 1
0.5%
257742.940368 1
0.5%
258151.149273 1
0.5%
258266.945111 1
0.5%
258485.190839 1
0.5%
258570.98584 1
0.5%
258803.907476 1
0.5%
259052.115282 1
0.5%
259239.566122 1
0.5%
259654.792081 1
0.5%
ValueCountFrequency (%)
273228.659246 1
 
0.5%
272600.063881 1
 
0.5%
270526.670797 1
 
0.5%
270013.374392 1
 
0.5%
269135.246601 3
1.5%
268476.874903 1
 
0.5%
268253.830253 1
 
0.5%
267912.114415 1
 
0.5%
267165.23181 1
 
0.5%
267099.854053 1
 
0.5%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
게임물제작업
197 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
게임물제작업 197
100.0%

Length

2024-04-19T14:56:32.732637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:32.818858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
게임물제작업 197
100.0%

문화사업자구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
유통관련업
197 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통관련업 197
100.0%

Length

2024-04-19T14:56:32.921936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:33.012950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통관련업 197
100.0%

총층수
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)27.3%
Missing131
Missing (%)66.5%
Infinite0
Infinite (%)0.0%
Mean7.8181818
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:33.117417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q38.75
95-th percentile25
Maximum26
Range25
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation6.8767369
Coefficient of variation (CV)0.87958263
Kurtosis1.5925331
Mean7.8181818
Median Absolute Deviation (MAD)2
Skewness1.6130431
Sum516
Variance47.28951
MonotonicityNot monotonic
2024-04-19T14:56:33.237403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
5 11
 
5.6%
4 11
 
5.6%
2 8
 
4.1%
3 7
 
3.6%
6 4
 
2.0%
25 4
 
2.0%
7 4
 
2.0%
8 3
 
1.5%
12 3
 
1.5%
26 2
 
1.0%
Other values (8) 9
 
4.6%
(Missing) 131
66.5%
ValueCountFrequency (%)
1 1
 
0.5%
2 8
4.1%
3 7
3.6%
4 11
5.6%
5 11
5.6%
6 4
 
2.0%
7 4
 
2.0%
8 3
 
1.5%
9 1
 
0.5%
11 1
 
0.5%
ValueCountFrequency (%)
26 2
1.0%
25 4
2.0%
20 1
 
0.5%
18 1
 
0.5%
16 1
 
0.5%
15 1
 
0.5%
13 2
1.0%
12 3
1.5%
11 1
 
0.5%
9 1
 
0.5%

주변환경명
Categorical

IMBALANCE 

Distinct7
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
145 
기타
38 
아파트지역
 
6
주택가주변
 
5
유흥업소밀집지역
 
1
Other values (2)
 
2

Length

Max length8
Median length4
Mean length3.7309645
Min length2

Unique

Unique3 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 145
73.6%
기타 38
 
19.3%
아파트지역 6
 
3.0%
주택가주변 5
 
2.5%
유흥업소밀집지역 1
 
0.5%
학교정화(절대) 1
 
0.5%
학교정화(상대) 1
 
0.5%

Length

2024-04-19T14:56:33.366633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:33.477924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 145
73.6%
기타 38
 
19.3%
아파트지역 6
 
3.0%
주택가주변 5
 
2.5%
유흥업소밀집지역 1
 
0.5%
학교정화(절대 1
 
0.5%
학교정화(상대 1
 
0.5%
Distinct101
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-19T14:56:33.684010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19
Mean length6.3604061
Min length2

Characters and Unicode

Total characters1253
Distinct characters118
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)42.6%

Sample

1st row게임물
2nd row모바일게임 소프트웨어
3rd row게임, 모바일 게임
4th row게임물
5th row온라인 게임
ValueCountFrequency (%)
게임물 47
18.1%
게임 24
 
9.2%
모바일게임 23
 
8.8%
모바일 11
 
4.2%
온라인 10
 
3.8%
소프트웨어 9
 
3.5%
온라인게임 8
 
3.1%
6
 
2.3%
아케이드게임 5
 
1.9%
게임제작 4
 
1.5%
Other values (88) 113
43.5%
2024-04-19T14:56:34.041867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
177
 
14.1%
177
 
14.1%
63
 
5.0%
53
 
4.2%
52
 
4.2%
52
 
4.2%
52
 
4.2%
41
 
3.3%
36
 
2.9%
36
 
2.9%
Other values (108) 514
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1118
89.2%
Space Separator 63
 
