Overview

Dataset statistics

Number of variables17
Number of observations76
Missing cells75
Missing cells (%)5.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.4 KiB
Average record size in memory140.7 B

Variable types

Categorical6
Numeric3
DateTime4
Text4

Dataset

Description폐업업소현황(업종명 인허가번호 인허가일자 업소명 소재지(도로명) 소재지(지번) 영업장면적 소재지전화 영업자시작일 우편번호(도로명) 우편번호(지번) 소재지시작일 행정동명 폐업일자 폐업구분 폐업사유 업태명)(2016.8.10등록파일임)
Author인천광역시 강화군
URLhttps://www.data.go.kr/data/15047500/fileData.do

Alerts

업태명 is highly overall correlated with 업종명 and 2 other fieldsHigh correlation
업종명 is highly overall correlated with 폐업사유 and 1 other fieldsHigh correlation
인허가번호 is highly overall correlated with 우편번호(도로명)High correlation
우편번호(도로명) is highly overall correlated with 인허가번호 and 3 other fieldsHigh correlation
우편번호(지번) is highly overall correlated with 우편번호(도로명) and 2 other fieldsHigh correlation
행정동명 is highly overall correlated with 우편번호(도로명) and 1 other fieldsHigh correlation
폐업구분 is highly overall correlated with 우편번호(도로명) and 3 other fieldsHigh correlation
폐업사유 is highly overall correlated with 업종명 and 2 other fieldsHigh correlation
업종명 is highly imbalanced (63.1%)Imbalance
소재지(도로명) has 15 (19.7%) missing valuesMissing
소재지전화 has 44 (57.9%) missing valuesMissing
우편번호(도로명) has 16 (21.1%) missing valuesMissing
인허가번호 has unique valuesUnique
업소명 has unique valuesUnique
영업장면적 has 1 (1.3%) zerosZeros

Reproduction

Analysis started2023-12-11 23:24:37.775805
Analysis finished2023-12-11 23:24:40.120258
Duration2.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
일반음식점
67 
휴게음식점
8 
제과점영업
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 67
88.2%
휴게음식점 8
 
10.5%
제과점영업 1
 
1.3%

Length

2023-12-12T08:24:40.170791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:24:40.255446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 67
88.2%
휴게음식점 8
 
10.5%
제과점영업 1
 
1.3%

인허가번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0103895 × 1010
Minimum1.9840211 × 1010
Maximum2.0160211 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-12T08:24:40.355717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9840211 × 1010
5-th percentile1.9922711 × 1010
Q12.0087711 × 1010
median2.0140211 × 1010
Q32.0160211 × 1010
95-th percentile2.0160211 × 1010
Maximum2.0160211 × 1010
Range3.1999999 × 108
Interquartile range (IQR)72500018

Descriptive statistics

Standard deviation81450882
Coefficient of variation (CV)0.0040514975
Kurtosis2.4518085
Mean2.0103895 × 1010
Median Absolute Deviation (MAD)20000010
Skewness-1.7830127
Sum1.527896 × 1012
Variance6.6342462 × 1015
MonotonicityNot monotonic
2023-12-12T08:24:40.488859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19860211050 1
 
1.3%
20160211067 1
 
1.3%
20160211074 1
 
1.3%
20160211073 1
 
1.3%
20160211072 1
 
1.3%
20160211071 1
 
1.3%
20160211070 1
 
1.3%
20160211069 1
 
1.3%
20160211068 1
 
1.3%
20160211064 1
 
1.3%
Other values (66) 66
86.8%
ValueCountFrequency (%)
19840211098 1
1.3%
19860211048 1
1.3%
19860211050 1
1.3%
19900211037 1
1.3%
19930211030 1
1.3%
19940211061 1
1.3%
19950211049 1
1.3%
19970211116 1
1.3%
19980211026 1
1.3%
19990211137 1
1.3%
ValueCountFrequency (%)
20160211085 1
1.3%
20160211084 1
1.3%
20160211083 1
1.3%
20160211082 1
1.3%
20160211080 1
1.3%
20160211079 1
1.3%
20160211078 1
1.3%
20160211077 1
1.3%
20160211076 1
1.3%
20160211075 1
1.3%

인허가일자
Date

Distinct53
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum1984-06-02 00:00:00
Maximum2016-04-14 00:00:00
2023-12-12T08:24:40.636884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:40.767357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-12T08:24:40.929058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length8.8289474
Min length2

Characters and Unicode

Total characters671
Distinct characters209
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

