Overview

Dataset statistics

Number of variables44
Number of observations38
Missing cells493
Missing cells (%)29.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.1 KiB
Average record size in memory379.5 B

Variable types

Categorical19
Text7
DateTime3
Unsupported10
Numeric4
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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-18344/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
위생업태명 is highly imbalanced (60.2%)Imbalance
보증액 is highly imbalanced (77.9%)Imbalance
월세액 is highly imbalanced (77.9%)Imbalance
시설총규모 is highly imbalanced (64.0%)Imbalance
인허가취소일자 has 38 (100.0%) missing valuesMissing
폐업일자 has 8 (21.1%) missing valuesMissing
휴업시작일자 has 38 (100.0%) missing valuesMissing
휴업종료일자 has 38 (100.0%) missing valuesMissing
재개업일자 has 38 (100.0%) missing valuesMissing
전화번호 has 2 (5.3%) missing valuesMissing
소재지면적 has 11 (28.9%) missing valuesMissing
도로명주소 has 24 (63.2%) missing valuesMissing
도로명우편번호 has 25 (65.8%) missing valuesMissing
좌표정보(X) has 3 (7.9%) missing valuesMissing
좌표정보(Y) has 3 (7.9%) missing valuesMissing
남성종사자수 has 38 (100.0%) missing valuesMissing
여성종사자수 has 38 (100.0%) missing valuesMissing
총인원 has 38 (100.0%) missing valuesMissing
건물소유구분명 has 34 (89.5%) missing valuesMissing
다중이용업소여부 has 3 (7.9%) missing valuesMissing
전통업소지정번호 has 38 (100.0%) missing valuesMissing
전통업소주된음식 has 38 (100.0%) missing valuesMissing
홈페이지 has 38 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
사업장명 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
남성종사자수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
여성종사자수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총인원 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

Reproduction

Analysis started2024-05-11 02:21:32.272393
Analysis finished2024-05-11 02:21:33.224611
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
3170000
38 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 38
100.0%

Length

2024-05-11T02:21:33.458990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:33.786414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 38
100.0%

관리번호
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-05-11T02:21:34.206801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters836
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

Unique38 ?
Unique (%)100.0%

Sample

1st row3170000-118-1985-00281
2nd row3170000-118-1985-00282
3rd row3170000-118-1986-00288
4th row3170000-118-1986-00289
5th row3170000-118-1988-00285
ValueCountFrequency (%)
3170000-118-1985-00281 1
 
2.6%
3170000-118-2007-00001 1
 
2.6%
3170000-118-2018-00001 1
 
2.6%
3170000-118-2003-00001 1
 
2.6%
3170000-118-2003-00002 1
 
2.6%
3170000-118-2004-00001 1
 
2.6%
3170000-118-2005-00001 1
 
2.6%
3170000-118-2005-00002 1
 
2.6%
3170000-118-2005-00003 1
 
2.6%
3170000-118-2008-00002 1
 
2.6%
Other values (28) 28
73.7%
2024-05-11T02:21:35.256010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 331
39.6%
1 152
18.2%
- 114
 
13.6%
8 61
 
7.3%
2 50
 
6.0%
3 45
 
5.4%
7 41
 
4.9%
9 21
 
2.5%
5 9
 
1.1%
4 9
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 722
86.4%
Dash Punctuation 114
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 331
45.8%
1 152
21.1%
8 61
 
8.4%
2 50
 
6.9%
3 45
 
6.2%
7 41
 
5.7%
9 21
 
2.9%
5 9
 
1.2%
4 9
 
1.2%
6 3
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 836
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 331
39.6%
1 152
18.2%
- 114
 
13.6%
8 61
 
7.3%
2 50
 
6.0%
3 45
 
5.4%
7 41
 
4.9%
9 21
 
2.5%
5 9
 
1.1%
4 9
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 331
39.6%
1 152
18.2%
- 114
 
13.6%
8 61
 
7.3%
2 50
 
6.0%
3 45
 
5.4%
7 41
 
4.9%
9 21
 
2.5%
5 9
 
1.1%
4 9
 
1.1%

인허가일자
Date

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
Minimum1985-09-28 00:00:00
Maximum2020-07-27 00:00:00
2024-05-11T02:21:35.683005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:21:36.155786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
3
30 
1
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 30
78.9%
1 8
 
21.1%

Length

2024-05-11T02:21:36.914002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:37.561693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 30
78.9%
1 8
 
21.1%

영업상태명
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
폐업
30 
영업/정상
8 

Length

Max length5
Median length2
Mean length2.6315789
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 30
78.9%
영업/정상 8
 
21.1%

Length

2024-05-11T02:21:38.317709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:38.675810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 30
78.9%
영업/정상 8
 
21.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
2
30 
1
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 30
78.9%
1 8
 
21.1%

Length

2024-05-11T02:21:39.212188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:39.522162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 30
78.9%
1 8
 
21.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
폐업
30 
영업
8 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 30
78.9%
영업 8
 
21.1%

Length

2024-05-11T02:21:39.844266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:40.160661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 30
78.9%
영업 8
 
