Overview

Dataset statistics

Number of variables47
Number of observations2951
Missing cells30493
Missing cells (%)22.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory405.0 B

Variable types

Numeric12
Categorical19
Text6
Unsupported8
DateTime1
Boolean1

Dataset

Description22년05월_6270000_대구광역시_07_22_18_P_제과점영업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000093418&dataSetDetailId=DDI_0000093469&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 is highly imbalanced (99.2%)Imbalance
위생업태명 is highly imbalanced (99.2%)Imbalance
급수시설구분명 is highly imbalanced (60.4%)Imbalance
다중이용업소여부 is highly imbalanced (89.6%)Imbalance
인허가취소일자 has 2951 (100.0%) missing valuesMissing
폐업일자 has 970 (32.9%) missing valuesMissing
휴업시작일자 has 2951 (100.0%) missing valuesMissing
휴업종료일자 has 2951 (100.0%) missing valuesMissing
재개업일자 has 2951 (100.0%) missing valuesMissing
소재지전화 has 1234 (41.8%) missing valuesMissing
소재지면적 has 104 (3.5%) missing valuesMissing
소재지우편번호 has 31 (1.1%) missing valuesMissing
도로명전체주소 has 830 (28.1%) missing valuesMissing
도로명우편번호 has 848 (28.7%) missing valuesMissing
좌표정보(X) has 80 (2.7%) missing valuesMissing
좌표정보(Y) has 80 (2.7%) missing valuesMissing
남성종사자수 has 1394 (47.2%) missing valuesMissing
여성종사자수 has 1314 (44.5%) missing valuesMissing
건물소유구분명 has 2951 (100.0%) missing valuesMissing
전통업소지정번호 has 2951 (100.0%) missing valuesMissing
전통업소주된음식 has 2951 (100.0%) missing valuesMissing
홈페이지 has 2951 (100.0%) 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
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 1101 (37.3%) zerosZeros
여성종사자수 has 1059 (35.9%) zerosZeros
시설총규모 has 136 (4.6%) zerosZeros

Reproduction

Analysis started2023-12-10 18:15:55.506890
Analysis finished2023-12-10 18:15:57.438135
Duration1.93 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct2951
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1476
Minimum1
Maximum2951
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:15:57.541107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile148.5
Q1738.5
median1476
Q32213.5
95-th percentile2803.5
Maximum2951
Range2950
Interquartile range (IQR)1475

Descriptive statistics

Standard deviation852.02465
Coefficient of variation (CV)0.57725247
Kurtosis-1.2
Mean1476
Median Absolute Deviation (MAD)738
Skewness0
Sum4355676
Variance725946
MonotonicityStrictly increasing
2023-12-11T03:15:57.720117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1972 1
 
< 0.1%
1963 1
 
< 0.1%
1964 1
 
< 0.1%
1965 1
 
< 0.1%
1966 1
 
< 0.1%
1967 1
 
< 0.1%
1968 1
 
< 0.1%
1969 1
 
< 0.1%
1970 1
 
< 0.1%
Other values (2941) 2941
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 (%)
2951 1
< 0.1%
2950 1
< 0.1%
2949 1
< 0.1%
2948 1
< 0.1%
2947 1
< 0.1%
2946 1
< 0.1%
2945 1
< 0.1%
2944 1
< 0.1%
2943 1
< 0.1%
2942 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
제과점영업
2951 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 2951
100.0%

Length

2023-12-11T03:15:58.082282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:15:58.214402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 2951
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
07_22_18_P
2951 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_18_P
2nd row07_22_18_P
3rd row07_22_18_P
4th row07_22_18_P
5th row07_22_18_P

Common Values

ValueCountFrequency (%)
07_22_18_P 2951
100.0%

Length

2023-12-11T03:15:58.337073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:15:58.459342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_18_p 2951
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447275.5
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:15:58.570306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation22026.91
Coefficient of variation (CV)0.0063896575
Kurtosis-1.121823
Mean3447275.5
Median Absolute Deviation (MAD)20000
Skewness-0.39102934
Sum1.017291 × 1010
Variance4.8518475 × 108
MonotonicityIncreasing
2023-12-11T03:15:58.740573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 585
19.8%
3460000 541
18.3%
3450000 529
17.9%
3410000 367
12.4%
3420000 338
11.5%
3430000 206
 
7.0%
3440000 194
 
6.6%
3480000 191
 
6.5%
ValueCountFrequency (%)
3410000 367
12.4%
3420000 338
11.5%
3430000 206
 
7.0%
3440000 194
 
6.6%
3450000 529
17.9%
3460000 541
18.3%
3470000 585
19.8%
3480000 191
 
6.5%
ValueCountFrequency (%)
3480000 191
 
6.5%
3470000 585
19.8%
3460000 541
18.3%
3450000 529
17.9%
3440000 194
 
6.6%
3430000 206
 
7.0%
3420000 338
11.5%
3410000 367
12.4%

관리번호
Text

UNIQUE 

Distinct2951
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
2023-12-11T03:15:59.026957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters64922
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

Unique2951 ?
Unique (%)100.0%

Sample

1st row3410000-121-2016-00010
2nd row3410000-121-2016-00011
3rd row3410000-121-2016-00013
4th row3410000-121-2016-00015
5th row3410000-121-2016-00016
ValueCountFrequency (%)
3410000-121-2016-00010 1
 
< 0.1%
3460000-121-2015-00002 1
 
< 0.1%
3460000-121-2011-00018 1
 
< 0.1%
3460000-121-2014-00008 1
 
< 0.1%
3460000-121-2014-00009 1
 
< 0.1%
3460000-121-2014-00010 1
 
< 0.1%
3460000-121-2014-00012 1
 
< 0.1%
3460000-121-2014-00014 1
 
< 0.1%
3460000-121-2014-00015 1
 
< 0.1%
3460000-121-2012-00016 1
 
< 0.1%
Other values (2941) 2941
99.7%
2023-12-11T03:15:59.459798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26148
40.3%
1 9548
 
14.7%
- 8853
 
13.6%
2 7330
 
11.3%
3 3880
 
6.0%
4 3792
 
5.8%
7 1195
 
1.8%
6 1150
 
1.8%
5 1144
 
1.8%
9 1057
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56069
86.4%
Dash Punctuation 8853
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26148
46.6%
1 9548
 
17.0%
2 7330
 
13.1%
3 3880
 
6.9%
4 3792
 
6.8%
7 1195
 
2.1%
6 1150
 
2.1%
5 1144
 
2.0%
9 1057
 
1.9%
8 825
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 8853
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64922
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26148
40.3%
1 9548
 
14.7%
- 8853
 
13.6%
2 7330
 
11.3%
3 3880
 
6.0%
4 3792
 
5.8%
7 1195
 
1.8%
6 1150
 
1.8%
5 1144
 
1.8%
9 1057
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64922
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26148
40.3%
1 9548
 