Unique76 ?
Unique (%)100.0%

Sample

1st row야생촌
2nd row뜨락식당
3rd row은행나무집
4th row청수정식당
5th row소라3호횟집
ValueCountFrequency (%)
진달래축제 2
 
2.3%
야생촌 1
 
1.2%
진달래축제부근1리(이연임 1
 
1.2%
진달래축제(고려산기도원 1
 
1.2%
진달래축제(양도면새마을부녀회 1
 
1.2%
진달래축제부근1리(김영희 1
 
1.2%
진달래축제(불은부녀회 1
 
1.2%
진달래축제부근1리(안상례 1
 
1.2%
진달래축제(하도2리노인회 1
 
1.2%
진달래축제부근1리(송영숙 1
 
1.2%
Other values (75) 75
87.2%
2023-12-12T08:24:41.205364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 30
 
4.5%
축 28
 
4.2%
래 28
 
4.2%
달 28
 
4.2%
진 28
 
4.2%
( 28
 
4.2%
) 28
 
4.2%
리 22
 
3.3%
부 20
 
3.0%
근 13
 
1.9%
Other values (199) 418
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 569
84.8%
Open Punctuation 28
 
4.2%
Close Punctuation 28
 
4.2%
Decimal Number 20
 
3.0%
Uppercase Letter 12
 
1.8%
Space Separator 10
 
1.5%
Lowercase Letter 3
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 30
 
5.3%
축 28
 
4.9%
래 28
 
4.9%
달 28
 
4.9%
진 28
 
4.9%
리 22
 
3.9%
부 20
 
3.5%
근 13
 
2.3%
회 11
 
1.9%
식 9
 
1.6%
Other values (180) 352
61.9%
Uppercase Letter
ValueCountFrequency (%)
E 2
16.7%
G 2
16.7%
A 2
16.7%
C 1
8.3%
Z 1
8.3%
R 1
8.3%
W 1
8.3%
H 1
8.3%
N 1
8.3%
Decimal Number
ValueCountFrequency (%)
2 10
50.0%
1 9
45.0%
3 1
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
33.3%
f 1
33.3%
e 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 569
84.8%
Common 87
 
13.0%
Latin 15
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 30
 
5.3%
축 28
 
4.9%
래 28
 
4.9%
달 28
 
4.9%
진 28
 
4.9%
리 22
 
3.9%
부 20
 
3.5%
근 13
 
2.3%
회 11
 
1.9%
식 9
 
1.6%
Other values (180) 352
61.9%
Latin
ValueCountFrequency (%)
E 2
13.3%
G 2
13.3%
A 2
13.3%
C 1
6.7%
a 1
6.7%
f 1
6.7%
e 1
6.7%
Z 1
6.7%
R 1
6.7%
W 1
6.7%
Other values (2) 2
13.3%
Common
ValueCountFrequency (%)
( 28
32.2%
) 28
32.2%
2 10
 
11.5%
10
 
11.5%
1 9
 
10.3%
. 1
 
1.1%
3 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 569
84.8%
ASCII 102
 
15.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 30
 
5.3%
축 28
 
4.9%
래 28
 
4.9%
달 28
 
4.9%
진 28
 
4.9%
리 22
 
3.9%
부 20
 
3.5%
근 13
 
2.3%
회 11
 
1.9%
식 9
 
1.6%
Other values (180) 352
61.9%
ASCII
ValueCountFrequency (%)
( 28
27.5%
) 28
27.5%
2 10
 
9.8%
10
 
9.8%
1 9
 
8.8%
E 2
 
2.0%
G 2
 
2.0%
A 2
 
2.0%
. 1
 
1.0%
C 1
 
1.0%
Other values (9) 9
 
8.8%

소재지(도로명)
Text

MISSING 

Distinct56
Distinct (%)91.8%
Missing15
Missing (%)19.7%
Memory size740.0 B
2023-12-12T08:24:41.416578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length27.016393
Min length19

Characters and Unicode

Total characters1648
Distinct characters80
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)90.2%

Sample

1st row인천광역시 강화군 강화읍 강화대로 378-8
2nd row인천광역시 강화군 강화읍 북문4길10번길 8-5
3rd row인천광역시 강화군 길상면 온수길38번길 6
4th row인천광역시 강화군 내가면 해안서로 907
5th row인천광역시 강화군 강화읍 강화대로 200
ValueCountFrequency (%)
인천광역시 61
17.7%
강화군 61
17.7%
강화읍 23
 
6.7%
하점면 19
 
5.5%
1층 17
 
4.9%
강화대로 15
 
4.4%
해안남로 8
 
2.3%
길상면 7
 
2.0%
994-19 6
 
1.7%
고인돌광장 6
 
1.7%
Other values (94) 121
35.2%
2023-12-12T08:24:41.735769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
283
17.2%
화 114
 
