Overview

Dataset statistics

Number of variables47
Number of observations3799
Missing cells44529
Missing cells (%)24.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory406.0 B

Variable types

Numeric16
Categorical15
Text6
Unsupported8
DateTime1
Boolean1

Dataset

Description22년09월_6270000_대구광역시_07_22_11_P_식품제조가공업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000096630&dataSetDetailId=DDI_0000096641&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
급수시설구분명 is highly imbalanced (55.9%)Imbalance
다중이용업소여부 is highly imbalanced (99.4%)Imbalance
홈페이지 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3799 (100.0%) missing valuesMissing
폐업일자 has 1038 (27.3%) missing valuesMissing
휴업시작일자 has 3799 (100.0%) missing valuesMissing
휴업종료일자 has 3799 (100.0%) missing valuesMissing
재개업일자 has 3799 (100.0%) missing valuesMissing
소재지전화 has 1070 (28.2%) missing valuesMissing
소재지면적 has 136 (3.6%) missing valuesMissing
소재지우편번호 has 82 (2.2%) missing valuesMissing
도로명전체주소 has 1370 (36.1%) missing valuesMissing
도로명우편번호 has 1398 (36.8%) missing valuesMissing
좌표정보(X) has 171 (4.5%) missing valuesMissing
좌표정보(Y) has 171 (4.5%) missing valuesMissing
영업장주변구분명 has 3799 (100.0%) missing valuesMissing
등급구분명 has 3799 (100.0%) missing valuesMissing
본사직원수 has 621 (16.3%) missing valuesMissing
공장사무직직원수 has 610 (16.1%) missing valuesMissing
공장판매직직원수 has 630 (16.6%) missing valuesMissing
공장생산직직원수 has 539 (14.2%) missing valuesMissing
보증액 has 3137 (82.6%) missing valuesMissing
월세액 has 3138 (82.6%) missing valuesMissing
전통업소지정번호 has 3799 (100.0%) missing valuesMissing
전통업소주된음식 has 3799 (100.0%) missing valuesMissing
공장사무직직원수 is highly skewed (γ1 = 22.27490108)Skewed
공장판매직직원수 is highly skewed (γ1 = 28.86313923)Skewed
공장생산직직원수 is highly skewed (γ1 = 34.77675308)Skewed
시설총규모 is highly skewed (γ1 = 30.04278904)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 3053 (80.4%) zerosZeros
공장사무직직원수 has 2786 (73.3%) zerosZeros
공장판매직직원수 has 2953 (77.7%) zerosZeros
공장생산직직원수 has 2334 (61.4%) zerosZeros
보증액 has 598 (15.7%) zerosZeros
월세액 has 597 (15.7%) zerosZeros
시설총규모 has 3007 (79.2%) zerosZeros

Reproduction

Analysis started2023-12-10 20:25:33.933893
Analysis finished2023-12-10 20:25:36.473200
Duration2.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3799
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1900
Minimum1
Maximum3799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:36.607091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile190.9
Q1950.5
median1900
Q32849.5
95-th percentile3609.1
Maximum3799
Range3798
Interquartile range (IQR)1899

Descriptive statistics

Standard deviation1096.8212
Coefficient of variation (CV)0.5772743
Kurtosis-1.2
Mean1900
Median Absolute Deviation (MAD)950
Skewness0
Sum7218100
Variance1203016.7
MonotonicityStrictly increasing
2023-12-11T05:25:36.856462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2539 1
 
< 0.1%
2527 1
 
< 0.1%
2528 1
 
< 0.1%
2529 1
 
< 0.1%
2530 1
 
< 0.1%
2531 1
 
< 0.1%
2532 1
 
< 0.1%
2533 1
 
< 0.1%
2534 1
 
< 0.1%
Other values (3789) 3789
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 (%)
3799 1
< 0.1%
3798 1
< 0.1%
3797 1
< 0.1%
3796 1
< 0.1%
3795 1
< 0.1%
3794 1
< 0.1%
3793 1
< 0.1%
3792 1
< 0.1%
3791 1
< 0.1%
3790 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
식품제조가공업
3799 

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 3799
100.0%

Length

2023-12-11T05:25:37.087975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:37.239950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3799
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
07_22_11_P
3799 

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 3799
100.0%

Length

2023-12-11T05:25:37.378326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:37.520642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_11_p 3799
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3449857.9
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:37.653518image/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 deviation20888.147
Coefficient of variation (CV)0.006054785
Kurtosis-0.95538123
Mean3449857.9
Median Absolute Deviation (MAD)20000
Skewness-0.3002469
Sum1.310601 × 1010
Variance4.363147 × 108
MonotonicityIncreasing
2023-12-11T05:25:37.854596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 959
25.2%
3470000 650
17.1%
3480000 472
12.4%
3420000 442
11.6%
3460000 437
11.5%
3430000 370
 
9.7%
3440000 245
 
6.4%
3410000 224
 
5.9%
ValueCountFrequency (%)
3410000 224
 
5.9%
3420000 442
11.6%
3430000 370
 
9.7%
3440000 245
 
6.4%
3450000 959
25.2%
3460000 437
11.5%
3470000 650
17.1%
3480000 472
12.4%
ValueCountFrequency (%)
3480000 472
12.4%
3470000 650
17.1%
3460000 437
11.5%
3450000 959
25.2%
3440000 245
 
6.4%
3430000 370
 
9.7%
3420000 442
11.6%
3410000 224
 
5.9%

관리번호
Text

UNIQUE 

Distinct3799
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
2023-12-11T05:25:38.398537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters83578
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

Unique3799 ?
Unique (%)100.0%

Sample

1st row3410000-106-2004-00001
2nd row3410000-106-2004-00002
3rd row3410000-106-2004-00003
4th row3410000-106-2004-00004
5th row3410000-106-2004-00005
ValueCountFrequency (%)
3410000-106-2004-00001 1
 
< 0.1%
3460000-106-2010-00003 1
 
< 0.1%
3460000-106-2010-00006 1
 
< 0.1%
3460000-106-2010-00010 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%
3460000-106-2011-00003 1
 
< 0.1%
Other values (3789) 3789
99.7%
2023-12-11T05:25:39.155210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38088
45.6%
- 11397
 
13.6%
1 8002
 
9.6%
2 5670
 
6.8%
3 5163
 
6.2%
6 4979
 
6.0%
4 4873
 
5.8%
5 1711
 
2.0%
7 1368
 
1.6%
9 1177
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72181
86.4%
Dash Punctuation 11397
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38088
52.8%
1 8002
 
11.1%
2 5670
 
7.9%
3 5163
 
7.2%
6 4979
 
6.9%
4 4873
 
6.8%
5 1711
 
2.4%
7 1368
 
1.9%
9 1177
 
1.6%
8 1150
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 11397
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83578
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38088
45.6%
- 11397
 
13.6%
1 8002
 
9.6%
2 5670
 
6.8%
3 5163
 
6.2%
6 4979
 
6.0%
4 4873
 
5.8%
5 1711
 
2.0%
7 1368
 
1.6%
9 1177
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83578
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38088
45.6%
- 11397
 
13.6%
1 8002
 
9.6%
2 5670
 
6.8%
3 5163
 
6.2%
6 4979
 
6.0%
4 4873
 
5.8%
5 1711
 
2.0%
7 1368
 
1.6%
9 1177
 
1.4%

인허가일자
Real number (ℝ)