21.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)93.3%
Missing8
Missing (%)21.1%
Infinite0
Infinite (%)0.0%
Mean20076432
Minimum19980903
Maximum20220609
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-05-11T02:21:40.600437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980903
5-th percentile19999646
Q120040138
median20060308
Q320105265
95-th percentile20190682
Maximum20220609
Range239706
Interquartile range (IQR)65127.25

Descriptive statistics

Standard deviation62883.132
Coefficient of variation (CV)0.0031321866
Kurtosis-0.11838758
Mean20076432
Median Absolute Deviation (MAD)29897.5
Skewness0.86368364
Sum6.0229296 × 108
Variance3.9542882 × 109
MonotonicityNot monotonic
2024-05-11T02:21:40.924417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
20080131 2
 
5.3%
20040504 2
 
5.3%
20220609 1
 
2.6%
20120608 1
 
2.6%
20110317 1
 
2.6%
20090109 1
 
2.6%
20060411 1
 
2.6%
20051221 1
 
2.6%
20060213 1
 
2.6%
20190412 1
 
2.6%
Other values (18) 18
47.4%
(Missing) 8
21.1%
ValueCountFrequency (%)
19980903 1
2.6%
19990423 1
2.6%
20010919 1
2.6%
20020328 1
2.6%
20020626 1
2.6%
20030127 1
2.6%
20030314 1
2.6%
20040113 1
2.6%
20040212 1
2.6%
20040504 2
5.3%
ValueCountFrequency (%)
20220609 1
2.6%
20190903 1
2.6%
20190412 1
2.6%
20180202 1
2.6%
20160623 1
2.6%
20160129 1
2.6%
20120608 1
2.6%
20110317 1
2.6%
20090109 1
2.6%
20080131 2
5.3%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

전화번호
Text

MISSING 

Distinct35
Distinct (%)97.2%
Missing2
Missing (%)5.3%
Memory size436.0 B
2024-05-11T02:21:41.350368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.5
Min length6

Characters and Unicode

Total characters378
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

Unique34 ?
Unique (%)94.4%

Sample

1st row02 8558425
2nd row02 8651472
3rd row02 8559551
4th row02 8044709
5th row02 8538211
ValueCountFrequency (%)
02 34
44.2%
8510105 2
 
2.6%
851 1
 
1.3%
7431 1
 
1.3%
6227 1
 
1.3%
8381055 1
 
1.3%
855 1
 
1.3%
9551 1
 
1.3%
0221630651 1
 
1.3%
8073690 1
 
1.3%
Other values (33) 33
42.9%
2024-05-11T02:21:42.547151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 66
17.5%
58
15.3%
2 54
14.3%
8 43
11.4%
5 39
10.3%
1 32
8.5%
7 22
 
5.8%
6 20
 
5.3%
3 18
 
4.8%
4 16
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 320
84.7%
Space Separator 58
 
15.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 66
20.6%
2 54
16.9%
8 43
13.4%
5 39
12.2%
1 32
10.0%
7 22
 
6.9%
6 20
 
6.2%
3 18
 
5.6%
4 16
 
5.0%
9 10
 
3.1%
Space Separator
ValueCountFrequency (%)
58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 378
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 66
17.5%
58
15.3%
2 54
14.3%
8 43
11.4%
5 39
10.3%
1 32
8.5%
7 22
 
5.8%
6 20
 
5.3%
3 18
 
4.8%
4 16
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 66
17.5%
58
15.3%
2 54
14.3%
8 43
11.4%
5 39
10.3%
1 32
8.5%
7 22
 
5.8%
6 20
 
5.3%
3 18
 
4.8%
4 16
 
4.2%

소재지면적
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing11
Missing (%)28.9%
Memory size436.0 B
2024-05-11T02:21:43.530525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.8148148
Min length3

Characters and Unicode

Total characters157
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

Unique27 ?
Unique (%)100.0%

Sample

1st row139.02
2nd row98.28
3rd row93.60
4th row.00
5th row442.68
ValueCountFrequency (%)
139.02 1
 
3.7%
1,544.00 1
 
3.7%
119.61 1
 
3.7%
345.00 1
 
3.7%
6317.00 1
 
3.7%
333.77 1
 
3.7%
132.00 1
 
3.7%
82.60 1
 
3.7%
230.40 1
 
3.7%
46.08 1
 
3.7%
Other values (17) 17
63.0%
2024-05-11T02:21:44.644697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28
17.8%
. 27
17.2%
1 18
11.5%
6 15
9.6%
3 14
8.9%
4 12
7.6%
2 10
 
6.4%
8 10
 
6.4%
7 9
 
5.7%
9 6
 
3.8%
Other values (2) 8
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 128
81.5%
Other Punctuation 29
 
18.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28
21.9%
1 18
14.1%
6 15
11.7%
3 14
10.9%
4 12
9.4%
2 10
 
7.8%
8 10
 
7.8%
7 9
 
7.0%
9 6
 
4.7%
5 6
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 27
93.1%
, 2
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
Common 157
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28
17.8%
. 27
17.2%
1 18
11.5%
6 15
9.6%
3 14
8.9%
4 12
7.6%
2 10
 
