Overview

Dataset statistics

Number of variables6
Number of observations264
Missing cells6
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.8 KiB
Average record size in memory49.5 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description인천광역시 중구의 인쇄소 및 출판사에 대한 정보입니다.파일명 인천광역시 중구 인쇄소및출판사내용 사업체명칭, 사업체소재지
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15074655&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 연번High correlation
사업체소재지(도로명) has 6 (2.3%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 17:40:29.099244
Analysis finished2024-01-28 17:40:29.749617
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct264
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.39394
Minimum1
Maximum347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-01-29T02:40:29.814058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.15
Q166.75
median132.5
Q3281.25
95-th percentile333.85
Maximum347
Range346
Interquartile range (IQR)214.5

Descriptive statistics

Standard deviation108.42872
Coefficient of variation (CV)0.69330512
Kurtosis-1.1950962
Mean156.39394
Median Absolute Deviation (MAD)76
Skewness0.42730851
Sum41288
Variance11756.787
MonotonicityStrictly increasing
2024-01-29T02:40:29.938162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
183 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
175 1
 
0.4%
176 1
 
0.4%
Other values (254) 254
96.2%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
347 1
0.4%
346 1
0.4%
345 1
0.4%
344 1
0.4%
343 1
0.4%
342 1
0.4%
341 1
0.4%
340 1
0.4%
339 1
0.4%
338 1
0.4%

업종
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
출판사
188 
인쇄사
76 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
출판사 188
71.2%
인쇄사 76
28.8%

Length

2024-01-29T02:40:30.052833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:40:30.131600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
출판사 188
71.2%
인쇄사 76
28.8%

사업체명칭
Text

Distinct245
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-01-29T02:40:30.337834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length17
Mean length6.469697
Min length2

Characters and Unicode

Total characters1708
Distinct characters351
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)86.0%

Sample

1st row(주)기호일보사
2nd row참글사
3rd row도서출판월드
4th row화신출판사
5th row주간앙코루출판부
ValueCountFrequency (%)
도서출판 14
 
4.1%
출판사 6
 
1.8%
주식회사 6
 
1.8%
주)인천일보 3
 
0.9%
새순기획 2
 
0.6%
시사외국어사 2
 
0.6%
주)이너스 2
 
0.6%
book 2
 
0.6%
출판 2
 
0.6%
우성인쇄기획 2
 
0.6%
Other values (282) 297
87.9%
2024-01-29T02:40:30.703435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74
 
4.3%
사 71
 
4.2%
인 62
 
3.6%
( 48
 
2.8%
) 48
 
2.8%
판 46
 
2.7%
출 44
 
2.6%
주 36
 
2.1%
스 31
 
1.8%
이 31
 
1.8%
Other values (341) 1217
71.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1315
77.0%
Lowercase Letter 106
 
6.2%
Uppercase Letter 104
 
6.1%
Space Separator 74
 
4.3%
Open Punctuation 48
 
2.8%
Close Punctuation 48
 
2.8%
Other Punctuation 7
 
0.4%
Decimal Number 5
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 71
 
5.4%
인 62
 
4.7%
판 46
 
3.5%
출 44
 
3.3%
주 36
 
2.7%
스 31
 
2.4%
이 31
 
2.4%
쇄 29
 
2.2%
아 24
 
1.8%
기 23
 
1.7%
Other values (286) 918
69.8%
Lowercase Letter
ValueCountFrequency (%)
o 18
17.0%
e 10
 
9.4%
s 9
 
8.5%
i 8
 
7.5%
r 7
 
6.6%
k 6
 
5.7%
a 6
 
5.7%
l 6
 
5.7%
u 5
 
4.7%
h 5
 
4.7%
Other values (12) 26
24.5%
Uppercase Letter
ValueCountFrequency (%)
M 14
13.5%
O 12
11.5%
E 8
 
7.7%
S 8
 
7.7%
T 8
 
7.7%
B 7
 
6.7%
N 7
 
6.7%
A 7
 
6.7%
P 5
 
4.8%
L 5
 
4.8%
Other values (11) 23
22.1%
Other Punctuation
ValueCountFrequency (%)
& 3
42.9%
' 1
 
14.3%
! 1
 
14.3%
, 1
 
14.3%
. 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
5 2
40.0%
1 2
40.0%
2 1
20.0%
Space Separator
ValueCountFrequency (%)
74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1315
77.0%
Latin 210
 