6.9%
강 108
 
6.6%
1 69
 
4.2%
인 67
 
4.1%
광 67
 
4.1%
시 62
 
3.8%
역 61
 
3.7%
군 61
 
3.7%
천 61
 
3.7%
Other values (70) 695
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1023
62.1%
Space Separator 283
 
17.2%
Decimal Number 264
 
16.0%
Dash Punctuation 23
 
1.4%
Open Punctuation 19
 
1.2%
Close Punctuation 19
 
1.2%
Other Punctuation 17
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 114
 
11.1%
강 108
 
10.6%
인 67
 
6.5%
광 67
 
6.5%
시 62
 
6.1%
역 61
 
6.0%
군 61
 
6.0%
천 61
 
6.0%
로 52
 
5.1%
면 38
 
3.7%
Other values (55) 332
32.5%
Decimal Number
ValueCountFrequency (%)
1 69
26.1%
9 41
15.5%
2 25
 
9.5%
3 24
 
9.1%
4 24
 
9.1%
8 22
 
8.3%
7 17
 
6.4%
0 15
 
5.7%
5 14
 
5.3%
6 13
 
4.9%
Space Separator
ValueCountFrequency (%)
283
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1023
62.1%
Common 625
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 114
 
11.1%
강 108
 
10.6%
인 67
 
6.5%
광 67
 
6.5%
시 62
 
6.1%
역 61
 
6.0%
군 61
 
6.0%
천 61
 
6.0%
로 52
 
5.1%
면 38
 
3.7%
Other values (55) 332
32.5%
Common
ValueCountFrequency (%)
283
45.3%
1 69
 
11.0%
9 41
 
6.6%
2 25
 
4.0%
3 24
 
3.8%
4 24
 
3.8%
- 23
 
3.7%
8 22
 
3.5%
( 19
 
3.0%
) 19
 
3.0%
Other values (5) 76
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1023
62.1%
ASCII 625
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
283
45.3%
1 69
 
11.0%
9 41
 
6.6%
2 25
 
4.0%
3 24
 
3.8%
4 24
 
3.8%
- 23
 
3.7%
8 22
 
3.5%
( 19
 
3.0%
) 19
 
3.0%
Other values (5) 76
 
12.2%
Hangul
ValueCountFrequency (%)
화 114
 
11.1%
강 108
 
10.6%
인 67
 
6.5%
광 67
 
6.5%
시 62
 
6.1%
역 61
 
6.0%
군 61
 
6.0%
천 61
 
6.0%
로 52
 
5.1%
면 38
 
3.7%
Other values (55) 332
32.5%

소재지(지번)
Text

Distinct70
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-12T08:24:42.008008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length26.394737
Min length4

Characters and Unicode

Total characters2006
Distinct characters86
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)90.8%

Sample

1st row인천광역시 강화군 강화읍 갑곳리 931번지
2nd row인천광역시 강화군 강화읍 관청리 119번지 5호
3rd row인천광역시 강화군 강화읍 관청리 737번지 2호
4th row인천광역시 강화군 길상면 온수리 513번지 4호
5th row인천광역시 강화군 내가면 외포리 582번지 21호
ValueCountFrequency (%)
인천광역시 69
 
16.3%
강화군 69
 
16.3%
강화읍 28
 
6.6%
하점면 18
 
4.3%
부근리 17
 
4.0%
1호 15
 
3.5%
2호 10
 
2.4%
갑곳리 9
 
2.1%
길상면 8
 
1.9%
화도면 6
 
1.4%
Other values (123) 174
41.1%
2023-12-12T08:24:42.429795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
502
25.0%
화 106
 
5.3%
강 97
 
4.8%
지 75
 
3.7%
1 72
 
3.6%
시 71
 
3.5%
인 71
 
3.5%
광 71
 
3.5%
천 70
 
3.5%
군 69
 
3.4%
Other values (76) 802
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1204
60.0%
Space Separator 502
25.0%
Decimal Number 295
 
14.7%
Other Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 106
 
8.8%
강 97
 
8.1%
지 75
 
6.2%
시 71
 
5.9%
인 71
 
5.9%
광 71
 
5.9%
천 70
 
5.8%
군 69
 
5.7%
리 69
 
5.7%
번 69
 
5.7%
Other values (61) 436
36.2%
Decimal Number
ValueCountFrequency (%)
1 72
24.4%
3 40
13.6%
2 36
12.2%
4 28
 
