Overview

Dataset statistics

Number of variables33
Number of observations467
Missing cells3373
Missing cells (%)21.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory129.2 KiB
Average record size in memory283.3 B

Variable types

Numeric13
Categorical12
Unsupported3
Text4
DateTime1

Dataset

Description6270000_대구광역시_07_22_05_P_축산가공업_5월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000085190&dataSetDetailId=DDI_0000085214&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
축산업무구분명 has constant value ""Constant
개방자치단체코드 is highly imbalanced (83.6%)Imbalance
상세영업상태코드 is highly imbalanced (50.7%)Imbalance
상세영업상태명 is highly imbalanced (50.7%)Imbalance
업태구분명 is highly imbalanced (77.7%)Imbalance
축산물가공업구분명 is highly imbalanced (77.7%)Imbalance
인허가취소일자 has 467 (100.0%) missing valuesMissing
폐업일자 has 300 (64.2%) missing valuesMissing
휴업시작일자 has 458 (98.1%) missing valuesMissing
휴업종료일자 has 459 (98.3%) missing valuesMissing
재개업일자 has 467 (100.0%) missing valuesMissing
소재지전화 has 151 (32.3%) missing valuesMissing
소재지면적 has 32 (6.9%) missing valuesMissing
소재지우편번호 has 319 (68.3%) missing valuesMissing
도로명전체주소 has 18 (3.9%) missing valuesMissing
도로명우편번호 has 161 (34.5%) missing valuesMissing
좌표정보(X) has 25 (5.4%) missing valuesMissing
좌표정보(Y) has 25 (5.4%) missing valuesMissing
축산일련번호 has 467 (100.0%) missing valuesMissing
총종업원수 has 24 (5.1%) missing valuesMissing
소재지면적 is highly skewed (γ1 = 20.01019543)Skewed
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 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
축산일련번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 163 (34.9%) zerosZeros
총종업원수 has 357 (76.4%) zerosZeros

Reproduction

Analysis started2023-12-10 19:23:10.876889
Analysis finished2023-12-10 19:23:11.743698
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct467
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean234
Minimum1
Maximum467
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:11.834049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24.3
Q1117.5
median234
Q3350.5
95-th percentile443.7
Maximum467
Range466
Interquartile range (IQR)233

Descriptive statistics

Standard deviation134.95555
Coefficient of variation (CV)0.57673311
Kurtosis-1.2
Mean234
Median Absolute Deviation (MAD)117
Skewness0
Sum109278
Variance18213
MonotonicityStrictly increasing
2023-12-11T04:23:12.040182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
309 1
 
0.2%
321 1
 
0.2%
320 1
 
0.2%
319 1
 
0.2%
318 1
 
0.2%
317 1
 
0.2%
316 1
 
0.2%
315 1
 
0.2%
314 1
 
0.2%
Other values (457) 457
97.9%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
467 1
0.2%
466 1
0.2%
465 1
0.2%
464 1
0.2%
463 1
0.2%
462 1
0.2%
461 1
0.2%
460 1
0.2%
459 1
0.2%
458 1
0.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
축산가공업
467 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산가공업 467
100.0%

Length

2023-12-11T04:23:12.230237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:12.352518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산가공업 467
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
07_22_05_P
467 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_05_P
2nd row07_22_05_P
3rd row07_22_05_P
4th row07_22_05_P
5th row07_22_05_P

Common Values

ValueCountFrequency (%)
07_22_05_P 467
100.0%

Length

2023-12-11T04:23:12.498172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:12.643766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_05_p 467
100.0%

개방자치단체코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
6270000
443 
3480000
 
10
3420000
 
8
3460000
 
5
3470000
 
1

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row3420000
2nd row3420000
3rd row3420000
4th row3420000
5th row3420000

Common Values

ValueCountFrequency (%)
6270000 443
94.9%
3480000 10
 
2.1%
3420000 8
 
1.7%
3460000 5
 
1.1%
3470000 1
 
0.2%

Length

2023-12-11T04:23:12.768080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:12.888340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6270000 443
94.9%
3480000 10
 
2.1%
3420000 8
 
1.7%
3460000 5
 
1.1%
3470000 1
 
0.2%

관리번호
Real number (ℝ)

UNIQUE 

Distinct467
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1253533 × 1017
Minimum3.42 × 1017
Maximum6.27 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:13.077140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.42 × 1017
5-th percentile4.317 × 1017
Q16.27 × 1017
median6.27 × 1017
Q36.27 × 1017
95-th percentile6.27 × 1017
Maximum6.27 × 1017
Range2.85 × 1017
Interquartile range (IQR)80000

Descriptive statistics

Standard deviation6.221426 × 1016
Coefficient of variation (CV)0.10156844
Kurtosis14.689044
Mean6.1253533 × 1017
Median Absolute Deviation (MAD)39936
Skewness-4.0772859
Sum-9.093905 × 1018
Variance3.8706141 × 1033
MonotonicityNot monotonic
2023-12-11T04:23:13.265818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
342000000419990001 1
 
0.2%
627000000420180002 1
 
0.2%
627000000420160017 1
 
0.2%
627000000420160019 1
 
0.2%
627000000420160021 1
 
0.2%
627000000420150017 1
 
0.2%
627000000420150019 1
 
0.2%
627000000420150022 1
 
0.2%
627000000420150023 1
 
0.2%
627000000420150005 1
 
0.2%
Other values (457) 457
97.9%
ValueCountFrequency (%)
342000000419990001 1
0.2%
342000000420000003 1
0.2%
342000000420000004 1
0.2%
342000000420020001 1
0.2%
342000000420020002 1
0.2%
342000000420030002 1
0.2%
342000000420030003 1
0.2%
342000000420030004 1
0.2%
346000000419980001 1
0.2%
346000000420000001 1
0.2%
ValueCountFrequency (%)
627000000420200014 1
0.2%
627000000420200013 1
0.2%
627000000420200012 1
0.2%
627000000420200011 1
0.2%
627000000420200010 1
0.2%
627000000420200009 1
0.2%
627000000420200008 1
0.2%
627000000420200007 1
0.2%
627000000420200006 1
0.2%
627000000420200005 1
0.2%

