Overview

Dataset statistics

Number of variables14
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory123.0 B

Variable types

Numeric4
Text5
Categorical1
DateTime4

Dataset

Description인천광역시 서구 소재 지식산업센터에 대한 데이터로, 지식산업센터명, 공장부지면적, 제조시설면적, 부대시설면적, 건축물동수, 건축물 층수, 설립승인일, 공장등록일, 준공일, 주소 등을 제공합니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15084509

Alerts

데이터기준일 has constant value ""Constant
공장부지면적 is highly overall correlated with 제조시설면적 and 1 other fieldsHigh correlation
제조시설면적 is highly overall correlated with 공장부지면적 and 2 other fieldsHigh correlation
부대시설면적 is highly overall correlated with 제조시설면적High correlation
건축물동수 is highly overall correlated with 공장부지면적 and 1 other fieldsHigh correlation
건축물동수 is highly imbalanced (66.5%)Imbalance
순번 has unique valuesUnique
지식산업센터명 has unique valuesUnique
공장부지면적 has unique valuesUnique
제조시설면적 has unique valuesUnique
호실수(산업_지원) has unique valuesUnique
준공일 has unique valuesUnique
공장대표주소(도로명) has unique valuesUnique
공장대표주소(지번) has unique valuesUnique
공장부지면적 has 1 (4.5%) zerosZeros
부대시설면적 has 2 (9.1%) zerosZeros

Reproduction

Analysis started2024-01-28 14:20:02.824281
Analysis finished2024-01-28 14:20:04.560651
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T23:20:04.617391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q16.25
median11.5
Q316.75
95-th percentile20.95
Maximum22
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.5646597
Kurtosis-1.2
Mean11.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum253
Variance42.166667
MonotonicityStrictly increasing
2024-01-28T23:20:04.725948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 1
 
4.5%
13 1
 
4.5%
22 1
 
4.5%
21 1
 
4.5%
20 1
 
4.5%
19 1
 
4.5%
18 1
 
4.5%
17 1
 
4.5%
16 1
 
4.5%
15 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
6 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
ValueCountFrequency (%)
22 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
18 1
4.5%
17 1
4.5%
16 1
4.5%
15 1
4.5%
14 1
4.5%
13 1
4.5%

지식산업센터명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T23:20:04.885059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length8.4545455
Min length4

Characters and Unicode

Total characters186
Distinct characters85
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

Unique22 ?
Unique (%)100.0%

Sample

1st row광양프런티어밸리 3차
2nd row인천PCB협동화사업장
3rd row금하산업
4th row대덕테크노타운
5th row가좌IC지식산업센터
ValueCountFrequency (%)
주안 2
 
6.9%
광양프런티어밸리 1
 
3.4%
3차 1
 
3.4%
m&j 1
 
3.4%
아르테크주안 1
 
3.4%
2차 1
 
3.4%
bt센터 1
 
3.4%
뷰티&테크노센터 1
 
3.4%
뷰티코스메틱센터 1
 
3.4%
인천 1
 
3.4%
Other values (18) 18
62.1%
2024-01-28T23:20:05.174266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 8
 
4.3%
센 8
 
4.3%
7
 
3.8%
업 7
 
3.8%
산 6
 
3.2%
타 6
 
3.2%
크 6
 
3.2%
테 6
 
3.2%
주 6
 
3.2%
지 5
 
2.7%
Other values (75) 121
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 155
83.3%
Uppercase Letter 11
 
5.9%
Space Separator 7
 
3.8%
Decimal Number 5
 
2.7%
Close Punctuation 3
 
1.6%
Open Punctuation 3
 
1.6%
Other Punctuation 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 8
 
5.2%
센 8
 
5.2%
업 7
 
4.5%
산 6
 
3.9%
타 6
 
3.9%
크 6
 
3.9%
테 6
 
3.9%
주 6
 
3.9%
지 5
 
3.2%
노 4
 
2.6%
Other values (58) 93
60.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
18.2%
B 2
18.2%
M 1
9.1%
T 1
9.1%
D 1
9.1%
H 1
9.1%
P 1
9.1%
I 1
9.1%
J 1
9.1%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
8 1
20.0%
0 1
20.0%
3 1
20.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 155
83.3%
Common 20
 
