Overview

Dataset statistics

Number of variables47
Number of observations2936
Missing cells30381
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

Description22년04월_6270000_대구광역시_07_22_18_P_제과점영업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000092918&dataSetDetailId=DDI_0000092969&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 (60.5%)Imbalance
총종업원수 is highly imbalanced (53.3%)Imbalance
본사종업원수 is highly imbalanced (52.5%)Imbalance
공장사무직종업원수 is highly imbalanced (52.5%)Imbalance
공장판매직종업원수 is highly imbalanced (52.5%)Imbalance
공장생산직종업원수 is highly imbalanced (52.5%)Imbalance
보증액 is highly imbalanced (52.5%)Imbalance
월세액 is highly imbalanced (52.5%)Imbalance
다중이용업소여부 is highly imbalanced (89.8%)Imbalance
인허가취소일자 has 2936 (100.0%) missing valuesMissing
폐업일자 has 971 (33.1%) missing valuesMissing
휴업시작일자 has 2936 (100.0%) missing valuesMissing
휴업종료일자 has 2936 (100.0%) missing valuesMissing
재개업일자 has 2936 (100.0%) missing valuesMissing
소재지전화 has 1220 (41.6%) missing valuesMissing
소재지면적 has 101 (3.4%) missing valuesMissing
소재지우편번호 has 30 (1.0%) missing valuesMissing
도로명전체주소 has 830 (28.3%) missing valuesMissing
도로명우편번호 has 847 (28.8%) missing valuesMissing
좌표정보(X) has 79 (2.7%) missing valuesMissing
좌표정보(Y) has 79 (2.7%) missing valuesMissing
남성종사자수 has 1408 (48.0%) missing valuesMissing
여성종사자수 has 1328 (45.2%) missing valuesMissing
건물소유구분명 has 2936 (100.0%) missing valuesMissing
전통업소지정번호 has 2936 (100.0%) missing valuesMissing
전통업소주된음식 has 2936 (100.0%) missing valuesMissing
홈페이지 has 2936 (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 1072 (36.5%) zerosZeros
여성종사자수 has 1030 (35.1%) zerosZeros
시설총규모 has 130 (4.4%) zerosZeros

Reproduction

Analysis started2024-04-17 17:40:58.822994
Analysis finished2024-04-17 17:40:59.964137
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct2936
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1468.5
Minimum1
Maximum2936
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:00.023637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile147.75
Q1734.75
median1468.5
Q32202.25
95-th percentile2789.25
Maximum2936
Range2935
Interquartile range (IQR)1467.5

Descriptive statistics

Standard deviation847.69452
Coefficient of variation (CV)0.57725197
Kurtosis-1.2
Mean1468.5
Median Absolute Deviation (MAD)734
Skewness0
Sum4311516
Variance718586
MonotonicityStrictly increasing
2024-04-18T02:41:00.142787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1952 1
 
< 0.1%
1954 1
 
< 0.1%
1955 1
 
< 0.1%
1956 1
 
< 0.1%
1957 1
 
< 0.1%
1958 1
 
< 0.1%
1959 1
 
< 0.1%
1960 1
 
< 0.1%
1961 1
 
< 0.1%
Other values (2926) 2926
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 (%)
2936 1
< 0.1%
2935 1
< 0.1%
2934 1
< 0.1%
2933 1
< 0.1%
2932 1
< 0.1%
2931 1
< 0.1%
2930 1
< 0.1%
2929 1
< 0.1%
2928 1
< 0.1%
2927 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
제과점영업
2936 

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 2936
100.0%

Length

2024-04-18T02:41:00.243516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:00.313823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 2936
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
07_22_18_P
2936 

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 2936
100.0%

Length

2024-04-18T02:41:00.398610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:00.466750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_18_p 2936
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447288.8
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:00.693585image/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 deviation22000.612
Coefficient of variation (CV)0.0063820044
Kurtosis-1.1200555
Mean3447288.8
Median Absolute Deviation (MAD)20000
Skewness-0.39307097
Sum1.012124 × 1010
Variance4.8402694 × 108
MonotonicityIncreasing
2024-04-18T02:41:00.776858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 583
19.9%
3460000 541
18.4%
3450000 526
17.9%
3410000 363
12.4%
3420000 337
11.5%
3430000 206
 
7.0%
3440000 192
 
6.5%
3480000 188
 
6.4%
ValueCountFrequency (%)
3410000 363
12.4%
3420000 337
11.5%
3430000 206
 
7.0%
3440000 192
 
6.5%
3450000 526
17.9%
3460000 541
18.4%
3470000 583
19.9%
3480000 188
 
6.4%
ValueCountFrequency (%)
3480000 188
 
6.4%
3470000 583
19.9%
3460000 541
18.4%
3450000 526
17.9%
3440000 192
 
6.5%
3430000 206
 
7.0%
3420000 337
11.5%
3410000 363
12.4%

관리번호
Text

UNIQUE 

Distinct2936
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
2024-04-18T02:41:00.930410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters64592
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

Unique2936 ?
Unique (%)100.0%

Sample

1st row3410000-121-2016-00015
2nd row3410000-121-2016-00016
3rd row3410000-121-2016-00017
4th row3410000-121-2016-00018
5th row3410000-121-2005-00074
ValueCountFrequency (%)
3410000-121-2016-00015 1
 