9.5%
5 27
 
9.2%
9 26
 
8.8%
6 21
 
7.1%
8 20
 
6.8%
0 15
 
5.1%
7 10
 
3.4%
Space Separator
ValueCountFrequency (%)
502
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1204
60.0%
Common 802
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 106
 
8.8%
강 97
 
8.1%
지 75
 
6.2%
시 71
 
5.9%
인 71
 
5.9%
광 71
 
5.9%
천 70
 
5.8%
군 69
 
5.7%
리 69
 
5.7%
번 69
 
5.7%
Other values (61) 436
36.2%
Common
ValueCountFrequency (%)
502
62.6%
1 72
 
9.0%
3 40
 
5.0%
2 36
 
4.5%
4 28
 
3.5%
5 27
 
3.4%
9 26
 
3.2%
6 21
 
2.6%
8 20
 
2.5%
0 15
 
1.9%
Other values (5) 15
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1204
60.0%
ASCII 802
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
502
62.6%
1 72
 
9.0%
3 40
 
5.0%
2 36
 
4.5%
4 28
 
3.5%
5 27
 
3.4%
9 26
 
3.2%
6 21
 
2.6%
8 20
 
2.5%
0 15
 
1.9%
Other values (5) 15
 
1.9%
Hangul
ValueCountFrequency (%)
화 106
 
8.8%
강 97
 
8.1%
지 75
 
6.2%
시 71
 
5.9%
인 71
 
5.9%
광 71
 
5.9%
천 70
 
5.8%
군 69
 
5.7%
리 69
 
5.7%
번 69
 
5.7%
Other values (61) 436
36.2%

영업장면적
Real number (ℝ)

ZEROS 

Distinct64
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.804079
Minimum0
Maximum513.73
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-12T08:24:42.589645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17.84
Q132.72
median50.8
Q3100
95-th percentile220.53
Maximum513.73
Range513.73
Interquartile range (IQR)67.28

Descriptive statistics

Standard deviation85.774188
Coefficient of variation (CV)1.0358691
Kurtosis9.7859566
Mean82.804079
Median Absolute Deviation (MAD)27.35
Skewness2.7885897
Sum6293.11
Variance7357.2114
MonotonicityNot monotonic
2023-12-12T08:24:42.726579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50.0 6
 
7.9%
100.0 5
 
6.6%
25.0 2
 
2.6%
18.0 2
 
2.6%
20.0 2
 
2.6%
70.91 1
 
1.3%
123.0 1
 
1.3%
55.9 1
 
1.3%
36.96 1
 
1.3%
61.0 1
 
1.3%
Other values (54) 54
71.1%
ValueCountFrequency (%)
0.0 1
1.3%
10.0 1
1.3%
12.73 1
1.3%
17.36 1
1.3%
18.0 2
2.6%
18.28 1
1.3%
18.9 1
1.3%
20.0 2
2.6%
22.04 1
1.3%
24.86 1
1.3%
ValueCountFrequency (%)
513.73 1
1.3%
382.4 1
1.3%
310.98 1
1.3%
300.0 1
1.3%
194.04 1
1.3%
190.82 1
1.3%
189.92 1
1.3%
165.3 1
1.3%
150.0 1
1.3%
148.2 1
1.3%

소재지전화
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing44
Missing (%)57.9%
Memory size740.0 B
2023-12-12T08:24:42.913940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters384
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

Unique32 ?
Unique (%)100.0%

Sample

1st row032-932-2612
2nd row032-934-3661
3rd row032-937-7199
4th row032-932-5839
5th row032-934-1121
ValueCountFrequency (%)
032-937-9852 1
 
3.1%
032-937-7199 1
 
3.1%
032-933-0588 1
 
3.1%
032-934-9886 1
 
3.1%
032-933-4844 1
 
3.1%
032-933-0666 1
 
3.1%
032-937-8564 1
 
3.1%
032-934-1033 1
 
3.1%
032-934-9500 1
 
3.1%
032-933-7882 1
 
3.1%
Other values (22) 22
68.8%
2023-12-12T08:24:43.214847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 82
21.4%
- 64
16.7%
2 52
13.5%
0 46
12.0%
9 44
11.5%
8 21
 
5.5%
4 21
 
5.5%
7 16
 
4.2%
6 15
 
3.9%
5 13
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 320
83.3%
Dash Punctuation 64
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 82
25.6%
2 52
16.2%
0 46
14.4%
9 44
13.8%
8 21
 