10.8%
Latin 11
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 8
 
5.2%
센 8
 
5.2%
업 7
 
4.5%
산 6
 
3.9%
타 6
 
3.9%
크 6
 
3.9%
테 6
 
3.9%
주 6
 
3.9%
지 5
 
3.2%
노 4
 
2.6%
Other values (58) 93
60.0%
Latin
ValueCountFrequency (%)
C 2
18.2%
B 2
18.2%
M 1
9.1%
T 1
9.1%
D 1
9.1%
H 1
9.1%
P 1
9.1%
I 1
9.1%
J 1
9.1%
Common
ValueCountFrequency (%)
7
35.0%
) 3
15.0%
( 3
15.0%
2 2
 
10.0%
& 2
 
10.0%
8 1
 
5.0%
0 1
 
5.0%
3 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 155
83.3%
ASCII 31
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 8
 
5.2%
센 8
 
5.2%
업 7
 
4.5%
산 6
 
3.9%
타 6
 
3.9%
크 6
 
3.9%
테 6
 
3.9%
주 6
 
3.9%
지 5
 
3.2%
노 4
 
2.6%
Other values (58) 93
60.0%
ASCII
ValueCountFrequency (%)
7
22.6%
) 3
9.7%
( 3
9.7%
2 2
 
6.5%
& 2
 
6.5%
C 2
 
6.5%
B 2
 
6.5%
8 1
 
3.2%
0 1
 
3.2%
M 1
 
3.2%
Other values (7) 7
22.6%

공장부지면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7112.7955
Minimum0
Maximum26441.9
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T23:20:05.277296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1673.095
Q13307.575
median5132.25
Q38832.9
95-th percentile22571.05
Maximum26441.9
Range26441.9
Interquartile range (IQR)5525.325

Descriptive statistics

Standard deviation6563.7278
Coefficient of variation (CV)0.92280565
Kurtosis3.7741283
Mean7112.7955
Median Absolute Deviation (MAD)2247.15
Skewness1.9452601
Sum156481.5
Variance43082523
MonotonicityNot monotonic
2024-01-28T23:20:05.367706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
9177.2 1
 
4.5%
2054.9 1
 
4.5%
4985.5 1
 
4.5%
6110.1 1
 
4.5%
3312.3 1
 
4.5%
3332.7 1
 
4.5%
3306.0 1
 
4.5%
4709.5 1
 
4.5%
0.0 1
 
4.5%
23146.9 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
0.0 1
4.5%
1653.0 1
4.5%
2054.9 1
4.5%
2170.0 1
4.5%
3305.7 1
4.5%
3306.0 1
4.5%
3312.3 1
4.5%
3332.7 1
4.5%
3566.7 1
4.5%
4709.5 1
4.5%
ValueCountFrequency (%)
26441.9 1
4.5%
23146.9 1
4.5%
11629.9 1
4.5%
11428.0 1
4.5%
10694.2 1
4.5%
9177.2 1
4.5%
7800.0 1
4.5%
6611.0 1
4.5%
6110.1 1
4.5%
5767.0 1
4.5%

제조시설면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25931.373
Minimum1847.7932
Maximum126462.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T23:20:05.461917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1847.7932
5-th percentile4292.1425
Q16897.75
median14596.535
Q327571.05
95-th percentile110224.39
Maximum126462.56
Range124614.77
Interquartile range (IQR)20673.3

Descriptive statistics

Standard deviation32651.133
Coefficient of variation (CV)1.2591363
Kurtosis5.6137314
Mean25931.373
Median Absolute Deviation (MAD)10178.46
Skewness2.4362848
Sum570490.21
Variance1.0660965 × 109
MonotonicityNot monotonic
2024-01-28T23:20:05.557479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
25319.29 1
 
4.5%
1847.7932 1
 
4.5%
32234.06 1
 
4.5%
45625.92 1
 
4.5%
11766.68 1
 
4.5%
5137.4 1
 
4.5%
9310.04 1
 
4.5%
25889.701 1
 
4.5%
33151.28 1
 
4.5%
113624.31 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1847.7932 1
4.5%
4278.15 1
4.5%
4558.0 1
4.5%
5137.4 1
4.5%
6416.0 1
4.5%
6558.0 1
4.5%
7917.0 1
4.5%
8182.414 1
4.5%
9310.04 1
4.5%
11766.68 1
4.5%
ValueCountFrequency (%)
126462.56 1
4.5%
113624.31 1
4.5%
45625.92 1
4.5%
33151.28 1
4.5%
32234.06 1
4.5%
28131.5 1
4.5%
25889.701 1
4.5%
25319.29 1
4.5%
24933.0 1
4.5%
19954.04 1
4.5%

