Overview

Dataset statistics

Number of variables44
Number of observations320
Missing cells2836
Missing cells (%)20.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory117.6 KiB
Average record size in memory376.4 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric5
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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-18264/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
남성종사자수 is highly imbalanced (71.3%)Imbalance
여성종사자수 is highly imbalanced (69.2%)Imbalance
영업장주변구분명 is highly imbalanced (52.1%)Imbalance
등급구분명 is highly imbalanced (59.2%)Imbalance
총인원 is highly imbalanced (79.9%)Imbalance
공장생산직종업원수 is highly imbalanced (50.9%)Imbalance
다중이용업소여부 is highly imbalanced (96.7%)Imbalance
인허가취소일자 has 320 (100.0%) missing valuesMissing
폐업일자 has 39 (12.2%) missing valuesMissing
휴업시작일자 has 320 (100.0%) missing valuesMissing
휴업종료일자 has 320 (100.0%) missing valuesMissing
재개업일자 has 320 (100.0%) missing valuesMissing
전화번호 has 69 (21.6%) missing valuesMissing
소재지면적 has 49 (15.3%) missing valuesMissing
도로명주소 has 157 (49.1%) missing valuesMissing
도로명우편번호 has 160 (50.0%) missing valuesMissing
좌표정보(X) has 28 (8.8%) missing valuesMissing
좌표정보(Y) has 28 (8.8%) missing valuesMissing
다중이용업소여부 has 33 (10.3%) missing valuesMissing
시설총규모 has 33 (10.3%) missing valuesMissing
전통업소지정번호 has 320 (100.0%) missing valuesMissing
전통업소주된음식 has 320 (100.0%) missing valuesMissing
홈페이지 has 320 (100.0%) missing valuesMissing
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
소재지면적 has 20 (6.2%) zerosZeros
시설총규모 has 237 (74.1%) zerosZeros

Reproduction

Analysis started2024-04-06 11:05:35.553088
Analysis finished2024-04-06 11:05:36.608283
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3120000
320 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 320
100.0%

Length

2024-04-06T20:05:36.745991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:36.882353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 320
100.0%

관리번호
Text

UNIQUE 

Distinct320
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-06T20:05:37.122105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters7040
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

Unique320 ?
Unique (%)100.0%

Sample

1st row3120000-106-1976-00066
2nd row3120000-106-1989-00025
3rd row3120000-106-1989-00026
4th row3120000-106-1990-00027
5th row3120000-106-1991-00070
ValueCountFrequency (%)
3120000-106-1976-00066 1
 
0.3%
3120000-106-1989-00025 1
 
0.3%
3120000-106-2011-00014 1
 
0.3%
3120000-106-2011-00013 1
 
0.3%
3120000-106-2011-00012 1
 
0.3%
3120000-106-2011-00011 1
 
0.3%
3120000-106-2011-00010 1
 
0.3%
3120000-106-2011-00009 1
 
0.3%
3120000-106-2011-00008 1
 
0.3%
3120000-106-2011-00015 1
 
0.3%
Other values (310) 310
96.9%
2024-04-06T20:05:37.665559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3183
45.2%
- 960
 
13.6%
1 940
 
13.4%
2 737
 
10.5%
3 416
 
5.9%
6 383
 
5.4%
9 140
 
2.0%
4 101
 
1.4%
5 82
 
1.2%
8 56
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6080
86.4%
Dash Punctuation 960
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3183
52.4%
1 940
 
15.5%
2 737
 
12.1%
3 416
 
6.8%
6 383
 
6.3%
9 140
 
2.3%
4 101
 
1.7%
5 82
 
1.3%
8 56
 
0.9%
7 42
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 960
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7040
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3183
45.2%
- 960
 
13.6%
1 940
 
13.4%
2 737
 
10.5%
3 416
 
5.9%
6 383
 
5.4%
9 140
 
2.0%
4 101
 
1.4%
5 82
 
1.2%
8 56
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7040
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3183
45.2%
- 960
 
13.6%
1 940
 
13.4%
2 737
 
10.5%
3 416
 
5.9%
6 383
 
5.4%
9 140
 
2.0%
4 101
 
1.4%
5 82
 
1.2%
8 56
 
0.8%

인허가일자
Date

Distinct303
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1976-08-10 00:00:00
Maximum2024-02-16 00:00:00
2024-04-06T20:05:37.931152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:05:38.233320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing320
Missing (%)100.0%
Memory size2.9 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3
281 
1
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 281
87.8%
1 39
 
12.2%

Length

2024-04-06T20:05:38.494346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:38.654979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 281
87.8%
1 39
 
12.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
폐업
281 
영업/정상
39 

Length

Max length5
Median length2
Mean length2.365625
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 281
87.8%
영업/정상 39
 
12.2%

Length

2024-04-06T20:05:38.833599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:39.002011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 281
87.8%
영업/정상 39
 
12.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2
281 
1
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 281
87.8%
1 39
 
12.2%

Length

2024-04-06T20:05:39.238211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:39.420944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 281
87.8%
1 39
 
12.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
폐업
281 
영업
39 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 281
87.8%
영업 39
 
12.2%

Length

2024-04-06T20:05:39.602249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:39.769799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 281
87.8%
영업 39
 
12.2%

폐업일자
Date

MISSING 

Distinct269
Distinct (%)95.7%
Missing39
Missing (%)12.2%
Memory size2.6 KiB
Minimum1996-09-16 00:00:00
Maximum2024-02-14 00:00:00
2024-04-06T20:05:39.978085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:05:40.212676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing320
Missing (%)100.0%
Memory size2.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing320
Missing (%)100.0%
Memory size2.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing320
Missing (%)100.0%
Memory size2.9 KiB

