Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells106430
Missing cells (%)24.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory383.0 B

Variable types

Numeric8
Text7
DateTime4
Unsupported7
Categorical17
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-16067/S/1/datasetView.do

Alerts

영업장주변구분명 is highly imbalanced (70.1%)Imbalance
등급구분명 is highly imbalanced (71.1%)Imbalance
급수시설구분명 is highly imbalanced (56.6%)Imbalance
총인원 is highly imbalanced (54.5%)Imbalance
공장사무직종업원수 is highly imbalanced (54.5%)Imbalance
공장판매직종업원수 is highly imbalanced (54.5%)Imbalance
공장생산직종업원수 is highly imbalanced (54.5%)Imbalance
건물소유구분명 is highly imbalanced (76.0%)Imbalance
보증액 is highly imbalanced (58.1%)Imbalance
월세액 is highly imbalanced (62.3%)Imbalance
다중이용업소여부 is highly imbalanced (98.1%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 5707 (57.1%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 1387 (13.9%) missing valuesMissing
소재지면적 has 1317 (13.2%) missing valuesMissing
도로명주소 has 1442 (14.4%) missing valuesMissing
도로명우편번호 has 1618 (16.2%) missing valuesMissing
좌표정보(X) has 285 (2.9%) missing valuesMissing
좌표정보(Y) has 285 (2.9%) missing valuesMissing
남성종사자수 has 7560 (75.6%) missing valuesMissing
여성종사자수 has 7544 (75.4%) missing valuesMissing
본사종업원수 has 4562 (45.6%) missing valuesMissing
다중이용업소여부 has 2332 (23.3%) missing valuesMissing
시설총규모 has 2332 (23.3%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
본사종업원수 is highly skewed (γ1 = 26.47516966)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
남성종사자수 has 2381 (23.8%) zerosZeros
여성종사자수 has 2254 (22.5%) zerosZeros
본사종업원수 has 5028 (50.3%) zerosZeros
시설총규모 has 2356 (23.6%) zerosZeros

Reproduction

Analysis started2024-05-11 03:43:41.988047
Analysis finished2024-05-11 03:43:48.490364
Duration6.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3132507
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:43:48.694195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13070000
median3140000
Q33200000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)130000

Descriptive statistics

Standard deviation71684.3
Coefficient of variation (CV)0.022884003
Kurtosis-1.1242053
Mean3132507
Median Absolute Deviation (MAD)60000
Skewness-0.23127189
Sum3.132507 × 1010
Variance5.1386388 × 109
MonotonicityNot monotonic
2024-05-11T03:43:49.150960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 744
 
7.4%
3180000 556
 
5.6%
3150000 551
 
5.5%
3230000 541
 
5.4%
3100000 504
 
5.0%
3210000 504
 
5.0%
3170000 461
 
4.6%
3110000 448
 
4.5%
3070000 435
 
4.3%
3160000 430
 
4.3%
Other values (15) 4826
48.3%
ValueCountFrequency (%)
3000000 337
3.4%
3010000 353
3.5%
3020000 272
2.7%
3030000 318
3.2%
3040000 268
2.7%
3050000 312
3.1%
3060000 302
3.0%
3070000 435
4.3%
3080000 262
2.6%
3090000 313
3.1%
ValueCountFrequency (%)
3240000 416
4.2%
3230000 541
5.4%
3220000 744
7.4%
3210000 504
5.0%
3200000 330
3.3%
3190000 299
3.0%
3180000 556
5.6%
3170000 461
4.6%
3160000 430
4.3%
3150000 551
5.5%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T03:43:49.778095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3100000-105-2010-00002
2nd row3170000-105-2003-00010
3rd row3100000-105-2016-00001
4th row3140000-105-1992-00007
5th row3030000-105-2020-00004
ValueCountFrequency (%)
3100000-105-2010-00002 1
 
< 0.1%
3000000-105-1981-00002 1
 
< 0.1%
3030000-105-2005-00030 1
 
< 0.1%
3060000-105-2006-00013 1
 
< 0.1%
3010000-105-2003-00007 1
 
< 0.1%
3230000-105-2022-00016 1
 
< 0.1%
3130000-105-2005-00017 1
 
< 0.1%
3210000-105-2014-00017 1
 
< 0.1%
3130000-105-2000-00062 1
 
< 0.1%
3020000-105-2017-00006 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T03:43:51.535217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 102319
46.5%
- 30000
 
13.6%
1 25760
 
11.7%
2 15969
 
7.3%
3 13978
 
6.4%
5 13856
 
6.3%
9 6282
 
2.9%
4 3387
 
1.5%
8 2955
 
1.3%
7 2805
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 102319
53.9%
1 25760
 
13.6%
2 15969
 
8.4%
3 13978
 
7.4%
5 13856
 
7.3%
9 6282
 
3.3%
4 3387
 
1.8%
8 2955
 
1.6%
7 2805
 
1.5%
6 2689
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 102319
46.5%
- 30000
 
13.6%
1 25760
 
11.7%
2 15969
 
7.3%
3 13978
 
6.4%
5 13856
 
6.3%
9 6282
 
2.9%
4 3387
 
1.5%
8 2955
 
1.3%
7 2805
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 102319
46.5%
- 30000
 
13.6%
1 25760
 
11.7%
2 15969
 
7.3%
3 13978
 
6.4%
5 13856
 
6.3%
9 6282
 
2.9%
4 3387
 
1.5%
8 2955
 
1.3%
7 2805
 
1.3%
Distinct4975
Distinct (%)49.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1960-01-04 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T03:43:52.168448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:43:52.753963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5707 
3
4293 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 5707
57.1%
3 4293
42.9%

Length

2024-05-11T03:43:53.335373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:43:53.756430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5707
57.1%
3 4293
42.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
5707 
폐업
4293 

Length

Max length5
Median length5
Mean length3.7121
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 5707
57.1%
폐업 4293
42.9%

Length

2024-05-11T03:43:54.306816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:43:54.783616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 5707
57.1%
폐업 4293
42.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5707 
2
4293 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 5707
57.1%
2 4293
42.9%

Length

2024-05-11T03:43:55.267690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:43:55.610635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5707
57.1%
2 4293
42.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업
5707 
폐업
4293 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 5707
57.1%
폐업 4293
42.9%

Length

2024-05-11T03:43:56.016221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:43:56.406965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 5707
57.1%
폐업 4293
42.9%

