Overview

Dataset statistics

Number of variables9
Number of observations297
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.8 KiB
Average record size in memory78.4 B

Variable types

Numeric6
Text3

Dataset

Description대전광역시 제조업체(공장) 현황에 대한 데이터로 업체명, 주생산품, 입주계약일, 용지면적,제조시설, 부대시설, 인원수 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15029058/fileData.do

Alerts

용지면적 is highly overall correlated with 제조시설 and 1 other fieldsHigh correlation
제조시설 is highly overall correlated with 용지면적 and 1 other fieldsHigh correlation
부대시설 is highly overall correlated with 용지면적 and 1 other fieldsHigh correlation
남 is highly overall correlated with 여High correlation
여 is highly overall correlated with 남High correlation
순번 has unique valuesUnique
용지면적 has 16 (5.4%) zerosZeros
제조시설 has 8 (2.7%) zerosZeros
부대시설 has 40 (13.5%) zerosZeros
남 has 205 (69.0%) zerosZeros
여 has 224 (75.4%) zerosZeros

Reproduction

Analysis started2023-12-12 11:45:46.715029
Analysis finished2023-12-12 11:45:51.973729
Duration5.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct297
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean149
Minimum1
Maximum297
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-12T20:45:52.057213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.8
Q175
median149
Q3223
95-th percentile282.2
Maximum297
Range296
Interquartile range (IQR)148

Descriptive statistics

Standard deviation85.880731
Coefficient of variation (CV)0.57638075
Kurtosis-1.2
Mean149
Median Absolute Deviation (MAD)74
Skewness0
Sum44253
Variance7375.5
MonotonicityStrictly increasing
2023-12-12T20:45:52.223881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
205 1
 
0.3%
203 1
 
0.3%
202 1
 
0.3%
201 1
 
0.3%
200 1
 
0.3%
199 1
 
0.3%
198 1
 
0.3%
197 1
 
0.3%
196 1
 
0.3%
Other values (287) 287
96.6%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
297 1
0.3%
296 1
0.3%
295 1
0.3%
294 1
0.3%
293 1
0.3%
292 1
0.3%
291 1
0.3%
290 1
0.3%
289 1
0.3%
288 1
0.3%

업체명
Text

Distinct294
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T20:45:52.526911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length6.6329966
Min length2

Characters and Unicode

Total characters1970
Distinct characters313
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique292 ?
Unique (%)98.3%

Sample

1st row(재)서울의과학연구소
2nd row(주)남산산업
3rd row(주)네오시스
4th row(주)누리텍
5th row(주)누림소프트
ValueCountFrequency (%)
주식회사 5
 
1.6%
세원유공압주식회사 3
 
0.9%
주)이우아이엔씨 2
 
0.6%
유한책임회사 2
 
0.6%
2공장 2
 
0.6%
주)테크노블루 2
 
0.6%
제이제이엔에스 1
 
0.3%
이수테크 1
 
0.3%
은하수상사 1
 
0.3%
윤민애 1
 
0.3%
Other values (298) 298
93.7%
2023-12-12T20:45:53.387288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 133
 
6.8%
( 130
 
6.6%
) 130
 
6.6%
이 103
 
5.2%
스 69
 
3.5%
에 45
 
2.3%
지 31
 
1.6%
아 31
 
1.6%
엔 29
 
1.5%
트 29
 
1.5%
Other values (303) 1240
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1647
83.6%
Open Punctuation 130
 
6.6%
Close Punctuation 130
 
6.6%
Uppercase Letter 24
 
1.2%
Space Separator 23
 
1.2%
Decimal Number 16
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 133
 
8.1%
이 103
 
6.3%
스 69
 
4.2%
에 45
 
2.7%
지 31
 
1.9%
아 31
 
1.9%
엔 29
 
1.8%
트 29
 
1.8%
크 28
 
1.7%
테 26
 
1.6%
Other values (278) 1123
68.2%
Uppercase Letter
ValueCountFrequency (%)
N 2
 
8.3%
C 2
 
8.3%
I 2
 
8.3%
T 2
 
8.3%
E 2
 
8.3%
H 2
 
8.3%
L 2
 
8.3%
P 2
 
8.3%
O 1
 
4.2%
F 1
 
4.2%
Other values (6) 6
25.0%
Decimal Number
ValueCountFrequency (%)
2 7
43.8%
0 4
25.0%
1 2
 