14.7%
- 8853
 
13.6%
2 7330
 
11.3%
3 3880
 
6.0%
4 3792
 
5.8%
7 1195
 
1.8%
6 1150
 
1.8%
5 1144
 
1.8%
9 1057
 
1.6%

인허가일자
Real number (ℝ)

Distinct2314
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20096090
Minimum19790328
Maximum20220527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:15:59.685620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19790328
5-th percentile19950224
Q120040728
median20101011
Q320161019
95-th percentile20210602
Maximum20220527
Range430199
Interquartile range (IQR)120291.5

Descriptive statistics

Standard deviation81674.741
Coefficient of variation (CV)0.0040642106
Kurtosis0.26584933
Mean20096090
Median Absolute Deviation (MAD)60105
Skewness-0.67772704
Sum5.9303561 × 1010
Variance6.6707633 × 109
MonotonicityNot monotonic
2023-12-11T03:15:59.919985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161206 7
 
0.2%
19940217 7
 
0.2%
20110802 6
 
0.2%
20161212 5
 
0.2%
20170223 4
 
0.1%
19930907 4
 
0.1%
19931030 4
 
0.1%
20070912 4
 
0.1%
20180119 4
 
0.1%
20080317 4
 
0.1%
Other values (2304) 2902
98.3%
ValueCountFrequency (%)
19790328 1
< 0.1%
19800612 1
< 0.1%
19801024 1
< 0.1%
19801114 1
< 0.1%
19810114 1
< 0.1%
19810720 1
< 0.1%
19810905 1
< 0.1%
19810914 1
< 0.1%
19811007 1
< 0.1%
19811008 1
< 0.1%
ValueCountFrequency (%)
20220527 1
< 0.1%
20220523 2
0.1%
20220520 1
< 0.1%
20220519 2
0.1%
20220518 1
< 0.1%
20220517 1
< 0.1%
20220516 1
< 0.1%
20220510 1
< 0.1%
20220509 2
0.1%
20220502 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2951
Missing (%)100.0%
Memory size26.1 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
3
1981 
1
970 

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 1981
67.1%
1 970
32.9%

Length

2023-12-11T03:16:00.087813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:00.206645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1981
67.1%
1 970
32.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
폐업
1981 
영업/정상
970 

Length

Max length5
Median length2
Mean length2.9861064
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1981
67.1%
영업/정상 970
32.9%

Length

2023-12-11T03:16:00.350899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:00.492932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1981
67.1%
영업/정상 970
32.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
2
1981 
1
970 

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 1981
67.1%
1 970
32.9%

Length

2023-12-11T03:16:00.649521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:00.796821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1981
67.1%
1 970
32.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
폐업
1981 
영업
970 

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 1981
67.1%
영업 970
32.9%

Length

2023-12-11T03:16:00.963002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:01.131427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1981
67.1%
영업 970
32.9%

폐업일자
Real number (ℝ)

MISSING 

Distinct1468
Distinct (%)74.1%
Missing970
Missing (%)32.9%
Infinite0
Infinite (%)0.0%
Mean20133675
Minimum20020319
Maximum20220523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:16:01.314923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020319
5-th percentile20051129
Q120090430
median20131227
Q320180328
95-th percentile20210927
Maximum20220523
Range200204
Interquartile range (IQR)89898

Descriptive statistics

Standard deviation51967.24
Coefficient of variation (CV)0.0025811104
Kurtosis-1.1886907
Mean20133675
Median Absolute Deviation (MAD)41115
Skewness-0.088213801
Sum3.9884811 × 1010
Variance2.700594 × 109
MonotonicityNot monotonic
2023-12-11T03:16:01.588894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211031 10
 
0.3%
20051111 7
 
0.2%
20180207 7
 
0.2%
20190108 6
 
0.2%
20130129 6
 
0.2%
20050125 5
 
0.2%
20141231 5
 
0.2%
20220518 5
 
0.2%
20220120 5
 
0.2%
20171226 4
 
0.1%
Other values (1458) 1921
65.1%
(Missing) 970
32.9%
ValueCountFrequency (%)
20020319 1
< 0.1%
20020423 1
< 0.1%
20020611 2
0.1%
20020704 1
< 0.1%
20021017 1
< 0.1%
20030228 1
< 0.1%
20030304 2
0.1%
20030408 1
< 0.1%
20030522 1
< 0.1%
20030616 1
< 0.1%
ValueCountFrequency (%)
20220523 1
 
< 0.1%
20220520 3
0.1%
20220518 5
0.2%
20220517 2
 
0.1%
20220513 2
 
0.1%
20220512 1
 
< 0.1%
20220503 2
 
0.1%
20220428 1
 
< 0.1%
20220425 1
 
< 0.1%
20220422 1
 
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2951
Missing (%)100.0%
Memory size26.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2951
Missing (%)100.0%
Memory size26.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2951
Missing (%)100.0%
Memory size26.1 KiB

소재지전화
Text

MISSING 

Distinct1607
Distinct (%)93.6%
Missing1234
Missing (%)41.8%
Memory size23.2 KiB
2023-12-11T03:16:02.176476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.728014
Min length3

Characters and Unicode

Total characters18420
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

Unique1525 ?
Unique (%)88.8%

Sample

1st row053 4248747
2nd row053 4242025
3rd row053 4310300
4th row053957 3977
5th row053 4287710
ValueCountFrequency (%)
053 1365
36.5%
070 23
 
0.6%
793 11
 
0.3%
741 11
 
0.3%
311 10
 
0.3%
2452901 10
 
0.3%
639 9
 
0.2%
380 9
 
0.2%
794 9
 
0.2%
642 8
 
0.2%
Other values (1716) 2275
60.8%
2023-12-11T03:16:02.999687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2967
16.1%
0 2628
14.3%
3 2600
14.1%
2049
11.1%
2 1479
8.0%
6 1326
7.2%
7 1205
6.5%
4 1138
 
6.2%
1 1093
 
5.9%
8 1029
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16371
88.9%
Space Separator 2049
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2967
18.1%
0 2628
16.1%
3 2600
15.9%
2 1479
9.0%
6 1326
8.1%
7 1205
7.4%
4 1138
 
7.0%
1 1093
 
6.7%
8 1029
 
6.3%
9 906
 
5.5%
Space Separator
ValueCountFrequency (%)
2049
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2967
16.1%
0 2628
14.3%
3 2600
14.1%
2049
11.1%
2 1479
8.0%
6 1326
7.2%
7 1205
6.5%
4 1138
 
6.2%
1 1093
 
5.9%
8 1029
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2967
16.1%
0 2628
14.3%
3 2600
14.1%
2049
11.1%
2 1479
8.0%
6 1326
7.2%
7 1205
6.5%
4 1138
 
6.2%
1 1093
 
5.9%
8 1029
 
5.6%

소재지면적
Text

MISSING 

Distinct1861
Distinct (%)65.4%
Missing104
Missing (%)3.5%
Memory size23.2 KiB
2023-12-11T03:16:03.624839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9683878
Min length3