Distinct2695
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20089943
Minimum19681218
Maximum20220929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:39.393718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19681218
5-th percentile19980404
Q120031109
median20091116
Q320150414
95-th percentile20201114
Maximum20220929
Range539711
Interquartile range (IQR)119305.5

Descriptive statistics

Standard deviation75494.416
Coefficient of variation (CV)0.0037578213
Kurtosis1.3584671
Mean20089943
Median Absolute Deviation (MAD)59590
Skewness-0.60889057
Sum7.6321694 × 1010
Variance5.6994068 × 109
MonotonicityNot monotonic
2023-12-11T05:25:39.630486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000302 28
 
0.7%
19960320 19
 
0.5%
19960516 7
 
0.2%
19930320 6
 
0.2%
20110520 6
 
0.2%
20180706 5
 
0.1%
20160523 5
 
0.1%
20071108 5
 
0.1%
20130725 5
 
0.1%
20110705 4
 
0.1%
Other values (2685) 3709
97.6%
ValueCountFrequency (%)
19681218 1
< 0.1%
19700224 1
< 0.1%
19710528 1
< 0.1%
19720522 1
< 0.1%
19720817 1
< 0.1%
19730502 1
< 0.1%
19740326 1
< 0.1%
19740803 1
< 0.1%
19741016 1
< 0.1%
19741220 1
< 0.1%
ValueCountFrequency (%)
20220929 1
 
< 0.1%
20220920 1
 
< 0.1%
20220916 1
 
< 0.1%
20220914 1
 
< 0.1%
20220907 1
 
< 0.1%
20220905 2
0.1%
20220902 4
0.1%
20220825 1
 
< 0.1%
20220822 1
 
< 0.1%
20220811 2
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3799
Missing (%)100.0%
Memory size33.5 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
3
2761 
1
1038 

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 2761
72.7%
1 1038
 
27.3%

Length

2023-12-11T05:25:39.798935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:39.930341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2761
72.7%
1 1038
 
27.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
폐업
2761 
영업/정상
1038 

Length

Max length5
Median length2
Mean length2.8196894
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2761
72.7%
영업/정상 1038
 
27.3%

Length

2023-12-11T05:25:40.096217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:40.250892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2761
72.7%
영업/정상 1038
 
27.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
2
2761 
1
1038 

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 2761
72.7%
1 1038
 
27.3%

Length

2023-12-11T05:25:40.400421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:40.540066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2761
72.7%
1 1038
 
27.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
폐업
2761 
영업
1038 

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 2761
72.7%
영업 1038
 
27.3%

Length

2023-12-11T05:25:40.694212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:40.847668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2761
72.7%
영업 1038
 
27.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct2050
Distinct (%)74.2%
Missing1038
Missing (%)27.3%
Infinite0
Infinite (%)0.0%
Mean20117934
Minimum20000424
Maximum20220930
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:41.034521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000424
5-th percentile20030307
Q120070105
median20120430
Q320170330
95-th percentile20210621
Maximum20220930
Range220506
Interquartile range (IQR)100225

Descriptive statistics

Standard deviation58805.892
Coefficient of variation (CV)0.0029230582
Kurtosis-1.1852675
Mean20117934
Median Absolute Deviation (MAD)50121
Skewness-0.012251828
Sum5.5545616 × 1010
Variance3.4581329 × 109
MonotonicityNot monotonic
2023-12-11T05:25:41.193961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20101231 6
 
0.2%
20181226 6
 
0.2%
20030711 5
 
0.1%
20181127 5
 
0.1%
20190509 4
 
0.1%
20050408 4
 
0.1%
20180223 4
 
0.1%
20111230 4
 
0.1%
20220103 4
 
0.1%
20040603 4
 
0.1%
Other values (2040) 2715
71.5%
(Missing) 1038
 
27.3%
ValueCountFrequency (%)
20000424 1
< 0.1%
20000512 1
< 0.1%
20000621 1
< 0.1%
20000905 1
< 0.1%
20000928 2
0.1%
20001106 1
< 0.1%
20001121 1
< 0.1%
20001217 1
< 0.1%
20010129 1
< 0.1%
20010212 1
< 0.1%
ValueCountFrequency (%)
20220930 1
< 0.1%
20220928 1
< 0.1%
20220923 1
< 0.1%
20220920 1
< 0.1%
20220914 1
< 0.1%
20220913 1
< 0.1%
20220908 1
< 0.1%
20220822 1
< 0.1%
20220818 1
< 0.1%
20220817 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3799
Missing (%)100.0%
Memory size33.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3799
Missing (%)100.0%
Memory size33.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3799
Missing (%)100.0%
Memory size33.5 KiB

소재지전화
Text

MISSING 

Distinct2529
Distinct (%)92.7%
Missing1070
Missing (%)28.2%
Memory size29.8 KiB
2023-12-11T05:25:41.687879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.848296
Min length3

Characters and Unicode

Total characters29605
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

Unique2340 ?
Unique (%)85.7%

Sample

1st row053 4244979
2nd row053 2564337
3rd row053 4240540
4th row053 4223318
5th row053 4294238
ValueCountFrequency (%)
053 2007
34.8%
070 69
 
1.2%
311 21
 
0.4%
313 15
 
0.3%
314 13
 
0.2%
983 13
 
0.2%
621 13
 
0.2%
611 12
 
0.2%
767 12
 
0.2%
615 11
 
0.2%
Other values (2685) 3573
62.0%
2023-12-11T05:25:42.429767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4890
16.5%
3 4326
14.6%
0 4236
14.3%
3110
10.5%
2 2119
7.2%
6 2090
7.1%
1 2051
6.9%
7 1881
 
6.4%
8 1780
 
6.0%
4 1635
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26495
89.5%
Space Separator 3110
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4890
18.5%
3 4326
16.3%
0 4236
16.0%
2 2119
8.0%
6 2090
7.9%
1 2051
7.7%
7 1881
 
7.1%
8 1780
 
6.7%
4 1635
 
6.2%
9 1487
 
5.6%
Space Separator
ValueCountFrequency (%)
3110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29605
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4890
16.5%
3 4326
14.6%
0 4236
14.3%
3110
10.5%
2 2119
7.2%
6 2090
7.1%
1 2051
6.9%
7 1881
 
6.4%
8 1780
 
6.0%
4 1635
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29605
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4890
16.5%
3 4326
14.6%
0 4236
14.3%
3110
10.5%
2 2119
7.2%
6 2090
7.1%
1 2051
6.9%
7 1881
 
6.4%
8 1780
 
6.0%
4 1635
 
5.5%

소재지면적
Text

MISSING 

Distinct2646
Distinct (%)72.2%
Missing136
Missing (%)3.6%
Memory size29.8 KiB
2023-12-11T05:25:43.037491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.3775594
Min length3

Characters and Unicode

Total characters19698
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2161 ?
Unique (%)59.0%

Sample

1st row74.55
2nd row14.70
3rd row41.85
4th row120.60
5th row34.52
ValueCountFrequency (%)
66.00 30
 
0.8%
33.00 25
 
0.7%
20.00 25
 
0.7%
40.00 17
 
0.5%
00 17
 
0.5%
30.00 15
 
0.4%
26.40 13
 
0.4%
38.00 12
 
0.3%
132.00 12
 
0.3%
15.00 12
 
0.3%
Other values (2636) 3485
95.1%
2023-12-11T05:25:43.927554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3663
18.6%
0 3408
17.3%
1 1805
9.2%
2 1746
8.9%
3 1449
 