인허가일자
Real number (ℝ)

Distinct364
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20111595
Minimum19850629
Maximum20200514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:13.459817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19850629
5-th percentile19980416
Q120080215
median20130709
Q320151062
95-th percentile20190608
Maximum20200514
Range349885
Interquartile range (IQR)70847.5

Descriptive statistics

Standard deviation62573.171
Coefficient of variation (CV)0.0031112983
Kurtosis0.814969
Mean20111595
Median Absolute Deviation (MAD)30190
Skewness-1.0461243
Sum9.392115 × 109
Variance3.9154017 × 109
MonotonicityNot monotonic
2023-12-11T04:23:13.712716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131029 12
 
2.6%
20131101 9
 
1.9%
20170117 5
 
1.1%
20140129 4
 
0.9%
20131030 4
 
0.9%
20131012 3
 
0.6%
20130522 3
 
0.6%
20140422 3
 
0.6%
20131212 3
 
0.6%
20120814 3
 
0.6%
Other values (354) 418
89.5%
ValueCountFrequency (%)
19850629 1
0.2%
19900524 1
0.2%
19920525 1
0.2%
19930120 2
0.4%
19940404 1
0.2%
19950420 1
0.2%
19950629 1
0.2%
19950907 1
0.2%
19960307 1
0.2%
19960414 1
0.2%
ValueCountFrequency (%)
20200514 1
0.2%
20200508 2
0.4%
20200506 1
0.2%
20200406 1
0.2%
20200403 1
0.2%
20200327 1
0.2%
20200310 1
0.2%
20200305 1
0.2%
20200227 1
0.2%
20200212 1
0.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

영업상태구분코드
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
1
295 
3
157 
4
 
11
2
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 295
63.2%
3 157
33.6%
4 11
 
2.4%
2 4
 
0.9%

Length

2023-12-11T04:23:13.915054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:14.046147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 295
63.2%
3 157
33.6%
4 11
 
2.4%
2 4
 
0.9%

영업상태명
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
영업/정상
295 
폐업
157 
취소/말소/만료/정지/중지
 
11
휴업
 
4

Length

Max length14
Median length5
Mean length4.1777302
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 295
63.2%
폐업 157
33.6%
취소/말소/만료/정지/중지 11
 
2.4%
휴업 4
 
0.9%

Length

2023-12-11T04:23:14.226567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:14.386754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 295
63.2%
폐업 157
33.6%
취소/말소/만료/정지/중지 11
 
2.4%
휴업 4
 
0.9%

상세영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
295 
2
157 
4
 
10
1
 
4
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 295
63.2%
2 157
33.6%
4 10
 
2.1%
1 4
 
0.9%
3 1
 
0.2%

Length

2023-12-11T04:23:14.578157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:14.772607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 295
63.2%
2 157
33.6%
4 10
 
2.1%
1 4
 
0.9%
3 1
 
0.2%

상세영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
정상
295 
폐업
157 
말소
 
10
휴업
 
4
인허가취소
 
1

Length

Max length5
Median length2
Mean length2.006424
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
정상 295
63.2%
폐업 157
33.6%
말소 10
 
2.1%
휴업 4
 
0.9%
인허가취소 1
 
0.2%

Length

2023-12-11T04:23:14.956174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:15.139435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 295
63.2%
폐업 157
33.6%
말소 10
 
2.1%
휴업 4
 
0.9%
인허가취소 1
 
0.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct132
Distinct (%)79.0%
Missing300
Missing (%)64.2%
Infinite0
Infinite (%)0.0%
Mean20147671
Minimum20000118
Maximum20200513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:15.368291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000118
5-th percentile20040804
Q120125918
median20161121
Q320190414
95-th percentile20191220
Maximum20200513
Range200395
Interquartile range (IQR)64496.5

Descriptive statistics

Standard deviation52150.767
Coefficient of variation (CV)0.0025884265
Kurtosis0.61392638
Mean20147671
Median Absolute Deviation (MAD)29388
Skewness-1.2604654
Sum3.3646611 × 109
Variance2.7197025 × 109
MonotonicityNot monotonic
2023-12-11T04:23:15.644364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190801 10
 
2.1%
20141231 4
 
0.9%
20190529 3
 
0.6%
20190729 3
 
0.6%
20040804 3
 
0.6%
20000118 3
 
0.6%
20090220 2
 
0.4%
20190819 2
 
0.4%
20181220 2
 
0.4%
20191210 2
 
0.4%
Other values (122) 133
28.5%
(Missing) 300
64.2%
ValueCountFrequency (%)
20000118 3
0.6%
20000821 1
 
0.2%
20011025 1
 
0.2%
20020401 1
 
0.2%
20021126 1
 
0.2%
20040204 1
 
0.2%
20040804 3
0.6%
20041108 1
 
0.2%
20051205 2
0.4%
20060404 1
 
0.2%
ValueCountFrequency (%)
20200513 1
0.2%
20200316 1
0.2%
20200309 1
0.2%
20200306 1
0.2%
20200303 1
0.2%
20200221 1
0.2%
20200114 1
0.2%
20191224 2
0.4%
20191210 2
0.4%
20191125 1
0.2%

휴업시작일자
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)100.0%
Missing458
Missing (%)98.1%
Infinite0
Infinite (%)0.0%
Mean20152838
Minimum20020601
Maximum20190910
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:15.859686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020601
5-th percentile20072613
Q120160301
median20161214
Q320170428
95-th percentile20190746
Maximum20190910
Range170309
Interquartile range (IQR)10127

Descriptive statistics

Standard deviation51431.234
Coefficient of variation (CV)0.0025520591
Kurtosis7.2997348
Mean20152838
Median Absolute Deviation (MAD)9214
Skewness-2.5889194
Sum1.8137554 × 108
Variance2.6451718 × 109
MonotonicityNot monotonic
2023-12-11T04:23:16.520889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
20020601 1
 