전화번호
Text

MISSING 

Distinct242
Distinct (%)96.4%
Missing69
Missing (%)21.6%
Memory size2.6 KiB
2024-04-06T20:05:40.655478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.103586
Min length2

Characters and Unicode

Total characters2536
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

Unique235 ?
Unique (%)93.6%

Sample

1st row02 3655901
2nd row02 3964806
3rd row02 3352111
4th row02 3625274
5th row02 3347020
ValueCountFrequency (%)
02 200
42.9%
7150401 2
 
0.4%
3750702 2
 
0.4%
3241027 2
 
0.4%
3635813 2
 
0.4%
3641183 2
 
0.4%
3263000 2
 
0.4%
303 1
 
0.2%
75822999 1
 
0.2%
070 1
 
0.2%
Other values (251) 251
53.9%
2024-04-06T20:05:41.340776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 473
18.7%
2 410
16.2%
3 371
14.6%
237
9.3%
1 172
 
6.8%
7 164
 
6.5%
8 153
 
6.0%
5 151
 
6.0%
6 144
 
5.7%
4 134
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2299
90.7%
Space Separator 237
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 473
20.6%
2 410
17.8%
3 371
16.1%
1 172
 
7.5%
7 164
 
7.1%
8 153
 
6.7%
5 151
 
6.6%
6 144
 
6.3%
4 134
 
5.8%
9 127
 
5.5%
Space Separator
ValueCountFrequency (%)
237
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2536
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 473
18.7%
2 410
16.2%
3 371
14.6%
237
9.3%
1 172
 
6.8%
7 164
 
6.5%
8 153
 
6.0%
5 151
 
6.0%
6 144
 
5.7%
4 134
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2536
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 473
18.7%
2 410
16.2%
3 371
14.6%
237
9.3%
1 172
 
6.8%
7 164
 
6.5%
8 153
 
6.0%
5 151
 
6.0%
6 144
 
5.7%
4 134
 
5.3%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct216
Distinct (%)79.7%
Missing49
Missing (%)15.3%
Infinite0
Infinite (%)0.0%
Mean67.143063
Minimum0
Maximum449.38
Zeros20
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T20:05:42.046795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123.05
median48
Q384.725
95-th percentile190.19
Maximum449.38
Range449.38
Interquartile range (IQR)61.675

Descriptive statistics

Standard deviation65.24687
Coefficient of variation (CV)0.97175892
Kurtosis5.8413198
Mean67.143063
Median Absolute Deviation (MAD)27.5
Skewness2.0429769
Sum18195.77
Variance4257.1541
MonotonicityNot monotonic
2024-04-06T20:05:42.325974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 20
 
6.2%
15.0 6
 
1.9%
40.0 4
 
1.2%
20.0 4
 
1.2%
66.0 3
 
0.9%
82.5 3
 
0.9%
26.4 3
 
0.9%
30.0 3
 
0.9%
21.0 2
 
0.6%
45.6 2
 
0.6%
Other values (206) 221
69.1%
(Missing) 49
 
15.3%
ValueCountFrequency (%)
0.0 20
6.2%
4.16 1
 
0.3%
8.6 1
 
0.3%
8.62 1
 
0.3%
8.93 1
 
0.3%
9.33 1
 
0.3%
10.0 1
 
0.3%
10.5 1
 
0.3%
11.52 1
 
0.3%
12.0 1
 
0.3%
ValueCountFrequency (%)
449.38 1
0.3%
324.4 1
0.3%
294.76 1
0.3%
285.0 1
0.3%
276.37 1
0.3%
273.87 1
0.3%
250.0 1
0.3%
244.7 1
0.3%
231.75 1
0.3%
230.0 1
0.3%

소재지우편번호
Text

Distinct78
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-06T20:05:42.705864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.04375
Min length6

Characters and Unicode

Total characters1934
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

Unique26 ?
Unique (%)8.1%

Sample

1st row120170
2nd row120855
3rd row120824
4th row120819
5th row120828
ValueCountFrequency (%)
120825 21
 
6.6%
120070 20
 
6.2%
120808 19
 
5.9%
120832 17
 
5.3%
120857 12
 
3.8%
120827 12
 
3.8%
120080 11
 
3.4%
120848 11
 
3.4%
120807 10
 
3.1%
120824 9
 
2.8%
Other values (68) 178
55.6%
2024-04-06T20:05:43.329455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 503
26.0%
2 414
21.4%
1 405
20.9%
8 296
15.3%
7 69
 
3.6%
5 65
 
3.4%
4 60
 
3.1%
3 52
 
2.7%
6 39
 
2.0%
9 17
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1920
99.3%
Dash Punctuation 14
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 503
26.2%
2 414
21.6%
1 405
21.1%
8 296
15.4%
7 69
 
3.6%
5 65
 
3.4%
4 60
 
3.1%
3 52
 
2.7%
6 39
 
2.0%
9 17
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1934
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 503
26.0%
2 414
21.4%
1 405
20.9%
8 296
15.3%
7 69
 
3.6%
5 65
 
3.4%
4 60
 
3.1%
3 52
 
2.7%
6 39
 
2.0%
9 17
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 503
26.0%
2 414
21.4%
1 405
20.9%
8 296
15.3%
7 69
 
3.6%
5 65
 
3.4%
4 60
 
3.1%
3 52
 
2.7%
6 39
 
2.0%
9 17
 
0.9%

지번주소
Text

Distinct311
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-06T20:05:43.786929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length37.5
Mean length27.15625
Min length18

