Overview

Dataset statistics

Number of variables44
Number of observations3208
Missing cells33095
Missing cells (%)23.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory380.0 B

Variable types

Numeric15
Categorical14
Text6
Unsupported7
DateTime1
Boolean1

Dataset

Description22년12월_6270000_대구광역시_05_19_01_P_이용업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000097295&dataSetDetailId=DDI_0000097311&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 is highly imbalanced (90.9%)Imbalance
위생업태명 is highly imbalanced (90.9%)Imbalance
여성종사자수 is highly imbalanced (67.1%)Imbalance
남성종사자수 is highly imbalanced (54.8%)Imbalance
다중이용업소여부 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3208 (100.0%) missing valuesMissing
폐업일자 has 902 (28.1%) missing valuesMissing
휴업시작일자 has 3208 (100.0%) missing valuesMissing
휴업종료일자 has 3208 (100.0%) missing valuesMissing
재개업일자 has 3208 (100.0%) missing valuesMissing
소재지전화 has 1001 (31.2%) missing valuesMissing
도로명전체주소 has 1411 (44.0%) missing valuesMissing
도로명우편번호 has 1436 (44.8%) missing valuesMissing
좌표정보(X) has 175 (5.5%) missing valuesMissing
좌표정보(Y) has 175 (5.5%) missing valuesMissing
건물지상층수 has 579 (18.0%) missing valuesMissing
건물지하층수 has 942 (29.4%) missing valuesMissing
사용시작지상층 has 813 (25.3%) missing valuesMissing
사용끝지상층 has 1045 (32.6%) missing valuesMissing
의자수 has 349 (10.9%) missing valuesMissing
조건부허가신고사유 has 3208 (100.0%) missing valuesMissing
조건부허가시작일자 has 3208 (100.0%) missing valuesMissing
조건부허가종료일자 has 3208 (100.0%) missing valuesMissing
침대수 has 1778 (55.4%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 652 (20.3%) zerosZeros
건물지하층수 has 1229 (38.3%) zerosZeros
사용시작지상층 has 537 (16.7%) zerosZeros
사용끝지상층 has 317 (9.9%) zerosZeros
의자수 has 165 (5.1%) zerosZeros
침대수 has 1414 (44.1%) zerosZeros

Reproduction

Analysis started2024-04-21 18:38:57.435700
Analysis finished2024-04-21 18:38:59.229154
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1604.5
Minimum1
Maximum3208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:38:59.415511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile161.35
Q1802.75
median1604.5
Q32406.25
95-th percentile3047.65
Maximum3208
Range3207
Interquartile range (IQR)1603.5

Descriptive statistics

Standard deviation926.21416
Coefficient of variation (CV)0.5772603
Kurtosis-1.2
Mean1604.5
Median Absolute Deviation (MAD)802
Skewness0
Sum5147236
Variance857872.67
MonotonicityStrictly increasing
2024-04-22T03:38:59.827836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2144 1
 
< 0.1%
2134 1
 
< 0.1%
2135 1
 
< 0.1%
2136 1
 
< 0.1%
2137 1
 
< 0.1%
2138 1
 
< 0.1%
2139 1
 
< 0.1%
2140 1
 
< 0.1%
2141 1
 
< 0.1%
Other values (3198) 3198
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3208 1
< 0.1%
3207 1
< 0.1%
3206 1
< 0.1%
3205 1
< 0.1%
3204 1
< 0.1%
3203 1
< 0.1%
3202 1
< 0.1%
3201 1
< 0.1%
3200 1
< 0.1%
3199 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
이용업
3208 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이용업 3208
100.0%

Length

2024-04-22T03:39:00.139589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:00.301959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용업 3208
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
05_19_01_P
3208 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05_19_01_P
2nd row05_19_01_P
3rd row05_19_01_P
4th row05_19_01_P
5th row05_19_01_P

Common Values

ValueCountFrequency (%)
05_19_01_P 3208
100.0%

Length

2024-04-22T03:39:00.468054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:00.632861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 3208
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3445330.4
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:00.777275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33460000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation21036.812
Coefficient of variation (CV)0.0061058911
Kurtosis-1.2551188
Mean3445330.4
Median Absolute Deviation (MAD)20000
Skewness-0.12479031
Sum1.105262 × 1010
Variance4.4254747 × 108
MonotonicityIncreasing
2024-04-22T03:39:00.976501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 624
19.5%
3450000 518
16.1%
3420000 516
16.1%
3460000 454
14.2%
3430000 417
13.0%
3440000 278
8.7%
3410000 249
 
7.8%
3480000 152
 
4.7%
ValueCountFrequency (%)
3410000 249
 
7.8%
3420000 516
16.1%
3430000 417
13.0%
3440000 278
8.7%
3450000 518
16.1%
3460000 454
14.2%
3470000 624
19.5%
3480000 152
 
4.7%
ValueCountFrequency (%)
3480000 152
 
4.7%
3470000 624
19.5%
3460000 454
14.2%
3450000 518
16.1%
3440000 278
8.7%
3430000 417
13.0%
3420000 516
16.1%
3410000 249
 
7.8%

관리번호
Text

UNIQUE 

Distinct3208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
2024-04-22T03:39:01.610939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters70576
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

Unique3208 ?
Unique (%)100.0%

Sample

1st row3410000-203-2010-00002
2nd row3410000-203-2008-00003
3rd row3410000-203-2010-00003
4th row3410000-203-2010-00004
5th row3410000-203-2001-00001
ValueCountFrequency (%)
3410000-203-2010-00002 1
 
< 0.1%
3460000-203-2002-00017 1
 
< 0.1%
3460000-203-1997-00002 1
 
< 0.1%
3460000-203-2001-00010 1
 
< 0.1%
3460000-203-1997-00024 1
 
< 0.1%
3460000-203-1997-00026 1
 
< 0.1%
3460000-203-1999-00023 1
 
< 0.1%
3460000-203-1997-00069 1
 
< 0.1%
3460000-203-1998-00016 1
 
< 0.1%
3460000-203-1998-00018 1
 
< 0.1%
Other values (3198) 3198
99.7%
2024-04-22T03:39:02.442554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 31172
44.2%
- 9624
 
13.6%
3 7888
 
11.2%
2 6821
 
9.7%
4 4204
 
6.0%
1 3566
 
5.1%
9 2617
 
3.7%
7 1390
 
2.0%
6 1277
 
1.8%
5 1098
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60952
86.4%
Dash Punctuation 9624
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31172
51.1%
3 7888
 
12.9%
2 6821
 
11.2%
4 4204
 
6.9%
1 3566
 
5.9%
9 2617
 
4.3%
7 1390
 
2.3%
6 1277
 
2.1%
5 1098
 
1.8%
8 919
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 9624
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70576
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31172
44.2%
- 9624
 