7.4%
4 1447
 
7.3%
5 1385
 
7.0%
6 1360
 
6.9%
8 1185
 
6.0%
7 1117
 
5.7%
Other values (2) 1133
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15961
81.0%
Other Punctuation 3737
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3408
21.4%
1 1805
11.3%
2 1746
10.9%
3 1449
9.1%
4 1447
9.1%
5 1385
8.7%
6 1360
 
8.5%
8 1185
 
7.4%
7 1117
 
7.0%
9 1059
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 3663
98.0%
, 74
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19698
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3663
18.6%
0 3408
17.3%
1 1805
9.2%
2 1746
8.9%
3 1449
 
7.4%
4 1447
 
7.3%
5 1385
 
7.0%
6 1360
 
6.9%
8 1185
 
6.0%
7 1117
 
5.7%
Other values (2) 1133
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19698
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3663
18.6%
0 3408
17.3%
1 1805
9.2%
2 1746
8.9%
3 1449
 
7.4%
4 1447
 
7.3%
5 1385
 
7.0%
6 1360
 
6.9%
8 1185
 
6.0%
7 1117
 
5.7%
Other values (2) 1133
 
5.8%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct551
Distinct (%)14.8%
Missing82
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean704583.08
Minimum700010
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:44.180061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700836.8
Q1702805
median703833
Q3705823
95-th percentile711850
Maximum711893
Range11883
Interquartile range (IQR)3018

Descriptive statistics

Standard deviation3082.75
Coefficient of variation (CV)0.0043752824
Kurtosis0.77485913
Mean704583.08
Median Absolute Deviation (MAD)1772
Skewness1.1830516
Sum2.6189353 × 109
Variance9503347.4
MonotonicityNot monotonic
2023-12-11T05:25:44.409686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 90
 
2.4%
702061 81
 
2.1%
703830 57
 
1.5%
703833 48
 
1.3%
702816 46
 
1.2%
704080 43
 
1.1%
702903 36
 
0.9%
704900 36
 
0.9%
711851 34
 
0.9%
701140 34
 
0.9%
Other values (541) 3212
84.5%
(Missing) 82
 
2.2%
ValueCountFrequency (%)
700010 2
 
0.1%
700020 1
 
< 0.1%
700030 1
 
< 0.1%
700040 1
 
< 0.1%
700050 3
0.1%
700060 1
 
< 0.1%
700070 1
 
< 0.1%
700082 3
0.1%
700091 1
 
< 0.1%
700092 6
0.2%
ValueCountFrequency (%)
711893 8
 
0.2%
711892 9
0.2%
711891 9
0.2%
711874 3
 
0.1%
711871 9
0.2%
711864 12
0.3%
711863 21
0.6%
711862 3
 
0.1%
711861 2
 
0.1%
711858 11
0.3%

소재지전체주소
Text

Distinct3529
Distinct (%)93.5%
Missing26
Missing (%)0.7%
Memory size29.8 KiB
2023-12-11T05:25:44.926826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length49
Mean length23.833289
Min length15

Characters and Unicode

Total characters89923
Distinct characters299
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

Unique3320 ?
Unique (%)88.0%

Sample

1st row대구광역시 중구 대봉동 0040-0033번지
2nd row대구광역시 중구 태평로1가 0001-0186번지
3rd row대구광역시 중구 남산동 2466-0001번지 보성황실아파트 116동 105호
4th row대구광역시 중구 봉산동 0165-0007번지
5th row대구광역시 중구 동인동3가 0302-0002번지
ValueCountFrequency (%)
대구광역시 3773
22.3%
북구 952
 
5.6%
달서구 647
 
3.8%
달성군 468
 
2.8%
동구 442
 
2.6%
수성구 425
 
2.5%
서구 371
 
2.2%
남구 245
 
1.4%
중구 224
 
1.3%
지상1층 201
 
1.2%
Other values (3922) 9183
54.2%
2023-12-11T05:25:45.711257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16893
18.8%
구 7182
 
8.0%
1 4463
 
5.0%
대 4107
 
4.6%
동 4021
 
4.5%
시 3828
 
4.3%
광 3778
 
4.2%
역 3778
 
4.2%
지 3495
 
3.9%
- 3148
 
3.5%
Other values (289) 35230
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50206
55.8%
Decimal Number 18725
 
20.8%
Space Separator 16893
 
18.8%
Dash Punctuation 3148
 
3.5%
Close Punctuation 346
 
0.4%
Open Punctuation 346
 
0.4%
Other Punctuation 126
 
0.1%
Uppercase Letter 117
 
0.1%
Math Symbol 13
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 7182
14.3%
대 4107
 
8.2%
동 4021
 
8.0%
시 3828
 
7.6%
광 3778
 
7.5%
역 3778
 
7.5%
지 3495
 
7.0%
번 2979
 
5.9%
성 1194
 
2.4%
달 1183
 
2.4%
Other values (260) 14661
29.2%
Decimal Number
ValueCountFrequency (%)
1 4463
23.8%
2 2347
12.5%
0 2057
11.0%
3 1936
10.3%
4 1567
 
8.4%
5 1452
 
7.8%
6 1361
 
7.3%
7 1264
 
6.8%
8 1163
 
6.2%
9 1115
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
B 52
44.4%
A 49
41.9%
C 8
 
6.8%
E 2
 
1.7%
T 2
 
1.7%
D 2
 
1.7%
J 1
 
0.9%
P 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 (%)
16893
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3148
100.0%
Close Punctuation
ValueCountFrequency (%)
) 346
100.0%
Open Punctuation
ValueCountFrequency (%)
( 346
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50206
55.8%
Common 39597
44.0%
Latin 120
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 7182
14.3%
대 4107
 
8.2%
동 4021
 
8.0%
시 3828
 
7.6%
광 3778
 
7.5%
역 3778
 
7.5%
지 3495
 
7.0%
번 2979
 
5.9%
성 1194
 
2.4%
달 1183
 
2.4%
Other values (260) 14661
29.2%
Common
ValueCountFrequency (%)
16893
42.7%
1 4463
 
11.3%
- 3148
 
8.0%
2 2347
 
5.9%
0 2057
 
5.2%
3 1936
 
4.9%
4 1567
 
4.0%
5 1452
 
3.7%
6 1361
 
3.4%
7 1264
 
3.2%
Other values (9) 3109
 
7.9%
Latin
ValueCountFrequency (%)
B 52
43.3%
A 49
40.8%
C 8
 
6.7%
E 2
 
1.7%
e 2
 
1.7%
T 2
 
1.7%
D 2
 
1.7%
J 1
 
0.8%
P 1
 
0.8%
c 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50206
55.8%
ASCII 39717
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16893
42.5%
1 4463
 
11.2%
- 3148
 
7.9%
2 2347
 
5.9%
0 2057
 
5.2%
3 1936
 
4.9%
4 1567
 
3.9%
5 1452
 
3.7%
6 1361
 
3.4%
7 1264
 
3.2%
Other values (19) 3229
 
8.1%
Hangul
ValueCountFrequency (%)
구 7182
14.3%
대 4107
 
8.2%
동 4021
 
8.0%
시 3828
 
7.6%
광 3778
 
7.5%
역 3778
 
7.5%
지 3495
 
7.0%
번 2979
 
5.9%
성 1194
 
2.4%
달 1183
 
2.4%
Other values (260) 14661
29.2%

도로명전체주소
Text

MISSING 

Distinct2319
Distinct (%)95.5%
Missing1370
Missing (%)36.1%
Memory size29.8 KiB
2023-12-11T05:25:46.279429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length54
Mean length27.828736
Min length20