폐업일자
Date

MISSING 

Distinct2746
Distinct (%)64.0%
Missing5707
Missing (%)57.1%
Memory size156.2 KiB
Minimum1990-12-31 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T03:43:56.856862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:43:57.280396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct8102
Distinct (%)94.1%
Missing1387
Missing (%)13.9%
Memory size156.2 KiB
2024-05-11T03:43:58.116968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.358876
Min length1

Characters and Unicode

Total characters89221
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

Unique7746 ?
Unique (%)89.9%

Sample

1st row02 9365999
2nd row02 9503106
3rd row0226441313
4th row0222963990
5th row02 8264503
ValueCountFrequency (%)
02 5595
35.3%
070 59
 
0.4%
0 27
 
0.2%
428 13
 
0.1%
401 12
 
0.1%
400 12
 
0.1%
406 11
 
0.1%
403 11
 
0.1%
474 11
 
0.1%
430 10
 
0.1%
Other values (8454) 10091
63.7%
2024-05-11T03:43:59.231129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15948
17.9%
2 15690
17.6%
9707
10.9%
3 6742
7.6%
1 6385
7.2%
6 6067
 
6.8%
4 5938
 
6.7%
5 5914
 
6.6%
9 5821
 
6.5%
7 5650
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79514
89.1%
Space Separator 9707
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15948
20.1%
2 15690
19.7%
3 6742
8.5%
1 6385
8.0%
6 6067
 
7.6%
4 5938
 
7.5%
5 5914
 
7.4%
9 5821
 
7.3%
7 5650
 
7.1%
8 5359
 
6.7%
Space Separator
ValueCountFrequency (%)
9707
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 89221
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15948
17.9%
2 15690
17.6%
9707
10.9%
3 6742
7.6%
1 6385
7.2%
6 6067
 
6.8%
4 5938
 
6.7%
5 5914
 
6.6%
9 5821
 
6.5%
7 5650
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15948
17.9%
2 15690
17.6%
9707
10.9%
3 6742
7.6%
1 6385
7.2%
6 6067
 
6.8%
4 5938
 
6.7%
5 5914
 
6.6%
9 5821
 
6.5%
7 5650
 
6.3%

소재지면적
Text

MISSING 

Distinct4120
Distinct (%)47.4%
Missing1317
Missing (%)13.2%
Memory size156.2 KiB
2024-05-11T03:44:00.023576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length4.9875619
Min length3

Characters and Unicode

Total characters43307
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

Unique3171 ?
Unique (%)36.5%

Sample

1st row3.30
2nd row155.36
3rd row.00
4th row56.27
5th row8.90
ValueCountFrequency (%)
00 1344
 
15.5%
0.00 194
 
2.2%
16.50 93
 
1.1%
33.00 87
 
1.0%
10.00 86
 
1.0%
9.90 63
 
0.7%
13.20 61
 
0.7%
12.00 60
 
0.7%
15.00 57
 
0.7%
20.00 47
 
0.5%
Other values (4110) 6591
75.9%
2024-05-11T03:44:01.207186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11099
25.6%
. 8683
20.0%
1 4381
 
10.1%
2 3151
 
7.3%
3 2646
 
6.1%
5 2512
 
5.8%
6 2453
 
5.7%
4 2309
 
5.3%
8 2178
 
5.0%
9 1992
 
4.6%
Other values (2) 1903
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34500
79.7%
Other Punctuation 8807
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11099
32.2%
1 4381
 
12.7%
2 3151
 
9.1%
3 2646
 
7.7%
5 2512
 
7.3%
6 2453
 
7.1%
4 2309
 
6.7%
8 2178
 
6.3%
9 1992
 
5.8%
7 1779
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 8683
98.6%
, 124
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 43307
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11099
25.6%
. 8683
20.0%
1 4381
 
10.1%
2 3151
 
7.3%
3 2646
 
6.1%
5 2512
 
5.8%
6 2453
 
5.7%
4 2309
 
5.3%
8 2178
 
5.0%
9 1992
 
4.6%
Other values (2) 1903
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11099
25.6%
. 8683
20.0%
1 4381
 
10.1%
2 3151
 
7.3%
3 2646
 
6.1%
5 2512
 
5.8%
6 2453
 
5.7%
4 2309
 
5.3%
8 2178
 
5.0%
9 1992
 
4.6%
Other values (2) 1903
 
4.4%
Distinct3227
Distinct (%)32.4%
Missing30
Missing (%)0.3%
Memory size156.2 KiB
2024-05-11T03:44:02.022566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1687061
Min length6

Characters and Unicode

Total characters61502
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

Unique1267 ?
Unique (%)12.7%

Sample

1st row139816
2nd row153030
3rd row139831
4th row158819
5th row133-858
ValueCountFrequency (%)
153803 80
 
0.8%
153801 53
 
0.5%
122200 44
 
0.4%
157930 42
 
0.4%
153802 42
 
0.4%
157210 35
 
0.4%
152848 34
 
0.3%
158070 33
 
0.3%
157-210 32
 
0.3%
139800 31
 
0.3%
Other values (3217) 9544
95.7%
2024-05-11T03:44:03.072077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13952
22.7%
8 9227
15.0%
3 7583
12.3%
0 7363
12.0%
5 5596
9.1%
2 4941
 
8.0%
4 3203
 
5.2%
7 2997
 
4.9%
9 2543
 
4.1%
6 2415
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59820
97.3%
Dash Punctuation 1682
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13952
23.3%
8 9227
15.4%
3 7583
12.7%
0 7363
12.3%
5 5596
9.4%
2 4941
 
8.3%
4 3203
 
5.4%
7 2997
 
5.0%
9 2543
 
4.3%
6 2415
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 1682
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61502
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13952
22.7%
8 9227
15.0%
3 7583
12.3%
0 7363
12.0%
5 5596
9.1%
2 4941
 
8.0%
4 3203
 
5.2%
7 2997
 
4.9%
9 2543
 
4.1%
6 2415
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61502
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13952
22.7%
8 9227
15.0%
3 7583
12.3%
0 7363
12.0%
5 5596
9.1%
2 4941
 
8.0%
4 3203
 
5.2%
7 2997
 
4.9%
9 2543
 
4.1%
6 2415
 
3.9%
Distinct9324
Distinct (%)93.5%
Missing29
Missing (%)0.3%
Memory size156.2 KiB
2024-05-11T03:44:03.769091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length49
Mean length25.097683
Min length6

Characters and Unicode

Total characters250249
Distinct characters609
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