부대시설면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7655.8555
Minimum0
Maximum44520.97
Zeros2
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T23:20:05.654769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.542
Q1500.16875
median3249.46
Q38250.3718
95-th percentile26554.505
Maximum44520.97
Range44520.97
Interquartile range (IQR)7750.203

Descriptive statistics

Standard deviation11245.893
Coefficient of variation (CV)1.4689271
Kurtosis4.7662579
Mean7655.8555
Median Absolute Deviation (MAD)2880.485
Skewness2.1550886
Sum168428.82
Variance1.2647012 × 108
MonotonicityNot monotonic
2024-01-28T23:20:05.760209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 2
 
9.1%
44520.97 1
 
4.5%
26692.69 1
 
4.5%
4299.65 1
 
4.5%
619.19 1
 
4.5%
2763.92 1
 
4.5%
4068.9 1
 
4.5%
4874.97 1
 
4.5%
8914.579 1
 
4.5%
6257.75 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
0.0 2
9.1%
310.84 1
4.5%
342.95 1
4.5%
395.0 1
4.5%
460.495 1
4.5%
619.19 1
4.5%
858.0 1
4.5%
2143.15 1
4.5%
2740.24 1
4.5%
2763.92 1
4.5%
ValueCountFrequency (%)
44520.97 1
4.5%
26692.69 1
4.5%
23928.99 1
4.5%
15499.28 1
4.5%
15002.257 1
4.5%
8914.579 1
4.5%
6257.75 1
4.5%
4874.97 1
4.5%
4299.65 1
4.5%
4068.9 1
4.5%

건축물동수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
1
20 
5
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)9.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 20
90.9%
5 1
 
4.5%
2 1
 
4.5%

Length

2024-01-28T23:20:05.866887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T23:20:06.246335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 20
90.9%
5 1
 
4.5%
2 1
 
4.5%

건축물 층수
Text

Distinct13
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T23:20:06.386091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length10.090909
Min length4

Characters and Unicode

Total characters222
Distinct characters27
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)36.4%

Sample

1st row지상14층, 지하1층
2nd row지상5층, 지하1층
3rd row지상4층, 지하1층
4th row지상4층, 지하1층
5th row지상4층
ValueCountFrequency (%)
지상4층 7
16.7%
지하1층 7
16.7%
지상8층,지하1층 3
 
7.1%
지하2층 2
 
4.8%
지상8층 2
 
4.8%
지상15층 2
 
4.8%
3층 2
 
4.8%
지상10층,지하1층 2
 
4.8%
지상14층 2
 
4.8%
지상7층 1
 
2.4%
Other values (12) 12
28.6%
2024-01-28T23:20:06.643744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
층 42
18.9%
지 37
16.7%
상 22
9.9%
1 20
9.0%
20
9.0%
, 19
8.6%
하 15
 
6.8%
4 10
 
4.5%
동 7
 
3.2%
8 5
 
2.3%
Other values (17) 25
11.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128
57.7%
Decimal Number 48
 
21.6%
Other Punctuation 21
 
9.5%
Space Separator 20
 
9.0%
Uppercase Letter 5
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 42
32.8%
지 37
28.9%
상 22
17.2%
하 15
 
11.7%
동 7
 
5.5%
사 1
 
0.8%
공 1
 
0.8%
숙 1
 
0.8%
기 1
 
0.8%
장 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 20
41.7%
4 10
20.8%
8 5
 
10.4%
2 3
 
6.2%
3 3
 
6.2%
5 3
 
6.2%
0 2
 
4.2%
7 1
 
2.1%
6 1
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
20.0%
E 1
20.0%
D 1
20.0%
C 1
20.0%
B 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 19
90.5%
: 2
 
9.5%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 128
57.7%
Common 89
40.1%
Latin 5
 
2.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
22.5%
20
22.5%
, 19
21.3%
4 10
11.2%
8 5
 
5.6%
2 3
 
3.4%
3 3
 
3.4%
5 3
 
3.4%
0 2
 
2.2%
: 2
 
2.2%
Other values (2) 2
 
2.2%
Hangul
ValueCountFrequency (%)
층 42
32.8%
지 37
28.9%
상 22
17.2%
하 15
 
11.7%
동 7
 
5.5%
사 1
 
0.8%
공 1
 
0.8%
숙 1
 
0.8%
기 1
 
0.8%
장 1
 
0.8%
Latin
ValueCountFrequency (%)
A 1
20.0%
E 1
20.0%
D 1
20.0%
C 1
20.0%
B 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 128
57.7%
ASCII 94
42.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
층 42
32.8%
지 37
28.9%
상 22
17.2%
하 15
 
