Overview

Dataset statistics

Number of variables15
Number of observations30
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory128.4 B

Variable types

Categorical3
Numeric4
Text8

Dataset

Description샘플 데이터
Author경기신용보증재단
URLhttps://bigdata-region.kr/#/dataset/a625aba0-4728-4594-bba9-1824e7dc5a49

Alerts

기준년월 has constant value ""Constant
시도명 has constant value ""Constant
주사업장우편번호 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 주사업장우편번호High correlation
경도 has 1 (3.3%) missing valuesMissing
상가업소번호 has unique valuesUnique
행정동명 has unique valuesUnique
업소명 has unique valuesUnique
주사업장우편번호 has unique valuesUnique
주사업장우편번호주소 has unique valuesUnique
위도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:48:08.086043
Analysis finished2023-12-10 13:48:12.441439
Duration4.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-10
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-10
2nd row2021-10
3rd row2021-10
4th row2021-10
5th row2021-10

Common Values

ValueCountFrequency (%)
2021-10 30
100.0%

Length

2023-12-10T22:48:12.672381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:48:12.846432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-10 30
100.0%

상가업소번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10149908
Minimum9842951
Maximum10316995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:48:13.125771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9842951
5-th percentile9934792.1
Q110101322
median10145750
Q310234440
95-th percentile10292768
Maximum10316995
Range474044
Interquartile range (IQR)133118.25

Descriptive statistics

Standard deviation113110.48
Coefficient of variation (CV)0.011143991
Kurtosis1.1629769
Mean10149908
Median Absolute Deviation (MAD)76986
Skewness-0.96520366
Sum3.0449723 × 108
Variance1.2793981 × 1010
MonotonicityNot monotonic
2023-12-10T22:48:13.491574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
10004196 1
 
3.3%
10164498 1
 
3.3%
10316995 1
 
3.3%
10302510 1
 
3.3%
10280862 1
 
3.3%
10268480 1
 
3.3%
10255116 1
 
3.3%
10254781 1
 
3.3%
10248071 1
 
3.3%
10237157 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
9842951 1
3.3%
9878007 1
3.3%
10004196 1
3.3%
10046442 1
3.3%
10061122 1
3.3%
10066035 1
3.3%
10076638 1
3.3%
10099120 1
3.3%
10107926 1
3.3%
10109389 1
3.3%
ValueCountFrequency (%)
10316995 1
3.3%
10302510 1
3.3%
10280862 1
3.3%
10268480 1
3.3%
10255116 1
3.3%
10254781 1
3.3%
10248071 1
3.3%
10237157 1
3.3%
10226288 1
3.3%
10220007 1
3.3%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 30
100.0%

Length

2023-12-10T22:48:13.863740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:48:14.049976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:48:14.392982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length4.1
Min length3

Characters and Unicode

Total characters123
Distinct characters33
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)33.3%

Sample

1st row안양시 동안구
2nd row용인시
3rd row용인시 수지구
4th row의왕시
5th row가평군
ValueCountFrequency (%)
용인시 4
 
10.5%
분당구 2
 
5.3%
김포시 2
 
5.3%
기흥구 2
 
5.3%
하남시 2
 
5.3%
화성시 2
 
5.3%
시흥시 2
 
5.3%
이천시 2
 
5.3%
성남시 2
 
5.3%
단원구 2
 
5.3%
Other values (13) 16
42.1%
2023-12-10T22:48:15.157413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 31
25.2%
8
 
6.5%
구 8
 
6.5%
남 5
 
4.1%
포 5
 
4.1%
성 5
 
4.1%
안 5
 
4.1%
천 5
 
4.1%
인 4
 
3.3%
용 4
 
3.3%
Other values (23) 43
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 115
93.5%
Space Separator 8
 
6.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 31
27.0%
구 8
 
7.0%
남 5
 
4.3%
포 5
 
4.3%
성 5
 
4.3%
안 5
 
4.3%
천 5
 
4.3%
인 4
 
3.5%
용 4
 
3.5%
흥 4
 
3.5%
Other values (22) 39
33.9%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 115
93.5%
Common 8
 
