Overview

Dataset statistics

Number of variables44
Number of observations6139
Missing cells96180
Missing cells (%)35.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 MiB
Average record size in memory375.0 B

Variable types

Numeric11
Text9
DateTime4
Unsupported7
Categorical12
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16069/S/1/datasetView.do

Alerts

업태구분명 has constant value ""Constant
영업장주변구분명 has constant value ""Constant
등급구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
급수시설구분명 is highly imbalanced (87.3%)Imbalance
인허가취소일자 has 6139 (100.0%) missing valuesMissing
폐업일자 has 2690 (43.8%) missing valuesMissing
휴업시작일자 has 6139 (100.0%) missing valuesMissing
휴업종료일자 has 6139 (100.0%) missing valuesMissing
재개업일자 has 6139 (100.0%) missing valuesMissing
전화번호 has 2557 (41.7%) missing valuesMissing
소재지면적 has 1807 (29.4%) missing valuesMissing
도로명주소 has 660 (10.8%) missing valuesMissing
도로명우편번호 has 681 (11.1%) missing valuesMissing
좌표정보(X) has 124 (2.0%) missing valuesMissing
좌표정보(Y) has 124 (2.0%) missing valuesMissing
영업장주변구분명 has 6138 (> 99.9%) missing valuesMissing
등급구분명 has 6138 (> 99.9%) missing valuesMissing
본사종업원수 has 4502 (73.3%) missing valuesMissing
공장사무직종업원수 has 4493 (73.2%) missing valuesMissing
공장판매직종업원수 has 4502 (73.3%) missing valuesMissing
공장생산직종업원수 has 4510 (73.5%) missing valuesMissing
보증액 has 4862 (79.2%) missing valuesMissing
월세액 has 4865 (79.2%) missing valuesMissing
다중이용업소여부 has 2249 (36.6%) missing valuesMissing
시설총규모 has 2249 (36.6%) missing valuesMissing
전통업소지정번호 has 6139 (100.0%) missing valuesMissing
전통업소주된음식 has 6139 (100.0%) missing valuesMissing
홈페이지 has 6139 (100.0%) missing valuesMissing
본사종업원수 is highly skewed (γ1 = 26.51221909)Skewed
공장사무직종업원수 is highly skewed (γ1 = 28.46724619)Skewed
공장판매직종업원수 is highly skewed (γ1 = 24.72743586)Skewed
공장생산직종업원수 is highly skewed (γ1 = 40.27764319)Skewed
보증액 is highly skewed (γ1 = 21.72760093)Skewed
시설총규모 is highly skewed (γ1 = 41.58909709)Skewed
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
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
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
본사종업원수 has 1596 (26.0%) zerosZeros
공장사무직종업원수 has 1556 (25.3%) zerosZeros
공장판매직종업원수 has 1555 (25.3%) zerosZeros
공장생산직종업원수 has 1611 (26.2%) zerosZeros
보증액 has 1185 (19.3%) zerosZeros
월세액 has 1187 (19.3%) zerosZeros
시설총규모 has 3207 (52.2%) zerosZeros

Reproduction

Analysis started2024-05-11 06:19:20.805914
Analysis finished2024-05-11 06:19:24.237635
Duration3.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3162383.1
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:24.368952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13130000
median3200000
Q33220000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation73628.92
Coefficient of variation (CV)0.023282732
Kurtosis-0.47120182
Mean3162383.1
Median Absolute Deviation (MAD)30000
Skewness-0.9748601
Sum1.941387 × 1010
Variance5.4212178 × 109
MonotonicityNot monotonic
2024-05-11T15:19:24.643378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 1582
25.8%
3210000 786
12.8%
3230000 545
 
8.9%
3180000 360
 
5.9%
3130000 357
 
5.8%
3150000 254
 
4.1%
3010000 231
 
3.8%
3170000 230
 
3.7%
3040000 187
 
3.0%
3160000 182
 
3.0%
Other values (15) 1425
23.2%
ValueCountFrequency (%)
3000000 139
2.3%
3010000 231
3.8%
3020000 127
2.1%
3030000 182
3.0%
3040000 187
3.0%
3050000 182
3.0%
3060000 76
 
1.2%
3070000 68
 
1.1%
3080000 38
 
0.6%
3090000 37
 
0.6%
ValueCountFrequency (%)
3240000 128
 
2.1%
3230000 545
 
8.9%
3220000 1582
25.8%
3210000 786
12.8%
3200000 96
 
1.6%
3190000 82
 
1.3%
3180000 360
 
5.9%
3170000 230
 
3.7%
3160000 182
 
3.0%
3150000 254
 
4.1%

관리번호
Text

UNIQUE 

Distinct6139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
2024-05-11T15:19:25.007107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters135058
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

Unique6139 ?
Unique (%)100.0%

Sample

1st row3040000-135-2023-00002
2nd row3220000-135-2023-00020
3rd row3210000-135-2024-00018
4th row3030000-135-2012-00003
5th row3040000-135-2012-00007
ValueCountFrequency (%)
3040000-135-2023-00002 1
 
< 0.1%
3220000-135-2008-00018 1
 
< 0.1%
3220000-135-2009-00020 1
 
< 0.1%
3220000-135-2009-00019 1
 
< 0.1%
3220000-135-2013-00012 1
 
< 0.1%
3220000-135-2005-00045 1
 
< 0.1%
3220000-135-2005-00044 1
 
< 0.1%
3220000-135-2015-00025 1
 
< 0.1%
3220000-135-2009-00003 1
 
< 0.1%
3220000-135-2009-00002 1
 
< 0.1%
Other values (6129) 6129
99.8%
2024-05-11T15:19:25.599282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 55863
41.4%
- 18417
 
13.6%
2 15456
 
11.4%
3 15202
 
11.3%
1 14668
 
10.9%
5 7891
 
5.8%
4 2117
 
1.6%
8 1472
 
1.1%
6 1406
 
1.0%
7 1387
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 116641
86.4%
Dash Punctuation 18417
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55863
47.9%
2 15456
 
13.3%
3 15202
 
13.0%
1 14668
 
12.6%
5 7891
 
6.8%
4 2117
 
1.8%
8 1472
 
1.3%
6 1406
 
1.2%
7 1387
 
1.2%
9 1179
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 18417
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 135058
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 55863
41.4%
- 18417
 
13.6%
2 15456
 
11.4%
3 15202
 
11.3%
1 14668
 
10.9%
5 7891
 
5.8%
4 2117
 
1.6%
8 1472
 
1.1%
6 1406
 
1.0%
7 1387
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 135058
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 55863
41.4%
- 18417
 