12.5%
3 1
 
6.2%
8 1
 
6.2%
4 1
 
6.2%
Open Punctuation
ValueCountFrequency (%)
( 130
100.0%
Close Punctuation
ValueCountFrequency (%)
) 130
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1647
83.6%
Common 299
 
15.2%
Latin 24
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 133
 
8.1%
이 103
 
6.3%
스 69
 
4.2%
에 45
 
2.7%
지 31
 
1.9%
아 31
 
1.9%
엔 29
 
1.8%
트 29
 
1.8%
크 28
 
1.7%
테 26
 
1.6%
Other values (278) 1123
68.2%
Latin
ValueCountFrequency (%)
N 2
 
8.3%
C 2
 
8.3%
I 2
 
8.3%
T 2
 
8.3%
E 2
 
8.3%
H 2
 
8.3%
L 2
 
8.3%
P 2
 
8.3%
O 1
 
4.2%
F 1
 
4.2%
Other values (6) 6
25.0%
Common
ValueCountFrequency (%)
( 130
43.5%
) 130
43.5%
23
 
7.7%
2 7
 
2.3%
0 4
 
1.3%
1 2
 
0.7%
3 1
 
0.3%
8 1
 
0.3%
4 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1647
83.6%
ASCII 323
 
16.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 133
 
8.1%
이 103
 
6.3%
스 69
 
4.2%
에 45
 
2.7%
지 31
 
1.9%
아 31
 
1.9%
엔 29
 
1.8%
트 29
 
1.8%
크 28
 
1.7%
테 26
 
1.6%
Other values (278) 1123
68.2%
ASCII
ValueCountFrequency (%)
( 130
40.2%
) 130
40.2%
23
 
7.1%
2 7
 
2.2%
0 4
 
1.2%
N 2
 
0.6%
C 2
 
0.6%
I 2
 
0.6%
T 2
 
0.6%
E 2
 
0.6%
Other values (15) 19
 
5.9%

업종
Text

Distinct138
Distinct (%)46.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T20:45:53.836881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length44
Mean length25.195286
Min length14

Characters and Unicode

Total characters7483
Distinct characters231
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)30.3%

Sample

1st row의학 및 약학 연구개발업 (70113)
2nd row구조용 금속 판제품 및 공작물 제조업 (25112)
3rd row물질 검사, 측정 및 분석기구 제조업 (27213)
4th row기타 정보기술 및 컴퓨터운영 관련 서비스업 (62090)
5th row응용 소프트웨어 개발 및 공급업 (58222)
ValueCountFrequency (%)
제조업 153
 
8.9%
및 146
 
8.4%
외 67
 
3.9%
기타 63
 
3.6%
개발 34
 
2.0%
공급업 34
 
2.0%
소프트웨어 34
 
2.0%
그 32
 
1.9%
서비스업 32
 
1.9%
1종 22
 
1.3%
Other values (383) 1111
64.3%
2023-12-12T20:45:54.433409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1431
19.1%
2 514
 
6.9%
1 381
 
5.1%
업 312
 
4.2%
) 299
 
4.0%
( 299
 
4.0%
9 244
 
3.3%
제 221
 
3.0%
기 192
 
2.6%
조 169
 
2.3%
Other values (221) 3421
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3522
47.1%
Decimal Number 1821
24.3%
Space Separator 1431
19.1%
Close Punctuation 299
 
4.0%
Open Punctuation 299
 
4.0%
Other Punctuation 111
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 312
 
8.9%
제 221
 
6.3%
기 192
 
5.5%
조 169
 
4.8%
및 146
 
4.1%
외 69
 
2.0%
공 68
 
1.9%
어 67
 
1.9%
타 63
 
1.8%
전 63
 
1.8%
Other values (206) 2152
61.1%
Decimal Number
ValueCountFrequency (%)
2 514
28.2%
1 381
20.9%
9 244
13.4%
7 140
 
7.7%
0 138
 
7.6%
3 133
 
7.3%
5 95
 
5.2%
8 85
 
4.7%
4 50
 
2.7%
6 41
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 109
98.2%
. 2
 
1.8%
Space Separator
ValueCountFrequency (%)
1431
100.0%
Close Punctuation
ValueCountFrequency (%)
) 299
100.0%
Open Punctuation
ValueCountFrequency (%)
( 299
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3961
52.9%
Hangul 3522
47.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 312
 
8.9%
제 221
 
6.3%
기 192
 
5.5%
조 169
 
4.8%
및 146
 
4.1%
외 69
 
2.0%
공 68
 
1.9%
어 67
 
1.9%
타 63
 
1.8%
전 63
 
1.8%
Other values (206) 2152
61.1%
Common
ValueCountFrequency (%)
1431
36.1%
2 514
 