Characters and Unicode

Total characters67596
Distinct characters323
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

Unique2220 ?
Unique (%)91.4%

Sample

1st row대구광역시 중구 남산로13길 17, 1층 (남산동, 보성황실아파트 116동 105호)
2nd row대구광역시 중구 동덕로30길 139-24, 1층 (동인동4가)
3rd row대구광역시 중구 서성로14길 85 (대안동, 지상2층)
4th row대구광역시 중구 남산로 23-15, 1층 (남산동)
5th row대구광역시 중구 달성공원로6길 8, 지상 1층 (대신동)
ValueCountFrequency (%)
대구광역시 2429
 
17.8%
북구 622
 
4.6%
1층 577
 
4.2%
달서구 357
 
2.6%
달성군 314
 
2.3%
동구 301
 
2.2%
수성구 285
 
2.1%
서구 236
 
1.7%
남구 162
 
1.2%
중구 153
 
1.1%
Other values (2647) 8174
60.1%
2023-12-11T05:25:47.097373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11182
 
16.5%
구 4777
 
7.1%
1 3040
 
4.5%
동 2938
 
4.3%
대 2937
 
4.3%
시 2531
 
3.7%
역 2449
 
3.6%
광 2430
 
3.6%
) 2235
 
3.3%
( 2235
 
3.3%
Other values (313) 30842
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38678
57.2%
Space Separator 11182
 
16.5%
Decimal Number 10980
 
16.2%
Close Punctuation 2235
 
3.3%
Open Punctuation 2235
 
3.3%
Other Punctuation 1345
 
2.0%
Dash Punctuation 768
 
1.1%
Uppercase Letter 145
 
0.2%
Math Symbol 26
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 4777
 
12.4%
동 2938
 
7.6%
대 2937
 
7.6%
시 2531
 
6.5%
역 2449
 
6.3%
광 2430
 
6.3%
로 2224
 
5.8%
길 1693
 
4.4%
성 1033
 
2.7%
층 1021
 
2.6%
Other values (281) 14645
37.9%
Uppercase Letter
ValueCountFrequency (%)
B 61
42.1%
A 54
37.2%
C 12
 
8.3%
T 4
 
2.8%
D 3
 
2.1%
E 3
 
2.1%
P 2
 
1.4%
J 2
 
1.4%
G 1
 
0.7%
M 1
 
0.7%
Other values (2) 2
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 3040
27.7%
2 1638
14.9%
3 1283
11.7%
4 924
 
8.4%
5 872
 
7.9%
6 780
 
7.1%
0 702
 
6.4%
7 680
 
6.2%
8 577
 
5.3%
9 484
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 1337
99.4%
· 4
 
0.3%
. 4
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
11182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2235
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2235
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 768
100.0%
Math Symbol
ValueCountFrequency (%)
~ 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38678
57.2%
Common 28771
42.6%
Latin 147
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 4777
 
12.4%
동 2938
 
7.6%
대 2937
 
7.6%
시 2531
 
6.5%
역 2449
 
6.3%
광 2430
 
6.3%
로 2224
 
5.8%
길 1693
 
4.4%
성 1033
 
2.7%
층 1021
 
2.6%
Other values (281) 14645
37.9%
Common
ValueCountFrequency (%)
11182
38.9%
1 3040
 
10.6%
) 2235
 
7.8%
( 2235
 
7.8%
2 1638
 
5.7%
, 1337
 
4.6%
3 1283
 
4.5%
4 924
 
3.2%
5 872
 
3.0%
6 780
 
2.7%
Other values (8) 3245
 
11.3%
Latin
ValueCountFrequency (%)
B 61
41.5%
A 54
36.7%
C 12
 
8.2%
T 4
 
2.7%
D 3
 
2.0%
E 3
 
2.0%
P 2
 
1.4%
J 2
 
1.4%
G 1
 
0.7%
e 1
 
0.7%
Other values (4) 4
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38678
57.2%
ASCII 28914
42.8%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11182
38.7%
1 3040
 
10.5%
) 2235
 
7.7%
( 2235
 
7.7%
2 1638
 
5.7%
, 1337
 
4.6%
3 1283
 
4.4%
4 924
 
3.2%
5 872
 
3.0%
6 780
 
2.7%
Other values (21) 3388
 
11.7%
Hangul
ValueCountFrequency (%)
구 4777
 
12.4%
동 2938
 
7.6%
대 2937
 
7.6%
시 2531
 
6.5%
역 2449
 
6.3%
광 2430
 
6.3%
로 2224
 
5.8%
길 1693
 
4.4%
성 1033
 
2.7%
층 1021
 
2.6%
Other values (281) 14645
37.9%
None
ValueCountFrequency (%)
· 4
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct819
Distinct (%)34.1%
Missing1398
Missing (%)36.8%
Infinite0
Infinite (%)0.0%
Mean42014.039
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:47.360661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41109
Q141489
median41933
Q342662
95-th percentile42972
Maximum43024
Range2024
Interquartile range (IQR)1173

Descriptive statistics

Standard deviation616.05083
Coefficient of variation (CV)0.014662976
Kurtosis-1.2969137
Mean42014.039
Median Absolute Deviation (MAD)491
Skewness0.16916864
Sum1.0087571 × 108
Variance379518.63
MonotonicityNot monotonic
2023-12-11T05:25:47.601707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41485 45
 
1.2%
41582 41
 
1.1%
41490 37
 
1.0%
41557 25
 
0.7%
41488 23
 
0.6%
41755 19
 
0.5%
42975 18
 
0.5%
42970 18
 
0.5%
42703 18
 
0.5%
41123 16
 
0.4%
Other values (809) 2141
56.4%
(Missing) 1398
36.8%
ValueCountFrequency (%)
41000 8
0.2%
41001 3
 
0.1%
41002 4
0.1%
41005 1
 
< 0.1%
41007 4
0.1%
41008 2
 
0.1%
41009 4
0.1%
41015 1
 
< 0.1%
41016 1
 
< 0.1%
41017 1
 
< 0.1%
ValueCountFrequency (%)
43024 1
 
< 0.1%
43023 5
0.1%
43022 1
 
< 0.1%
43013 2
 
0.1%
43012 1
 
< 0.1%
43011 6
0.2%
43009 1
 
< 0.1%
43008 2
 
0.1%
43007 1
 
< 0.1%
43006 4
0.1%

사업장명
Text

Distinct3211
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
2023-12-11T05:25:48.058198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length5.9128718
Min length1

Characters and Unicode

Total characters22463
Distinct characters770
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

Unique2797 ?
Unique (%)73.6%

Sample

1st row원숭이식품
2nd row동북상회
3rd row황실떡집
4th row에프엔에스
5th row이유통
ValueCountFrequency (%)
주식회사 100
 
2.3%
농업회사법인 15
 
0.4%
우리식품 14
 
0.3%
주 14
 
0.3%
커피 14
 
0.3%
푸드 12
 
0.3%
제일식품 11
 
0.3%
coffee 11
 
0.3%
food 9
 
0.2%
현대식품 9
 
0.2%
Other values (3395) 4049
95.1%
2023-12-11T05:25:48.816055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 1255
 
5.6%
품 1095
 
4.9%
주 643
 
2.9%
) 609
 
2.7%
( 601
 
2.7%
드 476
 
2.1%
461
 
2.1%
푸 446
 
2.0%
이 411
 
1.8%
스 367
 
1.6%
Other values (760) 16099
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19719
87.8%
Close Punctuation 609
 