13.6%
2 15456
 
11.4%
3 15202
 
11.3%
1 14668
 
10.9%
5 7891
 
5.8%
4 2117
 
1.6%
8 1472
 
1.1%
6 1406
 
1.0%
7 1387
 
1.0%
Distinct2943
Distinct (%)47.9%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
Minimum2004-02-10 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:19:25.873240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:19:26.448178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6139
Missing (%)100.0%
Memory size54.1 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
3
3449 
1
2690 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row1
4th row1
5th row3

Common Values

ValueCountFrequency (%)
3 3449
56.2%
1 2690
43.8%

Length

2024-05-11T15:19:26.700325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:26.903379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3449
56.2%
1 2690
43.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
폐업
3449 
영업/정상
2690 

Length

Max length5
Median length2
Mean length3.3145463
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3449
56.2%
영업/정상 2690
43.8%

Length

2024-05-11T15:19:27.145816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:27.356093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3449
56.2%
영업/정상 2690
43.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
2
3449 
1
2690 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 3449
56.2%
1 2690
43.8%

Length

2024-05-11T15:19:27.550383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:27.742931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3449
56.2%
1 2690
43.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
폐업
3449 
영업
2690 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3449
56.2%
영업 2690
43.8%

Length

2024-05-11T15:19:27.934813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:28.099437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3449
56.2%
영업 2690
43.8%

폐업일자
Date

MISSING 

Distinct2042
Distinct (%)59.2%
Missing2690
Missing (%)43.8%
Memory size48.1 KiB
Minimum2004-07-29 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:19:28.299389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:19:28.532019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6139
Missing (%)100.0%
Memory size54.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6139
Missing (%)100.0%
Memory size54.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6139
Missing (%)100.0%
Memory size54.1 KiB

전화번호
Text

MISSING 

Distinct2941
Distinct (%)82.1%
Missing2557
Missing (%)41.7%
Memory size48.1 KiB
2024-05-11T15:19:29.112185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.799832
Min length3

Characters and Unicode

Total characters38685
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

Unique2444 ?
Unique (%)68.2%

Sample

1st row070 88505130
2nd row070 88505130
3rd row02 7866771
4th row02 557 0501
5th row02 747 3839
ValueCountFrequency (%)
02 1890
28.0%
070 375
 
5.5%
031 37
 
0.5%
517 22
 
0.3%
553 13
 
0.2%
516 12
 
0.2%
565 11
 
0.2%
523 11
 
0.2%
568 11
 
0.2%
3339 10
 
0.1%
Other values (3199) 4369
64.6%
2024-05-11T15:19:30.014224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6934
17.9%
2 5442
14.1%
4475
11.6%
5 3269
8.5%
7 3077
8.0%
3 2806
7.3%
1 2745
 
7.1%
4 2725
 
7.0%
8 2651
 
6.9%
6 2645
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34210
88.4%
Space Separator 4475
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6934
20.3%
2 5442
15.9%
5 3269
9.6%
7 3077
9.0%
3 2806
8.2%
1 2745
 
8.0%
4 2725
 
8.0%
8 2651
 
7.7%
6 2645
 
7.7%
9 1916
 
5.6%
Space Separator
ValueCountFrequency (%)
4475
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38685
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6934
17.9%
2 5442
14.1%
4475
11.6%
5 3269
8.5%
7 3077
8.0%
3 2806
7.3%
1 2745
 
7.1%
4 2725
 
7.0%
8 2651
 
6.9%
6 2645
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38685
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6934
17.9%
2 5442
14.1%
4475
11.6%
5 3269
8.5%
7 3077
8.0%
3 2806
7.3%
1 2745
 
7.1%
4 2725
 
7.0%
8 2651
 
6.9%
6 2645
 
6.8%

소재지면적
Text

MISSING 

Distinct1883
Distinct (%)43.5%
Missing1807
Missing (%)29.4%
Memory size48.1 KiB
2024-05-11T15:19:30.643276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.9949215
Min length3

Characters and Unicode

Total characters21638
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

Unique1489 ?
Unique (%)34.4%

Sample

1st row2.20
2nd row0.00
3rd row134.60
4th row23.61
5th row49.81
ValueCountFrequency (%)
3.30 222
 
5.1%
00 190
 
4.4%
0.00 139
 
3.2%
33.00 133
 
3.1%
10.00 125
 
2.9%
30.00 68
 
1.6%
20.00 58
 
1.3%
66.00 55
 
1.3%
100.00 50
 
1.2%
3.00 47
 
1.1%
Other values (1873) 3245
74.9%
2024-05-11T15:19:31.614130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5791
26.8%
. 4332
20.0%
1 1947
 
9.0%
3 1945
 
9.0%
2 1440
 
6.7%
5 1252
 
5.8%
6 1243
 
5.7%
4 1059
 
4.9%
9 913
 
4.2%
8 891
 
4.1%
Other values (2) 825
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17276
79.8%
Other Punctuation 4362
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5791
33.5%
1 1947
 
11.3%
3 1945
 
11.3%
2 1440
 
8.3%
5 1252
 
7.2%
6 1243
 
7.2%
4 1059
 
6.1%
9 913
 
5.3%
8 891
 
5.2%
7 795
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 4332
99.3%
, 30
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 21638
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5791
26.8%
. 4332
20.0%
1 1947
 
9.0%
3 1945
 
9.0%
2 1440
 
6.7%
5 1252
 
5.8%
6 1243
 
5.7%
4 1059
 
4.9%
9 913
 
4.2%
8 891
 
4.1%
Other values (2) 825
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21638
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5791
26.8%
. 4332
20.0%
1 1947
 
9.0%
3 1945
 
9.0%
2 1440
 
6.7%
5 1252
 
5.8%
6 1243
 
5.7%
4 1059
 
4.9%
9 913
 
4.2%
8 891
 
4.1%
Other values (2) 825
 
3.8%
Distinct1953
Distinct (%)32.0%
Missing28
Missing (%)0.5%
Memory size48.1 KiB
2024-05-11T15:19:32.238469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.25135
Min length6

Characters and Unicode

Total characters38202
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

Unique910 ?
Unique (%)14.9%

Sample

1st row143-890
2nd row135-516
3rd row137-857
4th row133-834
5th row143-841
ValueCountFrequency (%)
157210 68
 
1.1%
138888 64
 
1.0%
153803 54
 
0.9%
152848 48
 
0.8%
157-210 40
 
0.7%
153-803 38
 
0.6%
137860 33
 
0.5%
135839 27
 
0.4%
135924 25
 
0.4%
152-848 24
 
0.4%
Other values (1943) 5690
93.1%
2024-05-11T15:19:32.985460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8347
21.8%
8 5773
15.1%
3 5522
14.5%
5 4116
10.8%
0 3479
9.1%
7 2398
 
6.3%
2 2127
 
5.6%
9 1845
 
4.8%
4 1832
 
4.8%
- 1536
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36666
96.0%
Dash Punctuation 1536
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8347
22.8%
8 5773
15.7%
3 5522
15.1%
5 4116
11.2%
0 3479
9.5%
7 2398
 
