Overview

Dataset statistics

Number of variables47
Number of observations3880
Missing cells44980
Missing cells (%)24.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory403.0 B

Variable types

Numeric13
Categorical15
Text6
DateTime4
Unsupported8
Boolean1

Dataset

Description23년06월_6270000_대구광역시_07_22_11_P_식품제조가공업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000098694&dataSetDetailId=DDI_0000098732&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
급수시설구분명 is highly imbalanced (55.7%)Imbalance
다중이용업소여부 is highly imbalanced (99.4%)Imbalance
홈페이지 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3880 (100.0%) missing valuesMissing
폐업일자 has 1031 (26.6%) missing valuesMissing
휴업시작일자 has 3880 (100.0%) missing valuesMissing
휴업종료일자 has 3880 (100.0%) missing valuesMissing
재개업일자 has 3880 (100.0%) missing valuesMissing
소재지전화 has 1125 (29.0%) missing valuesMissing
소재지면적 has 136 (3.5%) missing valuesMissing
소재지우편번호 has 89 (2.3%) missing valuesMissing
도로명전체주소 has 1370 (35.3%) missing valuesMissing
도로명우편번호 has 1398 (36.0%) missing valuesMissing
좌표정보(X) has 213 (5.5%) missing valuesMissing
좌표정보(Y) has 213 (5.5%) missing valuesMissing
영업장주변구분명 has 3880 (100.0%) missing valuesMissing
등급구분명 has 3880 (100.0%) missing valuesMissing
본사직원수 has 589 (15.2%) missing valuesMissing
공장사무직직원수 has 577 (14.9%) missing valuesMissing
공장판매직직원수 has 598 (15.4%) missing valuesMissing
공장생산직직원수 has 510 (13.1%) missing valuesMissing
보증액 has 3032 (78.1%) missing valuesMissing
월세액 has 3033 (78.2%) missing valuesMissing
전통업소지정번호 has 3880 (100.0%) missing valuesMissing
전통업소주된음식 has 3880 (100.0%) missing valuesMissing
소재지면적 is highly skewed (γ1 = 20.01345712)Skewed
공장사무직직원수 is highly skewed (γ1 = 21.32544484)Skewed
공장판매직직원수 is highly skewed (γ1 = 29.40363258)Skewed
공장생산직직원수 is highly skewed (γ1 = 34.26270954)Skewed
시설총규모 is highly skewed (γ1 = 29.03361587)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
본사직원수 has 3153 (81.3%) zerosZeros
공장사무직직원수 has 2882 (74.3%) zerosZeros
공장판매직직원수 has 3068 (79.1%) zerosZeros
공장생산직직원수 has 2423 (62.4%) zerosZeros
보증액 has 784 (20.2%) zerosZeros
월세액 has 783 (20.2%) zerosZeros
시설총규모 has 3049 (78.6%) zerosZeros

Reproduction

Analysis started2023-12-10 19:27:56.977892
Analysis finished2023-12-10 19:27:59.706463
Duration2.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3880
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1940.5
Minimum1
Maximum3880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:27:59.839367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile194.95
Q1970.75
median1940.5
Q32910.25
95-th percentile3686.05
Maximum3880
Range3879
Interquartile range (IQR)1939.5

Descriptive statistics

Standard deviation1120.2039
Coefficient of variation (CV)0.57727588
Kurtosis-1.2
Mean1940.5
Median Absolute Deviation (MAD)970
Skewness0
Sum7529140
Variance1254856.7
MonotonicityStrictly increasing
2023-12-11T04:28:00.078274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2608 1
 
< 0.1%
2580 1
 
< 0.1%
2581 1
 
< 0.1%
2582 1
 
< 0.1%
2583 1
 
< 0.1%
2584 1
 
< 0.1%
2585 1
 
< 0.1%
2586 1
 
< 0.1%
2587 1
 
< 0.1%
Other values (3870) 3870
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 (%)
3880 1
< 0.1%
3879 1
< 0.1%
3878 1
< 0.1%
3877 1
< 0.1%
3876 1
< 0.1%
3875 1
< 0.1%
3874 1
< 0.1%
3873 1
< 0.1%
3872 1
< 0.1%
3871 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
식품제조가공업
3880 

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 3880
100.0%

Length

2023-12-11T04:28:00.295411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:00.442439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3880
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
07_22_11_P
3880 

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 3880
100.0%

Length

2023-12-11T04:28:00.577474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:00.712555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_11_p 3880
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3450010.3
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:00.858113image/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 deviation20927.203
Coefficient of variation (CV)0.0060658378
Kurtosis-0.95630421
Mean3450010.3
Median Absolute Deviation (MAD)20000
Skewness-0.31105178
Sum1.338604 × 1010
Variance4.3794782 × 108
MonotonicityIncreasing
2023-12-11T04:28:00.988255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 970
25.0%
3470000 674
17.4%
3480000 488
12.6%
3420000 452
11.6%
3460000 450
11.6%
3430000 372
 
9.6%
3440000 246
 
6.3%
3410000 228
 
5.9%
ValueCountFrequency (%)
3410000 228
 
5.9%
3420000 452
11.6%
3430000 372
 
9.6%
3440000 246
 
6.3%
3450000 970
25.0%
3460000 450
11.6%
3470000 674
17.4%
3480000 488
12.6%
ValueCountFrequency (%)
3480000 488
12.6%
3470000 674
17.4%
3460000 450
11.6%
3450000 970
25.0%
3440000 246
 
6.3%
3430000 372
 
9.6%
3420000 452
11.6%
3410000 228
 
5.9%

관리번호
Text

UNIQUE 

Distinct3880
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
2023-12-11T04:28:01.280851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters85360
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

Unique3880 ?
Unique (%)100.0%

Sample

1st row3410000-106-2001-00009
2nd row3410000-106-2003-00005
3rd row3410000-106-2003-00006
4th row3410000-106-2003-00007
5th row3410000-106-2004-00001
ValueCountFrequency (%)
3410000-106-2001-00009 1
 
< 0.1%
3460000-106-2013-00003 1
 
< 0.1%
3460000-106-2010-00006 1
 
< 0.1%
3460000-106-2010-00010 1
 
< 0.1%
3460000-106-2000-00035 1
 
< 0.1%
3460000-106-2010-00011 1
 
< 0.1%
3460000-106-2010-00012 1
 
< 0.1%
3460000-106-2010-00013 1
 
< 0.1%
3460000-106-2010-00017 1
 
< 0.1%
3460000-106-2011-00002 1
 
< 0.1%
Other values (3870) 3870
99.7%
2023-12-11T04:28:01.743257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38870
45.5%
- 11640
 
13.6%
1 8126
 
9.5%
2 5881
 
6.9%
3 5309
 
6.2%
6 5081
 
6.0%
4 4966
 
5.8%
5 1731
 
2.0%
7 1400
 
1.6%
9 1184
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73720
86.4%
Dash Punctuation 11640
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38870
52.7%
1 8126
 