Unique8805 ?
Unique (%)88.3%

Sample

1st row서울특별시 노원구 상계동 320-1
2nd row서울특별시 금천구 시흥동 1020번지
3rd row서울특별시 노원구 상계동 772
4th row서울특별시 양천구 목동 793-3번지
5th row서울특별시 성동구 하왕십리동 976-13 신영어린이집
ValueCountFrequency (%)
서울특별시 9970
 
21.3%
강남구 741
 
1.6%
영등포구 552
 
1.2%
강서구 551
 
1.2%
송파구 541
 
1.2%
서초구 505
 
1.1%
노원구 502
 
1.1%
금천구 461
 
1.0%
1층 459
 
1.0%
지하1층 445
 
0.9%
Other values (10721) 32155
68.6%
2024-05-11T03:44:05.284922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44425
 
17.8%
11990
 
4.8%
11761
 
4.7%
10848
 
4.3%
10238
 
4.1%
10207
 
4.1%
10002
 
4.0%
9976
 
4.0%
1 9612
 
3.8%
8598
 
3.4%
Other values (599) 112592
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151175
60.4%
Decimal Number 44520
 
17.8%
Space Separator 44425
 
17.8%
Dash Punctuation 7862
 
3.1%
Open Punctuation 704
 
0.3%
Close Punctuation 703
 
0.3%
Uppercase Letter 490
 
0.2%
Other Punctuation 239
 
0.1%
Lowercase Letter 87
 
< 0.1%
Math Symbol 36
 
< 0.1%
Other values (2) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11990
 
7.9%
11761
 
7.8%
10848
 
7.2%
10238
 
6.8%
10207
 
6.8%
10002
 
6.6%
9976
 
6.6%
8598
 
5.7%
6568
 
4.3%
2332
 
1.5%
Other values (533) 58655
38.8%
Uppercase Letter
ValueCountFrequency (%)
B 54
11.0%
S 52
10.6%
C 48
 
9.8%
K 48
 
9.8%
D 33
 
6.7%
A 29
 
5.9%
M 27
 
5.5%
T 26
 
5.3%
L 23
 
4.7%
G 22
 
4.5%
Other values (14) 128
26.1%
Lowercase Letter
ValueCountFrequency (%)
e 25
28.7%
n 11
12.6%
i 9
 
10.3%
o 7
 
8.0%
r 5
 
5.7%
t 5
 
5.7%
a 4
 
4.6%
l 4
 
4.6%
s 4
 
4.6%
y 3
 
3.4%
Other values (5) 10
 
11.5%
Decimal Number
ValueCountFrequency (%)
1 9612
21.6%
2 5982
13.4%
3 4667
10.5%
0 4487
10.1%
4 3962
8.9%
5 3665
 
8.2%
6 3634
 
8.2%
7 3192
 
7.2%
8 2720
 
6.1%
9 2599
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 197
82.4%
@ 16
 
6.7%
. 10
 
4.2%
& 9
 
3.8%
? 5
 
2.1%
1
 
0.4%
/ 1
 
0.4%
Letter Number
ValueCountFrequency (%)
4
57.1%
2
28.6%
1
 
14.3%
Math Symbol
ValueCountFrequency (%)
~ 35
97.2%
+ 1
 
2.8%
Space Separator
ValueCountFrequency (%)
44425
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7862
100.0%
Open Punctuation
ValueCountFrequency (%)
( 704
100.0%
Close Punctuation
ValueCountFrequency (%)
) 703
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151176
60.4%
Common 98489
39.4%
Latin 584
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11990
 
7.9%
11761
 
7.8%
10848
 
7.2%
10238
 
6.8%
10207
 
6.8%
10002
 
6.6%
9976
 
6.6%
8598
 
5.7%
6568
 
4.3%
2332
 
1.5%
Other values (534) 58656
38.8%
Latin
ValueCountFrequency (%)
B 54
 
9.2%
S 52
 
8.9%
C 48
 
8.2%
K 48
 
8.2%
D 33
 
5.7%
A 29
 
5.0%
M 27
 
4.6%
T 26
 
4.5%
e 25
 
4.3%
L 23
 
3.9%
Other values (32) 219
37.5%
Common
ValueCountFrequency (%)
44425
45.1%
1 9612
 
9.8%
- 7862
 
8.0%
2 5982
 
6.1%
3 4667
 
4.7%
0 4487
 
4.6%
4 3962
 
4.0%
5 3665
 
3.7%
6 3634
 
3.7%
7 3192
 
3.2%
Other values (13) 7001
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151175
60.4%
ASCII 99065
39.6%
Number Forms 7
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44425
44.8%
1 9612
 
9.7%
- 7862
 
7.9%
2 5982
 
6.0%
3 4667
 
4.7%
0 4487
 
4.5%
4 3962
 
4.0%
5 3665
 
3.7%
6 3634
 
3.7%
7 3192
 
3.2%
Other values (51) 7577
 
7.6%
Hangul
ValueCountFrequency (%)
11990
 
7.9%
11761
 
7.8%
10848
 
7.2%
10238
 
6.8%
10207
 
6.8%
10002
 
6.6%
9976
 
6.6%
8598
 
5.7%
6568
 
4.3%
2332
 
1.5%
Other values (533) 58655
38.8%
Number Forms
ValueCountFrequency (%)
4
57.1%
2
28.6%
1
 
14.3%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명주소
Text

MISSING 

Distinct8021
Distinct (%)93.7%
Missing1442
Missing (%)14.4%
Memory size156.2 KiB
2024-05-11T03:44:06.406511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length60
Mean length30.467749
Min length19

Characters and Unicode

Total characters260743
Distinct characters637
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

Unique7585 ?
Unique (%)88.6%

Sample

1st row서울특별시 노원구 노원로30길 45 (상계동)
2nd row서울특별시 금천구 시흥대로73길 70 (시흥동)
3rd row서울특별시 노원구 덕릉로70길 99 (상계동)
4th row서울특별시 양천구 등촌로 22 (목동)
5th row서울특별시 성동구 무학봉16길 9-3, 지하1층 (하왕십리동)
ValueCountFrequency (%)
서울특별시 8558
 
17.2%
1층 823
 
1.6%
강남구 591
 
1.2%
지하1층 507
 
1.0%
강서구 494
 
1.0%
송파구 483
 
1.0%
영등포구 458
 
0.9%
노원구 436
 
0.9%
서초구 422
 
0.8%
은평구 407
 
0.8%
Other values (8660) 36705
73.6%
2024-05-11T03:44:08.562130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41341
 