6.4%
8 10
 
6.4%
7 9
 
5.7%
9 6
 
3.8%
Other values (2) 8
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 157
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28
17.8%
. 27
17.2%
1 18
11.5%
6 15
9.6%
3 14
8.9%
4 12
7.6%
2 10
 
6.4%
8 10
 
6.4%
7 9
 
5.7%
9 6
 
3.8%
Other values (2) 8
 
5.1%

소재지우편번호
Categorical

Distinct10
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
153813
9 
153803
9 
153802
5 
153814
5 
153801
4 
Other values (5)
6 

Length

Max length7
Median length6
Mean length6.0526316
Min length6

Unique

Unique4 ?
Unique (%)10.5%

Sample

1st row153813
2nd row153803
3rd row153813
4th row153802
5th row153841

Common Values

ValueCountFrequency (%)
153813 9
23.7%
153803 9
23.7%
153802 5
13.2%
153814 5
13.2%
153801 4
10.5%
153-803 2
 
5.3%
153841 1
 
2.6%
153829 1
 
2.6%
153864 1
 
2.6%
153010 1
 
2.6%

Length

2024-05-11T02:21:45.241676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:45.794170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
153813 9
23.7%
153803 9
23.7%
153802 5
13.2%
153814 5
13.2%
153801 4
10.5%
153-803 2
 
5.3%
153841 1
 
2.6%
153829 1
 
2.6%
153864 1
 
2.6%
153010 1
 
2.6%

지번주소
Text

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-05-11T02:21:46.488676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length35
Mean length26.078947
Min length18

Characters and Unicode

Total characters991
Distinct characters80
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)94.7%

Sample

1st row서울특별시 금천구 독산동 295-4
2nd row서울특별시 금천구 가산동 550-1
3rd row서울특별시 금천구 독산동 299-13
4th row서울특별시 금천구 가산동 345-19
5th row서울특별시 금천구 시흥동 832-24
ValueCountFrequency (%)
서울특별시 38
20.3%
금천구 38
20.3%
가산동 20
 
10.7%
독산동 16
 
8.6%
567-13 2
 
1.1%
301-14 2
 
1.1%
345-19 2
 
1.1%
시흥동 2
 
1.1%
1층 2
 
1.1%
가산디지털1길 2
 
1.1%
Other values (63) 63
33.7%
2024-05-11T02:21:47.592598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
188
19.0%
1 53
 
5.3%
산 45
 
4.5%
시 40
 
4.0%
3 40
 
4.0%
동 39
 
3.9%
서 38
 
3.8%
특 38
 
3.8%
별 38
 
3.8%
금 38
 
3.8%
Other values (70) 434
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 517
52.2%
Decimal Number 219
22.1%
Space Separator 188
 
19.0%
Dash Punctuation 36
 
3.6%
Open Punctuation 13
 
1.3%
Close Punctuation 13
 
1.3%
Uppercase Letter 4
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 45
 
8.7%
시 40
 
7.7%
동 39
 
7.5%
서 38
 
7.4%
특 38
 
7.4%
별 38
 
7.4%
금 38
 
7.4%
천 38
 
7.4%
구 38
 
7.4%
울 38
 
7.4%
Other values (49) 127
24.6%
Decimal Number
ValueCountFrequency (%)
1 53
24.2%
3 40
18.3%
2 26
11.9%
5 19
 
8.7%
9 18
 
8.2%
4 17
 
7.8%
0 15
 
6.8%
7 12
 
5.5%
6 11
 
5.0%
8 8
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
K 1
25.0%
S 1
25.0%
A 1
25.0%
B 1
25.0%
Open Punctuation
ValueCountFrequency (%)
[ 9
69.2%
( 4
30.8%
Close Punctuation
ValueCountFrequency (%)
] 9
69.2%
) 4
30.8%
Space Separator
ValueCountFrequency (%)
188
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 517
52.2%
Common 470
47.4%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 45
 
8.7%
시 40
 
7.7%
동 39
 
7.5%
서 38
 
7.4%
특 38
 
7.4%
별 38
 
7.4%
금 38
 
7.4%
천 38
 
7.4%
구 38
 
7.4%
울 38
 
7.4%
Other values (49) 127
24.6%
Common
ValueCountFrequency (%)
188
40.0%
1 53
 
11.3%
3 40
 
8.5%
- 36
 
7.7%
2 26
 
5.5%
5 19
 
4.0%
9 18
 
3.8%
4 17
 
3.6%
0 15
 
3.2%
7 12
 
2.6%
Other values (7) 46
 
9.8%
Latin
ValueCountFrequency (%)
K 1
25.0%
S 1
25.0%
A 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 517
52.2%
ASCII 474
47.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
188
39.7%
1 53
 