< 0.1%
3460000-121-2011-00014 1
 
< 0.1%
3460000-121-2013-00013 1
 
< 0.1%
3460000-121-2011-00028 1
 
< 0.1%
3460000-121-2011-00029 1
 
< 0.1%
3460000-121-2011-00031 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%
Other values (2926) 2926
99.7%
2024-04-18T02:41:01.181381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26019
40.3%
1 9506
 
14.7%
- 8808
 
13.6%
2 7271
 
11.3%
3 3863
 
6.0%
4 3774
 
5.8%
7 1190
 
1.8%
6 1147
 
1.8%
5 1139
 
1.8%
9 1056
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55784
86.4%
Dash Punctuation 8808
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26019
46.6%
1 9506
 
17.0%
2 7271
 
13.0%
3 3863
 
6.9%
4 3774
 
6.8%
7 1190
 
2.1%
6 1147
 
2.1%
5 1139
 
2.0%
9 1056
 
1.9%
8 819
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 8808
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64592
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26019
40.3%
1 9506
 
14.7%
- 8808
 
13.6%
2 7271
 
11.3%
3 3863
 
6.0%
4 3774
 
5.8%
7 1190
 
1.8%
6 1147
 
1.8%
5 1139
 
1.8%
9 1056
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26019
40.3%
1 9506
 
14.7%
- 8808
 
13.6%
2 7271
 
11.3%
3 3863
 
6.0%
4 3774
 
5.8%
7 1190
 
1.8%
6 1147
 
1.8%
5 1139
 
1.8%
9 1056
 
1.6%

인허가일자
Real number (ℝ)

Distinct2304
Distinct (%)78.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20095468
Minimum19790328
Maximum20220428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:01.302130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19790328
5-th percentile19947971
Q120040714
median20100924
Q320160920
95-th percentile20210427
Maximum20220428
Range430100
Interquartile range (IQR)120205.5

Descriptive statistics

Standard deviation81414.976
Coefficient of variation (CV)0.0040514098
Kurtosis0.27732188
Mean20095468
Median Absolute Deviation (MAD)60094
Skewness-0.68209532
Sum5.9000294 × 1010
Variance6.6283984 × 109
MonotonicityNot monotonic
2024-04-18T02:41:01.408654image/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%
20070912 4
 
0.1%
20031117 4
 
0.1%
20100528 4
 
0.1%
19931030 4
 
0.1%
20110823 4
 
0.1%
19930907 4
 
0.1%
Other values (2294) 2887
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 (%)
20220428 1
< 0.1%
20220427 1
< 0.1%
20220425 1
< 0.1%
20220419 1
< 0.1%
20220418 1
< 0.1%
20220413 1
< 0.1%
20220411 2
0.1%
20220408 1
< 0.1%
20220406 1
< 0.1%
20220405 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2936
Missing (%)100.0%
Memory size25.9 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
3
1965 
1
971 

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 1965
66.9%
1 971
33.1%

Length

2024-04-18T02:41:01.519928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:01.591571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1965
66.9%
1 971
33.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
폐업
1965 
영업/정상
971 

Length

Max length5
Median length2
Mean length2.9921662
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1965
66.9%
영업/정상 971
33.1%

Length

2024-04-18T02:41:01.667198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:01.740456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1965
66.9%
영업/정상 971
33.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
2
1965 
1
971 

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 1965
66.9%
1 971
33.1%

Length

2024-04-18T02:41:01.816965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:01.905109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1965
66.9%
1 971
33.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
폐업
1965 
영업
971 

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 1965
66.9%
영업 971
33.1%

Length

2024-04-18T02:41:01.981087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:02.048568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1965
66.9%
영업 971
33.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct1461
Distinct (%)74.4%
Missing971
Missing (%)33.1%
Infinite0
Infinite (%)0.0%
Mean20132968
Minimum20020319
Maximum20220428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:02.137049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020319
5-th percentile20051128
Q120090408
median20131202
Q320180207
95-th percentile20210722
Maximum20220428
Range200109
Interquartile range (IQR)89799

Descriptive statistics

Standard deviation51581.575
Coefficient of variation (CV)0.0025620452
Kurtosis-1.1901716
Mean20132968
Median Absolute Deviation (MAD)40998
Skewness-0.088687034
Sum3.9561283 × 1010
Variance2.6606589 × 109
MonotonicityNot monotonic
2024-04-18T02:41:02.262874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211031 10
 
0.3%
20180207 7
 
0.2%
20051111 7
 
0.2%
20190108 6
 
0.2%
20130129 6
 
0.2%
20220120 5
 
0.2%
20141231 5
 
0.2%
20050125 5
 
0.2%
20051220 4
 
0.1%
20051215 4
 
0.1%
Other values (1451) 1906
64.9%
(Missing) 971
33.1%
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 (%)
20220428 1
< 0.1%
20220425 1
< 0.1%
20220422 1
< 0.1%
20220412 1
< 0.1%
20220407 1
< 0.1%
20220406 1
< 0.1%
20220405 1
< 0.1%
20220404 1
< 0.1%
20220328 1
< 0.1%
20220324 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2936
Missing (%)100.0%
Memory size25.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2936
Missing (%)100.0%
Memory size25.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2936
Missing (%)100.0%
Memory size25.9 KiB

소재지전화
Text

MISSING 

Distinct1606
Distinct (%)93.6%
Missing1220
Missing (%)41.6%
Memory size23.1 KiB
2024-04-18T02:41:02.544773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.727273
Min length3

Characters and Unicode

Total characters18408
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

Unique1524 ?
Unique (%)88.8%

Sample

1st row053957 3977
2nd row053 4287710
3rd row053 2513220
4th row053 2528215
5th row053 4208720
ValueCountFrequency (%)
053 1364
36.5%
070 23
 