5.0%
Other Punctuation 33
 
2.6%
Uppercase Letter 21
 
1.7%
Close Punctuation 7
 
0.6%
Open Punctuation 7
 
0.6%
Decimal Number 2
 
0.2%
Lowercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
177
15.8%
177
15.8%
53
 
4.7%
52
 
4.7%
52
 
4.7%
52
 
4.7%
41
 
3.7%
36
 
3.2%
36
 
3.2%
32
 
2.9%
Other values (87) 410
36.7%
Uppercase Letter
ValueCountFrequency (%)
R 4
19.0%
V 4
19.0%
P 3
14.3%
C 3
14.3%
W 1
 
4.8%
S 1
 
4.8%
D 1
 
4.8%
H 1
 
4.8%
T 1
 
4.8%
M 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 28
84.8%
/ 3
 
9.1%
& 2
 
6.1%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
5 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
50.0%
p 1
50.0%
Space Separator
ValueCountFrequency (%)
63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1118
89.2%
Common 112
 
8.9%
Latin 23
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
177
15.8%
177
15.8%
53
 
4.7%
52
 
4.7%
52
 
4.7%
52
 
4.7%
41
 
3.7%
36
 
3.2%
36
 
3.2%
32
 
2.9%
Other values (87) 410
36.7%
Latin
ValueCountFrequency (%)
R 4
17.4%
V 4
17.4%
P 3
13.0%
C 3
13.0%
W 1
 
4.3%
S 1
 
4.3%
D 1
 
4.3%
c 1
 
4.3%
H 1
 
4.3%
T 1
 
4.3%
Other values (3) 3
13.0%
Common
ValueCountFrequency (%)
63
56.2%
, 28
25.0%
) 7
 
6.2%
( 7
 
6.2%
/ 3
 
2.7%
& 2
 
1.8%
3 1
 
0.9%
5 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1118
89.2%
ASCII 135
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
177
15.8%
177
15.8%
53
 
4.7%
52
 
4.7%
52
 
4.7%
52
 
4.7%
41
 
3.7%
36
 
3.2%
36
 
3.2%
32
 
2.9%
Other values (87) 410
36.7%
ASCII
ValueCountFrequency (%)
63
46.7%
, 28
20.7%
) 7
 
5.2%
( 7
 
5.2%
R 4
 
3.0%
V 4
 
3.0%
/ 3
 
2.2%
P 3
 
2.2%
C 3
 
2.2%
& 2
 
1.5%
Other values (11) 11
 
8.1%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct132
Distinct (%)82.5%
Missing37
Missing (%)18.8%
Infinite0
Infinite (%)0.0%
Mean134.89706
Minimum0
Maximum3310
Zeros3
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:34.186540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q125
median65.975
Q3150.03
95-th percentile445.3165
Maximum3310
Range3310
Interquartile range (IQR)125.03

Descriptive statistics

Standard deviation292.40858
Coefficient of variation (CV)2.1676423
Kurtosis88.417039
Mean134.89706
Median Absolute Deviation (MAD)51.6
Skewness8.4440881
Sum21583.53
Variance85502.775
MonotonicityNot monotonic
2024-04-19T14:56:34.362872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 12
 
6.1%
33.0 4
 
2.0%
30.0 3
 
1.5%
25.0 3
 
1.5%
0.0 3
 
1.5%
45.0 2
 
1.0%
150.74 2
 
1.0%
16.0 2
 
1.0%
26.4 2
 
1.0%
10.0 2
 
1.0%
Other values (122) 125
63.5%
(Missing) 37
 
18.8%
ValueCountFrequency (%)
0.0 3
 
1.5%
0.6 1
 
0.5%
1.0 12
6.1%
3.3 1
 
0.5%
7.36 1
 
0.5%
7.8 1
 
0.5%
8.0 2
 
1.0%
9.9 1
 
0.5%
10.0 2
 
1.0%
12.0 1
 
0.5%
ValueCountFrequency (%)
3310.0 1
0.5%
840.07 1
0.5%
816.22 1
0.5%
779.0 1
0.5%
598.0 1
0.5%
500.0 1
0.5%
485.15 1
0.5%
446.58 1
0.5%
445.25 1
0.5%
394.43 1
0.5%

지상층수
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)13.2%
Missing121
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean3.8552632
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T14:56:34.523016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile12
Maximum14
Range13
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.4359043
Coefficient of variation (CV)0.89122433
Kurtosis1.0254161
Mean3.8552632
Median Absolute Deviation (MAD)1
Skewness1.4670859
Sum293
Variance11.805439
MonotonicityNot monotonic
2024-04-19T14:56:34.960727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 25
 
