Overview

Dataset statistics

Number of variables47
Number of observations4035
Missing cells46182
Missing cells (%)24.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory403.0 B

Variable types

Numeric13
Categorical15
Text6
DateTime4
Unsupported8
Boolean1

Dataset

Description24년03월_6270000_대구광역시_07_22_11_P_식품제조가공업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000106619&dataSetDetailId=DDI_0000106669&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
급수시설구분명 is highly imbalanced (53.7%)Imbalance
다중이용업소여부 is highly imbalanced (99.4%)Imbalance
홈페이지 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 4035 (100.0%) missing valuesMissing
폐업일자 has 1070 (26.5%) missing valuesMissing
휴업시작일자 has 4035 (100.0%) missing valuesMissing
휴업종료일자 has 4035 (100.0%) missing valuesMissing
재개업일자 has 4035 (100.0%) missing valuesMissing
소재지전화 has 1194 (29.6%) missing valuesMissing
소재지면적 has 137 (3.4%) missing valuesMissing
소재지우편번호 has 172 (4.3%) missing valuesMissing
도로명전체주소 has 1390 (34.4%) missing valuesMissing
도로명우편번호 has 1417 (35.1%) missing valuesMissing
좌표정보(X) has 217 (5.4%) missing valuesMissing
좌표정보(Y) has 217 (5.4%) missing valuesMissing
영업장주변구분명 has 4035 (100.0%) missing valuesMissing
등급구분명 has 4035 (100.0%) missing valuesMissing
본사직원수 has 567 (14.1%) missing valuesMissing
공장사무직직원수 has 554 (13.7%) missing valuesMissing
공장판매직직원수 has 573 (14.2%) missing valuesMissing
공장생산직직원수 has 489 (12.1%) missing valuesMissing
보증액 has 2939 (72.8%) missing valuesMissing
월세액 has 2940 (72.9%) missing valuesMissing
전통업소지정번호 has 4035 (100.0%) missing valuesMissing
전통업소주된음식 has 4035 (100.0%) missing valuesMissing
소재지면적 is highly skewed (γ1 = 20.55183201)Skewed
공장사무직직원수 is highly skewed (γ1 = 21.4957765)Skewed
공장판매직직원수 is highly skewed (γ1 = 29.71451801)Skewed
공장생산직직원수 is highly skewed (γ1 = 34.47143563)Skewed
시설총규모 is highly skewed (γ1 = 28.32874844)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 3324 (82.4%) zerosZeros
공장사무직직원수 has 3042 (75.4%) zerosZeros
공장판매직직원수 has 3245 (80.4%) zerosZeros
공장생산직직원수 has 2562 (63.5%) zerosZeros
보증액 has 1031 (25.6%) zerosZeros
월세액 has 1030 (25.5%) zerosZeros
시설총규모 has 3129 (77.5%) zerosZeros

Reproduction

Analysis started2024-04-29 12:32:38.618919
Analysis finished2024-04-29 12:32:40.206536
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct4035
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018
Minimum1
Maximum4035
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:40.317003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile202.7
Q11009.5
median2018
Q33026.5
95-th percentile3833.3
Maximum4035
Range4034
Interquartile range (IQR)2017

Descriptive statistics

Standard deviation1164.9485
Coefficient of variation (CV)0.57727874
Kurtosis-1.2
Mean2018
Median Absolute Deviation (MAD)1009
Skewness0
Sum8142630
Variance1357105
MonotonicityStrictly increasing
2024-04-29T21:32:40.472445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2697 1
 
< 0.1%
2684 1
 
< 0.1%
2685 1
 
< 0.1%
2686 1
 
< 0.1%
2687 1
 
< 0.1%
2688 1
 
< 0.1%
2689 1
 
< 0.1%
2690 1
 
< 0.1%
2691 1
 
< 0.1%
Other values (4025) 4025
99.8%
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 (%)
4035 1
< 0.1%
4034 1
< 0.1%
4033 1
< 0.1%
4032 1
< 0.1%
4031 1
< 0.1%
4030 1
< 0.1%
4029 1
< 0.1%
4028 1
< 0.1%
4027 1
< 0.1%
4026 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
식품제조가공업
4035 

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 4035
100.0%

Length

2024-04-29T21:32:40.596153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:40.681709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 4035
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
07_22_11_P
4035 

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 4035
100.0%

Length

2024-04-29T21:32:40.774731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:40.857595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_11_p 4035
100.0%

개방자치단체코드
Real number (ℝ)

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3481815.6
Minimum3410000
Maximum5141000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:40.938020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33470000
95-th percentile3480000
Maximum5141000
Range1731000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation230851.71
Coefficient of variation (CV)0.066302107
Kurtosis47.345882
Mean3481815.6
Median Absolute Deviation (MAD)20000
Skewness6.9918921
Sum1.4049126 × 1010
Variance5.3292512 × 1010
MonotonicityIncreasing
2024-04-29T21:32:41.030571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
3450000 980
24.3%
3470000 687
17.0%
3480000 502
12.4%
3420000 472
11.7%
3460000 458
11.4%
3430000 377
 
9.3%
3440000 250
 
6.2%
3410000 233
 
5.8%
5141000 76
 
1.9%
ValueCountFrequency (%)
3410000 233
 
5.8%
3420000 472
11.7%
3430000 377
 
9.3%
3440000 250
 
6.2%
3450000 980
24.3%
3460000 458
11.4%
3470000 687
17.0%
3480000 502
12.4%
5141000 76
 
1.9%
ValueCountFrequency (%)
5141000 76
 
1.9%
3480000 502
12.4%
3470000 687
17.0%
3460000 458
11.4%
3450000 980
24.3%
3440000 250
 
6.2%
3430000 377
 
9.3%
3420000 472
11.7%
3410000 233
 
5.8%

관리번호
Text

UNIQUE 

Distinct4035
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
2024-04-29T21:32:41.216196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters88770
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

Unique4035 ?
Unique (%)100.0%

Sample

1st row3410000-106-2018-00003
2nd row3410000-106-2018-00005
3rd row3410000-106-2018-00006
4th row3410000-106-2018-00007
5th row3410000-106-2001-00008
ValueCountFrequency (%)
3410000-106-2018-00003 1
 