11.2%
3 40
 
8.4%
- 36
 
7.6%
2 26
 
5.5%
5 19
 
4.0%
9 18
 
3.8%
4 17
 
3.6%
0 15
 
3.2%
7 12
 
2.5%
Other values (11) 50
 
10.5%
Hangul
ValueCountFrequency (%)
산 45
 
8.7%
시 40
 
7.7%
동 39
 
7.5%
서 38
 
7.4%
특 38
 
7.4%
별 38
 
7.4%
금 38
 
7.4%
천 38
 
7.4%
구 38
 
7.4%
울 38
 
7.4%
Other values (49) 127
24.6%

도로명주소
Text

MISSING 

Distinct13
Distinct (%)92.9%
Missing24
Missing (%)63.2%
Memory size436.0 B
2024-05-11T02:21:48.126709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length50
Mean length37.642857
Min length24

Characters and Unicode

Total characters527
Distinct characters73
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)85.7%

Sample

1st row서울특별시 금천구 가산디지털1로 39 (가산동,[가산디지털1길 194])
2nd row서울특별시 금천구 두산로3길 50 (가산동,[모아래7길 16])
3rd row서울특별시 금천구 가산디지털2로 40 (가산동,[가산디지털2길 159])
4th row서울특별시 금천구 두산로11길 65 (가산동,[두산로11길 65] 1층)
5th row서울특별시 금천구 두산로9길 28 (독산동, 본관)
ValueCountFrequency (%)
서울특별시 14
 
15.1%
금천구 14
 
15.1%
가산동 5
 
5.4%
가산디지털1로 5
 
5.4%
독산동 4
 
4.3%
65 2
 
2.2%
28 2
 
2.2%
두산로9길 2
 
2.2%
지하1층 2
 
2.2%
서부샛길 2
 
2.2%
Other values (39) 41
44.1%
2024-05-11T02:21:49.105151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79
 
15.0%
1 36
 
6.8%
산 32
 
6.1%
가 20
 
3.8%
서 16
 
3.0%
) 15
 
2.8%
동 15
 
2.8%
( 15
 
2.8%
특 14
 
2.7%
별 14
 
2.7%
Other values (63) 271
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
56.9%
Decimal Number 91
 
17.3%
Space Separator 79
 
15.0%
Close Punctuation 20
 
3.8%
Open Punctuation 20
 
3.8%
Other Punctuation 13
 
2.5%
Uppercase Letter 3
 
0.6%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 32
 
10.7%
가 20
 
6.7%
서 16
 
5.3%
동 15
 
5.0%
특 14
 
4.7%
별 14
 
4.7%
시 14
 
4.7%
금 14
 
4.7%
천 14
 
4.7%
구 14
 
4.7%
Other values (43) 133
44.3%
Decimal Number
ValueCountFrequency (%)
1 36
39.6%
9 9
 
9.9%
0 8
 
8.8%
5 8
 
8.8%
2 8
 
8.8%
4 6
 
6.6%
3 5
 
5.5%
8 4
 
4.4%
7 4
 
4.4%
6 3
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
S 1
33.3%
K 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 15
75.0%
] 5
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 15
75.0%
[ 5
 
25.0%
Space Separator
ValueCountFrequency (%)
79
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 300
56.9%
Common 224
42.5%
Latin 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 32
 
10.7%
가 20
 
6.7%
서 16
 
5.3%
동 15
 
5.0%
특 14
 
4.7%
별 14
 
4.7%
시 14
 
4.7%
금 14
 
4.7%
천 14
 
4.7%
구 14
 
4.7%
Other values (43) 133
44.3%
Common
ValueCountFrequency (%)
79
35.3%
1 36
16.1%
) 15
 
6.7%
( 15
 
6.7%
, 13
 
5.8%
9 9
 
4.0%
0 8
 
3.6%
5 8
 
3.6%
2 8
 
3.6%
4 6
 
2.7%
Other values (7) 27
 
12.1%
Latin
ValueCountFrequency (%)
A 1
33.3%
S 1
33.3%
K 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 300
56.9%
ASCII 227
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
79
34.8%
1 36
15.9%
) 15
 
6.6%
( 15
 
6.6%
, 13
 
5.7%
9 9
 
4.0%
0 8
 
3.5%
5 8
 
3.5%
2 8
 
3.5%
4 6
 
2.6%
Other values (10) 30
 
13.2%
Hangul
ValueCountFrequency (%)
산 32
 
10.7%
가 20
 
6.7%
서 16
 
5.3%
동 15
 
5.0%
특 14
 
4.7%
별 14
 
4.7%
시 14
 
4.7%
금 14
 
4.7%
천 14
 
4.7%
구 14
 
4.7%
Other values (43) 133
44.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)61.5%
Missing25
Missing (%)65.8%
Infinite0
Infinite (%)0.0%
Mean8568
Minimum8501
Maximum8594
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-05-11T02:21:49.472605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8501
5-th percentile8511.8
Q18525
median8589
Q38592
95-th percentile8594
Maximum8594
Range93
Interquartile range (IQR)67

Descriptive statistics

Standard deviation35.667445
Coefficient of variation (CV)0.0041628671
Kurtosis-0.90881041
Mean8568
Median Absolute Deviation (MAD)5
Skewness-1.0125103
Sum111384
Variance1272.1667
MonotonicityNot monotonic
2024-05-11T02:21:49.816472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
8592 3
 