6.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 31
27.0%
구 8
 
7.0%
남 5
 
4.3%
포 5
 
4.3%
성 5
 
4.3%
안 5
 
4.3%
천 5
 
4.3%
인 4
 
3.5%
용 4
 
3.5%
흥 4
 
3.5%
Other values (22) 39
33.9%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 115
93.5%
ASCII 8
 
6.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 31
27.0%
구 8
 
7.0%
남 5
 
4.3%
포 5
 
4.3%
성 5
 
4.3%
안 5
 
4.3%
천 5
 
4.3%
인 4
 
3.5%
용 4
 
3.5%
흥 4
 
3.5%
Other values (22) 39
33.9%
ASCII
ValueCountFrequency (%)
8
100.0%

행정동명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:48:15.499204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.2333333
Min length2

Characters and Unicode

Total characters97
Distinct characters49
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row달안동
2nd row기타
3rd row동천동
4th row고천동
5th row청평면
ValueCountFrequency (%)
달안동 1
 
3.3%
기타 1
 
3.3%
대부동 1
 
3.3%
소흘읍 1
 
3.3%
대곶면 1
 
3.3%
증포동 1
 
3.3%
광남동 1
 
3.3%
호평동 1
 
3.3%
향남읍 1
 
3.3%
중1동 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T22:48:16.151469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 25
25.8%
1 4
 
4.1%
호 3
 
3.1%
읍 3
 
3.1%
현 3
 
3.1%
면 3
 
3.1%
2 3
 
3.1%
천 3
 
3.1%
대 2
 
2.1%
평 2
 
2.1%
Other values (39) 46
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89
91.8%
Decimal Number 8
 
8.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 25
28.1%
호 3
 
3.4%
읍 3
 
3.4%
현 3
 
3.4%
면 3
 
3.4%
천 3
 
3.4%
대 2
 
2.2%
평 2
 
2.2%
포 2
 
2.2%
남 2
 
2.2%
Other values (36) 41
46.1%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
2 3
37.5%
4 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89
91.8%
Common 8
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 25
28.1%
호 3
 
3.4%
읍 3
 
3.4%
현 3
 
3.4%
면 3
 
3.4%
천 3
 
3.4%
대 2
 
2.2%
평 2
 
2.2%
포 2
 
2.2%
남 2
 
2.2%
Other values (36) 41
46.1%
Common
ValueCountFrequency (%)
1 4
50.0%
2 3
37.5%
4 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89
91.8%
ASCII 8
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 25
28.1%
호 3
 
3.4%
읍 3
 
3.4%
현 3
 
3.4%
면 3
 
3.4%
천 3
 
3.4%
대 2
 
2.2%
평 2
 
2.2%
포 2
 
2.2%
남 2
 
2.2%
Other values (36) 41
46.1%
ASCII
ValueCountFrequency (%)
1 4
50.0%
2 3
37.5%
4 1
 
12.5%

업소명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:48:16.537412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9.5
Mean length5.6666667
Min length3

Characters and Unicode

Total characters170
Distinct characters116
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

Unique30 ?
Unique (%)100.0%

Sample

1st row이창명의짜장면시키신분
2nd row아트헤어
3rd row정원식당
4th row조명진블랙헤어
5th row종로김밥청평점
ValueCountFrequency (%)
이창명의짜장면시키신분 1
 
3.3%
아트헤어 1
 
3.3%
현미촌 1
 
3.3%
해와달 1
 
3.3%
한울이네 1
 
3.3%
한내생고기전문점 1
 
3.3%
한나낙지마당 1
 
3.3%
한가람 1
 
3.3%
하나로마트 1
 
3.3%
플라스틱아일랜드 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T22:48:17.055430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 5
 
2.9%
마 4
 
2.4%
어 4
 
2.4%
아 4
 
2.4%
점 4
 
2.4%
명 4
 
2.4%
한 4
 
2.4%
화 3
 
1.8%
트 3
 
1.8%
학 3
 
1.8%
Other values (106) 132
77.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 170
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 5
 
2.9%
마 4
 
2.4%
어 4
 
2.4%
아 4
 
2.4%
점 4
 
2.4%
명 4
 
2.4%
한 4
 
2.4%
화 3
 
1.8%
트 3
 
1.8%
학 3
 
1.8%
Other values (106) 132
77.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 170
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 5
 