0.6%
793 11
 
0.3%
741 11
 
0.3%
2452901 10
 
0.3%
311 10
 
0.3%
380 9
 
0.2%
639 9
 
0.2%
794 9
 
0.2%
795 8
 
0.2%
Other values (1715) 2273
60.8%
2024-04-18T02:41:02.889996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2966
16.1%
0 2627
14.3%
3 2598
14.1%
2047
11.1%
2 1478
8.0%
6 1325
7.2%
7 1205
6.5%
4 1138
 
6.2%
1 1092
 
5.9%
8 1026
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16361
88.9%
Space Separator 2047
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2966
18.1%
0 2627
16.1%
3 2598
15.9%
2 1478
9.0%
6 1325
8.1%
7 1205
7.4%
4 1138
 
7.0%
1 1092
 
6.7%
8 1026
 
6.3%
9 906
 
5.5%
Space Separator
ValueCountFrequency (%)
2047
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18408
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2966
16.1%
0 2627
14.3%
3 2598
14.1%
2047
11.1%
2 1478
8.0%
6 1325
7.2%
7 1205
6.5%
4 1138
 
6.2%
1 1092
 
5.9%
8 1026
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2966
16.1%
0 2627
14.3%
3 2598
14.1%
2047
11.1%
2 1478
8.0%
6 1325
7.2%
7 1205
6.5%
4 1138
 
6.2%
1 1092
 
5.9%
8 1026
 
5.6%

소재지면적
Text

MISSING 

Distinct1857
Distinct (%)65.5%
Missing101
Missing (%)3.4%
Memory size23.1 KiB
2024-04-18T02:41:03.187496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9693122
Min length3

Characters and Unicode

Total characters14088
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 (%)49.8%

Sample

1st row69.42
2nd row33.64
3rd row44.82
4th row16.10
5th row8.00
ValueCountFrequency (%)
00 58
 
2.0%
33.00 20
 
0.7%
20.00 18
 
0.6%
36.00 15
 
0.5%
30.00 14
 
0.5%
26.40 14
 
0.5%
3.30 13
 
0.5%
40.00 11
 
0.4%
19.80 11
 
0.4%
28.00 11
 
0.4%
Other values (1847) 2650
93.5%
2024-04-18T02:41:03.572726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 2835
20.1%
0 2311
16.4%
2 1424
10.1%
3 1184
8.4%
4 1135
8.1%
5 998
 
7.1%
1 997
 
7.1%
6 934
 
6.6%
8 824
 
5.8%
7 729
 
5.2%
Other values (2) 717
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11252
79.9%
Other Punctuation 2836
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2311
20.5%
2 1424
12.7%
3 1184
10.5%
4 1135
10.1%
5 998
8.9%
1 997
8.9%
6 934
8.3%
8 824
 
7.3%
7 729
 
6.5%
9 716
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 2835
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14088
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2835
20.1%
0 2311
16.4%
2 1424
10.1%
3 1184
8.4%
4 1135
8.1%
5 998
 
7.1%
1 997
 
7.1%
6 934
 
6.6%
8 824
 
5.8%
7 729
 
5.2%
Other values (2) 717
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14088
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2835
20.1%
0 2311
16.4%
2 1424
10.1%
3 1184
8.4%
4 1135
8.1%
5 998
 
7.1%
1 997
 
7.1%
6 934
 
6.6%
8 824
 
5.8%
7 729
 
5.2%
Other values (2) 717
 
5.1%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct508
Distinct (%)17.5%
Missing30
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean704244.04
Minimum700010
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:03.689486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700150
Q1702042.5
median704080
Q3705832
95-th percentile711812
Maximum711891
Range11881
Interquartile range (IQR)3789.5

Descriptive statistics

Standard deviation2741.1072
Coefficient of variation (CV)0.003892269
Kurtosis0.94954603
Mean704244.04
Median Absolute Deviation (MAD)1770
Skewness0.8220372
Sum2.0465332 × 109
Variance7513668.9
MonotonicityNot monotonic
2024-04-18T02:41:03.794674image/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 39
 
1.3%
706803 28
 
1.0%
704834 28
 
1.0%
702040 26
 
0.9%
700092 25
 
0.9%
702845 25
 
0.9%
700718 24
 
0.8%
702807 23
 
0.8%
Other values (498) 2572
87.6%
(Missing) 30
 
1.0%
ValueCountFrequency (%)
700010 1
 
< 0.1%
700040 3
 
0.1%
700060 8
 
0.3%
700070 18
 
0.6%
700082 74
2.5%
700092 25
 
0.9%
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%
Distinct2626
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
2024-04-18T02:41:04.085845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length26.627725
Min length16

Characters and Unicode

Total characters78179
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

Unique2458 ?
Unique (%)83.7%

Sample

1st row대구광역시 중구 동인동4가 0247-0005번지 지상1층
2nd row대구광역시 중구 대봉동 0632-0002번지 지상1층
3rd row대구광역시 중구 삼덕동3가 270-2번지 지상1층
4th row대구광역시 중구 계산동2가 0200번지 현대백화점 식품관
5th row대구광역시 중구 대봉동 0214번지 대백프라자
ValueCountFrequency (%)
대구광역시 2938
 
