Overview

Dataset statistics

Number of variables47
Number of observations3757
Missing cells44308
Missing cells (%)25.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory406.0 B

Variable types

Numeric16
Categorical15
Text6
Unsupported8
DateTime1
Boolean1

Dataset

Description22년05월_6270000_대구광역시_07_22_11_P_식품제조가공업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000093418&dataSetDetailId=DDI_0000093463&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
남성종사자수 is highly imbalanced (51.7%)Imbalance
여성종사자수 is highly imbalanced (51.7%)Imbalance
급수시설구분명 is highly imbalanced (55.9%)Imbalance
총종업원수 is highly imbalanced (52.9%)Imbalance
다중이용업소여부 is highly imbalanced (99.3%)Imbalance
홈페이지 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3757 (100.0%) missing valuesMissing
폐업일자 has 1025 (27.3%) missing valuesMissing
휴업시작일자 has 3757 (100.0%) missing valuesMissing
휴업종료일자 has 3757 (100.0%) missing valuesMissing
재개업일자 has 3757 (100.0%) missing valuesMissing
소재지전화 has 1043 (27.8%) missing valuesMissing
소재지면적 has 136 (3.6%) missing valuesMissing
소재지우편번호 has 82 (2.2%) missing valuesMissing
도로명전체주소 has 1370 (36.5%) missing valuesMissing
도로명우편번호 has 1398 (37.2%) missing valuesMissing
좌표정보(X) has 172 (4.6%) missing valuesMissing
좌표정보(Y) has 172 (4.6%) missing valuesMissing
영업장주변구분명 has 3757 (100.0%) missing valuesMissing
등급구분명 has 3757 (100.0%) missing valuesMissing
본사종업원수 has 634 (16.9%) missing valuesMissing
공장사무직종업원수 has 625 (16.6%) missing valuesMissing
공장판매직종업원수 has 645 (17.2%) missing valuesMissing
공장생산직종업원수 has 553 (14.7%) missing valuesMissing
보증액 has 3185 (84.8%) missing valuesMissing
월세액 has 3186 (84.8%) missing valuesMissing
전통업소지정번호 has 3757 (100.0%) missing valuesMissing
전통업소주된음식 has 3757 (100.0%) missing valuesMissing
공장사무직종업원수 is highly skewed (γ1 = 22.18081448)Skewed
공장판매직종업원수 is highly skewed (γ1 = 28.61222269)Skewed
공장생산직종업원수 is highly skewed (γ1 = 34.51131645)Skewed
시설총규모 is highly skewed (γ1 = 28.74267218)Skewed
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
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 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
본사종업원수 has 3000 (79.9%) zerosZeros
공장사무직종업원수 has 2739 (72.9%) zerosZeros
공장판매직종업원수 has 2896 (77.1%) zerosZeros
공장생산직종업원수 has 2284 (60.8%) zerosZeros
보증액 has 508 (13.5%) zerosZeros
월세액 has 507 (13.5%) zerosZeros
시설총규모 has 2985 (79.5%) zerosZeros

Reproduction

Analysis started2024-04-18 05:12:43.582949
Analysis finished2024-04-18 05:12:44.943220
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3757
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1879
Minimum1
Maximum3757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:45.006812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile188.8
Q1940
median1879
Q32818
95-th percentile3569.2
Maximum3757
Range3756
Interquartile range (IQR)1878

Descriptive statistics

Standard deviation1084.6968
Coefficient of variation (CV)0.57727345
Kurtosis-1.2
Mean1879
Median Absolute Deviation (MAD)939
Skewness0
Sum7059403
Variance1176567.2
MonotonicityStrictly increasing
2024-04-18T14:12:45.138683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2510 1
 
< 0.1%
2498 1
 
< 0.1%
2499 1
 
< 0.1%
2500 1
 
< 0.1%
2501 1
 
< 0.1%
2502 1
 
< 0.1%
2503 1
 
< 0.1%
2504 1
 
< 0.1%
2505 1
 
< 0.1%
Other values (3747) 3747
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 (%)
3757 1
< 0.1%
3756 1
< 0.1%
3755 1
< 0.1%
3754 1
< 0.1%
3753 1
< 0.1%
3752 1
< 0.1%
3751 1
< 0.1%
3750 1
< 0.1%
3749 1
< 0.1%
3748 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
식품제조가공업
3757 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 3757
100.0%

Length

2024-04-18T14:12:45.270011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:45.405731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3757
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
07_22_11_P
3757 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_11_P
2nd row07_22_11_P
3rd row07_22_11_P
4th row07_22_11_P
5th row07_22_11_P

Common Values

ValueCountFrequency (%)
07_22_11_P 3757
100.0%

Length

2024-04-18T14:12:45.501848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:45.591200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_11_p 3757
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3449872.2
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:45.675843image/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 deviation20906.88
Coefficient of variation (CV)0.0060601896
Kurtosis-0.95667876
Mean3449872.2
Median Absolute Deviation (MAD)20000
Skewness-0.30084916
Sum1.296117 × 1010
Variance4.3709762 × 108
MonotonicityIncreasing
2024-04-18T14:12:45.781415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 947
25.2%
3470000 643
17.1%
3480000 469
12.5%
3420000 434
11.6%
3460000 432
11.5%
3430000 370
 
9.8%
3440000 239
 
6.4%
3410000 223
 
5.9%
ValueCountFrequency (%)
3410000 223
 
5.9%
3420000 434
11.6%
3430000 370
 
9.8%
3440000 239
 
6.4%
3450000 947
25.2%
3460000 432
11.5%
3470000 643
17.1%
3480000 469
12.5%
ValueCountFrequency (%)
3480000 469
12.5%
3470000 643
17.1%
3460000 432
11.5%
3450000 947
25.2%
3440000 239
 
6.4%
3430000 370
 
9.8%
3420000 434
11.6%
3410000 223
 
5.9%

관리번호
Text

UNIQUE 

Distinct3757
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
2024-04-18T14:12:45.966095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters82654
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

Unique3757 ?
Unique (%)100.0%

Sample

1st row3410000-106-2004-00002
2nd row3410000-106-2004-00003
3rd row3410000-106-2004-00004
4th row3410000-106-2004-00005
5th row3410000-106-2004-00006
ValueCountFrequency (%)
3410000-106-2004-00002 1
 
< 0.1%
3460000-106-2007-00018 1
 
< 0.1%
3460000-106-2011-00002 1
 
< 0.1%
3460000-106-2013-00003 1
 
< 0.1%
3460000-106-2011-00003 1
 
< 0.1%
3460000-106-2011-00004 1
 
< 0.1%
3460000-106-2011-00005 1
 
< 0.1%
3460000-106-2011-00006 1
 
< 0.1%
3460000-106-2010-00007 1
 
< 0.1%
3460000-106-2010-00014 1
 
< 0.1%
Other values (3747) 3747
99.7%
2024-04-18T14:12:46.284979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37688
45.6%
- 11271
 
13.6%
1 7927
 
9.6%
2 5537
 
6.7%
3 5116
 
6.2%
6 4928
 
6.0%
4 4819
 
5.8%
5 1693
 
2.0%
7 1357
 
1.6%
9 1174
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71383
86.4%
Dash Punctuation 11271
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37688
52.8%
1 7927
 
11.1%
2 5537
 
7.8%
3 5116
 
7.2%
6 4928
 
6.9%
4 4819
 
6.8%
5 1693
 
2.4%
7 1357
 
1.9%
9 1174
 
1.6%
8 1144
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 11271
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 82654
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37688
45.6%
- 11271
 
13.6%
1 7927
 
9.6%
2 5537
 
6.7%
3 5116
 
6.2%
6 4928
 
6.0%
4 4819
 
5.8%
5 1693
 
2.0%
7 1357
 
1.6%
9 1174
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82654
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37688
45.6%
- 11271
 