2.9%
마 4
 
2.4%
어 4
 
2.4%
아 4
 
2.4%
점 4
 
2.4%
명 4
 
2.4%
한 4
 
2.4%
화 3
 
1.8%
트 3
 
1.8%
학 3
 
1.8%
Other values (106) 132
77.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 170
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 5
 
2.9%
마 4
 
2.4%
어 4
 
2.4%
아 4
 
2.4%
점 4
 
2.4%
명 4
 
2.4%
한 4
 
2.4%
화 3
 
1.8%
트 3
 
1.8%
학 3
 
1.8%
Other values (106) 132
77.6%

주사업장우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14632.267
Minimum10041
Maximum18593
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:48:17.273705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10041
5-th percentile10564.75
Q112801
median14993
Q316932.75
95-th percentile18021.3
Maximum18593
Range8552
Interquartile range (IQR)4131.75

Descriptive statistics

Standard deviation2499.395
Coefficient of variation (CV)0.17081393
Kurtosis-1.0459783
Mean14632.267
Median Absolute Deviation (MAD)2021
Skewness-0.25753327
Sum438968
Variance6246975.2
MonotonicityNot monotonic
2023-12-10T22:48:17.453705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
14043 1
 
3.3%
17578 1
 
3.3%
16988 1
 
3.3%
15638 1
 
3.3%
11186 1
 
3.3%
10041 1
 
3.3%
17348 1
 
3.3%
12768 1
 
3.3%
12141 1
 
3.3%
18593 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10041 1
3.3%
10108 1
3.3%
11123 1
3.3%
11186 1
3.3%
11487 1
3.3%
12141 1
3.3%
12452 1
3.3%
12768 1
3.3%
12900 1
3.3%
12956 1
3.3%
ValueCountFrequency (%)
18593 1
3.3%
18384 1
3.3%
17578 1
3.3%
17415 1
3.3%
17348 1
3.3%
16998 1
3.3%
16988 1
3.3%
16969 1
3.3%
16824 1
3.3%
16061 1
3.3%

주사업장우편번호주소
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:48:17.845456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length18.066667
Min length14

Characters and Unicode

Total characters542
Distinct characters94
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

Unique30 ?
Unique (%)100.0%

Sample

1st row경기도 안양시 동안구 달안로 61
2nd row경기도 용인시 기흥구 동백8로 19
3rd row경기도 용인시 수지구 고기로 203
4th row경기도 의왕시 현충탑길 41
5th row경기도 가평군 청평면 청평중앙로 52
ValueCountFrequency (%)
경기도 30
 
22.2%
용인시 4
 
3.0%
기흥구 3
 
2.2%
41 2
 
1.5%
하남시 2
 
1.5%
이천시 2
 
1.5%
화성시 2
 
1.5%
시흥시 2
 
1.5%
분당구 2
 
1.5%
성남시 2
 
1.5%
Other values (79) 84
62.2%
2023-12-10T22:48:18.474248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
19.4%
기 34
 
6.3%
시 31
 
5.7%
경 30
 
5.5%
도 30
 
5.5%
로 25
 
4.6%
1 24
 
4.4%
2 17
 
3.1%
길 12
 
2.2%
구 9
 
1.7%
Other values (84) 225
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 342
63.1%
Space Separator 105
 
19.4%
Decimal Number 93
 
17.2%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 34
 
9.9%
시 31
 
9.1%
경 30
 
8.8%
도 30
 
8.8%
로 25
 
7.3%
길 12
 
3.5%
구 9
 
2.6%
천 7
 
2.0%
남 7
 
2.0%
번 6
 
1.8%
Other values (72) 151
44.2%
Decimal Number
ValueCountFrequency (%)
1 24
25.8%
2 17
18.3%
0 9
 
9.7%
8 9
 
9.7%
6 7
 
7.5%
7 6
 
6.5%
5 6
 
6.5%
4 5
 
5.4%
3 5
 
5.4%
9 5
 
5.4%
Space Separator
ValueCountFrequency (%)
105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 342
63.1%
Common 200
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 34
 