Characters and Unicode

Total characters8690
Distinct characters118
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique303 ?
Unique (%)94.7%

Sample

1st row서울특별시 서대문구 대현동 37-24번지 ,27
2nd row서울특별시 서대문구 홍제동 157-73번지
3rd row서울특별시 서대문구 연희동 81-1번지
4th row서울특별시 서대문구 북아현동 129-75번지 3층
5th row서울특별시 서대문구 연희동 218-7번지
ValueCountFrequency (%)
서울특별시 320
20.8%
서대문구 320
20.8%
연희동 85
 
5.5%
1층 45
 
2.9%
북가좌동 36
 
2.3%
남가좌동 35
 
2.3%
홍제동 31
 
2.0%
홍은동 29
 
1.9%
지하1층 26
 
1.7%
대현동 25
 
1.6%
Other values (387) 590
38.3%
2024-04-06T20:05:44.557917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1505
 
17.3%
서 640
 
7.4%
1 371
 
4.3%
지 363
 
4.2%
대 350
 
4.0%
문 324
 
3.7%
시 323
 
3.7%
별 320
 
3.7%
울 320
 
3.7%
동 320
 
3.7%
Other values (108) 3854
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5114
58.8%
Decimal Number 1617
 
18.6%
Space Separator 1505
 
17.3%
Dash Punctuation 290
 
3.3%
Open Punctuation 70
 
0.8%
Close Punctuation 69
 
0.8%
Other Punctuation 21
 
0.2%
Math Symbol 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 640
12.5%
지 363
 
7.1%
대 350
 
6.8%
문 324
 
6.3%
시 323
 
6.3%
별 320
 
6.3%
울 320
 
6.3%
동 320
 
6.3%
특 320
 
6.3%
구 320
 
6.3%
Other values (90) 1514
29.6%
Decimal Number
ValueCountFrequency (%)
1 371
22.9%
2 242
15.0%
3 208
12.9%
4 166
10.3%
7 115
 
7.1%
0 111
 
6.9%
6 106
 
6.6%
5 104
 
6.4%
9 98
 
6.1%
8 96
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 19
90.5%
. 2
 
9.5%
Space Separator
ValueCountFrequency (%)
1505
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 290
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5114
58.8%
Common 3574
41.1%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 640
12.5%
지 363
 
7.1%
대 350
 
6.8%
문 324
 
6.3%
시 323
 
6.3%
별 320
 
6.3%
울 320
 
6.3%
동 320
 
6.3%
특 320
 
6.3%
구 320
 
6.3%
Other values (90) 1514
29.6%
Common
ValueCountFrequency (%)
1505
42.1%
1 371
 
10.4%
- 290
 
8.1%
2 242
 
6.8%
3 208
 
5.8%
4 166
 
4.6%
7 115
 
3.2%
0 111
 
3.1%
6 106
 
3.0%
5 104
 
2.9%
Other values (7) 356
 
10.0%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5114
58.8%
ASCII 3576
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1505
42.1%
1 371
 
10.4%
- 290
 
8.1%
2 242
 
6.8%
3 208
 
5.8%
4 166
 
4.6%
7 115
 
3.2%
0 111
 
3.1%
6 106
 
3.0%
5 104
 
2.9%
Other values (8) 358
 
10.0%
Hangul
ValueCountFrequency (%)
서 640
12.5%
지 363
 
7.1%
대 350
 
6.8%
문 324
 
6.3%
시 323
 
6.3%
별 320
 
6.3%
울 320
 
6.3%
동 320
 
6.3%
특 320
 
6.3%
구 320
 
6.3%
Other values (90) 1514
29.6%

도로명주소
Text

MISSING 

Distinct160
Distinct (%)98.2%
Missing157
Missing (%)49.1%
Memory size2.6 KiB
2024-04-06T20:05:45.102530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length44
Mean length32.184049
Min length23

Characters and Unicode

Total characters5246
Distinct characters130
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique157 ?
Unique (%)96.3%

Sample

1st row서울특별시 서대문구 북아현로4길 9-7 (북아현동, 3층)
2nd row서울특별시 서대문구 홍제내4길 5 (홍제동)
3rd row서울특별시 서대문구 응암로 117 (북가좌동, 지층)
4th row서울특별시 서대문구 증가로30길 45 (북가좌동, 지하1층)
5th row서울특별시 서대문구 연희로 132 (연희동, 지하1층)
ValueCountFrequency (%)
서울특별시 163
 
16.2%
서대문구 163
 
16.2%
연희동 56
 
5.6%
1층 40
 
4.0%
연희로 21
 
2.1%
지하1층 20
 
2.0%
2층 17
 
1.7%
남가좌동 16
 
1.6%
지층 16
 
1.6%
북가좌동 15
 
1.5%
Other values (259) 479
47.6%
2024-04-06T20:05:45.886978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
843
 
16.1%
서 328
 
6.3%
1 219
 
4.2%
대 197
 
3.8%
( 192
 
3.7%
) 192
 
3.7%
문 181
 
3.5%
울 171
 
3.3%
시 168
 
3.2%
동 166
 
3.2%
Other values (120) 2589
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3114
59.4%
Space Separator 843
 
16.1%
Decimal Number 697
 
13.3%
Open Punctuation 192
 
3.7%
Close Punctuation 192
 
3.7%
Other Punctuation 164
 
3.1%
Dash Punctuation 38
 
0.7%
Uppercase Letter 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 328
 
10.5%
대 197
 
6.3%
문 181
 
5.8%
울 171
 
5.5%
시 168
 
5.4%
동 166
 
5.3%
별 163
 
5.2%
특 163
 
5.2%
구 163
 
5.2%
층 152
 
4.9%
Other values (102) 1262
40.5%
Decimal Number
ValueCountFrequency (%)
1 219
31.4%
2 121
17.4%
3 81
 