13.6%
1 7927
 
9.6%
2 5537
 
6.7%
3 5116
 
6.2%
6 4928
 
6.0%
4 4819
 
5.8%
5 1693
 
2.0%
7 1357
 
1.6%
9 1174
 
1.4%

인허가일자
Real number (ℝ)

Distinct2670
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20088561
Minimum19681218
Maximum20220526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:46.446457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19681218
5-th percentile19980321
Q120031023
median20090925
Q320150225
95-th percentile20200609
Maximum20220526
Range539308
Interquartile range (IQR)119202

Descriptive statistics

Standard deviation74731.955
Coefficient of variation (CV)0.0037201249
Kurtosis1.4462996
Mean20088561
Median Absolute Deviation (MAD)59587
Skewness-0.633752
Sum7.5472722 × 1010
Variance5.5848651 × 109
MonotonicityNot monotonic
2024-04-18T14:12:46.587386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000302 28
 
0.7%
19960320 19
 
0.5%
19960516 7
 
0.2%
20110520 6
 
0.2%
19930320 6
 
0.2%
20071108 5
 
0.1%
20160523 5
 
0.1%
20130725 5
 
0.1%
20180706 5
 
0.1%
20150319 4
 
0.1%
Other values (2660) 3667
97.6%
ValueCountFrequency (%)
19681218 1
< 0.1%
19700224 1
< 0.1%
19710528 1
< 0.1%
19720522 1
< 0.1%
19720817 1
< 0.1%
19730502 1
< 0.1%
19740326 1
< 0.1%
19740803 1
< 0.1%
19741016 1
< 0.1%
19741220 1
< 0.1%
ValueCountFrequency (%)
20220526 1
< 0.1%
20220518 2
0.1%
20220513 1
< 0.1%
20220512 1
< 0.1%
20220511 2
0.1%
20220425 1
< 0.1%
20220421 1
< 0.1%
20220418 1
< 0.1%
20220415 1
< 0.1%
20220412 2
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3757
Missing (%)100.0%
Memory size33.1 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
3
2732 
1
1025 

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 2732
72.7%
1 1025
 
27.3%

Length

2024-04-18T14:12:46.710529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:46.802058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2732
72.7%
1 1025
 
27.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
폐업
2732 
영업/정상
1025 

Length

Max length5
Median length2
Mean length2.8184722
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2732
72.7%
영업/정상 1025
 
27.3%

Length

2024-04-18T14:12:46.901142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:47.065768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2732
72.7%
영업/정상 1025
 
27.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
2
2732 
1
1025 

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 2732
72.7%
1 1025
 
27.3%

Length

2024-04-18T14:12:47.168728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:47.290307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2732
72.7%
1 1025
 
27.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
폐업
2732 
영업
1025 

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 2732
72.7%
영업 1025
 
27.3%

Length

2024-04-18T14:12:47.388605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:47.493460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2732
72.7%
영업 1025
 
27.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct2024
Distinct (%)74.1%
Missing1025
Missing (%)27.3%
Infinite0
Infinite (%)0.0%
Mean20116843
Minimum20000424
Maximum20220527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:47.604141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000424
5-th percentile20030305
Q120061228
median20120324
Q320170214
95-th percentile20210217
Maximum20220527
Range220103
Interquartile range (IQR)108985.75

Descriptive statistics

Standard deviation58149.488
Coefficient of variation (CV)0.0028905872
Kurtosis-1.1889414
Mean20116843
Median Absolute Deviation (MAD)50091.5
Skewness-0.015217876
Sum5.4959214 × 1010
Variance3.381363 × 109
MonotonicityNot monotonic
2024-04-18T14:12:48.627959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20181226 6
 
0.2%
20101231 6
 
0.2%
20181127 5
 
0.1%
20030711 5
 
0.1%
20160127 4
 
0.1%
20120206 4
 
0.1%
20151203 4
 
0.1%
20111221 4
 
0.1%
20100715 4
 
0.1%
20150511 4
 
0.1%
Other values (2014) 2686
71.5%
(Missing) 1025
 
27.3%
ValueCountFrequency (%)
20000424 1
< 0.1%
20000512 1
< 0.1%
20000621 1
< 0.1%
20000905 1
< 0.1%
20000928 2
0.1%
20001106 1
< 0.1%
20001121 1
< 0.1%
20001217 1
< 0.1%
20010129 1
< 0.1%
20010212 1
< 0.1%
ValueCountFrequency (%)
20220527 1
< 0.1%
20220518 1
< 0.1%
20220428 1
< 0.1%
20220425 1
< 0.1%
20220421 1
< 0.1%
20220413 2
0.1%
20220401 1
< 0.1%
20220331 1
< 0.1%
20220330 2
0.1%
20220315 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3757
Missing (%)100.0%
Memory size33.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3757
Missing (%)100.0%
Memory size33.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3757
Missing (%)100.0%
Memory size33.1 KiB

소재지전화
Text

MISSING 

Distinct2514
Distinct (%)92.6%
Missing1043
Missing (%)27.8%
Memory size29.5 KiB
2024-04-18T14:12:48.912103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.848563
Min length3

Characters and Unicode

Total characters29443
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

Unique2326 ?
Unique (%)85.7%

Sample

1st row053 4244979
2nd row053 2564337
3rd row053 4240540
4th row053 4223318
5th row053 4294238
ValueCountFrequency (%)
053 1999
34.9%
070 69
 
1.2%
311 21
 
0.4%
313 15
 
0.3%
621 13
 
0.2%
314 13
 
0.2%
983 12
 
0.2%
767 12
 
0.2%
615 11
 
0.2%
611 11
 
0.2%
Other values (2672) 3554
62.0%
2024-04-18T14:12:49.349868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4859
16.5%
3 4295
14.6%
0 4219
14.3%
3097
10.5%
2 2101
7.1%
6 2080
7.1%
1 2037
6.9%
7 1870
 
6.4%
8 1768
 
6.0%
4 1632
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26346
89.5%
Space Separator 3097
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4859
18.4%
3 4295
16.3%
0 4219
16.0%
2 2101
8.0%
6 2080
7.9%
1 2037
7.7%
7 1870
 
7.1%
8 1768
 
6.7%
4 1632
 
6.2%
9 1485
 
5.6%
Space Separator
ValueCountFrequency (%)
3097
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29443
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4859
16.5%
3 4295
14.6%
0 4219
14.3%
3097
10.5%
2 2101
7.1%
6 2080
7.1%
1 2037
6.9%
7 1870
 
6.4%
8 1768
 
6.0%
4 1632
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29443
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4859
16.5%
3 4295
14.6%
0 4219
14.3%
3097
10.5%
2 2101
7.1%
6 2080
7.1%
1 2037
6.9%
7 1870
 
6.4%
8 1768
 
6.0%
4 1632
 
5.5%

소재지면적
Text

MISSING 

Distinct2618
Distinct (%)72.3%
Missing136
Missing (%)3.6%
Memory size29.5 KiB
2024-04-18T14:12:49.702061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.3769677
Min length3

Characters and Unicode

Total characters19470
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

Unique2139 ?
Unique (%)59.1%

Sample

1st row14.70
2nd row41.85
3rd row120.60
4th row34.52
5th row25.23
ValueCountFrequency (%)
66.00 30
 
0.8%
20.00 25
 
0.7%
33.00 25
 
0.7%
00 17
 
0.5%
40.00 17
 
0.5%
26.40 14
 
0.4%
30.00 13
 
0.4%
132.00 12
 
0.3%
15.00 12
 
0.3%
38.00 12
 
0.3%
Other values (2608) 3444
95.1%
2024-04-18T14:12:50.153012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3621
18.6%
0 3375
17.3%
1 1775
9.1%
2 1725
8.9%
3 1437
 