9.9%
시 31
 
9.1%
경 30
 
8.8%
도 30
 
8.8%
로 25
 
7.3%
길 12
 
3.5%
구 9
 
2.6%
천 7
 
2.0%
남 7
 
2.0%
번 6
 
1.8%
Other values (72) 151
44.2%
Common
ValueCountFrequency (%)
105
52.5%
1 24
 
12.0%
2 17
 
8.5%
0 9
 
4.5%
8 9
 
4.5%
6 7
 
3.5%
7 6
 
3.0%
5 6
 
3.0%
4 5
 
2.5%
3 5
 
2.5%
Other values (2) 7
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 342
63.1%
ASCII 200
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
52.5%
1 24
 
12.0%
2 17
 
8.5%
0 9
 
4.5%
8 9
 
4.5%
6 7
 
3.5%
7 6
 
3.0%
5 6
 
3.0%
4 5
 
2.5%
3 5
 
2.5%
Other values (2) 7
 
3.5%
Hangul
ValueCountFrequency (%)
기 34
 
9.9%
시 31
 
9.1%
경 30
 
8.8%
도 30
 
8.8%
로 25
 
7.3%
길 12
 
3.5%
구 9
 
2.6%
천 7
 
2.0%
남 7
 
2.0%
번 6
 
1.8%
Other values (72) 151
44.2%

업종대분류명
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
음식
19 
생활서비스
5 
소매
4 
학문/교육
2 

Length

Max length5
Median length2
Mean length2.7
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row음식
2nd row생활서비스
3rd row음식
4th row생활서비스
5th row음식

Common Values

ValueCountFrequency (%)
음식 19
63.3%
생활서비스 5
 
16.7%
소매 4
 
13.3%
학문/교육 2
 
6.7%

Length

2023-12-10T22:48:18.765177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:48:19.073438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식 19
63.3%
생활서비스 5
 
16.7%
소매 4
 
13.3%
학문/교육 2
 
6.7%

업종중분류명
Text

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:48:19.313501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9.5
Mean length4.3
Min length2

Characters and Unicode

Total characters129
Distinct characters57
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)30.0%

Sample

1st row중식
2nd row이/미용/건강
3rd row한식
4th row이/미용/건강
5th row분식
ValueCountFrequency (%)
한식 9
30.0%
중식 3
 
10.0%
이/미용/건강 3
 
10.0%
분식 2
 
6.7%
커피점/카페 2
 
6.7%
종합소매점 2
 
6.7%
학원-보습교습입시 1
 
3.3%
운송/배달/택배 1
 
3.3%
닭/오리요리 1
 
3.3%
학원-어학 1
 
3.3%
Other values (5) 5
16.7%
2023-12-10T22:48:19.838592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 16
 
12.4%
/ 15
 
11.6%
한 9
 
7.0%
점 4
 
3.1%
중 3
 
2.3%
이 3
 
2.3%
미 3
 
2.3%
용 3
 
2.3%
건 3
 
2.3%
강 3
 
2.3%
Other values (47) 67
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 112
86.8%
Other Punctuation 15
 
11.6%
Dash Punctuation 2
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 16
 
14.3%
한 9
 
8.0%
점 4
 
3.6%
중 3
 
2.7%
이 3
 
2.7%
미 3
 
2.7%
용 3
 
2.7%
건 3
 
2.7%
강 3
 
2.7%
학 3
 
2.7%
Other values (45) 62
55.4%
Other Punctuation
ValueCountFrequency (%)
/ 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 112
86.8%
Common 17
 
13.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 16
 
14.3%
한 9
 
8.0%
점 4
 
3.6%
중 3
 
2.7%
이 3
 
2.7%
미 3
 
2.7%
용 3
 
2.7%
건 3
 
2.7%
강 3
 
2.7%
학 3
 
2.7%
Other values (45) 62
55.4%
Common
ValueCountFrequency (%)
/ 15
88.2%
- 2
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 112
86.8%
ASCII 17
 
13.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 16
 
14.3%
한 9
 
8.0%
점 4
 
3.6%
중 3
 
2.7%
이 3
 
2.7%
미 3
 
2.7%
용 3
 
2.7%
건 3
 
2.7%
강 3
 
2.7%
학 3
 
2.7%
Other values (45) 62
55.4%
ASCII
ValueCountFrequency (%)
/ 15
88.2%
- 2
 
11.8%

업종소분류명
Text

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:48:20.113670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length7.2333333
Min length3

Characters and Unicode

Total characters217
Distinct characters76
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)40.0%