11.0%
2 5881
 
8.0%
3 5309
 
7.2%
6 5081
 
6.9%
4 4966
 
6.7%
5 1731
 
2.3%
7 1400
 
1.9%
9 1184
 
1.6%
8 1172
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 11640
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38870
45.5%
- 11640
 
13.6%
1 8126
 
9.5%
2 5881
 
6.9%
3 5309
 
6.2%
6 5081
 
6.0%
4 4966
 
5.8%
5 1731
 
2.0%
7 1400
 
1.6%
9 1184
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38870
45.5%
- 11640
 
13.6%
1 8126
 
9.5%
2 5881
 
6.9%
3 5309
 
6.2%
6 5081
 
6.0%
4 4966
 
5.8%
5 1731
 
2.0%
7 1400
 
1.6%
9 1184
 
1.4%
Distinct2754
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
Minimum1968-12-18 00:00:00
Maximum2023-06-27 00:00:00
2023-12-11T04:28:01.948377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:28:02.154838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3880
Missing (%)100.0%
Memory size34.2 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
3
2849 
1
1031 

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 2849
73.4%
1 1031
 
26.6%

Length

2023-12-11T04:28:02.349337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:02.502793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2849
73.4%
1 1031
 
26.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
폐업
2849 
영업/정상
1031 

Length

Max length5
Median length2
Mean length2.7971649
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2849
73.4%
영업/정상 1031
 
26.6%

Length

2023-12-11T04:28:02.648203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:02.785228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2849
73.4%
영업/정상 1031
 
26.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
2
2849 
1
1031 

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 2849
73.4%
1 1031
 
26.6%

Length

2023-12-11T04:28:02.935206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:03.060499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2849
73.4%
1 1031
 
26.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
폐업
2849 
영업
1031 

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 2849
73.4%
영업 1031
 
26.6%

Length

2023-12-11T04:28:03.206412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:03.339537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2849
73.4%
영업 1031
 
26.6%

폐업일자
Date

MISSING 

Distinct2117
Distinct (%)74.3%
Missing1031
Missing (%)26.6%
Memory size30.4 KiB
Minimum2000-04-24 00:00:00
Maximum2023-06-28 00:00:00
2023-12-11T04:28:03.506514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:28:03.705211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3880
Missing (%)100.0%
Memory size34.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3880
Missing (%)100.0%
Memory size34.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3880
Missing (%)100.0%
Memory size34.2 KiB

소재지전화
Text

MISSING 

Distinct2549
Distinct (%)92.5%
Missing1125
Missing (%)29.0%
Memory size30.4 KiB
2023-12-11T04:28:04.131404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.857713
Min length7

Characters and Unicode

Total characters29913
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

Unique2354 ?
Unique (%)85.4%

Sample

1st row053 4215900
2nd row2571231
3rd row053 5225074
4th row053 4213530
5th row053 4244979
ValueCountFrequency (%)
053 2025
34.8%
070 69
 
1.2%
311 21
 
0.4%
313 15
 
0.3%
983 13
 
0.2%
621 13
 
0.2%
314 13
 
0.2%
767 13
 
0.2%
611 13
 
0.2%
615 11
 
0.2%
Other values (2710) 3619
62.1%
2023-12-11T04:28:04.696483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4935
16.5%
3 4371
14.6%
0 4288
14.3%
3151
10.5%
2 2140
7.2%
6 2118
7.1%
1 2069
6.9%
7 1900
 
6.4%
8 1787
 
6.0%
4 1651
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26762
89.5%
Space Separator 3151
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4935
18.4%
3 4371
16.3%
0 4288
16.0%
2 2140
8.0%
6 2118
7.9%
1 2069
7.7%
7 1900
 
7.1%
8 1787
 
6.7%
4 1651
 
6.2%
9 1503
 
5.6%
Space Separator
ValueCountFrequency (%)
3151
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29913
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4935
16.5%
3 4371
14.6%
0 4288
14.3%
3151
10.5%
2 2140
7.2%
6 2118
7.1%
1 2069
6.9%
7 1900
 
6.4%
8 1787
 
6.0%
4 1651
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29913
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4935
16.5%
3 4371
14.6%
0 4288
14.3%
3151
10.5%
2 2140
7.2%
6 2118
7.1%
1 2069
6.9%
7 1900
 
6.4%
8 1787
 
6.0%
4 1651
 
5.5%

소재지면적
Real number (ℝ)

MISSING  SKEWED 

Distinct2698
Distinct (%)72.1%
Missing136
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean193.6845
Minimum0
Maximum30312.82
Zeros17
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:04.877352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.6
Q135.2725
median68
Q3148.625
95-th percentile494.1755
Maximum30312.82
Range30312.82
Interquartile range (IQR)113.3525

Descriptive statistics

Standard deviation846.53889
Coefficient of variation (CV)4.3707106
Kurtosis545.3896
Mean193.6845
Median Absolute Deviation (MAD)40.77
Skewness20.013457
Sum725154.77
Variance716628.1
MonotonicityNot monotonic
2023-12-11T04:28:05.062826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.0 30
 
0.8%
20.0 27
 
0.7%
33.0 25
 
0.6%
40.0 17
 
0.4%
0.0 17
 
0.4%
30.0 15
 
0.4%
15.0 13
 
0.3%
132.0 12
 
0.3%
38.0 12
 
0.3%
26.4 12
 
0.3%
Other values (2688) 3564
91.9%
(Missing) 136
 
3.5%
ValueCountFrequency (%)
0.0 17
0.4%
3.0 2
 
0.1%
3.24 1
 
< 0.1%
3.6 1
 
< 0.1%
4.72 1
 
< 0.1%
4.8 1
 
< 0.1%
5.0 3
 
0.1%
5.28 1
 
< 0.1%
5.33 1
 
< 0.1%
6.0 1
 
< 0.1%
ValueCountFrequency (%)
30312.82 1
< 0.1%
15974.08 1
< 0.1%
15142.38 1
< 0.1%
13984.23 1
< 0.1%
13537.95 1
< 0.1%
12144.51 1
< 0.1%
9439.4 1
< 0.1%
9051.41 1
< 0.1%
8918.8 1
< 0.1%
7007.0 1
< 0.1%

소재지우편번호
Text

MISSING 

Distinct552
Distinct (%)14.6%
Missing89
Missing (%)2.3%
Memory size30.4 KiB
2023-12-11T04:28:05.462383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters26537
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

Unique100 ?
Unique (%)2.6%

Sample

1st row700-802
2nd row700-809
3rd row700-380
4th row700-413
5th row700-809
ValueCountFrequency (%)
702-825 90
 