13.0%
1 381
 
9.6%
) 299
 
7.5%
( 299
 
7.5%
9 244
 
6.2%
7 140
 
3.5%
0 138
 
3.5%
3 133
 
3.4%
, 109
 
2.8%
Other values (5) 273
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3961
52.9%
Hangul 3518
47.0%
Compat Jamo 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1431
36.1%
2 514
 
13.0%
1 381
 
9.6%
) 299
 
7.5%
( 299
 
7.5%
9 244
 
6.2%
7 140
 
3.5%
0 138
 
3.5%
3 133
 
3.4%
, 109
 
2.8%
Other values (5) 273
 
6.9%
Hangul
ValueCountFrequency (%)
업 312
 
8.9%
제 221
 
6.3%
기 192
 
5.5%
조 169
 
4.8%
및 146
 
4.2%
외 69
 
2.0%
공 68
 
1.9%
어 67
 
1.9%
타 63
 
1.8%
전 63
 
1.8%
Other values (205) 2148
61.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 4
100.0%

주생산품
Text

Distinct286
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T20:45:54.766510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length25
Mean length11.885522
Min length2

Characters and Unicode

Total characters3530
Distinct characters379
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique275 ?
Unique (%)92.6%

Sample

1st row환자 검체 분석 등
2nd row창호
3rd row물질 분석 실험기기
4th row컴퓨터 장애복구 서비스
5th row통계DB관리 시스템
ValueCountFrequency (%)
및 34
 
4.1%
소프트웨어 22
 
2.7%
등 17
 
2.1%
디자인 15
 
1.8%
개발 10
 
1.2%
시스템 9
 
1.1%
서비스 8
 
1.0%
컨설팅 7
 
0.9%
관리 7
 
0.9%
제작 7
 
0.9%
Other values (547) 687
83.5%
2023-12-12T20:45:55.277888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
526
 
14.9%
, 116
 
3.3%
기 114
 
3.2%
자 75
 
2.1%
스 57
 
1.6%
장 54
 
1.5%
관 53
 
1.5%
전 53
 
1.5%
어 52
 
1.5%
리 48
 
1.4%
Other values (369) 2382
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2760
78.2%
Space Separator 526
 
14.9%
Other Punctuation 120
 
3.4%
Uppercase Letter 66
 
1.9%
Open Punctuation 21
 
0.6%
Close Punctuation 20
 
0.6%
Lowercase Letter 9
 
0.3%
Decimal Number 6
 
0.2%
Connector Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 114
 
4.1%
자 75
 
2.7%
스 57
 
2.1%
장 54
 
2.0%
관 53
 
1.9%
전 53
 
1.9%
어 52
 
1.9%
리 48
 
1.7%
제 45
 
1.6%
인 43
 
1.6%
Other values (334) 2166
78.5%
Uppercase Letter
ValueCountFrequency (%)
D 10
15.2%
S 8
12.1%
P 8
12.1%
C 6
9.1%
L 5
7.6%
R 5
7.6%
E 5
7.6%
U 4
 
6.1%
T 4
 
6.1%
V 4
 
6.1%
Other values (4) 7
10.6%
Lowercase Letter
ValueCountFrequency (%)
l 2
22.2%
c 2
22.2%
n 1
11.1%
o 1
11.1%
f 1
11.1%
e 1
11.1%
m 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 116
96.7%
& 1
 
0.8%
. 1
 
0.8%
" 1
 
0.8%
/ 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
3 3
50.0%
6 1
 
16.7%
1 1
 
16.7%
2 1
 
16.7%
Space Separator
ValueCountFrequency (%)
526
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2760
78.2%
Common 695
 
19.7%
Latin 75
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 114
 
4.1%
자 75
 
2.7%
스 57
 
2.1%
장 54
 
2.0%
관 53
 
1.9%
전 53
 
1.9%
어 52
 
1.9%
리 48
 
1.7%
제 45
 
1.6%
인 43
 
1.6%
Other values (334) 2166
78.5%
Latin
ValueCountFrequency (%)
D 10
13.3%
S 8
10.7%
P 8
10.7%
C 6
 