20.4%
달서구 583
 
4.0%
수성구 541
 
3.8%
북구 526
 
3.6%
중구 363
 
2.5%
동구 337
 
2.3%
서구 206
 
1.4%
남구 192
 
1.3%
달성군 188
 
1.3%
1층 187
 
1.3%
Other values (3307) 8356
58.0%
2024-04-18T02:41:04.503158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14149
18.1%
5830
 
7.5%
1 4192
 
5.4%
3588
 
4.6%
3436
 
4.4%
0 3175
 
4.1%
3021
 
3.9%
2969
 
3.8%
2963
 
3.8%
2951
 
3.8%
Other values (365) 31905
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43904
56.2%
Decimal Number 17160
 
21.9%
Space Separator 14149
 
18.1%
Dash Punctuation 2166
 
2.8%
Open Punctuation 256
 
0.3%
Close Punctuation 256
 
0.3%
Other Punctuation 144
 
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 (%)
5830
 
13.3%
3588
 
8.2%
3436
 
7.8%
3021
 
6.9%
2969
 
6.8%
2963
 
6.7%
2951
 
6.7%
2282
 
5.2%
1138
 
2.6%
911
 
2.1%
Other values (326) 14815
33.7%
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%
D 4
 
3.1%
P 4
 
3.1%
R 2
 
1.6%
Other values (6) 9
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 4192
24.4%
0 3175
18.5%
2 2052
12.0%
3 1440
 
8.4%
5 1241
 
7.2%
4 1206
 
7.0%
6 1080
 
6.3%
8 973
 
5.7%
7 907
 
5.3%
9 894
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 108
75.0%
. 21
 
14.6%
/ 13
 
9.0%
@ 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 (%)
14149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2166
100.0%
Open Punctuation
ValueCountFrequency (%)
( 256
100.0%
Close Punctuation
ValueCountFrequency (%)
) 256
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43904
56.2%
Common 34142
43.7%
Latin 133
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5830
 
13.3%
3588
 
8.2%
3436
 
7.8%
3021
 
6.9%
2969
 
6.8%
2963
 
6.7%
2951
 
6.7%
2282
 
5.2%
1138
 
2.6%
911
 
2.1%
Other values (326) 14815
33.7%
Common
ValueCountFrequency (%)
14149
41.4%
1 4192
 
12.3%
0 3175
 
9.3%
- 2166
 
6.3%
2 2052
 
6.0%
3 1440
 
4.2%
5 1241
 
3.6%
4 1206
 
3.5%
6 1080
 
3.2%
8 973
 
2.8%
Other values (11) 2468
 
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%
K 5
 
3.8%
e 5
 
3.8%
D 4
 
3.0%
P 4
 
3.0%
Other values (8) 12
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43903
56.2%
ASCII 34274
43.8%
Compat Jamo 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14149
41.3%
1 4192
 
12.2%
0 3175
 
9.3%
- 2166
 
6.3%
2 2052
 
6.0%
3 1440
 
4.2%
5 1241
 
3.6%
4 1206
 
3.5%
6 1080
 
3.2%
8 973
 
2.8%
Other values (28) 2600
 
7.6%
Hangul
ValueCountFrequency (%)
5830
 
13.3%
3588
 
8.2%
3436
 
7.8%
3021
 
6.9%
2969
 
6.8%
2963
 
6.7%
2951
 
6.7%
2282
 
5.2%
1138
 
2.6%
911
 
2.1%
Other values (325) 14814
33.7%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Arrows
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1943
Distinct (%)92.3%
Missing830
Missing (%)28.3%
Memory size23.1 KiB
2024-04-18T02:41:04.777454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length51
Mean length31.568851
Min length20

Characters and Unicode

Total characters66484
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

Unique1873 ?
Unique (%)88.9%

Sample

1st row대구광역시 중구 동덕로30길 63-4 (동인동4가, 지상1층)
2nd row대구광역시 중구 명덕로 243 (대봉동, 지상1층)
3rd row대구광역시 중구 달구벌대로447길 44-28 (삼덕동3가, 지상1층)
4th row대구광역시 중구 달구벌대로 2077 (계산동2가, 현대백화점 식품관)
5th row대구광역시 중구 국채보상로 607 (문화동, 지상1층)
ValueCountFrequency (%)
대구광역시 2107
 
16.0%
1층 655
 
5.0%
달서구 440
 
3.3%
북구 383
 
2.9%
수성구 363
 
2.8%
중구 278
 
2.1%
동구 252
 
1.9%
달구벌대로 178
 
1.4%
달성군 146
 
1.1%
남구 137
 
1.0%
Other values (2265) 8214
62.4%
2024-04-18T02:41:05.163577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11047
 
16.6%
4547
 
6.8%
1 3264
 
4.9%
3033
 
4.6%
3004
 
4.5%
2196
 
3.3%
2164
 
3.3%
2118
 
3.2%
2098
 
3.2%
) 2096
 
3.2%
Other values (389) 30917
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38390
57.7%
Space Separator 11047
 
16.6%
Decimal Number 10485
 
15.8%
Close Punctuation 2096
 
3.2%
Open Punctuation 2096
 
3.2%
Other Punctuation 1965
 
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 (%)
4547
 
11.8%
3033
 
7.9%
3004
 
7.8%
2196
 
5.7%
2164
 
5.6%
2118
 
5.5%
2098
 
5.5%
1113
 
2.9%
954
 
2.5%
880
 
2.3%
Other values (340) 16283
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%
D 5
 