2.7%
Open Punctuation 601
 
2.7%
Uppercase Letter 512
 
2.3%
Space Separator 461
 
2.1%
Lowercase Letter 438
 
1.9%
Decimal Number 61
 
0.3%
Other Punctuation 59
 
0.3%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 1255
 
6.4%
품 1095
 
5.6%
주 643
 
3.3%
드 476
 
2.4%
푸 446
 
2.3%
이 411
 
2.1%
스 367
 
1.9%
사 331
 
1.7%
산 307
 
1.6%
리 299
 
1.5%
Other values (693) 14089
71.4%
Uppercase Letter
ValueCountFrequency (%)
F 51
 
10.0%
O 45
 
8.8%
S 40
 
7.8%
C 39
 
7.6%
B 35
 
6.8%
T 27
 
5.3%
N 27
 
5.3%
E 25
 
4.9%
D 25
 
4.9%
M 24
 
4.7%
Other values (14) 174
34.0%
Lowercase Letter
ValueCountFrequency (%)
e 81
18.5%
o 62
14.2%
f 36
 
8.2%
n 34
 
7.8%
a 31
 
7.1%
c 23
 
5.3%
s 23
 
5.3%
r 22
 
5.0%
t 20
 
4.6%
d 16
 
3.7%
Other values (13) 90
20.5%
Decimal Number
ValueCountFrequency (%)
2 14
23.0%
1 12
19.7%
3 9
14.8%
5 6
9.8%
6 5
 
8.2%
4 4
 
6.6%
9 3
 
4.9%
0 3
 
4.9%
8 3
 
4.9%
7 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
& 35
59.3%
. 15
25.4%
' 4
 
6.8%
, 3
 
5.1%
· 2
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 609
100.0%
Open Punctuation
ValueCountFrequency (%)
( 601
100.0%
Space Separator
ValueCountFrequency (%)
461
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19714
87.8%
Common 1794
 
8.0%
Latin 950
 
4.2%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 1255
 
6.4%
품 1095
 
5.6%
주 643
 
3.3%
드 476
 
2.4%
푸 446
 
2.3%
이 411
 
2.1%
스 367
 
1.9%
사 331
 
1.7%
산 307
 
1.6%
리 299
 
1.5%
Other values (688) 14084
71.4%
Latin
ValueCountFrequency (%)
e 81
 
8.5%
o 62
 
6.5%
F 51
 
5.4%
O 45
 
4.7%
S 40
 
4.2%
C 39
 
4.1%
f 36
 
3.8%
B 35
 
3.7%
n 34
 
3.6%
a 31
 
3.3%
Other values (37) 496
52.2%
Common
ValueCountFrequency (%)
) 609
33.9%
( 601
33.5%
461
25.7%
& 35
 
2.0%
. 15
 
0.8%
2 14
 
0.8%
1 12
 
0.7%
3 9
 
0.5%
5 6
 
0.3%
6 5
 
0.3%
Other values (10) 27
 
1.5%
Han
ValueCountFrequency (%)
蓮 1
20.0%
本 1
20.0%
禮 1
20.0%
嘉 1
20.0%
手 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19714
87.8%
ASCII 2742
 
12.2%
CJK 5
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 1255
 
6.4%
품 1095
 
5.6%
주 643
 
3.3%
드 476
 
2.4%
푸 446
 
2.3%
이 411
 
2.1%
스 367
 
1.9%
사 331
 
1.7%
산 307
 
1.6%
리 299
 
1.5%
Other values (688) 14084
71.4%
ASCII
ValueCountFrequency (%)
) 609
22.2%
( 601
21.9%
461
16.8%
e 81
 
3.0%
o 62
 
2.3%
F 51
 
1.9%
O 45
 
1.6%
S 40
 
1.5%
C 39
 
1.4%
f 36
 
1.3%
Other values (56) 717
26.1%
None
ValueCountFrequency (%)
· 2
100.0%
CJK
ValueCountFrequency (%)
蓮 1
20.0%
本 1
20.0%
禮 1
20.0%
嘉 1
20.0%
手 1
20.0%

최종수정시점
Real number (ℝ)

Distinct3393
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0133126 × 1013
Minimum2.001082 × 1013
Maximum2.022093 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:49.054403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001082 × 1013
5-th percentile2.002071 × 1013
Q12.0071101 × 1013
median2.0160108 × 1013
Q32.0191129 × 1013
95-th percentile2.0220408 × 1013
Maximum2.022093 × 1013
Range2.1011017 × 1011
Interquartile range (IQR)1.2002802 × 1011

Descriptive statistics

Standard deviation6.7955184 × 1010
Coefficient of variation (CV)0.0033752923
Kurtosis-1.314617
Mean2.0133126 × 1013
Median Absolute Deviation (MAD)5.070394 × 1010
Skewness-0.33299935
Sum7.6485745 × 1016
Variance4.6179071 × 1021
MonotonicityNot monotonic
2023-12-11T05:25:49.314184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020205000000 55
 
1.4%
20041011000000 23
 
0.6%
20020926000000 21
 
0.6%
20010821000000 18
 
0.5%
20030407000000 18
 
0.5%
20020508000000 14
 
0.4%
20020509000000 13
 
0.3%
20020507000000 13
 
0.3%
20021108000000 12
 
0.3%
20031027000000 12
 
0.3%
Other values (3383) 3600
94.8%
ValueCountFrequency (%)
20010820000000 4
 
0.1%
20010821000000 18
0.5%
20011108000000 2
 
0.1%
20011119000000 1
 
< 0.1%
20011122000000 1
 
< 0.1%
20011126000000 1
 
< 0.1%
20011128000000 3
 
0.1%
20011210000000 1
 
< 0.1%
20011226000000 1
 
< 0.1%
20011228000000 1
 
< 0.1%
ValueCountFrequency (%)
20220930172835 1
< 0.1%
20220930135917 1
< 0.1%
20220930111938 1
< 0.1%
20220929162511 1
< 0.1%
20220929162459 1
< 0.1%
20220929162441 1
< 0.1%
20220929162114 1
< 0.1%
20220929162058 1
< 0.1%
20220929162045 1
< 0.1%
20220929162021 1
< 0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
I
2684 
U
1115 

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 2684
70.7%
U 1115
29.3%

Length

2023-12-11T05:25:49.519966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:49.692782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2684
70.7%
u 1115
29.3%

데이터갱신일자
Date

Distinct771
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
Minimum2018-08-31 23:59:59
Maximum2022-10-02 02:40:00
2023-12-11T05:25:49.896334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:25:50.164164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
식품제조가공업
2796 
기타 식품제조가공업
975 
도시락제조업
 
28

Length

Max length10
Median length7
Mean length7.7625691
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2796
73.6%
기타 식품제조가공업 975
 
25.7%
도시락제조업 28
 
0.7%

Length

2023-12-11T05:25:50.466720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:50.660808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3771
79.0%
기타 975
 
20.4%
도시락제조업 28
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3104
Distinct (%)85.6%
Missing171
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean341852.05
Minimum323038.14
Maximum356965.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:50.863173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum323038.14
5-th percentile331574.9
Q1338742.97
median341574.06
Q3345491.55
95-th percentile352888.6
Maximum356965.56
Range33927.418
Interquartile range (IQR)6748.5725

Descriptive statistics

Standard deviation5848.2363
Coefficient of variation (CV)0.017107507
Kurtosis0.10038674
Mean341852.05
Median Absolute Deviation (MAD)3351.2302
Skewness-0.026499339
Sum1.2402392 × 109
Variance34201868
MonotonicityNot monotonic
2023-12-11T05:25:51.094213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
339243.983122 27
 