< 0.1%
3460000-106-2000-00012 1
 
< 0.1%
3460000-106-2016-00002 1
 
< 0.1%
3460000-106-2016-00028 1
 
< 0.1%
3460000-106-2017-00001 1
 
< 0.1%
3460000-106-2017-00002 1
 
< 0.1%
3460000-106-2017-00003 1
 
< 0.1%
3460000-106-2017-00004 1
 
< 0.1%
3460000-106-2017-00008 1
 
< 0.1%
3460000-106-2017-00009 1
 
< 0.1%
Other values (4025) 4025
99.8%
2024-04-29T21:32:41.529817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40351
45.5%
- 12105
 
13.6%
1 8554
 
9.6%
2 6178
 
7.0%
3 5474
 
6.2%
6 5267
 
5.9%
4 5177
 
5.8%
5 1839
 
2.1%
7 1423
 
1.6%
8 1203
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76665
86.4%
Dash Punctuation 12105
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40351
52.6%
1 8554
 
11.2%
2 6178
 
8.1%
3 5474
 
7.1%
6 5267
 
6.9%
4 5177
 
6.8%
5 1839
 
2.4%
7 1423
 
1.9%
8 1203
 
1.6%
9 1199
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 12105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88770
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40351
45.5%
- 12105
 
13.6%
1 8554
 
9.6%
2 6178
 
7.0%
3 5474
 
6.2%
6 5267
 
5.9%
4 5177
 
5.8%
5 1839
 
2.1%
7 1423
 
1.6%
8 1203
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88770
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40351
45.5%
- 12105
 
13.6%
1 8554
 
9.6%
2 6178
 
7.0%
3 5474
 
6.2%
6 5267
 
5.9%
4 5177
 
5.8%
5 1839
 
2.1%
7 1423
 
1.6%
8 1203
 
1.4%
Distinct2860
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
Minimum1968-12-18 00:00:00
Maximum2024-03-28 00:00:00
2024-04-29T21:32:41.680625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:32:41.813676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4035
Missing (%)100.0%
Memory size35.6 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
3
2965 
1
1070 

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 2965
73.5%
1 1070
 
26.5%

Length

2024-04-29T21:32:41.932505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:42.018097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2965
73.5%
1 1070
 
26.5%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
폐업
2965 
영업/정상
1070 

Length

Max length5
Median length2
Mean length2.795539
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2965
73.5%
영업/정상 1070
 
26.5%

Length

2024-04-29T21:32:42.124589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:42.215060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2965
73.5%
영업/정상 1070
 
26.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
2
2965 
1
1070 

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 2965
73.5%
1 1070
 
26.5%

Length

2024-04-29T21:32:42.305438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:42.404530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2965
73.5%
1 1070
 
26.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
폐업
2965 
영업
1070 

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 2965
73.5%
영업 1070
 
26.5%

Length

2024-04-29T21:32:42.505351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:42.593652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2965
73.5%
영업 1070
 
26.5%

폐업일자
Date

MISSING 

Distinct2200
Distinct (%)74.2%
Missing1070
Missing (%)26.5%
Memory size31.7 KiB
Minimum2000-04-24 00:00:00
Maximum2024-03-13 00:00:00
2024-04-29T21:32:42.692979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:32:42.842675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4035
Missing (%)100.0%
Memory size35.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4035
Missing (%)100.0%
Memory size35.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4035
Missing (%)100.0%
Memory size35.6 KiB

소재지전화
Text

MISSING 

Distinct2625
Distinct (%)92.4%
Missing1194
Missing (%)29.6%
Memory size31.7 KiB
2024-04-29T21:32:43.138435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.87434
Min length7

Characters and Unicode

Total characters30894
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

Unique2424 ?
Unique (%)85.3%

Sample

1st row053 257 7723
2nd row053 2568222
3rd row053 4215900
4th row2571231
5th row053 5225074
ValueCountFrequency (%)
053 2044
33.9%
070 70
 
1.2%
054 63
 
1.0%
311 22
 
0.4%
382 15
 
0.2%
383 15
 
0.2%
313 15
 
0.2%
314 13
 
0.2%
611 13
 
0.2%
621 13
 
0.2%
Other values (2781) 3747
62.1%
2024-04-29T21:32:43.546676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 5058
16.4%
3 4533
14.7%
0 4430
14.3%
3275
10.6%
2 2215
7.2%
6 2151
7.0%
1 2103
6.8%
7 1957
 
6.3%
8 1891
 
6.1%
4 1748
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27619
89.4%
Space Separator 3275
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 5058
18.3%
3 4533
16.4%
0 4430
16.0%
2 2215
8.0%
6 2151
7.8%
1 2103
7.6%
7 1957
 
7.1%
8 1891
 
6.8%
4 1748
 
6.3%
9 1533
 
5.6%
Space Separator
ValueCountFrequency (%)
3275
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30894
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 5058
16.4%
3 4533
14.7%
0 4430
14.3%
3275
10.6%
2 2215
7.2%
6 2151
7.0%
1 2103
6.8%
7 1957
 
6.3%
8 1891
 
6.1%
4 1748
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30894
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 5058
16.4%
3 4533
14.7%
0 4430
14.3%
3275
10.6%
2 2215
7.2%
6 2151
7.0%
1 2103
6.8%
7 1957
 
6.3%
8 1891
 
6.1%
4 1748
 
5.7%

소재지면적
Real number (ℝ)

MISSING  SKEWED 

Distinct2803
Distinct (%)71.9%
Missing137
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean206.43168
Minimum0
Maximum31752
Zeros16
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:43.677509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.6
Q135.7
median69.44
Q3153.3425
95-th percentile498.7245
Maximum31752
Range31752
Interquartile range (IQR)117.6425

Descriptive statistics

Standard deviation983.91911
Coefficient of variation (CV)4.7663184
Kurtosis542.14508
Mean206.43168
Median Absolute Deviation (MAD)42.045
Skewness20.551832
Sum804670.69
Variance968096.81
MonotonicityNot monotonic
2024-04-29T21:32:43.803488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.0 31
 
0.8%
20.0 28
 
0.7%
33.0 28
 
0.7%
40.0 17
 
0.4%
0.0 16
 
0.4%
30.0 15
 
0.4%
15.0 13
 
0.3%
26.4 13
 
0.3%
38.0 12
 
0.3%
132.0 12
 
0.3%
Other values (2793) 3713
92.0%
(Missing) 137
 
3.4%
ValueCountFrequency (%)
0.0 16
0.4%
3.0 2
 
< 0.1%
3.2 1
 
< 0.1%
3.24 1
 
< 0.1%
3.6 1
 
< 0.1%
4.67 1
 
< 0.1%
4.72 1
 
< 0.1%
4.8 1
 
< 0.1%
5.0 3
 
0.1%
5.28 1
 
< 0.1%
ValueCountFrequency (%)
31752.0 1
< 0.1%
29708.82 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%
10547.09 1
< 0.1%
9439.4 1
< 0.1%
9051.41 1
< 0.1%