12.3%
Common 183
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 71
 
5.4%
인 62
 
4.7%
판 46
 
3.5%
출 44
 
3.3%
주 36
 
2.7%
스 31
 
2.4%
이 31
 
2.4%
쇄 29
 
2.2%
아 24
 
1.8%
기 23
 
1.7%
Other values (286) 918
69.8%
Latin
ValueCountFrequency (%)
o 18
 
8.6%
M 14
 
6.7%
O 12
 
5.7%
e 10
 
4.8%
s 9
 
4.3%
i 8
 
3.8%
E 8
 
3.8%
S 8
 
3.8%
T 8
 
3.8%
r 7
 
3.3%
Other values (33) 108
51.4%
Common
ValueCountFrequency (%)
74
40.4%
( 48
26.2%
) 48
26.2%
& 3
 
1.6%
5 2
 
1.1%
1 2
 
1.1%
' 1
 
0.5%
! 1
 
0.5%
2 1
 
0.5%
, 1
 
0.5%
Other values (2) 2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1315
77.0%
ASCII 393
 
23.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
74
18.8%
( 48
 
12.2%
) 48
 
12.2%
o 18
 
4.6%
M 14
 
3.6%
O 12
 
3.1%
e 10
 
2.5%
s 9
 
2.3%
i 8
 
2.0%
E 8
 
2.0%
Other values (45) 144
36.6%
Hangul
ValueCountFrequency (%)
사 71
 
5.4%
인 62
 
4.7%
판 46
 
3.5%
출 44
 
3.3%
주 36
 
2.7%
스 31
 
2.4%
이 31
 
2.4%
쇄 29
 
2.2%
아 24
 
1.8%
기 23
 
1.7%
Other values (286) 918
69.8%

사업체소재지(도로명)
Text

MISSING 

Distinct66
Distinct (%)25.6%
Missing6
Missing (%)2.3%
Memory size2.2 KiB
2024-01-29T02:40:30.953068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length8
Mean length12.906977
Min length8

Characters and Unicode

Total characters3330
Distinct characters105
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

Unique60 ?
Unique (%)23.3%

Sample

1st row인천광역시 중구
2nd row인천광역시 중구
3rd row인천광역시 중구
4th row인천광역시 중구
5th row인천광역시 중구
ValueCountFrequency (%)
인천광역시 258
35.1%
중구 258
35.1%
신흥동3가 8
 
1.1%
인중로 7
 
1.0%
신포로23번길 6
 
0.8%
서해대로 6
 
0.8%
유동 6
 
0.8%
제물량로 5
 
0.7%
도원로8번길 5
 
0.7%
선화동 4
 
0.5%
Other values (124) 172
23.4%
2024-01-29T02:40:31.351257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
507
15.2%
중 274
 
8.2%
인 273
 
8.2%
구 260
 
7.8%
천 259
 
7.8%
시 259
 
7.8%
광 259
 
7.8%
역 258
 
7.7%
로 67
 
2.0%
동 58
 
1.7%
Other values (95) 856
25.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2371
71.2%
Space Separator 507
 
15.2%
Decimal Number 302
 
9.1%
Open Punctuation 56
 
1.7%
Close Punctuation 56
 
1.7%
Other Punctuation 21
 
0.6%
Dash Punctuation 16
 
0.5%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 274
11.6%
인 273
11.5%
구 260
11.0%
천 259
10.9%
시 259
10.9%
광 259
10.9%
역 258
10.9%
로 67
 
2.8%
동 58
 
2.4%
길 37
 
1.6%
Other values (79) 367
15.5%
Decimal Number
ValueCountFrequency (%)
2 55
18.2%
1 51
16.9%
3 44
14.6%
4 44
14.6%
8 24
7.9%
5 23
7.6%
0 18
 
6.0%
6 17
 
5.6%
9 14
 
4.6%
7 12
 
4.0%
Space Separator
ValueCountFrequency (%)
507
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2371
71.2%
Common 958
28.8%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 274
11.6%
인 273
11.5%
구 260
11.0%
천 259
10.9%
시 259
10.9%
광 259
10.9%
역 258
10.9%
로 67
 
2.8%
동 58
 
2.4%
길 37
 
1.6%
Other values (79) 367
15.5%
Common
ValueCountFrequency (%)
507
52.9%
( 56
 
5.8%
) 56
 
5.8%
2 55
 
5.7%
1 51
 
5.3%
3 44
 
4.6%
4 44
 
4.6%
8 24
 
2.5%
5 23
 
2.4%
, 21
 
2.2%
Other values (5) 77
 
8.0%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2371
71.2%
ASCII 959
28.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
507
52.9%
( 56
 