11.6%
5 51
 
7.3%
0 47
 
6.7%
4 43
 
6.2%
9 42
 
6.0%
6 36
 
5.2%
8 29
 
4.2%
7 28
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 163
99.4%
. 1
 
0.6%
Space Separator
ValueCountFrequency (%)
843
100.0%
Open Punctuation
ValueCountFrequency (%)
( 192
100.0%
Close Punctuation
ValueCountFrequency (%)
) 192
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3114
59.4%
Common 2128
40.6%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 328
 
10.5%
대 197
 
6.3%
문 181
 
5.8%
울 171
 
5.5%
시 168
 
5.4%
동 166
 
5.3%
별 163
 
5.2%
특 163
 
5.2%
구 163
 
5.2%
층 152
 
4.9%
Other values (102) 1262
40.5%
Common
ValueCountFrequency (%)
843
39.6%
1 219
 
10.3%
( 192
 
9.0%
) 192
 
9.0%
, 163
 
7.7%
2 121
 
5.7%
3 81
 
3.8%
5 51
 
2.4%
0 47
 
2.2%
4 43
 
2.0%
Other values (7) 176
 
8.3%
Latin
ValueCountFrequency (%)
B 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3114
59.4%
ASCII 2132
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
843
39.5%
1 219
 
10.3%
( 192
 
9.0%
) 192
 
9.0%
, 163
 
7.6%
2 121
 
5.7%
3 81
 
3.8%
5 51
 
2.4%
0 47
 
2.2%
4 43
 
2.0%
Other values (8) 180
 
8.4%
Hangul
ValueCountFrequency (%)
서 328
 
10.5%
대 197
 
6.3%
문 181
 
5.8%
울 171
 
5.5%
시 168
 
5.4%
동 166
 
5.3%
별 163
 
5.2%
특 163
 
5.2%
구 163
 
5.2%
층 152
 
4.9%
Other values (102) 1262
40.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)45.0%
Missing160
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean3708.35
Minimum3600
Maximum3789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T20:05:46.115330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3600
5-th percentile3628
Q13680.75
median3704.5
Q33734
95-th percentile3781
Maximum3789
Range189
Interquartile range (IQR)53.25

Descriptive statistics

Standard deviation43.505107
Coefficient of variation (CV)0.011731662
Kurtosis-0.22122286
Mean3708.35
Median Absolute Deviation (MAD)29.5
Skewness-0.18276406
Sum593336
Variance1892.6943
MonotonicityNot monotonic
2024-04-06T20:05:46.360291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3734 11
 
3.4%
3708 8
 
2.5%
3700 8
 
2.5%
3699 7
 
2.2%
3703 6
 
1.9%
3692 5
 
1.6%
3766 5
 
1.6%
3698 4
 
1.2%
3676 4
 
1.2%
3723 4
 
1.2%
Other values (62) 98
30.6%
(Missing) 160
50.0%
ValueCountFrequency (%)
3600 1
0.3%
3602 1
0.3%
3606 1
0.3%
3614 1
0.3%
3617 2
0.6%
3619 1
0.3%
3628 2
0.6%
3632 1
0.3%
3636 2
0.6%
3640 1
0.3%
ValueCountFrequency (%)
3789 1
 
0.3%
3788 2
0.6%
3787 2
0.6%
3786 1
 
0.3%
3781 3
0.9%
3778 1
 
0.3%
3777 1
 
0.3%
3776 2
0.6%
3774 2
0.6%
3767 4
1.2%

사업장명
Text

Distinct307
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-06T20:05:46.699108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length6.021875
Min length2

Characters and Unicode

Total characters1927
Distinct characters395
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique295 ?
Unique (%)92.2%

Sample

1st row호원당
2nd row엄마손도시락
3rd row삼정
4th row성실식품
5th row서강냉동(주)
ValueCountFrequency (%)
주식회사 12
 
3.3%
열린김밥 3
 
0.8%
좋은식품 3
 
0.8%
커피 2
 
0.5%
초당푸드 2
 
0.5%
동일데코 2
 
0.5%
교회김밥 2
 
0.5%
대성식품 2
 
0.5%
food 2
 
0.5%
김정원식품 2
 
0.5%
Other values (332) 337
91.3%
2024-04-06T20:05:47.339589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 85
 
4.4%
품 66
 
3.4%
( 52
 
2.7%
) 52
 
2.7%
주 50
 
2.6%
49
 
2.5%
스 42
 
2.2%
이 38
 
2.0%
리 31
 
1.6%
피 29
 
1.5%
Other values (385) 1433
74.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1622
84.2%
Uppercase Letter 83
 
4.3%
Lowercase Letter 53
 
2.8%
Open Punctuation 52
 
2.7%
Close Punctuation 52
 
2.7%
Space Separator 49
 
2.5%
Decimal Number 10
 
0.5%
Other Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 85
 
5.2%
품 66
 
4.1%
주 50
 
3.1%
스 42
 
2.6%
이 38
 
2.3%
리 31
 
1.9%
피 29
 
1.8%
커 28
 
1.7%
드 27
 
1.7%
사 27
 
1.7%
Other values (334) 1199
73.9%
Lowercase Letter
ValueCountFrequency (%)
o 6
 
11.3%
l 6
 
11.3%
a 6
 
11.3%
r 3
 
5.7%
d 3
 
5.7%
u 3
 
5.7%
e 3
 
5.7%
t 3
 
5.7%
h 3
 
5.7%
n 2
 
3.8%
Other values (10) 15
28.3%
Uppercase Letter
ValueCountFrequency (%)
A 11
13.3%
E 10
12.0%
S 8
9.6%
F 7
8.4%
O 7
8.4%
T 6
 