0.2%
20170329 1
 
0.2%
20170428 1
 
0.2%
20160629 1
 
0.2%
20150630 1
 
0.2%
20190910 1
 
0.2%
20190501 1
 
0.2%
20161214 1
 
0.2%
20160301 1
 
0.2%
(Missing) 458
98.1%
ValueCountFrequency (%)
20020601 1
0.2%
20150630 1
0.2%
20160301 1
0.2%
20160629 1
0.2%
20161214 1
0.2%
20170329 1
0.2%
20170428 1
0.2%
20190501 1
0.2%
20190910 1
0.2%
ValueCountFrequency (%)
20190910 1
0.2%
20190501 1
0.2%
20170428 1
0.2%
20170329 1
0.2%
20161214 1
0.2%
20160629 1
0.2%
20160301 1
0.2%
20150630 1
0.2%
20020601 1
0.2%

휴업종료일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)87.5%
Missing459
Missing (%)98.3%
Infinite0
Infinite (%)0.0%
Mean20164550
Minimum20100817
Maximum20200209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:16.800630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100817
5-th percentile20121752
Q120161081
median20165726
Q320176029
95-th percentile20196997
Maximum20200209
Range99392
Interquartile range (IQR)14948

Descriptive statistics

Standard deviation29631.636
Coefficient of variation (CV)0.0014694916
Kurtosis3.3766667
Mean20164550
Median Absolute Deviation (MAD)5199
Skewness-1.4249792
Sum1.613164 × 108
Variance8.7803385 × 108
MonotonicityNot monotonic
2023-12-11T04:23:17.030821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20161231 2
 
0.4%
20171028 1
 
0.2%
20100817 1
 
0.2%
20160630 1
 
0.2%
20200209 1
 
0.2%
20191031 1
 
0.2%
20170222 1
 
0.2%
(Missing) 459
98.3%
ValueCountFrequency (%)
20100817 1
0.2%
20160630 1
0.2%
20161231 2
0.4%
20170222 1
0.2%
20171028 1
0.2%
20191031 1
0.2%
20200209 1
0.2%
ValueCountFrequency (%)
20200209 1
0.2%
20191031 1
0.2%
20171028 1
0.2%
20170222 1
0.2%
20161231 2
0.4%
20160630 1
0.2%
20100817 1
0.2%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

소재지전화
Text

MISSING 

Distinct302
Distinct (%)95.6%
Missing151
Missing (%)32.3%
Memory size3.8 KiB
2023-12-11T04:23:17.462466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.9462025
Min length8

Characters and Unicode

Total characters3143
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

Unique289 ?
Unique (%)91.5%

Sample

1st row964-0567
2nd row961-1172
3rd row964-5589
4th row941-4182
5th row982-1253
ValueCountFrequency (%)
0535259326 3
 
0.9%
0539512868 2
 
0.6%
0537460092 2
 
0.6%
0535582345 2
 
0.6%
0535921313 2
 
0.6%
0533252259 2
 
0.6%
0536349935 2
 
0.6%
0536515511 2
 
0.6%
0533811241 2
 
0.6%
0535883900 2
 
0.6%
Other values (292) 295
93.4%
2023-12-11T04:23:18.118160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 623
19.8%
3 567
18.0%
0 502
16.0%
1 240
 
7.6%
2 236
 
7.5%
6 217
 
6.9%
9 205
 
6.5%
8 205
 
6.5%
4 171
 
5.4%
7 163
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3129
99.6%
Dash Punctuation 14
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 623
19.9%
3 567
18.1%
0 502
16.0%
1 240
 
7.7%
2 236
 
7.5%
6 217
 
6.9%
9 205
 
6.6%
8 205
 
6.6%
4 171
 
5.5%
7 163
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3143
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 623
19.8%
3 567
18.0%
0 502
16.0%
1 240
 
7.6%
2 236
 
7.5%
6 217
 
6.9%
9 205
 
6.5%
8 205
 
6.5%
4 171
 
5.4%
7 163
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3143
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 623
19.8%
3 567
18.0%
0 502
16.0%
1 240
 
7.6%
2 236
 
7.5%
6 217
 
6.9%
9 205
 
6.5%
8 205
 
6.5%
4 171
 
5.4%
7 163
 
5.2%

소재지면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct258
Distinct (%)59.3%
Missing32
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean448.46825
Minimum0
Maximum96848
Zeros163
Zeros (%)34.9%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:18.409267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median87.58
Q3207.32
95-th percentile619.74
Maximum96848
Range96848
Interquartile range (IQR)207.32

Descriptive statistics

Standard deviation4700.4654
Coefficient of variation (CV)10.481155
Kurtosis410.34491
Mean448.46825
Median Absolute Deviation (MAD)87.58
Skewness20.010195
Sum195083.69
Variance22094375
MonotonicityNot monotonic
2023-12-11T04:23:18.653859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 163
34.9%
81.0 3
 
0.6%
100.0 3
 
0.6%
360.0 2
 
0.4%
195.0 2
 
0.4%
401.94 2
 
0.4%
494.0 2
 
0.4%
294.0 2
 
0.4%
76.0 2
 
0.4%
181.0 2
 
0.4%
Other values (248) 252
54.0%
(Missing) 32
 
6.9%
ValueCountFrequency (%)
0.0 163
34.9%
4.4 1
 
0.2%
18.85 1
 
0.2%
19.41 1
 
0.2%
21.5 1
 
0.2%
29.7 1
 
0.2%
40.0 1
 
0.2%
47.65 1
 
0.2%
48.18 1
 
0.2%
50.0 1
 
0.2%
ValueCountFrequency (%)
96848.0 1
0.2%
9783.99 1
0.2%
8649.25 1
0.2%
8594.92 1
0.2%
3842.0 1
0.2%
2100.0 1
0.2%
1887.68 1
0.2%
1643.0 1
0.2%
1547.56 1
0.2%
1379.0 1
0.2%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct104
Distinct (%)70.3%
Missing319
Missing (%)68.3%
Infinite0
Infinite (%)0.0%
Mean704457.68
Minimum700424
Maximum711882
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:18.881021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700424
5-th percentile701140
Q1702220
median703815.5
Q3704930.25
95-th percentile711844
Maximum711882
Range11458
Interquartile range (IQR)2710.25