7.9%
8594 3
 
7.9%
8525 2
 
5.3%
8519 1
 
2.6%
8589 1
 
2.6%
8583 1
 
2.6%
8584 1
 
2.6%
8501 1
 
2.6%
(Missing) 25
65.8%
ValueCountFrequency (%)
8501 1
 
2.6%
8519 1
 
2.6%
8525 2
5.3%
8583 1
 
2.6%
8584 1
 
2.6%
8589 1
 
2.6%
8592 3
7.9%
8594 3
7.9%
ValueCountFrequency (%)
8594 3
7.9%
8592 3
7.9%
8589 1
 
2.6%
8584 1
 
2.6%
8583 1
 
2.6%
8525 2
5.3%
8519 1
 
2.6%
8501 1
 
2.6%

사업장명
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-05-11T02:21:50.294681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.6842105
Min length2

Characters and Unicode

Total characters254
Distinct characters92
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row유림화학공업(주)
2nd row(주)원지산업
3rd row창원화학
4th row(주)삼보인쇄지기공업사
5th row동성상사
ValueCountFrequency (%)
유림화학공업(주 1
 
2.6%
주)삼화피앤티 1
 
2.6%
승명실업(주 1
 
2.6%
대우인쇄교역 1
 
2.6%
주)삼보에이팩 1
 
2.6%
주)남경케미스트리 1
 
2.6%
주)중앙포리텍 1
 
2.6%
특수산업기술주식회사 1
 
2.6%
나노산업 1
 
2.6%
주)원지산업 1
 
2.6%
Other values (29) 29
74.4%
2024-05-11T02:21:51.142153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 21
 
8.3%
( 20
 
7.9%
) 20
 
7.9%
업 13
 
5.1%
산 8
 
3.1%
피 7
 
2.8%
화 6
 
2.4%
동 6
 
2.4%
삼 6
 
2.4%
사 5
 
2.0%
Other values (82) 142
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 213
83.9%
Open Punctuation 20
 
7.9%
Close Punctuation 20
 
7.9%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 21
 
9.9%
업 13
 
6.1%
산 8
 
3.8%
피 7
 
3.3%
화 6
 
2.8%
동 6
 
2.8%
삼 6
 
2.8%
사 5
 
2.3%
학 5
 
2.3%
공 5
 
2.3%
Other values (79) 131
61.5%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 213
83.9%
Common 41
 
16.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 21
 
9.9%
업 13
 
6.1%
산 8
 
3.8%
피 7
 
3.3%
화 6
 
2.8%
동 6
 
2.8%
삼 6
 
2.8%
사 5
 
2.3%
학 5
 
2.3%
공 5
 
2.3%
Other values (79) 131
61.5%
Common
ValueCountFrequency (%)
( 20
48.8%
) 20
48.8%
1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 213
83.9%
ASCII 41
 
16.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 21
 
9.9%
업 13
 
6.1%
산 8
 
3.8%
피 7
 
3.3%
화 6
 
2.8%
동 6
 
2.8%
삼 6
 
2.8%
사 5
 
2.3%
학 5
 
2.3%
공 5
 
2.3%
Other values (79) 131
61.5%
ASCII
ValueCountFrequency (%)
( 20
48.8%
) 20
48.8%
1
 
2.4%

최종수정일자
Date

Distinct32
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size436.0 B
Minimum1999-09-02 00:00:00
Maximum2024-04-26 14:07:35
2024-05-11T02:21:51.537677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:21:51.958985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
I
29 
U
9 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 29
76.3%
U 9
 
23.7%

Length

2024-05-11T02:21:52.336780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:52.621471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 29
76.3%
u 9
 
23.7%

데이터갱신일자
Date

Distinct10
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:08:00
2024-05-11T02:21:52.920675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:21:53.357765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
용기.포장지제조업
38 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용기.포장지제조업
2nd row용기.포장지제조업
3rd row용기.포장지제조업
4th row용기.포장지제조업
5th row용기.포장지제조업

Common Values

ValueCountFrequency (%)
용기.포장지제조업 38
100.0%

Length

2024-05-11T02:21:53.753345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:54.096986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기.포장지제조업 38
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)91.4%
Missing3
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean190132.47
Minimum189089.93
Maximum191846.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-05-11T02:21:54.463642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189089.93
5-th percentile189223.27
Q1189723.54
median190157.88
Q3190502.45
95-th percentile190861.57
Maximum191846.28
Range2756.3559
Interquartile range (IQR)778.90842

Descriptive statistics

Standard deviation587.71455
Coefficient of variation (CV)0.0030910793
Kurtosis0.79320774
Mean190132.47
Median Absolute Deviation (MAD)389.08802
Skewness0.45232136
Sum6654636.5
Variance345408.39
MonotonicityNot monotonic
2024-05-11T02:21:54.895842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
189678.284548834 2
 