Sample

1st row중국음식/중국집
2nd row여성미용실
3rd row한식/백반/한정식
4th row여성미용실
5th row라면김밥분식
ValueCountFrequency (%)
한식/백반/한정식 6
20.0%
중국음식/중국집 3
 
10.0%
여성미용실 3
 
10.0%
라면김밥분식 2
 
6.7%
갈비/삼겹살 2
 
6.7%
커피전문점/카페/다방 2
 
6.7%
학원-외국어/어학 1
 
3.3%
유리/페인트/철물건축자재 1
 
3.3%
음식점-일식 1
 
3.3%
종합소매 1
 
3.3%
Other values (8) 8
26.7%
2023-12-10T22:48:20.588833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 26
 
12.0%
식 21
 
9.7%
한 12
 
5.5%
정 7
 
3.2%
국 7
 
3.2%
백 6
 
2.8%
반 6
 
2.8%
중 6
 
2.8%
점 4
 
1.8%
여 4
 
1.8%
Other values (66) 118
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 188
86.6%
Other Punctuation 26
 
12.0%
Dash Punctuation 3
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 21
 
11.2%
한 12
 
6.4%
정 7
 
3.7%
국 7
 
3.7%
백 6
 
3.2%
반 6
 
3.2%
중 6
 
3.2%
점 4
 
2.1%
여 4
 
2.1%
성 4
 
2.1%
Other values (64) 111
59.0%
Other Punctuation
ValueCountFrequency (%)
/ 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 188
86.6%
Common 29
 
13.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 21
 
11.2%
한 12
 
6.4%
정 7
 
3.7%
국 7
 
3.7%
백 6
 
3.2%
반 6
 
3.2%
중 6
 
3.2%
점 4
 
2.1%
여 4
 
2.1%
성 4
 
2.1%
Other values (64) 111
59.0%
Common
ValueCountFrequency (%)
/ 26
89.7%
- 3
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 188
86.6%
ASCII 29
 
13.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 26
89.7%
- 3
 
10.3%
Hangul
ValueCountFrequency (%)
식 21
 
11.2%
한 12
 
6.4%
정 7
 
3.7%
국 7
 
3.7%
백 6
 
3.2%
반 6
 
3.2%
중 6
 
3.2%
점 4
 
2.1%
여 4
 
2.1%
성 4
 
2.1%
Other values (64) 111
59.0%

표준산업분류코드
Text

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:48:20.831534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.6
Min length2

Characters and Unicode

Total characters168
Distinct characters17
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)30.0%

Sample

1st rowI56112
2nd row기타
3rd rowI56111
4th rowS96112
5th rowI56194
ValueCountFrequency (%)
i56111 9
30.0%
i56112 3
 
10.0%
기타 3
 
10.0%
s96112 2
 
6.7%
i56194 2
 
6.7%
i56220 2
 
6.7%
p85501 1
 
3.3%
h49311 1
 
3.3%
p85502 1
 
3.3%
s96912 1
 
3.3%
Other values (5) 5
16.7%
2023-12-10T22:48:21.257957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 51
30.4%
5 23
13.7%
6 21
12.5%
I 18
 
10.7%
2 12
 
7.1%
9 9
 
5.4%
4 7
 
4.2%
0 5
 
3.0%
타 3
 
1.8%
S 3
 
1.8%
Other values (7) 16
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 135
80.4%
Uppercase Letter 27
 
16.1%
Other Letter 6
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 51
37.8%
5 23
17.0%
6 21
15.6%
2 12
 
8.9%
9 9
 
6.7%
4 7
 
5.2%
0 5
 
3.7%
7 3
 
2.2%
8 2
 
1.5%
3 2
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
I 18
66.7%
S 3
 
11.1%
G 3
 
11.1%
P 2
 
7.4%
H 1
 
3.7%
Other Letter
ValueCountFrequency (%)
타 3
50.0%
기 3
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 135
80.4%
Latin 27
 
16.1%
Hangul 6
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 51
37.8%
5 23
17.0%
6 21
15.6%
2 12
 