Descriptive statistics

Standard deviation3307.3162
Coefficient of variation (CV)0.0046948402
Kurtosis0.84833884
Mean704457.68
Median Absolute Deviation (MAD)1210.5
Skewness1.4045235
Sum1.0425974 × 108
Variance10938341
MonotonicityNot monotonic
2023-12-11T04:23:19.132309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
703833 7
 
1.5%
703830 5
 
1.1%
704900 4
 
0.9%
701140 4
 
0.9%
702815 4
 
0.9%
702030 4
 
0.9%
702290 3
 
0.6%
702210 3
 
0.6%
701110 2
 
0.4%
711844 2
 
0.4%
Other values (94) 110
 
23.6%
(Missing) 319
68.3%
ValueCountFrequency (%)
700424 1
 
0.2%
700847 1
 
0.2%
701015 1
 
0.2%
701110 2
0.4%
701140 4
0.9%
701150 1
 
0.2%
701180 1
 
0.2%
701210 1
 
0.2%
701230 1
 
0.2%
701250 2
0.4%
ValueCountFrequency (%)
711882 1
0.2%
711874 1
0.2%
711863 1
0.2%
711858 1
0.2%
711855 2
0.4%
711851 1
0.2%
711844 2
0.4%
711843 1
0.2%
711842 2
0.4%
711841 2
0.4%

소재지전체주소
Text

Distinct306
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2023-12-11T04:23:19.584136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length17.430407
Min length1

Characters and Unicode

Total characters8140
Distinct characters146
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique285 ?
Unique (%)61.0%

Sample

1st row대구광역시 동구 동호동 109-1 번지
2nd row대구광역시 동구 신기동 118-2 번지
3rd row대구광역시 동구 용계동 878-55 번지
4th row대구광역시 동구 신암동 95-76 번지
5th row대구광역시 동구 도동 8-1 번지
ValueCountFrequency (%)
대구광역시 326
 
19.5%
북구 96
 
5.8%
달성군 65
 
3.9%
동구 55
 
3.3%
1호 44
 
2.6%
달서구 40
 
2.4%
서구 34
 
2.0%
0호 22
 
1.3%
3호 21
 
1.3%
2호 21
 
1.3%
Other values (461) 945
56.6%
2023-12-11T04:23:20.268902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2072
25.5%
구 592
 
7.3%
지 342
 
4.2%
대 340
 
4.2%
번 329
 
4.0%
시 327
 
4.0%
광 326
 
4.0%
역 326
 
4.0%
동 325
 
4.0%
1 313
 
3.8%
Other values (136) 2848
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4569
56.1%
Space Separator 2072
25.5%
Decimal Number 1471
 
18.1%
Dash Punctuation 21
 
0.3%
Uppercase Letter 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 592
13.0%
지 342
 
7.5%
대 340
 
7.4%
번 329
 
7.2%
시 327
 
7.2%
광 326
 
7.1%
역 326
 
7.1%
동 325
 
7.1%
호 269
 
5.9%
달 118
 
2.6%
Other values (118) 1275
27.9%
Decimal Number
ValueCountFrequency (%)
1 313
21.3%
2 176
12.0%
3 168
11.4%
0 150
10.2%
5 123
 
8.4%
6 119
 
8.1%
7 109
 
7.4%
4 107
 
7.3%
9 105
 
7.1%
8 101
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
/ 1
50.0%
Space Separator
ValueCountFrequency (%)
2072
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4569
56.1%
Common 3568
43.8%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 592
13.0%
지 342
 
7.5%
대 340
 
7.4%
번 329
 
7.2%
시 327
 
7.2%
광 326
 
7.1%
역 326
 
7.1%
동 325
 
7.1%
호 269
 
5.9%
달 118
 
2.6%
Other values (118) 1275
27.9%
Common
ValueCountFrequency (%)
2072
58.1%
1 313
 
8.8%
2 176
 
4.9%
3 168
 
4.7%
0 150
 
4.2%
5 123
 
3.4%
6 119
 
3.3%
7 109
 
3.1%
4 107
 
3.0%
9 105
 
2.9%
Other values (6) 126
 
3.5%
Latin
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4569
56.1%
ASCII 3571
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2072
58.0%
1 313
 
8.8%
2 176
 
4.9%
3 168
 
4.7%
0 150
 
4.2%
5 123
 
3.4%
6 119
 
3.3%
7 109
 
3.1%
4 107
 
3.0%
9 105
 
2.9%
Other values (8) 129
 
3.6%
Hangul
ValueCountFrequency (%)
구 592
13.0%
지 342
 
7.5%
대 340
 
7.4%
번 329
 
7.2%
시 327
 
7.2%
광 326
 
7.1%
역 326
 
7.1%
동 325
 
7.1%
호 269
 
5.9%
달 118
 
2.6%
Other values (118) 1275
27.9%

도로명전체주소
Text

MISSING 

Distinct410
Distinct (%)91.3%
Missing18
Missing (%)3.9%
Memory size3.8 KiB
2023-12-11T04:23:20.823214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length37
Mean length24.919822
Min length20

Characters and Unicode

Total characters11189
Distinct characters191
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique373 ?
Unique (%)83.1%

Sample

1st row대구광역시 수성구 만촌로1길 39 (만촌동)
2nd row대구광역시 달서구 용산큰못1길 60 (용산동)
3rd row대구광역시 달성군 화원읍 비슬로485길 50
4th row대구광역시 달성군 논공읍 논공로 465
5th row대구광역시 달성군 논공읍 논공중앙로 350
ValueCountFrequency (%)
대구광역시 449
 
19.7%
북구 145
 
6.4%
달성군 79
 
3.5%
달서구 66
 
2.9%
동구 57
 
2.5%
서구 56
 
2.5%
수성구 24
 
1.1%
논공읍 20
 
0.9%
노원동3가 19
 
0.8%
남구 17
 
0.7%
Other values (693) 1350
59.2%
2023-12-11T04:23:21.562901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1833
 
16.4%
구 850
 
7.6%
대 510
 
4.6%
동 478
 
4.3%
역 455
 
4.1%
시 455
 
4.1%
광 449
 
4.0%
1 405
 
3.6%
로 400
 
3.6%
) 371
 
3.3%
Other values (181) 4983
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6634
59.3%
Space Separator 1833
 