12.7%
1 16
 
8.1%
3 10
 
5.1%
8 7
 
3.6%
4 7
 
3.6%
12 5
 
2.5%
9 2
 
1.0%
5 2
 
1.0%
14 1
 
0.5%
11 1
 
0.5%
(Missing) 121
61.4%
ValueCountFrequency (%)
1 16
8.1%
2 25
12.7%
3 10
 
5.1%
4 7
 
3.6%
5 2
 
1.0%
8 7
 
3.6%
9 2
 
1.0%
11 1
 
0.5%
12 5
 
2.5%
14 1
 
0.5%
ValueCountFrequency (%)
14 1
 
0.5%
12 5
 
2.5%
11 1
 
0.5%
9 2
 
1.0%
8 7
 
3.6%
5 2
 
1.0%
4 7
 
3.6%
3 10
 
5.1%
2 25
12.7%
1 16
8.1%

지하층수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
186 
1
 
9
4
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.8324873
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row<NA>
3rd row4
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 186
94.4%
1 9
 
4.6%
4 1
 
0.5%
2 1
 
0.5%

Length

2024-04-19T14:56:35.094076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:56:35.201351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 186
94.4%
1 9
 
4.6%
4 1
 
0.5%
2 1
 
0.5%

건물용도명
Categorical

IMBALANCE 

Distinct13
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
137 
근린생활시설
22 
사무실
 
12
교육연구시설
 
11
기타
 
4
Other values (8)
 
11

Length

Max length15
Median length4
Mean length4.2893401
Min length2

Unique

Unique7 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 137
69.5%
근린생활시설 22
 
11.2%
사무실 12
 
6.1%
교육연구시설 11
 
5.6%
기타 4
 
2.0%
단독주택 4
 
2.0%
문화시설 1
 
0.5%
판매시설 1
 
0.5%
숙박시설 1
 
0.5%
유통시설 1
 
0.5%
Other values (3) 3
 
1.5%

Length

2024-04-19T14:56:35.322055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 137
69.2%
근린생활시설 22
 
11.1%
사무실 12
 
6.1%
교육연구시설 11
 
5.6%
기타 4
 
2.0%
단독주택 4
 
2.0%
문화시설 1
 
0.5%
판매시설 1
 
0.5%
숙박시설 1
 
0.5%
유통시설 1
 
0.5%
Other values (4) 4
 
2.0%

통로너비
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

조명시설조도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

노래방실수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

청소년실수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

비상계단여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

비상구여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

자동환기여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

청소년실여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

특수조명여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

방음시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

비디오재생기명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

조명시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

음향시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

편의시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

소방시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

총게임기수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

기존게임업외업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

제공게임물명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

공연장형태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

품목명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

최초등록시점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing197
Missing (%)100.0%
Memory size1.9 KiB

지역구분명
Categorical

Distinct11
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
126 
일반주거지역
32 
중심상업지역
17 
일반상업지역
 
9
근린상업지역
 
3
Other values (6)
 
10

Length

Max length6
Median length4
Mean length4.6497462
Min length4

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 126
64.0%
일반주거지역 32
 
16.2%
중심상업지역 17
 
8.6%
일반상업지역 9
 
4.6%
근린상업지역 3
 
1.5%
상업지역 2
 
1.0%
주거지역 2
 
1.0%
준공업지역 2
 
1.0%
준주거지역 2
 
1.0%
일반공업지역 1
 
0.5%

Length

2024-04-19T14:56:35.458225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 126
64.0%
일반주거지역 32
 