8.9%
9 9
 
6.7%
4 7
 
5.2%
0 5
 
3.7%
7 3
 
2.2%
8 2
 
1.5%
3 2
 
1.5%
Latin
ValueCountFrequency (%)
I 18
66.7%
S 3
 
11.1%
G 3
 
11.1%
P 2
 
7.4%
H 1
 
3.7%
Hangul
ValueCountFrequency (%)
타 3
50.0%
기 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 162
96.4%
Hangul 6
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 51
31.5%
5 23
14.2%
6 21
13.0%
I 18
 
11.1%
2 12
 
7.4%
9 9
 
5.6%
4 7
 
4.3%
0 5
 
3.1%
S 3
 
1.9%
G 3
 
1.9%
Other values (5) 10
 
6.2%
Hangul
ValueCountFrequency (%)
타 3
50.0%
기 3
50.0%

표준산업분류명
Text

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:48:21.489236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.8
Min length2

Characters and Unicode

Total characters204
Distinct characters57
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)30.0%

Sample

1st row중식 음식점업
2nd row기타
3rd row한식 음식점업
4th row두발미용업
5th row분식 및 김밥 전문점
ValueCountFrequency (%)
음식점업 14
23.3%
한식 9
15.0%
기타 4
 
6.7%
중식 3
 
5.0%
전문점 2
 
3.3%
일반 2
 
3.3%
음료점업 2
 
3.3%
비알콜 2
 
3.3%
김밥 2
 
3.3%
및 2
 
3.3%
Other values (16) 18
30.0%
2023-12-10T22:48:21.941669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
14.7%
식 30
14.7%
업 21
 
10.3%
점 18
 
8.8%
음 16
 
7.8%
한 9
 
4.4%
기 4
 
2.0%
타 4
 
2.0%
일 3
 
1.5%
중 3
 
1.5%
Other values (47) 66
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174
85.3%
Space Separator 30
 
14.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 30
17.2%
업 21
 
12.1%
점 18
 
10.3%
음 16
 
9.2%
한 9
 
5.2%
기 4
 
2.3%
타 4
 
2.3%
일 3
 
1.7%
중 3
 
1.7%
용 3
 
1.7%
Other values (46) 63
36.2%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 174
85.3%
Common 30
 
14.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 30
17.2%
업 21
 
12.1%
점 18
 
10.3%
음 16
 
9.2%
한 9
 
5.2%
기 4
 
2.3%
타 4
 
2.3%
일 3
 
1.7%
중 3
 
1.7%
용 3
 
1.7%
Other values (46) 63
36.2%
Common
ValueCountFrequency (%)
30
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 174
85.3%
ASCII 30
 
14.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
100.0%
Hangul
ValueCountFrequency (%)
식 30
17.2%
업 21
 
12.1%
점 18
 
10.3%
음 16
 
9.2%
한 9
 
5.2%
기 4
 
2.3%
타 4
 
2.3%
일 3
 
1.7%
중 3
 
1.7%
용 3
 
1.7%
Other values (46) 63
36.2%

경도
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)100.0%
Missing1
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean127.05387
Minimum126.54293
Maximum127.5928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:48:22.241107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54293
5-th percentile126.62857
Q1126.90897
median127.10581
Q3127.22148
95-th percentile127.44295
Maximum127.5928
Range1.0498665
Interquartile range (IQR)0.31251697

Descriptive statistics

Standard deviation0.25744578
Coefficient of variation (CV)0.0020262727
Kurtosis-0.27106282
Mean127.05387
Median Absolute Deviation (MAD)0.1559219
Skewness-0.15199696
Sum3684.5621
Variance0.066278332
MonotonicityNot monotonic
2023-12-10T22:48:22.451707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
126.9489528544 1
 