소재지우편번호
Text

MISSING 

Distinct557
Distinct (%)14.4%
Missing172
Missing (%)4.3%
Memory size31.7 KiB
2024-04-29T21:32:44.107932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters27041
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

Unique103 ?
Unique (%)2.7%

Sample

1st row700-413
2nd row700-421
3rd row700-822
4th row700-093
5th row700-300
ValueCountFrequency (%)
702-825 91
 
2.4%
702-061 84
 
2.2%
703-830 57
 
1.5%
703-833 50
 
1.3%
702-816 47
 
1.2%
704-080 44
 
1.1%
702-903 38
 
1.0%
704-900 37
 
1.0%
711-851 36
 
0.9%
704-190 34
 
0.9%
Other values (547) 3345
86.6%
2024-04-29T21:32:44.519652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5401
20.0%
7 4267
15.8%
- 3863
14.3%
8 3130
11.6%
1 2531
9.4%
2 2057
 
7.6%
4 1537
 
5.7%
3 1532
 
5.7%
6 1041
 
3.8%
5 989
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23178
85.7%
Dash Punctuation 3863
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5401
23.3%
7 4267
18.4%
8 3130
13.5%
1 2531
10.9%
2 2057
 
8.9%
4 1537
 
6.6%
3 1532
 
6.6%
6 1041
 
4.5%
5 989
 
4.3%
9 693
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 3863
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27041
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5401
20.0%
7 4267
15.8%
- 3863
14.3%
8 3130
11.6%
1 2531
9.4%
2 2057
 
7.6%
4 1537
 
5.7%
3 1532
 
5.7%
6 1041
 
3.8%
5 989
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27041
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5401
20.0%
7 4267
15.8%
- 3863
14.3%
8 3130
11.6%
1 2531
9.4%
2 2057
 
7.6%
4 1537
 
5.7%
3 1532
 
5.7%
6 1041
 
3.8%
5 989
 
3.7%
Distinct3745
Distinct (%)93.4%
Missing26
Missing (%)0.6%
Memory size31.7 KiB
2024-04-29T21:32:44.857836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length49
Mean length23.655775
Min length15

Characters and Unicode

Total characters94836
Distinct characters307
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

Unique3530 ?
Unique (%)88.1%

Sample

1st row대구광역시 중구 삼덕동3가 306-3
2nd row대구광역시 중구 동인동1가 0294-0004 지상 1층
3rd row대구광역시 중구 봉산동 24-9번지
4th row대구광역시 중구 동성로3가 0120-0002번지
5th row대구광역시 중구 인교동 0267-0001번지
ValueCountFrequency (%)
대구광역시 4009
22.3%
북구 973
 
5.4%
달서구 684
 
3.8%
달성군 498
 
2.8%
동구 473
 
2.6%
수성구 445
 
2.5%
서구 378
 
2.1%
남구 250
 
1.4%
중구 233
 
1.3%
지상1층 200
 
1.1%
Other values (4220) 9867
54.8%
2024-04-29T21:32:45.362231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17967
18.9%
7562
 
8.0%
1 4690
 
4.9%
4361
 
4.6%
4193
 
4.4%
4070
 
4.3%
4014
 
4.2%
4014
 
4.2%
3351
 
3.5%
- 3327
 
3.5%
Other values (297) 37287
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52814
55.7%
Decimal Number 19775
 
20.9%
Space Separator 17967
 
18.9%
Dash Punctuation 3327
 
3.5%
Close Punctuation 345
 
0.4%
Open Punctuation 345
 
0.4%
Other Punctuation 128
 
0.1%
Uppercase Letter 117
 
0.1%
Math Symbol 15
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7562
14.3%
4361
 
8.3%
4193
 
7.9%
4070
 
7.7%
4014
 
7.6%
4014
 
7.6%
3351
 
6.3%
2820
 
5.3%
1266
 
2.4%
1254
 
2.4%
Other values (268) 15909
30.1%
Decimal Number
ValueCountFrequency (%)
1 4690
23.7%
2 2482
12.6%
0 2153
10.9%
3 2035
10.3%
4 1670
 
8.4%
5 1540
 
7.8%
6 1462
 
7.4%
7 1339
 
6.8%
8 1236
 
6.3%
9 1168
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 52
44.4%
A 49
41.9%
C 8
 
6.8%
T 2
 
1.7%
D 2
 
1.7%
E 2
 
1.7%
P 1
 
0.9%
J 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 118
92.2%
. 7
 
5.5%
/ 2
 
1.6%
: 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
c 1
33.3%
Space Separator
ValueCountFrequency (%)
17967
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3327
100.0%
Close Punctuation
ValueCountFrequency (%)
) 345
100.0%
Open Punctuation
ValueCountFrequency (%)
( 345
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52814
55.7%
Common 41902
44.2%
Latin 120
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7562
14.3%
4361
 
8.3%
4193
 
7.9%
4070
 
7.7%
4014
 
7.6%
4014
 
7.6%
3351
 
6.3%
2820
 
5.3%
1266
 
2.4%
1254
 
2.4%
Other values (268) 15909
30.1%
Common
ValueCountFrequency (%)
17967
42.9%
1 4690
 
11.2%
- 3327
 
7.9%
2 2482
 
5.9%
0 2153
 
5.1%
3 2035
 
4.9%
4 1670
 
4.0%
5 1540
 
3.7%
6 1462
 
3.5%
7 1339
 
3.2%
Other values (9) 3237
 
7.7%
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%
c 1
 
0.8%
J 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52814
55.7%
ASCII 42022
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17967
42.8%
1 4690
 
11.2%
- 3327
 
7.9%
2 2482
 
5.9%
0 2153
 
5.1%
3 2035
 
4.8%
4 1670
 
4.0%
5 1540
 
3.7%
6 1462
 
3.5%
7 1339
 
3.2%
Other values (19) 3357
 
8.0%
Hangul
ValueCountFrequency (%)
7562
14.3%
4361
 
8.3%
4193
 
7.9%
4070
 
7.7%
4014
 
7.6%
4014
 
7.6%
3351
 
6.3%
2820
 
5.3%
1266
 
2.4%
1254
 
2.4%
Other values (268) 15909
30.1%

도로명전체주소
Text

MISSING 

Distinct2525
Distinct (%)95.5%
Missing1390
Missing (%)34.4%
Memory size31.7 KiB
2024-04-29T21:32:45.692376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length54
Mean length27.897543
Min length19