4.4%
H 5
 
4.4%
K 4
 
3.5%
L 3
 
2.6%
R 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%
n 1
 
4.2%
m 1
 
4.2%
d 1
 
4.2%
l 1
 
4.2%
t 1
 
4.2%
w 1
 
4.2%
Other values (2) 2
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 3264
31.1%
2 1449
13.8%
0 1195
 
11.4%
3 949
 
9.1%
4 760
 
7.2%
5 712
 
6.8%
6 631
 
6.0%
7 613
 
5.8%
9 465
 
4.4%
8 447
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 1953
99.4%
. 9
 
0.5%
/ 3
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 14
82.4%
+ 3
 
17.6%
Space Separator
ValueCountFrequency (%)
11047
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2096
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2096
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 250
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38390
57.7%
Common 27956
42.0%
Latin 138
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4547
 
11.8%
3033
 
7.9%
3004
 
7.8%
2196
 
5.7%
2164
 
5.6%
2118
 
5.5%
2098
 
5.5%
1113
 
2.9%
954
 
2.5%
880
 
2.3%
Other values (340) 16283
42.4%
Latin
ValueCountFrequency (%)
A 34
24.6%
B 19
13.8%
C 12
 
8.7%
M 8
 
5.8%
e 8
 
5.8%
S 7
 
5.1%
D 5
 
3.6%
H 5
 
3.6%
K 4
 
2.9%
c 3
 
2.2%
Other values (20) 33
23.9%
Common
ValueCountFrequency (%)
11047
39.5%
1 3264
 
11.7%
) 2096
 
7.5%
( 2096
 
7.5%
, 1953
 
7.0%
2 1449
 
5.2%
0 1195
 
4.3%
3 949
 
3.4%
4 760
 
2.7%
5 712
 
2.5%
Other values (9) 2435
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38390
57.7%
ASCII 28094
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11047
39.3%
1 3264
 
11.6%
) 2096
 
7.5%
( 2096
 
7.5%
, 1953
 
7.0%
2 1449
 
5.2%
0 1195
 
4.3%
3 949
 
3.4%
4 760
 
2.7%
5 712
 
2.5%
Other values (39) 2573
 
9.2%
Hangul
ValueCountFrequency (%)
4547
 
11.8%
3033
 
7.9%
3004
 
7.8%
2196
 
5.7%
2164
 
5.6%
2118
 
5.5%
2098
 
5.5%
1113
 
2.9%
954
 
2.5%
880
 
2.3%
Other values (340) 16283
42.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct769
Distinct (%)36.8%
Missing847
Missing (%)28.8%
Infinite0
Infinite (%)0.0%
Mean42063.38
Minimum41002
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:05.279277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41002
5-th percentile41143
Q141559
median42027
Q342627
95-th percentile42925
Maximum43024
Range2022
Interquartile range (IQR)1068

Descriptive statistics

Standard deviation570.13346
Coefficient of variation (CV)0.013554152
Kurtosis-1.1467569
Mean42063.38
Median Absolute Deviation (MAD)508
Skewness-0.051067897
Sum87870401
Variance325052.16
MonotonicityNot monotonic
2024-04-18T02:41:05.386948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41936 75
 
2.6%
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%
42918 12
 
0.4%
Other values (759) 1836
62.5%
(Missing) 847
28.8%
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%
Distinct2312
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
2024-04-18T02:41:05.634834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length7.4683243
Min length1

Characters and Unicode

Total characters21927
Distinct characters674
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

Unique2017 ?
Unique (%)68.7%

Sample

1st row빵장수꽈배기 동인지점
2nd row모모
3rd row삼덕동베이커리까페
4th row(주)파블로코리아
5th row단석명가찰보리빵
ValueCountFrequency (%)
파리바게뜨 79
 
2.2%
베이커리 64
 
1.8%
뚜레쥬르 55
 
1.6%
마들렌베이커리 23
 
0.7%
크라운베이커리 22
 
0.6%
반월당고로케 20
 
0.6%
뉴욕베이커리 17
 
0.5%
대백베이커리 17
 
0.5%
빵굽는마을 17
 
0.5%
잇브레드 13
 
0.4%
Other values (2416) 3186
90.7%
2024-04-18T02:41:05.991688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1163
 
5.3%
976
 
4.5%
911
 
4.2%
758
 
3.5%
710
 
3.2%
578
 
2.6%
403
 
1.8%
370
 
1.7%
) 368
 
1.7%
( 367
 
1.7%
Other values (664) 15323
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19333
88.2%
Space Separator 578
 
2.6%
Lowercase Letter 565
 
2.6%
Uppercase Letter 517
 
2.4%
Close Punctuation 368
 
1.7%
Open Punctuation 367
 
1.7%
Decimal Number 164
 
0.7%
Other Punctuation 27
 
0.1%
Dash Punctuation 6
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1163
 
6.0%
976
 
5.0%
911
 
4.7%
758
 
3.9%
710
 
3.7%
403
 
2.1%
370
 
1.9%
337
 
1.7%
316
 
1.6%
293
 
1.5%
Other values (594) 13096
67.7%
Lowercase Letter
ValueCountFrequency (%)
e 88
15.6%
a 64
11.3%
o 58
 
10.3%
n 38
 
6.7%
i 37
 
6.5%
r 33
 
5.8%
k 28
 
5.0%
c 24
 
4.2%
s 24
 
4.2%
t 20
 
3.5%
Other values (15) 151
26.7%
Uppercase Letter
ValueCountFrequency (%)
B 48
 
9.3%
E 48
 
9.3%
A 45
 
8.7%
K 40
 
7.7%
R 39
 
7.5%
O 38
 
7.4%
M 28
 
5.4%
N 27
 
5.2%
S 25
 
4.8%
C 24
 
4.6%
Other values (14) 155
30.0%
Decimal Number
ValueCountFrequency (%)
2 45
27.4%
1 34
20.7%
3 21
12.8%
0 15
 