6.5%
2 2127
 
5.8%
9 1845
 
5.0%
4 1832
 
5.0%
6 1227
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 1536
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8347
21.8%
8 5773
15.1%
3 5522
14.5%
5 4116
10.8%
0 3479
9.1%
7 2398
 
6.3%
2 2127
 
5.6%
9 1845
 
4.8%
4 1832
 
4.8%
- 1536
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8347
21.8%
8 5773
15.1%
3 5522
14.5%
5 4116
10.8%
0 3479
9.1%
7 2398
 
6.3%
2 2127
 
5.6%
9 1845
 
4.8%
4 1832
 
4.8%
- 1536
 
4.0%
Distinct4485
Distinct (%)73.4%
Missing28
Missing (%)0.5%
Memory size48.1 KiB
2024-05-11T15:19:33.469797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length48
Mean length27.165276
Min length14

Characters and Unicode

Total characters166007
Distinct characters600
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3768 ?
Unique (%)61.7%

Sample

1st row서울특별시 광진구 중곡동 ***-** ***호
2nd row서울특별시 강남구 일원동 *** 남경빌딩
3rd row서울특별시 서초구 서초동 ****-** BNK디지털타워 ***호
4th row서울특별시 성동구 성수동*가 ***-**
5th row서울특별시 광진구 자양동 **-*
ValueCountFrequency (%)
서울특별시 6109
19.4%
3374
 
10.7%
번지 2737
 
8.7%
강남구 1576
 
5.0%
1148
 
3.6%
995
 
3.2%
서초구 786
 
2.5%
송파구 544
 
1.7%
역삼동 492
 
1.6%
영등포구 358
 
1.1%
Other values (3006) 13379
42.5%
2024-05-11T15:19:34.316999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 32252
19.4%
28712
17.3%
7806
 
4.7%
6938
 
4.2%
6524
 
3.9%
6241
 
3.8%
6163
 
3.7%
6114
 
3.7%
6112
 
3.7%
- 5230
 
3.2%
Other values (590) 53915
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 97813
58.9%
Other Punctuation 32418
 
19.5%
Space Separator 28712
 
17.3%
Dash Punctuation 5230
 
3.2%
Uppercase Letter 792
 
0.5%
Decimal Number 488
 
0.3%
Open Punctuation 184
 
0.1%
Close Punctuation 182
 
0.1%
Lowercase Letter 135
 
0.1%
Letter Number 34
 
< 0.1%
Other values (2) 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7806
 
8.0%
6938
 
7.1%
6524
 
6.7%
6241
 
6.4%
6163
 
6.3%
6114
 
6.3%
6112
 
6.2%
3347
 
3.4%
2750
 
2.8%
2151
 
2.2%
Other values (516) 43667
44.6%
Uppercase Letter
ValueCountFrequency (%)
B 102
12.9%
A 81
 
10.2%
T 70
 
8.8%
I 69
 
8.7%
K 49
 
6.2%
C 42
 
5.3%
E 38
 
4.8%
O 36
 
4.5%
R 33
 
4.2%
S 32
 
4.0%
Other values (15) 240
30.3%
Lowercase Letter
ValueCountFrequency (%)
e 23
17.0%
o 17
12.6%
r 16
11.9%
n 10
 
7.4%
a 9
 
6.7%
s 8
 
5.9%
w 8
 
5.9%
l 8
 
5.9%
k 6
 
4.4%
i 5
 
3.7%
Other values (10) 25
18.5%
Decimal Number
ValueCountFrequency (%)
1 87
17.8%
2 82
16.8%
5 61
12.5%
6 55
11.3%
3 48
9.8%
4 46
9.4%
7 29
 
5.9%
0 29
 
5.9%
9 26
 
5.3%
8 25
 
5.1%
Other Punctuation
ValueCountFrequency (%)
* 32252
99.5%
, 139
 
0.4%
/ 12
 
< 0.1%
. 9
 
< 0.1%
@ 2
 
< 0.1%
: 2
 
< 0.1%
& 1
 
< 0.1%
? 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
14
41.2%
11
32.4%
9
26.5%
Open Punctuation
ValueCountFrequency (%)
( 175
95.1%
[ 9
 
4.9%
Close Punctuation
ValueCountFrequency (%)
) 173
95.1%
] 9
 
4.9%
Space Separator
ValueCountFrequency (%)
28712
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5230
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 97813
58.9%
Common 67233
40.5%
Latin 961
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7806
 
8.0%
6938
 
7.1%
6524
 
6.7%
6241
 
6.4%
6163
 
6.3%
6114
 
6.3%
6112
 
6.2%
3347
 
3.4%
2750
 
2.8%
2151
 
2.2%
Other values (516) 43667
44.6%
Latin
ValueCountFrequency (%)
B 102
 
10.6%
A 81
 
8.4%
T 70
 
7.3%
I 69
 
7.2%
K 49
 
5.1%
C 42
 
4.4%
E 38
 
4.0%
O 36
 
3.7%
R 33
 
3.4%
S 32
 
3.3%
Other values (38) 409
42.6%
Common
ValueCountFrequency (%)
* 32252
48.0%
28712
42.7%
- 5230
 
7.8%
( 175
 
0.3%
) 173
 
0.3%
, 139
 
0.2%
1 87
 
0.1%
2 82
 
0.1%
5 61
 
0.1%
6 55
 
0.1%
Other values (16) 267
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 97813
58.9%
ASCII 68156
41.1%
Number Forms 34
 
< 0.1%
CJK Compat 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 32252
47.3%
28712
42.1%
- 5230
 
7.7%
( 175
 
0.3%
) 173
 
0.3%
, 139
 
0.2%
B 102
 
0.1%
1 87
 
0.1%
2 82
 
0.1%
A 81
 
0.1%
Other values (60) 1123
 
1.6%
Hangul
ValueCountFrequency (%)
7806
 
8.0%
6938
 
7.1%
6524
 
6.7%
6241
 
6.4%
6163
 
6.3%
6114
 
6.3%
6112
 
6.2%
3347
 
3.4%
2750
 
2.8%
2151
 
2.2%
Other values (516) 43667
44.6%
Number Forms
ValueCountFrequency (%)
14
41.2%
11
32.4%
9
26.5%
CJK Compat
ValueCountFrequency (%)
4
100.0%

도로명주소
Text

MISSING 

Distinct4693
Distinct (%)85.7%
Missing660
Missing (%)10.8%
Memory size48.1 KiB
2024-05-11T15:19:34.834286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length52
Mean length36.57766
Min length21

Characters and Unicode

Total characters200409
Distinct characters633
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4159 ?
Unique (%)75.9%