5.3%
190471.011035762 2
 
5.3%
189768.794532397 2
 
5.3%
189575.815287955 1
 
2.6%
189279.333716731 1
 
2.6%
189089.927764903 1
 
2.6%
190735.202947348 1
 
2.6%
189232.30642848 1
 
2.6%
190057.736482527 1
 
2.6%
190479.023027172 1
 
2.6%
Other values (22) 22
57.9%
(Missing) 3
 
7.9%
ValueCountFrequency (%)
189089.927764903 1
2.6%
189202.181652324 1
2.6%
189232.30642848 1
2.6%
189279.333716731 1
2.6%
189497.04098479 1
2.6%
189575.815287955 1
2.6%
189586.505466234 1
2.6%
189678.284548834 2
5.3%
189768.794532397 2
5.3%
189827.526735208 1
2.6%
ValueCountFrequency (%)
191846.283660617 1
2.6%
191156.427263323 1
2.6%
190735.202947348 1
2.6%
190694.880295092 1
2.6%
190673.55942806 1
2.6%
190614.564573123 1
2.6%
190609.720795807 1
2.6%
190560.82783624 1
2.6%
190525.872894997 1
2.6%
190479.023027172 1
2.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)91.4%
Missing3
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean440959.29
Minimum438587.97
Maximum442569.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-05-11T02:21:55.322913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438587.97
5-th percentile439983.07
Q1440656.27
median441049.54
Q3441169.67
95-th percentile442503.67
Maximum442569.3
Range3981.3297
Interquartile range (IQR)513.40063

Descriptive statistics

Standard deviation763.23171
Coefficient of variation (CV)0.0017308439
Kurtosis3.4961315
Mean440959.29
Median Absolute Deviation (MAD)335.86857
Skewness-0.61398162
Sum15433575
Variance582522.65
MonotonicityNot monotonic
2024-05-11T02:21:55.804332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
441134.747749945 2
 
5.3%
441054.073460679 2
 
5.3%
440654.863022242 2
 
5.3%
441503.181731081 1
 
2.6%
441385.405235331 1
 
2.6%
442569.300676147 1
 
2.6%
440588.586890064 1
 
2.6%
442478.356256941 1
 
2.6%
440401.86132155 1
 
2.6%
440879.534068615 1
 
2.6%
Other values (22) 22
57.9%
(Missing) 3
 
7.9%
ValueCountFrequency (%)
438587.971010721 1
2.6%
439005.878692812 1
2.6%
440401.86132155 1
2.6%
440512.820199234 1
2.6%
440562.258137266 1
2.6%
440588.586890064 1
2.6%
440609.342128829 1
2.6%
440654.863022242 2
5.3%
440657.674206814 1
2.6%
440696.477654521 1
2.6%
ValueCountFrequency (%)
442569.300676147 1
2.6%
442562.722742062 1
2.6%
442478.356256941 1
2.6%
441728.27059771 1
2.6%
441503.181731081 1
2.6%
441385.405235331 1
2.6%
441290.29413211 1
2.6%
441231.02890367 1
2.6%
441187.464049907 1
2.6%
441151.874438984 1
2.6%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
용기.포장지제조업
35 
<NA>
 
3

Length

Max length9
Median length9
Mean length8.6052632
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용기.포장지제조업
2nd row용기.포장지제조업
3rd row용기.포장지제조업
4th row용기.포장지제조업
5th row용기.포장지제조업

Common Values

ValueCountFrequency (%)
용기.포장지제조업 35
92.1%
<NA> 3
 
7.9%

Length

2024-05-11T02:21:56.279325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:56.661152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기.포장지제조업 35
92.1%
na 3
 
7.9%

남성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

여성종사자수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

영업장주변구분명
Categorical

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
27 
기타
10 
주택가주변
 
1

Length

Max length5
Median length4
Mean length3.5
Min length2

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
71.1%
기타 10
 
26.3%
주택가주변 1
 
2.6%

Length

2024-05-11T02:21:57.194089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:57.605549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
71.1%
기타 10
 
26.3%
주택가주변 1
 
2.6%

등급구분명
Categorical

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
27 
자율
10 
기타
 
1

Length

Max length4
Median length4
Mean length3.4210526
Min length2

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
71.1%
자율 10
 
26.3%
기타 1
 
2.6%

Length

2024-05-11T02:21:57.992490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:58.657702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
71.1%
자율 10
 
26.3%
기타 1
 
2.6%

급수시설구분명
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
24 
상수도전용
14 

Length

Max length5
Median length4
Mean length4.3684211
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 24
63.2%
상수도전용 14
36.8%

Length

2024-05-11T02:21:59.090395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:21:59.462872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
63.2%
상수도전용 14
36.8%

총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

본사종업원수
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
22 
0
16 

Length

Max length4
Median length4
Mean length2.7368421
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 22
57.9%
0 16
42.1%

Length

2024-05-11T02:21:59.847221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:00.298723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
57.9%
0 16
42.1%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
22 
0
16 

Length

Max length4
Median length4
Mean length2.7368421
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 22
57.9%
0 16
42.1%

Length

2024-05-11T02:22:00.735327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:01.101362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
57.9%
0 16
42.1%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
22 
0
16 

Length

Max length4
Median length4
Mean length2.7368421
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 22
57.9%
0 16
42.1%

