Overview

Dataset statistics

Number of variables47
Number of observations3822
Missing cells44650
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

Description22년12월_6270000_대구광역시_07_22_11_P_식품제조가공업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000097396&dataSetDetailId=DDI_0000097433&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
급수시설구분명 is highly imbalanced (55.7%)Imbalance
다중이용업소여부 is highly imbalanced (99.4%)Imbalance
홈페이지 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3822 (100.0%) missing valuesMissing
폐업일자 has 1021 (26.7%) missing valuesMissing
휴업시작일자 has 3822 (100.0%) missing valuesMissing
휴업종료일자 has 3822 (100.0%) missing valuesMissing
재개업일자 has 3822 (100.0%) missing valuesMissing
소재지전화 has 1083 (28.3%) missing valuesMissing
소재지면적 has 136 (3.6%) missing valuesMissing
소재지우편번호 has 85 (2.2%) missing valuesMissing
도로명전체주소 has 1370 (35.8%) missing valuesMissing
도로명우편번호 has 1398 (36.6%) missing valuesMissing
좌표정보(X) has 212 (5.5%) missing valuesMissing
좌표정보(Y) has 212 (5.5%) missing valuesMissing
영업장주변구분명 has 3822 (100.0%) missing valuesMissing
등급구분명 has 3822 (100.0%) missing valuesMissing
본사직원수 has 610 (16.0%) missing valuesMissing
공장사무직직원수 has 598 (15.6%) missing valuesMissing
공장판매직직원수 has 616 (16.1%) missing valuesMissing
공장생산직직원수 has 528 (13.8%) missing valuesMissing
보증액 has 3089 (80.8%) missing valuesMissing
월세액 has 3090 (80.8%) missing valuesMissing
전통업소지정번호 has 3822 (100.0%) missing valuesMissing
전통업소주된음식 has 3822 (100.0%) missing valuesMissing
공장사무직직원수 is highly skewed (γ1 = 22.3883956)Skewed
공장판매직직원수 is highly skewed (γ1 = 29.02486237)Skewed
공장생산직직원수 is highly skewed (γ1 = 34.94618147)Skewed
시설총규모 is highly skewed (γ1 = 29.75521456)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 3085 (80.7%) zerosZeros
공장사무직직원수 has 2821 (73.8%) zerosZeros
공장판매직직원수 has 2990 (78.2%) zerosZeros
공장생산직직원수 has 2368 (62.0%) zerosZeros
보증액 has 669 (17.5%) zerosZeros
월세액 has 668 (17.5%) zerosZeros
시설총규모 has 3019 (79.0%) zerosZeros

Reproduction

Analysis started2023-12-10 17:53:10.199280
Analysis finished2023-12-10 17:53:13.765538
Duration3.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3822
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1911.5
Minimum1
Maximum3822
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:13.985490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile192.05
Q1956.25
median1911.5
Q32866.75
95-th percentile3630.95
Maximum3822
Range3821
Interquartile range (IQR)1910.5

Descriptive statistics

Standard deviation1103.4607
Coefficient of variation (CV)0.57727475
Kurtosis-1.2
Mean1911.5
Median Absolute Deviation (MAD)955.5
Skewness0
Sum7305753
Variance1217625.5
MonotonicityStrictly increasing
2023-12-11T02:53:14.438270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2554 1
 
< 0.1%
2542 1
 
< 0.1%
2543 1
 
< 0.1%
2544 1
 
< 0.1%
2545 1
 
< 0.1%
2546 1
 
< 0.1%
2547 1
 
< 0.1%
2548 1
 
< 0.1%
2549 1
 
< 0.1%
Other values (3812) 3812
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 (%)
3822 1
< 0.1%
3821 1
< 0.1%
3820 1
< 0.1%
3819 1
< 0.1%
3818 1
< 0.1%
3817 1
< 0.1%
3816 1
< 0.1%
3815 1
< 0.1%
3814 1
< 0.1%
3813 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
식품제조가공업
3822 

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 3822
100.0%

Length

2023-12-11T02:53:14.852021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:15.074476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3822
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
07_22_11_P
3822 

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 3822
100.0%

Length

2023-12-11T02:53:15.304004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:15.585979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_11_p 3822
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3449905.8
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:15.846116image/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 deviation20883.183
Coefficient of variation (CV)0.0060532617
Kurtosis-0.95423413
Mean3449905.8
Median Absolute Deviation (MAD)20000
Skewness-0.3026704
Sum1.318554 × 1010
Variance4.3610733 × 108
MonotonicityIncreasing
2023-12-11T02:53:16.195849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 965
25.2%
3470000 657
17.2%
3480000 476
12.5%
3420000 444
11.6%
3460000 439
11.5%
3430000 372
 
9.7%
3440000 245
 
6.4%
3410000 224
 
5.9%
ValueCountFrequency (%)
3410000 224
 
5.9%
3420000 444
11.6%
3430000 372
 
9.7%
3440000 245
 
6.4%
3450000 965
25.2%
3460000 439
11.5%
3470000 657
17.2%
3480000 476
12.5%
ValueCountFrequency (%)
3480000 476
12.5%
3470000 657
17.2%
3460000 439
11.5%
3450000 965
25.2%
3440000 245
 
6.4%
3430000 372
 
9.7%
3420000 444
11.6%
3410000 224
 
5.9%

관리번호
Text

UNIQUE 

Distinct3822
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
2023-12-11T02:53:16.730719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters84084
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

Unique3822 ?
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%
3460000-106-2010-00015 1
 
< 0.1%
3460000-106-2020-00008 1
 
< 0.1%
3460000-106-2007-00017 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%
3460000-106-2011-00004 1
 
< 0.1%
Other values (3812) 3812
99.7%
2023-12-11T02:53:17.654934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38298
45.5%
- 11466
 