2.4%
702-061 84
 
2.2%
703-830 57
 
1.5%
703-833 50
 
1.3%
702-816 46
 
1.2%
704-080 44
 
1.2%
702-903 38
 
1.0%
704-900 36
 
0.9%
701-140 34
 
0.9%
711-851 34
 
0.9%
Other values (542) 3278
86.5%
2023-12-11T04:28:06.005522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5299
20.0%
7 4191
15.8%
- 3791
14.3%
8 3066
11.6%
1 2470
9.3%
2 2025
 
7.6%
4 1509
 
5.7%
3 1508
 
5.7%
6 1024
 
3.9%
5 976
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22746
85.7%
Dash Punctuation 3791
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5299
23.3%
7 4191
18.4%
8 3066
13.5%
1 2470
10.9%
2 2025
 
8.9%
4 1509
 
6.6%
3 1508
 
6.6%
6 1024
 
4.5%
5 976
 
4.3%
9 678
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 3791
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26537
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5299
20.0%
7 4191
15.8%
- 3791
14.3%
8 3066
11.6%
1 2470
9.3%
2 2025
 
7.6%
4 1509
 
5.7%
3 1508
 
5.7%
6 1024
 
3.9%
5 976
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26537
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5299
20.0%
7 4191
15.8%
- 3791
14.3%
8 3066
11.6%
1 2470
9.3%
2 2025
 
7.6%
4 1509
 
5.7%
3 1508
 
5.7%
6 1024
 
3.9%
5 976
 
3.7%
Distinct3599
Distinct (%)93.4%
Missing26
Missing (%)0.7%
Memory size30.4 KiB
2023-12-11T04:28:06.531649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length49
Mean length23.736118
Min length15

Characters and Unicode

Total characters91479
Distinct characters302
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

Unique3387 ?
Unique (%)87.9%

Sample

1st row대구광역시 중구 남산동 0912-11번지
2nd row대구광역시 중구 대봉동 0121-0238번지
3rd row대구광역시 중구 달성동 0288-0013번지
4th row대구광역시 중구 삼덕동3가 0167-0001번지 (지상1층)
5th row대구광역시 중구 대봉동 0040-0033번지
ValueCountFrequency (%)
대구광역시 3854
22.3%
북구 963
 
5.6%
달서구 671
 
3.9%
달성군 484
 
2.8%
동구 452
 
2.6%
수성구 438
 
2.5%
서구 373
 
2.2%
남구 246
 
1.4%
중구 228
 
1.3%
지상1층 200
 
1.2%
Other values (4006) 9370
54.2%
2023-12-11T04:28:07.194290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17240
18.8%
7330
 
8.0%
1 4547
 
5.0%
4191
 
4.6%
4101
 
4.5%
3910
 
4.3%
3859
 
4.2%
3859
 
4.2%
3416
 
3.7%
- 3215
 
3.5%
Other values (292) 35811
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50958
55.7%
Decimal Number 19114
 
20.9%
Space Separator 17240
 
18.8%
Dash Punctuation 3215
 
3.5%
Open Punctuation 346
 
0.4%
Close Punctuation 346
 
0.4%
Other Punctuation 126
 
0.1%
Uppercase Letter 117
 
0.1%
Math Symbol 14
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7330
14.4%
4191
 
8.2%
4101
 
8.0%
3910
 
7.7%
3859
 
7.6%
3859
 
7.6%
3416
 
6.7%
2895
 
5.7%
1229
 
2.4%
1225
 
2.4%
Other values (263) 14943
29.3%
Decimal Number
ValueCountFrequency (%)
1 4547
23.8%
2 2389
12.5%
0 2104
11.0%
3 1975
10.3%
4 1605
 
8.4%
5 1479
 
7.7%
6 1400
 
7.3%
7 1288
 
6.7%
8 1196
 
6.3%
9 1131
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 52
44.4%
A 49
41.9%
C 8
 
6.8%
D 2
 
1.7%
T 2
 
1.7%
E 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 (%)
17240
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3215
100.0%
Open Punctuation
ValueCountFrequency (%)
( 346
100.0%
Close Punctuation
ValueCountFrequency (%)
) 346
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50958
55.7%
Common 40401
44.2%
Latin 120
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7330
14.4%
4191
 
8.2%
4101
 
8.0%
3910
 
7.7%
3859
 
7.6%
3859
 
7.6%
3416
 
6.7%
2895
 
5.7%
1229
 
2.4%
1225
 
2.4%
Other values (263) 14943
29.3%
Common
ValueCountFrequency (%)
17240
42.7%
1 4547
 
11.3%
- 3215
 
8.0%
2 2389
 
5.9%
0 2104
 
5.2%
3 1975
 
4.9%
4 1605
 
4.0%
5 1479
 
3.7%
6 1400
 
3.5%
7 1288
 
3.2%
Other values (9) 3159
 
7.8%
Latin
ValueCountFrequency (%)
B 52
43.3%
A 49
40.8%
C 8
 
6.7%
D 2
 
1.7%
e 2
 
1.7%
T 2
 
1.7%
E 2
 
1.7%
P 1
 
0.8%
c 1
 
0.8%
J 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50958
55.7%
ASCII 40521
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17240
42.5%
1 4547
 
11.2%
- 3215
 
7.9%
2 2389
 
5.9%
0 2104
 
5.2%
3 1975
 
4.9%
4 1605
 
4.0%
5 1479
 
3.6%
6 1400
 
3.5%
7 1288
 
3.2%
Other values (19) 3279
 
8.1%
Hangul
ValueCountFrequency (%)
7330
14.4%
4191
 
8.2%
4101
 
8.0%
3910
 
7.7%
3859
 
7.6%
3859
 
7.6%
3416
 
6.7%
2895
 
5.7%
1229
 
2.4%
1225
 
2.4%
Other values (263) 14943
29.3%

도로명전체주소
Text

MISSING 

Distinct2396
Distinct (%)95.5%
Missing1370
Missing (%)35.3%
Memory size30.4 KiB
2023-12-11T04:28:07.644268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length54
Mean length27.91753
Min length20

Characters and Unicode

Total characters70073
Distinct characters325
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

Unique2293 ?
Unique (%)91.4%

Sample

1st row대구광역시 중구 국채보상로150길 60, 1층 (삼덕동3가)
2nd row대구광역시 중구 남산로13길 17, 1층 (남산동, 보성황실아파트 116동 105호)
3rd row대구광역시 중구 동덕로30길 139-24, 1층 (동인동4가)
4th row대구광역시 중구 서성로14길 85 (대안동, 지상2층)
5th row대구광역시 중구 남산로 23-15, 1층 (남산동)
ValueCountFrequency (%)
대구광역시 2510
 