7.2%
R 5
 
6.0%
K 5
 
6.0%
C 4
 
4.8%
I 3
 
3.6%
Other values (9) 17
20.5%
Decimal Number
ValueCountFrequency (%)
1 4
40.0%
9 2
20.0%
3 1
 
10.0%
0 1
 
10.0%
4 1
 
10.0%
2 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
? 3
50.0%
& 2
33.3%
' 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Space Separator
ValueCountFrequency (%)
49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1620
84.1%
Common 169
 
8.8%
Latin 136
 
7.1%
Han 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 85
 
5.2%
품 66
 
4.1%
주 50
 
3.1%
스 42
 
2.6%
이 38
 
2.3%
리 31
 
1.9%
피 29
 
1.8%
커 28
 
1.7%
드 27
 
1.7%
사 27
 
1.7%
Other values (332) 1197
73.9%
Latin
ValueCountFrequency (%)
A 11
 
8.1%
E 10
 
7.4%
S 8
 
5.9%
F 7
 
5.1%
O 7
 
5.1%
o 6
 
4.4%
T 6
 
4.4%
l 6
 
4.4%
a 6
 
4.4%
R 5
 
3.7%
Other values (29) 64
47.1%
Common
ValueCountFrequency (%)
( 52
30.8%
) 52
30.8%
49
29.0%
1 4
 
2.4%
? 3
 
1.8%
& 2
 
1.2%
9 2
 
1.2%
3 1
 
0.6%
0 1
 
0.6%
' 1
 
0.6%
Other values (2) 2
 
1.2%
Han
ValueCountFrequency (%)
味 1
50.0%
一 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1620
84.1%
ASCII 305
 
15.8%
CJK 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 85
 
5.2%
품 66
 
4.1%
주 50
 
3.1%
스 42
 
2.6%
이 38
 
2.3%
리 31
 
1.9%
피 29
 
1.8%
커 28
 
1.7%
드 27
 
1.7%
사 27
 
1.7%
Other values (332) 1197
73.9%
ASCII
ValueCountFrequency (%)
( 52
17.0%
) 52
17.0%
49
16.1%
A 11
 
3.6%
E 10
 
3.3%
S 8
 
2.6%
F 7
 
2.3%
O 7
 
2.3%
o 6
 
2.0%
T 6
 
2.0%
Other values (41) 97
31.8%
CJK
ValueCountFrequency (%)
味 1
50.0%
一 1
50.0%

최종수정일자
Date

Distinct273
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1999-03-30 00:00:00
Maximum2024-02-29 13:33:24
2024-04-06T20:05:47.581887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:05:47.979537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
I
245 
U
75 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 245
76.6%
U 75
 
23.4%

Length

2024-04-06T20:05:48.285883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:48.530068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 245
76.6%
u 75
 
23.4%

데이터갱신일자
Date

Distinct82
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:02:00
2024-04-06T20:05:48.730406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:05:48.954981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
식품제조가공업
250 
기타 식품제조가공업
70 

Length

Max length10
Median length7
Mean length7.65625
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 250
78.1%
기타 식품제조가공업 70
 
21.9%

Length

2024-04-06T20:05:49.201456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:49.389488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 320
82.1%
기타 70
 
17.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct244
Distinct (%)83.6%
Missing28
Missing (%)8.8%
Infinite0
Infinite (%)0.0%
Mean194312.71
Minimum191513.61
Maximum196920.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T20:05:49.604412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191513.61
5-th percentile192100.82
Q1193371.22
median194100.97
Q3195247.97
95-th percentile196491.78
Maximum196920.38
Range5406.7735
Interquartile range (IQR)1876.7574

Descriptive statistics

Standard deviation1353.5286
Coefficient of variation (CV)0.0069657233
Kurtosis-0.85886761
Mean194312.71
Median Absolute Deviation (MAD)963.91088
Skewness0.10627811
Sum56739313
Variance1832039.7
MonotonicityNot monotonic
2024-04-06T20:05:49.865084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193416.921899655 6
 
1.9%
193865.64966259 4
 
1.2%
193496.619931554 3
 
0.9%
196310.944076058 3
 
0.9%
193423.550017619 3
 
0.9%
195250.910817386 3
 
0.9%
194005.155662741 3
 
0.9%
192260.299912091 3
 
0.9%
196417.482485029 2
 
0.6%
193186.387532981 2
 
0.6%
Other values (234) 260
81.2%
(Missing) 28
 
8.8%
ValueCountFrequency (%)
191513.605808387 1
0.3%
191552.612967645 1
0.3%
191722.904084852 2
0.6%
191775.454608314 1
0.3%
191813.968062976 1
0.3%
191833.644665447 1
0.3%
191890.551004527 1
0.3%
191900.345924872 1
0.3%
191906.306249876 1
0.3%
191934.180587634 1
0.3%
ValueCountFrequency (%)
196920.379343082 1
0.3%
196824.072701729 2
0.6%
196808.279318334 1
0.3%
196791.676370681 1
0.3%
196753.553383122 1
0.3%
196725.671915286 1
0.3%
196638.096232174 1
0.3%
196587.113380357 1
0.3%
196567.532335528 1
0.3%
196529.106004935 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct244
Distinct (%)83.6%
Missing28
Missing (%)8.8%
Infinite0
Infinite (%)0.0%
Mean452356.56
Minimum450514.69
Maximum455689.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T20:05:50.125188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450514.69
5-th percentile450615.47
Q1451606.57
median452224.24
Q3453069.5
95-th percentile454578.14
Maximum455689.57
Range5174.8765
Interquartile range (IQR)1462.925