9.1%
5 13
 
7.9%
9 9
 
5.5%
6 9
 
5.5%
7 7
 
4.3%
8 6
 
3.7%
4 5
 
3.0%
Other Punctuation
ValueCountFrequency (%)
& 10
37.0%
. 8
29.6%
, 4
 
14.8%
: 3
 
11.1%
' 2
 
7.4%
Space Separator
ValueCountFrequency (%)
578
100.0%
Close Punctuation
ValueCountFrequency (%)
) 368
100.0%
Open Punctuation
ValueCountFrequency (%)
( 367
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 19325
88.1%
Common 1511
 
6.9%
Latin 1083
 
4.9%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1163
 
6.0%
976
 
5.1%
911
 
4.7%
758
 
3.9%
710
 
3.7%
403
 
2.1%
370
 
1.9%
337
 
1.7%
316
 
1.6%
293
 
1.5%
Other values (587) 13088
67.7%
Latin
ValueCountFrequency (%)
e 88
 
8.1%
a 64
 
5.9%
o 58
 
5.4%
B 48
 
4.4%
E 48
 
4.4%
A 45
 
4.2%
K 40
 
3.7%
R 39
 
3.6%
n 38
 
3.5%
O 38
 
3.5%
Other values (40) 577
53.3%
Common
ValueCountFrequency (%)
578
38.3%
) 368
24.4%
( 367
24.3%
2 45
 
3.0%
1 34
 
2.3%
3 21
 
1.4%
0 15
 
1.0%
5 13
 
0.9%
& 10
 
0.7%
9 9
 
0.6%
Other values (10) 51
 
3.4%
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 19325
88.1%
ASCII 2593
 
11.8%
CJK 6
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1163
 
6.0%
976
 
5.1%
911
 
4.7%
758
 
3.9%
710
 
3.7%
403
 
2.1%
370
 
1.9%
337
 
1.7%
316
 
1.6%
293
 
1.5%
Other values (587) 13088
67.7%
ASCII
ValueCountFrequency (%)
578
22.3%
) 368
14.2%
( 367
14.2%
e 88
 
3.4%
a 64
 
2.5%
o 58
 
2.2%
B 48
 
1.9%
E 48
 
1.9%
2 45
 
1.7%
A 45
 
1.7%
Other values (59) 884
34.1%
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)

Distinct2699
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0139473 × 1013
Minimum2.001081 × 1013
Maximum2.0220428 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:06.101902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001081 × 1013
5-th percentile2.0020924 × 1013
Q12.0090615 × 1013
median2.0151119 × 1013
Q32.0200219 × 1013
95-th percentile2.0211226 × 1013
Maximum2.0220428 × 1013
Range2.0961818 × 1011
Interquartile range (IQR)1.096045 × 1011

Descriptive statistics

Standard deviation6.4167411 × 1010
Coefficient of variation (CV)0.0031861515
Kurtosis-1.0487152
Mean2.0139473 × 1013
Median Absolute Deviation (MAD)4.9998427 × 1010
Skewness-0.50547052
Sum5.9129492 × 1016
Variance4.1174566 × 1021
MonotonicityNot monotonic
2024-04-18T02:41:06.197919image/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%
20020412000000 5
 
0.2%
Other values (2689) 2826
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 (%)
20220428175601 1
< 0.1%
20220428104521 1
< 0.1%
20220427162453 1
< 0.1%
20220426171531 1
< 0.1%
20220426144731 1
< 0.1%
20220425192036 1
< 0.1%
20220425141359 1
< 0.1%
20220425125632 1
< 0.1%
20220425125604 1
< 0.1%
20220425125445 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
I
1942 
U
994 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1942
66.1%
U 994
33.9%

Length

2024-04-18T02:41:06.291835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:06.362585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1942
66.1%
u 994
33.9%
Distinct620
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
Minimum2018-08-31 23:59:59
Maximum2022-04-30 02:40:00
2024-04-18T02:41:06.440053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:41:06.541759image/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 size23.1 KiB
제과점영업
2934 
푸드트럭
 
2

Length

Max length5
Median length5
Mean length4.9993188
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 2934
99.9%
푸드트럭 2
 
0.1%

Length

2024-04-18T02:41:06.635162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:06.705781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 2934
99.9%
푸드트럭 2
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2043
Distinct (%)71.5%
Missing79
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean343102.28
Minimum327860.09
Maximum358046.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:06.789319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327860.09
5-th percentile334615.96
Q1339575.37
median343588.74
Q3346207.18
95-th percentile353602.89
Maximum358046.4
Range30186.309
Interquartile range (IQR)6631.8151

Descriptive statistics

Standard deviation5205.3852
Coefficient of variation (CV)0.015171526
Kurtosis0.26667286
Mean343102.28
Median Absolute Deviation (MAD)3448.5064
Skewness0.095055923
Sum9.8024322 × 108
Variance27096035
MonotonicityNot monotonic
2024-04-18T02:41:06.886014image/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
 