13.6%
3 7888
 
11.2%
2 6821
 
9.7%
4 4204
 
6.0%
1 3566
 
5.1%
9 2617
 
3.7%
7 1390
 
2.0%
6 1277
 
1.8%
5 1098
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70576
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31172
44.2%
- 9624
 
13.6%
3 7888
 
11.2%
2 6821
 
9.7%
4 4204
 
6.0%
1 3566
 
5.1%
9 2617
 
3.7%
7 1390
 
2.0%
6 1277
 
1.8%
5 1098
 
1.6%

인허가일자
Real number (ℝ)

Distinct2128
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20019948
Minimum19601125
Maximum20221223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:02.690769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19601125
5-th percentile19810720
Q119970184
median20021001
Q320080502
95-th percentile20190411
Maximum20221223
Range620098
Interquartile range (IQR)110318.5

Descriptive statistics

Standard deviation102664.71
Coefficient of variation (CV)0.0051281206
Kurtosis1.2519739
Mean20019948
Median Absolute Deviation (MAD)50881
Skewness-0.62744308
Sum6.4223994 × 1010
Variance1.0540042 × 1010
MonotonicityNot monotonic
2024-04-22T03:39:02.945151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19961221 113
 
3.5%
19961224 97
 
3.0%
20030728 85
 
2.6%
20030708 77
 
2.4%
19961212 28
 
0.9%
19970114 23
 
0.7%
20030120 22
 
0.7%
19970120 22
 
0.7%
19961213 19
 
0.6%
20000426 16
 
0.5%
Other values (2118) 2706
84.4%
ValueCountFrequency (%)
19601125 1
< 0.1%
19601220 1
< 0.1%
19620824 1
< 0.1%
19630420 1
< 0.1%
19631009 1
< 0.1%
19631109 1
< 0.1%
19640812 1
< 0.1%
19650525 1
< 0.1%
19650731 1
< 0.1%
19661112 1
< 0.1%
ValueCountFrequency (%)
20221223 1
< 0.1%
20221208 1
< 0.1%
20221205 1
< 0.1%
20221128 1
< 0.1%
20221116 1
< 0.1%
20221004 1
< 0.1%
20220929 1
< 0.1%
20220927 1
< 0.1%
20220926 1
< 0.1%
20220915 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3208
Missing (%)100.0%
Memory size28.3 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
3
2306 
1
902 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 2306
71.9%
1 902
 
28.1%

Length

2024-04-22T03:39:03.182091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:03.349287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2306
71.9%
1 902
 
28.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
폐업
2306 
영업/정상
902 

Length

Max length5
Median length2
Mean length2.8435162
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2306
71.9%
영업/정상 902
 
28.1%

Length

2024-04-22T03:39:03.531338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:03.738136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2306
71.9%
영업/정상 902
 
28.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
2
2306 
1
902 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 2306
71.9%
1 902
 
28.1%

Length

2024-04-22T03:39:04.071776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:04.385306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2306
71.9%
1 902
 
28.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
폐업
2306 
영업
902 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2306
71.9%
영업 902
 
28.1%

Length

2024-04-22T03:39:04.715535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:05.028392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2306
71.9%
영업 902
 
28.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct1662
Distinct (%)72.1%
Missing902
Missing (%)28.1%
Infinite0
Infinite (%)0.0%
Mean20102406
Minimum19980506
Maximum20221229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:05.378632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980506
5-th percentile20030312
Q120041101
median20090221
Q320160428
95-th percentile20210831
Maximum20221229
Range240723
Interquartile range (IQR)119326.75

Descriptive statistics

Standard deviation63251.781
Coefficient of variation (CV)0.0031464782
Kurtosis-1.2122554
Mean20102406
Median Absolute Deviation (MAD)50096.5
Skewness0.39662724
Sum4.6356148 × 1010
Variance4.0007878 × 109
MonotonicityNot monotonic
2024-04-22T03:39:06.015768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040312 41
 
1.3%
20031231 28
 
0.9%
20030708 26
 
0.8%
20031120 25
 
0.8%
20031229 14
 
0.4%
20050117 11
 
0.3%
20031226 11
 
0.3%
20031230 10
 
0.3%
20031128 10
 
0.3%
20031222 9
 
0.3%
Other values (1652) 2121
66.1%
(Missing) 902
28.1%
ValueCountFrequency (%)
19980506 1
< 0.1%
19990524 1
< 0.1%
20000603 1
< 0.1%
20000710 1
< 0.1%
20000712 1
< 0.1%
20000812 1
< 0.1%
20000831 1
< 0.1%
20000925 1
< 0.1%
20001009 1
< 0.1%
20001212 1
< 0.1%
ValueCountFrequency (%)
20221229 1
< 0.1%
20221228 1
< 0.1%
20221227 2
0.1%
20221226 1
< 0.1%
20221221 1
< 0.1%
20221216 1
< 0.1%
20221214 1
< 0.1%
20221212 1
< 0.1%
20221130 1
< 0.1%
20221117 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3208
Missing (%)100.0%
Memory size28.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3208
Missing (%)100.0%
Memory size28.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3208
Missing (%)100.0%
Memory size28.3 KiB

소재지전화
Text

MISSING 

Distinct2082
Distinct (%)94.3%
Missing1001
Missing (%)31.2%
Memory size25.2 KiB
2024-04-22T03:39:07.215247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.771636
Min length6

Characters and Unicode

Total characters23773
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

Unique1974 ?
Unique (%)89.4%

Sample

1st row053 2572955
2nd row053 2536037
3rd row053 4233939
4th row053 4236188
5th row053 2562176
ValueCountFrequency (%)
053 1921
41.9%
764 16
 
0.3%
763 11
 
0.2%
352 11
 
0.2%
791 10
 
0.2%
762 9
 
0.2%
956 9
 
0.2%
756 8
 
0.2%
754 8
 
0.2%
755 8
 
0.2%
Other values (2213) 2572
56.1%
2024-04-22T03:39:08.790693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4377
18.4%
3 3559
15.0%
0 2937
12.4%
2395
10.1%
2 1937
8.1%
6 1809
7.6%
7 1459
 
6.1%
4 1441
 
6.1%
1 1317
 
5.5%
8 1273
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21378
89.9%
Space Separator 2395
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4377
20.5%
3 3559
16.6%
0 2937
13.7%
2 1937
9.1%
6 1809
8.5%
7 1459
 
6.8%
4 1441
 
6.7%
1 1317
 
6.2%
8 1273
 
6.0%
9 1269
 
5.9%
Space Separator
ValueCountFrequency (%)
2395
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23773
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4377
18.4%
3 3559
15.0%
0 2937
12.4%
2395
10.1%
2 1937
8.1%
6 1809
7.6%
7 1459
 