Characters and Unicode

Total characters73789
Distinct characters337
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

Unique2417 ?
Unique (%)91.4%

Sample

1st row대구광역시 중구 달구벌대로443길 26-11, 1층 (삼덕동3가)
2nd row대구광역시 중구 동덕로 184-1, 지상 1층 (동인동1가)
3rd row대구광역시 중구 동성로3길 9-5 (봉산동)
4th row대구광역시 중구 동성로1길 29-23 (동성로3가)
5th row대구광역시 중구 국채보상로150길 60, 1층 (삼덕동3가)
ValueCountFrequency (%)
대구광역시 2645
 
17.7%
1층 678
 
4.5%
북구 643
 
4.3%
달서구 394
 
2.6%
달성군 344
 
2.3%
동구 332
 
2.2%
수성구 305
 
2.0%
서구 243
 
1.6%
남구 167
 
1.1%
중구 162
 
1.1%
Other values (2836) 8995
60.3%
2024-04-29T21:32:46.380026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12264
 
16.6%
5144
 
7.0%
1 3380
 
4.6%
3179
 
4.3%
3142
 
4.3%
2758
 
3.7%
2665
 
3.6%
2646
 
3.6%
2401
 
3.3%
) 2364
 
3.2%
Other values (327) 33846
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42190
57.2%
Space Separator 12264
 
16.6%
Decimal Number 12068
 
16.4%
Close Punctuation 2364
 
3.2%
Open Punctuation 2364
 
3.2%
Other Punctuation 1519
 
2.1%
Dash Punctuation 834
 
1.1%
Uppercase Letter 153
 
0.2%
Math Symbol 31
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5144
 
12.2%
3179
 
7.5%
3142
 
7.4%
2758
 
6.5%
2665
 
6.3%
2646
 
6.3%
2401
 
5.7%
1816
 
4.3%
1156
 
2.7%
1133
 
2.7%
Other values (294) 16150
38.3%
Uppercase Letter
ValueCountFrequency (%)
B 65
42.5%
A 57
37.3%
C 12
 
7.8%
T 4
 
2.6%
D 3
 
2.0%
E 3
 
2.0%
J 2
 
1.3%
P 2
 
1.3%
R 1
 
0.7%
F 1
 
0.7%
Other values (3) 3
 
2.0%
Decimal Number
ValueCountFrequency (%)
1 3380
28.0%
2 1798
14.9%
3 1384
11.5%
4 1021
 
8.5%
5 917
 
7.6%
6 866
 
7.2%
0 792
 
6.6%
7 748
 
6.2%
8 616
 
5.1%
9 546
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 1511
99.5%
· 4
 
0.3%
. 4
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
12264
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2364
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2364
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 834
100.0%
Math Symbol
ValueCountFrequency (%)
~ 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42190
57.2%
Common 31444
42.6%
Latin 155
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5144
 
12.2%
3179
 
7.5%
3142
 
7.4%
2758
 
6.5%
2665
 
6.3%
2646
 
6.3%
2401
 
5.7%
1816
 
4.3%
1156
 
2.7%
1133
 
2.7%
Other values (294) 16150
38.3%
Common
ValueCountFrequency (%)
12264
39.0%
1 3380
 
10.7%
) 2364
 
7.5%
( 2364
 
7.5%
2 1798
 
5.7%
, 1511
 
4.8%
3 1384
 
4.4%
4 1021
 
3.2%
5 917
 
2.9%
6 866
 
2.8%
Other values (8) 3575
 
11.4%
Latin
ValueCountFrequency (%)
B 65
41.9%
A 57
36.8%
C 12
 
7.7%
T 4
 
2.6%
D 3
 
1.9%
E 3
 
1.9%
J 2
 
1.3%
P 2
 
1.3%
R 1
 
0.6%
e 1
 
0.6%
Other values (5) 5
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42190
57.2%
ASCII 31595
42.8%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12264
38.8%
1 3380
 
10.7%
) 2364
 
7.5%
( 2364
 
7.5%
2 1798
 
5.7%
, 1511
 
4.8%
3 1384
 
4.4%
4 1021
 
3.2%
5 917
 
2.9%
6 866
 
2.7%
Other values (22) 3726
 
11.8%
Hangul
ValueCountFrequency (%)
5144
 
12.2%
3179
 
7.5%
3142
 
7.4%
2758
 
6.5%
2665
 
6.3%
2646
 
6.3%
2401
 
5.7%
1816
 
4.3%
1156
 
2.7%
1133
 
2.7%
Other values (294) 16150
38.3%
None
ValueCountFrequency (%)
· 4
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct881
Distinct (%)33.7%
Missing1417
Missing (%)35.1%
Infinite0
Infinite (%)0.0%
Mean42045.227
Minimum41000
Maximum43166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:46.526142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41102.85
Q141490
median41947
Q342698
95-th percentile42977
Maximum43166
Range2166
Interquartile range (IQR)1208

Descriptive statistics

Standard deviation635.56163
Coefficient of variation (CV)0.015116142
Kurtosis-1.32092
Mean42045.227
Median Absolute Deviation (MAD)506
Skewness0.13342931
Sum1.100744 × 108
Variance403938.58
MonotonicityNot monotonic
2024-04-29T21:32:46.669961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41485 45
 
1.1%
41582 44
 
1.1%
41490 39
 
1.0%
41557 25
 
0.6%
41488 24
 
0.6%
42701 22
 
0.5%
41755 20
 
0.5%
42703 19
 
0.5%
42970 19
 
0.5%
42974 19
 
0.5%
Other values (871) 2342
58.0%
(Missing) 1417
35.1%
ValueCountFrequency (%)
41000 8
0.2%
41001 3
 
0.1%
41002 5
0.1%
41004 1
 
< 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%
ValueCountFrequency (%)
43166 3
0.1%
43165 1
 
< 0.1%
43163 1
 
< 0.1%
43162 1
 
< 0.1%
43161 1
 
< 0.1%
43160 3
0.1%
43159 1
 
< 0.1%
43158 3
0.1%
43154 1
 
< 0.1%
43153 1
 
< 0.1%
Distinct3425
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
2024-04-29T21:32:46.926332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length5.9724907
Min length1

Characters and Unicode

Total characters24099
Distinct characters791
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

Unique2994 ?
Unique (%)74.2%

Sample

1st row다사랑보호작업장
2nd row오프더스트릿(off the street)
3rd row문현사커피로스터스
4th row이박사마카롱디저트LBG
5th row북성로찐빵
ValueCountFrequency (%)
주식회사 126
 