13.6%
1 8042
 
9.6%
2 5751
 
6.8%
3 5189
 
6.2%
6 5007
 
6.0%
4 4899
 
5.8%
5 1720
 
2.0%
7 1378
 
1.6%
9 1179
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72618
86.4%
Dash Punctuation 11466
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38298
52.7%
1 8042
 
11.1%
2 5751
 
7.9%
3 5189
 
7.1%
6 5007
 
6.9%
4 4899
 
6.7%
5 1720
 
2.4%
7 1378
 
1.9%
9 1179
 
1.6%
8 1155
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 11466
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84084
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38298
45.5%
- 11466
 
13.6%
1 8042
 
9.6%
2 5751
 
6.8%
3 5189
 
6.2%
6 5007
 
6.0%
4 4899
 
5.8%
5 1720
 
2.0%
7 1378
 
1.6%
9 1179
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84084
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38298
45.5%
- 11466
 
13.6%
1 8042
 
9.6%
2 5751
 
6.8%
3 5189
 
6.2%
6 5007
 
6.0%
4 4899
 
5.8%
5 1720
 
2.0%
7 1378
 
1.6%
9 1179
 
1.4%

인허가일자
Real number (ℝ)

Distinct2714
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20090724
Minimum19681218
Maximum20221226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:18.044714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19681218
5-th percentile19980413
Q120031126
median20091210
Q320150610
95-th percentile20210210
Maximum20221226
Range540008
Interquartile range (IQR)119484

Descriptive statistics

Standard deviation75935.383
Coefficient of variation (CV)0.003779624
Kurtosis1.3083918
Mean20090724
Median Absolute Deviation (MAD)59518.5
Skewness-0.59533544
Sum7.6786748 × 1010
Variance5.7661824 × 109
MonotonicityNot monotonic
2023-12-11T02:53:18.442087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000302 28
 
0.7%
19960320 19
 
0.5%
19960516 7
 
0.2%
20110520 6
 
0.2%
19930320 6
 
0.2%
20071108 5
 
0.1%
20160523 5
 
0.1%
20180706 5
 
0.1%
20130725 5
 
0.1%
20160322 4
 
0.1%
Other values (2704) 3732
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 (%)
20221226 1
< 0.1%
20221223 1
< 0.1%
20221222 1
< 0.1%
20221221 1
< 0.1%
20221216 1
< 0.1%
20221215 1
< 0.1%
20221206 1
< 0.1%
20221129 1
< 0.1%
20221125 2
0.1%
20221117 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3822
Missing (%)100.0%
Memory size33.7 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
3
2801 
1
1021 

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 2801
73.3%
1 1021
 
26.7%

Length

2023-12-11T02:53:18.770368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:18.997668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2801
73.3%
1 1021
 
26.7%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
폐업
2801 
영업/정상
1021 

Length

Max length5
Median length2
Mean length2.8014129
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2801
73.3%
영업/정상 1021
 
26.7%

Length

2023-12-11T02:53:19.284625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:19.589501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2801
73.3%
영업/정상 1021
 
26.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
2
2801 
1
1021 

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 2801
73.3%
1 1021
 
26.7%

Length

2023-12-11T02:53:19.876503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:20.123853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2801
73.3%
1 1021
 
26.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
폐업
2801 
영업
1021 

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 2801
73.3%
영업 1021
 
26.7%

Length

2023-12-11T02:53:20.398239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:20.669016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2801
73.3%
영업 1021
 
26.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct2079
Distinct (%)74.2%
Missing1021
Missing (%)26.7%
Infinite0
Infinite (%)0.0%
Mean20119408
Minimum20000424
Maximum20221231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:21.001301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000424
5-th percentile20030311
Q120070131
median20120612
Q320170529
95-th percentile20211115
Maximum20221231
Range220807
Interquartile range (IQR)100398

Descriptive statistics

Standard deviation59655.306
Coefficient of variation (CV)0.0029650627
Kurtosis-1.1853547
Mean20119408
Median Absolute Deviation (MAD)50284
Skewness-0.011712363
Sum5.6354462 × 1010
Variance3.5587556 × 109
MonotonicityNot monotonic
2023-12-11T02:53:21.454016image/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%
20100715 4
 
0.1%
20160127 4
 
0.1%
20111221 4
 
0.1%
20140514 4
 
0.1%
20071108 4
 
0.1%
20120206 4
 
0.1%
Other values (2069) 2755
72.1%
(Missing) 1021
 
26.7%
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 (%)
20221231 1
 
< 0.1%
20221230 3
0.1%
20221229 2
0.1%
20221227 2
0.1%
20221226 1
 
< 0.1%
20221222 2
0.1%
20221220 1
 
< 0.1%
20221216 1
 
< 0.1%
20221214 3
0.1%
20221213 1
 
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3822
Missing (%)100.0%
Memory size33.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3822
Missing (%)100.0%
Memory size33.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3822
Missing (%)100.0%
Memory size33.7 KiB

소재지전화
Text

MISSING 

Distinct2536
Distinct (%)92.6%
Missing1083
Missing (%)28.3%
Memory size30.0 KiB
2023-12-11T02:53:22.257631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.85031
Min length3

Characters and Unicode

Total characters29719
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

Unique2344 ?
Unique (%)85.6%

Sample

1st row053 4244979
2nd row053 2564337
3rd row053 4240540
4th row053 4223318
5th row053 4294238
ValueCountFrequency (%)
053 2014
34.8%
070 69
 
1.2%
311 21
 
0.4%
313 15
 
0.3%
611 13
 
0.2%
621 13
 
0.2%
314 13
 
0.2%
983 13
 
0.2%
767 12
 
0.2%
615 11
 
0.2%
Other values (2694) 3588
62.1%
2023-12-11T02:53:23.362859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4908
16.5%
3 4346
14.6%
0 4255
14.3%
3123
10.5%
2 2127
7.2%
6 2097
7.1%
1 2062
6.9%
7 1886
 
