Overview

Dataset statistics

Number of variables8
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory70.1 B

Variable types

Numeric1
DateTime1
Text4
Categorical2

Dataset

Description이 데이터는 2023년 9월 13일 기준으로 남원시 소재에 있는 인쇄소에 대하여 신고일자, 사업체명칭, 사업체소재지(도로명), 전화번호 등에 대한 데이터입니다.
Author전라북도 남원시
URLhttps://www.data.go.kr/data/3075530/fileData.do

Alerts

업종 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
신고일자 has unique valuesUnique
사업체명칭 has unique valuesUnique
성 명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:09:08.282970
Analysis finished2023-12-12 03:09:09.435852
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T12:09:09.503625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-12T12:09:09.641515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

신고일자
Date

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum1960-03-30 00:00:00
Maximum2013-10-08 00:00:00
2023-12-12T12:09:09.778553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:09:09.913529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

사업체명칭
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T12:09:10.162129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length5.6538462
Min length2

Characters and Unicode

Total characters147
Distinct characters58
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

Unique26 ?
Unique (%)100.0%

Sample

1st row현대인쇄소
2nd row서광인쇄소
3rd row호남인쇄소
4th row삼화인쇄소
5th row대영인쇄사
ValueCountFrequency (%)
현대인쇄소 1
 
3.3%
서광인쇄소 1
 
3.3%
내척동 1
 
3.3%
광고시대 1
 
3.3%
유한회사 1
 
3.3%
프린트 1
 
3.3%
혜은 1
 
3.3%
대영기획 1
 
3.3%
유)도시광고산업 1
 
3.3%
만인쇄출판사 1
 
3.3%
Other values (20) 20
66.7%
2023-12-12T12:09:10.654647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 14
 
9.5%
쇄 14
 
9.5%
소 9
 
6.1%
사 8
 
5.4%
광 6
 
4.1%
문 5
 
3.4%
화 5
 
3.4%
고 5
 
3.4%
대 4
 
2.7%
동 4
 
2.7%
Other values (48) 73
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
93.2%
Space Separator 4
 
2.7%
Open Punctuation 3
 
2.0%
Close Punctuation 3
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 14
 
10.2%
쇄 14
 
10.2%
소 9
 
6.6%
사 8
 
5.8%
광 6
 
4.4%
문 5
 
3.6%
화 5
 
3.6%
고 5
 
3.6%
대 4
 
2.9%
동 4
 
2.9%
Other values (45) 63
46.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
93.2%
Common 10
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 14
 
10.2%
쇄 14
 
10.2%
소 9
 
6.6%
사 8
 
5.8%
광 6
 
4.4%
문 5
 
3.6%
화 5
 
3.6%
고 5
 
3.6%
대 4
 
2.9%
동 4
 
2.9%
Other values (45) 63
46.0%
Common
ValueCountFrequency (%)
4
40.0%
( 3
30.0%
) 3
30.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
93.2%
ASCII 10
 
6.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 14
 
10.2%
쇄 14
 
10.2%
소 9
 
6.6%
사 8
 
5.8%
광 6
 
4.4%
문 5
 
3.6%
화 5
 
3.6%
고 5
 
3.6%
대 4
 
2.9%
동 4
 
2.9%
Other values (45) 63
46.0%
ASCII
ValueCountFrequency (%)
4
40.0%
( 3
30.0%
) 3
30.0%

사업체소재지
Text

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T12:09:10.930731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length17.807692
Min length17

Characters and Unicode

Total characters463
Distinct characters43
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

Unique24 ?
Unique (%)92.3%

Sample

1st row 전라북도 남원시 광한북로 80
2nd row 전라북도 남원시 시청로 65
3rd row 전라북도 남원시 용성로 51
4th row 전라북도 남원시 용성로 62
5th row 전라북도 남원시 향단로 55
ValueCountFrequency (%)
전라북도 26
25.0%
남원시 26
25.0%
용성로 6
 