7.4%
4 1430
 
7.3%
5 1369
 
7.0%
6 1352
 
6.9%
8 1168
 
6.0%
7 1104
 
5.7%
Other values (2) 1114
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15777
81.0%
Other Punctuation 3693
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3375
21.4%
1 1775
11.3%
2 1725
10.9%
3 1437
9.1%
4 1430
9.1%
5 1369
8.7%
6 1352
8.6%
8 1168
 
7.4%
7 1104
 
7.0%
9 1042
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 3621
98.1%
, 72
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 19470
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3621
18.6%
0 3375
17.3%
1 1775
9.1%
2 1725
8.9%
3 1437
 
7.4%
4 1430
 
7.3%
5 1369
 
7.0%
6 1352
 
6.9%
8 1168
 
6.0%
7 1104
 
5.7%
Other values (2) 1114
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3621
18.6%
0 3375
17.3%
1 1775
9.1%
2 1725
8.9%
3 1437
 
7.4%
4 1430
 
7.3%
5 1369
 
7.0%
6 1352
 
6.9%
8 1168
 
6.0%
7 1104
 
5.7%
Other values (2) 1114
 
5.7%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct551
Distinct (%)15.0%
Missing82
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean704586.22
Minimum700010
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:50.294757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700835.4
Q1702805.5
median703833
Q3705823
95-th percentile711850.3
Maximum711893
Range11883
Interquartile range (IQR)3017.5

Descriptive statistics

Standard deviation3086.0433
Coefficient of variation (CV)0.0043799371
Kurtosis0.76842421
Mean704586.22
Median Absolute Deviation (MAD)1761
Skewness1.1821377
Sum2.5893544 × 109
Variance9523663.3
MonotonicityNot monotonic
2024-04-18T14:12:50.449010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 89
 
2.4%
702061 80
 
2.1%
703830 57
 
1.5%
703833 48
 
1.3%
702816 45
 
1.2%
704080 42
 
1.1%
704900 36
 
1.0%
702903 35
 
0.9%
701140 34
 
0.9%
711851 34
 
0.9%
Other values (541) 3175
84.5%
(Missing) 82
 
2.2%
ValueCountFrequency (%)
700010 2
 
0.1%
700020 1
 
< 0.1%
700030 1
 
< 0.1%
700040 1
 
< 0.1%
700050 3
0.1%
700060 1
 
< 0.1%
700070 1
 
< 0.1%
700082 3
0.1%
700091 1
 
< 0.1%
700092 6
0.2%
ValueCountFrequency (%)
711893 8
 
0.2%
711892 9
0.2%
711891 9
0.2%
711874 3
 
0.1%
711871 9
0.2%
711864 12
0.3%
711863 21
0.6%
711862 3
 
0.1%
711861 2
 
0.1%
711858 11
0.3%
Distinct3496
Distinct (%)93.7%
Missing26
Missing (%)0.7%
Memory size29.5 KiB
2024-04-18T14:12:50.821794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length49
Mean length23.889842
Min length15

Characters and Unicode

Total characters89133
Distinct characters296
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

Unique3293 ?
Unique (%)88.3%

Sample

1st row대구광역시 중구 태평로1가 0001-0186번지
2nd row대구광역시 중구 남산동 2466-0001번지 보성황실아파트 116동 105호
3rd row대구광역시 중구 봉산동 0165-0007번지
4th row대구광역시 중구 동인동3가 0302-0002번지
5th row대구광역시 중구 동인동1가 0196번지
ValueCountFrequency (%)
대구광역시 3731
22.3%
북구 940
 
5.6%
달서구 640
 
3.8%
달성군 465
 
2.8%
동구 434
 
2.6%
수성구 420
 
2.5%
서구 371
 
2.2%
남구 238
 
1.4%
중구 223
 
1.3%
지상1층 201
 
1.2%
Other values (3882) 9092
54.3%
2024-04-18T14:12:51.319437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16717
18.8%
7100
 
8.0%
1 4431
 
5.0%
4059
 
4.6%
3972
 
4.5%
3785
 
4.2%
3736
 
4.2%
3736
 
4.2%
3534
 
4.0%
- 3112
 
3.5%
Other values (286) 34951
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49815
55.9%
Decimal Number 18536
 
20.8%
Space Separator 16717
 
18.8%
Dash Punctuation 3112
 
3.5%
Close Punctuation 347
 
0.4%
Open Punctuation 347
 
0.4%
Other Punctuation 126
 
0.1%
Uppercase Letter 117
 
0.1%
Math Symbol 13
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7100
14.3%
4059
 
8.1%
3972
 
8.0%
3785
 
7.6%
3736
 
7.5%
3736
 
7.5%
3534
 
7.1%
3020
 
6.1%
1184
 
2.4%
1172
 
2.4%
Other values (257) 14517
29.1%
Decimal Number
ValueCountFrequency (%)
1 4431
23.9%
2 2334
12.6%
0 2037
11.0%
3 1905
10.3%
4 1559
 
8.4%
5 1438
 
7.8%
6 1340
 
7.2%
7 1250
 
6.7%
8 1141
 
6.2%
9 1101
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 52
44.4%
A 49
41.9%
C 8
 
6.8%
T 2
 
1.7%
E 2
 
1.7%
D 2
 
1.7%
P 1
 
0.9%
J 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 116
92.1%
. 7
 
5.6%
/ 2
 
1.6%
: 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
c 1
33.3%
Space Separator
ValueCountFrequency (%)
16717
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3112
100.0%
Close Punctuation
ValueCountFrequency (%)
) 347
100.0%
Open Punctuation
ValueCountFrequency (%)
( 347
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49815
55.9%
Common 39198
44.0%
Latin 120
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7100
14.3%
4059
 
8.1%
3972
 
8.0%
3785
 
7.6%
3736
 
7.5%
3736
 
7.5%
3534
 
7.1%
3020
 
6.1%
1184
 
2.4%
1172
 
2.4%
Other values (257) 14517
29.1%
Common
ValueCountFrequency (%)
16717
42.6%
1 4431
 
11.3%
- 3112
 
7.9%
2 2334
 
6.0%
0 2037
 
5.2%
3 1905
 
4.9%
4 1559
 
4.0%
5 1438
 
3.7%
6 1340
 
3.4%
7 1250
 
3.2%
Other values (9) 3075
 
7.8%
Latin
ValueCountFrequency (%)
B 52
43.3%
A 49
40.8%
C 8
 
6.7%
T 2
 
1.7%
E 2
 
1.7%
D 2
 
1.7%
e 2
 
1.7%
P 1
 
0.8%
J 1
 
0.8%
c 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49815
55.9%
ASCII 39318
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16717
42.5%
1 4431
 
11.3%
- 3112
 
7.9%
2 2334
 
5.9%
0 2037
 
5.2%
3 1905
 
4.8%
4 1559
 
4.0%
5 1438
 
3.7%
6 1340
 
3.4%
7 1250
 
3.2%
Other values (19) 3195
 
8.1%
Hangul
ValueCountFrequency (%)
7100
14.3%
4059
 
8.1%
3972
 
8.0%
3785
 
7.6%
3736
 
7.5%
3736
 
7.5%
3534
 
7.1%
3020
 
6.1%
1184
 
2.4%
1172
 
2.4%
Other values (257) 14517
29.1%

도로명전체주소
Text

MISSING 

Distinct2279
Distinct (%)95.5%
Missing1370
Missing (%)36.5%
Memory size29.5 KiB
2024-04-18T14:12:51.679981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length54
Mean length27.764558
Min length20