6.1%
4 1441
 
6.1%
1 1317
 
5.5%
8 1273
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23773
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4377
18.4%
3 3559
15.0%
0 2937
12.4%
2395
10.1%
2 1937
8.1%
6 1809
7.6%
7 1459
 
6.1%
4 1441
 
6.1%
1 1317
 
5.5%
8 1273
 
5.4%
Distinct1407
Distinct (%)44.2%
Missing24
Missing (%)0.7%
Memory size25.2 KiB
2024-04-22T03:39:10.187048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.7748116
Min length3

Characters and Unicode

Total characters15203
Distinct characters12
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

Unique990 ?
Unique (%)31.1%

Sample

1st row6.45
2nd row9.36
3rd row12.60
4th row6.20
5th row39.60
ValueCountFrequency (%)
00 241
 
7.6%
16.50 60
 
1.9%
33.00 59
 
1.9%
19.80 48
 
1.5%
20.00 43
 
1.4%
23.10 40
 
1.3%
15.00 37
 
1.2%
6.60 32
 
1.0%
26.40 32
 
1.0%
18.00 31
 
1.0%
Other values (1397) 2561
80.4%
2024-04-22T03:39:12.001667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3377
22.2%
. 3184
20.9%
1 1471
9.7%
2 1450
9.5%
3 1005
 
6.6%
5 961
 
6.3%
6 893
 
5.9%
4 818
 
5.4%
8 759
 
5.0%
9 691
 
4.5%
Other values (2) 594
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12015
79.0%
Other Punctuation 3188
 
21.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3377
28.1%
1 1471
12.2%
2 1450
12.1%
3 1005
 
8.4%
5 961
 
8.0%
6 893
 
7.4%
4 818
 
6.8%
8 759
 
6.3%
9 691
 
5.8%
7 590
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 3184
99.9%
, 4
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 15203
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3377
22.2%
. 3184
20.9%
1 1471
9.7%
2 1450
9.5%
3 1005
 
6.6%
5 961
 
6.3%
6 893
 
5.9%
4 818
 
5.4%
8 759
 
5.0%
9 691
 
4.5%
Other values (2) 594
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15203
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3377
22.2%
. 3184
20.9%
1 1471
9.7%
2 1450
9.5%
3 1005
 
6.6%
5 961
 
6.3%
6 893
 
5.9%
4 818
 
5.4%
8 759
 
5.0%
9 691
 
4.5%
Other values (2) 594
 
3.9%

소재지우편번호
Real number (ℝ)

Distinct545
Distinct (%)17.0%
Missing9
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean704177.17
Minimum700010
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:12.419146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700814.9
Q1702050
median703840
Q3705809
95-th percentile706852
Maximum711892
Range11882
Interquartile range (IQR)3759

Descriptive statistics

Standard deviation2491.7072
Coefficient of variation (CV)0.0035384663
Kurtosis1.7233885
Mean704177.17
Median Absolute Deviation (MAD)1965
Skewness1.0588245
Sum2.2526628 × 109
Variance6208604.7
MonotonicityNot monotonic
2024-04-22T03:39:12.821595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704080 41
 
1.3%
704060 35
 
1.1%
702040 30
 
0.9%
704932 25
 
0.8%
704834 23
 
0.7%
711852 23
 
0.7%
704904 22
 
0.7%
703805 22
 
0.7%
705809 22
 
0.7%
706839 21
 
0.7%
Other values (535) 2935
91.5%
ValueCountFrequency (%)
700010 7
0.2%
700020 3
0.1%
700030 4
0.1%
700040 1
 
< 0.1%
700060 1
 
< 0.1%
700070 1
 
< 0.1%
700081 1
 
< 0.1%
700082 4
0.1%
700093 1
 
< 0.1%
700111 4
0.1%
ValueCountFrequency (%)
711892 4
0.1%
711891 6
0.2%
711874 5
0.2%
711873 3
 
0.1%
711872 9
0.3%
711871 1
 
< 0.1%
711864 4
0.1%
711863 1
 
< 0.1%
711861 2
 
0.1%
711858 2
 
0.1%
Distinct2839
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
2024-04-22T03:39:14.101719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length46
Mean length23.687656
Min length17

Characters and Unicode

Total characters75990
Distinct characters291
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2553 ?
Unique (%)79.6%

Sample

1st row대구광역시 중구 삼덕동2가 0210-0001번지 지하1층
2nd row대구광역시 중구 서성로1가 0109-0001번지 (2층)
3rd row대구광역시 중구 동인동4가 0347-0001번지
4th row대구광역시 중구 남산동 0693-0008번지 지상2층
5th row대구광역시 중구 수창동 0099-0002번지
ValueCountFrequency (%)
대구광역시 3208
22.8%
달서구 624
 
4.4%
북구 518
 
3.7%
동구 517
 
3.7%
수성구 453
 
3.2%
서구 417
 
3.0%
남구 278
 
2.0%
중구 249
 
1.8%
대명동 205
 
1.5%
달성군 152
 
1.1%
Other values (3221) 7457
53.0%
2024-04-22T03:39:15.665327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13956
18.4%
6314
 
8.3%
3785
 
5.0%
1 3642
 
4.8%
3547
 
4.7%
3241
 
4.3%
3216
 
4.2%
3212
 
4.2%
3152
 
4.1%
- 2781
 
3.7%
Other values (281) 29144
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42214
55.6%
Decimal Number 16313
 
21.5%
Space Separator 13956
 
18.4%
Dash Punctuation 2781
 
3.7%
Close Punctuation 311
 
0.4%
Open Punctuation 311
 
0.4%
Other Punctuation 61
 
0.1%
Uppercase Letter 42
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6314
15.0%
3785
 
9.0%
3547
 
8.4%
3241
 
7.7%
3216
 
7.6%
3212
 
7.6%
3152
 
7.5%
2710
 
6.4%
1111
 
2.6%
895
 
2.1%
Other values (254) 11031
26.1%
Decimal Number
ValueCountFrequency (%)
1 3642
22.3%
2 2206
13.5%
0 1962
12.0%
3 1581
9.7%
4 1431
 
8.8%
5 1278
 
7.8%
6 1103
 
6.8%
7 1074
 
6.6%
9 1035
 
6.3%
8 1001
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
A 17
40.5%
B 13
31.0%
P 4
 
9.5%
T 4
 
9.5%
L 1
 
2.4%
H 1
 
2.4%
C 1
 
2.4%
S 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 54
88.5%
/ 3
 
4.9%
. 3
 
4.9%
@ 1
 
1.6%
Space Separator
ValueCountFrequency (%)
13956
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2781
100.0%
Close Punctuation
ValueCountFrequency (%)
) 311
100.0%
Open Punctuation
ValueCountFrequency (%)
( 311
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42213
55.6%
Common 33734
44.4%
Latin 42
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6314
15.0%
3785
 