6.3%
8 1784
 
6.0%
4 1637
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26596
89.5%
Space Separator 3123
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4908
18.5%
3 4346
16.3%
0 4255
16.0%
2 2127
8.0%
6 2097
7.9%
1 2062
7.8%
7 1886
 
7.1%
8 1784
 
6.7%
4 1637
 
6.2%
9 1494
 
5.6%
Space Separator
ValueCountFrequency (%)
3123
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29719
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4908
16.5%
3 4346
14.6%
0 4255
14.3%
3123
10.5%
2 2127
7.2%
6 2097
7.1%
1 2062
6.9%
7 1886
 
6.3%
8 1784
 
6.0%
4 1637
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29719
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4908
16.5%
3 4346
14.6%
0 4255
14.3%
3123
10.5%
2 2127
7.2%
6 2097
7.1%
1 2062
6.9%
7 1886
 
6.3%
8 1784
 
6.0%
4 1637
 
5.5%

소재지면적
Text

MISSING 

Distinct2661
Distinct (%)72.2%
Missing136
Missing (%)3.6%
Memory size30.0 KiB
2023-12-11T02:53:24.216707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.378459
Min length3

Characters and Unicode

Total characters19825
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

Unique2173 ?
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%
20.00 25
 
0.7%
33.00 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 (2651) 3508
95.2%
2023-12-11T02:53:25.454396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3686
18.6%
0 3432
17.3%
1 1820
9.2%
2 1754
8.8%
4 1459
 
7.4%
3 1457
 
7.3%
5 1397
 
7.0%
6 1370
 
6.9%
8 1189
 
6.0%
7 1119
 
5.6%
Other values (2) 1142
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16065
81.0%
Other Punctuation 3760
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3432
21.4%
1 1820
11.3%
2 1754
10.9%
4 1459
9.1%
3 1457
9.1%
5 1397
8.7%
6 1370
 
8.5%
8 1189
 
7.4%
7 1119
 
7.0%
9 1068
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 3686
98.0%
, 74
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19825
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3686
18.6%
0 3432
17.3%
1 1820
9.2%
2 1754
8.8%
4 1459
 
7.4%
3 1457
 
7.3%
5 1397
 
7.0%
6 1370
 
6.9%
8 1189
 
6.0%
7 1119
 
5.6%
Other values (2) 1142
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19825
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3686
18.6%
0 3432
17.3%
1 1820
9.2%
2 1754
8.8%
4 1459
 
7.4%
3 1457
 
7.3%
5 1397
 
7.0%
6 1370
 
6.9%
8 1189
 
6.0%
7 1119
 
5.6%
Other values (2) 1142
 
5.8%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct551
Distinct (%)14.7%
Missing85
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean704580.61
Minimum700010
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:25.915312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700837
Q1702805
median703833
Q3705823
95-th percentile711846
Maximum711893
Range11883
Interquartile range (IQR)3018

Descriptive statistics

Standard deviation3079.1262
Coefficient of variation (CV)0.0043701547
Kurtosis0.78504645
Mean704580.61
Median Absolute Deviation (MAD)1761
Skewness1.1858533
Sum2.6330177 × 109
Variance9481018.3
MonotonicityNot monotonic
2023-12-11T02:53:26.311066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 90
 
2.4%
702061 83
 
2.2%
703830 57
 
1.5%
703833 50
 
1.3%
702816 46
 
1.2%
704080 43
 
1.1%
702903 36
 
0.9%
704900 36
 
0.9%
701140 34
 
0.9%
711851 34
 
0.9%
Other values (541) 3228
84.5%
(Missing) 85
 
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 2
 
0.1%
711871 9
0.2%
711864 12
0.3%
711863 21
0.5%
711862 3
 
0.1%
711861 2
 
0.1%
711858 11
0.3%
Distinct3547
Distinct (%)93.4%
Missing26
Missing (%)0.7%
Memory size30.0 KiB
2023-12-11T02:53:27.311327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length49
Mean length23.810327
Min length15

Characters and Unicode

Total characters90384
Distinct characters301
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

Unique3337 ?
Unique (%)87.9%

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 3796
22.3%
북구 958
 
5.6%
달서구 654
 
3.8%
달성군 472
 
2.8%
동구 444
 
2.6%
수성구 427
 
2.5%
서구 373
 
2.2%
남구 245
 
1.4%
중구 224
 
1.3%
지상1층 201
 
1.2%
Other values (3947) 9239
54.2%
2023-12-11T02:53:28.623354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16994
18.8%
7226
 
8.0%
1 4501
 
5.0%
4131
 
4.6%
4043
 
4.5%
3851
 
4.3%
3801
 
4.2%
3801
 
4.2%
3467
 
3.8%
- 3170
 
3.5%
Other values (291) 35399
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50415
55.8%
Decimal Number 18853
 
20.9%
Space Separator 16994
 
18.8%
Dash Punctuation 3170
 
3.5%
Open Punctuation 346
 
0.4%
Close Punctuation 346
 
0.4%
Other Punctuation 126
 
0.1%
Uppercase Letter 117
 
0.1%
Math Symbol 14
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7226
14.3%
4131
 
8.2%
4043
 
8.0%
3851
 
7.6%
3801
 
7.5%
3801
 
7.5%
3467
 
6.9%
2950
 
5.9%
1202
 
2.4%
1194
 
2.4%
Other values (262) 14749
29.3%
Decimal Number
ValueCountFrequency (%)
1 4501
23.9%
2 2358
12.5%
0 2070
11.0%
3 1950
10.3%
4 1574
 
8.3%
5 1458
 
7.7%
6 1377
 
7.3%
7 1271
 
6.7%
8 1174
 
6.2%
9 1120
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 52
44.4%
A 49
41.9%
C 8
 