1.0%
347037.24197 21
 
0.7%
344047.979265 17
 
0.6%
340320.72271 13
 
0.4%
339047.793379 12
 
0.4%
343705.561002 12
 
0.4%
347008.880529 12
 
0.4%
347060.417753 10
 
0.3%
Other values (2033) 2619
89.2%
(Missing) 79
 
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 

Distinct2042
Distinct (%)71.5%
Missing79
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean263310.95
Minimum240452.6
Maximum277860.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:06.986349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240452.6
5-th percentile257464.24
Q1261215.33
median263366.3
Q3265338.51
95-th percentile271412.22
Maximum277860.93
Range37408.331
Interquartile range (IQR)4123.1801

Descriptive statistics

Standard deviation4448.8762
Coefficient of variation (CV)0.016895903
Kurtosis4.3068895
Mean263310.95
Median Absolute Deviation (MAD)2041.1075
Skewness-0.89385037
Sum7.5227938 × 108
Variance19792499
MonotonicityNot monotonic
2024-04-18T02:41:07.326509image/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
 
1.0%
265407.404337 21
 
0.7%
264405.128696 17
 
0.6%
272735.67566 13
 
0.4%
265530.003516 12
 
0.4%
258741.90218 12
 
0.4%
264056.630949 12
 
0.4%
265732.622769 10
 
0.3%
Other values (2032) 2619
89.2%
(Missing) 79
 
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 size23.1 KiB
제과점영업
2934 
푸드트럭
 
2

Length

Max length5
Median length5
Mean length4.9993188
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 2934
99.9%
푸드트럭 2
 
0.1%

Length

2024-04-18T02:41:07.429679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:07.499065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 2934
99.9%
푸드트럭 2
 
0.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.7%
Missing1408
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean0.47382199
Minimum0
Maximum17
Zeros1072
Zeros (%)36.5%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:07.563068image/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 deviation1.0258457
Coefficient of variation (CV)2.1650446
Kurtosis64.854252
Mean0.47382199
Median Absolute Deviation (MAD)0
Skewness5.7650891
Sum724
Variance1.0523594
MonotonicityNot monotonic
2024-04-18T02:41:07.643158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 1072
36.5%
1 304
 
10.4%
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) 1408
48.0%
ValueCountFrequency (%)
0 1072
36.5%
1 304
 
10.4%
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
10.4%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)0.9%
Missing1328
Missing (%)45.2%
Infinite0
Infinite (%)0.0%
Mean0.69465174
Minimum0
Maximum47
Zeros1030
Zeros (%)35.1%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:07.727875image/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 deviation1.7205291
Coefficient of variation (CV)2.4768225
Kurtosis335.47227
Mean0.69465174
Median Absolute Deviation (MAD)0
Skewness13.829153
Sum1117
Variance2.9602203
MonotonicityNot monotonic
2024-04-18T02:41:07.805064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 1030
35.1%
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) 1328
45.2%
ValueCountFrequency (%)
0 1030
35.1%
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 size23.1 KiB
<NA>
1228 
기타
875 
주택가주변
395 
아파트지역
349 
유흥업소밀집지역
 
50
Other values (3)
 
39

Length

Max length8
Median length7
Mean length3.7782698
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1228
41.8%
기타 875
29.8%
주택가주변 395
 
13.5%
아파트지역 349
 
11.9%
유흥업소밀집지역 50
 
1.7%
학교정화(상대) 29
 
1.0%
학교정화(절대) 9
 
0.3%
결혼예식장주변 1
 
< 0.1%

Length

2024-04-18T02:41:07.898761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:07.986901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1228
41.8%
기타 875
29.8%
주택가주변 395
 
13.5%
아파트지역 349
 
11.9%
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 size23.1 KiB
<NA>
2055 
자율
643 
기타
235 
 
3

Length

Max length4
Median length4
Mean length3.398842
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2055
70.0%
자율 643
 
21.9%
기타 235
 
8.0%
3
 
0.1%

Length

2024-04-18T02:41:08.087639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:08.163170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2055
70.0%
자율 643
 
21.9%
기타 235
 
8.0%
3
 
0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
상수도전용
2257 
<NA>
676 
전용상수도(특정시설의 자가용 수도)
 
2
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length19
Median length5
Mean length4.7833787
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2257
76.9%
<NA> 676
 
23.0%
전용상수도(특정시설의 자가용 수도) 2
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2024-04-18T02:41:08.250679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:08.334936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2257
76.8%
na 676
 
23.0%
전용상수도(특정시설의 2
 
0.1%
자가용 2
 
0.1%
수도 2
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2644 
0
292 

Length

Max length4
Median length4
Mean length3.7016349
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2644
90.1%
0 292
 
9.9%

Length

2024-04-18T02:41:08.423765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:08.498590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2644
90.1%
0 292
 
9.9%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2637 
0
299 

Length

Max length4
Median length4
Mean length3.6944823
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2637
89.8%
0 299
 
10.2%

Length

2024-04-18T02:41:08.574559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:08.650203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2637
89.8%
0 299
 
10.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2637 
0
299 

Length

Max length4
Median length4
Mean length3.6944823
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2637
89.8%
0 299
 
10.2%

Length

2024-04-18T02:41:08.742403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:08.820100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2637
89.8%
0 299
 
10.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2637 
0
299 

Length

Max length4
Median length4
Mean length3.6944823
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2637
89.8%
0 299
 
10.2%

Length

2024-04-18T02:41:08.900127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:08.971514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2637
89.8%
0 299
 
10.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2637 
0
299 

Length

Max length4
Median length4
Mean length3.6944823
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2637
89.8%
0 299
 
10.2%

Length

2024-04-18T02:41:09.049342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:09.120667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2637
89.8%
0 299
 