2.8%
농업회사법인 17
 
0.4%
15
 
0.3%
커피 15
 
0.3%
우리식품 14
 
0.3%
푸드 13
 
0.3%
coffee 12
 
0.3%
food 11
 
0.2%
제일식품 11
 
0.2%
현대식품 9
 
0.2%
Other values (3622) 4314
94.7%
2024-04-29T21:32:47.326568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1314
 
5.5%
1124
 
4.7%
711
 
3.0%
) 654
 
2.7%
( 646
 
2.7%
524
 
2.2%
508
 
2.1%
477
 
2.0%
444
 
1.8%
399
 
1.7%
Other values (781) 17298
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21096
87.5%
Close Punctuation 654
 
2.7%
Open Punctuation 646
 
2.7%
Uppercase Letter 569
 
2.4%
Space Separator 524
 
2.2%
Lowercase Letter 475
 
2.0%
Other Punctuation 69
 
0.3%
Decimal Number 62
 
0.3%
Dash Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1314
 
6.2%
1124
 
5.3%
711
 
3.4%
508
 
2.4%
477
 
2.3%
444
 
2.1%
399
 
1.9%
373
 
1.8%
320
 
1.5%
317
 
1.5%
Other values (715) 15109
71.6%
Uppercase Letter
ValueCountFrequency (%)
F 61
 
10.7%
O 56
 
9.8%
S 44
 
7.7%
B 41
 
7.2%
C 41
 
7.2%
N 31
 
5.4%
D 31
 
5.4%
T 29
 
5.1%
M 26
 
4.6%
E 26
 
4.6%
Other values (14) 183
32.2%
Lowercase Letter
ValueCountFrequency (%)
e 89
18.7%
o 66
13.9%
f 40
8.4%
n 36
 
7.6%
a 33
 
6.9%
s 27
 
5.7%
r 25
 
5.3%
c 24
 
5.1%
t 21
 
4.4%
d 17
 
3.6%
Other values (13) 97
20.4%
Decimal Number
ValueCountFrequency (%)
2 17
27.4%
1 12
19.4%
3 9
14.5%
5 7
11.3%
6 5
 
8.1%
4 4
 
6.5%
9 3
 
4.8%
7 3
 
4.8%
8 2
 
3.2%
Other Punctuation
ValueCountFrequency (%)
& 40
58.0%
. 20
29.0%
' 4
 
5.8%
, 3
 
4.3%
· 2
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 654
100.0%
Open Punctuation
ValueCountFrequency (%)
( 646
100.0%
Space Separator
ValueCountFrequency (%)
524
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21087
87.5%
Common 1959
 
8.1%
Latin 1044
 
4.3%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1314
 
6.2%
1124
 
5.3%
711
 
3.4%
508
 
2.4%
477
 
2.3%
444
 
2.1%
399
 
1.9%
373
 
1.8%
320
 
1.5%
317
 
1.5%
Other values (706) 15100
71.6%
Latin
ValueCountFrequency (%)
e 89
 
8.5%
o 66
 
6.3%
F 61
 
5.8%
O 56
 
5.4%
S 44
 
4.2%
B 41
 
3.9%
C 41
 
3.9%
f 40
 
3.8%
n 36
 
3.4%
a 33
 
3.2%
Other values (37) 537
51.4%
Common
ValueCountFrequency (%)
) 654
33.4%
( 646
33.0%
524
26.7%
& 40
 
2.0%
. 20
 
1.0%
2 17
 
0.9%
1 12
 
0.6%
3 9
 
0.5%
5 7
 
0.4%
6 5
 
0.3%
Other values (9) 25
 
1.3%
Han
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21087
87.5%
ASCII 3001
 
12.5%
CJK 9
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1314
 
6.2%
1124
 
5.3%
711
 
3.4%
508
 
2.4%
477
 
2.3%
444
 
2.1%
399
 
1.9%
373
 
1.8%
320
 
1.5%
317
 
1.5%
Other values (706) 15100
71.6%
ASCII
ValueCountFrequency (%)
) 654
21.8%
( 646
21.5%
524
17.5%
e 89
 
3.0%
o 66
 
2.2%
F 61
 
2.0%
O 56
 
1.9%
S 44
 
1.5%
B 41
 
1.4%
C 41
 
1.4%
Other values (55) 779
26.0%
None
ValueCountFrequency (%)
· 2
100.0%
CJK
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Distinct3626
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
Minimum2001-07-24 00:00:00
Maximum2024-03-29 09:46:01
2024-04-29T21:32:47.474922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:32:47.617218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
I
2712 
U
1323 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2712
67.2%
U 1323
32.8%

Length

2024-04-29T21:32:47.738674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:47.820503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2712
67.2%
u 1323
32.8%
Distinct972
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
Minimum2018-08-31 23:59:59
Maximum2024-03-31 00:15:17
2024-04-29T21:32:47.916952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:32:48.046783image/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 size31.7 KiB
식품제조가공업
2858 
기타 식품제조가공업
1147 
도시락제조업
 
30

Length

Max length10
Median length7
Mean length7.8453532
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2858
70.8%
기타 식품제조가공업 1147
28.4%
도시락제조업 30
 
0.7%

Length

2024-04-29T21:32:48.177382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:48.286164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 4005
77.3%
기타 1147
 
22.1%
도시락제조업 30
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3249
Distinct (%)85.1%
Missing217
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean341910.42
Minimum323038.14
Maximum368613.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:48.396582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum323038.14
5-th percentile331601.68
Q1338706.8
median341603.52
Q3345585.75
95-th percentile353150.04
Maximum368613.45
Range45575.311
Interquartile range (IQR)6878.9504

Descriptive statistics

Standard deviation5975.6893
Coefficient of variation (CV)0.017477354
Kurtosis0.18120467
Mean341910.42
Median Absolute Deviation (MAD)3404.1823
Skewness0.037349057
Sum1.305414 × 109
Variance35708862
MonotonicityNot monotonic
2024-04-29T21:32:48.521846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
339243.983122111 28
 