8.0%
L 5
 
6.7%
R 5
 
6.7%
E 5
 
6.7%
U 4
 
5.3%
T 4
 
5.3%
V 4
 
5.3%
Other values (11) 16
21.3%
Common
ValueCountFrequency (%)
526
75.7%
, 116
 
16.7%
( 21
 
3.0%
) 20
 
2.9%
3 3
 
0.4%
6 1
 
0.1%
1 1
 
0.1%
& 1
 
0.1%
. 1
 
0.1%
2 1
 
0.1%
Other values (4) 4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2760
78.2%
ASCII 770
 
21.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
526
68.3%
, 116
 
15.1%
( 21
 
2.7%
) 20
 
2.6%
D 10
 
1.3%
S 8
 
1.0%
P 8
 
1.0%
C 6
 
0.8%
L 5
 
0.6%
R 5
 
0.6%
Other values (25) 45
 
5.8%
Hangul
ValueCountFrequency (%)
기 114
 
4.1%
자 75
 
2.7%
스 57
 
2.1%
장 54
 
2.0%
관 53
 
1.9%
전 53
 
1.9%
어 52
 
1.9%
리 48
 
1.7%
제 45
 
1.6%
인 43
 
1.6%
Other values (334) 2166
78.5%

용지면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct162
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean278.99164
Minimum0
Maximum6820.4
Zeros16
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-12T20:45:55.448424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123.01
median29.06
Q370.85
95-th percentile1811.8
Maximum6820.4
Range6820.4
Interquartile range (IQR)47.84

Descriptive statistics

Standard deviation839.33757
Coefficient of variation (CV)3.0084686
Kurtosis29.538843
Mean278.99164
Median Absolute Deviation (MAD)14.76
Skewness5.0057932
Sum82860.517
Variance704487.56
MonotonicityNot monotonic
2023-12-12T20:45:55.621281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.19 24
 
8.1%
0.0 16
 
5.4%
23.52 14
 
4.7%
23.01 9
 
3.0%
12.74 7
 
2.4%
27.36 7
 
2.4%
23.4 6
 
2.0%
32.65 6
 
2.0%
43.64 5
 
1.7%
47.04 5
 
1.7%
Other values (152) 198
66.7%
ValueCountFrequency (%)
0.0 16
5.4%
6.8 1
 
0.3%
9.0 1
 
0.3%
9.81 1
 
0.3%
10.0 1
 
0.3%
11.175 1
 
0.3%
11.51 1
 
0.3%
12.0 1
 
0.3%
12.74 7
2.4%
13.0 1
 
0.3%
ValueCountFrequency (%)
6820.4 1
 
0.3%
6129.5 2
0.7%
3727.0 1
 
0.3%
3373.0 1
 
0.3%
3312.5 1
 
0.3%
3283.0 1
 
0.3%
2548.1 1
 
0.3%
2314.3 1
 
0.3%
1984.1 1
 
0.3%
1900.0 3
1.0%

제조시설
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct165
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.04746
Minimum0
Maximum6986.4
Zeros8
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-12T20:45:55.773024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile32.726
Q175.6
median89.88
Q3185.22
95-th percentile1050.602
Maximum6986.4
Range6986.4
Interquartile range (IQR)109.62

Descriptive statistics

Standard deviation659.89338
Coefficient of variation (CV)2.6496691
Kurtosis75.899941
Mean249.04746
Median Absolute Deviation (MAD)43.41
Skewness8.0790289
Sum73967.097
Variance435459.28
MonotonicityNot monotonic
2023-12-12T20:45:55.994183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82.74 26
 
8.8%
77.28 14
 
4.7%
75.6 9
 
3.0%
0.0 8
 
2.7%
89.88 7
 
2.4%
41.86 7
 
2.4%
105.84 6
 
2.0%
76.86 6
 
2.0%
143.37 5
 
1.7%
154.56 5
 
1.7%
Other values (155) 204
68.7%
ValueCountFrequency (%)
0.0 8
2.7%
20.0 1
 
0.3%
22.05 1
 
0.3%
24.0 1
 
0.3%
27.0 1
 
0.3%
28.05 1
 
0.3%
28.98 1
 
0.3%
31.63 1
 
0.3%
33.0 3
 
1.0%
36.225 1
 
0.3%
ValueCountFrequency (%)
6986.4 2
0.7%
4000.0 1
 
0.3%
1639.02 3
1.0%
1498.24 1
 
0.3%
1357.49 1
 
0.3%
1350.3 1
 
0.3%
1294.31 1
 
0.3%
1196.01 1
 
0.3%
1168.66 1
 
0.3%
1155.54 1
 
0.3%

부대시설
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct139
Distinct (%)46.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.98386
Minimum0
Maximum3717.26
Zeros40
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-12T20:45:56.232199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q165
median82.49
Q3147.4
95-th percentile416.27
Maximum3717.26
Range3717.26
Interquartile range (IQR)82.4