Characters and Unicode

Total characters66274
Distinct characters320
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2180 ?
Unique (%)91.3%

Sample

1st row대구광역시 중구 남산로13길 17, 1층 (남산동, 보성황실아파트 116동 105호)
2nd row대구광역시 중구 동덕로30길 139-24, 1층 (동인동4가)
3rd row대구광역시 중구 서성로14길 85 (대안동, 지상2층)
4th row대구광역시 중구 남산로 23-15, 1층 (남산동)
5th row대구광역시 중구 달성공원로6길 8, 지상 1층 (대신동)
ValueCountFrequency (%)
대구광역시 2387
 
17.9%
북구 610
 
4.6%
1층 541
 
4.1%
달서구 350
 
2.6%
달성군 311
 
2.3%
동구 293
 
2.2%
수성구 280
 
2.1%
서구 236
 
1.8%
남구 155
 
1.2%
중구 152
 
1.1%
Other values (2611) 8019
60.1%
2024-04-18T14:12:52.171575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10948
 
16.5%
4693
 
7.1%
1 2952
 
4.5%
2884
 
4.4%
2878
 
4.3%
2487
 
3.8%
2406
 
3.6%
2388
 
3.6%
) 2195
 
3.3%
( 2195
 
3.3%
Other values (310) 30248
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37963
57.3%
Space Separator 10948
 
16.5%
Decimal Number 10753
 
16.2%
Close Punctuation 2195
 
3.3%
Open Punctuation 2195
 
3.3%
Other Punctuation 1297
 
2.0%
Dash Punctuation 755
 
1.1%
Uppercase Letter 143
 
0.2%
Math Symbol 23
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4693
 
12.4%
2884
 
7.6%
2878
 
7.6%
2487
 
6.6%
2406
 
6.3%
2388
 
6.3%
2184
 
5.8%
1669
 
4.4%
1014
 
2.7%
978
 
2.6%
Other values (278) 14382
37.9%
Uppercase Letter
ValueCountFrequency (%)
B 61
42.7%
A 53
37.1%
C 11
 
7.7%
T 4
 
2.8%
E 3
 
2.1%
D 3
 
2.1%
J 2
 
1.4%
P 2
 
1.4%
G 1
 
0.7%
M 1
 
0.7%
Other values (2) 2
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 2952
27.5%
2 1609
15.0%
3 1267
11.8%
4 912
 
8.5%
5 854
 
7.9%
6 767
 
7.1%
0 687
 
6.4%
7 659
 
6.1%
8 565
 
5.3%
9 481
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 1289
99.4%
· 4
 
0.3%
. 4
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
10948
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2195
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2195
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 755
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37963
57.3%
Common 28166
42.5%
Latin 145
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4693
 
12.4%
2884
 
7.6%
2878
 
7.6%
2487
 
6.6%
2406
 
6.3%
2388
 
6.3%
2184
 
5.8%
1669
 
4.4%
1014
 
2.7%
978
 
2.6%
Other values (278) 14382
37.9%
Common
ValueCountFrequency (%)
10948
38.9%
1 2952
 
10.5%
) 2195
 
7.8%
( 2195
 
7.8%
2 1609
 
5.7%
, 1289
 
4.6%
3 1267
 
4.5%
4 912
 
3.2%
5 854
 
3.0%
6 767
 
2.7%
Other values (8) 3178
 
11.3%
Latin
ValueCountFrequency (%)
B 61
42.1%
A 53
36.6%
C 11
 
7.6%
T 4
 
2.8%
E 3
 
2.1%
D 3
 
2.1%
J 2
 
1.4%
P 2
 
1.4%
G 1
 
0.7%
M 1
 
0.7%
Other values (4) 4
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37963
57.3%
ASCII 28307
42.7%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10948
38.7%
1 2952
 
10.4%
) 2195
 
7.8%
( 2195
 
7.8%
2 1609
 
5.7%
, 1289
 
4.6%
3 1267
 
4.5%
4 912
 
3.2%
5 854
 
3.0%
6 767
 
2.7%
Other values (21) 3319
 
11.7%
Hangul
ValueCountFrequency (%)
4693
 
12.4%
2884
 
7.6%
2878
 
7.6%
2487
 
6.6%
2406
 
6.3%
2388
 
6.3%
2184
 
5.8%
1669
 
4.4%
1014
 
2.7%
978
 
2.6%
Other values (278) 14382
37.9%
None
ValueCountFrequency (%)
· 4
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct815
Distinct (%)34.5%
Missing1398
Missing (%)37.2%
Infinite0
Infinite (%)0.0%
Mean42015.048
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:52.332420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41109
Q141489.5
median41931
Q342662
95-th percentile42972.2
Maximum43024
Range2024
Interquartile range (IQR)1172.5

Descriptive statistics

Standard deviation615.95581
Coefficient of variation (CV)0.014660362
Kurtosis-1.2943726
Mean42015.048
Median Absolute Deviation (MAD)490
Skewness0.17147948
Sum99113498
Variance379401.56
MonotonicityNot monotonic
2024-04-18T14:12:52.483030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41485 44
 
1.2%
41582 40
 
1.1%
41490 36
 
1.0%
41557 23
 
0.6%
41488 23
 
0.6%
41755 19
 
0.5%
42970 18
 
0.5%
42975 18
 
0.5%
42703 18
 
0.5%
41123 16
 
0.4%
Other values (805) 2104
56.0%
(Missing) 1398
37.2%
ValueCountFrequency (%)
41000 8
0.2%
41001 3
 
0.1%
41002 4
0.1%
41005 1
 
< 0.1%
41007 4
0.1%
41008 2
 
0.1%
41009 4
0.1%
41015 1
 
< 0.1%
41016 1
 
< 0.1%
41017 1
 
< 0.1%
ValueCountFrequency (%)
43024 1
 
< 0.1%
43023 5
0.1%
43022 1
 
< 0.1%
43013 2
 
0.1%
43012 1
 
< 0.1%
43011 6
0.2%
43009 1
 
< 0.1%
43008 2
 
0.1%
43007 1
 
< 0.1%
43006 4
0.1%
Distinct3174
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
2024-04-18T14:12:52.765805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length5.8908704
Min length1

Characters and Unicode

Total characters22132
Distinct characters764
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2765 ?
Unique (%)73.6%

Sample

1st row동북상회
2nd row황실떡집
3rd row에프엔에스
4th row이유통
5th row불스푸드
ValueCountFrequency (%)
주식회사 95
 
2.3%
농업회사법인 15
 
0.4%
우리식품 14
 
0.3%
커피 14
 
0.3%
14
 
0.3%
푸드 12
 
0.3%
coffee 11
 
0.3%
제일식품 11
 
0.3%
현대식품 9
 
0.2%
food 9
 
0.2%
Other values (3352) 4000
95.1%
2024-04-18T14:12:53.184322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1246
 
5.6%
1091
 
4.9%
630
 
2.8%
) 596
 
2.7%
( 588
 
2.7%
470
 
2.1%
449
 
2.0%
441
 
2.0%
402
 
1.8%
358
 
1.6%
Other values (754) 15861
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19473
88.0%
Close Punctuation 596
 
2.7%
Open Punctuation 588
 
2.7%
Uppercase Letter 482
 
2.2%
Space Separator 449
 
2.0%
Lowercase Letter 422
 
1.9%
Decimal Number 61
 
0.3%
Other Punctuation 58
 
0.3%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1246
 
6.4%
1091
 
5.6%
630
 
3.2%
470
 
2.4%
441
 
2.3%
402
 
2.1%
358
 
1.8%
323
 
1.7%
307
 
1.6%
297
 
1.5%
Other values (687) 13908
71.4%
Uppercase Letter
ValueCountFrequency (%)
F 48
 