0.7%
336661.678721891 18
 
0.4%
334406.500395956 7
 
0.2%
348434.155717765 5
 
0.1%
346004.036082066 5
 
0.1%
343157.682044362 4
 
0.1%
335996.823890094 4
 
0.1%
332331.724410241 4
 
0.1%
338678.797272666 4
 
0.1%
343260.899952683 4
 
0.1%
Other values (3239) 3735
92.6%
(Missing) 217
 
5.4%
ValueCountFrequency (%)
323038.137301829 2
< 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 (%)
368613.448132383 1
< 0.1%
364191.914913724 1
< 0.1%
362025.095014495 1
< 0.1%
359649.30764586 1
< 0.1%
357670.391535579 1
< 0.1%
357642.615896972 1
< 0.1%
356965.555232748 1
< 0.1%
356696.976822927 1
< 0.1%
356437.392326278 1
< 0.1%
356410.892344199 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3249
Distinct (%)85.1%
Missing217
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean263980.18
Minimum236164.39
Maximum313355.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:48.644880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum236164.39
5-th percentile253672.7
Q1261115.83
median264066.38
Q3266668.9
95-th percentile272551.89
Maximum313355.9
Range77191.51
Interquartile range (IQR)5553.0698

Descriptive statistics

Standard deviation7184.0725
Coefficient of variation (CV)0.027214439
Kurtosis10.343715
Mean263980.18
Median Absolute Deviation (MAD)2763.0461
Skewness1.4752196
Sum1.0078763 × 109
Variance51610897
MonotonicityNot monotonic
2024-04-29T21:32:48.794826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
268026.454530584 28
 
0.7%
261224.266018286 18
 
0.4%
260208.389649832 7
 
0.2%
264017.165938686 5
 
0.1%
269131.730019622 5
 
0.1%
261957.795169076 4
 
0.1%
261375.426756584 4
 
0.1%
249198.891144425 4
 
0.1%
260540.364298043 4
 
0.1%
267937.999113354 4
 
0.1%
Other values (3239) 3735
92.6%
(Missing) 217
 
5.4%
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 2
< 0.1%
238893.362765047 1
< 0.1%
238893.829911915 1
< 0.1%
239059.112587617 1
< 0.1%
239098.142264127 1
< 0.1%
ValueCountFrequency (%)
313355.902312406 1
< 0.1%
311880.756310527 1
< 0.1%
310537.144981545 1
< 0.1%
308819.131349169 1
< 0.1%
308254.799686136 1
< 0.1%
308132.334323979 1
< 0.1%
308097.975321815 1
< 0.1%
306833.60464033 1
< 0.1%
306755.250398852 1
< 0.1%
305945.115363686 1
< 0.1%

위생업태명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
식품제조가공업
2858 
기타 식품제조가공업
1147 
도시락제조업
 
30

Length

Max length10
Median length7
Mean length7.8453532
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2858
70.8%
기타 식품제조가공업 1147
28.4%
도시락제조업 30
 
0.7%

Length

2024-04-29T21:32:48.928001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:49.030184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 4005
77.3%
기타 1147
 
22.1%
도시락제조업 30
 
0.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
<NA>
3109 
0
926 

Length

Max length4
Median length4
Mean length3.3115242
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3109
77.1%
0 926
 
22.9%

Length

2024-04-29T21:32:49.134958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:49.245508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3109
77.1%
0 926
 
22.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
<NA>
3109 
0
926 

Length

Max length4
Median length4
Mean length3.3115242
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3109
77.1%
0 926
 
22.9%

Length

2024-04-29T21:32:49.352826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:49.452141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3109
77.1%
0 926
 
22.9%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4035
Missing (%)100.0%
Memory size35.6 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4035
Missing (%)100.0%
Memory size35.6 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
상수도전용
2326 
<NA>
1660 
지하수전용
 
33
간이상수도
 
14
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length5
Mean length4.5945477
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2326
57.6%
<NA> 1660
41.1%
지하수전용 33
 
0.8%
간이상수도 14
 
0.3%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%

Length

2024-04-29T21:32:49.553866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:49.647834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2326
57.6%
na 1660
41.1%
지하수전용 33
 
0.8%
간이상수도 14
 
0.3%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%

총직원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
<NA>
3123 
0
912 

Length

Max length4
Median length4
Mean length3.3219331
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3123
77.4%
0 912
 
22.6%

Length

2024-04-29T21:32:49.757529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:49.865189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3123
77.4%
0 912
 
22.6%

본사직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.3%
Missing567
Missing (%)14.1%
Infinite0
Infinite (%)0.0%
Mean0.074394464
Minimum0
Maximum12
Zeros3324
Zeros (%)82.4%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:49.958494image/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 deviation0.48060336
Coefficient of variation (CV)6.4602033
Kurtosis189.59546
Mean0.074394464
Median Absolute Deviation (MAD)0
Skewness11.480218
Sum258
Variance0.23097959
MonotonicityNot monotonic
2024-04-29T21:32:50.056465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 3324
82.4%
1 96
 
2.4%
2 18
 
0.4%
3 17
 
0.4%
5 5
 
0.1%
4 4
 
0.1%
12 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
(Missing) 567
 
14.1%
ValueCountFrequency (%)
0 3324
82.4%
1 96
 
2.4%
2 18
 
0.4%
3 17
 
0.4%
4 4
 
0.1%
5 5
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 5
 
0.1%
4 4
 
0.1%
3 17
 
0.4%
2 18
 
0.4%
1 96
 
2.4%
0 3324
82.4%

공장사무직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct13
Distinct (%)0.4%
Missing554
Missing (%)13.7%
Infinite0
Infinite (%)0.0%
Mean0.20626257
Minimum0
Maximum40
Zeros3042
Zeros (%)75.4%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:50.163437image/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 deviation1.0085701
Coefficient of variation (CV)4.8897389
Kurtosis736.86664
Mean0.20626257
Median Absolute Deviation (MAD)0
Skewness21.495776
Sum718
Variance1.0172136
MonotonicityNot monotonic
2024-04-29T21:32:50.264617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 3042
75.4%
1 329
 
8.2%
2 63
 
1.6%
3 23
 
0.6%
4 9
 
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) 554
 
13.7%
ValueCountFrequency (%)
0 3042
75.4%
1 329
 
8.2%
2 63
 
1.6%
3 23
 
0.6%
4 9
 
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 9
 
0.2%
3 23
0.6%

공장판매직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.3%
Missing573
Missing (%)14.2%
Infinite0
Infinite (%)0.0%
Mean0.094742923
Minimum0
Maximum30
Zeros3245
Zeros (%)80.4%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:50.367319image/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 deviation0.6558968
Coefficient of variation (CV)6.9229107
Kurtosis1271.0397
Mean0.094742923
Median Absolute Deviation (MAD)0
Skewness29.714518
Sum328
Variance0.43020061
MonotonicityNot monotonic
2024-04-29T21:32:50.476785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3245
80.4%
1 166
 