Descriptive statistics

Standard deviation1174.6846
Coefficient of variation (CV)0.0025968112
Kurtosis-0.24649561
Mean452356.56
Median Absolute Deviation (MAD)749.9576
Skewness0.43827942
Sum1.3208812 × 108
Variance1379883.9
MonotonicityNot monotonic
2024-04-06T20:05:50.342867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452463.4370783 6
 
1.9%
451726.70946695 4
 
1.2%
452433.673774827 3
 
0.9%
452215.456955745 3
 
0.9%
452263.136505739 3
 
0.9%
454382.754575063 3
 
0.9%
451865.85926568 3
 
0.9%
452692.508806554 3
 
0.9%
452051.567055794 2
 
0.6%
452804.435490701 2
 
0.6%
Other values (234) 260
81.2%
(Missing) 28
 
8.8%
ValueCountFrequency (%)
450514.690947083 1
0.3%
450521.675152727 1
0.3%
450545.586789985 1
0.3%
450549.583846685 1
0.3%
450553.482394679 1
0.3%
450554.494715659 1
0.3%
450555.023793313 1
0.3%
450557.294546519 1
0.3%
450561.690366905 1
0.3%
450572.551844617 1
0.3%
ValueCountFrequency (%)
455689.567479919 1
0.3%
455430.406456381 1
0.3%
455238.626257559 1
0.3%
455227.459706339 1
0.3%
455093.126165183 1
0.3%
455046.787095163 1
0.3%
455022.470008475 1
0.3%
454951.662049415 1
0.3%
454849.736986874 1
0.3%
454840.5866926 1
0.3%

위생업태명
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
식품제조가공업
244 
기타 식품제조가공업
43 
<NA>
33 

Length

Max length10
Median length7
Mean length7.09375
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 244
76.2%
기타 식품제조가공업 43
 
13.4%
<NA> 33
 
10.3%

Length

2024-04-06T20:05:50.583144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:50.769543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 287
79.1%
기타 43
 
11.8%
na 33
 
9.1%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
275 
0
34 
1
 
8
7
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.578125
Min length1

Unique

Unique3 ?
Unique (%)0.9%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row7

Common Values

ValueCountFrequency (%)
<NA> 275
85.9%
0 34
 
10.6%
1 8
 
2.5%
7 1
 
0.3%
2 1
 
0.3%
3 1
 
0.3%

Length

2024-04-06T20:05:51.007416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:51.241924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 275
85.9%
0 34
 
10.6%
1 8
 
2.5%
7 1
 
0.3%
2 1
 
0.3%
3 1
 
0.3%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
275 
0
37 
1
 
4
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.578125
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row3
5th row2

Common Values

ValueCountFrequency (%)
<NA> 275
85.9%
0 37
 
11.6%
1 4
 
1.2%
2 3
 
0.9%
3 1
 
0.3%

Length

2024-04-06T20:05:51.426625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:51.614000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 275
85.9%
0 37
 
11.6%
1 4
 
1.2%
2 3
 
0.9%
3 1
 
0.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
254 
주택가주변
37 
기타
28 
아파트지역
 
1

Length

Max length5
Median length4
Mean length3.94375
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row기타
2nd row주택가주변
3rd row주택가주변
4th row주택가주변
5th row주택가주변

Common Values

ValueCountFrequency (%)
<NA> 254
79.4%
주택가주변 37
 
11.6%
기타 28
 
8.8%
아파트지역 1
 
0.3%

Length

2024-04-06T20:05:51.813061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:52.014168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 254
79.4%
주택가주변 37
 
11.6%
기타 28
 
8.8%
아파트지역 1
 
0.3%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
254 
기타
51 
자율
 
10
우수
 
4
을
 
1

Length

Max length4
Median length4
Mean length3.584375
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row을
2nd row기타
3rd row기타
4th row기타
5th row우수

Common Values

ValueCountFrequency (%)
<NA> 254
79.4%
기타 51
 
15.9%
자율 10
 
3.1%
우수 4
 
1.2%
을 1
 
0.3%

Length

2024-04-06T20:05:52.217170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:52.400805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 254
79.4%
기타 51
 
15.9%
자율 10
 
3.1%
우수 4
 
1.2%
을 1
 
0.3%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
상수도전용
160 
<NA>
160 

Length

Max length5
Median length4.5
Mean length4.5
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 160
50.0%
<NA> 160
50.0%

Length

2024-04-06T20:05:52.600628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:52.808534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 160
50.0%
na 160
50.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
310 
0
 
10

Length

Max length4
Median length4
Mean length3.90625
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> 310
96.9%
0 10
 
3.1%

Length

2024-04-06T20:05:53.039061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:53.234272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 310
96.9%
0 10
 
3.1%

본사종업원수
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
186 
<NA>
133 
3
 
1

Length

Max length4
Median length1
Mean length2.246875
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 186
58.1%
<NA> 133
41.6%
3 1
 
0.3%

Length

2024-04-06T20:05:53.421622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:53.636261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 186
58.1%
na 133
41.6%
3 1
 
0.3%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
185 
<NA>
132 
1
 
3

Length

Max length4
Median length1
Mean length2.2375
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 185
57.8%
<NA> 132
41.2%
1 3
 
0.9%

Length

2024-04-06T20:05:53.846366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:54.411210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 185
57.8%
na 132
41.2%
1 3
 