Characters and Unicode

Total characters14145
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

Unique1411 ?
Unique (%)49.6%

Sample

1st row25.92
2nd row32.55
3rd row41.70
4th row69.42
5th row33.64
ValueCountFrequency (%)
00 61
 
2.1%
33.00 20
 
0.7%
20.00 18
 
0.6%
36.00 15
 
0.5%
26.40 14
 
0.5%
30.00 14
 
0.5%
3.30 13
 
0.5%
40.00 12
 
0.4%
27.00 11
 
0.4%
19.80 11
 
0.4%
Other values (1851) 2658
93.4%
2023-12-11T03:16:04.401703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 2847
20.1%
0 2326
16.4%
2 1428
10.1%
3 1190
8.4%
4 1138
 
8.0%
5 1003
 
7.1%
1 1000
 
7.1%
6 938
 
6.6%
8 824
 
5.8%
7 732
 
5.2%
Other values (2) 719
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11297
79.9%
Other Punctuation 2848
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2326
20.6%
2 1428
12.6%
3 1190
10.5%
4 1138
10.1%
5 1003
8.9%
1 1000
8.9%
6 938
8.3%
8 824
 
7.3%
7 732
 
6.5%
9 718
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 2847
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14145
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2847
20.1%
0 2326
16.4%
2 1428
10.1%
3 1190
8.4%
4 1138
 
8.0%
5 1003
 
7.1%
1 1000
 
7.1%
6 938
 
6.6%
8 824
 
5.8%
7 732
 
5.2%
Other values (2) 719
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14145
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2847
20.1%
0 2326
16.4%
2 1428
10.1%
3 1190
8.4%
4 1138
 
8.0%
5 1003
 
7.1%
1 1000
 
7.1%
6 938
 
6.6%
8 824
 
5.8%
7 732
 
5.2%
Other values (2) 719
 
5.1%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct509
Distinct (%)17.4%
Missing31
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean704243.39
Minimum700010
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:16:04.680138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700150
Q1702040
median704080
Q3705832
95-th percentile711812
Maximum711891
Range11881
Interquartile range (IQR)3792

Descriptive statistics

Standard deviation2746.2787
Coefficient of variation (CV)0.0038996159
Kurtosis0.9467696
Mean704243.39
Median Absolute Deviation (MAD)1770
Skewness0.82487932
Sum2.0563907 × 109
Variance7542046.6
MonotonicityNot monotonic
2023-12-11T03:16:04.941777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
700082 74
 
2.5%
706170 42
 
1.4%
702886 40
 
1.4%
704834 28
 
0.9%
706803 28
 
0.9%
702040 26
 
0.9%
702845 25
 
0.8%
700092 25
 
0.8%
700718 24
 
0.8%
711815 23
 
0.8%
Other values (499) 2585
87.6%
(Missing) 31
 
1.1%
ValueCountFrequency (%)
700010 1
 
< 0.1%
700040 3
 
0.1%
700060 8
 
0.3%
700070 18
 
0.6%
700082 74
2.5%
700092 25
 
0.8%
700093 13
 
0.4%
700100 1
 
< 0.1%
700111 1
 
< 0.1%
700150 15
 
0.5%
ValueCountFrequency (%)
711891 6
 
0.2%
711874 5
 
0.2%
711873 1
 
< 0.1%
711872 1
 
< 0.1%
711864 3
 
0.1%
711863 4
 
0.1%
711862 1
 
< 0.1%
711852 20
0.7%
711845 1
 
< 0.1%
711843 2
 
0.1%
Distinct2640
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
2023-12-11T03:16:05.545558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length26.613351
Min length16

Characters and Unicode

Total characters78536
Distinct characters375
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

Unique2472 ?
Unique (%)83.8%

Sample

1st row대구광역시 중구 남일동 0094-0001번지 지상1층
2nd row대구광역시 중구 봉산동 0037-0015 지상1층
3rd row대구광역시 중구 봉산동 0033-0001번지 지상1층
4th row대구광역시 중구 동인동4가 0247-0005번지 지상1층
5th row대구광역시 중구 대봉동 0632-0002번지 지상1층
ValueCountFrequency (%)
대구광역시 2953
 
20.4%
달서구 585
 
4.0%
수성구 541
 
3.7%
북구 529
 
3.7%
중구 367
 
2.5%
동구 338
 
2.3%
서구 206
 
1.4%
남구 194
 
1.3%
달성군 191
 
1.3%
1층 189
 
1.3%
Other values (3325) 8400
58.0%
2023-12-11T03:16:06.439290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14225
18.1%
5858
 
7.5%
1 4220
 
5.4%
3605
 
4.6%
3454
 
4.4%
0 3194
 
4.1%
3038
 
3.9%
2984
 
3.8%
2966
 
3.8%
2946
 
3.8%
Other values (365) 32046
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44076
56.1%
Decimal Number 17256
 
22.0%
Space Separator 14225
 
18.1%
Dash Punctuation 2177
 
2.8%
Open Punctuation 256
 
0.3%
Close Punctuation 256
 
0.3%
Other Punctuation 146
 
0.2%
Uppercase Letter 127
 
0.2%
Math Symbol 11
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5858
 
13.3%
3605
 
8.2%
3454
 
7.8%
3038
 
6.9%
2984
 
6.8%
2966
 
6.7%
2946
 
6.7%
2265
 
5.1%
1141
 
2.6%
915
 
2.1%
Other values (326) 14904
33.8%
Uppercase Letter
ValueCountFrequency (%)
A 47
37.0%
B 21
16.5%
C 16
 
12.6%
S 7
 
5.5%
T 6
 
4.7%
M 6
 
4.7%
K 5
 
3.9%
P 4
 
3.1%
D 4
 
3.1%
E 2
 
1.6%
Other values (6) 9
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 4220
24.5%
0 3194
18.5%
2 2059
11.9%
3 1453
 
8.4%
5 1245
 
7.2%
4 1211
 
7.0%
6 1088
 
6.3%
8 974
 
5.6%
7 914
 
5.3%
9 898
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 110
75.3%
. 21
 
14.4%
/ 13
 
8.9%
@ 2
 
1.4%
Math Symbol
ValueCountFrequency (%)
~ 8
72.7%
+ 2
 
18.2%
1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 5
83.3%
c 1
 
16.7%
Space Separator
ValueCountFrequency (%)
14225
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2177
100.0%
Open Punctuation
ValueCountFrequency (%)
( 256
100.0%
Close Punctuation
ValueCountFrequency (%)
) 256
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44076
56.1%
Common 34327
43.7%
Latin 133
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5858
 
13.3%
3605
 
8.2%
3454
 
7.8%
3038
 
6.9%
2984
 
6.8%
2966
 
6.7%
2946
 
6.7%
2265
 
5.1%
1141
 
2.6%
915
 
2.1%
Other values (326) 14904
33.8%
Common
ValueCountFrequency (%)
14225
41.4%
1 4220
 