4.1%
2 36
 
0.9%
3 7
 
0.2%
4 3
 
0.1%
5 2
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
30 1
 
< 0.1%
(Missing) 573
 
14.2%
ValueCountFrequency (%)
0 3245
80.4%
1 166
 
4.1%
2 36
 
0.9%
3 7
 
0.2%
4 3
 
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 3
 
0.1%
3 7
 
0.2%
2 36
 
0.9%
1 166
 
4.1%
0 3245
80.4%

공장생산직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct29
Distinct (%)0.8%
Missing489
Missing (%)12.1%
Infinite0
Infinite (%)0.0%
Mean0.82092499
Minimum0
Maximum220
Zeros2562
Zeros (%)63.5%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:50.605314image/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 deviation4.545873
Coefficient of variation (CV)5.5375011
Kurtosis1563.0258
Mean0.82092499
Median Absolute Deviation (MAD)0
Skewness34.471436
Sum2911
Variance20.664961
MonotonicityNot monotonic
2024-04-29T21:32:50.734607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 2562
63.5%
1 476
 
11.8%
2 218
 
5.4%
3 114
 
2.8%
4 54
 
1.3%
5 33
 
0.8%
7 18
 
0.4%
8 14
 
0.3%
6 14
 
0.3%
9 8
 
0.2%
Other values (19) 35
 
0.9%
(Missing) 489
 
12.1%
ValueCountFrequency (%)
0 2562
63.5%
1 476
 
11.8%
2 218
 
5.4%
3 114
 
2.8%
4 54
 
1.3%
5 33
 
0.8%
6 14
 
0.3%
7 18
 
0.4%
8 14
 
0.3%
9 8
 
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%
23 1
< 0.1%
22 1
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
<NA>
1960 
임대
1198 
자가
877 

Length

Max length4
Median length2
Mean length2.9714994
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1960
48.6%
임대 1198
29.7%
자가 877
21.7%

Length

2024-04-29T21:32:50.858263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:50.973762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1960
48.6%
임대 1198
29.7%
자가 877
21.7%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)1.7%
Missing2939
Missing (%)72.8%
Infinite0
Infinite (%)0.0%
Mean591196.9
Minimum0
Maximum50000000
Zeros1031
Zeros (%)25.6%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:51.078580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4550000
Maximum50000000
Range50000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3401630.7
Coefficient of variation (CV)5.7538034
Kurtosis112.44267
Mean591196.9
Median Absolute Deviation (MAD)0
Skewness9.5149314
Sum6.479518 × 108
Variance1.1571092 × 1013
MonotonicityNot monotonic
2024-04-29T21:32:51.184486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 1031
 
25.6%
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%
300 1
 
< 0.1%
18000000 1
 
< 0.1%
Other values (9) 9
 
0.2%
(Missing) 2939
72.8%
ValueCountFrequency (%)
0 1031
25.6%
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%
28050000 1
 
< 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%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)2.4%
Missing2940
Missing (%)72.9%
Infinite0
Infinite (%)0.0%
Mean32274.146
Minimum0
Maximum2200000
Zeros1030
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:51.292666image/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 deviation162962.25
Coefficient of variation (CV)5.0493126
Kurtosis71.469329
Mean32274.146
Median Absolute Deviation (MAD)0
Skewness7.4555949
Sum35340190
Variance2.6556696 × 1010
MonotonicityNot monotonic
2024-04-29T21:32:51.411878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 1030
 
25.5%
300000 13
 
0.3%
500000 11
 
0.3%
600000 5
 
0.1%
400000 5
 
0.1%
350000 3
 
0.1%
800000 3
 
0.1%
200000 3
 
0.1%
450000 2
 
< 0.1%
700000 2
 
< 0.1%
Other values (16) 18
 
0.4%
(Missing) 2940
72.9%
ValueCountFrequency (%)
0 1030
25.5%
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 size4.1 KiB
False
4033 
True
 
2
ValueCountFrequency (%)
False 4033
> 99.9%
True 2
 
< 0.1%
2024-04-29T21:32:51.757179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct630
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.30176
Minimum0
Maximum4673.38
Zeros3129
Zeros (%)77.5%
Negative0
Negative (%)0.0%
Memory size35.6 KiB
2024-04-29T21:32:51.858508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile51.451
Maximum4673.38
Range4673.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation122.50058
Coefficient of variation (CV)8.5654199
Kurtosis982.4365
Mean14.30176
Median Absolute Deviation (MAD)0
Skewness28.328748
Sum57707.6
Variance15006.391
MonotonicityNot monotonic
2024-04-29T21:32:51.975587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3129
77.5%
3.0 24
 
0.6%
6.0 18
 
0.4%
1.0 15
 
0.4%
4.0 13
 
0.3%
2.0 12
 
0.3%
3.3 10
 
0.2%
347.13 9
 
0.2%
4.5 9
 
0.2%
6.6 8
 
0.2%
Other values (620) 788
 
19.5%
ValueCountFrequency (%)
0.0 3129
77.5%
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%
943.03 1
< 0.1%
875.0 1
< 0.1%
832.2 1
< 0.1%
802.0 1
< 0.1%
792.9 1
< 0.1%
701.08 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4035
Missing (%)100.0%
Memory size35.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4035
Missing (%)100.0%
Memory size35.6 KiB

홈페이지
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
<NA>
4033 
4
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.998513
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> 4033
> 99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Length