Length

2024-05-11T02:22:01.646354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:02.152740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
57.9%
0 16
42.1%

공장생산직종업원수
Categorical

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
21 
0
16 
2
 
1

Length

Max length4
Median length4
Mean length2.6578947
Min length1

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
55.3%
0 16
42.1%
2 1
 
2.6%

Length

2024-05-11T02:22:02.691182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:03.186367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
55.3%
0 16
42.1%
2 1
 
2.6%

건물소유구분명
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing34
Missing (%)89.5%
Memory size436.0 B
2024-05-11T02:22:03.555120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters8
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st row임대
2nd row임대
3rd row임대
4th row자가
ValueCountFrequency (%)
임대 3
75.0%
자가 1
 
25.0%
2024-05-11T02:22:04.521894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
임 3
37.5%
대 3
37.5%
자 1
 
12.5%
가 1
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
임 3
37.5%
대 3
37.5%
자 1
 
12.5%
가 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
임 3
37.5%
대 3
37.5%
자 1
 
12.5%
가 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
임 3
37.5%
대 3
37.5%
자 1
 
12.5%
가 1
 
12.5%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
36 
21000000
 
1
18000000
 
1

Length

Max length8
Median length4
Mean length4.2105263
Min length4

Unique

Unique2 ?
Unique (%)5.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
94.7%
21000000 1
 
2.6%
18000000 1
 
2.6%

Length

2024-05-11T02:22:05.009259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:05.493701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
94.7%
21000000 1
 
2.6%
18000000 1
 
2.6%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
36 
2400000
 
1
2000000
 
1

Length

Max length7
Median length4
Mean length4.1578947
Min length4

Unique

Unique2 ?
Unique (%)5.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
94.7%
2400000 1
 
2.6%
2000000 1
 
2.6%

Length

2024-05-11T02:22:05.966721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:06.309680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
94.7%
2400000 1
 
2.6%
2000000 1
 
2.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.9%
Missing3
Missing (%)7.9%
Memory size208.0 B
False
35 
(Missing)
 
3
ValueCountFrequency (%)
False 35
92.1%
(Missing) 3
 
7.9%
2024-05-11T02:22:06.577983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
0.0
34 
<NA>
 
3
186.09
 
1

Length

Max length6
Median length3
Mean length3.1578947
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 34
89.5%
<NA> 3
 
7.9%
186.09 1
 
2.6%

Length

2024-05-11T02:22:06.989911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:22:07.416523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 34
89.5%
na 3
 