3.3%
127.1536743101 1
 
3.3%
127.1460560037 1
 
3.3%
126.5682582225 1
 
3.3%
127.1647503814 1
 
3.3%
126.5429349806 1
 
3.3%
127.4580708332 1
 
3.3%
127.2214824802 1
 
3.3%
127.2519995675 1
 
3.3%
126.9089655125 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
126.5429349806 1
3.3%
126.5682582225 1
3.3%
126.7190255268 1
3.3%
126.729753667 1
3.3%
126.741322823 1
3.3%
126.7752992196 1
3.3%
126.8278083006 1
3.3%
126.9089655125 1
3.3%
126.9413310148 1
3.3%
126.9489528544 1
3.3%
ValueCountFrequency (%)
127.59280144 1
3.3%
127.4580708332 1
3.3%
127.420270912 1
3.3%
127.3097302767 1
3.3%
127.2617345406 1
3.3%
127.2519995675 1
3.3%
127.2253176974 1
3.3%
127.2214824802 1
3.3%
127.2029341683 1
3.3%
127.1647503814 1
3.3%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.418526
Minimum37.008623
Maximum127.06437
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:48:22.651020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.008623
5-th percentile37.121808
Q137.294251
median37.386495
Q337.608278
95-th percentile37.863852
Maximum127.06437
Range90.05575
Interquartile range (IQR)0.31402678

Descriptive statistics

Standard deviation16.366149
Coefficient of variation (CV)0.40491702
Kurtosis29.988953
Mean40.418526
Median Absolute Deviation (MAD)0.11209045
Skewness5.4757627
Sum1212.5558
Variance267.85083
MonotonicityNot monotonic
2023-12-10T22:48:22.836127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.3965021687 1
 
3.3%
37.0086233258 1
 
3.3%
37.2758844875 1
 
3.3%
37.2767306793 1
 
3.3%
37.7792956982 1
 
3.3%
37.6401088164 1
 
3.3%
37.2895465906 1
 
3.3%
37.4015481159 1
 
3.3%
37.6702169172 1
 
3.3%
37.1320601462 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
37.0086233258 1
3.3%
37.1134205163 1
3.3%
37.1320601462 1
3.3%
37.2729241142 1
3.3%
37.2758844875 1
3.3%
37.2767306793 1
3.3%
37.2873470717 1
3.3%
37.2895465906 1
3.3%
37.3083657715 1
3.3%
37.3489929691 1
3.3%
ValueCountFrequency (%)
127.0643735076 1
3.3%
37.9193154172 1
3.3%
37.7960635963 1
3.3%
37.7792956982 1
3.3%
37.73789544 1
3.3%
37.6702169172 1
3.3%
37.6401088164 1
3.3%
37.6200055539 1
3.3%
37.5730960003 1
3.3%
37.5345985793 1
3.3%

Interactions

2023-12-10T22:48:11.384749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:09.037538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:10.039743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:10.729257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:11.517055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:09.594612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:10.169818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:10.858537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:11.631647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:09.782751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:10.280851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:11.022695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:11.770790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:09.915020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:10.504177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:48:11.235413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:48:23.004576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상가업소번호시군구명행정동명업소명주사업장우편번호주사업장우편번호주소업종대분류명업종중분류명업종소분류명표준산업분류코드표준산업분류명경도위도
상가업소번호1.0000.5571.0001.0000.2551.0000.6380.5320.3670.5640.5640.2810.000
시군구명0.5571.0001.0001.0001.0001.0000.8840.7180.3280.3030.3030.8990.000
행정동명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주사업장우편번호0.2551.0001.0001.0001.0001.0000.4190.1600.0000.5470.5470.8190.643
주사업장우편번호주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
업종대분류명0.6380.8841.0001.0000.4191.0001.0001.0001.0000.9560.9560.0000.544
업종중분류명0.5320.7181.0001.0000.1601.0001.0001.0001.0000.9960.9960.0001.000
업종소분류명0.3670.3281.0001.0000.0001.0001.0001.0001.0000.9900.9900.0001.000
표준산업분류코드0.5640.3031.0001.0000.5471.0000.9560.9960.9901.0001.0000.0001.000
표준산업분류명0.5640.3031.0001.0000.5471.0000.9560.9960.9901.0001.0000.0001.000
경도0.2810.8991.0001.0000.8191.0000.0000.0000.0000.0000.0001.000NaN
위도0.0000.0001.0001.0000.6431.0000.5441.0001.0001.0001.000NaN1.000
2023-12-10T22:48:23.707556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상가업소번호주사업장우편번호경도위도업종대분류명
상가업소번호1.000-0.096-0.0040.0810.137
주사업장우편번호-0.0961.0000.082-0.7650.241
경도-0.0040.0821.0000.0450.000
위도0.081-0.7650.0451.0000.354
업종대분류명0.1370.2410.0000.3541.000

Missing values

2023-12-10T22:48:11.952993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:48:12.314322image/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.