6.8%
T 2
 
1.7%
E 2
 
1.7%
D 2
 
1.7%
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 (%)
16994
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3170
100.0%
Open Punctuation
ValueCountFrequency (%)
( 346
100.0%
Close Punctuation
ValueCountFrequency (%)
) 346
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50415
55.8%
Common 39849
44.1%
Latin 120
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7226
14.3%
4131
 
8.2%
4043
 
8.0%
3851
 
7.6%
3801
 
7.5%
3801
 
7.5%
3467
 
6.9%
2950
 
5.9%
1202
 
2.4%
1194
 
2.4%
Other values (262) 14749
29.3%
Common
ValueCountFrequency (%)
16994
42.6%
1 4501
 
11.3%
- 3170
 
8.0%
2 2358
 
5.9%
0 2070
 
5.2%
3 1950
 
4.9%
4 1574
 
3.9%
5 1458
 
3.7%
6 1377
 
3.5%
7 1271
 
3.2%
Other values (9) 3126
 
7.8%
Latin
ValueCountFrequency (%)
B 52
43.3%
A 49
40.8%
C 8
 
6.7%
e 2
 
1.7%
T 2
 
1.7%
E 2
 
1.7%
D 2
 
1.7%
J 1
 
0.8%
P 1
 
0.8%
c 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50415
55.8%
ASCII 39969
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16994
42.5%
1 4501
 
11.3%
- 3170
 
7.9%
2 2358
 
5.9%
0 2070
 
5.2%
3 1950
 
4.9%
4 1574
 
3.9%
5 1458
 
3.6%
6 1377
 
3.4%
7 1271
 
3.2%
Other values (19) 3246
 
8.1%
Hangul
ValueCountFrequency (%)
7226
14.3%
4131
 
8.2%
4043
 
8.0%
3851
 
7.6%
3801
 
7.5%
3801
 
7.5%
3467
 
6.9%
2950
 
5.9%
1202
 
2.4%
1194
 
2.4%
Other values (262) 14749
29.3%

도로명전체주소
Text

MISSING 

Distinct2340
Distinct (%)95.4%
Missing1370
Missing (%)35.8%
Memory size30.0 KiB
2023-12-11T02:53:29.590658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length54
Mean length27.864192
Min length20

Characters and Unicode

Total characters68323
Distinct characters324
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

Unique2239 ?
Unique (%)91.3%

Sample

1st row대구광역시 중구 남산로13길 17, 1층 (남산동, 보성황실아파트 116동 105호)
2nd row대구광역시 중구 동덕로30길 139-24, 1층 (동인동4가)
3rd row대구광역시 중구 서성로14길 85 (대안동, 지상2층)
4th row대구광역시 중구 남산로 23-15, 1층 (남산동)
5th row대구광역시 중구 달성공원로6길 8, 지상 1층 (대신동)
ValueCountFrequency (%)
대구광역시 2452
 
17.8%
북구 628
 
4.6%
1층 595
 
4.3%
달서구 364
 
2.6%
달성군 318
 
2.3%
동구 303
 
2.2%
수성구 287
 
2.1%
서구 238
 
1.7%
남구 162
 
1.2%
중구 153
 
1.1%
Other values (2667) 8260
60.0%
2023-12-11T02:53:31.098690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11309
 
16.6%
4821
 
7.1%
1 3091
 
4.5%
2961
 
4.3%
2960
 
4.3%
2557
 
3.7%
2472
 
3.6%
2453
 
3.6%
( 2254
 
3.3%
) 2254
 
3.3%
Other values (314) 31191
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39066
57.2%
Space Separator 11309
 
16.6%
Decimal Number 11119
 
16.3%
Open Punctuation 2254
 
3.3%
Close Punctuation 2254
 
3.3%
Other Punctuation 1369
 
2.0%
Dash Punctuation 777
 
1.1%
Uppercase Letter 146
 
0.2%
Math Symbol 27
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4821
 
12.3%
2961
 
7.6%
2960
 
7.6%
2557
 
6.5%
2472
 
6.3%
2453
 
6.3%
2246
 
5.7%
1704
 
4.4%
1047
 
2.7%
1043
 
2.7%
Other values (282) 14802
37.9%
Uppercase Letter
ValueCountFrequency (%)
B 62
42.5%
A 54
37.0%
C 12
 
8.2%
T 4
 
2.7%
E 3
 
2.1%
D 3
 
2.1%
J 2
 
1.4%
P 2
 
1.4%
G 1
 
0.7%
M 1
 
0.7%
Other values (2) 2
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 3091
27.8%
2 1659
14.9%
3 1299
11.7%
4 930
 
8.4%
5 877
 
7.9%
6 791
 
7.1%
0 714
 
6.4%
7 691
 
6.2%
8 579
 
5.2%
9 488
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 1361
99.4%
· 4
 
0.3%
. 4
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
11309
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2254
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2254
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 777
100.0%
Math Symbol
ValueCountFrequency (%)
~ 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39066
57.2%
Common 29109
42.6%
Latin 148
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4821
 
12.3%
2961
 
7.6%
2960
 
7.6%
2557
 
6.5%
2472
 
6.3%
2453
 
6.3%
2246
 
5.7%
1704
 
4.4%
1047
 
2.7%
1043
 
2.7%
Other values (282) 14802
37.9%
Common
ValueCountFrequency (%)
11309
38.9%
1 3091
 
10.6%
( 2254
 
7.7%
) 2254
 
7.7%
2 1659
 
5.7%
, 1361
 
4.7%
3 1299
 
4.5%
4 930
 
3.2%
5 877
 
3.0%
6 791
 
2.7%
Other values (8) 3284
 
11.3%
Latin
ValueCountFrequency (%)
B 62
41.9%
A 54
36.5%
C 12
 
8.1%
T 4
 
2.7%
E 3
 
2.0%
D 3
 
2.0%
J 2
 
1.4%
P 2
 
1.4%
e 1
 
0.7%
G 1
 
0.7%
Other values (4) 4
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39066
57.2%
ASCII 29253
42.8%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11309
38.7%
1 3091
 