11.7%
동 7
 
5.5%
사 1
 
0.8%
공 1
 
0.8%
숙 1
 
0.8%
기 1
 
0.8%
장 1
 
0.8%
ASCII
ValueCountFrequency (%)
1 20
21.3%
20
21.3%
, 19
20.2%
4 10
10.6%
8 5
 
5.3%
2 3
 
3.2%
3 3
 
3.2%
5 3
 
3.2%
0 2
 
2.1%
: 2
 
2.1%
Other values (7) 7
 
7.4%

호실수(산업_지원)
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T23:20:06.824972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.4090909
Min length6

Characters and Unicode

Total characters207
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row435(200/235)
2nd row22(21/1)
3rd row20(20/0)
4th row52(46/6)
5th row18(18/0)
ValueCountFrequency (%)
435(200/235 1
 
4.5%
22(21/1 1
 
4.5%
225(219/6 1
 
4.5%
78(68/10 1
 
4.5%
44(44/0 1
 
4.5%
29(23/6 1
 
4.5%
281(157/124 1
 
4.5%
129(110/19 1
 
4.5%
416(216/200 1
 
4.5%
941(520/421 1
 
4.5%
Other values (12) 12
54.5%
2024-01-28T23:20:07.118414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 29
14.0%
2 28
13.5%
( 22
10.6%
/ 22
10.6%
) 22
10.6%
0 16
7.7%
4 14
6.8%
6 12
5.8%
3 11
 
5.3%
8 11
 
5.3%
Other values (3) 20
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 141
68.1%
Open Punctuation 22
 
10.6%
Other Punctuation 22
 
10.6%
Close Punctuation 22
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 29
20.6%
2 28
19.9%
0 16
11.3%
4 14
9.9%
6 12
8.5%
3 11
 
7.8%
8 11
 
7.8%
5 9
 
6.4%
9 6
 
4.3%
7 5
 
3.5%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 207
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 29
14.0%
2 28
13.5%
( 22
10.6%
/ 22
10.6%
) 22
10.6%
0 16
7.7%
4 14
6.8%
6 12
5.8%
3 11
 
5.3%
8 11
 
5.3%
Other values (3) 20
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 207
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 29
14.0%
2 28
13.5%
( 22
10.6%
/ 22
10.6%
) 22
10.6%
0 16
7.7%
4 14
6.8%
6 12
5.8%
3 11
 
5.3%
8 11
 
5.3%
Other values (3) 20
9.7%

설립승인일
Date

Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum1994-11-05 00:00:00
Maximum2020-07-01 00:00:00
2024-01-28T23:20:07.221785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:07.319700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

공장등록일
Date

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2000-06-21 00:00:00
Maximum2020-09-28 00:00:00
2024-01-28T23:20:07.424222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:07.522652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

준공일
Date

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum1976-09-13 00:00:00
Maximum2020-07-23 00:00:00
2024-01-28T23:20:07.617829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:07.705660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

공장대표주소(도로명)
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T23:20:07.890749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length30
Mean length26.181818
Min length16

Characters and Unicode

Total characters576
Distinct characters80
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

Unique22 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 가석로 30 (가좌동)
2nd row인천광역시 서구 중봉대로198번길 27 (가좌동)
3rd row인천광역시 서구 중봉대로240번길 24 (석남동)
4th row인천광역시 서구 백범로934번길 15 (가좌동, 대덕테크노타운)
5th row인천광역시 서구 가정로37번길 33 (가좌동, 가좌I.C APT형 공장)
ValueCountFrequency (%)
서구 22
18.5%
인천광역시 21
17.6%
가좌동 15
 
12.6%
가좌로 3
 
2.5%
백범로 3
 
2.5%
가정로37번길 2
 
1.7%
29번길 2
 
1.7%
14 2
 
1.7%
오류동 2
 
1.7%
4 2
 
1.7%
Other values (44) 45
37.8%
2024-01-28T23:20:08.191286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
98
 
17.0%
가 27
 
4.7%
인 22
 
3.8%
광 22
 
3.8%
서 22
 
3.8%
구 22
 
3.8%
로 22
 
3.8%
천 22
 
3.8%
역 21
 
3.6%
시 21
 
3.6%
Other values (70) 277
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 349
60.6%
Space Separator 98
 