12.3%
0 3194
 
9.3%
- 2177
 
6.3%
2 2059
 
6.0%
3 1453
 
4.2%
5 1245
 
3.6%
4 1211
 
3.5%
6 1088
 
3.2%
8 974
 
2.8%
Other values (11) 2481
 
7.2%
Latin
ValueCountFrequency (%)
A 47
35.3%
B 21
15.8%
C 16
 
12.0%
S 7
 
5.3%
T 6
 
4.5%
M 6
 
4.5%
e 5
 
3.8%
K 5
 
3.8%
P 4
 
3.0%
D 4
 
3.0%
Other values (8) 12
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44075
56.1%
ASCII 34459
43.9%
Compat Jamo 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14225
41.3%
1 4220
 
12.2%
0 3194
 
9.3%
- 2177
 
6.3%
2 2059
 
6.0%
3 1453
 
4.2%
5 1245
 
3.6%
4 1211
 
3.5%
6 1088
 
3.2%
8 974
 
2.8%
Other values (28) 2613
 
7.6%
Hangul
ValueCountFrequency (%)
5858
 
13.3%
3605
 
8.2%
3454
 
7.8%
3038
 
6.9%
2984
 
6.8%
2966
 
6.7%
2946
 
6.7%
2265
 
5.1%
1141
 
2.6%
915
 
2.1%
Other values (325) 14903
33.8%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Arrows
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1958
Distinct (%)92.3%
Missing830
Missing (%)28.1%
Memory size23.2 KiB
2023-12-11T03:16:07.087667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length52
Mean length31.595002
Min length20

Characters and Unicode

Total characters67013
Distinct characters399
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1888 ?
Unique (%)89.0%

Sample

1st row대구광역시 중구 중앙대로 406-14 (남일동, 지상1층)
2nd row대구광역시 중구 동성로1길 46-26 (봉산동, 지상1층)
3rd row대구광역시 중구 동성로1길 47 (봉산동, 지상1층)
4th row대구광역시 중구 동덕로30길 63-4 (동인동4가, 지상1층)
5th row대구광역시 중구 명덕로 243 (대봉동, 지상1층)
ValueCountFrequency (%)
대구광역시 2122
 
16.0%
1층 667
 
5.0%
달서구 442
 
3.3%
북구 386
 
2.9%
수성구 363
 
2.7%
중구 282
 
2.1%
동구 253
 
1.9%
달구벌대로 179
 
1.3%
달성군 149
 
1.1%
남구 139
 
1.0%
Other values (2277) 8278
62.4%
2023-12-11T03:16:08.051734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11139
 
16.6%
4576
 
6.8%
1 3297
 
4.9%
3055
 
4.6%
3026
 
4.5%
2213
 
3.3%
2179
 
3.3%
2133
 
3.2%
2111
 
3.2%
) 2109
 
3.1%
Other values (389) 31175
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38674
57.7%
Space Separator 11139
 
16.6%
Decimal Number 10590
 
15.8%
Close Punctuation 2109
 
3.1%
Open Punctuation 2109
 
3.1%
Other Punctuation 1987
 
3.0%
Dash Punctuation 250
 
0.4%
Uppercase Letter 114
 
0.2%
Lowercase Letter 24
 
< 0.1%
Math Symbol 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4576
 
11.8%
3055
 
7.9%
3026
 
7.8%
2213
 
5.7%
2179
 
5.6%
2133
 
5.5%
2111
 
5.5%
1127
 
2.9%
958
 
2.5%
885
 
2.3%
Other values (340) 16411
42.4%
Uppercase Letter
ValueCountFrequency (%)
A 34
29.8%
B 19
16.7%
C 12
 
10.5%
M 8
 
7.0%
S 7
 
6.1%
H 5
 
4.4%
D 5
 
4.4%
K 4
 
3.5%
L 3
 
2.6%
T 3
 
2.6%
Other values (8) 14
12.3%
Lowercase Letter
ValueCountFrequency (%)
e 8
33.3%
c 3
 
12.5%
a 3
 
12.5%
i 2
 
8.3%
m 1
 
4.2%
d 1
 
4.2%
l 1
 
4.2%
t 1
 
4.2%
o 1
 
4.2%
w 1
 
4.2%
Other values (2) 2
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 3297
31.1%
2 1462
13.8%
0 1210
 
11.4%
3 958
 
9.0%
4 770
 
7.3%
5 717
 
6.8%
6 637
 
6.0%
7 619
 
5.8%
9 469
 
4.4%
8 451
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 1975
99.4%
. 9
 
0.5%
/ 3
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 14
82.4%
+ 3
 
17.6%
Space Separator
ValueCountFrequency (%)
11139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 250
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38674
57.7%
Common 28201
42.1%
Latin 138
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4576
 
11.8%
3055
 
7.9%
3026
 
7.8%
2213
 
5.7%
2179
 
5.6%
2133
 
5.5%
2111
 
5.5%
1127
 
2.9%
958
 
2.5%
885
 
2.3%
Other values (340) 16411
42.4%
Latin
ValueCountFrequency (%)
A 34
24.6%
B 19
13.8%
C 12
 
8.7%
e 8
 
5.8%
M 8
 
5.8%
S 7
 
5.1%
H 5
 
3.6%
D 5
 
3.6%
K 4
 
2.9%
c 3
 
2.2%
Other values (20) 33
23.9%
Common
ValueCountFrequency (%)
11139
39.5%
1 3297
 
11.7%
) 2109
 
7.5%
( 2109
 
7.5%
, 1975
 
7.0%
2 1462
 
5.2%
0 1210
 
4.3%
3 958
 
3.4%
4 770
 
2.7%
5 717
 
2.5%
Other values (9) 2455
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38674
57.7%
ASCII 28339
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11139
39.3%
1 3297
 
11.6%
) 2109
 
7.4%
( 2109
 
7.4%
, 1975
 
7.0%
2 1462
 
5.2%
0 1210
 
4.3%
3 958
 
3.4%
4 770
 
2.7%
5 717
 
2.5%
Other values (39) 2593
 
9.1%
Hangul
ValueCountFrequency (%)
4576
 
11.8%
3055
 
7.9%
3026
 
7.8%
2213
 
5.7%
2179
 
5.6%
2133
 
5.5%
2111
 
5.5%
1127
 
2.9%
958
 
2.5%
885
 
2.3%
Other values (340) 16411
42.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct771
Distinct (%)36.7%
Missing848
Missing (%)28.7%
Infinite0
Infinite (%)0.0%
Mean42063.642
Minimum41002
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:16:08.324005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41002
5-th percentile41143
Q141559
median42025
Q342627
95-th percentile42925
Maximum43024
Range2022
Interquartile range (IQR)1068