10.6%
( 2254
 
7.7%
) 2254
 
7.7%
2 1659
 
5.7%
, 1361
 
4.7%
3 1299
 
4.4%
4 930
 
3.2%
5 877
 
3.0%
6 791
 
2.7%
Other values (21) 3428
 
11.7%
Hangul
ValueCountFrequency (%)
4821
 
12.3%
2961
 
7.6%
2960
 
7.6%
2557
 
6.5%
2472
 
6.3%
2453
 
6.3%
2246
 
5.7%
1704
 
4.4%
1047
 
2.7%
1043
 
2.7%
Other values (282) 14802
37.9%
None
ValueCountFrequency (%)
· 4
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct822
Distinct (%)33.9%
Missing1398
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean42015.47
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:31.455051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41109
Q141489.75
median41933
Q342664
95-th percentile42972
Maximum43024
Range2024
Interquartile range (IQR)1174.25

Descriptive statistics

Standard deviation616.66136
Coefficient of variation (CV)0.014677007
Kurtosis-1.3014004
Mean42015.47
Median Absolute Deviation (MAD)492
Skewness0.16596825
Sum1.018455 × 108
Variance380271.23
MonotonicityNot monotonic
2023-12-11T02:53:32.244312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41485 45
 
1.2%
41582 43
 
1.1%
41490 37
 
1.0%
41557 25
 
0.7%
41488 23
 
0.6%
41755 20
 
0.5%
42975 18
 
0.5%
42703 18
 
0.5%
42970 18
 
0.5%
41123 16
 
0.4%
Other values (812) 2161
56.5%
(Missing) 1398
36.6%
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%
Distinct3233
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
2023-12-11T02:53:32.741235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length5.9238619
Min length1

Characters and Unicode

Total characters22641
Distinct characters772
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

Unique2818 ?
Unique (%)73.7%

Sample

1st row원숭이식품
2nd row동북상회
3rd row황실떡집
4th row에프엔에스
5th row이유통
ValueCountFrequency (%)
주식회사 107
 
2.5%
농업회사법인 15
 
0.3%
우리식품 14
 
0.3%
커피 14
 
0.3%
14
 
0.3%
푸드 12
 
0.3%
coffee 11
 
0.3%
제일식품 11
 
0.3%
현대식품 9
 
0.2%
food 9
 
0.2%
Other values (3417) 4071
95.0%
2023-12-11T02:53:33.618447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1264
 
5.6%
1096
 
4.8%
655
 
2.9%
) 614
 
2.7%
( 607
 
2.7%
482
 
2.1%
467
 
2.1%
452
 
2.0%
421
 
1.9%
371
 
1.6%
Other values (762) 16212
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19868
87.8%
Close Punctuation 614
 
2.7%
Open Punctuation 607
 
2.7%
Uppercase Letter 519
 
2.3%
Space Separator 467
 
2.1%
Lowercase Letter 442
 
2.0%
Decimal Number 61
 
0.3%
Other Punctuation 60
 
0.3%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1264
 
6.4%
1096
 
5.5%
655
 
3.3%
482
 
2.4%
452
 
2.3%
421
 
2.1%
371
 
1.9%
339
 
1.7%
307
 
1.5%
303
 
1.5%
Other values (695) 14178
71.4%
Uppercase Letter
ValueCountFrequency (%)
F 53
 
10.2%
O 46
 
8.9%
S 41
 
7.9%
C 40
 
7.7%
B 36
 
6.9%
N 28
 
5.4%
T 27
 
5.2%
E 25
 
4.8%
D 25
 
4.8%
M 24
 
4.6%
Other values (14) 174
33.5%
Lowercase Letter
ValueCountFrequency (%)
e 81
18.3%
o 64
14.5%
f 36
 
8.1%
n 35
 
7.9%
a 31
 
7.0%
s 23
 
5.2%
c 23
 
5.2%
r 22
 
5.0%
t 20
 
4.5%
d 17
 
3.8%
Other values (13) 90
20.4%
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%
8 3
 
4.9%
0 3
 
4.9%
7 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
& 36
60.0%
. 15
25.0%
' 4
 
6.7%
, 3
 
5.0%
· 2
 
3.3%
Close Punctuation
ValueCountFrequency (%)
) 614
100.0%
Open Punctuation
ValueCountFrequency (%)
( 607
100.0%
Space Separator
ValueCountFrequency (%)
467
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19863
87.7%
Common 1812
 
8.0%
Latin 961
 
4.2%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1264
 
6.4%
1096
 
5.5%
655
 
3.3%
482
 
2.4%
452
 
2.3%
421
 
2.1%
371
 
1.9%
339
 
1.7%
307
 
1.5%
303
 
1.5%
Other values (690) 14173
71.4%
Latin
ValueCountFrequency (%)
e 81
 
8.4%
o 64
 
6.7%
F 53
 
5.5%
O 46
 
4.8%
S 41
 
4.3%
C 40
 
4.2%
B 36
 
3.7%
f 36
 
3.7%
n 35
 
3.6%
a 31
 
3.2%
Other values (37) 498
51.8%
Common
ValueCountFrequency (%)
) 614
33.9%
( 607
33.5%
467
25.8%
& 36
 
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 (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19863
87.7%
ASCII 2771
 
12.2%
CJK 5
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1264
 
6.4%
1096
 
5.5%
655
 
3.3%
482
 
2.4%
452
 
2.3%
421
 
2.1%
371
 
1.9%
339
 
1.7%
307
 
1.5%
303
 
1.5%
Other values (690) 14173
71.4%
ASCII
ValueCountFrequency (%)
) 614
22.2%
( 607
21.9%
467
16.9%
e 81
 