17.8%
북구 633
 
4.5%
1층 630
 
4.5%
달서구 381
 
2.7%
달성군 330
 
2.3%
동구 311
 
2.2%
수성구 298
 
2.1%
서구 238
 
1.7%
남구 163
 
1.2%
중구 157
 
1.1%
Other values (2705) 8471
60.0%
2023-12-11T04:28:08.293732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11613
 
16.6%
4930
 
7.0%
1 3199
 
4.6%
3029
 
4.3%
3024
 
4.3%
2616
 
3.7%
2530
 
3.6%
2511
 
3.6%
) 2300
 
3.3%
( 2300
 
3.3%
Other values (315) 32021
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40011
57.1%
Space Separator 11613
 
16.6%
Decimal Number 11447
 
16.3%
Close Punctuation 2300
 
3.3%
Open Punctuation 2300
 
3.3%
Other Punctuation 1432
 
2.0%
Dash Punctuation 791
 
1.1%
Uppercase Letter 149
 
0.2%
Math Symbol 28
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4930
 
12.3%
3029
 
7.6%
3024
 
7.6%
2616
 
6.5%
2530
 
6.3%
2511
 
6.3%
2297
 
5.7%
1739
 
4.3%
1087
 
2.7%
1083
 
2.7%
Other values (283) 15165
37.9%
Uppercase Letter
ValueCountFrequency (%)
B 63
42.3%
A 56
37.6%
C 12
 
8.1%
T 4
 
2.7%
D 3
 
2.0%
E 3
 
2.0%
P 2
 
1.3%
J 2
 
1.3%
R 1
 
0.7%
G 1
 
0.7%
Other values (2) 2
 
1.3%
Decimal Number
ValueCountFrequency (%)
1 3199
27.9%
2 1701
14.9%
3 1329
11.6%
4 962
 
8.4%
5 888
 
7.8%
6 817
 
7.1%
0 748
 
6.5%
7 714
 
6.2%
8 585
 
5.1%
9 504
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 1424
99.4%
· 4
 
0.3%
. 4
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
11613
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2300
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2300
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 791
100.0%
Math Symbol
ValueCountFrequency (%)
~ 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40011
57.1%
Common 29911
42.7%
Latin 151
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4930
 
12.3%
3029
 
7.6%
3024
 
7.6%
2616
 
6.5%
2530
 
6.3%
2511
 
6.3%
2297
 
5.7%
1739
 
4.3%
1087
 
2.7%
1083
 
2.7%
Other values (283) 15165
37.9%
Common
ValueCountFrequency (%)
11613
38.8%
1 3199
 
10.7%
) 2300
 
7.7%
( 2300
 
7.7%
2 1701
 
5.7%
, 1424
 
4.8%
3 1329
 
4.4%
4 962
 
3.2%
5 888
 
3.0%
6 817
 
2.7%
Other values (8) 3378
 
11.3%
Latin
ValueCountFrequency (%)
B 63
41.7%
A 56
37.1%
C 12
 
7.9%
T 4
 
2.6%
D 3
 
2.0%
E 3
 
2.0%
P 2
 
1.3%
J 2
 
1.3%
R 1
 
0.7%
e 1
 
0.7%
Other values (4) 4
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40011
57.1%
ASCII 30058
42.9%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11613
38.6%
1 3199
 
10.6%
) 2300
 
7.7%
( 2300
 
7.7%
2 1701
 
5.7%
, 1424
 
4.7%
3 1329
 
4.4%
4 962
 
3.2%
5 888
 
3.0%
6 817
 
2.7%
Other values (21) 3525
 
11.7%
Hangul
ValueCountFrequency (%)
4930
 
12.3%
3029
 
7.6%
3024
 
7.6%
2616
 
6.5%
2530
 
6.3%
2511
 
6.3%
2297
 
5.7%
1739
 
4.3%
1087
 
2.7%
1083
 
2.7%
Other values (283) 15165
37.9%
None
ValueCountFrequency (%)
· 4
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct834
Distinct (%)33.6%
Missing1398
Missing (%)36.0%
Infinite0
Infinite (%)0.0%
Mean42021.438
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:08.507099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41102.05
Q141490
median41936.5
Q342672.5
95-th percentile42973.9
Maximum43024
Range2024
Interquartile range (IQR)1182.5

Descriptive statistics

Standard deviation618.6707
Coefficient of variation (CV)0.01472274
Kurtosis-1.3106463
Mean42021.438
Median Absolute Deviation (MAD)495
Skewness0.14622336
Sum1.0429721 × 108
Variance382753.44
MonotonicityNot monotonic
2023-12-11T04:28:08.751306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41485 45
 
1.2%
41582 44
 
1.1%
41490 39
 
1.0%
41557 24
 
0.6%
41488 23
 
0.6%
41755 20
 
0.5%
42701 20
 
0.5%
42970 18
 
0.5%
42975 18
 
0.5%
42703 18
 
0.5%
Other values (824) 2213
57.0%
(Missing) 1398
36.0%
ValueCountFrequency (%)
41000 8
0.2%
41001 3
 
0.1%
41002 5
0.1%
41005 2
 
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 2
 
0.1%
43006 4
0.1%
Distinct3286
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
2023-12-11T04:28:09.108291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length5.9314433
Min length1

Characters and Unicode

Total characters23014
Distinct characters777
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

Unique2868 ?
Unique (%)73.9%

Sample

1st row고려식품
2nd row두레식품A공장
3rd row한국식품
4th row우리두리식품
5th row원숭이식품
ValueCountFrequency (%)
주식회사 114
 
2.6%
농업회사법인 16
 
0.4%
우리식품 14
 
0.3%
커피 14
 
0.3%
14
 
0.3%
푸드 13
 
0.3%
coffee 11
 
0.3%
제일식품 11
 
0.3%
food 10
 
0.2%
현대식품 9
 
0.2%
Other values (3475) 4138
94.8%
2023-12-11T04:28:09.686386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1278
 
5.6%
1102
 
4.8%
669
 
2.9%
) 621
 
2.7%
( 614
 
2.7%
492
 
2.1%
486
 
2.1%
462
 
2.0%
426
 
1.9%
381
 
1.7%
Other values (767) 16483
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20175
87.7%
Close Punctuation 621
 
2.7%
Open Punctuation 614
 
2.7%
Uppercase Letter 535
 
2.3%
Space Separator 486
 
2.1%
Lowercase Letter 458
 
2.0%
Other Punctuation 63
 
0.3%
Decimal Number 59
 
0.3%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1278
 
6.3%
1102
 
5.5%
669
 
3.3%
492
 
2.4%
462
 
2.3%
426
 
2.1%
381
 
1.9%
347
 
1.7%
308
 
1.5%
306
 
1.5%
Other values (701) 14404
71.4%
Uppercase Letter
ValueCountFrequency (%)
F 56
 