10.0%
O 43
 
8.9%
C 38
 
7.9%
S 36
 
7.5%
B 33
 
6.8%
N 26
 
5.4%
T 25
 
5.2%
D 24
 
5.0%
M 23
 
4.8%
E 21
 
4.4%
Other values (14) 165
34.2%
Lowercase Letter
ValueCountFrequency (%)
e 78
18.5%
o 62
14.7%
f 36
8.5%
n 33
 
7.8%
a 31
 
7.3%
s 22
 
5.2%
c 22
 
5.2%
r 20
 
4.7%
t 18
 
4.3%
d 15
 
3.6%
Other values (13) 85
20.1%
Decimal Number
ValueCountFrequency (%)
2 14
23.0%
1 12
19.7%
3 9
14.8%
5 6
9.8%
6 5
 
8.2%
4 4
 
6.6%
9 3
 
4.9%
0 3
 
4.9%
8 3
 
4.9%
7 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
& 35
60.3%
. 15
25.9%
, 3
 
5.2%
' 3
 
5.2%
· 2
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 596
100.0%
Open Punctuation
ValueCountFrequency (%)
( 588
100.0%
Space Separator
ValueCountFrequency (%)
449
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19468
88.0%
Common 1755
 
7.9%
Latin 904
 
4.1%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1246
 
6.4%
1091
 
5.6%
630
 
3.2%
470
 
2.4%
441
 
2.3%
402
 
2.1%
358
 
1.8%
323
 
1.7%
307
 
1.6%
297
 
1.5%
Other values (682) 13903
71.4%
Latin
ValueCountFrequency (%)
e 78
 
8.6%
o 62
 
6.9%
F 48
 
5.3%
O 43
 
4.8%
C 38
 
4.2%
f 36
 
4.0%
S 36
 
4.0%
n 33
 
3.7%
B 33
 
3.7%
a 31
 
3.4%
Other values (37) 466
51.5%
Common
ValueCountFrequency (%)
) 596
34.0%
( 588
33.5%
449
25.6%
& 35
 
2.0%
. 15
 
0.9%
2 14
 
0.8%
1 12
 
0.7%
3 9
 
0.5%
5 6
 
0.3%
6 5
 
0.3%
Other values (10) 26
 
1.5%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19468
88.0%
ASCII 2657
 
12.0%
CJK 5
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1246
 
6.4%
1091
 
5.6%
630
 
3.2%
470
 
2.4%
441
 
2.3%
402
 
2.1%
358
 
1.8%
323
 
1.7%
307
 
1.6%
297
 
1.5%
Other values (682) 13903
71.4%
ASCII
ValueCountFrequency (%)
) 596
22.4%
( 588
22.1%
449
16.9%
e 78
 
2.9%
o 62
 
2.3%
F 48
 
1.8%
O 43
 
1.6%
C 38
 
1.4%
f 36
 
1.4%
S 36
 
1.4%
Other values (56) 683
25.7%
None
ValueCountFrequency (%)
· 2
100.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

최종수정시점
Real number (ℝ)

Distinct3351
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0131651 × 1013
Minimum2.001082 × 1013
Maximum2.0220527 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:53.337551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001082 × 1013
5-th percentile2.0020708 × 1013
Q12.0070907 × 1013
median2.015052 × 1013
Q32.019093 × 1013
95-th percentile2.0220121 × 1013
Maximum2.0220527 × 1013
Range2.0970711 × 1011
Interquartile range (IQR)1.2002298 × 1011

Descriptive statistics

Standard deviation6.717294 × 1010
Coefficient of variation (CV)0.0033366831
Kurtosis-1.316438
Mean2.0131651 × 1013
Median Absolute Deviation (MAD)5.0405048 × 1010
Skewness-0.3324823
Sum7.5634612 × 1016
Variance4.5122039 × 1021
MonotonicityNot monotonic
2024-04-18T14:12:53.545447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020205000000 55
 
1.5%
20041011000000 23
 
0.6%
20020926000000 21
 
0.6%
20010821000000 18
 
0.5%
20030407000000 18
 
0.5%
20020508000000 14
 
0.4%
20020507000000 13
 
0.3%
20020509000000 13
 
0.3%
20031027000000 12
 
0.3%
20021108000000 12
 
0.3%
Other values (3341) 3558
94.7%
ValueCountFrequency (%)
20010820000000 4
 
0.1%
20010821000000 18
0.5%
20011108000000 2
 
0.1%
20011119000000 1
 
< 0.1%
20011122000000 1
 
< 0.1%
20011126000000 1
 
< 0.1%
20011128000000 3
 
0.1%
20011210000000 1
 
< 0.1%
20011226000000 1
 
< 0.1%
20011228000000 1
 
< 0.1%
ValueCountFrequency (%)
20220527110718 1
< 0.1%
20220526111852 1
< 0.1%
20220525105242 1
< 0.1%
20220524193153 1
< 0.1%
20220524173729 1
< 0.1%
20220524104627 1
< 0.1%
20220520105939 1
< 0.1%
20220520104721 1
< 0.1%
20220519101611 1
< 0.1%
20220518133243 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
I
2688 
U
1069 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2688
71.5%
U 1069
 
28.5%

Length

2024-04-18T14:12:53.687544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:53.799630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2688
71.5%
u 1069
 
28.5%
Distinct732
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
Minimum2018-08-31 23:59:59
Maximum2022-05-29 02:40:00
2024-04-18T14:12:53.912031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T14:12:54.059301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
식품제조가공업
2794 
기타 식품제조가공업
936 
도시락제조업
 
27

Length

Max length10
Median length7
Mean length7.7402183
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2794
74.4%
기타 식품제조가공업 936
 
24.9%
도시락제조업 27
 
0.7%

Length

2024-04-18T14:12:54.197638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:54.316926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3730
79.5%
기타 936
 
19.9%
도시락제조업 27
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3070
Distinct (%)85.6%
Missing172
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean341834.86
Minimum323038.14
Maximum356965.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:54.430217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum323038.14
5-th percentile331543.43
Q1338738.2
median341563.69
Q3345487.76
95-th percentile352819.77
Maximum356965.56
Range33927.418
Interquartile range (IQR)6749.563

Descriptive statistics

Standard deviation5839.2444
Coefficient of variation (CV)0.017082062
Kurtosis0.10335026
Mean341834.86
Median Absolute Deviation (MAD)3351.2976
Skewness-0.032669032
Sum1.225478 × 109
Variance34096775
MonotonicityNot monotonic
2024-04-18T14:12:54.573508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
339243.983122 27
 
0.7%
334406.500396 7
 
0.2%
348434.155718 5
 
0.1%
346004.036082 5
 
0.1%
335619.487404 4
 
0.1%
326739.522357 4
 
0.1%
338678.797273 4
 
0.1%
343157.682044 4
 
0.1%
346828.290809 4
 
0.1%
332327.523657 4
 
0.1%
Other values (3060) 3517
93.6%
(Missing) 172
 
4.6%
ValueCountFrequency (%)
323038.137302 1
 
< 0.1%
323583.427786 1
 
< 0.1%
325649.192591 1
 
< 0.1%
325694.253396 1
 
< 0.1%
326018.881016 1
 
< 0.1%
326032.481595 1
 
< 0.1%
326631.950345 1
 
< 0.1%
326739.522357 4
0.1%
326760.851184 1
 
< 0.1%
326950.230819 1
 
< 0.1%
ValueCountFrequency (%)
356965.555233 1
 
< 0.1%
356410.892344 1
 
< 0.1%
356370.038499 1
 
< 0.1%
356353.91544 1
 
< 0.1%
356349.757069 3
0.1%
356345.316761 1
 
< 0.1%
356335.999166 1
 
< 0.1%
356331.110923 1
 
< 0.1%
356328.871819 1
 
< 0.1%
356326.419641 2
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3069
Distinct (%)85.6%
Missing172
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean263376.72
Minimum236164.39
Maximum278073.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:54.787682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum236164.39
5-th percentile253717.58
Q1261089.87
median263989.98
Q3266456.37
95-th percentile271932.17
Maximum278073.62
Range41909.231
Interquartile range (IQR)5366.4967