9.0%
3547
 
8.4%
3241
 
7.7%
3216
 
7.6%
3212
 
7.6%
3152
 
7.5%
2710
 
6.4%
1111
 
2.6%
895
 
2.1%
Other values (253) 11030
26.1%
Common
ValueCountFrequency (%)
13956
41.4%
1 3642
 
10.8%
- 2781
 
8.2%
2 2206
 
6.5%
0 1962
 
5.8%
3 1581
 
4.7%
4 1431
 
4.2%
5 1278
 
3.8%
6 1103
 
3.3%
7 1074
 
3.2%
Other values (9) 2720
 
8.1%
Latin
ValueCountFrequency (%)
A 17
40.5%
B 13
31.0%
P 4
 
9.5%
T 4
 
9.5%
L 1
 
2.4%
H 1
 
2.4%
C 1
 
2.4%
S 1
 
2.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42213
55.6%
ASCII 33776
44.4%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13956
41.3%
1 3642
 
10.8%
- 2781
 
8.2%
2 2206
 
6.5%
0 1962
 
5.8%
3 1581
 
4.7%
4 1431
 
4.2%
5 1278
 
3.8%
6 1103
 
3.3%
7 1074
 
3.2%
Other values (17) 2762
 
8.2%
Hangul
ValueCountFrequency (%)
6314
15.0%
3785
 
9.0%
3547
 
8.4%
3241
 
7.7%
3216
 
7.6%
3212
 
7.6%
3152
 
7.5%
2710
 
6.4%
1111
 
2.6%
895
 
2.1%
Other values (253) 11030
26.1%
CJK
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1712
Distinct (%)95.3%
Missing1411
Missing (%)44.0%
Memory size25.2 KiB
2024-04-22T03:39:17.072180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length48
Mean length27.742348
Min length18

Characters and Unicode

Total characters49853
Distinct characters307
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

Unique1642 ?
Unique (%)91.4%

Sample

1st row대구광역시 중구 동덕로 115 (삼덕동2가, 지하1층)
2nd row대구광역시 중구 국채보상로 723 (동인동4가)
3rd row대구광역시 중구 국채보상로 458, 2층 (대신동)
4th row대구광역시 중구 국채보상로 570-8 (전동)
5th row대구광역시 중구 달구벌대로447길 72-1 (삼덕동3가)
ValueCountFrequency (%)
대구광역시 1797
 
17.7%
달서구 338
 
3.3%
1층 310
 
3.1%
동구 295
 
2.9%
북구 289
 
2.9%
수성구 255
 
2.5%
서구 209
 
2.1%
남구 172
 
1.7%
중구 139
 
1.4%
대명동 123
 
1.2%
Other values (2059) 6209
61.3%
2024-04-22T03:39:18.707939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8339
 
16.7%
3698
 
7.4%
2399
 
4.8%
2290
 
4.6%
1 2040
 
4.1%
1833
 
3.7%
( 1817
 
3.6%
) 1817
 
3.6%
1804
 
3.6%
1800
 
3.6%
Other values (297) 22016
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28824
57.8%
Space Separator 8339
 
16.7%
Decimal Number 7712
 
15.5%
Open Punctuation 1817
 
3.6%
Close Punctuation 1817
 
3.6%
Other Punctuation 986
 
2.0%
Dash Punctuation 323
 
0.6%
Uppercase Letter 34
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3698
 
12.8%
2399
 
8.3%
2290
 
7.9%
1833
 
6.4%
1804
 
6.3%
1800
 
6.2%
1712
 
5.9%
992
 
3.4%
755
 
2.6%
712
 
2.5%
Other values (271) 10829
37.6%
Decimal Number
ValueCountFrequency (%)
1 2040
26.5%
2 1148
14.9%
3 901
11.7%
0 637
 
8.3%
4 627
 
8.1%
5 553
 
7.2%
6 529
 
6.9%
7 475
 
6.2%
8 422
 
5.5%
9 380
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
A 15
44.1%
B 11
32.4%
E 2
 
5.9%
T 2
 
5.9%
P 2
 
5.9%
S 1
 
2.9%
H 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 983
99.7%
/ 1
 
0.1%
. 1
 
0.1%
@ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
8339
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1817
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1817
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 323
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28824
57.8%
Common 20995
42.1%
Latin 34
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3698
 
12.8%
2399
 
8.3%
2290
 
7.9%
1833
 
6.4%
1804
 
6.3%
1800
 
6.2%
1712
 
5.9%
992
 
3.4%
755
 
2.6%
712
 
2.5%
Other values (271) 10829
37.6%
Common
ValueCountFrequency (%)
8339
39.7%
1 2040
 
9.7%
( 1817
 
8.7%
) 1817
 
8.7%
2 1148
 
5.5%
, 983
 
4.7%
3 901
 
4.3%
0 637
 
3.0%
4 627
 
3.0%
5 553
 
2.6%
Other values (9) 2133
 
10.2%
Latin
ValueCountFrequency (%)
A 15
44.1%
B 11
32.4%
E 2
 
5.9%
T 2
 
5.9%
P 2
 
5.9%
S 1
 
2.9%
H 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28824
57.8%
ASCII 21029
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8339
39.7%
1 2040
 
9.7%
( 1817
 
8.6%
) 1817
 
8.6%
2 1148
 
5.5%
, 983
 
4.7%
3 901
 
4.3%
0 637
 
3.0%
4 627
 
3.0%
5 553
 
2.6%
Other values (16) 2167
 
10.3%
Hangul
ValueCountFrequency (%)
3698
 
12.8%
2399
 
8.3%
2290
 
7.9%
1833
 
6.4%
1804
 
6.3%
1800
 
6.2%
1712
 
5.9%
992
 
3.4%
755
 
2.6%
712
 
2.5%
Other values (271) 10829
37.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct852
Distinct (%)48.1%
Missing1436
Missing (%)44.8%
Infinite0
Infinite (%)0.0%
Mean42009.207
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:18.959698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41118.55
Q141535
median41962
Q342509
95-th percentile42920.25
Maximum43024
Range2024
Interquartile range (IQR)974

Descriptive statistics

Standard deviation577.67959
Coefficient of variation (CV)0.013751262
Kurtosis-1.1881046
Mean42009.207
Median Absolute Deviation (MAD)498
Skewness0.0014929356
Sum74440314
Variance333713.71
MonotonicityNot monotonic
2024-04-22T03:39:19.223825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41913 9
 