15.9%
11198
 
4.3%
10757
 
4.1%
9421
 
3.6%
9254
 
3.5%
8971
 
3.4%
( 8878
 
3.4%
) 8878
 
3.4%
8823
 
3.4%
8600
 
3.3%
Other values (627) 134622
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 158822
60.9%
Space Separator 41341
 
15.9%
Decimal Number 35362
 
13.6%
Open Punctuation 8879
 
3.4%
Close Punctuation 8879
 
3.4%
Other Punctuation 5712
 
2.2%
Dash Punctuation 1046
 
0.4%
Uppercase Letter 529
 
0.2%
Lowercase Letter 94
 
< 0.1%
Math Symbol 72
 
< 0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11198
 
7.1%
10757
 
6.8%
9421
 
5.9%
9254
 
5.8%
8971
 
5.6%
8823
 
5.6%
8600
 
5.4%
8565
 
5.4%
4832
 
3.0%
3443
 
2.2%
Other values (558) 74958
47.2%
Uppercase Letter
ValueCountFrequency (%)
B 75
14.2%
S 54
 
10.2%
C 48
 
9.1%
K 46
 
8.7%
D 36
 
6.8%
A 36
 
6.8%
M 28
 
5.3%
L 26
 
4.9%
T 23
 
4.3%
H 20
 
3.8%
Other values (14) 137
25.9%
Lowercase Letter
ValueCountFrequency (%)
e 28
29.8%
n 12
12.8%
i 9
 
9.6%
o 7
 
7.4%
r 6
 
6.4%
t 6
 
6.4%
s 4
 
4.3%
l 4
 
4.3%
a 4
 
4.3%
y 3
 
3.2%
Other values (6) 11
 
11.7%
Decimal Number
ValueCountFrequency (%)
1 8482
24.0%
2 5381
15.2%
3 4098
11.6%
4 3233
 
9.1%
5 2947
 
8.3%
6 2549
 
7.2%
0 2456
 
6.9%
7 2297
 
6.5%
8 2016
 
5.7%
9 1903
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 5672
99.3%
@ 13
 
0.2%
. 12
 
0.2%
& 9
 
0.2%
/ 2
 
< 0.1%
? 2
 
< 0.1%
1
 
< 0.1%
* 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 8878
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 8878
> 99.9%
] 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 71
98.6%
+ 1
 
1.4%
Letter Number
ValueCountFrequency (%)
4
66.7%
2
33.3%
Space Separator
ValueCountFrequency (%)
41341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1046
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 158823
60.9%
Common 101291
38.8%
Latin 629
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11198
 
7.1%
10757
 
6.8%
9421
 
5.9%
9254
 
5.8%
8971
 
5.6%
8823
 
5.6%
8600
 
5.4%
8565
 
5.4%
4832
 
3.0%
3443
 
2.2%
Other values (559) 74959
47.2%
Latin
ValueCountFrequency (%)
B 75
 
11.9%
S 54
 
8.6%
C 48
 
7.6%
K 46
 
7.3%
D 36
 
5.7%
A 36
 
5.7%
M 28
 
4.5%
e 28
 
4.5%
L 26
 
4.1%
T 23
 
3.7%
Other values (32) 229
36.4%
Common
ValueCountFrequency (%)
41341
40.8%
( 8878
 
8.8%
) 8878
 
8.8%
1 8482
 
8.4%
, 5672
 
5.6%
2 5381
 
5.3%
3 4098
 
4.0%
4 3233
 
3.2%
5 2947
 
2.9%
6 2549
 
2.5%
Other values (16) 9832
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 158822
60.9%
ASCII 101913
39.1%
Number Forms 6
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41341
40.6%
( 8878
 
8.7%
) 8878
 
8.7%
1 8482
 
8.3%
, 5672
 
5.6%
2 5381
 
5.3%
3 4098
 
4.0%
4 3233
 
3.2%
5 2947
 
2.9%
6 2549
 
2.5%
Other values (55) 10454
 
10.3%
Hangul
ValueCountFrequency (%)
11198
 
7.1%
10757
 
6.8%
9421
 
5.9%
9254
 
5.8%
8971
 
5.6%
8823
 
5.6%
8600
 
5.4%
8565
 
5.4%
4832
 
3.0%
3443
 
2.2%
Other values (558) 74958
47.2%
Number Forms
ValueCountFrequency (%)
4
66.7%
2
33.3%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct3650
Distinct (%)43.5%
Missing1618
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean5157.1008
Minimum1000
Maximum8866
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:44:09.173471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1406.15
Q13159.25
median5269
Q37261
95-th percentile8590
Maximum8866
Range7866
Interquartile range (IQR)4101.75

Descriptive statistics

Standard deviation2302.5895
Coefficient of variation (CV)0.44648914
Kurtosis-1.2115906
Mean5157.1008
Median Absolute Deviation (MAD)2029.5
Skewness-0.10415698
Sum43226819
Variance5301918.5
MonotonicityNot monotonic
2024-05-11T03:44:09.802260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7505 19
 
0.2%
3722 19
 
0.2%
1772 16
 
0.2%
3322 16
 
0.2%
3428 15
 
0.1%
5510 15
 
0.1%
6593 13
 
0.1%
7233 11
 
0.1%
8592 11
 
0.1%
2447 11
 
0.1%
Other values (3640) 8236
82.4%
(Missing) 1618
 
16.2%
ValueCountFrequency (%)
1000 2
< 0.1%
1001 1
 
< 0.1%
1002 2
< 0.1%
1003 1
 
< 0.1%
1005 3
< 0.1%
1006 2
< 0.1%
1007 2
< 0.1%
1012 3
< 0.1%
1014 4
< 0.1%
1015 2
< 0.1%
ValueCountFrequency (%)
8866 2
 
< 0.1%
8865 1
 
< 0.1%
8864 2
 
< 0.1%
8863 1
 
< 0.1%
8861 1
 
< 0.1%
8860 2
 
< 0.1%
8859 9
0.1%
8858 3
 
< 0.1%
8857 1
 
< 0.1%
8856 1
 
< 0.1%
Distinct8580
Distinct (%)85.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T03:44:10.672739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length33
Mean length8.3739
Min length2

Characters and Unicode

Total characters83739
Distinct characters777
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7565 ?
Unique (%)75.6%

Sample

1st row양지유치원
2nd row오류자료
3rd row서울시립노원청소년센터
4th row제성병원
5th row왕십리하나어린이집 구내식당
ValueCountFrequency (%)
어린이집 415
 