16.4%
Decimal Number 1766
 
15.8%
Close Punctuation 371
 
3.3%
Open Punctuation 371
 
3.3%
Dash Punctuation 170
 
1.5%
Other Punctuation 41
 
0.4%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 850
 
12.8%
대 510
 
7.7%
동 478
 
7.2%
역 455
 
6.9%
시 455
 
6.9%
광 449
 
6.8%
로 400
 
6.0%
길 309
 
4.7%
북 180
 
2.7%
달 179
 
2.7%
Other values (164) 2369
35.7%
Decimal Number
ValueCountFrequency (%)
1 405
22.9%
2 253
14.3%
3 220
12.5%
4 176
10.0%
6 149
 
8.4%
5 148
 
8.4%
7 133
 
7.5%
0 106
 
6.0%
9 98
 
5.5%
8 78
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
1833
100.0%
Close Punctuation
ValueCountFrequency (%)
) 371
100.0%
Open Punctuation
ValueCountFrequency (%)
( 371
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 170
100.0%
Other Punctuation
ValueCountFrequency (%)
, 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6634
59.3%
Common 4552
40.7%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 850
 
12.8%
대 510
 
7.7%
동 478
 
7.2%
역 455
 
6.9%
시 455
 
6.9%
광 449
 
6.8%
로 400
 
6.0%
길 309
 
4.7%
북 180
 
2.7%
달 179
 
2.7%
Other values (164) 2369
35.7%
Common
ValueCountFrequency (%)
1833
40.3%
1 405
 
8.9%
) 371
 
8.2%
( 371
 
8.2%
2 253
 
5.6%
3 220
 
4.8%
4 176
 
3.9%
- 170
 
3.7%
6 149
 
3.3%
5 148
 
3.3%
Other values (5) 456
 
10.0%
Latin
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6634
59.3%
ASCII 4555
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1833
40.2%
1 405
 
8.9%
) 371
 
8.1%
( 371
 
8.1%
2 253
 
5.6%
3 220
 
4.8%
4 176
 
3.9%
- 170
 
3.7%
6 149
 
3.3%
5 148
 
3.2%
Other values (7) 459
 
10.1%
Hangul
ValueCountFrequency (%)
구 850
 
12.8%
대 510
 
7.7%
동 478
 
7.2%
역 455
 
6.9%
시 455
 
6.9%
광 449
 
6.8%
로 400
 
6.0%
길 309
 
4.7%
북 180
 
2.7%
달 179
 
2.7%
Other values (164) 2369
35.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct158
Distinct (%)51.6%
Missing161
Missing (%)34.5%
Infinite0
Infinite (%)0.0%
Mean702436.9
Minimum42624
Maximum711882
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:21.790281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42624
5-th percentile701245
Q1702815.25
median703824.5
Q3704935
95-th percentile711844
Maximum711882
Range669258
Interquartile range (IQR)2119.75

Descriptive statistics

Standard deviation37969.602
Coefficient of variation (CV)0.05405411
Kurtosis301.8886
Mean702436.9
Median Absolute Deviation (MAD)1022
Skewness-17.31604
Sum2.1494569 × 108
Variance1.4416906 × 109
MonotonicityNot monotonic
2023-12-11T04:23:22.012800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
703833 13
 
2.8%
703830 12
 
2.6%
704900 8
 
1.7%
702872 7
 
1.5%
701140 7
 
1.5%
702815 7
 
1.5%
703100 6
 
1.3%
702903 6
 
1.3%
702834 5
 
1.1%
702800 5
 
1.1%
Other values (148) 230
49.3%
(Missing) 161
34.5%
ValueCountFrequency (%)
42624 1
 
0.2%
700230 1
 
0.2%
700847 2
 
0.4%
701140 7
1.5%
701150 1
 
0.2%
701180 3
0.6%
701240 1
 
0.2%
701260 4
0.9%
701340 1
 
0.2%
701808 1
 
0.2%
ValueCountFrequency (%)
711882 2
0.4%
711874 2
0.4%
711858 2
0.4%
711856 2
0.4%
711855 4
0.9%
711851 2
0.4%
711845 1
 
0.2%
711844 2
0.4%
711843 1
 
0.2%
711842 2
0.4%

사업장명
Text

Distinct443
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2023-12-11T04:23:22.444733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length6.0042827
Min length2

Characters and Unicode

Total characters2804
Distinct characters331
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique421 ?
Unique (%)90.1%

Sample

1st row(주)춘광냉동종합식품
2nd row(주)청담원
3rd row부성종합식품
4th row대구유통
5th row푸드팜
ValueCountFrequency (%)
주식회사 15
 
2.9%
농업회사법인 7
 
1.4%
주)국보푸드시스템 3
 
0.6%
세영종합식품 3
 
0.6%
주)진우식품 3
 
0.6%
영진유통 2
 
0.4%
food 2
 
0.4%
대영식품 2
 
0.4%
주)비락 2
 
0.4%
천하식품 2
 
0.4%
Other values (451) 470
92.0%
2023-12-11T04:23:23.132584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 159
 
5.7%
품 141
 
5.0%
주 140
 
5.0%
) 128
 
4.6%
푸 128
 
4.6%
( 127
 
4.5%
드 125
 
4.5%
유 46
 
1.6%
44
 
1.6%
산 44
 
1.6%
Other values (321) 1722
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2419
86.3%
Close Punctuation 128
 
4.6%
Open Punctuation 127
 
4.5%
Uppercase Letter 70
 
2.5%
Space Separator 44
 
1.6%
Other Punctuation 9
 
0.3%
Lowercase Letter 5
 
0.2%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 159
 
6.6%
품 141
 
5.8%
주 140
 
5.8%
푸 128
 
5.3%
드 125
 
5.2%
유 46
 
1.9%
산 44
 
1.8%
스 43
 
1.8%
통 43
 
1.8%
대 39
 
1.6%
Other values (291) 1511
62.5%
Uppercase Letter
ValueCountFrequency (%)
S 13
18.6%
F 8
11.4%
D 7
10.0%
J 5
 