0.3%
41558 9
 
0.3%
42612 8
 
0.2%
41122 8
 
0.2%
42632 8
 
0.2%
41465 8
 
0.2%
41535 7
 
0.2%
41552 7
 
0.2%
42653 7
 
0.2%
42400 7
 
0.2%
Other values (842) 1694
52.8%
(Missing) 1436
44.8%
ValueCountFrequency (%)
41000 3
0.1%
41002 4
0.1%
41005 2
0.1%
41007 3
0.1%
41009 3
0.1%
41011 1
 
< 0.1%
41017 1
 
< 0.1%
41020 1
 
< 0.1%
41026 1
 
< 0.1%
41027 1
 
< 0.1%
ValueCountFrequency (%)
43024 1
 
< 0.1%
43013 4
0.1%
43010 2
0.1%
43006 1
 
< 0.1%
43005 1
 
< 0.1%
43004 1
 
< 0.1%
43003 1
 
< 0.1%
43000 4
0.1%
42999 3
0.1%
42996 3
0.1%
Distinct2039
Distinct (%)63.6%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
2024-04-22T03:39:20.189471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length5
Mean length5.1147132
Min length1

Characters and Unicode

Total characters16408
Distinct characters522
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1546 ?
Unique (%)48.2%

Sample

1st row진석이용소
2nd row삼정이용소
3rd row육교이용소
4th row아미가
5th row월드
ValueCountFrequency (%)
이용소 37
 
1.1%
현대이용소 26
 
0.8%
대성이용소 25
 
0.8%
명성이용소 20
 
0.6%
그린이용소 17
 
0.5%
삼성이용소 17
 
0.5%
블루클럽 15
 
0.5%
동원이용소 15
 
0.5%
보성이용소 13
 
0.4%
제일이용소 12
 
0.4%
Other values (2003) 3114
94.1%
2024-04-22T03:39:21.390919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2291
 
14.0%
2217
 
13.5%
2126
 
13.0%
343
 
2.1%
299
 
1.8%
205
 
1.2%
184
 
1.1%
184
 
1.1%
176
 
1.1%
160
 
1.0%
Other values (512) 8223
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15860
96.7%
Space Separator 184
 
1.1%
Uppercase Letter 139
 
0.8%
Lowercase Letter 82
 
0.5%
Open Punctuation 42
 
0.3%
Close Punctuation 42
 
0.3%
Decimal Number 41
 
0.2%
Other Punctuation 15
 
0.1%
Letter Number 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2291
 
14.4%
2217
 
14.0%
2126
 
13.4%
343
 
2.2%
299
 
1.9%
205
 
1.3%
184
 
1.2%
176
 
1.1%
160
 
1.0%
150
 
0.9%
Other values (450) 7709
48.6%
Uppercase Letter
ValueCountFrequency (%)
B 15
 
10.8%
A 12
 
8.6%
S 12
 
8.6%
R 11
 
7.9%
E 11
 
7.9%
O 9
 
6.5%
T 8
 
5.8%
M 7
 
5.0%
K 6
 
4.3%
G 6
 
4.3%
Other values (14) 42
30.2%
Lowercase Letter
ValueCountFrequency (%)
o 11
13.4%
r 10
12.2%
a 9
11.0%
s 8
9.8%
e 7
8.5%
b 7
8.5%
n 6
7.3%
h 6
7.3%
p 5
6.1%
l 3
 
3.7%
Other values (7) 10
12.2%
Decimal Number
ValueCountFrequency (%)
1 10
24.4%
8 8
19.5%
3 6
14.6%
0 6
14.6%
2 6
14.6%
4 2
 
4.9%
5 1
 
2.4%
9 1
 
2.4%
7 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 7
46.7%
' 4
26.7%
& 1
 
6.7%
, 1
 
6.7%
# 1
 
6.7%
· 1
 
6.7%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
184
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15860
96.7%
Common 325
 
2.0%
Latin 223
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2291
 
14.4%
2217
 
14.0%
2126
 
13.4%
343
 
2.2%
299
 
1.9%
205
 
1.3%
184
 
1.2%
176
 
1.1%
160
 
1.0%
150
 
0.9%
Other values (450) 7709
48.6%
Latin
ValueCountFrequency (%)
B 15
 
6.7%
A 12
 
5.4%
S 12
 
5.4%
R 11
 
4.9%
o 11
 
4.9%
E 11
 
4.9%
r 10
 
4.5%
O 9
 
4.0%
a 9
 
4.0%
T 8
 
3.6%
Other values (33) 115
51.6%
Common
ValueCountFrequency (%)
184
56.6%
( 42
 
12.9%
) 42
 
12.9%
1 10
 
3.1%
8 8
 
2.5%
. 7
 
2.2%
3 6
 
1.8%
0 6
 
1.8%
2 6
 
1.8%
' 4
 
1.2%
Other values (9) 10
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15860
96.7%
ASCII 545
 
3.3%
Number Forms 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2291
 
14.4%
2217
 
14.0%
2126
 
13.4%
343
 
2.2%
299
 
1.9%
205
 
1.3%
184
 
1.2%
176
 
1.1%
160
 
1.0%
150
 
0.9%
Other values (450) 7709
48.6%
ASCII
ValueCountFrequency (%)
184
33.8%
( 42
 
7.7%
) 42
 
7.7%
B 15
 
2.8%
A 12
 
2.2%
S 12
 
2.2%
R 11
 
2.0%
o 11
 
2.0%
E 11
 
2.0%
1 10
 
1.8%
Other values (49) 195
35.8%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

Distinct2494
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0112334 × 1013
Minimum2.0011006 × 1013
Maximum2.022123 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:21.636379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0011006 × 1013
5-th percentile2.0021011 × 1013
Q12.0040405 × 1013
median2.0110417 × 1013
Q32.0181016 × 1013
95-th percentile2.0220109 × 1013
Maximum2.022123 × 1013
Range2.102242 × 1011
Interquartile range (IQR)1.4061135 × 1011

Descriptive statistics

Standard deviation6.9523851 × 1010
Coefficient of variation (CV)0.0034567769
Kurtosis-1.487733
Mean2.0112334 × 1013
Median Absolute Deviation (MAD)7.0106453 × 1010
Skewness0.16071782
Sum6.4520366 × 1016
Variance4.8335658 × 1021
MonotonicityNot monotonic
2024-04-22T03:39:21.877210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20031031000000 39
 