5.8%
광한북로 3
 
2.9%
향단로 3
 
2.9%
솔터길 2
 
1.9%
55 2
 
1.9%
51 2
 
1.9%
62 2
 
1.9%
의총로 2
 
1.9%
Other values (28) 30
28.8%
2023-12-12T12:09:11.391735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
130
28.1%
북 29
 
6.3%
시 29
 
6.3%
남 28
 
6.0%
전 27
 
5.8%
라 26
 
5.6%
도 26
 
5.6%
원 26
 
5.6%
로 21
 
4.5%
1 13
 
2.8%
Other values (33) 108
23.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 265
57.2%
Space Separator 130
28.1%
Decimal Number 62
 
13.4%
Dash Punctuation 6
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 29
10.9%
시 29
10.9%
남 28
10.6%
전 27
10.2%
라 26
9.8%
도 26
9.8%
원 26
9.8%
로 21
7.9%
용 6
 
2.3%
성 6
 
2.3%
Other values (21) 41
15.5%
Decimal Number
ValueCountFrequency (%)
1 13
21.0%
5 11
17.7%
2 8
12.9%
6 7
11.3%
9 5
 
8.1%
7 4
 
6.5%
0 4
 
6.5%
4 4
 
6.5%
8 3
 
4.8%
3 3
 
4.8%
Space Separator
ValueCountFrequency (%)
130
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 265
57.2%
Common 198
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 29
10.9%
시 29
10.9%
남 28
10.6%
전 27
10.2%
라 26
9.8%
도 26
9.8%
원 26
9.8%
로 21
7.9%
용 6
 
2.3%
성 6
 
2.3%
Other values (21) 41
15.5%
Common
ValueCountFrequency (%)
130
65.7%
1 13
 
6.6%
5 11
 
5.6%
2 8
 
4.0%
6 7
 
3.5%
- 6
 
3.0%
9 5
 
2.5%
7 4
 
2.0%
0 4
 
2.0%
4 4
 
2.0%
Other values (2) 6
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 265
57.2%
ASCII 198
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
130
65.7%
1 13
 
6.6%
5 11
 
5.6%
2 8
 
4.0%
6 7
 
3.5%
- 6
 
3.0%
9 5
 
2.5%
7 4
 
2.0%
0 4
 
2.0%
4 4
 
2.0%
Other values (2) 6
 
3.0%
Hangul
ValueCountFrequency (%)
북 29
10.9%
시 29
10.9%
남 28
10.6%
전 27
10.2%
라 26
9.8%
도 26
9.8%
원 26
9.8%
로 21
7.9%
용 6
 
2.3%
성 6
 
2.3%
Other values (21) 41
15.5%

전화번호
Text

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T12:09:11.638973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters312
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

Unique24 ?
Unique (%)92.3%

Sample

1st row063-631-0694
2nd row063-625-3227
3rd row063-631-3733
4th row063-631-2961
5th row063-631-3321
ValueCountFrequency (%)
063-633-7657 2
 
7.7%
063-631-0694 1
 
3.8%
063-632-0255 1
 
3.8%
063-632-5682 1
 
3.8%
063-625-3321 1
 
3.8%
063-633-3350 1
 
3.8%
063-625-4572 1
 
3.8%
063-626-7841 1
 
3.8%
063-626-3884 1
 
3.8%
063-636-6167 1
 
3.8%
Other values (15) 15
57.7%
2023-12-12T12:09:12.061382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 65
20.8%
3 62
19.9%
- 52
16.7%
0 34
10.9%
2 27
8.7%
5 21
 
6.7%
4 14
 
4.5%
1 12
 
3.8%
7 10
 
3.2%
8 10
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 260
83.3%
Dash Punctuation 52
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 65
25.0%
3 62
23.8%
0 34
13.1%
2 27
10.4%
5 21
 
8.1%
4 14
 
5.4%
1 12
 
4.6%
7 10
 
3.8%
8 10
 
3.8%
9 5
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 65
20.8%
3 62
19.9%
- 52
16.7%
0 34
10.9%
2 27
8.7%
5 21
 