Descriptive statistics

Standard deviation570.26919
Coefficient of variation (CV)0.013557295
Kurtosis-1.1477188
Mean42063.642
Median Absolute Deviation (MAD)506
Skewness-0.050989797
Sum88459840
Variance325206.95
MonotonicityNot monotonic
2023-12-11T03:16:08.590328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41936 75
 
2.5%
41229 45
 
1.5%
41581 22
 
0.7%
41953 21
 
0.7%
41423 18
 
0.6%
41938 17
 
0.6%
41942 16
 
0.5%
41515 14
 
0.5%
42760 13
 
0.4%
41422 13
 
0.4%
Other values (761) 1849
62.7%
(Missing) 848
28.7%
ValueCountFrequency (%)
41002 3
0.1%
41003 2
 
0.1%
41005 3
0.1%
41007 2
 
0.1%
41009 1
 
< 0.1%
41020 1
 
< 0.1%
41026 7
0.2%
41027 1
 
< 0.1%
41029 1
 
< 0.1%
41030 1
 
< 0.1%
ValueCountFrequency (%)
43024 1
 
< 0.1%
43018 11
0.4%
43017 5
0.2%
43014 5
0.2%
43009 2
 
0.1%
43008 3
 
0.1%
43005 2
 
0.1%
43004 1
 
< 0.1%
43003 3
 
0.1%
42999 1
 
< 0.1%
Distinct2325
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
2023-12-11T03:16:09.048001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length31
Mean length7.4822094
Min length1

Characters and Unicode

Total characters22080
Distinct characters677
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2028 ?
Unique (%)68.7%

Sample

1st row키세키
2nd row빠다롤뺑프랑스
3rd row요고타르트
4th row빵장수꽈배기 동인지점
5th row모모
ValueCountFrequency (%)
파리바게뜨 81
 
2.3%
베이커리 64
 
1.8%
뚜레쥬르 55
 
1.6%
마들렌베이커리 23
 
0.7%
크라운베이커리 22
 
0.6%
반월당고로케 20
 
0.6%
빵굽는마을 17
 
0.5%
대백베이커리 17
 
0.5%
뉴욕베이커리 17
 
0.5%
잇브레드 13
 
0.4%
Other values (2435) 3208
90.7%
2023-12-11T03:16:09.940012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1166
 
5.3%
978
 
4.4%
915
 
4.1%
760
 
3.4%
711
 
3.2%
587
 
2.7%
405
 
1.8%
374
 
1.7%
) 372
 
1.7%
( 371
 
1.7%
Other values (667) 15441
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19428
88.0%
Lowercase Letter 590
 
2.7%
Space Separator 587
 
2.7%
Uppercase Letter 527
 
2.4%
Close Punctuation 372
 
1.7%
Open Punctuation 371
 
1.7%
Decimal Number 168
 
0.8%
Other Punctuation 29
 
0.1%
Dash Punctuation 6
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1166
 
6.0%
978
 
5.0%
915
 
4.7%
760
 
3.9%
711
 
3.7%
405
 
2.1%
374
 
1.9%
339
 
1.7%
317
 
1.6%
294
 
1.5%
Other values (597) 13169
67.8%
Lowercase Letter
ValueCountFrequency (%)
e 90
15.3%
a 66
11.2%
o 60
 
10.2%
n 40
 
6.8%
i 39
 
6.6%
r 35
 
5.9%
k 29
 
4.9%
s 27
 
4.6%
c 25
 
4.2%
t 23
 
3.9%
Other values (15) 156
26.4%
Uppercase Letter
ValueCountFrequency (%)
B 49
 
9.3%
E 49
 
9.3%
A 46
 
8.7%
K 41
 
7.8%
R 40
 
7.6%
O 39
 
7.4%
M 28
 
5.3%
N 27
 
5.1%
S 25
 
4.7%
C 24
 
4.6%
Other values (14) 159
30.2%
Decimal Number
ValueCountFrequency (%)
2 46
27.4%
1 36
21.4%
3 21
12.5%
0 16
 
9.5%
5 13
 
7.7%
6 9
 
5.4%
9 9
 
5.4%
7 7
 
4.2%
8 6
 
3.6%
4 5
 
3.0%
Other Punctuation
ValueCountFrequency (%)
& 10
34.5%
. 9
31.0%
, 4
 
13.8%
: 3
 
10.3%
' 3
 
10.3%
Space Separator
ValueCountFrequency (%)
587
100.0%
Close Punctuation
ValueCountFrequency (%)
) 372
100.0%
Open Punctuation
ValueCountFrequency (%)
( 371
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19420
88.0%
Common 1534
 
6.9%
Latin 1118
 
5.1%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1166
 
6.0%
978
 
5.0%
915
 
4.7%
760
 
3.9%
711
 
3.7%
405
 
2.1%
374
 
1.9%
339
 
1.7%
317
 
1.6%
294
 
1.5%
Other values (590) 13161
67.8%
Latin
ValueCountFrequency (%)
e 90
 
8.1%
a 66
 
5.9%
o 60
 
5.4%
B 49
 
4.4%
E 49
 
4.4%
A 46
 
4.1%
K 41
 
3.7%
R 40
 
3.6%
n 40
 
3.6%
i 39
 
3.5%
Other values (40) 598
53.5%
Common
ValueCountFrequency (%)
587
38.3%
) 372
24.3%
( 371
24.2%
2 46
 
3.0%
1 36
 
2.3%
3 21
 
1.4%
0 16
 
1.0%
5 13
 
0.8%
& 10
 
0.7%
6 9
 
0.6%
Other values (10) 53
 
3.5%
Han
ValueCountFrequency (%)
2
25.0%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19420
88.0%
ASCII 2651
 
12.0%
CJK 6
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1166
 
6.0%
978
 
5.0%
915
 
4.7%
760
 
3.9%
711
 
3.7%
405
 
2.1%
374
 
1.9%
339
 
1.7%
317
 
1.6%
294
 
1.5%
Other values (590) 13161
67.8%
ASCII
ValueCountFrequency (%)
587
22.1%
) 372
14.0%
( 371
14.0%
e 90
 
3.4%
a 66
 
2.5%
o 60
 
2.3%
B 49
 
1.8%
E 49
 
1.8%
2 46
 
1.7%
A 46
 
1.7%
Other values (59) 915
34.5%
CJK Compat Ideographs
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Number Forms
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct2714
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0140107 × 1013
Minimum2.001081 × 1013
Maximum2.0220527 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:16:10.204860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001081 × 1013
5-th percentile2.0020924 × 1013
Q12.0090621 × 1013
median2.0151218 × 1013
Q32.0200407 × 1013
95-th percentile2.022012 × 1013
Maximum2.0220527 × 1013
Range2.0971717 × 1011
Interquartile range (IQR)1.09786 × 1011