Sample

1st row서울특별시 광진구 용마산로 **, ***호 (중곡동)
2nd row서울특별시 강남구 일원로 **, 남경빌딩 지상*층 ****호 (일원동)
3rd row서울특별시 서초구 서초대로 ***, BNK디지털타워 ***호 (서초동)
4th row서울특별시 성동구 아차산로*길 **, *층 *-*호 (성수동*가)
5th row서울특별시 광진구 아차산로**길 **, *층 ***호 (자양동)
ValueCountFrequency (%)
5494
 
14.4%
서울특별시 5476
 
14.3%
2725
 
7.1%
2535
 
6.6%
강남구 1448
 
3.8%
서초구 695
 
1.8%
지상*층 552
 
1.4%
송파구 501
 
1.3%
역삼동 404
 
1.1%
영등포구 319
 
0.8%
Other values (4036) 18116
47.3%
2024-05-11T15:19:35.597696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 34095
17.0%
32796
 
16.4%
7269
 
3.6%
6882
 
3.4%
, 6554
 
3.3%
6013
 
3.0%
5917
 
3.0%
5657
 
2.8%
( 5580
 
2.8%
) 5580
 
2.8%
Other values (623) 84066
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 112966
56.4%
Other Punctuation 40667
 
20.3%
Space Separator 32796
 
16.4%
Open Punctuation 5585
 
2.8%
Close Punctuation 5585
 
2.8%
Uppercase Letter 1036
 
0.5%
Dash Punctuation 959
 
0.5%
Decimal Number 613
 
0.3%
Lowercase Letter 135
 
0.1%
Letter Number 36
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7269
 
6.4%
6882
 
6.1%
6013
 
5.3%
5917
 
5.2%
5657
 
5.0%
5538
 
4.9%
5483
 
4.9%
5478
 
4.8%
3941
 
3.5%
3299
 
2.9%
Other values (552) 57489
50.9%
Uppercase Letter
ValueCountFrequency (%)
B 196
18.9%
A 161
15.5%
T 76
 
7.3%
I 67
 
6.5%
C 60
 
5.8%
E 45
 
4.3%
L 45
 
4.3%
R 41
 
4.0%
D 39
 
3.8%
K 37
 
3.6%
Other values (15) 269
26.0%
Lowercase Letter
ValueCountFrequency (%)
e 20
14.8%
o 17
12.6%
r 15
11.1%
a 11
 
8.1%
b 8
 
5.9%
n 8
 
5.9%
s 8
 
5.9%
l 7
 
5.2%
w 6
 
4.4%
k 6
 
4.4%
Other values (10) 29
21.5%
Decimal Number
ValueCountFrequency (%)
1 143
23.3%
2 124
20.2%
0 68
11.1%
3 62
10.1%
6 51
 
8.3%
5 49
 
8.0%
4 45
 
7.3%
9 28
 
4.6%
7 24
 
3.9%
8 19
 
3.1%
Other Punctuation
ValueCountFrequency (%)
* 34095
83.8%
, 6554
 
16.1%
/ 10
 
< 0.1%
. 6
 
< 0.1%
& 1
 
< 0.1%
: 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
14
38.9%
11
30.6%
11
30.6%
Open Punctuation
ValueCountFrequency (%)
( 5580
99.9%
[ 5
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 5580
99.9%
] 5
 
0.1%
Space Separator
ValueCountFrequency (%)
32796
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 959
100.0%
Math Symbol
ValueCountFrequency (%)
~ 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 112966
56.4%
Common 86236
43.0%
Latin 1207
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7269
 
6.4%
6882
 
6.1%
6013
 
5.3%
5917
 
5.2%
5657
 
5.0%
5538
 
4.9%
5483
 
4.9%
5478
 
4.8%
3941
 
3.5%
3299
 
2.9%
Other values (552) 57489
50.9%
Latin
ValueCountFrequency (%)
B 196
16.2%
A 161
 
13.3%
T 76
 
6.3%
I 67
 
5.6%
C 60
 
5.0%
E 45
 
3.7%
L 45
 
3.7%
R 41
 
3.4%
D 39
 
3.2%
K 37
 
3.1%
Other values (38) 440
36.5%
Common
ValueCountFrequency (%)
* 34095
39.5%
32796
38.0%
, 6554
 
7.6%
( 5580
 
6.5%
) 5580
 
6.5%
- 959
 
1.1%
1 143
 
0.2%
2 124
 
0.1%
0 68
 
0.1%
3 62
 
0.1%
Other values (13) 275
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 112966
56.4%
ASCII 87407
43.6%
Number Forms 36
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 34095
39.0%
32796
37.5%
, 6554
 
7.5%
( 5580
 
6.4%
) 5580
 
6.4%
- 959
 
1.1%
B 196
 
0.2%
A 161
 
0.2%
1 143
 
0.2%
2 124
 
0.1%
Other values (58) 1219
 
1.4%
Hangul
ValueCountFrequency (%)
7269
 
6.4%
6882
 
6.1%
6013
 
5.3%
5917
 
5.2%
5657
 
5.0%
5538
 
4.9%
5483
 
4.9%
5478
 
4.8%
3941
 
3.5%
3299
 
2.9%
Other values (552) 57489
50.9%
Number Forms
ValueCountFrequency (%)
14
38.9%
11
30.6%
11
30.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1769
Distinct (%)32.4%
Missing681
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean5873.1326
Minimum1006
Maximum54632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:35.865987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1006
5-th percentile2585
Q14808
median6126
Q36733
95-th percentile8503
Maximum54632
Range53626
Interquartile range (IQR)1925

Descriptive statistics

Standard deviation1772.6939
Coefficient of variation (CV)0.30183108
Kurtosis106.5654
Mean5873.1326
Median Absolute Deviation (MAD)811.5
Skewness3.548424
Sum32055558
Variance3142443.8
MonotonicityNot monotonic
2024-05-11T15:19:36.147084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8506 39
 
0.6%
5838 35
 
0.6%
6132 34
 
0.6%
6083 29
 
0.5%
5854 27
 
0.4%
5719 26
 
0.4%
7788 24
 
0.4%
5510 24
 
0.4%
7238 23
 
0.4%
8505 22
 
0.4%
Other values (1759) 5175
84.3%
(Missing) 681
 
11.1%
ValueCountFrequency (%)
1006 1
 
< 0.1%
1044 2
 
< 0.1%
1053 1
 
< 0.1%
1054 1
 
< 0.1%
1055 5
0.1%
1056 1
 
< 0.1%
1058 1
 
< 0.1%
1061 1
 
< 0.1%
1062 1
 
< 0.1%
1069 1
 
< 0.1%
ValueCountFrequency (%)
54632 1
 
< 0.1%
24387 1
 
< 0.1%
13524 1
 
< 0.1%
8862 1
 
< 0.1%
8861 1
 
< 0.1%
8852 1
 
< 0.1%
8846 1
 
< 0.1%
8832 2
 
< 0.1%
8826 6
0.1%
8808 1
 
< 0.1%
Distinct5151
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
2024-05-11T15:19:36.678675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length26
Mean length8.3611337
Min length2