10.2%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2936
Missing (%)100.0%
Memory size25.9 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2637 
0
299 

Length

Max length4
Median length4
Mean length3.6944823
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2637
89.8%
0 299
 
10.2%

Length

2024-04-18T02:41:09.220313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:09.313913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2637
89.8%
0 299
 
10.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2637 
0
299 

Length

Max length4
Median length4
Mean length3.6944823
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2637
89.8%
0 299
 
10.2%

Length

2024-04-18T02:41:09.391580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:41:09.464664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2637
89.8%
0 299
 
10.2%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
False
2897 
True
 
39
ValueCountFrequency (%)
False 2897
98.7%
True 39
 
1.3%
2024-04-18T02:41:09.524131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct1874
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.608644
Minimum0
Maximum1300
Zeros130
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-18T02:41:09.610465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.98
Q123.1425
median35.28
Q356.39
95-th percentile115.995
Maximum1300
Range1300
Interquartile range (IQR)33.2475

Descriptive statistics

Standard deviation52.340317
Coefficient of variation (CV)1.1229745
Kurtosis146.93062
Mean46.608644
Median Absolute Deviation (MAD)14.79
Skewness8.5344599
Sum136842.98
Variance2739.5088
MonotonicityNot monotonic
2024-04-18T02:41:09.716599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 130
 
4.4%
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%
27.0 11
 
0.4%
19.8 11
 
0.4%
40.0 11
 
0.4%
Other values (1864) 2679
91.2%
ValueCountFrequency (%)
0.0 130
4.4%
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%
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%
345.48 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2936
Missing (%)100.0%
Memory size25.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2936
Missing (%)100.0%
Memory size25.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2936
Missing (%)100.0%
Memory size25.9 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01제과점영업07_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>
12제과점영업07_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>
23제과점영업07_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>
34제과점영업07_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>
45제과점영업07_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>
56제과점영업07_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>
67제과점영업07_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>
78제과점영업07_22_18_P34100003410000-121-2005-0007520050727<NA>3폐업2폐업20070220<NA><NA><NA>053 251322014.47700070대구광역시 중구 덕산동 0053-0003번지<NA><NA>쿡마마오베르20050727000000I2018-08-31 23:59:59.0제과점영업343705.561002264056.630949제과점영업11기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N14.47<NA><NA><NA>
89제과점영업07_22_18_P34100003410000-121-2005-0006420050811<NA>3폐업2폐업20060509<NA><NA><NA><NA>61.05700180대구광역시 중구 동문동 20-11번지<NA><NA>(주)신라명과동아백화점직매장20050811000000I2018-08-31 23:59:59.0제과점영업344138.507492264773.346334제과점영업33기타자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N61.05<NA><NA><NA>
910제과점영업07_22_18_P34100003410000-121-2005-0006820050826<NA>3폐업2폐업20090907<NA><NA><NA><NA>11.28700811대구광역시 중구 대봉동 214번지<NA><NA>오픈테이블델리20050826000000I2018-08-31 23:59:59.0제과점영업345032.238221262949.871621제과점영업11기타자율상수도전용<NA>0000<NA>00N11.28<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
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29272928제과점영업07_22_18_P34800003480000-121-2016-0001120160909<NA>1영업/정상1영업<NA><NA><NA><NA>053 614 176740.13711873대구광역시 달성군 현풍면 중리 470-9번지 1층대구광역시 달성군 현풍면 테크노중앙대로5길 8, 1층43014파네디파파(pane di papa))20161220153326I2018-08-31 23:59:59.0제과점영업331651.937451245189.117708제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N40.13<NA><NA><NA>
29282929제과점영업07_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>
29292930제과점영업07_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>
29302931제과점영업07_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>
29312932제과점영업07_22_18_P34800003480000-121-2015-0000420151104<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.00711842대구광역시 달성군 옥포면 강림리 1168번지대구광역시 달성군 옥포면 돌미로2서길 3-4, 1층42974베이커리20160330163420I2018-08-31 23:59:59.0제과점영업329898.834237254152.127229제과점영업<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N24.0<NA><NA><NA>
29322933제과점영업07_22_18_P34800003480000-121-2016-0000120160201<NA>1영업/정상1영업<NA><NA><NA><NA><NA>73.60711842대구광역시 달성군 옥포면 강림리 1123번지대구광역시 달성군 옥포면 돌미로2서길 8, 1층 104,105호42974뚜레쥬르 대구옥포점20180619103117I2018-08-31 23:59:59.0제과점영업329894.345198254196.774067제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N73.6<NA><NA><NA>
29332934제과점영업07_22_18_P34800003480000-121-2016-0000320160310<NA>1영업/정상1영업<NA><NA><NA><NA><NA>95.57711843대구광역시 달성군 옥포면 교항리 2919번지대구광역시 달성군 옥포면 돌미상업로 9, 1층 105,106호42974파리바게트 대구옥포점20160422110702I2018-08-31 23:59:59.0제과점영업330283.226863254512.172379제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N95.57<NA><NA><NA>
29342935제과점영업07_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>
29352936제과점영업07_22_18_P34800003480000-121-2016-0000520160510<NA>1영업/정상1영업<NA><NA><NA><NA><NA>105.69711812대구광역시 달성군 다사읍 매곡리 1526번지 1층대구광역시 달성군 다사읍 대실역북로2길 137, 1층42911우리밀 레헴20160523094705I2018-08-31 23:59:59.0제과점영업332392.456162263776.054896제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N68.5<NA><NA><NA>