Descriptive statistics

Standard deviation6.4484222 × 1010
Coefficient of variation (CV)0.0032017814
Kurtosis-1.04927
Mean2.0140107 × 1013
Median Absolute Deviation (MAD)5.0010006 × 1010
Skewness-0.50423565
Sum5.9433457 × 1016
Variance4.1582149 × 1021
MonotonicityNot monotonic
2023-12-11T03:16:10.465362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041008000000 21
 
0.7%
20020919000000 19
 
0.6%
20020916000000 13
 
0.4%
20021024000000 13
 
0.4%
20211101041509 10
 
0.3%
20020918000000 9
 
0.3%
20021101000000 8
 
0.3%
20021209000000 6
 
0.2%
20020830000000 6
 
0.2%
20021127000000 5
 
0.2%
Other values (2704) 2841
96.3%
ValueCountFrequency (%)
20010810000000 2
0.1%
20010811000000 2
0.1%
20010816000000 1
< 0.1%
20010817000000 2
0.1%
20011030000000 1
< 0.1%
20011031000000 2
0.1%
20011101000000 1
< 0.1%
20011102000000 1
< 0.1%
20011105000000 2
0.1%
20011107000000 1
< 0.1%
ValueCountFrequency (%)
20220527170845 1
< 0.1%
20220527154059 1
< 0.1%
20220527152435 1
< 0.1%
20220527145114 1
< 0.1%
20220527093557 1
< 0.1%
20220526175405 1
< 0.1%
20220524100606 1
< 0.1%
20220523115209 1
< 0.1%
20220523115153 1
< 0.1%
20220523094113 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
I
1941 
U
1010 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1941
65.8%
U 1010
34.2%

Length

2023-12-11T03:16:10.689175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:10.875443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1941
65.8%
u 1010
34.2%
Distinct632
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
Minimum2018-08-31 23:59:59
Maximum2022-05-29 02:40:00
2023-12-11T03:16:11.081576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:16:11.356796image/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 size23.2 KiB
제과점영업
2949 
푸드트럭
 
2

Length

Max length5
Median length5
Mean length4.9993223
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 2949
99.9%
푸드트럭 2
 
0.1%

Length

2023-12-11T03:16:11.633560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:11.804685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 2949
99.9%
푸드트럭 2
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2054
Distinct (%)71.5%
Missing80
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean343096.35
Minimum327860.09
Maximum358046.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:16:12.005698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327860.09
5-th percentile334602.48
Q1339572.13
median343588.74
Q3346200.74
95-th percentile353606.47
Maximum358046.4
Range30186.309
Interquartile range (IQR)6628.6049

Descriptive statistics

Standard deviation5203.7523
Coefficient of variation (CV)0.015167029
Kurtosis0.26592213
Mean343096.35
Median Absolute Deviation (MAD)3448.5064
Skewness0.098047588
Sum9.8502962 × 108
Variance27079038
MonotonicityNot monotonic
2023-12-11T03:16:12.256989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
343588.735555 71
 
2.4%
345032.238221 42
 
1.4%
344047.164924 28
 
0.9%
347037.24197 21
 
0.7%
344047.979265 17
 
0.6%
340320.72271 13
 
0.4%
339047.793379 12
 
0.4%
347008.880529 12
 
0.4%
343705.561002 12
 
0.4%
348194.499421 10
 
0.3%
Other values (2044) 2633
89.2%
(Missing) 80
 
2.7%
ValueCountFrequency (%)
327860.094827 1
< 0.1%
327994.771471 1
< 0.1%
328015.993727 1
< 0.1%
328158.321294 1
< 0.1%
328209.625282 1
< 0.1%
328226.964839 1
< 0.1%
329894.345198 1
< 0.1%
329898.834237 1
< 0.1%
330013.035782 1
< 0.1%
330084.748297 1
< 0.1%
ValueCountFrequency (%)
358046.403776 1
< 0.1%
357908.12325 1
< 0.1%
357881.329153 1
< 0.1%
356437.578421 1
< 0.1%
356425.755845 1
< 0.1%
356353.91544 2
0.1%
356351.120591 1
< 0.1%
356312.340344 1
< 0.1%
356222.826617 1
< 0.1%
356202.878304 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2053
Distinct (%)71.5%
Missing80
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean263315.61
Minimum240452.6
Maximum277860.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:16:12.994601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240452.6
5-th percentile257488.54
Q1261205.07
median263371.67
Q3265336.24
95-th percentile271412.22
Maximum277860.93
Range37408.331
Interquartile range (IQR)4131.1713

Descriptive statistics

Standard deviation4448.7204
Coefficient of variation (CV)0.016895012
Kurtosis4.2926013
Mean263315.61
Median Absolute Deviation (MAD)2035.7334
Skewness-0.88665405
Sum7.5597911 × 108
Variance19791113
MonotonicityNot monotonic
2023-12-11T03:16:13.293928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
264119.01075 71
 
2.4%
262949.871621 42
 
1.4%
265132.987974 28
 
0.9%
265407.404337 21
 
0.7%
264405.128696 17
 
0.6%
272735.67566 13
 
0.4%
258741.90218 12
 
0.4%
265530.003516 12
 
0.4%
264056.630949 12
 
0.4%
259144.519321 10
 
0.3%
Other values (2043) 2633
89.2%
(Missing) 80
 
2.7%
ValueCountFrequency (%)
240452.59556 1
< 0.1%
240482.499847 1
< 0.1%
240483.091393 1
< 0.1%
240483.177406 1
< 0.1%
240839.348978 1
< 0.1%
240868.08825 1
< 0.1%
244475.0 1
< 0.1%
244562.0 1
< 0.1%
244624.0 2
0.1%
244625.0 1
< 0.1%
ValueCountFrequency (%)
277860.926384 1
< 0.1%
275847.996577 1
< 0.1%
274018.517122 1
< 0.1%
274001.175164 1
< 0.1%
273719.251935 1
< 0.1%
273712.082489 1
< 0.1%
273612.928446 1
< 0.1%
273587.706164 1
< 0.1%
273506.093893 1
< 0.1%
273495.538932 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
제과점영업
2949 
푸드트럭
 
2

Length

Max length5
Median length5
Mean length4.9993223
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 2949
99.9%
푸드트럭 2
 
0.1%

Length

2023-12-11T03:16:13.551134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:13.734695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 2949
99.9%
푸드트럭 2
 
0.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.7%
Missing1394
Missing (%)47.2%
Infinite0
Infinite (%)0.0%
Mean0.46499679
Minimum0
Maximum17
Zeros1101
Zeros (%)37.3%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:16:13.888754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum17
Range17
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0182595
Coefficient of variation (CV)2.1898205
Kurtosis65.793806
Mean0.46499679
Median Absolute Deviation (MAD)0
Skewness5.8090516
Sum724
Variance1.0368524
MonotonicityNot monotonic
2023-12-11T03:16:14.082753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 1101
37.3%
1 304
 