0.7%
334406.500396 7
 
0.2%
336661.678722 5
 
0.1%
346004.036082 5
 
0.1%
348434.155718 5
 
0.1%
338678.797273 4
 
0.1%
332331.72441 4
 
0.1%
335619.487404 4
 
0.1%
343260.899953 4
 
0.1%
345484.223256 4
 
0.1%
Other values (3094) 3559
93.7%
(Missing) 171
 
4.5%
ValueCountFrequency (%)
323038.137302 1
 
< 0.1%
323583.427786 1
 
< 0.1%
325649.192591 1
 
< 0.1%
325694.253396 1
 
< 0.1%
326018.881016 1
 
< 0.1%
326032.481595 1
 
< 0.1%
326631.950345 1
 
< 0.1%
326739.522357 4
0.1%
326760.851184 1
 
< 0.1%
326950.230819 1
 
< 0.1%
ValueCountFrequency (%)
356965.555233 1
 
< 0.1%
356410.892344 1
 
< 0.1%
356388.525062 1
 
< 0.1%
356370.038499 1
 
< 0.1%
356353.91544 1
 
< 0.1%
356349.757069 3
0.1%
356345.316761 1
 
< 0.1%
356335.999166 1
 
< 0.1%
356331.110923 1
 
< 0.1%
356328.871819 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3103
Distinct (%)85.5%
Missing171
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean263391.56
Minimum236164.39
Maximum278073.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:51.358311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum236164.39
5-th percentile253720.9
Q1261104.67
median263997.23
Q3266457.87
95-th percentile271937.64
Maximum278073.62
Range41909.231
Interquartile range (IQR)5353.2046

Descriptive statistics

Standard deviation5386.6182
Coefficient of variation (CV)0.02045099
Kurtosis3.3015662
Mean263391.56
Median Absolute Deviation (MAD)2700.2752
Skewness-1.104953
Sum9.5558457 × 108
Variance29015656
MonotonicityNot monotonic
2023-12-11T05:25:52.026935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
268026.454531 27
 
0.7%
260208.38965 7
 
0.2%
264017.165939 5
 
0.1%
261224.266018 5
 
0.1%
269131.73002 5
 
0.1%
259655.384838 4
 
0.1%
261375.426757 4
 
0.1%
242019.624632 4
 
0.1%
250014.011622 4
 
0.1%
265012.3332 4
 
0.1%
Other values (3093) 3559
93.7%
(Missing) 171
 
4.5%
ValueCountFrequency (%)
236164.392418 1
< 0.1%
237999.437164 1
< 0.1%
238531.35408 1
< 0.1%
238772.106218 1
< 0.1%
238772.40735 1
< 0.1%
238824.505921 1
< 0.1%
238893.362765 1
< 0.1%
238893.829912 1
< 0.1%
239059.112588 1
< 0.1%
239098.142264 1
< 0.1%
ValueCountFrequency (%)
278073.623286 1
< 0.1%
278029.090204 1
< 0.1%
277860.926384 1
< 0.1%
277755.206408 2
0.1%
277749.024029 1
< 0.1%
277673.246368 1
< 0.1%
277500.515376 1
< 0.1%
277489.106534 1
< 0.1%
277348.717166 1
< 0.1%
277022.824657 1
< 0.1%

위생업태명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
식품제조가공업
2796 
기타 식품제조가공업
975 
도시락제조업
 
28

Length

Max length10
Median length7
Mean length7.7625691
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2796
73.6%
기타 식품제조가공업 975
 
25.7%
도시락제조업 28
 
0.7%

Length

2023-12-11T05:25:52.243529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:52.444065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3771
79.0%
기타 975
 
20.4%
도시락제조업 28
 
0.6%

남성종사자수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
<NA>
3315 
0
484 

Length

Max length4
Median length4
Mean length3.6177942
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3315
87.3%
0 484
 
12.7%

Length

2023-12-11T05:25:52.633124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:52.843635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3315
87.3%
0 484
 
12.7%

여성종사자수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
<NA>
3315 
0
484 

Length

Max length4
Median length4
Mean length3.6177942
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3315
87.3%
0 484
 
12.7%

Length

2023-12-11T05:25:53.068294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:53.251654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3315
87.3%
0 484
 
12.7%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3799
Missing (%)100.0%
Memory size33.5 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3799
Missing (%)100.0%
Memory size33.5 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
상수도전용
2218 
<NA>
1561 
지하수전용
 
16
간이상수도
 
3
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length5
Mean length4.5922611
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2218
58.4%
<NA> 1561
41.1%
지하수전용 16
 
0.4%
간이상수도 3
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2023-12-11T05:25:53.443693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:53.678243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2218
58.4%
na 1561
41.1%
지하수전용 16
 
0.4%
간이상수도 3
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총직원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
<NA>
3329 
0
470 

Length

Max length4
Median length4
Mean length3.6288497
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> 3329
87.6%
0 470
 
12.4%

Length

2023-12-11T05:25:53.902874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:54.095050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3329
87.6%
0 470
 
12.4%

본사직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.3%
Missing621
Missing (%)16.3%
Infinite0
Infinite (%)0.0%
Mean0.068281938
Minimum0
Maximum12
Zeros3053
Zeros (%)80.4%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:54.271678image/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 deviation0.45168966
Coefficient of variation (CV)6.6150679
Kurtosis213.81088
Mean0.068281938
Median Absolute Deviation (MAD)0
Skewness11.993479
Sum217
Variance0.20402355
MonotonicityNot monotonic
2023-12-11T05:25:54.467714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3053
80.4%
1 86
 
2.3%
3 15
 
0.4%
2 14
 
0.4%
5 5
 
0.1%
4 2
 
0.1%
12 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 621
 
16.3%
ValueCountFrequency (%)
0 3053
80.4%
1 86
 
2.3%
2 14
 
0.4%
3 15
 
0.4%
4 2
 
0.1%
5 5
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 5
 
0.1%
4 2
 
0.1%
3 15
 
0.4%
2 14
 
0.4%
1 86
 
2.3%
0 3053
80.4%

공장사무직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct11
Distinct (%)0.3%
Missing610
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean0.20539354
Minimum0
Maximum40
Zeros2786
Zeros (%)73.3%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:54.682844image/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 deviation1.0193343
Coefficient of variation (CV)4.9628352
Kurtosis767.39061
Mean0.20539354
Median Absolute Deviation (MAD)0
Skewness22.274901
Sum655
Variance1.0390424
MonotonicityNot monotonic
2023-12-11T05:25:54.881994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 2786
73.3%
1 302
 
7.9%
2 59
 
1.6%
3 21
 
0.6%
4 8
 
0.2%
6 4
 
0.1%
5 3
 
0.1%
11 2
 
0.1%
15 2
 
0.1%
40 1
 
< 0.1%
(Missing) 610
 
16.1%
ValueCountFrequency (%)
0 2786
73.3%
1 302
 
7.9%
2 59
 
1.6%
3 21
 
0.6%
4 8
 
0.2%
5 3
 
0.1%
6 4
 
0.1%
9 1
 
< 0.1%
11 2
 
0.1%
15 2
 
0.1%
ValueCountFrequency (%)
40 1
 
< 0.1%
15 2
 
0.1%
11 2
 
0.1%
9 1
 
< 0.1%
6 4
 
0.1%
5 3
 
0.1%
4 8
 
0.2%
3 21
 
0.6%
2 59
 
1.6%
1 302
7.9%

공장판매직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.3%
Missing630
Missing (%)16.6%
Infinite0
Infinite (%)0.0%
Mean0.10224045
Minimum0
Maximum30
Zeros2953
Zeros (%)77.7%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:55.056352image/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 deviation0.68138907
Coefficient of variation (CV)6.664574
Kurtosis1190.5577
Mean0.10224045
Median Absolute Deviation (MAD)0
Skewness28.863139
Sum324
Variance0.46429106
MonotonicityNot monotonic
2023-12-11T05:25:55.227949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 2953
77.7%
1 166
 