6.6%
4 21
 
6.6%
7 16
 
5.0%
6 15
 
4.7%
5 13
 
4.1%
1 10
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 82
21.4%
- 64
16.7%
2 52
13.5%
0 46
12.0%
9 44
11.5%
8 21
 
5.5%
4 21
 
5.5%
7 16
 
4.2%
6 15
 
3.9%
5 13
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 82
21.4%
- 64
16.7%
2 52
13.5%
0 46
12.0%
9 44
11.5%
8 21
 
5.5%
4 21
 
5.5%
7 16
 
4.2%
6 15
 
3.9%
5 13
 
3.4%

영업자시작일
Date

Distinct53
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum1984-06-02 00:00:00
Maximum2016-04-14 00:00:00
2023-12-12T08:24:43.584321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:43.754378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

우편번호(도로명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)43.3%
Missing16
Missing (%)21.1%
Infinite0
Infinite (%)0.0%
Mean23032.1
Minimum23014
Maximum23062
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-12T08:24:43.857243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23014
5-th percentile23014
Q123014
median23031
Q323043
95-th percentile23059.15
Maximum23062
Range48
Interquartile range (IQR)29

Descriptive statistics

Standard deviation15.783171
Coefficient of variation (CV)0.00068526841
Kurtosis-1.0509667
Mean23032.1
Median Absolute Deviation (MAD)17
Skewness0.38929289
Sum1381926
Variance249.10847
MonotonicityNot monotonic
2023-12-12T08:24:43.953748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
23014 17
22.4%
23037 4
 
5.3%
23062 3
 
3.9%
23027 3
 
3.9%
23052 3
 
3.9%
23024 2
 
2.6%
23031 2
 
2.6%
23059 2
 
2.6%
23033 2
 
2.6%
23036 2
 
2.6%
Other values (16) 20
26.3%
(Missing) 16
21.1%
ValueCountFrequency (%)
23014 17
22.4%
23015 1
 
1.3%
23019 1
 
1.3%
23024 2
 
2.6%
23025 1
 
1.3%
23026 2
 
2.6%
23027 3
 
3.9%
23028 1
 
1.3%
23029 1
 
1.3%
23031 2
 
2.6%
ValueCountFrequency (%)
23062 3
3.9%
23059 2
2.6%
23057 1
 
1.3%
23054 1
 
1.3%
23052 3
3.9%
23051 2
2.6%
23050 1
 
1.3%
23048 1
 
1.3%
23046 1
 
1.3%
23042 2
2.6%

우편번호(지번)
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)32.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
417-871
12 
<NA>
7 
417-843
5 
417-872
5 
417-862
5 
Other values (20)
42 

Length

Max length7
Median length7
Mean length6.7236842
Min length4

Unique

Unique10 ?
Unique (%)13.2%

Sample

1st row417-942
2nd row417-802
3rd row417-803
4th row417-841
5th row417-894

Common Values

ValueCountFrequency (%)
417-871 12
15.8%
<NA> 7
 
9.2%
417-843 5
 
6.6%
417-872 5
 
6.6%
417-862 5
 
6.6%
417-942 4
 
5.3%
417-805 4
 
5.3%
417-807 4
 
5.3%
417-803 4
 
5.3%
417-941 4
 
5.3%
Other values (15) 22
28.9%

Length

2023-12-12T08:24:44.064339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
417-871 12
15.8%
na 7
 
9.2%
417-843 5
 
6.6%
417-872 5
 
6.6%
417-862 5
 
6.6%
417-942 4
 
5.3%
417-805 4
 
5.3%
417-807 4
 
5.3%
417-803 4
 
5.3%
417-941 4
 
5.3%
Other values (15) 22
28.9%

소재지시작일
Date

Distinct53
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum1986-10-16 00:00:00
Maximum2016-04-14 00:00:00
2023-12-12T08:24:44.189025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:44.297333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

행정동명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size740.0 B
강화읍
28 
하점면
18 
길상면
8 
<NA>
7 
화도면
6 
Other values (5)
9 

Length

Max length4
Median length3
Mean length3.0921053
Min length3

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st row강화읍
2nd row강화읍
3rd row강화읍
4th row길상면
5th row내가면

Common Values

ValueCountFrequency (%)
강화읍 28
36.8%
하점면 18
23.7%
길상면 8
 
10.5%
<NA> 7
 
9.2%
화도면 6
 
7.9%
선원면 3
 
3.9%
내가면 2
 
2.6%
양도면 2
 
2.6%
불은면 1
 
1.3%
송해면 1
 
1.3%

Length

2023-12-12T08:24:44.400343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:24:44.523342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강화읍 28
36.8%
하점면 18
23.7%
길상면 8
 