17.0%
Decimal Number 75
 
13.0%
Open Punctuation 20
 
3.5%
Close Punctuation 20
 
3.5%
Other Punctuation 9
 
1.6%
Uppercase Letter 5
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 27
 
7.7%
인 22
 
6.3%
광 22
 
6.3%
서 22
 
6.3%
구 22
 
6.3%
로 22
 
6.3%
천 22
 
6.3%
역 21
 
6.0%
시 21
 
6.0%
좌 19
 
5.4%
Other values (50) 129
37.0%
Decimal Number
ValueCountFrequency (%)
1 18
24.0%
4 10
13.3%
2 9
12.0%
3 8
10.7%
6 6
 
8.0%
9 6
 
8.0%
8 5
 
6.7%
7 5
 
6.7%
5 4
 
5.3%
0 4
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
I 1
20.0%
C 1
20.0%
A 1
20.0%
P 1
20.0%
T 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
. 1
 
11.1%
Space Separator
ValueCountFrequency (%)
98
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 349
60.6%
Common 222
38.5%
Latin 5
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 27
 
7.7%
인 22
 
6.3%
광 22
 
6.3%
서 22
 
6.3%
구 22
 
6.3%
로 22
 
6.3%
천 22
 
6.3%
역 21
 
6.0%
시 21
 
6.0%
좌 19
 
5.4%
Other values (50) 129
37.0%
Common
ValueCountFrequency (%)
98
44.1%
( 20
 
9.0%
) 20
 
9.0%
1 18
 
8.1%
4 10
 
4.5%
2 9
 
4.1%
3 8
 
3.6%
, 8
 
3.6%
6 6
 
2.7%
9 6
 
2.7%
Other values (5) 19
 
8.6%
Latin
ValueCountFrequency (%)
I 1
20.0%
C 1
20.0%
A 1
20.0%
P 1
20.0%
T 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 349
60.6%
ASCII 227
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
98
43.2%
( 20
 
8.8%
) 20
 
8.8%
1 18
 
7.9%
4 10
 
4.4%
2 9
 
4.0%
3 8
 
3.5%
, 8
 
3.5%
6 6
 
2.6%
9 6
 
2.6%
Other values (10) 24
 
10.6%
Hangul
ValueCountFrequency (%)
가 27
 
7.7%
인 22
 
6.3%
광 22
 
6.3%
서 22
 
6.3%
구 22
 
6.3%
로 22
 
6.3%
천 22
 
6.3%
역 21
 
6.0%
시 21
 
6.0%
좌 19
 
5.4%
Other values (50) 129
37.0%

공장대표주소(지번)
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T23:20:08.342710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length12.636364
Min length10

Characters and Unicode

Total characters278
Distinct characters21
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

Unique22 ?
Unique (%)100.0%

Sample

1st row서구 가좌동 274-1
2nd row서구 가좌동 602-33
3rd row서구 석남동 650-63
4th row서구 가좌동 178-164
5th row서구 가좌동 585-20
ValueCountFrequency (%)
서구 22
33.8%
가좌동 18
27.7%
오류동 2
 
3.1%
524-11 1
 
1.5%
530-3 1
 
1.5%
539-16 1
 
1.5%
539-15 1
 
1.5%
524-8 1
 
1.5%
541-1 1
 
1.5%
1610-1 1
 
1.5%
Other values (16) 16
24.6%
2024-01-28T23:20:08.609660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43
15.5%
1 23
 
8.3%
동 22
 
7.9%
구 22
 
7.9%
서 22
 
7.9%
- 21
 
7.6%
좌 18
 
6.5%
가 18
 
6.5%
5 16
 
5.8%
2 11
 
4.0%
Other values (11) 62
22.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 110
39.6%
Decimal Number 104
37.4%
Space Separator 43
 
15.5%
Dash Punctuation 21
 
7.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
22.1%
5 16
15.4%
2 11
10.6%
6 11
10.6%
3 10
9.6%
4 9
 
8.7%
8 9
 
8.7%
0 7
 
6.7%
7 6
 
5.8%
9 2
 
1.9%
Other Letter
ValueCountFrequency (%)
동 22
20.0%
구 22
20.0%
서 22
20.0%
좌 18
16.4%
가 18
16.4%
석 2
 
1.8%
남 2
 
1.8%
오 2
 
1.8%
류 2
 
1.8%
Space Separator
ValueCountFrequency (%)
43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 168
60.4%
Hangul 110
39.6%