2.9%
o 64
 
2.3%
F 53
 
1.9%
O 46
 
1.7%
S 41
 
1.5%
C 40
 
1.4%
B 36
 
1.3%
Other values (56) 722
26.1%
None
ValueCountFrequency (%)
· 2
100.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

최종수정시점
Real number (ℝ)

Distinct3416
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0134101 × 1013
Minimum2.001082 × 1013
Maximum2.0221231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:33.988458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001082 × 1013
5-th percentile2.0020723 × 1013
Q12.0071108 × 1013
median2.0160111 × 1013
Q32.0200121 × 1013
95-th percentile2.0220726 × 1013
Maximum2.0221231 × 1013
Range2.1041112 × 1011
Interquartile range (IQR)1.2901277 × 1011

Descriptive statistics

Standard deviation6.8542986 × 1010
Coefficient of variation (CV)0.0034043232
Kurtosis-1.3162792
Mean2.0134101 × 1013
Median Absolute Deviation (MAD)5.0998996 × 1010
Skewness-0.33123465
Sum7.6952533 × 1016
Variance4.698141 × 1021
MonotonicityNot monotonic
2023-12-11T02:53:34.315874image/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
 
0.5%
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 (3406) 3623
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 (%)
20221231120845 1
< 0.1%
20221230154248 1
< 0.1%
20221230092647 1
< 0.1%
20221230090954 1
< 0.1%
20221229162209 1
< 0.1%
20221229143812 1
< 0.1%
20221229141503 1
< 0.1%
20221229134420 1
< 0.1%
20221229113020 1
< 0.1%
20221228161131 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
I
2668 
U
1154 

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 2668
69.8%
U 1154
30.2%

Length

2023-12-11T02:53:34.662250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:35.003409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2668
69.8%
u 1154
30.2%
Distinct806
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-01-02 02:40:00
2023-12-11T02:53:35.494544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:53:36.162378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
식품제조가공업
2796 
기타 식품제조가공업
997 
도시락제조업
 
29

Length

Max length10
Median length7
Mean length7.7749869
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2796
73.2%
기타 식품제조가공업 997
 
26.1%
도시락제조업 29
 
0.8%

Length

2023-12-11T02:53:36.663041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:37.295983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3793
78.7%
기타 997
 
20.7%
도시락제조업 29
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3084
Distinct (%)85.4%
Missing212
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean341828.04
Minimum323038.14
Maximum356965.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:37.836651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum323038.14
5-th percentile331647.03
Q1338718.4
median341518.3
Q3345484.22
95-th percentile352830.33
Maximum356965.56
Range33927.418
Interquartile range (IQR)6765.8272

Descriptive statistics

Standard deviation5839.3607
Coefficient of variation (CV)0.017082743
Kurtosis0.095273211
Mean341828.04
Median Absolute Deviation (MAD)3348.74
Skewness-0.0044951465
Sum1.2339992 × 109
Variance34098133
MonotonicityNot monotonic
2023-12-11T02:53:38.169070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
339243.983122111 27
 
0.7%
336661.678721891 9
 
0.2%
334406.500395956 7
 
0.2%
348434.155717765 5
 
0.1%
346004.036082066 5
 
0.1%
334946.049344089 4
 
0.1%
332327.523656941 4
 
0.1%
326739.522357072 4
 
0.1%
344858.271846812 4
 
0.1%
343260.899952683 4
 
0.1%
Other values (3074) 3537
92.5%
(Missing) 212
 
5.5%
ValueCountFrequency (%)
323038.137301829 1
 
< 0.1%
323583.427786547 1
 
< 0.1%
325649.192591441 1
 
< 0.1%
325694.253396024 1
 
< 0.1%
326018.881016045 1
 
< 0.1%
326032.481594907 1
 
< 0.1%
326631.950344976 1
 
< 0.1%
326739.522357072 4
0.1%
326760.851184406 1
 
< 0.1%
326950.230818611 1
 
< 0.1%
ValueCountFrequency (%)
356965.555232748 1
 
< 0.1%
356410.892344199 1
 
< 0.1%
356388.525061719 1
 
< 0.1%
356370.038499315 1
 
< 0.1%
356353.915440362 1
 
< 0.1%
356351.617490545 1
 
< 0.1%
356349.757069022 3
0.1%
356345.316761317 1
 
< 0.1%
356335.999166053 1
 
< 0.1%
356331.11092277 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3084
Distinct (%)85.4%
Missing212
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean263395.18
Minimum236164.39
Maximum278073.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:38.514513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum236164.39
5-th percentile253719.94
Q1261087.49
median264013
Q3266501.66
95-th percentile271954.6
Maximum278073.62
Range41909.231
Interquartile range (IQR)5414.1647

Descriptive statistics

Standard deviation5428.5496
Coefficient of variation (CV)0.020609905
Kurtosis3.2990947
Mean263395.18
Median Absolute Deviation (MAD)2725.4875
Skewness-1.1190942
Sum9.508566 × 108
Variance29469151
MonotonicityNot monotonic
2023-12-11T02:53:38.868384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
268026.454530584 27
 
0.7%
261224.266018286 9
 
0.2%
260208.389649832 7
 
0.2%
264017.165938686 5
 
0.1%
269131.730019622 5
 
0.1%
259655.384837927 4
 
0.1%
250014.011621729 4
 
0.1%
242019.624631518 4
 
0.1%
265012.333200178 4
 
0.1%
267937.999113354 4
 
0.1%
Other values (3074) 3537
92.5%
(Missing) 212
 
5.5%
ValueCountFrequency (%)
236164.392417907 1
< 0.1%
237999.437164484 1
< 0.1%
238531.354079775 1
< 0.1%
238772.106217885 1
< 0.1%
238772.407350058 1
< 0.1%
238824.505920574 1
< 0.1%
238893.362765047 1
< 0.1%
238893.829911915 1
< 0.1%
239059.112587617 1
< 0.1%
239098.142264127 1
< 0.1%
ValueCountFrequency (%)
278073.623285671 1
< 0.1%
278032.753892201 1
< 0.1%
277860.926383971 1
< 0.1%
277755.206407657 2
0.1%
277749.024028649 1
< 0.1%
277673.246367512 1
< 0.1%
277500.515376485 1
< 0.1%
277489.106534381 1
< 0.1%
277348.717165567 1
< 0.1%
277022.824656934 1
< 0.1%