7.9%
186.09 1
 
2.6%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031700003170000-118-1985-0028119851028<NA>3폐업2폐업20020328<NA><NA><NA>02 8558425139.02153813서울특별시 금천구 독산동 295-4<NA><NA>유림화학공업(주)2002-01-13 00:00:00I2018-08-31 23:59:59.0용기.포장지제조업190673.559428441049.536664용기.포장지제조업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131700003170000-118-1985-0028219850928<NA>3폐업2폐업20040504<NA><NA><NA><NA><NA>153803서울특별시 금천구 가산동 550-1<NA><NA>(주)원지산업2003-05-15 00:00:00I2018-08-31 23:59:59.0용기.포장지제조업<NA><NA>용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
231700003170000-118-1986-0028819860715<NA>3폐업2폐업20040504<NA><NA><NA>02 865147298.28153813서울특별시 금천구 독산동 299-13<NA><NA>창원화학1999-09-09 00:00:00I2018-08-31 23:59:59.0용기.포장지제조업190614.564573441068.718318용기.포장지제조업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331700003170000-118-1986-0028919861018<NA>3폐업2폐업20030127<NA><NA><NA>02 855955193.60153802서울특별시 금천구 가산동 345-19<NA><NA>(주)삼보인쇄지기공업사2002-06-24 00:00:00I2018-08-31 23:59:59.0용기.포장지제조업189678.284549441134.74775용기.포장지제조업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
431700003170000-118-1988-0028519881114<NA>3폐업2폐업20060629<NA><NA><NA>02 8044709.00153841서울특별시 금천구 시흥동 832-24<NA><NA>동성상사1999-09-09 00:00:00I2018-08-31 23:59:59.0용기.포장지제조업191846.283661439005.878693용기.포장지제조업<NA><NA>기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
531700003170000-118-1990-0028319900303<NA>3폐업2폐업20040212<NA><NA><NA>02 8538211442.68153803서울특별시 금천구 가산동 371-16<NA><NA>동산산업2002-01-13 00:00:00I2018-08-31 23:59:59.0용기.포장지제조업189497.040985441728.270598용기.포장지제조업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631700003170000-118-1992-0028719920616<NA>3폐업2폐업19980903<NA><NA><NA>02 0147.60153814서울특별시 금천구 독산동 333-25<NA><NA>경향상사2002-01-13 00:00:00I2018-08-31 23:59:59.0용기.포장지제조업<NA><NA>용기.포장지제조업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731700003170000-118-1995-0028019950822<NA>3폐업2폐업20050414<NA><NA><NA>02 8592225160.00153801서울특별시 금천구 가산동 238-50<NA><NA>(주)조양피엔씨1999-09-09 00:00:00I2018-08-31 23:59:59.0용기.포장지제조업189962.874825441151.874439용기.포장지제조업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
831700003170000-118-1995-0028619950110<NA>3폐업2폐업20010919<NA><NA><NA>02 8570012176.30153801서울특별시 금천구 가산동 236-8<NA><NA>덕성2002-11-30 00:00:00I2018-08-31 23:59:59.0용기.포장지제조업190374.446832441290.294132용기.포장지제조업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931700003170000-118-1997-0041019971021<NA>3폐업2폐업20050415<NA><NA><NA>02 8057709154.84153814서울특별시 금천구 독산동 333-11<NA><NA>한진산업1999-09-02 00:00:00I2018-08-31 23:59:59.0용기.포장지제조업190346.053952440705.616847용기.포장지제조업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
2831700003170000-118-2008-0000120080701<NA>1영업/정상1영업<NA><NA><NA><NA>02 8516414420.00153802서울특별시 금천구 가산동 345-9 SK트윈테크타워서울특별시 금천구 가산디지털1로 119, SK트윈테크타워 지하1층 101, 102호 (가산동)8589삼일포장2020-01-09 15:19:26U2020-01-11 02:40:00.0용기.포장지제조업189575.815288441503.181731용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
2931700003170000-118-2008-0000220081016<NA>3폐업2폐업20110317<NA><NA><NA>02 893353546.08153813서울특별시 금천구 독산동 330-16 [두산길 41] 지하1층<NA><NA>(주)삼화피앤티2008-11-08 12:23:29I2018-08-31 23:59:59.0용기.포장지제조업190479.023027440879.534069용기.포장지제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
3031700003170000-118-2009-0000120090226<NA>3폐업2폐업20120608<NA><NA><NA>02 8667131230.40153803서울특별시 금천구 가산동 715 고려테크온 113호,206호<NA><NA>유피지산업(주)2009-04-01 20:07:34I2018-08-31 23:59:59.0용기.포장지제조업190057.736483440401.861322용기.포장지제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
3131700003170000-118-2010-0000120100305<NA>1영업/정상1영업<NA><NA><NA><NA>02 807646482.60153814서울특별시 금천구 독산동 333-12서울특별시 금천구 벚꽃로18길 43 (독산동)8583대동리빙2019-01-28 16:55:37U2019-01-30 02:40:00.0용기.포장지제조업190319.367342440696.477655용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
3231700003170000-118-2014-0000120140116<NA>1영업/정상1영업<NA><NA><NA><NA>02 8510105132.00153813서울특별시 금천구 독산동 301-14 신관서울특별시 금천구 두산로9길 28 (독산동, 신관)8525죠이프린라이프2016-03-15 14:05:57I2018-08-31 23:59:59.0용기.포장지제조업190471.011036441054.073461용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
3331700003170000-118-2014-0000220140424<NA>1영업/정상1영업<NA><NA><NA><NA>02 807 8783333.77153803서울특별시 금천구 가산동 670-2서울특별시 금천구 가산디지털1로 19 (가산동, 대륭테크노타운 18차 1101,1102호)8594(주)이루팩2022-01-19 13:40:01U2022-01-21 02:40:00.0용기.포장지제조업189889.938753440609.342129용기.포장지제조업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N186.09<NA><NA><NA>
3431700003170000-118-2014-000032014-05-16<NA>1영업/정상1영업<NA><NA><NA><NA>02 852 74316317.00153-803서울특별시 금천구 가산동 567-13서울특별시 금천구 서부샛길 314 (가산동)8594오일기업(주)2024-04-26 14:07:35U2023-12-03 22:08:00.0용기.포장지제조업189768.794532440654.863022<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3531700003170000-118-2014-000042014-09-24<NA>1영업/정상1영업<NA><NA><NA><NA>02 863 2846345.00153-803서울특별시 금천구 가산동 567-13서울특별시 금천구 서부샛길 314 (가산동)8594(주)삼양패키징 구로공장2023-04-18 15:39:44U2022-12-03 22:00:00.0용기.포장지제조업189768.794532440654.863022<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3631700003170000-118-2018-0000120180327<NA>3폐업2폐업20220609<NA><NA><NA>02 851 5427119.61153813서울특별시 금천구 독산동 291-1 현대지식산업센터서울특별시 금천구 두산로 70, 현대지식산업센터 A동 705호 (독산동)8584(주)한양패키지2022-06-09 10:30:20U2021-12-05 23:01:00.0용기.포장지제조업190694.880295440764.426278<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3731700003170000-118-2020-0000120200727<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.00153803서울특별시 금천구 가산동 517-4 에이스 가산 포휴(지식산업센터)서울특별시 금천구 가산디지털1로 225, 에이스 가산 포휴(지식산업센터) 지하1층 119일부호 (가산동)8501(주)남도피앤피2021-01-08 13:34:28I2021-01-09 00:23:05.0용기.포장지제조업189202.181652442562.722742용기.포장지제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>