Descriptive statistics

Standard deviation5404.483
Coefficient of variation (CV)0.020519972
Kurtosis3.2717639
Mean263376.72
Median Absolute Deviation (MAD)2705.0063
Skewness-1.1047669
Sum9.4420555 × 108
Variance29208437
MonotonicityNot monotonic
2024-04-18T14:12:54.930550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
268026.454531 27
 
0.7%
260208.38965 7
 
0.2%
269131.73002 5
 
0.1%
264017.165939 5
 
0.1%
242019.624632 4
 
0.1%
261926.024856 4
 
0.1%
259655.384838 4
 
0.1%
260540.364298 4
 
0.1%
265012.3332 4
 
0.1%
261375.426757 4
 
0.1%
Other values (3059) 3517
93.6%
(Missing) 172
 
4.6%
ValueCountFrequency (%)
236164.392418 1
< 0.1%
237999.437164 1
< 0.1%
238531.35408 1
< 0.1%
238772.106218 1
< 0.1%
238772.40735 1
< 0.1%
238824.505921 1
< 0.1%
238893.362765 1
< 0.1%
238893.829912 1
< 0.1%
239059.112588 1
< 0.1%
239098.142264 1
< 0.1%
ValueCountFrequency (%)
278073.623286 1
< 0.1%
278029.090204 1
< 0.1%
277860.926384 1
< 0.1%
277755.206408 2
0.1%
277749.024029 1
< 0.1%
277673.246368 1
< 0.1%
277500.515376 1
< 0.1%
277489.106534 1
< 0.1%
277348.717166 1
< 0.1%
277022.824657 1
< 0.1%

위생업태명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
식품제조가공업
2794 
기타 식품제조가공업
936 
도시락제조업
 
27

Length

Max length10
Median length7
Mean length7.7402183
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2794
74.4%
기타 식품제조가공업 936
 
24.9%
도시락제조업 27
 
0.7%

Length

2024-04-18T14:12:55.065065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:55.177299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3730
79.5%
기타 936
 
19.9%
도시락제조업 27
 
0.6%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
<NA>
3365 
0
392 

Length

Max length4
Median length4
Mean length3.6869843
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3365
89.6%
0 392
 
10.4%

Length

2024-04-18T14:12:55.296803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:55.404492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3365
89.6%
0 392
 
10.4%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
<NA>
3365 
0
392 

Length

Max length4
Median length4
Mean length3.6869843
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3365
89.6%
0 392
 
10.4%

Length

2024-04-18T14:12:55.519907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:55.625544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3365
89.6%
0 392
 
10.4%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3757
Missing (%)100.0%
Memory size33.1 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3757
Missing (%)100.0%
Memory size33.1 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
상수도전용
2198 
<NA>
1539 
지하수전용
 
16
간이상수도
 
3
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length5
Mean length4.5935587
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2198
58.5%
<NA> 1539
41.0%
지하수전용 16
 
0.4%
간이상수도 3
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2024-04-18T14:12:55.754102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:55.863715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2198
58.5%
na 1539
41.0%
지하수전용 16
 
0.4%
간이상수도 3
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
<NA>
3379 
0
378 

Length

Max length4
Median length4
Mean length3.6981634
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> 3379
89.9%
0 378
 
10.1%

Length

2024-04-18T14:12:55.988819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:56.086936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3379
89.9%
0 378
 
10.1%

본사종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.3%
Missing634
Missing (%)16.9%
Infinite0
Infinite (%)0.0%
Mean0.06884406
Minimum0
Maximum12
Zeros3000
Zeros (%)79.9%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:56.170712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.454953
Coefficient of variation (CV)6.6084568
Kurtosis211.30463
Mean0.06884406
Median Absolute Deviation (MAD)0
Skewness11.93499
Sum215
Variance0.20698223
MonotonicityNot monotonic
2024-04-18T14:12:56.278894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3000
79.9%
1 84
 
2.2%
3 15
 
0.4%
2 14
 
0.4%
5 5
 
0.1%
4 2
 
0.1%
12 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 634
 
16.9%
ValueCountFrequency (%)
0 3000
79.9%
1 84
 
2.2%
2 14
 
0.4%
3 15
 
0.4%
4 2
 
0.1%
5 5
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 5
 
0.1%
4 2
 
0.1%
3 15
 
0.4%
2 14
 
0.4%
1 84
 
2.2%
0 3000
79.9%

공장사무직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct11
Distinct (%)0.4%
Missing625
Missing (%)16.6%
Infinite0
Infinite (%)0.0%
Mean0.20561941
Minimum0
Maximum40
Zeros2739
Zeros (%)72.9%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:56.382003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum40
Range40
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0268794
Coefficient of variation (CV)4.9940782
Kurtosis758.61654
Mean0.20561941
Median Absolute Deviation (MAD)0
Skewness22.180814
Sum644
Variance1.0544813
MonotonicityNot monotonic
2024-04-18T14:12:56.496937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 2739
72.9%
1 293
 
7.8%
2 58
 
1.5%
3 21
 
0.6%
4 8
 
0.2%
6 4
 
0.1%
5 3
 
0.1%
11 2
 
0.1%
15 2
 
0.1%
40 1
 
< 0.1%
(Missing) 625
 
16.6%
ValueCountFrequency (%)
0 2739
72.9%
1 293
 
7.8%
2 58
 
1.5%
3 21
 
0.6%
4 8
 
0.2%
5 3
 
0.1%
6 4
 
0.1%
9 1
 
< 0.1%
11 2
 
0.1%
15 2
 
0.1%
ValueCountFrequency (%)
40 1
 
< 0.1%
15 2
 
0.1%
11 2
 
0.1%
9 1
 
< 0.1%
6 4
 
0.1%
5 3
 
0.1%
4 8
 
0.2%
3 21
 
0.6%
2 58
 
1.5%
1 293
7.8%

공장판매직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.3%
Missing645
Missing (%)17.2%
Infinite0
Infinite (%)0.0%
Mean0.10411311
Minimum0
Maximum30
Zeros2896
Zeros (%)77.1%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:56.603040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum30
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.68746114
Coefficient of variation (CV)6.6030218
Kurtosis1169.7786
Mean0.10411311
Median Absolute Deviation (MAD)0
Skewness28.612223
Sum324
Variance0.47260281
MonotonicityNot monotonic
2024-04-18T14:12:56.716594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 2896
77.1%
1 166
 
4.4%
2 36
 
1.0%
3 7
 
0.2%
5 2
 
0.1%
4 2
 
0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
30 1
 
< 0.1%
(Missing) 645
 
17.2%
ValueCountFrequency (%)
0 2896
77.1%
1 166
 
4.4%
2 36
 
1.0%
3 7
 
0.2%
4 2
 
0.1%
5 2
 
0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
30 1
 
< 0.1%
ValueCountFrequency (%)
30 1
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
5 2
 