Most frequent character per script

Common
ValueCountFrequency (%)
43
25.6%
1 23
13.7%
- 21
12.5%
5 16
 
9.5%
2 11
 
6.5%
6 11
 
6.5%
3 10
 
6.0%
4 9
 
5.4%
8 9
 
5.4%
0 7
 
4.2%
Other values (2) 8
 
4.8%
Hangul
ValueCountFrequency (%)
동 22
20.0%
구 22
20.0%
서 22
20.0%
좌 18
16.4%
가 18
16.4%
석 2
 
1.8%
남 2
 
1.8%
오 2
 
1.8%
류 2
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 168
60.4%
Hangul 110
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43
25.6%
1 23
13.7%
- 21
12.5%
5 16
 
9.5%
2 11
 
6.5%
6 11
 
6.5%
3 10
 
6.0%
4 9
 
5.4%
8 9
 
5.4%
0 7
 
4.2%
Other values (2) 8
 
4.8%
Hangul
ValueCountFrequency (%)
동 22
20.0%
구 22
20.0%
서 22
20.0%
좌 18
16.4%
가 18
16.4%
석 2
 
1.8%
남 2
 
1.8%
오 2
 
1.8%
류 2
 
1.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2023-07-10 00:00:00
Maximum2023-07-10 00:00:00
2024-01-28T23:20:08.723547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:08.803544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T23:20:04.059526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.219414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.497330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.770921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:04.122480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.275295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.568527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.838497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:04.190712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.340503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.637960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.906533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:04.258491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.414589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.704671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:20:03.989166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T23:20:08.872927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번지식산업센터명공장부지면적제조시설면적부대시설면적건축물동수건축물 층수호실수(산업_지원)설립승인일공장등록일준공일공장대표주소(도로명)공장대표주소(지번)
순번1.0001.0000.6040.0000.4600.4850.6461.0000.8790.9751.0001.0001.000
지식산업센터명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
공장부지면적0.6041.0001.0000.7780.6970.7470.7311.0000.9120.9391.0001.0001.000
제조시설면적0.0001.0000.7781.0000.6940.8960.8021.0000.9930.9601.0001.0001.000
부대시설면적0.4601.0000.6970.6941.0000.3820.8901.0001.0001.0001.0001.0001.000
건축물동수0.4851.0000.7470.8960.3821.0001.0001.0001.0001.0001.0001.0001.000
건축물 층수0.6461.0000.7310.8020.8901.0001.0001.0000.8860.8581.0001.0001.000
호실수(산업_지원)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설립승인일0.8791.0000.9120.9931.0001.0000.8861.0001.0001.0001.0001.0001.000
공장등록일0.9751.0000.9390.9601.0001.0000.8581.0001.0001.0001.0001.0001.000
준공일1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
공장대표주소(도로명)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
공장대표주소(지번)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-01-28T23:20:08.995916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번공장부지면적제조시설면적부대시설면적건축물동수
순번1.000-0.0220.4010.1130.227
공장부지면적-0.0221.0000.5830.1750.595
제조시설면적0.4010.5831.0000.5620.561
부대시설면적0.1130.1750.5621.0000.115
건축물동수0.2270.5950.5610.1151.000

Missing values

2024-01-28T23:20:04.353366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T23:20:04.502889image/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

순번지식산업센터명공장부지면적제조시설면적부대시설면적건축물동수건축물 층수호실수(산업_지원)설립승인일공장등록일준공일공장대표주소(도로명)공장대표주소(지번)데이터기준일
01광양프런티어밸리 3차9177.225319.2944520.971지상14층, 지하1층435(200/235)2017-09-082019-11-082019-09-19인천광역시 서구 가석로 30 (가좌동)서구 가좌동 274-12023-07-10
12인천PCB협동화사업장2170.06416.0858.01지상5층, 지하1층22(21/1)2001-03-102001-03-101995-08-21인천광역시 서구 중봉대로198번길 27 (가좌동)서구 가좌동 602-332023-07-10
23금하산업1653.04558.0395.01지상4층, 지하1층20(20/0)2001-03-102001-03-101995-12-22인천광역시 서구 중봉대로240번길 24 (석남동)서구 석남동 650-632023-07-10
34대덕테크노타운5279.06558.02143.151지상4층, 지하1층52(46/6)2001-03-102001-11-021987-12-29인천광역시 서구 백범로934번길 15 (가좌동, 대덕테크노타운)서구 가좌동 178-1642023-07-10
45가좌IC지식산업센터3566.74278.15342.951지상4층18(18/0)2010-06-032011-04-192010-12-16인천광역시 서구 가정로37번길 33 (가좌동, 가좌I.C APT형 공장)서구 가좌동 585-202023-07-10
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