Characters and Unicode

Total characters51329
Distinct characters805
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4331 ?
Unique (%)70.5%

Sample

1st row국메디앙스 주식회사
2nd row닥터블릿헬스케어 주식회사
3rd row라운드포 주식회사
4th row(주)오하나
5th row(주)오하나
ValueCountFrequency (%)
주식회사 1404
 
17.5%
48
 
0.6%
유한회사 24
 
0.3%
서울지점 14
 
0.2%
코리아 13
 
0.2%
생활건강 9
 
0.1%
헬스케어 9
 
0.1%
유한책임회사 9
 
0.1%
바이오 8
 
0.1%
7
 
0.1%
Other values (5312) 6476
80.7%
2024-05-11T15:19:37.364599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4470
 
8.7%
) 3132
 
6.1%
( 3121
 
6.1%
2494
 
4.9%
1885
 
3.7%
1695
 
3.3%
1680
 
3.3%
1574
 
3.1%
1568
 
3.1%
897
 
1.7%
Other values (795) 28813
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41737
81.3%
Close Punctuation 3134
 
6.1%
Open Punctuation 3123
 
6.1%
Space Separator 1885
 
3.7%
Uppercase Letter 777
 
1.5%
Lowercase Letter 491
 
1.0%
Decimal Number 105
 
0.2%
Other Punctuation 66
 
0.1%
Dash Punctuation 9
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4470
 
10.7%
2494
 
6.0%
1695
 
4.1%
1680
 
4.0%
1574
 
3.8%
1568
 
3.8%
897
 
2.1%
772
 
1.8%
706
 
1.7%
694
 
1.7%
Other values (724) 25187
60.3%
Uppercase Letter
ValueCountFrequency (%)
B 61
 
7.9%
L 60
 
7.7%
S 51
 
6.6%
N 50
 
6.4%
I 49
 
6.3%
H 45
 
5.8%
M 43
 
5.5%
E 42
 
5.4%
O 40
 
5.1%
A 39
 
5.0%
Other values (16) 297
38.2%
Lowercase Letter
ValueCountFrequency (%)
e 74
15.1%
a 57
11.6%
o 43
 
8.8%
n 37
 
7.5%
l 35
 
7.1%
t 31
 
6.3%
i 30
 
6.1%
r 29
 
5.9%
u 19
 
3.9%
s 16
 
3.3%
Other values (13) 120
24.4%
Decimal Number
ValueCountFrequency (%)
3 24
22.9%
1 18
17.1%
5 16
15.2%
6 13
12.4%
8 10
9.5%
2 9
 
8.6%
0 8
 
7.6%
4 6
 
5.7%
9 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
& 33
50.0%
. 27
40.9%
, 4
 
6.1%
1
 
1.5%
' 1
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 3132
99.9%
] 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 3121
99.9%
[ 2
 
0.1%
Space Separator
ValueCountFrequency (%)
1885
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41738
81.3%
Common 8323
 
16.2%
Latin 1268
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4470
 
10.7%
2494
 
6.0%
1695
 
4.1%
1680
 
4.0%
1574
 
3.8%
1568
 
3.8%
897
 
2.1%
772
 
1.8%
706
 
1.7%
694
 
1.7%
Other values (725) 25188
60.3%
Latin
ValueCountFrequency (%)
e 74
 
5.8%
B 61
 
4.8%
L 60
 
4.7%
a 57
 
4.5%
S 51
 
4.0%
N 50
 
3.9%
I 49
 
3.9%
H 45
 
3.5%
o 43
 
3.4%
M 43
 
3.4%
Other values (39) 735
58.0%
Common
ValueCountFrequency (%)
) 3132
37.6%
( 3121
37.5%
1885
22.6%
& 33
 
0.4%
. 27
 
0.3%
3 24
 
0.3%
1 18
 
0.2%
5 16
 
0.2%
6 13
 
0.2%
8 10
 
0.1%
Other values (11) 44
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41737
81.3%
ASCII 9590
 
18.7%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4470
 
10.7%
2494
 
6.0%
1695
 
4.1%
1680
 
4.0%
1574
 
3.8%
1568
 
3.8%
897
 
2.1%
772
 
1.8%
706
 
1.7%
694
 
1.7%
Other values (724) 25187
60.3%
ASCII
ValueCountFrequency (%)
) 3132
32.7%
( 3121
32.5%
1885
19.7%
e 74
 
0.8%
B 61
 
0.6%
L 60
 
0.6%
a 57
 
0.6%
S 51
 
0.5%
N 50
 
0.5%
I 49
 
0.5%
Other values (59) 1050
 
10.9%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct6013
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
Minimum2004-03-26 00:00:00
Maximum2024-05-09 17:59:59
2024-05-11T15:19:37.584155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:19:37.828599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
I
3257 
U
2881 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 3257
53.1%
U 2881
46.9%
D 1
 
< 0.1%

Length

2024-05-11T15:19:38.091358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:38.298846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3257
53.1%
u 2881
46.9%
d 1
 
< 0.1%
Distinct1539
Distinct (%)25.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:19:38.533421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:19:38.850963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
건강기능식품유통전문판매업
6139 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 6139
100.0%

Length

2024-05-11T15:19:39.142281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:39.289602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 6139
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4002
Distinct (%)66.5%
Missing124
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean200359.11
Minimum182376.78
Maximum265468.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:39.455571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182376.78
5-th percentile188798.42
Q1194871.78
median202425.73
Q3204614.82
95-th percentile210656.15
Maximum265468.35
Range83091.568
Interquartile range (IQR)9743.0344

Descriptive statistics

Standard deviation6841.6887
Coefficient of variation (CV)0.034147131
Kurtosis0.68967133
Mean200359.11
Median Absolute Deviation (MAD)3754.7356
Skewness-0.32193271
Sum1.20516 × 109
Variance46808704
MonotonicityNot monotonic
2024-05-11T15:19:39.682552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210986.460698452 33
 