Sample

기준년월상가업소번호시도명시군구명행정동명업소명주사업장우편번호주사업장우편번호주소업종대분류명업종중분류명업종소분류명표준산업분류코드표준산업분류명경도위도
02021-1010004196경기도안양시 동안구달안동이창명의짜장면시키신분14043경기도 안양시 동안구 달안로 61음식중식중국음식/중국집I56112중식 음식점업126.94895337.396502
12021-109842951경기도용인시기타아트헤어16998경기도 용인시 기흥구 동백8로 19생활서비스이/미용/건강여성미용실기타기타127.15367437.287347
22021-1010046442경기도용인시 수지구동천동정원식당16824경기도 용인시 수지구 고기로 203음식한식한식/백반/한정식I56111한식 음식점업127.08327137.351124
32021-1010061122경기도의왕시고천동조명진블랙헤어16061경기도 의왕시 현충탑길 41생활서비스이/미용/건강여성미용실S96112두발미용업126.97728237.349661
42021-1010066035경기도가평군청평면종로김밥청평점12452경기도 가평군 청평면 청평중앙로 52음식분식라면김밥분식I56194분식 및 김밥 전문점127.42027137.737895
52021-1010076638경기도포천시화현면중국성11123경기도 포천시 화현면 화동로 597음식중식중국음식/중국집I56112중식 음식점업127.3097337.919315
62021-1010099120경기도의왕시내손1동쪽갈비명가16039경기도 의왕시 계원대학로 22음식한식갈비/삼겹살I56111한식 음식점업126.97387837.379177
72021-109878007경기도안산시 단원구호수동엔아이티입시학원15476경기도 안산시 단원구 광덕1로 163학문/교육학원-보습교습입시학원-입시P85501일반 교과 학원126.82780837.308366
82021-1010107926경기도성남시 분당구서현1동크림팝13591경기도 성남시 분당구 성남대로 601음식분식라면김밥분식I56194분식 및 김밥 전문점127.12342137.385003
92021-1010109389경기도시흥시월곶동처갓집월곶점14966경기도 시흥시 월곶중앙로 38음식한식한식/백반/한정식I56111한식 음식점업126.74132337.387987
기준년월상가업소번호시도명시군구명행정동명업소명주사업장우편번호주사업장우편번호주소업종대분류명업종중분류명업종소분류명표준산업분류코드표준산업분류명경도위도
202021-1010220007경기도하남시미사1동풍납칡냉면12900경기도 하남시 미사동로 70음식한식냉면집I56111한식 음식점업127.20293437.573096
212021-1010226288경기도부천시중1동플라스틱아일랜드14548경기도 부천시 길주로 300소매의복의류여성의류전문점기타기타126.77529937.502533
222021-1010237157경기도화성시향남읍하나로마트18593경기도 화성시 향남읍 평2길 16소매종합소매점종합소매G47190그외 기타 종합 소매업126.90896637.13206
232021-1010248071경기도남양주시호평동한가람12141경기도 남양주시 천마산로 110음식한식한식/백반/한정식I56111한식 음식점업127.25237.670217
242021-1010254781경기도광주시광남동한나낙지마당12768경기도 광주시 순암로 278음식한식한식/백반/한정식I56111한식 음식점업127.22148237.401548
252021-1010255116경기도이천시증포동한내생고기전문점17348경기도 이천시 갈산로 41음식한식갈비/삼겹살I56111한식 음식점업127.45807137.289547
262021-1010268480경기도김포시대곶면한울이네10041경기도 김포시 대곶면 대명항1로92번길 20음식일식/수산물음식점-일식I56113일식 음식점업126.54293537.640109
272021-1010280862경기도포천시소흘읍해와달11186경기도 포천시 소흘읍 죽엽산로 627음식양식정통양식/경양식I56114서양식 음식점업127.1647537.779296
282021-1010302510경기도안산시 단원구대부동현미촌15638경기도 안산시 단원구 서위길 17음식한식한식/백반/한정식I56111한식 음식점업126.56825837.276731
292021-1010316995경기도용인시 기흥구동백동화궁용인영업소16988경기도 용인시 기흥구 어정로 149음식중식중국음식/중국집I56112중식 음식점업127.14605637.275884