5.8%
) 56
 
5.8%
2 55
 
5.7%
1 51
 
5.3%
3 44
 
4.6%
4 44
 
4.6%
8 24
 
2.5%
5 23
 
2.4%
, 21
 
2.2%
Other values (6) 78
 
8.1%
Hangul
ValueCountFrequency (%)
중 274
11.6%
인 273
11.5%
구 260
11.0%
천 259
10.9%
시 259
10.9%
광 259
10.9%
역 258
10.9%
로 67
 
2.8%
동 58
 
2.4%
길 37
 
1.6%
Other values (79) 367
15.5%

사업체소재지(지번)
Text

Distinct70
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-01-29T02:40:31.601874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length8
Mean length11.253788
Min length8

Characters and Unicode

Total characters2971
Distinct characters75
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)23.9%

Sample

1st row인천광역시 중구
2nd row인천광역시 중구
3rd row인천광역시 중구
4th row인천광역시 중구
5th row인천광역시 중구
ValueCountFrequency (%)
인천광역시 264
37.8%
중구 264
37.8%
신흥동3가 12
 
1.7%
유동 7
 
1.0%
중앙동2가 6
 
0.9%
신흥동2가 5
 
0.7%
용동 4
 
0.6%
항동4가 4
 
0.6%
18-1 4
 
0.6%
선화동 4
 
0.6%
Other values (90) 124
17.8%
2024-01-29T02:40:31.964886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
506
17.0%
중 273
9.2%
인 270
9.1%
구 266
9.0%
광 265
8.9%
천 265
8.9%
역 264
8.9%
시 264
8.9%
동 78
 
2.6%
1 75
 
2.5%
Other values (65) 445
15.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2141
72.1%
Space Separator 506
 
17.0%
Decimal Number 267
 
9.0%
Dash Punctuation 54
 
1.8%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 273
12.8%
인 270
12.6%
구 266
12.4%
광 265
12.4%
천 265
12.4%
역 264
12.3%
시 264
12.3%
동 78
 
3.6%
가 37
 
1.7%
신 26
 
1.2%
Other values (50) 133
6.2%
Decimal Number
ValueCountFrequency (%)
1 75
28.1%
2 55
20.6%
3 35
13.1%
4 32
12.0%
6 15
 
5.6%
9 14
 
5.2%
7 14
 
5.2%
8 11
 
4.1%
5 8
 
3.0%
0 8
 
3.0%
Space Separator
ValueCountFrequency (%)
506
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2141
72.1%
Common 829
 
27.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 273
12.8%
인 270
12.6%
구 266
12.4%
광 265
12.4%
천 265
12.4%
역 264
12.3%
시 264
12.3%
동 78
 
3.6%
가 37
 
1.7%
신 26
 
1.2%
Other values (50) 133
6.2%
Common
ValueCountFrequency (%)
506
61.0%
1 75
 
9.0%
2 55
 
6.6%
- 54
 
6.5%
3 35
 
4.2%
4 32
 
3.9%
6 15
 
1.8%
9 14
 
1.7%
7 14
 
1.7%
8 11
 
1.3%
Other values (4) 18
 
2.2%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2141
72.1%
ASCII 830
 
27.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
506
61.0%
1 75
 
9.0%
2 55
 
6.6%
- 54
 
6.5%
3 35
 
4.2%
4 32
 
3.9%
6 15
 
1.8%
9 14
 
1.7%
7 14
 
1.7%
8 11
 
1.3%
Other values (5) 19
 
2.3%
Hangul
ValueCountFrequency (%)
중 273
12.8%
인 270
12.6%
구 266
12.4%
광 265
12.4%
천 265
12.4%
역 264
12.3%
시 264
12.3%
동 78
 
3.6%
가 37
 
1.7%
신 26
 
1.2%
Other values (50) 133
6.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-08-04
264 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-04
2nd row2023-08-04
3rd row2023-08-04
4th row2023-08-04
5th row2023-08-04

Common Values

ValueCountFrequency (%)
2023-08-04 264
100.0%

Length

2024-01-29T02:40:32.079767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:40:32.166108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-04 264
100.0%

Interactions

2024-01-29T02:40:29.519033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:40:32.222109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종사업체소재지(도로명)사업체소재지(지번)
연번1.0001.0000.7300.714
업종1.0001.0001.0001.000
사업체소재지(도로명)0.7301.0001.0001.000
사업체소재지(지번)0.7141.0001.0001.000
2024-01-29T02:40:32.654977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.987
업종0.9871.000

Missing values

2024-01-29T02:40:29.623811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:40:29.708844image/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

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