0.1%
4 2
 
0.1%
3 7
 
0.2%
2 36
 
1.0%
1 166
 
4.4%
0 2896
77.1%

공장생산직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct27
Distinct (%)0.8%
Missing553
Missing (%)14.7%
Infinite0
Infinite (%)0.0%
Mean0.82802747
Minimum0
Maximum220
Zeros2284
Zeros (%)60.8%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:56.850063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum220
Range220
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.6923538
Coefficient of variation (CV)5.666906
Kurtosis1522.7203
Mean0.82802747
Median Absolute Deviation (MAD)0
Skewness34.511316
Sum2653
Variance22.018184
MonotonicityNot monotonic
2024-04-18T14:12:56.971512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 2284
60.8%
1 456
 
12.1%
2 202
 
5.4%
3 106
 
2.8%
4 48
 
1.3%
5 30
 
0.8%
7 18
 
0.5%
6 13
 
0.3%
8 12
 
0.3%
10 7
 
0.2%
Other values (17) 28
 
0.7%
(Missing) 553
 
14.7%
ValueCountFrequency (%)
0 2284
60.8%
1 456
 
12.1%
2 202
 
5.4%
3 106
 
2.8%
4 48
 
1.3%
5 30
 
0.8%
6 13
 
0.3%
7 18
 
0.5%
8 12
 
0.3%
9 5
 
0.1%
ValueCountFrequency (%)
220 1
< 0.1%
83 1
< 0.1%
50 1
< 0.1%
42 1
< 0.1%
32 1
< 0.1%
28 1
< 0.1%
25 1
< 0.1%
22 1
< 0.1%
21 1
< 0.1%
20 2
0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
<NA>
1795 
임대
1140 
자가
822 

Length

Max length4
Median length2
Mean length2.9555496
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1795
47.8%
임대 1140
30.3%
자가 822
21.9%

Length

2024-04-18T14:12:57.101328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:57.213332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1795
47.8%
임대 1140
30.3%
자가 822
21.9%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)3.1%
Missing3185
Missing (%)84.8%
Infinite0
Infinite (%)0.0%
Mean1083744.4
Minimum0
Maximum50000000
Zeros508
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:57.321148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10000000
Maximum50000000
Range50000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4506231.3
Coefficient of variation (CV)4.1580204
Kurtosis63.58201
Mean1083744.4
Median Absolute Deviation (MAD)0
Skewness7.1360553
Sum6.199018 × 108
Variance2.0306121 × 1013
MonotonicityNot monotonic
2024-04-18T14:12:57.445328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 508
 
13.5%
10000000 24
 
0.6%
5000000 19
 
0.5%
3000000 3
 
0.1%
8000000 2
 
0.1%
30000000 2
 
0.1%
50000000 2
 
0.1%
2000000 2
 
0.1%
500 1
 
< 0.1%
6000000 1
 
< 0.1%
Other values (8) 8
 
0.2%
(Missing) 3185
84.8%
ValueCountFrequency (%)
0 508
13.5%
300 1
 
< 0.1%
500 1
 
< 0.1%
1000 1
 
< 0.1%
500000 1
 
< 0.1%
2000000 2
 
0.1%
3000000 3
 
0.1%
4400000 1
 
< 0.1%
5000000 19
 
0.5%
6000000 1
 
< 0.1%
ValueCountFrequency (%)
50000000 2
 
0.1%
40000000 1
 
< 0.1%
30000000 2
 
0.1%
20000000 1
 
< 0.1%
18000000 1
 
< 0.1%
10000000 24
0.6%
8000000 2
 
0.1%
7000000 1
 
< 0.1%
6000000 1
 
< 0.1%
5000000 19
0.5%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)4.6%
Missing3186
Missing (%)84.8%
Infinite0
Infinite (%)0.0%
Mean60840.963
Minimum0
Maximum2200000
Zeros507
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:57.559187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile500000
Maximum2200000
Range2200000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation220525.58
Coefficient of variation (CV)3.6246234
Kurtosis36.846414
Mean60840.963
Median Absolute Deviation (MAD)0
Skewness5.3648167
Sum34740190
Variance4.8631532 × 1010
MonotonicityNot monotonic
2024-04-18T14:12:57.676934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 507
 
13.5%
300000 13
 
0.3%
500000 11
 
0.3%
400000 5
 
0.1%
600000 4
 
0.1%
350000 3
 
0.1%
200000 3
 
0.1%
800000 3
 
0.1%
450000 2
 
0.1%
250000 2
 
0.1%
Other values (16) 18
 
0.5%
(Missing) 3186
84.8%
ValueCountFrequency (%)
0 507
13.5%
10 1
 
< 0.1%
30 1
 
< 0.1%
150 1
 
< 0.1%
150000 1
 
< 0.1%
200000 3
 
0.1%
250000 2
 
0.1%
300000 13
 
0.3%
350000 3
 
0.1%
400000 5
 
0.1%
ValueCountFrequency (%)
2200000 1
 
< 0.1%
2000000 1
 
< 0.1%
1800000 1
 
< 0.1%
1300000 1
 
< 0.1%
1200000 1
 
< 0.1%
1100000 1
 
< 0.1%
900000 1
 
< 0.1%
850000 2
0.1%
800000 3
0.1%
750000 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
False
3755 
True
 
2
ValueCountFrequency (%)
False 3755
99.9%
True 2
 
0.1%
2024-04-18T14:12:57.787151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct538
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.229944
Minimum0
Maximum4673.38
Zeros2985
Zeros (%)79.5%
Negative0
Negative (%)0.0%
Memory size33.1 KiB
2024-04-18T14:12:57.909853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile37.568
Maximum4673.38
Range4673.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation125.23441
Coefficient of variation (CV)10.239982
Kurtosis972.3551
Mean12.229944
Median Absolute Deviation (MAD)0
Skewness28.742672
Sum45947.9
Variance15683.658
MonotonicityNot monotonic
2024-04-18T14:12:58.146612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2985
79.5%
3.0 23
 
0.6%
6.0 16
 
0.4%
1.0 15
 
0.4%
4.0 12
 
0.3%
2.0 11
 
0.3%
3.3 10
 
0.3%
4.5 8
 
0.2%
1.2 8
 
0.2%
9.0 7
 
0.2%
Other values (528) 662
 
17.6%
ValueCountFrequency (%)
0.0 2985
79.5%
1.0 15
 
0.4%
1.1 1
 
< 0.1%
1.2 8
 
0.2%
1.23 1
 
< 0.1%
1.3 1
 
< 0.1%
1.39 1
 
< 0.1%
1.5 5
 
0.1%
1.64 1
 
< 0.1%
1.7 1
 
< 0.1%
ValueCountFrequency (%)
4673.38 1
< 0.1%
4439.37 1
< 0.1%
2313.89 1
< 0.1%
1680.5 1
< 0.1%
1520.96 1
< 0.1%
943.03 1
< 0.1%
875.0 1
< 0.1%
802.0 1
< 0.1%
701.08 1
< 0.1%
695.92 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3757
Missing (%)100.0%
Memory size33.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3757
Missing (%)100.0%
Memory size33.1 KiB

홈페이지
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
<NA>
3755 
4
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.998403
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3755
99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Length