0.9%

공장판매직종업원수
Categorical

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
183 
<NA>
133 
1
 
3
3
 
1

Length

Max length4
Median length1
Mean length2.246875
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 183
57.2%
<NA> 133
41.6%
1 3
 
0.9%
3 1
 
0.3%

Length

2024-04-06T20:05:54.637072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:54.818320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 183
57.2%
na 133
41.6%
1 3
 
0.9%
3 1
 
0.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
177 
<NA>
129 
2
 
6
1
 
6
4
 
1

Length

Max length4
Median length1
Mean length2.209375
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 177
55.3%
<NA> 129
40.3%
2 6
 
1.9%
1 6
 
1.9%
4 1
 
0.3%
3 1
 
0.3%

Length

2024-04-06T20:05:55.000292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:55.178887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 177
55.3%
na 129
40.3%
2 6
 
1.9%
1 6
 
1.9%
4 1
 
0.3%
3 1
 
0.3%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
임대
147 
<NA>
140 
자가
33 

Length

Max length4
Median length2
Mean length2.875
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 (%)
임대 147
45.9%
<NA> 140
43.8%
자가 33
 
10.3%

Length

2024-04-06T20:05:55.417322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:55.603010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 147
45.9%
na 140
43.8%
자가 33
 
10.3%

보증액
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
274 
0
46 

Length

Max length4
Median length4
Mean length3.56875
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> 274
85.6%
0 46
 
14.4%

Length

2024-04-06T20:05:55.777032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:56.008832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 274
85.6%
0 46
 
14.4%

월세액
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
274 
0
46 

Length

Max length4
Median length4
Mean length3.56875
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> 274
85.6%
0 46
 
14.4%

Length

2024-04-06T20:05:56.197691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:05:56.401030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 274
85.6%
0 46
 
14.4%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.7%
Missing33
Missing (%)10.3%
Memory size772.0 B
False
286 
True
 
1
(Missing)
33 
ValueCountFrequency (%)
False 286
89.4%
True 1
 
0.3%
(Missing) 33
 
10.3%
2024-04-06T20:05:56.565409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct51
Distinct (%)17.8%
Missing33
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean4.7955052
Minimum0
Maximum110
Zeros237
Zeros (%)74.1%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-06T20:05:56.781218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile31.211
Maximum110
Range110
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.37261
Coefficient of variation (CV)2.9971002
Kurtosis19.086987
Mean4.7955052
Median Absolute Deviation (MAD)0
Skewness4.0747991
Sum1376.31
Variance206.57191
MonotonicityNot monotonic
2024-04-06T20:05:57.010797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 237
74.1%
12.68 1
 