위생업태명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
식품제조가공업
2796 
기타 식품제조가공업
997 
도시락제조업
 
29

Length

Max length10
Median length7
Mean length7.7749869
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2796
73.2%
기타 식품제조가공업 997
 
26.1%
도시락제조업 29
 
0.8%

Length

2023-12-11T02:53:39.201807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:39.534571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3793
78.7%
기타 997
 
20.7%
도시락제조업 29
 
0.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
<NA>
3265 
0
557 

Length

Max length4
Median length4
Mean length3.5627943
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> 3265
85.4%
0 557
 
14.6%

Length

2023-12-11T02:53:39.969271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:40.294435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3265
85.4%
0 557
 
14.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
<NA>
3265 
0
557 

Length

Max length4
Median length4
Mean length3.5627943
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> 3265
85.4%
0 557
 
14.6%

Length

2023-12-11T02:53:40.660862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:40.961927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3265
85.4%
0 557
 
14.6%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3822
Missing (%)100.0%
Memory size33.7 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3822
Missing (%)100.0%
Memory size33.7 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
상수도전용
2226 
<NA>
1575 
지하수전용
 
16
간이상수도
 
3
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length5
Mean length4.5941915
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2226
58.2%
<NA> 1575
41.2%
지하수전용 16
 
0.4%
간이상수도 3
 
0.1%
상수도(음용)지하수(주방용)겸용 2
 
0.1%

Length

2023-12-11T02:53:41.341746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:41.644144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2226
58.2%
na 1575
41.2%
지하수전용 16
 
0.4%
간이상수도 3
 
0.1%
상수도(음용)지하수(주방용)겸용 2
 
0.1%

총직원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
<NA>
3279 
0
543 

Length

Max length4
Median length4
Mean length3.5737834
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> 3279
85.8%
0 543
 
14.2%

Length

2023-12-11T02:53:42.044775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:42.373374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3279
85.8%
0 543
 
14.2%

본사직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.3%
Missing610
Missing (%)16.0%
Infinite0
Infinite (%)0.0%
Mean0.068181818
Minimum0
Maximum12
Zeros3085
Zeros (%)80.7%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:42.669805image/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 deviation0.44994487
Coefficient of variation (CV)6.5991914
Kurtosis214.87981
Mean0.068181818
Median Absolute Deviation (MAD)0
Skewness12.011155
Sum219
Variance0.20245038
MonotonicityNot monotonic
2023-12-11T02:53:43.005508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3085
80.7%
1 88
 
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) 610
 
16.0%
ValueCountFrequency (%)
0 3085
80.7%
1 88
 
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 88
 
2.3%
0 3085
80.7%

공장사무직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct11
Distinct (%)0.3%
Missing598
Missing (%)15.6%
Infinite0
Infinite (%)0.0%
Mean0.20316377
Minimum0
Maximum40
Zeros2821
Zeros (%)73.8%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:43.345894image/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 deviation1.014008
Coefficient of variation (CV)4.9910865
Kurtosis775.34344
Mean0.20316377
Median Absolute Deviation (MAD)0
Skewness22.388396
Sum655
Variance1.0282121
MonotonicityNot monotonic
2023-12-11T02:53:43.718526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 2821
73.8%
1 302
 
7.9%
2 59
 
1.5%
3 21
 
0.5%
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) 598
 
15.6%
ValueCountFrequency (%)
0 2821
73.8%
1 302
 
7.9%
2 59
 
1.5%
3 21
 
0.5%
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
 
0.5%
2 59
 
1.5%
1 302
7.9%

공장판매직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.3%
Missing616
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean0.10106051
Minimum0
Maximum30
Zeros2990
Zeros (%)78.2%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:44.058346image/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 deviation0.67753255
Coefficient of variation (CV)6.7042264
Kurtosis1204.0462
Mean0.10106051
Median Absolute Deviation (MAD)0
Skewness29.024862
Sum324
Variance0.45905036
MonotonicityNot monotonic
2023-12-11T02:53:44.371376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 2990
78.2%
1 166
 
4.3%
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) 616
 
16.1%
ValueCountFrequency (%)
0 2990
78.2%
1 166
 
4.3%
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
 
4.3%
0 2990
78.2%

공장생산직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct27
Distinct (%)0.8%
Missing528
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean0.80904675
Minimum0
Maximum220
Zeros2368
Zeros (%)62.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:44.673423image/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 deviation4.6303666
Coefficient of variation (CV)5.7232373
Kurtosis1562.5922
Mean0.80904675
Median Absolute Deviation (MAD)0
Skewness34.946181
Sum2665
Variance21.440295
MonotonicityNot monotonic
2023-12-11T02:53:45.011452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 2368
62.0%
1 460
 
12.0%
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) 528
 
13.8%
ValueCountFrequency (%)
0 2368
62.0%
1 460
 
12.0%
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%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
<NA>
1838 
임대
1158 
자가
826 

Length

Max length4
Median length2
Mean length2.9618001
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1838
48.1%
임대 1158
30.3%
자가 826
21.6%

Length

2023-12-11T02:53:45.382279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:45.701338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1838
48.1%
임대 1158
30.3%
자가 826
21.6%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)2.5%
Missing3089
Missing (%)80.8%
Infinite0
Infinite (%)0.0%
Mean845705.05
Minimum0
Maximum50000000
Zeros669
Zeros (%)17.5%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:45.978737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation4005180.4
Coefficient of variation (CV)4.7359069
Kurtosis81.954204
Mean845705.05
Median Absolute Deviation (MAD)0
Skewness8.0964094
Sum6.199018 × 108
Variance1.604147 × 1013
MonotonicityNot monotonic
2023-12-11T02:53:46.399772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 669
 