10.5%
O 48
 
9.0%
S 42
 
7.9%
C 41
 
7.7%
B 39
 
7.3%
N 28
 
5.2%
T 27
 
5.0%
D 27
 
5.0%
E 25
 
4.7%
R 24
 
4.5%
Other values (14) 178
33.3%
Lowercase Letter
ValueCountFrequency (%)
e 86
18.8%
o 65
14.2%
f 38
8.3%
n 35
 
7.6%
a 31
 
6.8%
s 27
 
5.9%
c 23
 
5.0%
r 23
 
5.0%
t 21
 
4.6%
d 17
 
3.7%
Other values (13) 92
20.1%
Decimal Number
ValueCountFrequency (%)
2 15
25.4%
1 12
20.3%
3 9
15.3%
5 6
 
10.2%
6 5
 
8.5%
4 4
 
6.8%
9 3
 
5.1%
7 3
 
5.1%
8 2
 
3.4%
Other Punctuation
ValueCountFrequency (%)
& 38
60.3%
. 16
25.4%
' 4
 
6.3%
, 3
 
4.8%
· 2
 
3.2%
Close Punctuation
ValueCountFrequency (%)
) 621
100.0%
Open Punctuation
ValueCountFrequency (%)
( 614
100.0%
Space Separator
ValueCountFrequency (%)
486
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20170
87.6%
Common 1846
 
8.0%
Latin 993
 
4.3%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1278
 
6.3%
1102
 
5.5%
669
 
3.3%
492
 
2.4%
462
 
2.3%
426
 
2.1%
381
 
1.9%
347
 
1.7%
308
 
1.5%
306
 
1.5%
Other values (696) 14399
71.4%
Latin
ValueCountFrequency (%)
e 86
 
8.7%
o 65
 
6.5%
F 56
 
5.6%
O 48
 
4.8%
S 42
 
4.2%
C 41
 
4.1%
B 39
 
3.9%
f 38
 
3.8%
n 35
 
3.5%
a 31
 
3.1%
Other values (37) 512
51.6%
Common
ValueCountFrequency (%)
) 621
33.6%
( 614
33.3%
486
26.3%
& 38
 
2.1%
. 16
 
0.9%
2 15
 
0.8%
1 12
 
0.7%
3 9
 
0.5%
5 6
 
0.3%
6 5
 
0.3%
Other values (9) 24
 
1.3%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20170
87.6%
ASCII 2837
 
12.3%
CJK 5
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1278
 
6.3%
1102
 
5.5%
669
 
3.3%
492
 
2.4%
462
 
2.3%
426
 
2.1%
381
 
1.9%
347
 
1.7%
308
 
1.5%
306
 
1.5%
Other values (696) 14399
71.4%
ASCII
ValueCountFrequency (%)
) 621
21.9%
( 614
21.6%
486
17.1%
e 86
 
3.0%
o 65
 
2.3%
F 56
 
2.0%
O 48
 
1.7%
S 42
 
1.5%
C 41
 
1.4%
B 39
 
1.4%
Other values (55) 739
26.0%
None
ValueCountFrequency (%)
· 2
100.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Distinct3474
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
Minimum2001-08-20 00:00:00
Maximum2023-06-29 10:39:30
2023-12-11T04:28:09.926217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:28:10.157896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
I
2648 
U
1232 

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 2648
68.2%
U 1232
31.8%

Length

2023-12-11T04:28:10.705012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:10.825329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2648
68.2%
u 1232
31.8%
Distinct870
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-07-01 02:40:00
2023-12-11T04:28:10.948545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:28:11.119472image/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 size30.4 KiB
식품제조가공업
2799 
기타 식품제조가공업
1052 
도시락제조업
 
29

Length

Max length10
Median length7
Mean length7.8059278
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2799
72.1%
기타 식품제조가공업 1052
 
27.1%
도시락제조업 29
 
0.7%

Length

2023-12-11T04:28:11.328941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:11.469557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3851
78.1%
기타 1052
 
21.3%
도시락제조업 29
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3127
Distinct (%)85.3%
Missing213
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean341812.23
Minimum323038.14
Maximum356965.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:11.648360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum323038.14
5-th percentile331615.93
Q1338690.5
median341511.39
Q3345489.18
95-th percentile352830.38
Maximum356965.56
Range33927.418
Interquartile range (IQR)6798.6818

Descriptive statistics

Standard deviation5855.1202
Coefficient of variation (CV)0.017129639
Kurtosis0.075940433
Mean341812.23
Median Absolute Deviation (MAD)3394.5404
Skewness-0.0056126591
Sum1.2534255 × 109
Variance34282433
MonotonicityNot monotonic
2023-12-11T04:28:11.858142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
339243.983122111 27
 
0.7%
336661.678721891 16
 
0.4%
334406.500395956 7
 
0.2%
346004.036082066 5
 
0.1%
348434.155717765 5
 
0.1%
334946.049344089 4
 
0.1%
346828.290809466 4
 
0.1%
335619.4874035 4
 
0.1%
335996.823890094 4
 
0.1%
326739.522357072 4
 
0.1%
Other values (3117) 3587
92.4%
(Missing) 213
 
5.5%
ValueCountFrequency (%)
323038.137301829 1
 
< 0.1%
323583.427786547 1
 
< 0.1%
325649.192591441 1
 
< 0.1%
325694.253396024 1
 
< 0.1%
326018.881016045 1
 
< 0.1%
326032.481594907 1
 
< 0.1%
326631.950344976 1
 
< 0.1%
326739.522357072 4
0.1%
326760.851184406 1
 
< 0.1%
326950.230818611 1
 
< 0.1%
ValueCountFrequency (%)
356965.555232748 1
 
< 0.1%
356410.892344199 1
 
< 0.1%
356388.525061719 1
 
< 0.1%
356370.038499315 1
 
< 0.1%
356353.915440362 1
 
< 0.1%
356351.617490545 1
 
< 0.1%
356349.757069022 3
0.1%
356345.316761317 1
 
< 0.1%
356335.999166053 1
 
< 0.1%
356331.11092277 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3127
Distinct (%)85.3%
Missing213
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean263366.84
Minimum236164.39
Maximum278073.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:12.104336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum236164.39
5-th percentile253642.24
Q1261071.58
median264007.22
Q3266484.92
95-th percentile271948.59
Maximum278073.62
Range41909.231
Interquartile range (IQR)5413.3375

Descriptive statistics

Standard deviation5444.0469
Coefficient of variation (CV)0.020670966
Kurtosis3.3034282
Mean263366.84
Median Absolute Deviation (MAD)2745.1006
Skewness-1.1249569
Sum9.6576619 × 108
Variance29637647
MonotonicityNot monotonic
2023-12-11T04:28:12.321418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
268026.454530584 27
 