0.3%
8.71 1
 
0.3%
3.08 1
 
0.3%
21.58 1
 
0.3%
8.19 1
 
0.3%
11.98 1
 
0.3%
23.86 1
 
0.3%
2.5 1
 
0.3%
18.62 1
 
0.3%
Other values (41) 41
 
12.8%
(Missing) 33
 
10.3%
ValueCountFrequency (%)
0.0 237
74.1%
1.5 1
 
0.3%
2.5 1
 
0.3%
3.08 1
 
0.3%
4.5 1
 
0.3%
4.83 1
 
0.3%
5.88 1
 
0.3%
7.0 1
 
0.3%
8.19 1
 
0.3%
8.71 1
 
0.3%
ValueCountFrequency (%)
110.0 1
0.3%
85.0 1
0.3%
74.5 1
0.3%
72.9 1
0.3%
68.66 1
0.3%
64.91 1
0.3%
57.25 1
0.3%
51.57 1
0.3%
49.35 1
0.3%
45.79 1
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing320
Missing (%)100.0%
Memory size2.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing320
Missing (%)100.0%
Memory size2.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing320
Missing (%)100.0%
Memory size2.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031200003120000-106-1976-0006619760810<NA>3폐업2폐업20111103<NA><NA><NA>02 3655901294.76120170서울특별시 서대문구 대현동 37-24번지 ,27<NA><NA>호원당2011-09-21 11:38:42I2018-08-31 23:59:59.0식품제조가공업195001.627823450662.634874식품제조가공업00기타을상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
131200003120000-106-1989-0002519890327<NA>3폐업2폐업19980713<NA><NA><NA>02 3964806136.91120855서울특별시 서대문구 홍제동 157-73번지<NA><NA>엄마손도시락2001-09-30 00:00:00I2018-08-31 23:59:59.0식품제조가공업195137.943673453720.747482식품제조가공업<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231200003120000-106-1989-0002619890516<NA>3폐업2폐업20011108<NA><NA><NA>02 33521110.0120824서울특별시 서대문구 연희동 81-1번지<NA><NA>삼정1999-04-12 00:00:00I2018-08-31 23:59:59.0식품제조가공업194193.238981452248.148691식품제조가공업<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331200003120000-106-1990-0002719901126<NA>1영업/정상1영업<NA><NA><NA><NA>02 3625274107.16120819서울특별시 서대문구 북아현동 129-75번지 3층서울특별시 서대문구 북아현로4길 9-7 (북아현동, 3층)3756성실식품2019-01-24 15:49:15U2019-01-26 02:40:00.0식품제조가공업196156.80095450841.045096식품제조가공업03주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
431200003120000-106-1991-0007019911021<NA>3폐업2폐업20120704<NA><NA><NA>02 3347020217.04120828서울특별시 서대문구 연희동 218-7번지<NA><NA>서강냉동(주)2002-03-05 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업72주택가주변우수<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
531200003120000-106-1992-0001919920822<NA>3폐업2폐업19980713<NA><NA><NA>02 312805170.18120050서울특별시 서대문구 냉천동 24-3번지<NA><NA>희성식품2002-03-06 00:00:00I2018-08-31 23:59:59.0식품제조가공업196753.553383451675.348246식품제조가공업<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631200003120000-106-1993-0000119930803<NA>3폐업2폐업19960916<NA><NA><NA>02 39439990.0120857서울특별시 서대문구 홍제동 266-181번지<NA><NA>동일사2001-09-30 00:00:00I2018-08-31 23:59:59.0식품제조가공업195250.910817454382.754575식품제조가공업00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731200003120000-106-1994-0000219940406<NA>3폐업2폐업20090813<NA><NA><NA>02 336361264.25120823서울특별시 서대문구 연희동 75-8번지<NA><NA>부향식품2002-03-05 00:00:00I2018-08-31 23:59:59.0식품제조가공업194356.524455452336.196647식품제조가공업00주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
831200003120000-106-1994-0002819940225<NA>3폐업2폐업20011224<NA><NA><NA>02 33802510.0120832서울특별시 서대문구 연희동 629-0번지<NA><NA>(주)선비외식산업2002-03-06 00:00:00I2018-08-31 23:59:59.0식품제조가공업193416.9219452463.437078식품제조가공업<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931200003120000-106-1994-0002919940601<NA>3폐업2폐업20170228<NA><NA><NA>02 363987152.0120861서울특별시 서대문구 홍제동 334-93번지서울특별시 서대문구 홍제내4길 5 (홍제동)3640우리김밥2016-03-15 15:19:37I2018-08-31 23:59:59.0식품제조가공업194345.761674453956.10009식품제조가공업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
31031200003120000-106-2021-0000520210907<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.36120825서울특별시 서대문구 연희동 137-1 2층서울특별시 서대문구 연희로 109, 2층 (연희동)3708프로토콜(protokoll)2021-09-07 16:36:22I2021-09-09 00:22:49.0기타 식품제조가공업193865.649663451726.709467기타 식품제조가공업00<NA><NA>상수도전용00000임대00N0.0<NA><NA><NA>
31131200003120000-106-2021-0000620210909<NA>3폐업2폐업20221202<NA><NA><NA>02 312125112.5120808서울특별시 서대문구 대현동 45-41 1층서울특별시 서대문구 이화여대2길 10, 1층 (대현동)3767폴어반(Paul Urban)2022-12-02 13:44:06U2021-11-02 00:04:00.0기타 식품제조가공업195201.928159450557.294547<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31231200003120000-106-2021-000072021-10-26<NA>3폐업2폐업2023-03-31<NA><NA><NA>02 5439901177.72120-825서울특별시 서대문구 연희동 137-1 지층서울특별시 서대문구 연희로 109, 지층 (연희동)3708디앤지푸드2023-03-31 16:18:11U2022-12-04 00:02:00.0기타 식품제조가공업193865.649663451726.709467<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31331200003120000-106-2021-0000820211102<NA>1영업/정상1영업<NA><NA><NA><NA>07042811688165.61120825서울특별시 서대문구 연희동 193-7 영화빌딩 2층 202호서울특별시 서대문구 연희로 77-12, 영화빌딩 2층 202호 (연희동)3708팩토리12022-08-24 09:58:48U2021-12-07 22:06:00.0기타 식품제조가공업193672.286457451473.301783<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31431200003120000-106-2022-0000120220214<NA>1영업/정상1영업<NA><NA><NA><NA><NA>49.5120824서울특별시 서대문구 연희동 92-18 연희빌딩서울특별시 서대문구 증가로 18, 연희빌딩 1층 (연희동)3698커피가게 동경2022-02-14 16:24:38I2022-02-16 00:22:49.0기타 식품제조가공업193860.582118451975.128846기타 식품제조가공업00<NA><NA>상수도전용00000<NA>00N0.0<NA><NA><NA>
31531200003120000-106-2022-000022022-09-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>45.0120-814서울특별시 서대문구 북가좌동 316-32서울특별시 서대문구 거북골로 208-1, 2층 (북가좌동)3681주식회사 네마2023-10-20 16:54:28U2022-10-30 22:02:00.0기타 식품제조가공업191833.644665452973.216988<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31631200003120000-106-2022-0000320221007<NA>1영업/정상1영업<NA><NA><NA><NA><NA>153.12120829서울특별시 서대문구 연희동 88-22서울특별시 서대문구 연희로 130, 지하1층 (연희동)3723주식회사 빅이어2022-10-07 15:02:09I2021-10-31 00:09:00.0기타 식품제조가공업194005.155663451865.859266<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31731200003120000-106-2022-0000420221109<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.5120825서울특별시 서대문구 연희동 192-17 노엘서울특별시 서대문구 성산로 333, 노엘 2층 (연희동)3707디폴트 밸류(default value)2022-11-09 10:59:39I2021-10-31 23:02:00.0기타 식품제조가공업193512.517179451546.509556<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31831200003120000-106-2023-0000120230110<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.9120825서울특별시 서대문구 연희동 122-2 연희빌딩서울특별시 서대문구 증가로 15, 연희빌딩 지하1층 (연희동)3703명인미트2023-01-10 16:09:40I2022-11-30 23:02:00.0기타 식품제조가공업193838.398371451917.623382<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31931200003120000-106-2024-000012024-02-16<NA>1영업/정상1영업<NA><NA><NA><NA>02 7630163177.72120-825서울특별시 서대문구 연희동 137-1서울특별시 서대문구 연희로 109, 지하1층 (연희동)3708생과방2024-02-16 11:03:25I2023-12-01 23:08:00.0기타 식품제조가공업193865.649663451726.709467<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>