10.3%
2 96
 
3.3%
3 34
 
1.2%
4 13
 
0.4%
5 3
 
0.1%
7 2
 
0.1%
13 1
 
< 0.1%
6 1
 
< 0.1%
17 1
 
< 0.1%
(Missing) 1394
47.2%
ValueCountFrequency (%)
0 1101
37.3%
1 304
 
10.3%
2 96
 
3.3%
3 34
 
1.2%
4 13
 
0.4%
5 3
 
0.1%
6 1
 
< 0.1%
7 2
 
0.1%
9 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
13 1
 
< 0.1%
9 1
 
< 0.1%
7 2
 
0.1%
6 1
 
< 0.1%
5 3
 
0.1%
4 13
 
0.4%
3 34
 
1.2%
2 96
 
3.3%
1 304
10.3%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)0.9%
Missing1314
Missing (%)44.5%
Infinite0
Infinite (%)0.0%
Mean0.68234575
Minimum0
Maximum47
Zeros1059
Zeros (%)35.9%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:16:14.299231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum47
Range47
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.7076736
Coefficient of variation (CV)2.5026514
Kurtosis339.9773
Mean0.68234575
Median Absolute Deviation (MAD)0
Skewness13.91326
Sum1117
Variance2.916149
MonotonicityNot monotonic
2023-12-11T03:16:14.499352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 1059
35.9%
1 318
 
10.8%
2 155
 
5.3%
3 58
 
2.0%
4 16
 
0.5%
5 10
 
0.3%
6 10
 
0.3%
7 5
 
0.2%
47 1
 
< 0.1%
11 1
 
< 0.1%
Other values (4) 4
 
0.1%
(Missing) 1314
44.5%
ValueCountFrequency (%)
0 1059
35.9%
1 318
 
10.8%
2 155
 
5.3%
3 58
 
2.0%
4 16
 
0.5%
5 10
 
0.3%
6 10
 
0.3%
7 5
 
0.2%
8 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
47 1
 
< 0.1%
18 1
 
< 0.1%
12 1
 
< 0.1%
11 1
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
7 5
 
0.2%
6 10
0.3%
5 10
0.3%
4 16
0.5%
Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
<NA>
1240 
기타
878 
주택가주변
395 
아파트지역
349 
유흥업소밀집지역
 
50
Other values (3)
 
39

Length

Max length8
Median length7
Mean length3.7773636
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1240
42.0%
기타 878
29.8%
주택가주변 395
 
13.4%
아파트지역 349
 
11.8%
유흥업소밀집지역 50
 
1.7%
학교정화(상대) 29
 
1.0%
학교정화(절대) 9
 
0.3%
결혼예식장주변 1
 
< 0.1%

Length

2023-12-11T03:16:14.743034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:14.961612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1240
42.0%
기타 878
29.8%
주택가주변 395
 
13.4%
아파트지역 349
 
11.8%
유흥업소밀집지역 50
 
1.7%
학교정화(상대 29
 
1.0%
학교정화(절대 9
 
0.3%
결혼예식장주변 1
 
< 0.1%

등급구분명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
<NA>
2070 
자율
643 
기타
235 
 
3

Length

Max length4
Median length4
Mean length3.4018977
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2070
70.1%
자율 643
 
21.8%
기타 235
 
8.0%
3
 
0.1%

Length

2023-12-11T03:16:15.192297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:15.399906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2070
70.1%
자율 643
 
21.8%
기타 235
 
8.0%
3
 
0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
상수도전용
2266 
<NA>
682 
전용상수도(특정시설의 자가용 수도)
 
2
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length19
Median length5
Mean length4.7824466
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2266
76.8%
<NA> 682
 
23.1%
전용상수도(특정시설의 자가용 수도) 2
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2023-12-11T03:16:15.612413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:15.800244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2266
76.7%
na 682
 
23.1%
전용상수도(특정시설의 2
 
0.1%
자가용 2
 
0.1%
수도 2
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
<NA>
2625 
0
326 

Length

Max length4
Median length4
Mean length3.6685869
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2625
89.0%
0 326
 
11.0%

Length

2023-12-11T03:16:16.024242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:16.194019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2625
89.0%
0 326
 
11.0%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
<NA>
2618 
0
333 

Length

Max length4
Median length4
Mean length3.6614707
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2618
88.7%
0 333
 
11.3%

Length

2023-12-11T03:16:16.393681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:16.619801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2618
88.7%
0 333
 
11.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
<NA>
2618 
0
333 

Length

Max length4
Median length4
Mean length3.6614707
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2618
88.7%
0 333
 
11.3%

Length

2023-12-11T03:16:16.824108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:16.991126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2618
88.7%
0 333
 
11.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
<NA>
2618 
0
333 

Length

Max length4
Median length4
Mean length3.6614707
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2618
88.7%
0 333
 
11.3%

Length

2023-12-11T03:16:17.152104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:17.314057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2618
88.7%
0 333
 
11.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
<NA>
2618 
0
333 

Length

Max length4
Median length4
Mean length3.6614707
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2618
88.7%
0 333
 
11.3%

Length

2023-12-11T03:16:17.490144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:17.656171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2618
88.7%
0 333
 
11.3%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2951
Missing (%)100.0%
Memory size26.1 KiB

보증액
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
<NA>
2618 
0
333 

Length

Max length4
Median length4
Mean length3.6614707
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2618
88.7%
0 333
 
11.3%

Length

2023-12-11T03:16:17.846969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:18.002300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2618
88.7%
0 333
 
11.3%

월세액
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.2 KiB
<NA>
2618 
0
333 

Length

Max length4
Median length4
Mean length3.6614707
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2618
88.7%
0 333
 
11.3%

Length

2023-12-11T03:16:18.171932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:18.322602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2618
88.7%
0 333
 
11.3%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
False
2911 
True
 
40
ValueCountFrequency (%)
False 2911
98.6%
True 40
 
1.4%
2023-12-11T03:16:18.458817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct1878
Distinct (%)63.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.752321
Minimum0
Maximum1300
Zeros136
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size26.1 KiB
2023-12-11T03:16:18.618170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.525
Q123.1
median35.2
Q356.23
95-th percentile116.16
Maximum1300
Range1300
Interquartile range (IQR)33.13

Descriptive statistics

Standard deviation53.80158
Coefficient of variation (CV)1.1507788
Kurtosis139.57831
Mean46.752321
Median Absolute Deviation (MAD)14.76
Skewness8.51853
Sum137966.1
Variance2894.61
MonotonicityNot monotonic
2023-12-11T03:16:18.834908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 136
 