0.7%
261224.266018286 16
 
0.4%
260208.389649832 7
 
0.2%
269131.730019622 5
 
0.1%
264017.165938686 5
 
0.1%
259655.384837927 4
 
0.1%
269356.648959318 4
 
0.1%
261926.024856078 4
 
0.1%
261375.426756584 4
 
0.1%
242019.624631518 4
 
0.1%
Other values (3117) 3587
92.4%
(Missing) 213
 
5.5%
ValueCountFrequency (%)
236164.392417907 1
< 0.1%
237999.437164484 1
< 0.1%
238531.354079775 1
< 0.1%
238772.106217885 1
< 0.1%
238772.407350058 1
< 0.1%
238824.505920574 1
< 0.1%
238893.362765047 1
< 0.1%
238893.829911915 1
< 0.1%
239059.112587617 1
< 0.1%
239098.142264127 1
< 0.1%
ValueCountFrequency (%)
278073.623285671 1
< 0.1%
278032.753892201 1
< 0.1%
277860.926383971 1
< 0.1%
277755.206407657 2
0.1%
277749.024028649 1
< 0.1%
277673.246367512 1
< 0.1%
277500.515376485 1
< 0.1%
277489.106534381 1
< 0.1%
277348.717165567 1
< 0.1%
277022.824656934 1
< 0.1%

위생업태명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
식품제조가공업
2799 
기타 식품제조가공업
1052 
도시락제조업
 
29

Length

Max length10
Median length7
Mean length7.8059278
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2799
72.1%
기타 식품제조가공업 1052
 
27.1%
도시락제조업 29
 
0.7%

Length

2023-12-11T04:28:12.523442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:12.688693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3851
78.1%
기타 1052
 
21.3%
도시락제조업 29
 
0.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
<NA>
3203 
0
677 

Length

Max length4
Median length4
Mean length3.4765464
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3203
82.6%
0 677
 
17.4%

Length

2023-12-11T04:28:12.863008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:13.014599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3203
82.6%
0 677
 
17.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
<NA>
3203 
0
677 

Length

Max length4
Median length4
Mean length3.4765464
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3203
82.6%
0 677
 
17.4%

Length

2023-12-11T04:28:13.208742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:13.358027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3203
82.6%
0 677
 
17.4%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3880
Missing (%)100.0%
Memory size34.2 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3880
Missing (%)100.0%
Memory size34.2 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
상수도전용
2246 
<NA>
1613 
지하수전용
 
16
간이상수도
 
3
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length5
Mean length4.5904639
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2246
57.9%
<NA> 1613
41.6%
지하수전용 16
 
0.4%
간이상수도 3
 
0.1%
상수도(음용)지하수(주방용)겸용 2
 
0.1%

Length

2023-12-11T04:28:13.529544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:13.729784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2246
57.9%
na 1613
41.6%
지하수전용 16
 
0.4%
간이상수도 3
 
0.1%
상수도(음용)지하수(주방용)겸용 2
 
0.1%

총직원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
<NA>
3217 
0
663 

Length

Max length4
Median length4
Mean length3.4873711
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> 3217
82.9%
0 663
 
17.1%

Length

2023-12-11T04:28:13.918793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:14.092301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3217
82.9%
0 663
 
17.1%

본사직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.3%
Missing589
Missing (%)15.2%
Infinite0
Infinite (%)0.0%
Mean0.073230021
Minimum0
Maximum12
Zeros3153
Zeros (%)81.3%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:14.230577image/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 deviation0.46302546
Coefficient of variation (CV)6.3228912
Kurtosis190.07473
Mean0.073230021
Median Absolute Deviation (MAD)0
Skewness11.252389
Sum241
Variance0.21439257
MonotonicityNot monotonic
2023-12-11T04:28:14.385217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3153
81.3%
1 93
 
2.4%
2 17
 
0.4%
3 16
 
0.4%
5 5
 
0.1%
4 4
 
0.1%
12 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 589
 
15.2%
ValueCountFrequency (%)
0 3153
81.3%
1 93
 
2.4%
2 17
 
0.4%
3 16
 
0.4%
4 4
 
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 4
 
0.1%
3 16
 
0.4%
2 17
 
0.4%
1 93
 
2.4%
0 3153
81.3%

공장사무직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct13
Distinct (%)0.4%
Missing577
Missing (%)14.9%
Infinite0
Infinite (%)0.0%
Mean0.20950651
Minimum0
Maximum40
Zeros2882
Zeros (%)74.3%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:14.544879image/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 deviation1.0285185
Coefficient of variation (CV)4.9092435
Kurtosis717.70871
Mean0.20950651
Median Absolute Deviation (MAD)0
Skewness21.325445
Sum692
Variance1.0578502
MonotonicityNot monotonic
2023-12-11T04:28:14.725910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 2882
74.3%
1 316
 
8.1%
2 60
 
1.5%
3 22
 
0.6%
4 8
 
0.2%
6 4
 
0.1%
5 3
 
0.1%
11 2
 
0.1%
15 2
 
0.1%
8 1
 
< 0.1%
Other values (3) 3
 
0.1%
(Missing) 577
 
14.9%
ValueCountFrequency (%)
0 2882
74.3%
1 316
 
8.1%
2 60
 
1.5%
3 22
 
0.6%
4 8
 
0.2%
5 3
 
0.1%
6 4
 
0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
40 1
 
< 0.1%
15 2
 
0.1%
11 2
 
0.1%
10 1
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%
6 4
 
0.1%
5 3
 
0.1%
4 8
 
0.2%
3 22
0.6%

공장판매직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.3%
Missing598
Missing (%)15.4%
Infinite0
Infinite (%)0.0%
Mean0.098110908
Minimum0
Maximum30
Zeros3068
Zeros (%)79.1%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:14.886092image/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 deviation0.66944647
Coefficient of variation (CV)6.8233643
Kurtosis1234.5579
Mean0.098110908
Median Absolute Deviation (MAD)0
Skewness29.403633
Sum322
Variance0.44815858
MonotonicityNot monotonic
2023-12-11T04:28:15.042932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3068
79.1%
1 164
 
4.2%
2 36
 
0.9%
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) 598
 
15.4%
ValueCountFrequency (%)
0 3068
79.1%
1 164
 
4.2%
2 36
 
0.9%
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
 
0.9%
1 164
 
4.2%
0 3068
79.1%

공장생산직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct28
Distinct (%)0.8%
Missing510
Missing (%)13.1%
Infinite0
Infinite (%)0.0%
Mean0.82344214
Minimum0
Maximum220
Zeros2423
Zeros (%)62.4%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:15.216536image/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 deviation4.6311869
Coefficient of variation (CV)5.6241801
Kurtosis1526.6164
Mean0.82344214
Median Absolute Deviation (MAD)0
Skewness34.26271
Sum2775
Variance21.447892
MonotonicityNot monotonic
2023-12-11T04:28:15.395333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 2423
62.4%
1 467
 