10.5%
na 7
 
9.2%
화도면 6
 
7.9%
선원면 3
 
3.9%
내가면 2
 
2.6%
양도면 2
 
2.6%
불은면 1
 
1.3%
송해면 1
 
1.3%

폐업일자
Date

Distinct40
Distinct (%)52.6%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum2016-01-13 00:00:00
Maximum2016-07-28 00:00:00
2023-12-12T08:24:44.658807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:44.792661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

폐업구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
자진폐업
45 
기타
28 
행정처분
 
2
전출
 
1

Length

Max length4
Median length4
Mean length3.2368421
Min length2

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
자진폐업 45
59.2%
기타 28
36.8%
행정처분 2
 
2.6%
전출 1
 
1.3%

Length

2023-12-12T08:24:44.901298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:24:44.987135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자진폐업 45
59.2%
기타 28
36.8%
행정처분 2
 
2.6%
전출 1
 
1.3%

폐업사유
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size740.0 B
조건부기간 완료에 따른 폐업처리
28 
개인사정
26 
영업부진
3 
건물철거
 
2
사업부진
 
2
Other values (13)
15 

Length

Max length29
Median length4
Mean length9.5131579
Min length3

Unique

Unique11 ?
Unique (%)14.5%

Sample

1st row건물철거
2nd row개인사정
3rd row개인사정
4th row개인사정
5th row건물철거

Common Values

ValueCountFrequency (%)
조건부기간 완료에 따른 폐업처리 28
36.8%
개인사정 26
34.2%
영업부진 3
 
3.9%
건물철거 2
 
2.6%
사업부진 2
 
2.6%
행정처분 2
 
2.6%
영업불황 2
 
2.6%
장소이전 1
 
1.3%
자진폐업 1
 
1.3%
업종변경 1
 
1.3%
Other values (8) 8
 
10.5%

Length

2023-12-12T08:24:45.074701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조건부기간 28
16.3%
따른 28
16.3%
폐업처리 28
16.3%
완료에 28
16.3%
개인사정 26
15.1%
영업부진 3
 
1.7%
행정처분 2
 
1.2%
영업불황 2
 
1.2%
인한 2
 
1.2%
사업부진 2
 
1.2%
Other values (22) 23
13.4%

업태명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size740.0 B
한식
45 
일식
5 
기타
 
4
경양식
 
3
까페
 
3
Other values (11)
16 

Length

Max length8
Median length2
Mean length2.5394737
Min length2

Unique

Unique6 ?
Unique (%)7.9%

Sample

1st row탕류(보신용)
2nd row한식
3rd row한식
4th row한식
5th row일식

Common Values

ValueCountFrequency (%)
한식 45
59.2%
일식 5
 
6.6%
기타 4
 
5.3%
경양식 3
 
3.9%
까페 3
 
3.9%
분식 2
 
2.6%
통닭(치킨) 2
 
2.6%
다방 2
 
2.6%
패스트푸드 2
 
2.6%
커피숍 2
 
2.6%
Other values (6) 6
 
7.9%

Length

2023-12-12T08:24:45.168810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 45
58.4%
일식 5
 