0.5%
205271.275273064 24
 
0.4%
189202.600232089 20
 
0.3%
210431.832858016 19
 
0.3%
189459.065518928 15
 
0.2%
189378.332493727 13
 
0.2%
189497.04098479 13
 
0.2%
202623.297219041 12
 
0.2%
203588.048190661 12
 
0.2%
190680.536850936 12
 
0.2%
Other values (3992) 5842
95.2%
(Missing) 124
 
2.0%
ValueCountFrequency (%)
182376.780106464 1
< 0.1%
182857.528466005 1
< 0.1%
182883.960042013 1
< 0.1%
182909.911073945 1
< 0.1%
183087.143467593 1
< 0.1%
183200.30073641 1
< 0.1%
183206.351589223 1
< 0.1%
183356.918545529 1
< 0.1%
183382.861571856 2
< 0.1%
183515.10497574 1
< 0.1%
ValueCountFrequency (%)
265468.347701022 1
< 0.1%
215784.2264 1
< 0.1%
215144.766442481 1
< 0.1%
215008.531272849 1
< 0.1%
214958.713997465 1
< 0.1%
214956.131343654 1
< 0.1%
214857.430314121 1
< 0.1%
214202.035389784 1
< 0.1%
214135.999511848 1
< 0.1%
213839.356195548 2
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4001
Distinct (%)66.5%
Missing124
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean446773.85
Minimum272986
Maximum484357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:39.925720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum272986
5-th percentile441725.29
Q1443659.86
median445808.56
Q3449619.36
95-th percentile454263.49
Maximum484357
Range211371
Interquartile range (IQR)5959.4987

Descriptive statistics

Standard deviation4790.0521
Coefficient of variation (CV)0.010721424
Kurtosis288.54317
Mean446773.85
Median Absolute Deviation (MAD)2763.6955
Skewness-7.1708412
Sum2.6873447 × 109
Variance22944599
MonotonicityNot monotonic
2024-05-11T15:19:40.151919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441725.293491662 33
 
0.5%
445852.638814088 24
 
0.4%
441848.24299943 20
 
0.3%
443465.4592322 19
 
0.3%
441844.960857588 15
 
0.2%
442066.99866487 13
 
0.2%
441728.27059771 13
 
0.2%
443154.964346798 12
 
0.2%
446183.368328818 12
 
0.2%
442392.645303533 12
 
0.2%
Other values (3991) 5842
95.2%
(Missing) 124
 
2.0%
ValueCountFrequency (%)
272986.0 1
 
< 0.1%
432815.237680924 1
 
< 0.1%
437644.047174663 2
 
< 0.1%
437914.06299827 5
0.1%
438012.1279662 1
 
< 0.1%
438089.937256048 2
 
< 0.1%
438278.235724516 1
 
< 0.1%
438293.331675201 1
 
< 0.1%
438690.814038292 2
 
< 0.1%
438769.485852873 1
 
< 0.1%
ValueCountFrequency (%)
484356.995863933 1
 
< 0.1%
465106.406054016 1
 
< 0.1%
464866.74995962 1
 
< 0.1%
464814.717432497 1
 
< 0.1%
464208.305428933 1
 
< 0.1%
464199.048415229 3
< 0.1%
464080.593904719 1
 
< 0.1%
463573.102150294 1
 
< 0.1%
463511.788573322 1
 
< 0.1%
463253.973796138 1
 
< 0.1%

위생업태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
건강기능식품유통전문판매업
3890 
<NA>
2249 

Length

Max length13
Median length13
Mean length9.7028832
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 3890
63.4%
<NA> 2249
36.6%

Length

2024-05-11T15:19:40.374581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:40.567516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 3890
63.4%
na 2249
36.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
<NA>
5322 
0
817 

Length

Max length4
Median length4
Mean length3.6007493
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> 5322
86.7%
0 817
 
13.3%

Length

2024-05-11T15:19:40.763705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:41.360874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5322
86.7%
0 817
 
13.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
<NA>
5322 
0
817 

Length

Max length4
Median length4
Mean length3.6007493
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> 5322
86.7%
0 817
 
13.3%

Length

2024-05-11T15:19:41.562869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:41.748427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5322
86.7%
0 817
 
13.3%

영업장주변구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing6138
Missing (%)> 99.9%
Memory size48.1 KiB
2024-05-11T15:19:41.879931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row기타
ValueCountFrequency (%)
기타 1
100.0%
2024-05-11T15:19:42.270752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

등급구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing6138
Missing (%)> 99.9%
Memory size48.1 KiB
2024-05-11T15:19:42.454681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row자율
ValueCountFrequency (%)
자율 1
100.0%
2024-05-11T15:19:42.883098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
<NA>
5948 
상수도전용
 
190
간이상수도
 
1

Length

Max length5
Median length4
Mean length4.0311126
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5948
96.9%
상수도전용 190
 
3.1%
간이상수도 1
 
< 0.1%

Length

2024-05-11T15:19:43.139058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:43.338247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5948
96.9%
상수도전용 190
 
3.1%
간이상수도 1
 
< 0.1%

총인원
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
<NA>
5346 
0
793 

Length

Max length4
Median length4
Mean length3.6124776
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> 5346
87.1%
0 793
 
12.9%

Length

2024-05-11T15:19:43.563831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:43.791073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5346
87.1%
0 793
 
12.9%

본사종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct15
Distinct (%)0.9%
Missing4502
Missing (%)73.3%
Infinite0
Infinite (%)0.0%
Mean3.8362859
Minimum0
Maximum2500
Zeros1596
Zeros (%)26.0%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:43.983832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2500
Range2500
Interquartile range (IQR)0

Descriptive statistics

Standard deviation90.23774
Coefficient of variation (CV)23.522162
Kurtosis721.39293
Mean3.8362859
Median Absolute Deviation (MAD)0
Skewness26.512219
Sum6280
Variance8142.8497
MonotonicityNot monotonic
2024-05-11T15:19:44.207348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 1596
 
26.0%
2 6
 
0.1%
5 6
 
0.1%
4 5
 
0.1%
7 4
 
0.1%
1 4
 
0.1%
3 4
 
0.1%
10 3
 
< 0.1%
2500 2
 
< 0.1%
13 2
 
< 0.1%
Other values (5) 5
 
0.1%
(Missing) 4502
73.3%
ValueCountFrequency (%)
0 1596
26.0%
1 4
 
0.1%
2 6
 
0.1%
3 4
 
0.1%
4 5
 
0.1%
5 6
 
0.1%
6 1
 
< 0.1%
7 4
 
0.1%
9 1
 
< 0.1%
10 3
 
< 0.1%
ValueCountFrequency (%)
2500 2
 
< 0.1%
900 1
 
< 0.1%
185 1
 
< 0.1%
18 1
 
< 0.1%
13 2
 
< 0.1%
10 3
< 0.1%
9 1
 
< 0.1%
7 4
0.1%
6 1
 
< 0.1%
5 6
0.1%

공장사무직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct18
Distinct (%)1.1%
Missing4493
Missing (%)73.2%
Infinite0
Infinite (%)0.0%
Mean3.4769137
Minimum0
Maximum2500
Zeros1556
Zeros (%)25.3%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:44.408289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum2500
Range2500
Interquartile range (IQR)0

Descriptive statistics

Standard deviation87.30888
Coefficient of variation (CV)25.111029
Kurtosis812.76069
Mean3.4769137
Median Absolute Deviation (MAD)0
Skewness28.467246
Sum5723
Variance7622.8405
MonotonicityNot monotonic
2024-05-11T15:19:44.617409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 1556
 