4.6%
33.0 20
 
0.7%
20.0 18
 
0.6%
36.0 16
 
0.5%
26.4 14
 
0.5%
30.0 13
 
0.4%
3.3 13
 
0.4%
40.0 12
 
0.4%
19.8 11
 
0.4%
28.0 11
 
0.4%
Other values (1868) 2687
91.1%
ValueCountFrequency (%)
0.0 136
4.6%
0.9 1
 
< 0.1%
1.0 4
 
0.1%
1.2 1
 
< 0.1%
1.44 3
 
0.1%
1.5 3
 
0.1%
1.55 1
 
< 0.1%
1.6 2
 
0.1%
1.69 1
 
< 0.1%
1.92 1
 
< 0.1%
ValueCountFrequency (%)
1300.0 1
< 0.1%
787.0 1
< 0.1%
734.07 1
< 0.1%
732.0 1
< 0.1%
613.0 1
< 0.1%
504.1 1
< 0.1%
432.0 1
< 0.1%
424.58 1
< 0.1%
401.85 1
< 0.1%
381.9 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2951
Missing (%)100.0%
Memory size26.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2951
Missing (%)100.0%
Memory size26.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2951
Missing (%)100.0%
Memory size26.1 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01제과점영업07_22_18_P34100003410000-121-2016-0001020160429<NA>3폐업2폐업20180518<NA><NA><NA>053 424874725.92700060대구광역시 중구 남일동 0094-0001번지 지상1층대구광역시 중구 중앙대로 406-14 (남일동, 지상1층)41937키세키20180518163042I2018-08-31 23:59:59.0제과점영업343938.33559264400.984778제과점영업<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N25.92<NA><NA><NA>
12제과점영업07_22_18_P34100003410000-121-2016-0001120160503<NA>3폐업2폐업20211007<NA><NA><NA>053 424202532.55700823대구광역시 중구 봉산동 0037-0015 지상1층대구광역시 중구 동성로1길 46-26 (봉산동, 지상1층)41943빠다롤뺑프랑스20211007150209U2021-10-09 02:40:00.0제과점영업343984.381766264045.733058제과점영업22기타자율상수도전용00000<NA>00N32.55<NA><NA><NA>
23제과점영업07_22_18_P34100003410000-121-2016-0001320160705<NA>3폐업2폐업20171207<NA><NA><NA>053 431030041.70700822대구광역시 중구 봉산동 0033-0001번지 지상1층대구광역시 중구 동성로1길 47 (봉산동, 지상1층)41942요고타르트20171207175259I2018-08-31 23:59:59.0제과점영업344086.421015264046.40316제과점영업22기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N41.7<NA><NA><NA>
34제과점영업07_22_18_P34100003410000-121-2016-0001520160721<NA>3폐업2폐업20180906<NA><NA><NA><NA>69.42700847대구광역시 중구 동인동4가 0247-0005번지 지상1층대구광역시 중구 동덕로30길 63-4 (동인동4가, 지상1층)41945빵장수꽈배기 동인지점20180906113524U2018-09-06 23:59:59.0제과점영업345107.305348264161.720179제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N69.42<NA><NA><NA>
45제과점영업07_22_18_P34100003410000-121-2016-0001620160801<NA>3폐업2폐업20180125<NA><NA><NA><NA>33.64700813대구광역시 중구 대봉동 0632-0002번지 지상1층대구광역시 중구 명덕로 243 (대봉동, 지상1층)41962모모20180125155921I2018-08-31 23:59:59.0제과점영업344180.890971262983.785368제과점영업<NA><NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N33.64<NA><NA><NA>
56제과점영업07_22_18_P34100003410000-121-2016-0001720160829<NA>3폐업2폐업20190830<NA><NA><NA><NA>44.82700413대구광역시 중구 삼덕동3가 270-2번지 지상1층대구광역시 중구 달구벌대로447길 44-28 (삼덕동3가, 지상1층)41948삼덕동베이커리까페20190830103012U2019-09-01 02:40:00.0제과점영업345285.258246263835.432669제과점영업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N44.82<NA><NA><NA>
67제과점영업07_22_18_P34100003410000-121-2016-0001820161128<NA>3폐업2폐업20170615<NA><NA><NA><NA>16.10700082대구광역시 중구 계산동2가 0200번지 현대백화점 식품관대구광역시 중구 달구벌대로 2077 (계산동2가, 현대백화점 식품관)41936(주)파블로코리아20170615110117I2018-08-31 23:59:59.0제과점영업343588.735555264119.01075제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N16.1<NA><NA><NA>
78제과점영업07_22_18_P34100003410000-121-2005-0007420050502<NA>3폐업2폐업20100830<NA><NA><NA><NA>8.00700718대구광역시 중구 대봉동 0214번지 대백프라자<NA><NA>단석명가찰보리빵20050615000000I2018-08-31 23:59:59.0제과점영업345032.238221262949.871621제과점영업11기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N8.0<NA><NA><NA>
89제과점영업07_22_18_P34100003410000-121-2005-0007920050531<NA>3폐업2폐업20070528<NA><NA><NA>053957 39778.64700070대구광역시 중구 덕산동 0053-0003번지<NA><NA>백설마루20050531000000I2018-08-31 23:59:59.0제과점영업343705.561002264056.630949제과점영업01기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N8.64<NA><NA><NA>
910제과점영업07_22_18_P34100003410000-121-2005-0007020050705<NA>3폐업2폐업20101006<NA><NA><NA>053 428771023.15700823대구광역시 중구 봉산동 0137-0015번지 (1층)<NA><NA>토스트굽는사람들20100617095406I2018-08-31 23:59:59.0제과점영업344127.944529263895.481558제과점영업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N23.15<NA><NA><NA>
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29432944제과점영업07_22_18_P34800003480000-121-2014-0000520141208<NA>1영업/정상1영업<NA><NA><NA><NA>053 202 1232285.00711813대구광역시 달성군 다사읍 서재리 121-3대구광역시 달성군 다사읍 서재본길 4, 1~2층42923양과부띠끄엘20220118092418U2022-01-20 02:40:00.0제과점영업335138.716049264584.919088제과점영업00기타<NA>상수도전용00000<NA>00Y285.0<NA><NA><NA>
29442945제과점영업07_22_18_P34800003480000-121-2018-0000120180328<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.27711852대구광역시 달성군 논공읍 북리 803-302번지대구광역시 달성군 논공읍 논공로 774, 1층42979호밀빵20180425201620I2018-08-31 23:59:59.0제과점영업330430.957874248611.080445제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N61.27<NA><NA><NA>
29452946제과점영업07_22_18_P34800003480000-121-2014-0000420140731<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00711852대구광역시 달성군 논공읍 북리 833-75번지 외1필지대구광역시 달성군 논공읍 논공중앙로 12842985나이스 빵집20140731115743I2018-08-31 23:59:59.0제과점영업330992.612575248466.723517제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N30.0<NA><NA><NA>
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29492950제과점영업07_22_18_P34800003480000-121-2016-0000420160316<NA>1영업/정상1영업<NA><NA><NA><NA>053 611 828491.93<NA>대구광역시 달성군 현풍읍 중리 489-105대구광역시 달성군 현풍읍 테크노상업로 46, 1층 105호43017뚜레쥬르(현풍테크노점)20201210144428U2020-12-12 02:40:00.0제과점영업331608.0244625.0제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N91.93<NA><NA><NA>
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