1.2%
20040313000000 37
 
1.2%
20041129000000 34
 
1.1%
20020416000000 27
 
0.8%
20040312000000 25
 
0.8%
20031010000000 24
 
0.7%
20040213000000 23
 
0.7%
20021011000000 21
 
0.7%
20030731000000 17
 
0.5%
20020729000000 16
 
0.5%
Other values (2484) 2945
91.8%
ValueCountFrequency (%)
20011006000000 4
 
0.1%
20011218000000 1
 
< 0.1%
20020320000000 1
 
< 0.1%
20020330000000 1
 
< 0.1%
20020412000000 1
 
< 0.1%
20020416000000 27
0.8%
20020417000000 8
 
0.2%
20020418000000 3
 
0.1%
20020508000000 1
 
< 0.1%
20020510000000 1
 
< 0.1%
ValueCountFrequency (%)
20221230195534 1
< 0.1%
20221230155235 1
< 0.1%
20221229171441 1
< 0.1%
20221229171246 1
< 0.1%
20221229160939 1
< 0.1%
20221229105816 1
< 0.1%
20221228155004 1
< 0.1%
20221228150303 1
< 0.1%
20221228131526 1
< 0.1%
20221227133737 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
I
2435 
U
773 

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 2435
75.9%
U 773
 
24.1%

Length

2024-04-22T03:39:22.098169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:22.264209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2435
75.9%
u 773
 
24.1%
Distinct527
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-01-01 02:40:00
2024-04-22T03:39:22.446234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T03:39:22.684042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
일반이용업
3171 
이용업 기타
 
37

Length

Max length6
Median length5
Mean length5.0115337
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 3171
98.8%
이용업 기타 37
 
1.2%

Length

2024-04-22T03:39:22.917436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:23.091971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 3171
97.7%
이용업 37
 
1.1%
기타 37
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2340
Distinct (%)77.2%
Missing175
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean343047.37
Minimum327557.21
Maximum358563.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:23.282448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327557.21
5-th percentile335197.86
Q1339874.86
median342647.08
Q3346241.97
95-th percentile353059.01
Maximum358563.65
Range31006.443
Interquartile range (IQR)6367.1178

Descriptive statistics

Standard deviation4918.3851
Coefficient of variation (CV)0.014337335
Kurtosis0.46755247
Mean343047.37
Median Absolute Deviation (MAD)3100.0164
Skewness0.074835663
Sum1.0404627 × 109
Variance24190512
MonotonicityNot monotonic
2024-04-22T03:39:23.530395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
342056.356661388 10
 
0.3%
338881.747007639 8
 
0.2%
342355.950930826 8
 
0.2%
342647.084475007 7
 
0.2%
344046.261884685 7
 
0.2%
346440.105796948 6
 
0.2%
342979.501830192 6
 
0.2%
339440.669923424 6
 
0.2%
335728.273516917 6
 
0.2%
337346.64886395 6
 
0.2%
Other values (2330) 2963
92.4%
(Missing) 175
 
5.5%
ValueCountFrequency (%)
327557.206608826 1
 
< 0.1%
327693.549167456 1
 
< 0.1%
327698.913649169 1
 
< 0.1%
328243.083724349 1
 
< 0.1%
328293.623590322 3
0.1%
328337.353662064 1
 
< 0.1%
328389.300032891 1
 
< 0.1%
328440.18513358 1
 
< 0.1%
328655.490514703 1
 
< 0.1%
328965.130661119 1
 
< 0.1%
ValueCountFrequency (%)
358563.649366386 1
< 0.1%
356728.776844986 1
< 0.1%
356534.131252198 2
0.1%
356515.752177861 1
< 0.1%
356485.853105172 1
< 0.1%
356437.578420985 1
< 0.1%
356428.086600051 1
< 0.1%
356290.801263866 1
< 0.1%
356197.467672222 1
< 0.1%
356142.765211698 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2340
Distinct (%)77.2%
Missing175
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean263518.18
Minimum238769.81
Maximum278091.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:23.784410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238769.81
5-th percentile257645.01
Q1261584.47
median263732.85
Q3265693.88
95-th percentile270349.64
Maximum278091.65
Range39321.841
Interquartile range (IQR)4109.4123

Descriptive statistics

Standard deviation4202.6595
Coefficient of variation (CV)0.015948272
Kurtosis6.2955582
Mean263518.18
Median Absolute Deviation (MAD)2061.6519
Skewness-1.2672505
Sum7.9925064 × 108
Variance17662347
MonotonicityNot monotonic
2024-04-22T03:39:24.051358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
261454.668093245 10
 
0.3%
261852.136015552 8
 
0.2%
261485.129229362 8
 
0.2%
261852.098143208 7
 
0.2%
261742.707245162 7
 
0.2%
267083.375923729 6
 
0.2%
262488.906250829 6
 
0.2%
261637.957403825 6
 
0.2%
262684.165543172 6
 
0.2%
258035.007517312 6
 
0.2%
Other values (2330) 2963
92.4%
(Missing) 175
 
5.5%
ValueCountFrequency (%)
238769.812521748 3
0.1%
238810.5377739 1
 
< 0.1%
240701.340010657 1
 
< 0.1%
240715.264385673 1
 
< 0.1%
240837.868214765 1
 
< 0.1%
240992.822164019 1
 
< 0.1%
241925.497217826 1
 
< 0.1%
242247.963900382 1
 
< 0.1%
242378.729863202 1
 
< 0.1%
242604.778959053 1
 
< 0.1%
ValueCountFrequency (%)
278091.653532319 3
0.1%
277462.879247206 4
0.1%
274407.551765224 1
 
< 0.1%
274171.709713046 2
0.1%
274148.358810386 1
 
< 0.1%
273712.08248913 1
 
< 0.1%
273313.159204495 1
 
< 0.1%
273237.600006005 1
 
< 0.1%
273183.361741168 1
 
< 0.1%
273092.974880511 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
일반이용업
3171 
이용업 기타
 
37

Length

Max length6
Median length5
Mean length5.0115337
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 3171
98.8%
이용업 기타 37
 
1.2%

Length

2024-04-22T03:39:24.295444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:24.469965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 3171
97.7%
이용업 37
 
1.1%
기타 37
 
1.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)0.8%
Missing579
Missing (%)18.0%
Infinite0
Infinite (%)0.0%
Mean2.5507798
Minimum0
Maximum35
Zeros652
Zeros (%)20.3%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:24.633584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile6
Maximum35
Range35
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.5061926
Coefficient of variation (CV)0.98252016
Kurtosis36.732291
Mean2.5507798
Median Absolute Deviation (MAD)2
Skewness3.8723357
Sum6706
Variance6.2810011
MonotonicityNot monotonic
2024-04-22T03:39:24.840892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 652
20.3%
3 560
17.5%
2 524
16.3%
4 341
10.6%
5 219
 