3.4%
구립 187
 
1.5%
주식회사 113
 
0.9%
구내식당 69
 
0.6%
직원식당 50
 
0.4%
서초구립 42
 
0.3%
의료법인 30
 
0.2%
서울특별시 28
 
0.2%
요양병원 25
 
0.2%
유치원 20
 
0.2%
Other values (8914) 11164
91.9%
2024-05-11T03:44:12.115335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4159
 
5.0%
3657
 
4.4%
3395
 
4.1%
3378
 
4.0%
2664
 
3.2%
2159
 
2.6%
2144
 
2.6%
1972
 
2.4%
1713
 
2.0%
) 1369
 
1.6%
Other values (767) 57129
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77536
92.6%
Space Separator 2145
 
2.6%
Close Punctuation 1369
 
1.6%
Open Punctuation 1353
 
1.6%
Uppercase Letter 694
 
0.8%
Decimal Number 353
 
0.4%
Lowercase Letter 160
 
0.2%
Other Punctuation 93
 
0.1%
Dash Punctuation 30
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4159
 
5.4%
3657
 
4.7%
3395
 
4.4%
3378
 
4.4%
2664
 
3.4%
2159
 
2.8%
1972
 
2.5%
1713
 
2.2%
1359
 
1.8%
1261
 
1.6%
Other values (697) 51819
66.8%
Uppercase Letter
ValueCountFrequency (%)
S 106
15.3%
K 87
12.5%
G 51
 
7.3%
C 50
 
7.2%
L 47
 
6.8%
D 42
 
6.1%
I 37
 
5.3%
B 36
 
5.2%
T 33
 
4.8%
A 28
 
4.0%
Other values (14) 177
25.5%
Lowercase Letter
ValueCountFrequency (%)
e 24
15.0%
s 20
12.5%
t 13
8.1%
a 13
8.1%
m 11
 
6.9%
r 11
 
6.9%
i 11
 
6.9%
n 10
 
6.2%
u 8
 
5.0%
o 7
 
4.4%
Other values (11) 32
20.0%
Decimal Number
ValueCountFrequency (%)
2 101
28.6%
1 91
25.8%
3 46
13.0%
5 27
 
7.6%
4 24
 
6.8%
0 21
 
5.9%
7 13
 
3.7%
6 12
 
3.4%
9 9
 
2.5%
8 9
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 30
32.3%
. 29
31.2%
& 21
22.6%
? 7
 
7.5%
! 4
 
4.3%
1
 
1.1%
/ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
2144
> 99.9%
  1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 1369
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1353
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77536
92.6%
Common 5347
 
6.4%
Latin 856
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4159
 
5.4%
3657
 
4.7%
3395
 
4.4%
3378
 
4.4%
2664
 
3.4%
2159
 
2.8%
1972
 
2.5%
1713
 
2.2%
1359
 
1.8%
1261
 
1.6%
Other values (697) 51819
66.8%
Latin
ValueCountFrequency (%)
S 106
 
12.4%
K 87
 
10.2%
G 51
 
6.0%
C 50
 
5.8%
L 47
 
5.5%
D 42
 
4.9%
I 37
 
4.3%
B 36
 
4.2%
T 33
 
3.9%
A 28
 
3.3%
Other values (37) 339
39.6%
Common
ValueCountFrequency (%)
2144
40.1%
) 1369
25.6%
( 1353
25.3%
2 101
 
1.9%
1 91
 
1.7%
3 46
 
0.9%
- 30
 
0.6%
, 30
 
0.6%
. 29
 
0.5%
5 27
 
0.5%
Other values (13) 127
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77536
92.6%
ASCII 6199
 
7.4%
None 2
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4159
 
5.4%
3657
 
4.7%
3395
 
4.4%
3378
 
4.4%
2664
 
3.4%
2159
 
2.8%
1972
 
2.5%
1713
 
2.2%
1359
 
1.8%
1261
 
1.6%
Other values (697) 51819
66.8%
ASCII
ValueCountFrequency (%)
2144
34.6%
) 1369
22.1%
( 1353
21.8%
S 106
 
1.7%
2 101
 
1.6%
1 91
 
1.5%
K 87
 
1.4%
G 51
 
0.8%
C 50
 
0.8%
L 47
 
0.8%
Other values (56) 800
 
12.9%
None
ValueCountFrequency (%)
  1
50.0%
1
50.0%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct9081
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-26 00:00:00
Maximum2024-05-09 16:51:31
2024-05-11T03:44:12.663661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:44:13.240542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
5336 
U
4664 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 5336
53.4%
U 4664
46.6%

Length

2024-05-11T03:44:13.800269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:14.177863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5336
53.4%
u 4664
46.6%
Distinct1512
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T03:44:15.060327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:44:15.559037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
어린이집
3490 
집단급식소
2196 
학교
1424 
산업체
1115 
병원
660 
Other values (6)
1115 

Length

Max length8
Median length6
Mean length3.8653
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row어린이집
2nd row집단급식소
3rd row수련원
4th row집단급식소
5th row어린이집

Common Values

ValueCountFrequency (%)
어린이집 3490
34.9%
집단급식소 2196
22.0%
학교 1424
14.2%
산업체 1115
 
11.2%
병원 660
 
6.6%
사회복지시설 511
 
5.1%
공공기관 348
 
3.5%
기타 집단급식소 194
 
1.9%
기숙사 36
 
0.4%
수련원 24
 
0.2%

Length

2024-05-11T03:44:16.300730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
어린이집 3490
34.2%
집단급식소 2390
23.4%
학교 1424
14.0%
산업체 1115
 
10.9%
병원 660
 
6.5%
사회복지시설 511
 
5.0%
공공기관 348
 
3.4%
기타 194
 
1.9%
기숙사 36
 
0.4%
수련원 24
 
0.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct7209
Distinct (%)74.2%
Missing285
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean198928.86
Minimum180384.55
Maximum215966.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:44:16.745294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum180384.55
5-th percentile186101.92
Q1192397.81
median199976.27
Q3204940.09
95-th percentile211372.28
Maximum215966.73
Range35582.181
Interquartile range (IQR)12542.281

Descriptive statistics

Standard deviation7753.7329
Coefficient of variation (CV)0.038977415
Kurtosis-0.95518845
Mean198928.86
Median Absolute Deviation (MAD)6282.3789
Skewness-0.084830855
Sum1.9325939 × 109
Variance60120373
MonotonicityNot monotonic
2024-05-11T03:44:17.314616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194584.959249312 21
 