2024-04-18T14:12:58.323584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:12:58.471145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3755
99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품제조가공업07_22_11_P34100003410000-106-2004-0000220040507<NA>3폐업2폐업20050324<NA><NA><NA>053 424497914.70700111대구광역시 중구 태평로1가 0001-0186번지<NA><NA>동북상회20041102000000I2018-08-31 23:59:59.0식품제조가공업344182.487426265065.535111식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0011<NA><NA><NA>N0.0<NA><NA><NA>
12식품제조가공업07_22_11_P34100003410000-106-2004-0000320040524<NA>3폐업2폐업20150424<NA><NA><NA>053 256433741.85700837대구광역시 중구 남산동 2466-0001번지 보성황실아파트 116동 105호대구광역시 중구 남산로13길 17, 1층 (남산동, 보성황실아파트 116동 105호)41978황실떡집20150304143402I2018-08-31 23:59:59.0식품제조가공업342754.486268263376.49575식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0002자가<NA><NA>N0.0<NA><NA><NA>
23식품제조가공업07_22_11_P34100003410000-106-2004-0000420040629<NA>3폐업2폐업20040908<NA><NA><NA>053 4240540120.60700823대구광역시 중구 봉산동 0165-0007번지<NA><NA>에프엔에스20040901000000I2018-08-31 23:59:59.0식품제조가공업344341.820223263777.999999식품제조가공업00<NA><NA>상수도전용<NA>0121임대<NA><NA>N0.0<NA><NA><NA>
34식품제조가공업07_22_11_P34100003410000-106-2004-0000520041101<NA>3폐업2폐업20080717<NA><NA><NA>053 422331834.52700845대구광역시 중구 동인동3가 0302-0002번지<NA><NA>이유통20071126103251I2018-08-31 23:59:59.0식품제조가공업345483.514708264655.185763식품제조가공업<NA><NA><NA><NA>상수도전용<NA>1000자가<NA><NA>N0.0<NA><NA><NA>
45식품제조가공업07_22_11_P34100003410000-106-2004-0000620041111<NA>3폐업2폐업20050906<NA><NA><NA><NA>25.23700421대구광역시 중구 동인동1가 0196번지<NA><NA>불스푸드20050321000000I2018-08-31 23:59:59.0식품제조가공업344696.914116264897.878354식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0111자가<NA><NA>N0.0<NA><NA><NA>
56식품제조가공업07_22_11_P34100003410000-106-2004-0000720041119<NA>3폐업2폐업20041120<NA><NA><NA>053 4294238<NA>700180대구광역시 중구 동문동 0020-0004번지<NA><NA>(사)농어촌특산단지전남연합회20041119000000I2018-08-31 23:59:59.0식품제조가공업344148.352033264812.35373식품제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
67식품제조가공업07_22_11_P34100003410000-106-2004-0000820041202<NA>3폐업2폐업20100621<NA><NA><NA>053 254013230.20700413대구광역시 중구 삼덕동3가 0042번지<NA><NA>교자춘20071113181224I2018-08-31 23:59:59.0식품제조가공업345042.851191263965.608979식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0102자가<NA><NA>N0.0<NA><NA><NA>
78식품제조가공업07_22_11_P34100003410000-106-2005-0000220050623<NA>3폐업2폐업20050706<NA><NA><NA><NA><NA>700320대구광역시 중구 대신동 115-370번지 1층<NA><NA>경북농산20050623000000I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
89식품제조가공업07_22_11_P34100003410000-106-2005-0000420050908<NA>3폐업2폐업20070208<NA><NA><NA><NA>67.75700413대구광역시 중구 삼덕동3가 0227-0006번지<NA><NA>(주)승민식품20050908000000I2018-08-31 23:59:59.0식품제조가공업345171.417199263913.270601식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0202자가<NA><NA>N0.0<NA><NA><NA>
910식품제조가공업07_22_11_P34100003410000-106-2005-0000520050927<NA>3폐업2폐업20070918<NA><NA><NA><NA>58.84700812대구광역시 중구 대봉동 0166-0010번지<NA><NA>(주)엠빠나다20051028000000I2018-08-31 23:59:59.0식품제조가공업344440.147732263031.504086식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0101임대<NA><NA>N0.0<NA><NA><NA>
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37473748식품제조가공업07_22_11_P34800003480000-106-2021-0001020210901<NA>1영업/정상1영업<NA><NA><NA><NA><NA>212.69<NA>대구광역시 달성군 옥포읍 본리리 2315대구광역시 달성군 옥포읍 비슬로434길 5, 1층42970모든찬20210901083927I2021-09-03 00:22:50.0기타 식품제조가공업331839.170903255123.033878기타 식품제조가공업00<NA><NA>상수도전용00000<NA>00N87.19<NA><NA><NA>
37483749식품제조가공업07_22_11_P34800003480000-106-2013-0001520131016<NA>1영업/정상1영업<NA><NA><NA><NA><NA>78.42711864대구광역시 달성군 가창면 용계리 233-16대구광역시 달성군 가창면 가창로213길 8-1, 1층42936보리채움20220207173857U2022-02-09 02:40:00.0식품제조가공업346565.952924256681.467415식품제조가공업00<NA><NA>상수도전용00000임대00N0.0<NA><NA><NA>
37493750식품제조가공업07_22_11_P34800003480000-106-2021-0000620210430<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.00711852대구광역시 달성군 논공읍 남리 224-110대구광역시 달성군 논공읍 논공로 806-1, 1층42978네츄럴팩트20210430134728I2021-05-02 00:22:57.0기타 식품제조가공업330115.35775248516.530338기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
37503751식품제조가공업07_22_11_P34800003480000-106-2008-0001720080104<NA>1영업/정상1영업<NA><NA><NA><NA>053 627 2557447.00711850대구광역시 달성군 논공읍 삼리리 632-1번지 외 1필지 A동대구광역시 달성군 논공읍 위천2길 6, A동 1층42976정통식품20160127164501I2018-08-31 23:59:59.0식품제조가공업327021.529591252397.401938식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
37513752식품제조가공업07_22_11_P34800003480000-106-2012-0001020120911<NA>1영업/정상1영업<NA><NA><NA><NA>070 75325543149.47711832대구광역시 달성군 화원읍 명곡리 105번지 2층대구광역시 달성군 화원읍 명곡로 12-11, 2층42960청원푸드20160128102651I2018-08-31 23:59:59.0식품제조가공업335094.531933256378.574073식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
37523753식품제조가공업07_22_11_P34800003480000-106-2013-0000620130808<NA>1영업/정상1영업<NA><NA><NA><NA>053 639 5887159.30711839대구광역시 달성군 화원읍 성산리 536-6번지대구광역시 달성군 화원읍 성천로12길 1142946선미 푸드20160128164651I2018-08-31 23:59:59.0식품제조가공업334521.009928256794.676167식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
37533754식품제조가공업07_22_11_P34800003480000-106-2012-0000520120615<NA>1영업/정상1영업<NA><NA><NA><NA>053 584 4884472.00711821대구광역시 달성군 하빈면 하산리 133-1번지대구광역시 달성군 하빈면 하산4길 7842900훈식품20170825094405I2018-08-31 23:59:59.0식품제조가공업327642.468368267180.710022식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
37543755식품제조가공업07_22_11_P34800003480000-106-2007-0001820071108<NA>1영업/정상1영업<NA><NA><NA><NA>053 6443684204.00711855대구광역시 달성군 논공읍 본리리 29-53번지대구광역시 달성군 논공읍 논공로71길 2742982미성20191011162442U2019-10-13 02:40:00.0식품제조가공업332803.386147250052.269534식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0102임대<NA><NA>N8.0<NA><NA><NA>
37553756식품제조가공업07_22_11_P34800003480000-106-2007-0001920071113<NA>1영업/정상1영업<NA><NA><NA><NA>053 61196111,205.93711892대구광역시 달성군 구지면 내리 839-11번지대구광역시 달성군 구지면 달성2차로 2743011(주)푸름원20160127154201I2018-08-31 23:59:59.0식품제조가공업327415.835763238772.106218식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
37563757식품제조가공업07_22_11_P34800003480000-106-1997-0000819970924<NA>1영업/정상1영업<NA><NA><NA><NA><NA>837.90711823대구광역시 달성군 하빈면 봉촌리 1032-3번지대구광역시 달성군 하빈면 하빈남로 40742905연꽃마을20160127155832I2018-08-31 23:59:59.0식품제조가공업325649.192591263403.704757식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0102<NA><NA><NA>N0.0<NA><NA><NA>