6.8%
1 179
 
5.6%
6 58
 
1.8%
7 31
 
1.0%
9 23
 
0.7%
10 15
 
0.5%
Other values (11) 27
 
0.8%
(Missing) 579
18.0%
ValueCountFrequency (%)
0 652
20.3%
1 179
 
5.6%
2 524
16.3%
3 560
17.5%
4 341
10.6%
5 219
 
6.8%
6 58
 
1.8%
7 31
 
1.0%
8 10
 
0.3%
9 23
 
0.7%
ValueCountFrequency (%)
35 2
0.1%
31 1
 
< 0.1%
28 1
 
< 0.1%
23 1
 
< 0.1%
20 3
0.1%
19 1
 
< 0.1%
17 1
 
< 0.1%
15 3
0.1%
12 1
 
< 0.1%
11 3
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.4%
Missing942
Missing (%)29.4%
Infinite0
Infinite (%)0.0%
Mean0.5494263
Minimum0
Maximum9
Zeros1229
Zeros (%)38.3%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:25.038183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.76368002
Coefficient of variation (CV)1.389959
Kurtosis19.118588
Mean0.5494263
Median Absolute Deviation (MAD)0
Skewness3.0120491
Sum1245
Variance0.58320718
MonotonicityNot monotonic
2024-04-22T03:39:25.595213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 1229
38.3%
1 909
28.3%
2 95
 
3.0%
4 14
 
0.4%
3 9
 
0.3%
5 3
 
0.1%
6 3
 
0.1%
7 3
 
0.1%
9 1
 
< 0.1%
(Missing) 942
29.4%
ValueCountFrequency (%)
0 1229
38.3%
1 909
28.3%
2 95
 
3.0%
3 9
 
0.3%
4 14
 
0.4%
5 3
 
0.1%
6 3
 
0.1%
7 3
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
7 3
 
0.1%
6 3
 
0.1%
5 3
 
0.1%
4 14
 
0.4%
3 9
 
0.3%
2 95
 
3.0%
1 909
28.3%
0 1229
38.3%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.4%
Missing813
Missing (%)25.3%
Infinite0
Infinite (%)0.0%
Mean1.3135699
Minimum0
Maximum9
Zeros537
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:25.924156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2414299
Coefficient of variation (CV)0.94508096
Kurtosis5.7382043
Mean1.3135699
Median Absolute Deviation (MAD)1
Skewness1.8936982
Sum3146
Variance1.5411483
MonotonicityNot monotonic
2024-04-22T03:39:26.266201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 1150
35.8%
0 537
16.7%
2 374
 
11.7%
3 206
 
6.4%
4 71
 
2.2%
5 27
 
0.8%
6 12
 
0.4%
8 11
 
0.3%
7 6
 
0.2%
9 1
 
< 0.1%
(Missing) 813
25.3%
ValueCountFrequency (%)
0 537
16.7%
1 1150
35.8%
2 374
 
11.7%
3 206
 
6.4%
4 71
 
2.2%
5 27
 
0.8%
6 12
 
0.4%
7 6
 
0.2%
8 11
 
0.3%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
8 11
 
0.3%
7 6
 
0.2%
6 12
 
0.4%
5 27
 
0.8%
4 71
 
2.2%
3 206
 
6.4%
2 374
 
11.7%
1 1150
35.8%
0 537
16.7%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.4%
Missing1045
Missing (%)32.6%
Infinite0
Infinite (%)0.0%
Mean1.4378178
Minimum0
Maximum8
Zeros317
Zeros (%)9.9%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:26.595257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2162914
Coefficient of variation (CV)0.8459287
Kurtosis5.5508737
Mean1.4378178
Median Absolute Deviation (MAD)0
Skewness1.9041307
Sum3110
Variance1.4793647
MonotonicityNot monotonic
2024-04-22T03:39:26.971536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 1150
35.8%
2 371
 
11.6%
0 317
 
9.9%
3 196
 
6.1%
4 70
 
2.2%
5 30
 
0.9%
6 13
 
0.4%
8 10
 
0.3%
7 6
 
0.2%
(Missing) 1045
32.6%
ValueCountFrequency (%)
0 317
 
9.9%
1 1150
35.8%
2 371
 
11.6%
3 196
 
6.1%
4 70
 
2.2%
5 30
 
0.9%
6 13
 
0.4%
7 6
 
0.2%
8 10
 
0.3%
ValueCountFrequency (%)
8 10
 
0.3%
7 6
 
0.2%
6 13
 
0.4%
5 30
 
0.9%
4 70
 
2.2%
3 196
 
6.1%
2 371
 
11.6%
1 1150
35.8%
0 317
 
9.9%
Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
0
1615 
<NA>
1394 
1
193 
2
 
5
6
 
1

Length

Max length4
Median length1
Mean length2.303616
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 1615
50.3%
<NA> 1394
43.5%
1 193
 
6.0%
2 5
 
0.2%
6 1
 
< 0.1%

Length

2024-04-22T03:39:27.400713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:27.743876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1615
50.3%
na 1394
43.5%
1 193
 
6.0%
2 5
 
0.2%
6 1
 
< 0.1%
Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
<NA>
1701 
0
1268 
1
233 
2
 
5
6
 
1

Length

Max length4
Median length4
Mean length2.5907107
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
<NA> 1701
53.0%
0 1268
39.5%
1 233
 
7.3%
2 5
 
0.2%
6 1
 
< 0.1%

Length

2024-04-22T03:39:28.133519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:28.425246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1701
53.0%
0 1268
39.5%
1 233
 
7.3%
2 5
 
0.2%
6 1
 
< 0.1%

의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.6%
Missing349
Missing (%)10.9%
Infinite0
Infinite (%)0.0%
Mean3.4882826
Minimum0
Maximum18
Zeros165
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:28.599882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile9
Maximum18
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.5069782
Coefficient of variation (CV)0.71868551
Kurtosis1.9580231
Mean3.4882826
Median Absolute Deviation (MAD)1
Skewness1.3674534
Sum9973
Variance6.2849396
MonotonicityNot monotonic
2024-04-22T03:39:28.803134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3 747
23.3%
2 686
21.4%
4 370
11.5%
1 276
 
8.6%
0 165
 
5.1%
5 128
 
4.0%
6 106
 
3.3%
8 99
 
3.1%
7 96
 
3.0%
9 92
 
2.9%
Other values (6) 94
 
2.9%
(Missing) 349
10.9%
ValueCountFrequency (%)
0 165
 
5.1%
1 276
 
8.6%
2 686
21.4%
3 747
23.3%
4 370
11.5%
5 128
 
4.0%
6 106
 
3.3%
7 96
 
3.0%
8 99
 
3.1%
9 92
 
2.9%
ValueCountFrequency (%)
18 1
 
< 0.1%
15 2
 
0.1%
13 4
 
0.1%
12 22
 
0.7%
11 22
 
0.7%
10 43
1.3%
9 92
2.9%
8 99
3.1%
7 96
3.0%
6 106
3.3%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3208
Missing (%)100.0%
Memory size28.3 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3208
Missing (%)100.0%
Memory size28.3 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3208
Missing (%)100.0%
Memory size28.3 KiB
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
<NA>
1639 
임대
1428 
자가
 