4.4%
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) 630
 
16.6%
ValueCountFrequency (%)
0 2953
77.7%
1 166
 
4.4%
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%
1 166
 
4.4%
0 2953
77.7%

공장생산직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct27
Distinct (%)0.8%
Missing539
Missing (%)14.2%
Infinite0
Infinite (%)0.0%
Mean0.81748466
Minimum0
Maximum220
Zeros2334
Zeros (%)61.4%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:55.429106image/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 deviation4.6537161
Coefficient of variation (CV)5.6927259
Kurtosis1547.1919
Mean0.81748466
Median Absolute Deviation (MAD)0
Skewness34.776753
Sum2665
Variance21.657074
MonotonicityNot monotonic
2023-12-11T05:25:55.637047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 2334
61.4%
1 460
 
12.1%
2 202
 
5.3%
3 107
 
2.8%
4 48
 
1.3%
5 31
 
0.8%
7 18
 
0.5%
6 13
 
0.3%
8 12
 
0.3%
10 7
 
0.2%
Other values (17) 28
 
0.7%
(Missing) 539
 
14.2%
ValueCountFrequency (%)
0 2334
61.4%
1 460
 
12.1%
2 202
 
5.3%
3 107
 
2.8%
4 48
 
1.3%
5 31
 
0.8%
6 13
 
0.3%
7 18
 
0.5%
8 12
 
0.3%
9 5
 
0.1%
ValueCountFrequency (%)
220 1
< 0.1%
83 1
< 0.1%
50 1
< 0.1%
42 1
< 0.1%
32 1
< 0.1%
28 1
< 0.1%
25 1
< 0.1%
22 1
< 0.1%
21 1
< 0.1%
20 2
0.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
<NA>
1820 
임대
1154 
자가
825 

Length

Max length4
Median length2
Mean length2.9581469
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1820
47.9%
임대 1154
30.4%
자가 825
21.7%

Length

2023-12-11T05:25:55.850847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:56.020101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1820
47.9%
임대 1154
30.4%
자가 825
21.7%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)2.7%
Missing3137
Missing (%)82.6%
Infinite0
Infinite (%)0.0%
Mean936407.55
Minimum0
Maximum50000000
Zeros598
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:56.161118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6950000
Maximum50000000
Range50000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4204696.1
Coefficient of variation (CV)4.4902416
Kurtosis73.849549
Mean936407.55
Median Absolute Deviation (MAD)0
Skewness7.6875657
Sum6.199018 × 108
Variance1.7679469 × 1013
MonotonicityNot monotonic
2023-12-11T05:25:56.332932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 598
 
15.7%
10000000 24
 
0.6%
5000000 19
 
0.5%
3000000 3
 
0.1%
8000000 2
 
0.1%
30000000 2
 
0.1%
50000000 2
 
0.1%
2000000 2
 
0.1%
500 1
 
< 0.1%
6000000 1
 
< 0.1%
Other values (8) 8
 
0.2%
(Missing) 3137
82.6%
ValueCountFrequency (%)
0 598
15.7%
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 (%)3.9%
Missing3138
Missing (%)82.6%
Infinite0
Infinite (%)0.0%
Mean52557.02
Minimum0
Maximum2200000
Zeros597
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:56.514896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile440000
Maximum2200000
Range2200000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation206000
Coefficient of variation (CV)3.9195525
Kurtosis43.063814
Mean52557.02
Median Absolute Deviation (MAD)0
Skewness5.7989207
Sum34740190
Variance4.2435999 × 1010
MonotonicityNot monotonic
2023-12-11T05:25:56.705009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 597
 
15.7%
300000 13
 
0.3%
500000 11
 
0.3%
400000 5
 
0.1%
600000 4
 
0.1%
350000 3
 
0.1%
200000 3
 
0.1%
800000 3
 
0.1%
450000 2
 
0.1%
250000 2
 
0.1%
Other values (16) 18
 
0.5%
(Missing) 3138
82.6%
ValueCountFrequency (%)
0 597
15.7%
10 1
 
< 0.1%
30 1
 
< 0.1%
150 1
 
< 0.1%
150000 1
 
< 0.1%
200000 3
 
0.1%
250000 2
 
0.1%
300000 13
 
0.3%
350000 3
 
0.1%
400000 5
 
0.1%
ValueCountFrequency (%)
2200000 1
 
< 0.1%
2000000 1
 
< 0.1%
1800000 1
 
< 0.1%
1300000 1
 
< 0.1%
1200000 1
 
< 0.1%
1100000 1
 
< 0.1%
900000 1
 
< 0.1%
850000 2
0.1%
800000 3
0.1%
750000 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
False
3797 
True
 
2
ValueCountFrequency (%)
False 3797
99.9%
True 2
 
0.1%
2023-12-11T05:25:56.839789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct552
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.042909
Minimum0
Maximum4673.38
Zeros3007
Zeros (%)79.2%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-11T05:25:57.012089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile40.082
Maximum4673.38
Range4673.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation122.29055
Coefficient of variation (CV)10.154569
Kurtosis1051.9259
Mean12.042909
Median Absolute Deviation (MAD)0
Skewness30.042789
Sum45751.01
Variance14954.979
MonotonicityNot monotonic
2023-12-11T05:25:57.222491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3007
79.2%
3.0 24
 
0.6%
6.0 17
 
0.4%
1.0 15
 
0.4%
4.0 12
 
0.3%
2.0 12
 
0.3%
3.3 10
 
0.3%
4.5 8
 
0.2%
1.2 8
 
0.2%
9.0 7
 
0.2%
Other values (542) 679
 
17.9%
ValueCountFrequency (%)
0.0 3007
79.2%
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 

Missing3799
Missing (%)100.0%
Memory size33.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3799
Missing (%)100.0%
Memory size33.5 KiB

홈페이지
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
<NA>
3797 
4
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.9984206
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> 3797
99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Length