25.3%
1 25
 
0.4%
2 18
 
0.3%
3 14
 
0.2%
4 7
 
0.1%
5 6
 
0.1%
6 5
 
0.1%
7 3
 
< 0.1%
2500 2
 
< 0.1%
85 2
 
< 0.1%
Other values (8) 8
 
0.1%
(Missing) 4493
73.2%
ValueCountFrequency (%)
0 1556
25.3%
1 25
 
0.4%
2 18
 
0.3%
3 14
 
0.2%
4 7
 
0.1%
5 6
 
0.1%
6 5
 
0.1%
7 3
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
2500 2
< 0.1%
200 1
< 0.1%
85 2
< 0.1%
50 1
< 0.1%
28 1
< 0.1%
22 1
< 0.1%
14 1
< 0.1%
10 1
< 0.1%
9 1
< 0.1%
8 1
< 0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct18
Distinct (%)1.1%
Missing4502
Missing (%)73.3%
Infinite0
Infinite (%)0.0%
Mean0.47159438
Minimum0
Maximum200
Zeros1555
Zeros (%)25.3%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:44.821010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.2
Maximum200
Range200
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.2408823
Coefficient of variation (CV)13.233581
Kurtosis706.31957
Mean0.47159438
Median Absolute Deviation (MAD)0
Skewness24.727436
Sum772
Variance38.948612
MonotonicityNot monotonic
2024-05-11T15:19:45.011929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 1555
 
25.3%
1 24
 
0.4%
2 16
 
0.3%
3 13
 
0.2%
10 7
 
0.1%
4 5
 
0.1%
6 4
 
0.1%
5 2
 
< 0.1%
8 2
 
< 0.1%
11 1
 
< 0.1%
Other values (8) 8
 
0.1%
(Missing) 4502
73.3%
ValueCountFrequency (%)
0 1555
25.3%
1 24
 
0.4%
2 16
 
0.3%
3 13
 
0.2%
4 5
 
0.1%
5 2
 
< 0.1%
6 4
 
0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
10 7
 
0.1%
ValueCountFrequency (%)
200 1
 
< 0.1%
100 1
 
< 0.1%
90 1
 
< 0.1%
45 1
 
< 0.1%
39 1
 
< 0.1%
23 1
 
< 0.1%
20 1
 
< 0.1%
11 1
 
< 0.1%
10 7
0.1%
9 1
 
< 0.1%

공장생산직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.5%
Missing4510
Missing (%)73.5%
Infinite0
Infinite (%)0.0%
Mean0.2737876
Minimum0
Maximum400
Zeros1611
Zeros (%)26.2%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:45.205998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum400
Range400
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.916788
Coefficient of variation (CV)36.220735
Kurtosis1624.4639
Mean0.2737876
Median Absolute Deviation (MAD)0
Skewness40.277643
Sum446
Variance98.342685
MonotonicityNot monotonic
2024-05-11T15:19:45.427530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1611
 
26.2%
1 7
 
0.1%
3 3
 
< 0.1%
2 3
 
< 0.1%
4 2
 
< 0.1%
11 1
 
< 0.1%
5 1
 
< 0.1%
400 1
 
< 0.1%
(Missing) 4510
73.5%
ValueCountFrequency (%)
0 1611
26.2%
1 7
 
0.1%
2 3
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
11 1
 
< 0.1%
400 1
 
< 0.1%
ValueCountFrequency (%)
400 1
 
< 0.1%
11 1
 
< 0.1%
5 1
 
< 0.1%
4 2
 
< 0.1%
3 3
 
< 0.1%
2 3
 
< 0.1%
1 7
 
0.1%
0 1611
26.2%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.1 KiB
<NA>
3665 
자가
1332 
임대
1142 

Length

Max length4
Median length4
Mean length3.1940055
Min length2

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> 3665
59.7%
자가 1332
 
21.7%
임대 1142
 
18.6%

Length

2024-05-11T15:19:45.695463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:19:45.890500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3665
59.7%
자가 1332
 
21.7%
임대 1142
 
18.6%

보증액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct36
Distinct (%)2.8%
Missing4862
Missing (%)79.2%
Infinite0
Infinite (%)0.0%
Mean3976448.4
Minimum0
Maximum1.4 × 109
Zeros1185
Zeros (%)19.3%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:46.119674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7600000
Maximum1.4 × 109
Range1.4 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation51517013
Coefficient of variation (CV)12.955534
Kurtosis518.36882
Mean3976448.4
Median Absolute Deviation (MAD)0
Skewness21.727601
Sum5.0779246 × 109
Variance2.6540027 × 1015
MonotonicityNot monotonic
2024-05-11T15:19:46.367042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 1185
 
19.3%
10000000 18
 
0.3%
20000000 14
 
0.2%
5000000 11
 
0.2%
300000 5
 
0.1%
6000000 3
 
< 0.1%
7500000 3
 
< 0.1%
30000000 3
 
< 0.1%
15000000 3
 
< 0.1%
50000000 2
 
< 0.1%
Other values (26) 30
 
0.5%
(Missing) 4862
79.2%
ValueCountFrequency (%)
0 1185
19.3%
300000 5
 
0.1%
1000000 1
 
< 0.1%
1500000 1
 
< 0.1%
2200000 1
 
< 0.1%
4000000 1
 
< 0.1%
5000000 11
 
0.2%
6000000 3
 
< 0.1%
6500000 1
 
< 0.1%
7000000 1
 
< 0.1%
ValueCountFrequency (%)
1400000000 1
< 0.1%
888250000 1
< 0.1%
712400000 1
< 0.1%
200000000 1
< 0.1%
150000000 1
< 0.1%
139225600 1
< 0.1%
102804500 2
< 0.1%
100000000 1
< 0.1%
70000000 1
< 0.1%
60000000 2
< 0.1%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct43
Distinct (%)3.4%
Missing4865
Missing (%)79.2%
Infinite0
Infinite (%)0.0%
Mean123339.45
Minimum0
Maximum13922560
Zeros1187
Zeros (%)19.3%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:46.606785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile507000
Maximum13922560
Range13922560
Interquartile range (IQR)0

Descriptive statistics

Standard deviation802013.14
Coefficient of variation (CV)6.5024867
Kurtosis154.27626
Mean123339.45
Median Absolute Deviation (MAD)0
Skewness11.315212
Sum1.5713446 × 108
Variance6.4322507 × 1011
MonotonicityNot monotonic
2024-05-11T15:19:46.875599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 1187
 