0.2%
203684.127182478 20
 
0.2%
196139.864969792 13
 
0.1%
206479.980833988 12
 
0.1%
207918.320414714 12
 
0.1%
209607.590372037 12
 
0.1%
192450.93552236 11
 
0.1%
204469.209049094 11
 
0.1%
199628.172805473 10
 
0.1%
194577.192321587 10
 
0.1%
Other values (7199) 9583
95.8%
(Missing) 285
 
2.9%
ValueCountFrequency (%)
180384.547605318 1
 
< 0.1%
180784.022319515 1
 
< 0.1%
181077.669193479 1
 
< 0.1%
181682.433518522 1
 
< 0.1%
181881.234660314 1
 
< 0.1%
182029.065433146 1
 
< 0.1%
182086.388313239 2
< 0.1%
182141.205465089 4
< 0.1%
182162.406429892 2
< 0.1%
182524.823835629 3
< 0.1%
ValueCountFrequency (%)
215966.729045494 1
< 0.1%
215927.688523964 1
< 0.1%
215898.113091143 1
< 0.1%
215884.426023533 2
< 0.1%
215875.024969 2
< 0.1%
215844.448775419 1
< 0.1%
215722.425040339 1
< 0.1%
215705.162771801 1
< 0.1%
215687.672374226 1
< 0.1%
215672.146934322 2
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct7207
Distinct (%)74.2%
Missing285
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean449496.7
Minimum437299.64
Maximum465803.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:44:17.795942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437299.64
5-th percentile441196.83
Q1444477.61
median449241.89
Q3453430.51
95-th percentile460650.85
Maximum465803.59
Range28503.953
Interquartile range (IQR)8952.8969

Descriptive statistics

Standard deviation5951.7203
Coefficient of variation (CV)0.013240854
Kurtosis-0.5994918
Mean449496.7
Median Absolute Deviation (MAD)4532.9698
Skewness0.40007689
Sum4.3668604 × 109
Variance35422975
MonotonicityNot monotonic
2024-05-11T03:44:18.296502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451381.585492051 21
 
0.2%
450698.570810848 20
 
0.2%
439023.167125842 13
 
0.1%
458383.983421656 12
 
0.1%
449827.630945538 12
 
0.1%
447120.577229325 12
 
0.1%
454934.047367752 11
 
0.1%
447649.476828035 11
 
0.1%
457491.95841735 10
 
0.1%
455069.448360472 10
 
0.1%
Other values (7197) 9583
95.8%
(Missing) 285
 
2.9%
ValueCountFrequency (%)
437299.637939286 1
< 0.1%
437574.410581167 1
< 0.1%
437674.901694125 2
< 0.1%
437726.629174077 1
< 0.1%
437732.05990343 1
< 0.1%
437908.607859024 1
< 0.1%
437998.135238761 1
< 0.1%
438086.021838555 1
< 0.1%
438086.053183246 1
< 0.1%
438186.22864238 1
< 0.1%
ValueCountFrequency (%)
465803.591403923 3
< 0.1%
465298.499445422 1
 
< 0.1%
465291.710893362 1
 
< 0.1%
465077.944095077 1
 
< 0.1%
465026.559768614 1
 
< 0.1%
465017.323060748 1
 
< 0.1%
465002.243917998 2
< 0.1%
464925.338705852 1
 
< 0.1%
464922.213107238 1
 
< 0.1%
464915.302353733 1
 
< 0.1%

위생업태명
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
어린이집
2571 
<NA>
2332 
집단급식소
2196 
학교
1074 
산업체
638 
Other values (7)
1189 

Length

Max length8
Median length4
Mean length3.957
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 2571
25.7%
<NA> 2332
23.3%
집단급식소 2196
22.0%
학교 1074
10.7%
산업체 638
 
6.4%
병원 453
 
4.5%
사회복지시설 352
 
3.5%
공공기관 242
 
2.4%
기타 집단급식소 100
 
1.0%
기숙사 22
 
0.2%
Other values (2) 20
 
0.2%

Length

2024-05-11T03:44:18.705652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
어린이집 2571
25.5%
na 2332
23.1%
집단급식소 2296
22.7%
학교 1074
10.6%
산업체 638
 
6.3%
병원 453
 
4.5%
사회복지시설 352
 
3.5%
공공기관 242
 
2.4%
기타 100
 
1.0%
기숙사 22
 
0.2%
Other values (2) 20
 
0.2%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.3%
Missing7560
Missing (%)75.6%
Infinite0
Infinite (%)0.0%
Mean0.040163934
Minimum0
Maximum11
Zeros2381
Zeros (%)23.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:44:19.174588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.35654941
Coefficient of variation (CV)8.8773527
Kurtosis426.14466
Mean0.040163934
Median Absolute Deviation (MAD)0
Skewness17.385826
Sum98
Variance0.12712748
MonotonicityNot monotonic
2024-05-11T03:44:19.714176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 2381
 
23.8%
1 43
 
0.4%
2 8
 
0.1%
5 3
 
< 0.1%
3 3
 
< 0.1%
11 1
 
< 0.1%
4 1
 
< 0.1%
(Missing) 7560
75.6%
ValueCountFrequency (%)
0 2381
23.8%
1 43
 
0.4%
2 8
 
0.1%
3 3
 
< 0.1%
4 1
 
< 0.1%
5 3
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
5 3
 
< 0.1%
4 1
 
< 0.1%
3 3
 
< 0.1%
2 8
 
0.1%
1 43
 
0.4%
0 2381
23.8%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)0.7%
Missing7544
Missing (%)75.4%
Infinite0
Infinite (%)0.0%
Mean0.46213355
Minimum0
Maximum27
Zeros2254
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:44:20.111973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.25
Maximum27
Range27
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7932299
Coefficient of variation (CV)3.8803283
Kurtosis38.769677
Mean0.46213355
Median Absolute Deviation (MAD)0
Skewness5.2502818
Sum1135
Variance3.2156735
MonotonicityNot monotonic
2024-05-11T03:44:20.600352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 2254
 
22.5%
6 35
 
0.4%
4 34
 
0.3%
5 32
 
0.3%
3 27
 
0.3%
7 26
 
0.3%
2 11
 
0.1%
8 9
 
0.1%
1 7
 
0.1%
9 4
 
< 0.1%
Other values (8) 17
 
0.2%
(Missing) 7544
75.4%
ValueCountFrequency (%)
0 2254
22.5%
1 7
 
0.1%
2 11
 
0.1%
3 27
 
0.3%
4 34
 
0.3%
5 32
 
0.3%
6 35
 
0.4%
7 26
 
0.3%
8 9
 
0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
27 1
 
< 0.1%
16 1
 
< 0.1%
15 3
 
< 0.1%
14 3
 
< 0.1%
13 1
 
< 0.1%
12 2
 
< 0.1%
11 2
 
< 0.1%
10 4
< 0.1%
9 4
< 0.1%
8 9
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8057 
기타
1613 
주택가주변
 