6.5%
기타 5
 
6.5%
경양식 3
 
3.9%
까페 3
 
3.9%
분식 2
 
2.6%
통닭(치킨 2
 
2.6%
다방 2
 
2.6%
패스트푸드 2
 
2.6%
커피숍 2
 
2.6%
Other values (6) 6
 
7.8%

Interactions

2023-12-12T08:24:39.424791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:38.841313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:39.077557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:39.530574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:38.917839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:39.197671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:39.617069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:38.993449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:24:39.312397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:24:45.247261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명인허가번호인허가일자업소명소재지(도로명)소재지(지번)영업장면적소재지전화영업자시작일우편번호(도로명)우편번호(지번)소재지시작일행정동명폐업일자폐업구분폐업사유업태명
업종명1.0000.0001.0001.0001.0000.8170.0001.0001.0000.0000.0001.0000.0000.7970.0890.9831.000
인허가번호0.0001.0001.0001.0001.0001.0000.2961.0001.0000.0000.6411.0000.2590.9650.4870.6180.546
인허가일자1.0001.0001.0001.0000.9970.9970.8931.0001.0001.0000.9781.0000.9101.0001.0001.0000.996
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지(도로명)1.0001.0000.9971.0001.0000.9961.0001.0000.9971.0001.0000.9971.0001.0001.0001.0001.000
소재지(지번)0.8171.0000.9971.0000.9961.0000.9951.0000.9971.0001.0000.9971.0000.9970.9860.9990.986
영업장면적0.0000.2960.8931.0001.0000.9951.0001.0000.8930.3920.0000.8930.3170.8630.3530.0000.000
소재지전화1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
영업자시작일1.0001.0001.0001.0000.9970.9970.8931.0001.0001.0000.9781.0000.9101.0001.0001.0000.996
우편번호(도로명)0.0000.0001.0001.0001.0001.0000.3921.0001.0001.0001.0001.0000.9700.0000.8500.5720.563
우편번호(지번)0.0000.6410.9781.0001.0001.0000.0001.0000.9781.0001.0000.9781.0000.9510.9920.8710.633
소재지시작일1.0001.0001.0001.0000.9970.9970.8931.0001.0001.0000.9781.0000.9101.0001.0001.0000.996
행정동명0.0000.2590.9101.0001.0001.0000.3171.0000.9100.9701.0000.9101.0000.8070.6690.7390.000
폐업일자0.7970.9651.0001.0001.0000.9970.8631.0001.0000.0000.9511.0000.8071.0000.9170.9650.972
폐업구분0.0890.4871.0001.0001.0000.9860.3531.0001.0000.8500.9921.0000.6690.9171.0001.0000.853
폐업사유0.9830.6181.0001.0001.0000.9990.0001.0001.0000.5720.8711.0000.7390.9651.0001.0000.888
업태명1.0000.5460.9961.0001.0000.9860.0001.0000.9960.5630.6330.9960.0000.9720.8530.8881.000
2023-12-12T08:24:45.376925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐업구분폐업사유우편번호(지번)행정동명업태명업종명
폐업구분1.0000.8980.7390.4790.5150.080
폐업사유0.8981.0000.4180.3080.5260.760
우편번호(지번)0.7390.4181.0000.8660.1980.000
행정동명0.4790.3080.8661.0000.0000.000
업태명0.5150.5260.1980.0001.0000.907
업종명0.0800.7600.0000.0000.9071.000
2023-12-12T08:24:45.462669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호영업장면적우편번호(도로명)업종명우편번호(지번)행정동명폐업구분폐업사유업태명
인허가번호1.000-0.134-0.6560.0000.2480.1100.3030.2050.237
영업장면적-0.1341.0000.4690.0000.0000.1540.1550.0000.000
우편번호(도로명)-0.6560.4691.0000.1770.8440.9020.5050.3040.228
업종명0.0000.0000.1771.0000.0000.0000.0800.7600.907
우편번호(지번)0.2480.0000.8440.0001.0000.8660.7390.4180.198
행정동명0.1100.1540.9020.0000.8661.0000.4790.3080.000
폐업구분0.3030.1550.5050.0800.7390.4791.0000.8980.515
폐업사유0.2050.0000.3040.7600.4180.3080.8981.0000.526
업태명0.2370.0000.2280.9070.1980.0000.5150.5261.000