19.3%
800000 8
 
0.1%
100000 7
 
0.1%
2000000 5
 
0.1%
500000 5
 
0.1%
200000 5
 
0.1%
600000 4
 
0.1%
2200000 3
 
< 0.1%
1050000 3
 
< 0.1%
6000000 3
 
< 0.1%
Other values (33) 44
 
0.7%
(Missing) 4865
79.2%
ValueCountFrequency (%)
0 1187
19.3%
50000 1
 
< 0.1%
100000 7
 
0.1%
150000 1
 
< 0.1%
200000 5
 
0.1%
220000 1
 
< 0.1%
350000 1
 
< 0.1%
400000 2
 
< 0.1%
500000 5
 
0.1%
520000 1
 
< 0.1%
ValueCountFrequency (%)
13922560 1
 
< 0.1%
12028000 1
 
< 0.1%
10280450 2
< 0.1%
6000000 3
< 0.1%
5000000 1
 
< 0.1%
3400000 1
 
< 0.1%
3200000 1
 
< 0.1%
2900000 1
 
< 0.1%
2848000 1
 
< 0.1%
2700000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing2249
Missing (%)36.6%
Memory size12.1 KiB
False
3890 
(Missing)
2249 
ValueCountFrequency (%)
False 3890
63.4%
(Missing) 2249
36.6%
2024-05-11T15:19:47.056905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct399
Distinct (%)10.3%
Missing2249
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean19.029452
Minimum0
Maximum8294.38
Zeros3207
Zeros (%)52.2%
Negative0
Negative (%)0.0%
Memory size54.1 KiB
2024-05-11T15:19:47.230518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile102.359
Maximum8294.38
Range8294.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation153.59927
Coefficient of variation (CV)8.0716599
Kurtosis2177.9206
Mean19.029452
Median Absolute Deviation (MAD)0
Skewness41.589097
Sum74024.57
Variance23592.735
MonotonicityNot monotonic
2024-05-11T15:19:47.484323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3207
52.2%
3.3 55
 
0.9%
33.0 29
 
0.5%
10.0 23
 
0.4%
30.0 11
 
0.2%
6.6 10
 
0.2%
66.0 10
 
0.2%
16.5 10
 
0.2%
4.0 10
 
0.2%
20.0 10
 
0.2%
Other values (389) 515
 
8.4%
(Missing) 2249
36.6%
ValueCountFrequency (%)
0.0 3207
52.2%
1.0 1
 
< 0.1%
1.3 1
 
< 0.1%
1.44 2
 
< 0.1%
1.65 4
 
0.1%
2.0 5
 
0.1%
2.6 1
 
< 0.1%
3.0 8
 
0.1%
3.3 55
 
0.9%
3.4 1
 
< 0.1%
ValueCountFrequency (%)
8294.38 1
< 0.1%
1867.2 1
< 0.1%
1475.65 1
< 0.1%
1254.0 1
< 0.1%
1093.33 1
< 0.1%
967.73 1
< 0.1%
890.41 1
< 0.1%
857.36 1
< 0.1%
847.75 1
< 0.1%
729.0 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6139
Missing (%)100.0%
Memory size54.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6139
Missing (%)100.0%
Memory size54.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6139
Missing (%)100.0%
Memory size54.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030400003040000-135-2023-000022023-02-28<NA>3폐업2폐업2024-01-19<NA><NA><NA><NA><NA>143-890서울특별시 광진구 중곡동 ***-** ***호서울특별시 광진구 용마산로 **, ***호 (중곡동)4931국메디앙스 주식회사2024-01-19 09:43:34U2023-11-30 22:01:00.0건강기능식품유통전문판매업207714.297453450297.069529<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
132200003220000-135-2023-000202023-02-28<NA>3폐업2폐업2024-04-19<NA><NA><NA><NA>2.20135-516서울특별시 강남구 일원동 *** 남경빌딩서울특별시 강남구 일원로 **, 남경빌딩 지상*층 ****호 (일원동)6343닥터블릿헬스케어 주식회사2024-04-19 11:03:27U2023-12-03 22:01:00.0건강기능식품유통전문판매업207112.195695443163.101895<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
232100003210000-135-2024-000182024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-857서울특별시 서초구 서초동 ****-** BNK디지털타워 ***호서울특별시 서초구 서초대로 ***, BNK디지털타워 ***호 (서초동)6619라운드포 주식회사2024-04-09 09:37:31I2023-12-03 23:01:00.0건강기능식품유통전문판매업202152.435829443826.911881<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
330300003030000-135-2012-000032012-02-08<NA>1영업/정상1영업<NA><NA><NA><NA>070 88505130<NA>133-834서울특별시 성동구 성수동*가 ***-**서울특별시 성동구 아차산로*길 **, *층 *-*호 (성수동*가)4795(주)오하나2024-01-29 17:08:25U2023-11-30 21:01:00.0건강기능식품유통전문판매업204848.299602449551.236386<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430400003040000-135-2012-000072012-02-08<NA>3폐업2폐업2023-02-28<NA><NA><NA>070 88505130<NA>143-841서울특별시 광진구 자양동 **-*서울특별시 광진구 아차산로**길 **, *층 ***호 (자양동)5072(주)오하나2023-02-28 15:19:30U2022-12-03 00:03:00.0건강기능식품유통전문판매업205744.438483448699.898787<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
531500003150000-135-2018-000132018-03-09<NA>3폐업2폐업2023-02-28<NA><NA><NA>02 7866771<NA>157-905서울특별시 강서구 화곡동 ***-* 동양하우징 ***동 ***호서울특별시 강서구 곰달래로**길 **, 동양하우징 ***동 *층 ***호 (화곡동, 동양하우징)7747(주)윈사이트2023-03-04 11:09:45U2022-12-03 00:06:00.0건강기능식품유통전문판매업187120.042929447941.386443<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
632400003240000-135-2023-000022023-03-06<NA>3폐업2폐업2024-01-08<NA><NA><NA>02 557 05010.00134-851서울특별시 강동구 성내동 ***서울특별시 강동구 성내로 **, ***호 (성내동)5399주식회사 코벨트2024-01-08 17:41:54U2023-11-30 23:00:00.0건강기능식품유통전문판매업211087.676152447317.959443<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
730000003000000-135-2011-0000120110211<NA>3폐업2폐업20211123<NA><NA><NA>02 747 3839134.60110500서울특별시 종로구 이화동 ***-* *층서울특별시 종로구 율곡로 ***-* (이화동,*층)3100(주)어생당2021-11-23 17:32:05U2021-11-25 02:40:00.0건강기능식품유통전문판매업200184.037836452702.513467건강기능식품유통전문판매업00<NA><NA><NA>00000임대00N0.0<NA><NA><NA>
831300003130000-135-2022-000262022-08-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>121-843서울특별시 마포구 성산동 **-**서울특별시 마포구 월드컵북로 ***, *층 (성산동)3972(주)대한월드무역공사2023-03-06 14:58:23I2022-12-03 00:08:00.0건강기능식품유통전문판매업192212.251351451389.941892<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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