141

Length

Max length4
Median length4
Mean length3.0218204
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1639
51.1%
임대 1428
44.5%
자가 141
 
4.4%

Length

2024-04-22T03:39:29.144980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:29.489924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1639
51.1%
임대 1428
44.5%
자가 141
 
4.4%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
<NA>
2699 
0
393 
1
 
111
2
 
4
3
 
1

Length

Max length4
Median length4
Mean length3.5240025
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2699
84.1%
0 393
 
12.3%
1 111
 
3.5%
2 4
 
0.1%
3 1
 
< 0.1%

Length

2024-04-22T03:39:29.851713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:30.185427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2699
84.1%
0 393
 
12.3%
1 111
 
3.5%
2 4
 
0.1%
3 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.2 KiB
<NA>
2596 
0
335 
1
272 
2
 
5

Length

Max length4
Median length4
Mean length3.4276808
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2596
80.9%
0 335
 
10.4%
1 272
 
8.5%
2 5
 
0.2%

Length

2024-04-22T03:39:30.563682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:39:30.894815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2596
80.9%
0 335
 
10.4%
1 272
 
8.5%
2 5
 
0.2%

침대수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.6%
Missing1778
Missing (%)55.4%
Infinite0
Infinite (%)0.0%
Mean0.055244755
Minimum0
Maximum8
Zeros1414
Zeros (%)44.1%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2024-04-22T03:39:31.208533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5847584
Coefficient of variation (CV)10.584867
Kurtosis134.10885
Mean0.055244755
Median Absolute Deviation (MAD)0
Skewness11.452449
Sum79
Variance0.34194238
MonotonicityNot monotonic
2024-04-22T03:39:31.578104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1414
44.1%
7 5
 
0.2%
2 3
 
0.1%
8 2
 
0.1%
1 2
 
0.1%
6 2
 
0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 1778
55.4%
ValueCountFrequency (%)
0 1414
44.1%
1 2
 
0.1%
2 3
 
0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
6 2
 
0.1%
7 5
 
0.2%
8 2
 
0.1%
ValueCountFrequency (%)
8 2
 
0.1%
7 5
 
0.2%
6 2
 
0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
2 3
 
0.1%
1 2
 
0.1%
0 1414
44.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
False
3207 
True
 
1
ValueCountFrequency (%)
False 3207
> 99.9%
True 1
 
< 0.1%
2024-04-22T03:39:31.923064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수침대수다중이용업소여부
01이용업05_19_01_P34100003410000-203-2010-0000220100414<NA>3폐업2폐업20170405<NA><NA><NA><NA>6.45700412대구광역시 중구 삼덕동2가 0210-0001번지 지하1층대구광역시 중구 동덕로 115 (삼덕동2가, 지하1층)41940진석이용소20170405162201I2018-08-31 23:59:59.0일반이용업344686.259338263958.880864일반이용업20100111<NA><NA><NA>임대<NA>10N
12이용업05_19_01_P34100003410000-203-2008-0000320080604<NA>3폐업2폐업20100809<NA><NA><NA><NA>9.36700261대구광역시 중구 서성로1가 0109-0001번지 (2층)<NA><NA>삼정이용소20100614144140I2018-08-31 23:59:59.0일반이용업343315.940921264622.218272일반이용업5122001<NA><NA><NA><NA><NA><NA><NA>N
23이용업05_19_01_P34100003410000-203-2010-0000320101020<NA>3폐업2폐업20130122<NA><NA><NA><NA>12.60700848대구광역시 중구 동인동4가 0347-0001번지대구광역시 중구 국채보상로 723 (동인동4가)41907육교이용소20120208113538I2018-08-31 23:59:59.0일반이용업345308.284791264380.077089일반이용업0011001<NA><NA><NA>임대<NA><NA>0N
34이용업05_19_01_P34100003410000-203-2010-0000420101025<NA>3폐업2폐업20101215<NA><NA><NA><NA>6.20700802대구광역시 중구 남산동 0693-0008번지 지상2층<NA><NA>아미가20101028091811I2018-08-31 23:59:59.0일반이용업343879.713037263432.678243일반이용업0022002<NA><NA><NA>임대<NA><NA>0N
45이용업05_19_01_P34100003410000-203-2001-0000120010326<NA>3폐업2폐업20110120<NA><NA><NA>053 257295539.60700850대구광역시 중구 수창동 0099-0002번지<NA><NA>월드20101026121254I2018-08-31 23:59:59.0일반이용업343287.506361264938.059384일반이용업31<NA><NA>118<NA><NA><NA><NA><NA><NA><NA>N
56이용업05_19_01_P34100003410000-203-2010-0000520101124<NA>3폐업2폐업20120726<NA><NA><NA><NA>56.10700320대구광역시 중구 대신동 0115-0005번지 지상2층대구광역시 중구 국채보상로 458, 2층 (대신동)41926서남이용소20120208113611I2018-08-31 23:59:59.0일반이용업342714.834681264487.841783일반이용업9022007<NA><NA><NA><NA><NA><NA>0N
67이용업05_19_01_P34100003410000-203-1982-0000419820818<NA>3폐업2폐업20090817<NA><NA><NA>053 253603731.32700832대구광역시 중구 남산동 698-22번지<NA><NA>20081021113237I2018-08-31 23:59:59.0일반이용업343722.34105263487.941195일반이용업<NA><NA><NA><NA><NA><NA>7<NA><NA><NA><NA><NA><NA><NA>N
78이용업05_19_01_P34100003410000-203-2008-0000520080918<NA>3폐업2폐업20101015<NA><NA><NA><NA>4.32700821대구광역시 중구 동산동 0360번지 지하1층<NA><NA>엘디스리젠트20090310140131I2018-08-31 23:59:59.0일반이용업343184.151781264080.683793일반이용업8100111<NA><NA><NA>임대<NA><NA><NA>N
89이용업05_19_01_P34100003410000-203-2004-0000420040630<NA>3폐업2폐업20140410<NA><NA><NA>053 4233939102.00700030대구광역시 중구 전동 0035번지대구광역시 중구 국채보상로 570-8 (전동)41935새중앙20120208112755I2018-08-31 23:59:59.0일반이용업343774.488375264525.318535일반이용업0000115<NA><NA><NA><NA><NA><NA>0N
910이용업05_19_01_P34100003410000-203-2009-0000320090811<NA>3폐업2폐업20090928<NA><NA><NA><NA>6.00700810대구광역시 중구 대봉동 0044-0010번지 청운상가 305호<NA><NA>코스팜코리아20090812171018I2018-08-31 23:59:59.0일반이용업344728.621174263286.553667일반이용업3133001<NA><NA><NA><NA><NA>10N
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수침대수다중이용업소여부
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