16.2%
중심상업지역 17
 
8.6%
일반상업지역 9
 
4.6%
근린상업지역 3
 
1.5%
상업지역 2
 
1.0%
주거지역 2
 
1.0%
준공업지역 2
 
1.0%
준주거지역 2
 
1.0%
일반공업지역 1
 
0.5%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명총층수주변환경명제작취급품목내용시설면적지상층수지하층수건물용도명통로너비조명시설조도노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부비디오재생기명조명시설유무음향시설여부편의시설여부소방시설여부총게임기수기존게임업외업종명제공게임물명공연장형태구분명품목명최초등록시점지역구분명
01게임물제작업03_05_02_P3410000CDFF224108200300000120030702201011024취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>(053)427-0500<NA>700180대구광역시 중구 동문동 9-21번지대구광역시 중구 교동4길 33-21 (동문동)<NA>한양전자20101104132359I2018-08-31 23:59:59.0<NA>344471.562932264753.265278게임물제작업유통관련업<NA><NA>게임물<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>
12게임물제작업03_05_02_P3410000CDFF224108201900000320190620<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 중구 상서동 23-1번지 대구YMCA청소년회관대구광역시 중구 국채보상로 541, 대구YMCA청소년회관 6층 5호 (상서동)41919어바웃 게임즈(ABOUT GAMES)20190711162838I2019-07-13 02:21:44.0<NA>343510.247922264550.37715게임물제작업유통관련업25기타모바일게임 소프트웨어7.88<NA>사무실<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>중심상업지역
23게임물제작업03_05_02_P3410000CDFF224108201600000320160523<NA>3폐업3폐업20171107<NA><NA><NA><NA><NA><NA>대구광역시 중구 남산동 2466-24번지 3층대구광역시 중구 남산로 43-1, 3층 (남산동)41978스타터 유한책임회사20171109091623I2018-08-31 23:59:59.0<NA>342854.118053263404.801719게임물제작업유통관련업4<NA>게임, 모바일 게임485.1514근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34게임물제작업03_05_02_P3410000CDFF224108200200000320020515<NA>3폐업3폐업20050912<NA><NA><NA>(053)422-6030<NA>700170대구광역시 중구 완전동 1-55번지대구광역시 중구 교동4길 25-8 (완전동)<NA>대경실업20070808171801I2018-08-31 23:59:59.0<NA>344406.597938264791.378242게임물제작업유통관련업<NA><NA>게임물<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>
45게임물제작업03_05_02_P3410000CDFF224108201100000220100618<NA>3폐업3폐업20140205<NA><NA><NA>07041381580<NA><NA>대구광역시 중구 동인동1가 116번지 78태평아파트 2동 102호대구광역시 중구 태평로 225, 2동 102호 (동인동1가, 태평아파트)700754사이드빌(SIDEVIL)20140205121317I2018-08-31 23:59:59.0<NA>344618.224393264938.197473게임물제작업유통관련업<NA><NA>온라인 게임43.1214<NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56게임물제작업03_05_02_P3410000CDFF224108201100000120110127<NA>3폐업3폐업20150501<NA><NA><NA><NA><NA><NA>대구광역시 중구 완전동 5-60번지대구광역시 중구 교동4길 30 (완전동)41912국제전자20180206161329I2018-08-31 23:59:59.0<NA>344424.874177265100.963729게임물제작업유통관련업<NA><NA>전자게임기144.0<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>
67게임물제작업03_05_02_P3410000CDFF224108200900000120090626<NA>3폐업3폐업20120919<NA><NA><NA>053-254-8380<NA><NA>대구광역시 중구 남산동 2270-41번지대구광역시 중구 명덕로 67 (남산동)700836동글소프트20120919150504I2018-08-31 23:59:59.0<NA>342500.756548263200.567711게임물제작업유통관련업<NA><NA>pc게임177.71<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>
78게임물제작업03_05_02_P3410000CDFF224108200300000220030529<NA>3폐업3폐업20050912<NA><NA><NA>(053)254-7253<NA>700170대구광역시 중구 완전동 1-11번지대구광역시 중구 교동4길 33-15 (완전동)<NA>부영전자20070808173421I2018-08-31 23:59:59.0<NA>344446.867181264761.79538게임물제작업유통관련업<NA><NA>게임물<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>
89게임물제작업03_05_02_P3410000CDFF224108200200000520021124<NA>3폐업3폐업20070126<NA><NA><NA>(053)422-4803<NA>700180대구광역시 중구 동문동 9-37번지대구광역시 중구 경상감영길 233-1 (동문동)<NA>로얄전자20070808180106I2018-08-31 23:59:59.0<NA>344446.219956264696.71715게임물제작업유통관련업<NA><NA>게임물<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>
910게임물제작업03_05_02_P3410000CDFF224108200200000420020923<NA>3폐업3폐업20050912<NA><NA><NA>(053)241-1119<NA>700743대구광역시 중구 동인동1가 358-2번지 동화빌딩 8층대구광역시 중구 동덕로 194 (동인동1가,동화빌딩 8층)<NA>(주)케이티엠에스20070808172638I2018-08-31 23:59:59.0<NA>344864.509609264713.227959게임물제작업유통관련업<NA><NA>게임물<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>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명총층수주변환경명제작취급품목내용시설면적지상층수지하층수건물용도명통로너비조명시설조도노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부비디오재생기명조명시설유무음향시설여부편의시설여부소방시설여부총게임기수기존게임업외업종명제공게임물명공연장형태구분명품목명최초등록시점지역구분명