7.1%
C 5
 
7.1%
O 4
 
5.7%
B 4
 
5.7%
G 4
 
5.7%
K 3
 
4.3%
Y 3
 
4.3%
Other values (8) 14
20.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
20.0%
f 1
20.0%
b 1
20.0%
s 1
20.0%
d 1
20.0%
Other Punctuation
ValueCountFrequency (%)
& 5
55.6%
. 4
44.4%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
8 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 128
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2419
86.3%
Common 310
 
11.1%
Latin 75
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 159
 
6.6%
품 141
 
5.8%
주 140
 
5.8%
푸 128
 
5.3%
드 125
 
5.2%
유 46
 
1.9%
산 44
 
1.8%
스 43
 
1.8%
통 43
 
1.8%
대 39
 
1.6%
Other values (291) 1511
62.5%
Latin
ValueCountFrequency (%)
S 13
17.3%
F 8
10.7%
D 7
 
9.3%
J 5
 
6.7%
C 5
 
6.7%
O 4
 
5.3%
B 4
 
5.3%
G 4
 
5.3%
K 3
 
4.0%
Y 3
 
4.0%
Other values (13) 19
25.3%
Common
ValueCountFrequency (%)
) 128
41.3%
( 127
41.0%
44
 
14.2%
& 5
 
1.6%
. 4
 
1.3%
1 1
 
0.3%
8 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2419
86.3%
ASCII 385
 
13.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 159
 
6.6%
품 141
 
5.8%
주 140
 
5.8%
푸 128
 
5.3%
드 125
 
5.2%
유 46
 
1.9%
산 44
 
1.8%
스 43
 
1.8%
통 43
 
1.8%
대 39
 
1.6%
Other values (291) 1511
62.5%
ASCII
ValueCountFrequency (%)
) 128
33.2%
( 127
33.0%
44
 
11.4%
S 13
 
3.4%
F 8
 
2.1%
D 7
 
1.8%
J 5
 
1.3%
C 5
 
1.3%
& 5
 
1.3%
O 4
 
1.0%
Other values (20) 39
 
10.1%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct467
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0167489 × 1013
Minimum2.0040308 × 1013
Maximum2.0200519 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:23.390197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0040308 × 1013
5-th percentile2.007043 × 1013
Q12.0160108 × 1013
median2.0180626 × 1013
Q32.0190827 × 1013
95-th percentile2.0200409 × 1013
Maximum2.0200519 × 1013
Range1.6021098 × 1011
Interquartile range (IQR)3.071856 × 1010

Descriptive statistics

Standard deviation3.8945006 × 1010
Coefficient of variation (CV)0.0019310786
Kurtosis2.7952461
Mean2.0167489 × 1013
Median Absolute Deviation (MAD)1.9516029 × 1010
Skewness-1.8411083
Sum9.4182175 × 1015
Variance1.5167135 × 1021
MonotonicityNot monotonic
2023-12-11T04:23:23.647160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040308131215 1
 
0.2%
20190710153542 1
 
0.2%
20190530141238 1
 
0.2%
20191107095529 1
 
0.2%
20190131180342 1
 
0.2%
20200519112759 1
 
0.2%
20151111192610 1
 
0.2%
20171010165034 1
 
0.2%
20160826102117 1
 
0.2%
20200108111703 1
 
0.2%
Other values (457) 457
97.9%
ValueCountFrequency (%)
20040308131215 1
0.2%
20040308145200 1
0.2%
20040308151033 1
0.2%
20040308153014 1
0.2%
20040308153520 1
0.2%
20040308154639 1
0.2%
20040309103412 1
0.2%
20040309113517 1
0.2%
20040319085420 1
0.2%
20040319085800 1
0.2%
ValueCountFrequency (%)
20200519112759 1
0.2%
20200515105931 1
0.2%
20200514181203 1
0.2%
20200513174642 1
0.2%
20200513174529 1
0.2%
20200508171849 1
0.2%
20200508171549 1
0.2%
20200506181351 1
0.2%
20200413180210 1
0.2%
20200410104354 1
0.2%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
I
272 
U
195 

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 272
58.2%
U 195
41.8%

Length

2023-12-11T04:23:23.896528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:24.045622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 272
58.2%
u 195
41.8%

데이터갱신일자
Date

Distinct134
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2018-08-31 23:59:59
Maximum2020-05-21 02:40:00
2023-12-11T04:23:24.227119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:23:24.473481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
식육가공업
442 
유가공업
 
14
알가공업
 
11

Length

Max length5
Median length5
Mean length4.9464668
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유가공업
2nd row식육가공업
3rd row식육가공업
4th row알가공업
5th row식육가공업

Common Values

ValueCountFrequency (%)
식육가공업 442
94.6%
유가공업 14
 
3.0%
알가공업 11
 
2.4%

Length

2023-12-11T04:23:24.725496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:24.890712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 442
94.6%
유가공업 14
 
3.0%
알가공업 11
 
2.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct398
Distinct (%)90.0%
Missing25
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean341179.54
Minimum326163.25
Maximum358511.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:25.079748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326163.25
5-th percentile331761.13
Q1337899.06
median340384.61
Q3344889.81
95-th percentile353135.55
Maximum358511.63
Range32348.377
Interquartile range (IQR)6990.7549

Descriptive statistics

Standard deviation6129.5525
Coefficient of variation (CV)0.017965768
Kurtosis-0.053301388
Mean341179.54
Median Absolute Deviation (MAD)3721.3903
Skewness0.33088248
Sum1.5080136 × 108
Variance37571413
MonotonicityNot monotonic
2023-12-11T04:23:25.326074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
338448.856663 3
 