Missing values

2023-12-12T08:24:39.741964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:24:39.949495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T08:24:40.061877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업종명인허가번호인허가일자업소명소재지(도로명)소재지(지번)영업장면적소재지전화영업자시작일우편번호(도로명)우편번호(지번)소재지시작일행정동명폐업일자폐업구분폐업사유업태명
0일반음식점198602110501986-10-27야생촌<NA>인천광역시 강화군 강화읍 갑곳리 931번지165.3032-932-26122007-05-03<NA>417-9421986-10-27강화읍2016-03-03자진폐업건물철거탕류(보신용)
1일반음식점199002110371990-09-21뜨락식당인천광역시 강화군 강화읍 강화대로 378-8인천광역시 강화군 강화읍 관청리 119번지 5호29.7032-934-36612006-04-2123036417-8021990-09-21강화읍2016-02-24자진폐업개인사정한식
2일반음식점199302110301993-06-22은행나무집인천광역시 강화군 강화읍 북문4길10번길 8-5인천광역시 강화군 강화읍 관청리 737번지 2호27.65<NA>1993-06-2223029417-8031993-06-22강화읍2016-03-18자진폐업개인사정한식
3일반음식점199402110611994-09-07청수정식당인천광역시 강화군 길상면 온수길38번길 6인천광역시 강화군 길상면 온수리 513번지 4호66.5032-937-71992010-10-0823050417-8411994-09-07길상면2016-07-21자진폐업개인사정한식
4일반음식점199502110491995-08-04소라3호횟집인천광역시 강화군 내가면 해안서로 907인천광역시 강화군 내가면 외포리 582번지 21호32.48032-932-58392006-07-1123054417-8941995-08-04내가면2016-04-07자진폐업건물철거일식
5일반음식점199702111161997-07-16분오리저수식당<NA>인천광역시 강화군 화도면 사기리 484번지 1호0.0<NA>1997-07-16<NA>417-8621997-07-16화도면2016-03-25자진폐업개인사정한식
6일반음식점199802110261998-03-28황경도아바이왕순대전문점인천광역시 강화군 강화읍 강화대로 200인천광역시 강화군 강화읍 용정리 646번지 2호43.48<NA>1998-03-2823026417-8081998-03-28강화읍2016-04-04자진폐업영업불황한식
7일반음식점199902111371999-11-06천수면인천광역시 강화군 강화읍 대월로 8인천광역시 강화군 강화읍 갑곳리 198번지66.0032-934-11212015-02-0323025417-9412012-03-21강화읍2016-03-18자진폐업개인사정분식
8일반음식점200002111212000-12-16파도회집인천광역시 강화군 화도면 해안남로 1486-1인천광역시 강화군 화도면 동막리 12번지 2호189.92032-937-89522006-06-2023062417-8622000-12-16화도면2016-03-22자진폐업개인사정일식
9일반음식점200502110342005-04-08섬마을<NA>인천광역시 강화군 불은면 오두리 89-11번지115.14032-937-52512012-03-08<NA>417-8322005-04-08불은면2016-03-14자진폐업영업불황한식
업종명인허가번호인허가일자업소명소재지(도로명)소재지(지번)영업장면적소재지전화영업자시작일우편번호(도로명)우편번호(지번)소재지시작일행정동명폐업일자폐업구분폐업사유업태명
66일반음식점201602110852016-04-14진달래축제(하점면주민자치위원회)<NA>인천광역시 강화군 하점면 부근리 산 153번지300.0<NA>2016-04-14<NA>417-8712016-04-14하점면2016-04-26기타조건부기간 완료에 따른 폐업처리한식
67휴게음식점198402110981984-06-02은성다방인천광역시 강화군 불은면 강화동로 550-164.96032-937-46201984-06-0223046<NA>2012-07-19<NA>2016-02-05자진폐업개인사정다방
68휴게음식점198602110481986-10-16은다방인천광역시 강화군 강화읍 강화대로 437인천광역시 강화군 강화읍 신문리 241번지 15호50.6032-934-23682008-04-1823033417-8071986-10-16강화읍2016-03-21자진폐업불경기다방
69휴게음식점200902110962009-08-14수 치킨 피자인천광역시 강화군 화도면 해안남로1502번길 11인천광역시 강화군 화도면 동막리 61번지 19호44.55032-324-59502013-07-1023062417-8622009-08-14화도면2016-02-17자진폐업개인사정패스트푸드
70휴게음식점201202110792012-07-09건평휴게소<NA>인천광역시 강화군 양도면 건평리 751번지 1호12.73<NA>2012-07-09<NA>417-8512012-07-09양도면2016-07-28자진폐업업종변경패스트푸드
71휴게음식점201302110642013-06-10로컬푸드카페 어서오시겨인천광역시 강화군 강화읍 북문길 23인천광역시 강화군 강화읍 관청리 616번지 1호17.36032-932-34482013-06-1023032417-8032013-06-10강화읍2016-02-22자진폐업자진폐업기타 휴게음식점
72휴게음식점201402110622014-04-29Cafe EZER(카페에젤)인천광역시 강화군 강화읍 갑룡길73번길 2, 지하층인천광역시 강화군 강화읍 갑곳리 77번지 11호36.3032-934-44322014-04-2923024417-9412014-04-29강화읍2016-02-11자진폐업사업부진커피숍
73휴게음식점201502110572015-04-07빙고인천광역시 강화군 강화읍 강화대로 413 (2층)인천광역시 강화군 강화읍 신문리 133번지76.03032-933-22002015-08-2623035417-8072015-04-07강화읍2016-04-29자진폐업영업부진커피숍
74휴게음식점201502111062015-05-22야생초만두.찐빵인천광역시 강화군 강화읍 중앙로 27 (1층)인천광역시 강화군 강화읍 남산리 39번지 1호40.92<NA>2015-05-2223037417-8052015-05-22강화읍2016-03-24자진폐업영업부진일반조리판매
75제과점영업201302110932013-07-02베이킹 스토리인천광역시 강화군 강화읍 갑룡길 99인천광역시 강화군 강화읍 갑곳리 24번지 2호32.8<NA>2013-07-0223024417-9412013-07-02강화읍2016-02-12자진폐업매출부진제과점영업