187188게임물제작업03_05_02_P3470000CDFF224108201100000120110621<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 달서구 송현동 1909-20번지 (2층)대구광역시 달서구 송현로 110, 2층 (송현동)427438.0-솔루션20111030144142I2018-08-31 23:59:59.0<NA>339474.911581259654.792081게임물제작업유통관련업<NA><NA>소프트웨어개발78.512<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
188189게임물제작업03_05_02_P3470000CDFF224108201000000120100205<NA>1영업/정상13영업중<NA><NA><NA><NA>0505-509-1500<NA><NA>대구광역시 달서구 진천동 286-8번지 A동 (2층)대구광역시 달서구 진천로 14 (진천동,A동 (2층))<NA>(주)동헌20110120101042I2018-08-31 23:59:59.0<NA>337914.979019257742.940368게임물제작업유통관련업<NA><NA>게임물86.252<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
189190게임물제작업03_05_02_P3470000CDFF224108200800000120080204<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>704390대구광역시 달서구 유천동 175-0번지대구광역시 달서구 월배로5길 28 (유천동)<NA>게임버스20080204135825I2018-08-31 23:59:59.0<NA>336931.697991258151.149273게임물제작업유통관련업<NA><NA>인터넷게임<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>준공업지역
190191게임물제작업03_05_02_P3470000CDFF224108200600000120060714<NA>1영업/정상13영업중<NA><NA><NA><NA>566-4888<NA>704937대구광역시 달서구 용산동 958-19번지 용산하이츠 201호대구광역시 달서구 용산큰못길 53-13, 201호 (용산동,용산하이츠)<NA>태건전자20080108133613I2018-08-31 23:59:59.0<NA>337814.707161263405.908055게임물제작업유통관련업<NA><NA>아케이드게임기<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>
191192게임물제작업03_05_02_P3470000CDFF224108200500000220051227<NA>1영업/정상13영업중<NA><NA><NA><NA>1688-5441<NA>704833대구광역시 달서구 월암동 1075번지 본관 1F,2F대구광역시 달서구 성서공단로 236 (월암동,본관 1F,2F)<NA>(주)올제20080108133559I2018-08-31 23:59:59.0<NA>336249.114209260423.280201게임물제작업유통관련업<NA><NA>게임물<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>
192193게임물제작업03_05_02_P3470000CDFF224108201500000220151103<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 달서구 월성동 1551번지 코오롱하늘채 203동 1305호대구광역시 달서구 조암남로16길 20, 203동 1305호 (월성동, 월성코오롱하늘채아파트 2단지)42756태풍소프트20151105100634I2018-08-31 23:59:59.0<NA>337678.732425259052.115282게임물제작업유통관련업<NA><NA>아케이드게임14.4<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>
193194게임물제작업03_05_02_P3470000CDFF224108200800000420080819<NA>4취소/말소/만료/정지/중지35직권말소20110704<NA><NA><NA><NA><NA><NA>대구광역시 달서구 성당동 382-1번지대구광역시 달서구 야외음악당로8길 8 (성당동)<NA>낙원20110705101207I2018-08-31 23:59:59.0<NA>340270.575428261138.314676게임물제작업유통관련업<NA><NA>오락기46.2<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>
194195게임물제작업03_05_02_P3480000CDFF224108200800000120080618<NA>3폐업3폐업20130426<NA><NA><NA><NA><NA><NA>대구광역시 달성군 하빈면 현내리 858-26번지대구광역시 달성군 하빈면 하빈로77길 23-0711822서광WM시스템20130429085342I2018-08-31 23:59:59.0<NA>330188.025284267912.114415게임물제작업유통관련업<NA><NA>오락, 게임용기계제작500.01<NA>기타<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
195196게임물제작업03_05_02_P3480000CDFF224108201900000220180703<NA>1영업/정상13영업중<NA><NA><NA><NA>0534220320<NA><NA>대구광역시 달성군 다사읍 세천리 1702-6번지대구광역시 달성군 다사읍 세천남로 30, 3~4층42930주식회사파코웨어20190926162127I2019-09-27 02:22:37.0<NA>333415.217405264526.649705게임물제작업유통관련업5<NA>모바일,컴퓨터온라인게임371.12<NA>교육연구시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>녹지지역
196197게임물제작업03_05_02_P3480000CDFF224108201900000120190402<NA>1영업/정상13영업중<NA><NA><NA><NA>0536172100<NA><NA>대구광역시 달성군 유가읍 한정리 337-2번지대구광역시 달성군 유가읍 달창로26길 2542992흑룡솔루션20190402180611I2019-04-04 02:20:12.0<NA>332041.965348239240.086699게임물제작업유통관련업<NA><NA>웹보드게임3310.0<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>