0.6%
345549.639709 3
 
0.6%
334163.630785 2
 
0.4%
330107.385344 2
 
0.4%
337298.590887 2
 
0.4%
331541.808475 2
 
0.4%
335732.871134 2
 
0.4%
339114.603003 2
 
0.4%
341328.663367 2
 
0.4%
340465.502743 2
 
0.4%
Other values (388) 420
89.9%
(Missing) 25
 
5.4%
ValueCountFrequency (%)
326163.253025 1
0.2%
327486.570258 2
0.4%
328237.006988 1
0.2%
328396.070219 1
0.2%
329081.425721 1
0.2%
329147.0 1
0.2%
329261.678079 1
0.2%
329302.725714 1
0.2%
329618.609425 1
0.2%
329727.557829 1
0.2%
ValueCountFrequency (%)
358511.630306 1
0.2%
356477.570168 1
0.2%
356472.230525 1
0.2%
355759.73219 1
0.2%
355254.243982 1
0.2%
355064.679345 1
0.2%
354955.161771 1
0.2%
354561.486965 1
0.2%
353944.492709 1
0.2%
353919.977793 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct398
Distinct (%)90.0%
Missing25
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean263757.06
Minimum239193.22
Maximum274637.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:25.568551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum239193.22
5-th percentile250746.9
Q1260904.47
median265031.74
Q3267457.05
95-th percentile271910.32
Maximum274637.22
Range35443.995
Interquartile range (IQR)6552.5789

Descriptive statistics

Standard deviation5915.2353
Coefficient of variation (CV)0.022426832
Kurtosis2.3698393
Mean263757.06
Median Absolute Deviation (MAD)2947.8529
Skewness-1.2903853
Sum1.1658062 × 108
Variance34990009
MonotonicityNot monotonic
2023-12-11T04:23:25.841901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
264078.515685 3
 
0.6%
268252.175255 3
 
0.6%
256000.711138 2
 
0.4%
244607.915396 2
 
0.4%
257570.015888 2
 
0.4%
249475.583994 2
 
0.4%
261855.546173 2
 
0.4%
267638.154317 2
 
0.4%
260661.018273 2
 
0.4%
259526.429643 2
 
0.4%
Other values (388) 420
89.9%
(Missing) 25
 
5.4%
ValueCountFrequency (%)
239193.219579 1
0.2%
239536.919741 1
0.2%
242313.644674 1
0.2%
242646.872394 1
0.2%
243049.515883 1
0.2%
244518.668328 1
0.2%
244607.915396 2
0.4%
244700.0 1
0.2%
248807.777332 1
0.2%
249192.670686 1
0.2%
ValueCountFrequency (%)
274637.215016 1
0.2%
274111.427951 1
0.2%
273994.885719 1
0.2%
273672.145236 1
0.2%
273353.135752 1
0.2%
273295.763942 1
0.2%
273220.608261 1
0.2%
273124.515307 1
0.2%
273085.155488 1
0.2%
273005.206023 1
0.2%

축산업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
축산물가공업
467 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
축산물가공업 467
100.0%

Length

2023-12-11T04:23:26.053861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:26.194050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물가공업 467
100.0%

축산물가공업구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
식육가공업
442 
유가공업
 
14
알가공업
 
11

Length

Max length5
Median length5
Mean length4.9464668
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유가공업
2nd row식육가공업
3rd row식육가공업
4th row알가공업
5th row식육가공업

Common Values

ValueCountFrequency (%)
식육가공업 442
94.6%
유가공업 14
 
3.0%
알가공업 11
 
2.4%

Length

2023-12-11T04:23:26.364086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:26.529853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식육가공업 442
94.6%
유가공업 14
 
3.0%
알가공업 11
 
2.4%

축산일련번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing467
Missing (%)100.0%
Memory size4.2 KiB

권리주체일련번호
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
000
330 
L00
137 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row000
2nd row000
3rd row000
4th row000
5th row000

Common Values

ValueCountFrequency (%)
000 330
70.7%
L00 137
29.3%

Length

2023-12-11T04:23:26.719444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:26.875319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
000 330
70.7%
l00 137
29.3%

총종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct29
Distinct (%)6.5%
Missing24
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean2.3702032
Minimum0
Maximum121
Zeros357
Zeros (%)76.4%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-11T04:23:27.027454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum121
Range121
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.872699
Coefficient of variation (CV)4.5872434
Kurtosis66.385249
Mean2.3702032
Median Absolute Deviation (MAD)0
Skewness7.6672242
Sum1050
Variance118.21558
MonotonicityNot monotonic
2023-12-11T04:23:27.229162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 357
76.4%
2 13
 