148
학교정화(절대)
 
125
아파트지역
 
30
Other values (3)
 
27

Length

Max length8
Median length4
Mean length3.7558
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8057
80.6%
기타 1613
 
16.1%
주택가주변 148
 
1.5%
학교정화(절대) 125
 
1.2%
아파트지역 30
 
0.3%
학교정화(상대) 18
 
0.2%
유흥업소밀집지역 7
 
0.1%
결혼예식장주변 2
 
< 0.1%

Length

2024-05-11T03:44:21.137640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:21.491596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8057
80.6%
기타 1613
 
16.1%
주택가주변 148
 
1.5%
학교정화(절대 125
 
1.2%
아파트지역 30
 
0.3%
학교정화(상대 18
 
0.2%
유흥업소밀집지역 7
 
0.1%
결혼예식장주변 2
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8057 
기타
1629 
자율
 
230
우수
 
72
 
4
Other values (3)
 
8

Length

Max length4
Median length4
Mean length3.6107
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8057
80.6%
기타 1629
 
16.3%
자율 230
 
2.3%
우수 72
 
0.7%
4
 
< 0.1%
3
 
< 0.1%
지도 3
 
< 0.1%
관리 2
 
< 0.1%

Length

2024-05-11T03:44:22.088015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:22.584189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8057
80.6%
기타 1629
 
16.3%
자율 230
 
2.3%
우수 72
 
0.7%
4
 
< 0.1%
3
 
< 0.1%
지도 3
 
< 0.1%
관리 2
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5165 
상수도전용
4829 
간이상수도
 
2
지하수전용
 
2
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length4
Mean length4.4859
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5165
51.6%
상수도전용 4829
48.3%
간이상수도 2
 
< 0.1%
지하수전용 2
 
< 0.1%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%

Length

2024-05-11T03:44:22.999231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:23.332017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5165
51.6%
상수도전용 4829
48.3%
간이상수도 2
 
< 0.1%
지하수전용 2
 
< 0.1%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9045 
0
955 

Length

Max length4
Median length4
Mean length3.7135
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> 9045
90.5%
0 955
 
9.6%

Length

2024-05-11T03:44:23.738708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:24.159743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9045
90.5%
0 955
 
9.6%

본사종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct31
Distinct (%)0.6%
Missing4562
Missing (%)45.6%
Infinite0
Infinite (%)0.0%
Mean0.41412284
Minimum0
Maximum150
Zeros5028
Zeros (%)50.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:44:24.589445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum150
Range150
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.2978386
Coefficient of variation (CV)7.9634309
Kurtosis988.78789
Mean0.41412284
Median Absolute Deviation (MAD)0
Skewness26.47517
Sum2252
Variance10.875739
MonotonicityNot monotonic
2024-05-11T03:44:25.384294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 5028
50.3%
1 115
 
1.1%
2 79
 
0.8%
3 48
 
0.5%
4 34
 
0.3%
7 20
 
0.2%
6 18
 
0.2%
5 17
 
0.2%
9 15
 
0.1%
10 12
 
0.1%
Other values (21) 52
 
0.5%
(Missing) 4562
45.6%
ValueCountFrequency (%)
0 5028
50.3%
1 115
 
1.1%
2 79
 
0.8%
3 48
 
0.5%
4 34
 
0.3%
5 17
 
0.2%
6 18
 
0.2%
7 20
 
0.2%
8 8
 
0.1%
9 15
 
0.1%
ValueCountFrequency (%)
150 1
< 0.1%
98 1
< 0.1%
70 1
< 0.1%
63 1
< 0.1%
35 1
< 0.1%
33 1
< 0.1%
32 1
< 0.1%
30 1
< 0.1%
27 1
< 0.1%
22 1
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9045 
0
955 

Length

Max length4
Median length4
Mean length3.7135
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> 9045
90.5%
0 955
 
9.6%

Length

2024-05-11T03:44:25.928725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:26.328251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9045
90.5%
0 955
 
9.6%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9045 
0
955 

Length

Max length4
Median length4
Mean length3.7135
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> 9045
90.5%
0 955
 
9.6%

Length

2024-05-11T03:44:26.662330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:26.965620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9045
90.5%
0 955
 
9.6%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9045 
0
955 

Length

Max length4
Median length4
Mean length3.7135
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> 9045
90.5%
0 955
 
9.6%

Length

2024-05-11T03:44:27.345308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:27.692803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9045
90.5%
0 955
 
9.6%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9389 
자가
 
462
임대
 
149

Length

Max length4
Median length4
Mean length3.8778
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> 9389
93.9%
자가 462
 
4.6%
임대 149
 
1.5%

Length

2024-05-11T03:44:28.201324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:28.517301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9389
93.9%
자가 462
 
4.6%
임대 149
 
1.5%

보증액
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6032 
0
3965 
500000000
 
1
2000000000
 
1
90000000
 
1

Length

Max length10
Median length4
Mean length2.812
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6032
60.3%
0 3965
39.6%
500000000 1
 
< 0.1%
2000000000 1
 
< 0.1%
90000000 1
 
< 0.1%

Length

2024-05-11T03:44:28.831155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:29.236502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6032
60.3%
0 3965
39.6%
500000000 1
 
< 0.1%
2000000000 1
 
< 0.1%
90000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6032 
0
3964 
50000000
 
1
2970000
 
1
5000000
 
1

Length

Max length8
Median length4
Mean length2.8121
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6032
60.3%
0 3964
39.6%
50000000 1
 
< 0.1%
2970000 1
 
< 0.1%
5000000 1
 
< 0.1%
4000000 1
 
< 0.1%

Length

2024-05-11T03:44:29.711179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:30.059818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6032
60.3%
0 3964
39.6%
50000000 1
 
< 0.1%
2970000 1
 
< 0.1%
5000000 1
 
< 0.1%
4000000 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing2332
Missing (%)23.3%
Memory size97.7 KiB
False
7654 
True
 
14
(Missing)
2332 
ValueCountFrequency (%)
False 7654
76.5%
True 14
 
0.1%
(Missing) 2332
 
23.3%
2024-05-11T03:44:30.418225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct3335
Distinct (%)43.5%
Missing2332
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean119.30692
Minimum0
Maximum4500
Zeros2356
Zeros (%)23.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:44:30.858470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median21
Q3141.7725
95-th percentile539.1365
Maximum4500
Range4500
Interquartile range (IQR)141.7725