12.0%
2 207
 
5.3%
3 109
 
2.8%
4 49
 
1.3%
5 31
 
0.8%
7 18
 
0.5%
6 14
 
0.4%
8 13
 
0.3%
10 7
 
0.2%
Other values (18) 32
 
0.8%
(Missing) 510
 
13.1%
ValueCountFrequency (%)
0 2423
62.4%
1 467
 
12.0%
2 207
 
5.3%
3 109
 
2.8%
4 49
 
1.3%
5 31
 
0.8%
6 14
 
0.4%
7 18
 
0.5%
8 13
 
0.3%
9 6
 
0.2%
ValueCountFrequency (%)
220 1
< 0.1%
83 1
< 0.1%
50 1
< 0.1%
42 1
< 0.1%
35 1
< 0.1%
32 1
< 0.1%
28 1
< 0.1%
25 1
< 0.1%
22 1
< 0.1%
21 1
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
<NA>
1878 
임대
1171 
자가
831 

Length

Max length4
Median length2
Mean length2.9680412
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1878
48.4%
임대 1171
30.2%
자가 831
21.4%

Length

2023-12-11T04:28:15.584070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:15.758150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1878
48.4%
임대 1171
30.2%
자가 831
21.4%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)2.1%
Missing3032
Missing (%)78.1%
Infinite0
Infinite (%)0.0%
Mean731016.27
Minimum0
Maximum50000000
Zeros784
Zeros (%)20.2%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:15.928766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5000000
Maximum50000000
Range50000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3734622.4
Coefficient of variation (CV)5.1088089
Kurtosis95.087281
Mean731016.27
Median Absolute Deviation (MAD)0
Skewness8.7182992
Sum6.199018 × 108
Variance1.3947405 × 1013
MonotonicityNot monotonic
2023-12-11T04:28:16.142748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 784
 
20.2%
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%
40000000 1
 
< 0.1%
18000000 1
 
< 0.1%
Other values (8) 8
 
0.2%
(Missing) 3032
78.1%
ValueCountFrequency (%)
0 784
20.2%
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 (%)3.1%
Missing3033
Missing (%)78.2%
Infinite0
Infinite (%)0.0%
Mean41015.573
Minimum0
Maximum2200000
Zeros783
Zeros (%)20.2%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:16.294286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile300000
Maximum2200000
Range2200000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation183248.57
Coefficient of variation (CV)4.4677803
Kurtosis55.932166
Mean41015.573
Median Absolute Deviation (MAD)0
Skewness6.6070522
Sum34740190
Variance3.3580037 × 1010
MonotonicityNot monotonic
2023-12-11T04:28:16.487859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 783
 
20.2%
300000 13
 
0.3%
500000 11
 
0.3%
400000 5
 
0.1%
600000 4
 
0.1%
800000 3
 
0.1%
350000 3
 
0.1%
200000 3
 
0.1%
250000 2
 
0.1%
700000 2
 
0.1%
Other values (16) 18
 
0.5%
(Missing) 3033
78.2%
ValueCountFrequency (%)
0 783
20.2%
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 size3.9 KiB
False
3878 
True
 
2
ValueCountFrequency (%)
False 3878
99.9%
True 2
 
0.1%
2023-12-11T04:28:16.642893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct581
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.462332
Minimum0
Maximum4673.38
Zeros3049
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size34.2 KiB
2023-12-11T04:28:16.809629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile47.8515
Maximum4673.38
Range4673.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation122.88713
Coefficient of variation (CV)9.1282194
Kurtosis1008.8236
Mean13.462332
Median Absolute Deviation (MAD)0
Skewness29.033616
Sum52233.85
Variance15101.245
MonotonicityNot monotonic
2023-12-11T04:28:17.044498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3049
78.6%
3.0 24
 
0.6%
6.0 17
 
0.4%
1.0 15
 
0.4%
2.0 12
 
0.3%
4.0 12
 
0.3%
3.3 10
 
0.3%
347.13 9
 
0.2%
1.2 8
 
0.2%
4.5 8
 
0.2%
Other values (571) 716
 
18.5%
ValueCountFrequency (%)
0.0 3049
78.6%
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%
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%
569.6 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3880
Missing (%)100.0%
Memory size34.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3880
Missing (%)100.0%
Memory size34.2 KiB

홈페이지
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.4 KiB
<NA>
3878 
4
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.9984536
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> 3878
99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Length