2024-04-29T21:32:52.093714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:32:52.190055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4033
> 99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품제조가공업07_22_11_P34100003410000-106-2018-000032018-03-28<NA>3폐업2폐업2023-02-13<NA><NA><NA><NA>12.52700-413대구광역시 중구 삼덕동3가 306-3대구광역시 중구 달구벌대로443길 26-11, 1층 (삼덕동3가)41948다사랑보호작업장2023-02-13 13:06:00U2023-02-15 02:40:00기타 식품제조가공업344982.217751263835.91565기타 식품제조가공업00<NA><NA>상수도전용00101<NA>00N0.0<NA><NA><NA>
12식품제조가공업07_22_11_P34100003410000-106-2018-000052018-04-12<NA>3폐업2폐업2021-08-05<NA><NA><NA><NA>59.5700-421대구광역시 중구 동인동1가 0294-0004 지상 1층대구광역시 중구 동덕로 184-1, 지상 1층 (동인동1가)41908오프더스트릿(off the street)2021-08-05 14:03:07U2021-08-07 02:40:00기타 식품제조가공업344846.881977264618.504405기타 식품제조가공업00<NA><NA>상수도전용00000<NA>00N0.0<NA><NA><NA>
23식품제조가공업07_22_11_P34100003410000-106-2018-000062018-04-23<NA>3폐업2폐업2019-01-28<NA><NA><NA><NA>7.0700-822대구광역시 중구 봉산동 24-9번지대구광역시 중구 동성로3길 9-5 (봉산동)41942문현사커피로스터스2019-01-28 11:22:44U2019-01-30 02:40:00기타 식품제조가공업344151.460242264040.947304기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
34식품제조가공업07_22_11_P34100003410000-106-2018-000072018-04-25<NA>3폐업2폐업2020-03-23<NA><NA><NA>053 257 772354.0700-093대구광역시 중구 동성로3가 0120-0002번지대구광역시 중구 동성로1길 29-23 (동성로3가)41942이박사마카롱디저트LBG2020-03-23 10:47:51U2020-03-25 02:40:00기타 식품제조가공업343997.625632264200.22888기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
45식품제조가공업07_22_11_P34100003410000-106-2001-000082001-12-06<NA>3폐업2폐업2006-12-11<NA><NA><NA>053 256822276.74700-300대구광역시 중구 인교동 0267-0001번지<NA><NA>북성로찐빵2003-12-15 00:00:00I2018-08-31 23:59:59식품제조가공업343146.586512264617.95844식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0105임대<NA><NA>N0.0<NA><NA><NA>
56식품제조가공업07_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>
67식품제조가공업07_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>
78식품제조가공업07_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>
89식품제조가공업07_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>
910식품제조가공업07_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>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
40254026식품제조가공업07_22_11_P51410005141000-106-2013-000032013-11-26<NA>3폐업2폐업2016-12-28<NA><NA><NA><NA>498.72<NA>대구광역시 군위군 효령면 고곡리 845대구광역시 군위군 효령면 용매로 1012-343137동해촌된장2016-06-09 17:34:37I2023-07-01 16:42:10식품제조가공업342289.713345290068.356532식품제조가공업00<NA><NA>상수도전용00000자가00N5.6<NA><NA><NA>
40264027식품제조가공업07_22_11_P51410005141000-106-2013-000042013-11-28<NA>3폐업2폐업2021-04-12<NA><NA><NA>054 382 35551193.38<NA>대구광역시 군위군 군위읍 정리 490-1대구광역시 군위군 군위읍 군청로 33243110(주)미본2021-04-12 17:12:49I2023-07-01 16:42:10식품제조가공업340964.246356306755.250399식품제조가공업00<NA><NA>상수도전용00000<NA>00N304.61<NA><NA><NA>
40274028식품제조가공업07_22_11_P51410005141000-106-2013-000052013-12-19<NA>3폐업2폐업2020-10-30<NA><NA><NA>054 382 7337334.9<NA>대구광역시 군위군 의흥면 원산리 517대구광역시 군위군 의흥면 원산금양길 219-943151리팜F&B2020-10-30 14:48:09I2023-07-01 16:42:10식품제조가공업356123.86661297012.149117식품제조가공업00<NA><NA>간이상수도00000자가00N21.26<NA><NA><NA>
40284029식품제조가공업07_22_11_P51410005141000-106-2017-000012017-12-18<NA>3폐업2폐업2023-04-03<NA><NA><NA>070 77550011156.0<NA>대구광역시 군위군 효령면 거매리 487-9대구광역시 군위군 효령면 효령공단길 12-943130(주)예몽2023-04-03 11:51:56I2023-07-01 16:42:10기타 식품제조가공업343215.414683295758.236465기타 식품제조가공업00<NA><NA>상수도전용00000임대00N0.0<NA><NA><NA>
40294030식품제조가공업07_22_11_P51410005141000-106-2005-000042005-05-17<NA>3폐업2폐업2017-07-13<NA><NA><NA>054 3820045472.0<NA>대구광역시 군위군 부계면 대율리 429-2대구광역시 군위군 부계면 한티로 2206-3743165참농부식품2017-07-13 11:15:35I2023-07-01 16:42:10식품제조가공업349395.920291285933.63265식품제조가공업00<NA><NA>지하수전용00102자가00N0.0<NA><NA><NA>
40304031식품제조가공업07_22_11_P51410005141000-106-2005-000052005-06-15<NA>3폐업2폐업2008-02-18<NA><NA><NA>054 382379279.5<NA>대구광역시 군위군 효령면 병수리 792-2<NA><NA>청정장2008-01-11 15:42:33I2023-07-01 16:42:10식품제조가공업342519.724316298229.310864식품제조가공업00<NA><NA>상수도전용00000자가00N0.0<NA><NA><NA>
40314032식품제조가공업07_22_11_P51410005141000-106-2005-000062005-06-24<NA>3폐업2폐업2008-03-21<NA><NA><NA>054 383191048.0<NA>대구광역시 군위군 효령면 금매리 716<NA><NA>선조식품2008-01-11 14:37:51I2023-07-01 16:42:10식품제조가공업345355.75736293826.163938식품제조가공업00<NA><NA>지하수전용00002자가00N0.0<NA><NA><NA>
40324033식품제조가공업07_22_11_P51410005141000-106-2006-000012006-01-11<NA>3폐업2폐업2019-08-01<NA><NA><NA>054 3831223784.23<NA>대구광역시 군위군 군위읍 수서리 421-10대구광역시 군위군 군위읍 군위공단길 198-843123(주)흥안바이오텍2019-08-01 14:44:38I2023-07-01 16:42:10식품제조가공업340012.620941302283.496294식품제조가공업00<NA><NA>상수도전용00003<NA>00N0.0<NA><NA><NA>
40334034식품제조가공업07_22_11_P51410005141000-106-2006-000042006-09-11<NA>3폐업2폐업2013-02-22<NA><NA><NA>054 3830395121.44<NA>대구광역시 군위군 삼국유사면 학암리 575대구광역시 군위군 삼국유사면 학암2길 52-143153학암농원2010-06-30 10:07:44I2023-07-01 16:42:10식품제조가공업368613.448132297351.621703식품제조가공업00<NA><NA>지하수전용00002자가00N0.0<NA><NA><NA>
40344035식품제조가공업07_22_11_P51410005141000-106-2006-000052006-11-29<NA>3폐업2폐업2023-12-07<NA><NA><NA>054 383012312.16<NA>대구광역시 군위군 의흥면 지호리 807대구광역시 군위군 의흥면 지호4길 743152高家食品2023-12-07 09:52:59U2023-12-09 02:40:00식품제조가공업359649.307646298037.593847식품제조가공업00<NA><NA>간이상수도00000자가00N0.0<NA><NA><NA>