2.8%
1 12
 
2.6%
4 10
 
2.1%
3 10
 
2.1%
5 9
 
1.9%
7 3
 
0.6%
11 3
 
0.6%
13 3
 
0.6%
6 2
 
0.4%
Other values (19) 21
 
4.5%
(Missing) 24
 
5.1%
ValueCountFrequency (%)
0 357
76.4%
1 12
 
2.6%
2 13
 
2.8%
3 10
 
2.1%
4 10
 
2.1%
5 9
 
1.9%
6 2
 
0.4%
7 3
 
0.6%
8 1
 
0.2%
9 2
 
0.4%
ValueCountFrequency (%)
121 1
0.2%
99 1
0.2%
93 1
0.2%
88 1
0.2%
57 1
0.2%
41 1
0.2%
39 1
0.2%
37 1
0.2%
35 1
0.2%
27 1
0.2%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총종업원수
01축산가공업07_22_05_P342000034200000041999000119990219<NA>1영업/정상0정상<NA><NA><NA><NA>964-05670.0<NA>대구광역시 동구 동호동 109-1 번지<NA><NA>(주)춘광냉동종합식품20040308131215I2018-08-31 23:59:59.0유가공업<NA><NA>축산물가공업유가공업<NA>000<NA>
12축산가공업07_22_05_P342000034200000042000000320000922<NA>1영업/정상0정상<NA><NA><NA><NA>961-11720.0<NA>대구광역시 동구 신기동 118-2 번지<NA><NA>(주)청담원20040308154639I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>000<NA>
23축산가공업07_22_05_P342000034200000042002000120020319<NA>1영업/정상0정상<NA><NA><NA><NA>964-55890.0<NA>대구광역시 동구 용계동 878-55 번지<NA><NA>부성종합식품20040308145200I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>000<NA>
34축산가공업07_22_05_P342000034200000042002000220020422<NA>1영업/정상0정상<NA><NA><NA><NA>941-41820.0<NA>대구광역시 동구 신암동 95-76 번지<NA><NA>대구유통20040308151033I2018-08-31 23:59:59.0알가공업<NA><NA>축산물가공업알가공업<NA>000<NA>
45축산가공업07_22_05_P342000034200000042003000220030715<NA>1영업/정상0정상<NA><NA><NA><NA>982-12530.0<NA>대구광역시 동구 도동 8-1 번지<NA><NA>푸드팜20040308153014I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>000<NA>
56축산가공업07_22_05_P342000034200000042003000320031208<NA>1영업/정상0정상<NA><NA><NA><NA>984-11000.0<NA>대구광역시 동구 지저동 736-1 번지<NA><NA>세영종합식품20040308153520I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>000<NA>
67축산가공업07_22_05_P342000034200000042003000420030225<NA>1영업/정상0정상<NA><NA><NA><NA>963-02370.0<NA>대구광역시 동구 신서동 625-6 번지<NA><NA>(주)정성원종합식품20040309113517I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>000<NA>
78축산가공업07_22_05_P342000034200000042000000420001010<NA>2휴업1휴업<NA>20020601<NA><NA><NA>0.0<NA>대구광역시 동구 율암동 363-3 번지<NA><NA>(주)두현후레쉬20040309103412I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>000<NA>
89축산가공업07_22_05_P346000034600000042000000120000626<NA>1영업/정상0정상<NA><NA><NA><NA>811-82240.0<NA>대구광역시 수성구 사월동 37-1 번지<NA><NA>계림물산20040319085420I2018-08-31 23:59:59.0식육가공업<NA><NA>축산물가공업식육가공업<NA>000<NA>
910축산가공업07_22_05_P346000034600000041998000119980813<NA>1영업/정상0정상<NA><NA><NA><NA><NA>0.0<NA>대구광역시 수성구 만촌동 1036-11번지대구광역시 수성구 만촌로1길 39 (만촌동)<NA>또와축산20050124103616I2018-08-31 23:59:59.0식육가공업348363.180782263409.144293축산물가공업식육가공업<NA>000<NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)축산업무구분명축산물가공업구분명축산일련번호권리주체일련번호총종업원수
457458축산가공업07_22_05_P627000062700000042019000820190401<NA>1영업/정상0정상<NA><NA><NA><NA>0532615500119.77<NA>대구광역시 중구 동인동3가 394번지 1호대구광역시 중구 태평로51길 75 (동인동3가)<NA>주식회사 정인엘에프 제조공장20200205171318U2020-02-07 02:40:00.0식육가공업345260.392121264951.792224축산물가공업식육가공업<NA>0000
458459축산가공업07_22_05_P627000062700000042019001920191002<NA>1영업/정상0정상<NA><NA><NA><NA><NA>178.5<NA>대구광역시 달성군 다사읍 세천리 1607번지 1호대구광역시 달성군 다사읍 세천로10길 44-13<NA>더줌푸드시스템20191002100015I2019-10-04 02:22:41.0식육가공업333090.900078264317.117043축산물가공업식육가공업<NA>0000
459460축산가공업07_22_05_P627000062700000042019001720190911<NA>1영업/정상0정상<NA><NA><NA><NA><NA>161.68<NA>대구광역시 달성군 옥포읍 간경리 952번지 0호대구광역시 달성군 옥포읍 간경1길 11-2<NA>(주)우리축산20190911143151I2019-09-13 02:22:26.0식육가공업<NA><NA>축산물가공업식육가공업<NA>L000
460461축산가공업07_22_05_P627000062700000042019001320190703<NA>1영업/정상0정상<NA><NA><NA><NA>0537455111109.2<NA>대구광역시 수성구 만촌동 673번지 44호대구광역시 수성구 공경로 10 (만촌동)<NA>나래축산유통20190703164513I2019-07-05 02:21:29.0식육가공업348536.558949264462.03006축산물가공업식육가공업<NA>0000
461462축산가공업07_22_05_P627000062700000042019001620190905<NA>1영업/정상0정상<NA><NA><NA><NA><NA>65.26<NA>대구광역시 달성군 옥포읍 본리리 1940번지 0호대구광역시 달성군 옥포읍 본리로9길 42<NA>달구벌푸드20190905172752I2019-09-07 02:22:25.0식육가공업331538.220272255701.263732축산물가공업식육가공업<NA>0000
462463축산가공업07_22_05_P627000062700000042019001520190902<NA>1영업/정상0정상<NA><NA><NA><NA><NA>47.65<NA>대구광역시 중구 남산동 2266번지 4호대구광역시 중구 남산로1길 7 (남산동)<NA>하루족발보쌈20190902175123I2019-09-04 02:22:18.0식육가공업342841.213847263046.555117축산물가공업식육가공업<NA>0000
463464축산가공업07_22_05_P627000062700000042019001420190724<NA>1영업/정상0정상<NA><NA><NA><NA><NA>328.52<NA>대구광역시 달서구 진천동 723번지 5호대구광역시 달서구 상화로9길 14, 1층,2층 (진천동)<NA>경남푸드20190917173333U2019-09-19 02:40:00.0식육가공업337275.67501257588.632143축산물가공업식육가공업<NA>0000
464465축산가공업07_22_05_P627000062700000042019001820190925<NA>1영업/정상0정상<NA><NA><NA><NA>053641377319.41<NA>대구광역시 달성군 논공읍 금포리 1809번지 2호 2층대구광역시 달성군 논공읍 비슬로 1786, 2층<NA>성원푸드20190925162555I2019-09-27 02:22:37.0식육가공업328396.070219253610.903342축산물가공업식육가공업<NA>0000
465466축산가공업07_22_05_P627000062700000042019002120191127<NA>1영업/정상0정상<NA><NA><NA><NA>05315776805369.9<NA>대구광역시 달성군 옥포읍 신당리 1100번지 5호대구광역시 달성군 옥포읍 금계길 116<NA>은성유통20191127175805I2019-11-29 00:23:27.0식육가공업330321.0255751.0축산물가공업식육가공업<NA>0000
466467축산가공업07_22_05_P627000062700000042019002020191126<NA>1영업/정상0정상<NA><NA><NA><NA>0539639956260.3<NA>대구광역시 동구 신평동 40번지 8호대구광역시 동구 신덕로5길 96 (신평동)<NA>(주)소범식품20191126160912I2019-11-28 00:23:35.0식육가공업353039.907561266171.796199축산물가공업식육가공업<NA>L000