17.5%
10000000 24
 
0.6%
5000000 19
 
0.5%
3000000 3
 
0.1%
8000000 2
 
0.1%
30000000 2
 
0.1%
50000000 2
 
0.1%
2000000 2
 
0.1%
6000000 1
 
< 0.1%
18000000 1
 
< 0.1%
Other values (8) 8
 
0.2%
(Missing) 3089
80.8%
ValueCountFrequency (%)
0 669
17.5%
300 1
 
< 0.1%
500 1
 
< 0.1%
1000 1
 
< 0.1%
500000 1
 
< 0.1%
2000000 2
 
0.1%
3000000 3
 
0.1%
4400000 1
 
< 0.1%
5000000 19
 
0.5%
6000000 1
 
< 0.1%
ValueCountFrequency (%)
50000000 2
 
0.1%
40000000 1
 
< 0.1%
30000000 2
 
0.1%
20000000 1
 
< 0.1%
18000000 1
 
< 0.1%
10000000 24
0.6%
8000000 2
 
0.1%
7000000 1
 
< 0.1%
6000000 1
 
< 0.1%
5000000 19
0.5%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)3.6%
Missing3090
Missing (%)80.8%
Infinite0
Infinite (%)0.0%
Mean47459.276
Minimum0
Maximum2200000
Zeros668
Zeros (%)17.5%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:46.748676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile400000
Maximum2200000
Range2200000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation196358.28
Coefficient of variation (CV)4.1374057
Kurtosis47.973606
Mean47459.276
Median Absolute Deviation (MAD)0
Skewness6.1199058
Sum34740190
Variance3.8556574 × 1010
MonotonicityNot monotonic
2023-12-11T02:53:47.064630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 668
 
17.5%
300000 13
 
0.3%
500000 11
 
0.3%
400000 5
 
0.1%
600000 4
 
0.1%
350000 3
 
0.1%
200000 3
 
0.1%
800000 3
 
0.1%
250000 2
 
0.1%
700000 2
 
0.1%
Other values (16) 18
 
0.5%
(Missing) 3090
80.8%
ValueCountFrequency (%)
0 668
17.5%
10 1
 
< 0.1%
30 1
 
< 0.1%
150 1
 
< 0.1%
150000 1
 
< 0.1%
200000 3
 
0.1%
250000 2
 
0.1%
300000 13
 
0.3%
350000 3
 
0.1%
400000 5
 
0.1%
ValueCountFrequency (%)
2200000 1
 
< 0.1%
2000000 1
 
< 0.1%
1800000 1
 
< 0.1%
1300000 1
 
< 0.1%
1200000 1
 
< 0.1%
1100000 1
 
< 0.1%
900000 1
 
< 0.1%
850000 2
0.1%
800000 3
0.1%
750000 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
False
3820 
True
 
2
ValueCountFrequency (%)
False 3820
99.9%
True 2
 
0.1%
2023-12-11T02:53:47.324667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct559
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.465769
Minimum0
Maximum4673.38
Zeros3019
Zeros (%)79.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-11T02:53:47.646761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile44.809
Maximum4673.38
Range4673.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation122.45585
Coefficient of variation (CV)9.8233693
Kurtosis1039.5782
Mean12.465769
Median Absolute Deviation (MAD)0
Skewness29.755215
Sum47644.17
Variance14995.436
MonotonicityNot monotonic
2023-12-11T02:53:47.986145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3019
79.0%
3.0 24
 
0.6%
6.0 17
 
0.4%
1.0 15
 
0.4%
2.0 12
 
0.3%
4.0 12
 
0.3%
3.3 10
 
0.3%
1.2 8
 
0.2%
4.5 8
 
0.2%
9.0 7
 
0.2%
Other values (549) 690
 
18.1%
ValueCountFrequency (%)
0.0 3019
79.0%
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 

Missing3822
Missing (%)100.0%
Memory size33.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3822
Missing (%)100.0%
Memory size33.7 KiB

홈페이지
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
<NA>
3820 
4
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.9984301
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> 3820
99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Length

2023-12-11T02:53:48.317660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:53:48.582369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3820
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>
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38123813식품제조가공업07_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>
38133814식품제조가공업07_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>
38143815식품제조가공업07_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>
38153816식품제조가공업07_22_11_P34800003480000-106-2013-0000620130808<NA>1영업/정상1영업<NA><NA><NA><NA>053 639 5887159.30711839대구광역시 달성군 화원읍 성산리 536-6대구광역시 달성군 화원읍 성천로12길 1142946선미 푸드20221122114629U2022-11-24 02:40:00.0식품제조가공업334521.009928256794.676167식품제조가공업00<NA><NA>상수도전용00000임대00N0.0<NA><NA><NA>
38163817식품제조가공업07_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>
38173818식품제조가공업07_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>
38183819식품제조가공업07_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>
38193820식품제조가공업07_22_11_P34800003480000-106-1997-0000819970924<NA>1영업/정상1영업<NA><NA><NA><NA><NA>837.90711823대구광역시 달성군 하빈면 봉촌리 1032-3대구광역시 달성군 하빈면 하빈남로 40742905연꽃마을20221122104440U2022-11-24 02:40:00.0식품제조가공업325649.192591263403.704757식품제조가공업00<NA><NA>상수도전용00102<NA>00N0.0<NA><NA><NA>
38203821식품제조가공업07_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 23:59:59.0식품제조가공업329261.634904254746.592244식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0103<NA><NA><NA>N0.0<NA><NA><NA>
38213822식품제조가공업07_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>