2023-12-11T04:28:17.239591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:28:17.396770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3878
99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품제조가공업07_22_11_P34100003410000-106-2001-000092001-12-15<NA>3폐업2폐업2002-02-04<NA><NA><NA>053 421590012.66700-802대구광역시 중구 남산동 0912-11번지<NA><NA>고려식품2002-11-14 00:00:00I2018-08-31 23:59:59식품제조가공업343976.878848263799.748137식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0302임대<NA><NA>N0.0<NA><NA><NA>
12식품제조가공업07_22_11_P34100003410000-106-2003-000052003-10-31<NA>3폐업2폐업2004-08-31<NA><NA><NA>257123173.26700-809대구광역시 중구 대봉동 0121-0238번지<NA><NA>두레식품A공장2003-12-16 00:00:00I2018-08-31 23:59:59식품제조가공업344944.08694263011.296422식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0016임대<NA><NA>N0.0<NA><NA><NA>
23식품제조가공업07_22_11_P34100003410000-106-2003-000062003-12-10<NA>3폐업2폐업2006-02-16<NA><NA><NA>053 522507439.0700-380대구광역시 중구 달성동 0288-0013번지<NA><NA>한국식품2005-04-07 00:00:00I2018-08-31 23:59:59식품제조가공업342640.368189264893.236838식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0001임대<NA><NA>N0.0<NA><NA><NA>
34식품제조가공업07_22_11_P34100003410000-106-2003-000072003-12-30<NA>3폐업2폐업2015-01-13<NA><NA><NA>053 421353052.0700-413대구광역시 중구 삼덕동3가 0167-0001번지 (지상1층)대구광역시 중구 국채보상로150길 60, 1층 (삼덕동3가)41946우리두리식품2012-02-01 15:38:47I2018-08-31 23:59:59식품제조가공업345392.220953264045.219028식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0012임대<NA><NA>N0.0<NA><NA><NA>
45식품제조가공업07_22_11_P34100003410000-106-2004-000012004-03-15<NA>3폐업2폐업2004-12-04<NA><NA><NA><NA>74.55700-809대구광역시 중구 대봉동 0040-0033번지<NA><NA>원숭이식품2004-04-09 00:00:00I2018-08-31 23:59:59식품제조가공업344927.7812263298.66826식품제조가공업00<NA><NA>상수도전용<NA>0111임대<NA><NA>N0.0<NA><NA><NA>
56식품제조가공업07_22_11_P34100003410000-106-2004-000022004-05-07<NA>3폐업2폐업2005-03-24<NA><NA><NA>053 424497914.7700-111대구광역시 중구 태평로1가 0001-0186번지<NA><NA>동북상회2004-11-02 00:00:00I2018-08-31 23:59:59식품제조가공업344182.487426265065.535111식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0011<NA><NA><NA>N0.0<NA><NA><NA>
67식품제조가공업07_22_11_P34100003410000-106-2004-000032004-05-24<NA>3폐업2폐업2015-04-24<NA><NA><NA>053 256433741.85700-837대구광역시 중구 남산동 2466-0001번지 보성황실아파트 116동 105호대구광역시 중구 남산로13길 17, 1층 (남산동, 보성황실아파트 116동 105호)41978황실떡집2015-03-04 14:34:02I2018-08-31 23:59:59식품제조가공업342754.486268263376.49575식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0002자가<NA><NA>N0.0<NA><NA><NA>
78식품제조가공업07_22_11_P34100003410000-106-2004-000042004-06-29<NA>3폐업2폐업2004-09-08<NA><NA><NA>053 4240540120.6700-823대구광역시 중구 봉산동 0165-0007번지<NA><NA>에프엔에스2004-09-01 00:00:00I2018-08-31 23:59:59식품제조가공업344341.820223263777.999999식품제조가공업00<NA><NA>상수도전용<NA>0121임대<NA><NA>N0.0<NA><NA><NA>
89식품제조가공업07_22_11_P34100003410000-106-2004-000052004-11-01<NA>3폐업2폐업2008-07-17<NA><NA><NA>053 422331834.52700-845대구광역시 중구 동인동3가 0302-0002번지<NA><NA>이유통2007-11-26 10:32:51I2018-08-31 23:59:59식품제조가공업345483.514708264655.185763식품제조가공업<NA><NA><NA><NA>상수도전용<NA>1000자가<NA><NA>N0.0<NA><NA><NA>
910식품제조가공업07_22_11_P34100003410000-106-2004-000062004-11-11<NA>3폐업2폐업2005-09-06<NA><NA><NA><NA>25.23700-421대구광역시 중구 동인동1가 0196번지<NA><NA>불스푸드2005-03-21 00:00:00I2018-08-31 23:59:59식품제조가공업344696.914116264897.878354식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0111자가<NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
38703871식품제조가공업07_22_11_P34800003480000-106-2020-000072020-06-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>71.04<NA>대구광역시 달성군 옥포읍 본리리 2649 달성삼환나우빌대구광역시 달성군 옥포읍 비슬로447길 11, 상가동 103호 (달성삼환나우빌)42971수수방앗간2021-12-09 11:39:48U2021-12-11 02:40:00기타 식품제조가공업332388.406477255542.068583기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA>1<NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
38713872식품제조가공업07_22_11_P34800003480000-106-2021-000132021-09-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>115.71<NA>대구광역시 달성군 옥포읍 본리리 1063대구광역시 달성군 옥포읍 본리로 88, 1층42970(주)그린쿡2021-09-24 10:11:35I2021-09-26 00:22:48기타 식품제조가공업331483.699407255820.217563기타 식품제조가공업00<NA><NA>상수도전용00000<NA>00N25.41<NA><NA><NA>
38723873식품제조가공업07_22_11_P34800003480000-106-2021-000112021-09-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>486.93711-856대구광역시 달성군 논공읍 노이리 1156-2대구광역시 달성군 논공읍 노이길 173, 3층42975파인식품 2공장2021-09-08 17:34:43I2021-09-10 00:22:49기타 식품제조가공업329428.047607252331.99552기타 식품제조가공업00<NA><NA>상수도전용00000<NA>00N0.0<NA><NA><NA>
38733874식품제조가공업07_22_11_P34800003480000-106-2021-000122021-09-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.57711-839대구광역시 달성군 화원읍 성산리 514-4대구광역시 달성군 화원읍 성화로 20, 1층42946행복울타리2022-10-11 16:40:00U2022-10-13 02:40:00기타 식품제조가공업334662.637839256680.908339기타 식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
38743875식품제조가공업07_22_11_P34800003480000-106-2021-000102021-09-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>212.69<NA>대구광역시 달성군 옥포읍 본리리 2315대구광역시 달성군 옥포읍 비슬로434길 5, 1층42970모든찬2021-09-01 08:39:27I2021-09-03 00:22:50기타 식품제조가공업331839.170903255123.033878기타 식품제조가공업00<NA><NA>상수도전용00000<NA>00N87.19<NA><NA><NA>
38753876식품제조가공업07_22_11_P34800003480000-106-2013-000152013-10-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>78.42711-864대구광역시 달성군 가창면 용계리 233-16대구광역시 달성군 가창면 가창로213길 8-1, 1층42936보리채움2022-02-07 17:38:57U2022-02-09 02:40:00식품제조가공업346565.952924256681.467415식품제조가공업00<NA><NA>상수도전용00000임대00N0.0<NA><NA><NA>
38763877식품제조가공업07_22_11_P34800003480000-106-2022-000152022-11-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>55.54<NA>대구광역시 달성군 현풍읍 하리 249-28대구광역시 달성군 현풍읍 비슬로120길 23, 1층43004선정 F&S2023-05-09 09:49:21U2023-05-11 02:40:00기타 식품제조가공업330658.653379244623.641022기타 식품제조가공업00<NA><NA><NA>00000<NA>00N2.84<NA><NA><NA>
38773878식품제조가공업07_22_11_P34800003480000-106-2022-000162022-12-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.16711-814대구광역시 달성군 다사읍 세천리 1579-7대구광역시 달성군 다사읍 세천로9길 45, 1층42922주식회사 이용재베이커리2022-12-15 09:39:08I2022-12-17 00:40:08기타 식품제조가공업333465.190397264920.305546기타 식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
38783879식품제조가공업07_22_11_P34800003480000-106-2023-000012023-01-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0<NA>대구광역시 달성군 옥포읍 본리리 2617-3대구광역시 달성군 옥포읍 비슬로447길 41, 105호42971엘씨로스팅랩2023-01-26 14:38:36I2023-01-28 00:40:49기타 식품제조가공업332454.432485255797.97166기타 식품제조가공업00<NA><NA><NA>00000임대00N0.0<NA><NA><NA>
38793880식품제조가공업07_22_11_P34800003480000-106-2022-000172022-12-22<NA>1영업/정상1영업<NA><NA><NA><NA>053 611 9131314.5<NA>대구광역시 달성군 옥포읍 신당리 1184대구광역시 달성군 옥포읍 신당5길 1042969(주)완뚝2022-12-22 09:57:38I2022-12-24 00:40:15기타 식품제조가공업330226.370111256028.075523기타 식품제조가공업00<NA><NA><NA>00000<NA>00N141.0<NA><NA><NA>