2023-12-11T05:25:57.444508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:25:57.619867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3797
99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품제조가공업07_22_11_P34100003410000-106-2004-0000120040315<NA>3폐업2폐업20041204<NA><NA><NA><NA>74.55700809대구광역시 중구 대봉동 0040-0033번지<NA><NA>원숭이식품20040409000000I2018-08-31 23:59:59.0식품제조가공업344927.7812263298.66826식품제조가공업00<NA><NA>상수도전용<NA>0111임대<NA><NA>N0.0<NA><NA><NA>
12식품제조가공업07_22_11_P34100003410000-106-2004-0000220040507<NA>3폐업2폐업20050324<NA><NA><NA>053 424497914.70700111대구광역시 중구 태평로1가 0001-0186번지<NA><NA>동북상회20041102000000I2018-08-31 23:59:59.0식품제조가공업344182.487426265065.535111식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0011<NA><NA><NA>N0.0<NA><NA><NA>
23식품제조가공업07_22_11_P34100003410000-106-2004-0000320040524<NA>3폐업2폐업20150424<NA><NA><NA>053 256433741.85700837대구광역시 중구 남산동 2466-0001번지 보성황실아파트 116동 105호대구광역시 중구 남산로13길 17, 1층 (남산동, 보성황실아파트 116동 105호)41978황실떡집20150304143402I2018-08-31 23:59:59.0식품제조가공업342754.486268263376.49575식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0002자가<NA><NA>N0.0<NA><NA><NA>
34식품제조가공업07_22_11_P34100003410000-106-2004-0000420040629<NA>3폐업2폐업20040908<NA><NA><NA>053 4240540120.60700823대구광역시 중구 봉산동 0165-0007번지<NA><NA>에프엔에스20040901000000I2018-08-31 23:59:59.0식품제조가공업344341.820223263777.999999식품제조가공업00<NA><NA>상수도전용<NA>0121임대<NA><NA>N0.0<NA><NA><NA>
45식품제조가공업07_22_11_P34100003410000-106-2004-0000520041101<NA>3폐업2폐업20080717<NA><NA><NA>053 422331834.52700845대구광역시 중구 동인동3가 0302-0002번지<NA><NA>이유통20071126103251I2018-08-31 23:59:59.0식품제조가공업345483.514708264655.185763식품제조가공업<NA><NA><NA><NA>상수도전용<NA>1000자가<NA><NA>N0.0<NA><NA><NA>
56식품제조가공업07_22_11_P34100003410000-106-2004-0000620041111<NA>3폐업2폐업20050906<NA><NA><NA><NA>25.23700421대구광역시 중구 동인동1가 0196번지<NA><NA>불스푸드20050321000000I2018-08-31 23:59:59.0식품제조가공업344696.914116264897.878354식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0111자가<NA><NA>N0.0<NA><NA><NA>
67식품제조가공업07_22_11_P34100003410000-106-2004-0000720041119<NA>3폐업2폐업20041120<NA><NA><NA>053 4294238<NA>700180대구광역시 중구 동문동 0020-0004번지<NA><NA>(사)농어촌특산단지전남연합회20041119000000I2018-08-31 23:59:59.0식품제조가공업344148.352033264812.35373식품제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
78식품제조가공업07_22_11_P34100003410000-106-2004-0000820041202<NA>3폐업2폐업20100621<NA><NA><NA>053 254013230.20700413대구광역시 중구 삼덕동3가 0042번지<NA><NA>교자춘20071113181224I2018-08-31 23:59:59.0식품제조가공업345042.851191263965.608979식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0102자가<NA><NA>N0.0<NA><NA><NA>
89식품제조가공업07_22_11_P34100003410000-106-2005-0000220050623<NA>3폐업2폐업20050706<NA><NA><NA><NA><NA>700320대구광역시 중구 대신동 115-370번지 1층<NA><NA>경북농산20050623000000I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
910식품제조가공업07_22_11_P34100003410000-106-2005-0000420050908<NA>3폐업2폐업20070208<NA><NA><NA><NA>67.75700413대구광역시 중구 삼덕동3가 0227-0006번지<NA><NA>(주)승민식품20050908000000I2018-08-31 23:59:59.0식품제조가공업345171.417199263913.270601식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0202자가<NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
37893790식품제조가공업07_22_11_P34800003480000-106-2021-0000620210430<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.00711852대구광역시 달성군 논공읍 남리 224-110대구광역시 달성군 논공읍 논공로 806-1, 1층42978네츄럴팩트20210430134728I2021-05-02 00:22:57.0기타 식품제조가공업330115.35775248516.530338기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
37903791식품제조가공업07_22_11_P34800003480000-106-2008-0001720080104<NA>1영업/정상1영업<NA><NA><NA><NA>053 627 2557447.00711850대구광역시 달성군 논공읍 삼리리 632-1번지 외 1필지 A동대구광역시 달성군 논공읍 위천2길 6, A동 1층42976정통식품20160127164501I2018-08-31 23:59:59.0식품제조가공업327021.529591252397.401938식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
37913792식품제조가공업07_22_11_P34800003480000-106-2012-0001020120911<NA>1영업/정상1영업<NA><NA><NA><NA>070 75325543149.47711832대구광역시 달성군 화원읍 명곡리 105번지 2층대구광역시 달성군 화원읍 명곡로 12-11, 2층42960청원푸드20160128102651I2018-08-31 23:59:59.0식품제조가공업335094.531933256378.574073식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
37923793식품제조가공업07_22_11_P34800003480000-106-2013-0000620130808<NA>1영업/정상1영업<NA><NA><NA><NA>053 639 5887159.30711839대구광역시 달성군 화원읍 성산리 536-6번지대구광역시 달성군 화원읍 성천로12길 1142946선미 푸드20160128164651I2018-08-31 23:59:59.0식품제조가공업334521.009928256794.676167식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
37933794식품제조가공업07_22_11_P34800003480000-106-2012-0000520120615<NA>1영업/정상1영업<NA><NA><NA><NA>053 584 4884472.00711821대구광역시 달성군 하빈면 하산리 133-1번지대구광역시 달성군 하빈면 하산4길 7842900훈식품20170825094405I2018-08-31 23:59:59.0식품제조가공업327642.468368267180.710022식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
37943795식품제조가공업07_22_11_P34800003480000-106-2007-0001820071108<NA>1영업/정상1영업<NA><NA><NA><NA>053 6443684204.00711855대구광역시 달성군 논공읍 본리리 29-53번지대구광역시 달성군 논공읍 논공로71길 2742982미성20191011162442U2019-10-13 02:40:00.0식품제조가공업332803.386147250052.269534식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0102임대<NA><NA>N8.0<NA><NA><NA>
37953796식품제조가공업07_22_11_P34800003480000-106-2007-0001920071113<NA>1영업/정상1영업<NA><NA><NA><NA>053 61196111,205.93711892대구광역시 달성군 구지면 내리 839-11번지대구광역시 달성군 구지면 달성2차로 2743011(주)푸름원20160127154201I2018-08-31 23:59:59.0식품제조가공업327415.835763238772.106218식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
37963797식품제조가공업07_22_11_P34800003480000-106-1997-0000819970924<NA>1영업/정상1영업<NA><NA><NA><NA><NA>837.90711823대구광역시 달성군 하빈면 봉촌리 1032-3번지대구광역시 달성군 하빈면 하빈남로 40742905연꽃마을20160127155832I2018-08-31 23:59:59.0식품제조가공업325649.192591263403.704757식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0102<NA><NA><NA>N0.0<NA><NA><NA>
37973798식품제조가공업07_22_11_P34800003480000-106-1997-0001019971006<NA>1영업/정상1영업<NA><NA><NA><NA>053 6153645225.00711842대구광역시 달성군 옥포면 강림리 263번지대구광역시 달성군 옥포면 시저로4길 1642968나진제과20160127155852I2018-08-31 23:59:59.0식품제조가공업329266.735737254748.099287식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0103<NA><NA><NA>N0.0<NA><NA><NA>
37983799식품제조가공업07_22_11_P34800003480000-106-1998-0000119980319<NA>1영업/정상1영업<NA><NA><NA><NA>053 6390167176.00711833대구광역시 달성군 화원읍 설화리 613-2번지대구광역시 달성군 화원읍 모개골길 15-1142957서울종합식품20160127155920I2018-08-31 23:59:59.0식품제조가공업334243.190347256051.77438식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0111임대<NA><NA>N0.0<NA><NA><NA>