Descriptive statistics

Standard deviation253.13539
Coefficient of variation (CV)2.1217159
Kurtosis56.289222
Mean119.30692
Median Absolute Deviation (MAD)21
Skewness5.7796721
Sum914845.46
Variance64077.528
MonotonicityNot monotonic
2024-05-11T03:44:31.325077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2356
23.6%
10.0 79
 
0.8%
16.5 64
 
0.6%
13.2 54
 
0.5%
33.0 53
 
0.5%
15.0 48
 
0.5%
9.9 48
 
0.5%
20.0 47
 
0.5%
30.0 43
 
0.4%
12.0 40
 
0.4%
Other values (3325) 4836
48.4%
(Missing) 2332
23.3%
ValueCountFrequency (%)
0.0 2356
23.6%
0.01 1
 
< 0.1%
0.1 1
 
< 0.1%
1.0 2
 
< 0.1%
2.0 2
 
< 0.1%
2.61 1
 
< 0.1%
3.0 3
 
< 0.1%
3.17 1
 
< 0.1%
3.3 13
 
0.1%
3.37 1
 
< 0.1%
ValueCountFrequency (%)
4500.0 1
< 0.1%
4066.8 1
< 0.1%
3936.79 1
< 0.1%
3387.39 1
< 0.1%
3228.08 1
< 0.1%
3120.0 1
< 0.1%
3039.3 1
< 0.1%
2861.0 1
< 0.1%
2766.52 1
< 0.1%
2738.3 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
417331000003100000-105-2010-0000220100303<NA>3폐업2폐업20210305<NA><NA><NA>02 93659993.30139816서울특별시 노원구 상계동 320-1서울특별시 노원구 노원로30길 45 (상계동)1703양지유치원2021-03-05 13:30:37U2021-03-07 02:40:00.0어린이집206084.193595461437.009361어린이집<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N3.3<NA><NA><NA>
683131700003170000-105-2003-0001020020329<NA>3폐업2폐업20160812<NA><NA><NA><NA>155.36153030서울특별시 금천구 시흥동 1020번지서울특별시 금천구 시흥대로73길 70 (시흥동)8611오류자료2016-08-12 17:07:06I2018-08-31 23:59:59.0집단급식소190676.233229439411.341662집단급식소<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N155.36<NA><NA><NA>
428431000003100000-105-2016-0000120160111<NA>3폐업2폐업20210621<NA><NA><NA>02 9503106.00139831서울특별시 노원구 상계동 772서울특별시 노원구 덕릉로70길 99 (상계동)1772서울시립노원청소년센터2021-06-21 13:35:55U2021-06-23 02:40:00.0수련원205136.50023459748.436215수련원<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N0.0<NA><NA><NA>
563331400003140000-105-1992-0000719920516<NA>3폐업2폐업20130208<NA><NA><NA>022644131356.27158819서울특별시 양천구 목동 793-3번지서울특별시 양천구 등촌로 22 (목동)7966제성병원2013-02-13 16:32:42I2018-08-31 23:59:59.0집단급식소187918.421583447753.887261집단급식소00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N121.95<NA><NA><NA>
39630300003030000-105-2020-000042020-05-11<NA>1영업/정상1영업<NA><NA><NA><NA>02229639908.90133-858서울특별시 성동구 하왕십리동 976-13 신영어린이집서울특별시 성동구 무학봉16길 9-3, 지하1층 (하왕십리동)4714왕십리하나어린이집 구내식당2023-08-28 15:08:57U2022-12-07 21:00:00.0어린이집202758.640476450959.783205<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
771931900003190000-105-2005-0005420050712<NA>1영업/정상1영업<NA><NA><NA><NA>02 826450318.10156848서울특별시 동작구 신대방동 364-18번지서울특별시 동작구 여의대방로22길 44 (신대방동)7058구립 보라매어린이집2019-09-24 09:43:18U2019-09-26 02:40:00.0어린이집193065.774018443931.740215어린이집<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N18.1<NA><NA><NA>
716231800003180000-105-2007-0002320070828<NA>1영업/정상1영업<NA><NA><NA><NA>0221220557195.00150879서울특별시 영등포구 여의도동 26-3번지 원창빌딩 9층서울특별시 영등포구 여의나루로 53-2 (여의도동,원창빌딩 9층)7327동화기업(주)2017-07-10 10:54:36I2018-08-31 23:59:59.0산업체193280.599686446747.124542산업체00<NA><NA>상수도전용00000<NA>00N54.0<NA><NA><NA>
759531900003190000-105-2016-0000120160309<NA>1영업/정상1영업<NA><NA><NA><NA>023280114513.10156840서울특별시 동작구 상도동 197-11서울특별시 동작구 상도로22길 45, 지상2층 (상도동)6961구립상도4동어린이집2020-08-06 13:31:34U2020-08-08 02:40:00.0어린이집194389.186297444340.170324어린이집<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N13.1<NA><NA><NA>
794532000003200000-105-2000-0005720000329<NA>1영업/정상1영업<NA><NA><NA><NA>02 8878573121.57151809서울특별시 관악구 봉천동 28-6번지서울특별시 관악구 행운1라길 17 (봉천동)8736서울봉천초등학교2017-08-23 18:51:01I2018-08-31 23:59:59.0학교196203.216216442328.137877학교00주택가주변기타<NA><NA>0<NA><NA><NA><NA><NA><NA>N176.69<NA><NA><NA>
467231100003110000-105-2008-0001520081020<NA>1영업/정상1영업<NA><NA><NA><NA>02 383 5379588.30122200서울특별시 은평구 진관동 16번지 진관중학교서울특별시 은평구 진관4로 36, 진관중학교 (진관동)3302진관중학교2018-03-09 10:22:20I2018-08-31 23:59:59.0학교193381.279748460162.764479학교<NA><NA><NA><NA>상수도전용<NA>0<NA><NA><NA><NA>00N228.2<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
863432100003210000-105-1999-0006619990210<NA>3폐업2폐업20200403<NA><NA><NA>023470961336.98137868서울특별시 서초구 서초동 1467-10번지 지하1층서울특별시 서초구 명달로 6, 지하1층 (서초동)6713휠라코리아(주)급식소2020-04-03 11:48:48U2020-04-05 02:40:00.0산업체200557.980157441769.323198산업체00기타기타상수도전용<NA>6<NA><NA><NA><NA><NA><NA>N246.92<NA><NA><NA>
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