6.7%
4 14
 
4.5%
1 12
 
3.8%
7 10
 
3.2%
8 10
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 65
20.8%
3 62
19.9%
- 52
16.7%
0 34
10.9%
2 27
8.7%
5 21
 
6.7%
4 14
 
4.5%
1 12
 
3.8%
7 10
 
3.2%
8 10
 
3.2%

성 명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T12:09:12.341939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters78
Distinct characters47
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

Unique26 ?
Unique (%)100.0%

Sample

1st row이봉섭
2nd row손상수
3rd row장문석
4th row황의택
5th row이신웅
ValueCountFrequency (%)
이봉섭 1
 
3.8%
손상수 1
 
3.8%
오혜은 1
 
3.8%
이창훈 1
 
3.8%
김희만 1
 
3.8%
백영섭 1
 
3.8%
정명재 1
 
3.8%
김혜정 1
 
3.8%
김영주 1
 
3.8%
김현식 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T12:09:12.804495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 9
 
11.5%
김 4
 
5.1%
수 3
 
3.8%
정 3
 
3.8%
명 3
 
3.8%
영 3
 
3.8%
장 2
 
2.6%
기 2
 
2.6%
섭 2
 
2.6%
훈 2
 
2.6%
Other values (37) 45
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 9
 
11.5%
김 4
 
5.1%
수 3
 
3.8%
정 3
 
3.8%
명 3
 
3.8%
영 3
 
3.8%
장 2
 
2.6%
기 2
 
2.6%
섭 2
 
2.6%
훈 2
 
2.6%
Other values (37) 45
57.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 9
 
11.5%
김 4
 
5.1%
수 3
 
3.8%
정 3
 
3.8%
명 3
 
3.8%
영 3
 
3.8%
장 2
 
2.6%
기 2
 
2.6%
섭 2
 
2.6%
훈 2
 
2.6%
Other values (37) 45
57.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 9
 
11.5%
김 4
 
5.1%
수 3
 
3.8%
정 3
 
3.8%
명 3
 
3.8%
영 3
 
3.8%
장 2
 
2.6%
기 2
 
2.6%
섭 2
 
2.6%
훈 2
 
2.6%
Other values (37) 45
57.7%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
인쇄사
26 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인쇄사 26
100.0%

Length

2023-12-12T12:09:12.978510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:09:13.112938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인쇄사 26
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-09-14
26 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-14
2nd row2023-09-14
3rd row2023-09-14
4th row2023-09-14
5th row2023-09-14

Common Values

ValueCountFrequency (%)
2023-09-14 26
100.0%

Length

2023-12-12T12:09:13.233642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:09:13.358454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-14 26
100.0%

Interactions

2023-12-12T12:09:08.619191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:09:13.459612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번신고일자사업체명칭사업체소재지전화번호성 명
연번1.0001.0001.0000.9160.9161.000
신고일자1.0001.0001.0001.0001.0001.000
사업체명칭1.0001.0001.0001.0001.0001.000
사업체소재지0.9161.0001.0001.0000.9881.000
전화번호0.9161.0001.0000.9881.0001.000
성 명1.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T12:09:09.221735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:09:09.383989image/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

연번신고일자사업체명칭사업체소재지전화번호성 명업종데이터기준일자
011960-03-30현대인쇄소전라북도 남원시 광한북로 80063-631-0694이봉섭인쇄사2023-09-14
121967-12-01서광인쇄소전라북도 남원시 시청로 65063-625-3227손상수인쇄사2023-09-14
231970-11-13호남인쇄소전라북도 남원시 용성로 51063-631-3733장문석인쇄사2023-09-14
341971-04-29삼화인쇄소전라북도 남원시 용성로 62063-631-2961황의택인쇄사2023-09-14
451973-08-03대영인쇄사전라북도 남원시 향단로 55063-631-3321이신웅인쇄사2023-09-14
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