Descriptive statistics

Standard deviation369.14887
Coefficient of variation (CV)2.1845215
Kurtosis49.644359
Mean168.98386
Median Absolute Deviation (MAD)40.76
Skewness6.5173677
Sum50188.205
Variance136270.89
MonotonicityNot monotonic
2023-12-12T20:45:56.474455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 40
 
13.5%
82.49 24
 
8.1%
77.04 14
 
4.7%
75.37 9
 
3.0%
41.73 7
 
2.4%
89.61 7
 
2.4%
76.62 6
 
2.0%
142.93 5
 
1.7%
154.08 5
 
1.7%
65.32 4
 
1.3%
Other values (129) 176
59.3%
ValueCountFrequency (%)
0.0 40
13.5%
8.35 1
 
0.3%
14.3 1
 
0.3%
16.575 1
 
0.3%
20.0 1
 
0.3%
30.0 2
 
0.7%
37.68 1
 
0.3%
39.13 1
 
0.3%
41.73 7
 
2.4%
42.57 1
 
0.3%
ValueCountFrequency (%)
3717.26 1
0.3%
3110.2 1
0.3%
2554.32 1
0.3%
1746.99 2
0.7%
1468.68 1
0.3%
1317.18 1
0.3%
1014.95 1
0.3%
803.13 1
0.3%
746.15 2
0.7%
554.81 1
0.3%

남
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.956229
Minimum0
Maximum106
Zeros205
Zeros (%)69.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-12T20:45:56.666540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile11
Maximum106
Range106
Interquartile range (IQR)1

Descriptive statistics

Standard deviation7.4802512
Coefficient of variation (CV)3.8238117
Kurtosis129.2556
Mean1.956229
Median Absolute Deviation (MAD)0
Skewness10.039911
Sum581
Variance55.954159
MonotonicityNot monotonic
2023-12-12T20:45:56.834087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 205
69.0%
1 26
 
8.8%
2 15
 
5.1%
3 14
 
4.7%
4 9
 
3.0%
6 5
 
1.7%
11 4
 
1.3%
5 4
 
1.3%
8 3
 
1.0%
15 3
 
1.0%
Other values (8) 9
 
3.0%
ValueCountFrequency (%)
0 205
69.0%
1 26
 
8.8%
2 15
 
5.1%
3 14
 
4.7%
4 9
 
3.0%
5 4
 
1.3%
6 5
 
1.7%
8 3
 
1.0%
11 4
 
1.3%
13 2
 
0.7%
ValueCountFrequency (%)
106 1
 
0.3%
36 1
 
0.3%
32 1
 
0.3%
25 1
 
0.3%
24 1
 
0.3%
19 1
 
0.3%
16 1
 
0.3%
15 3
1.0%
13 2
0.7%
11 4
1.3%

여
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.84175084
Minimum0
Maximum48
Zeros224
Zeros (%)75.4%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-12T20:45:56.975144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum48
Range48
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.5629296
Coefficient of variation (CV)4.2327603
Kurtosis113.27442
Mean0.84175084
Median Absolute Deviation (MAD)0
Skewness9.6447764
Sum250
Variance12.694467
MonotonicityNot monotonic
2023-12-12T20:45:57.145052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 224
75.4%
1 34
 
11.4%
2 21
 
7.1%
3 5
 
1.7%
5 3
 
1.0%
4 3
 
1.0%
10 2
 
0.7%
26 1
 
0.3%
14 1
 
0.3%
15 1
 
0.3%
Other values (2) 2
 
0.7%
ValueCountFrequency (%)
0 224
75.4%
1 34
 
11.4%
2 21
 
7.1%
3 5
 
1.7%
4 3
 
1.0%
5 3
 
1.0%
9 1
 
0.3%
10 2
 
0.7%
14 1
 
0.3%
15 1
 
0.3%
ValueCountFrequency (%)
48 1
 
0.3%
26 1
 
0.3%
15 1
 
0.3%
14 1
 
0.3%
10 2
 
0.7%
9 1
 
0.3%
5 3
 
1.0%
4 3
 
1.0%
3 5
 
1.7%
2 21
7.1%

Interactions

2023-12-12T20:45:51.003718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:47.338038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:48.013731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:48.777219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:49.575061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:50.365470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:51.099506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:47.428379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:48.116991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:48.918726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:49.717650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:50.468307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:51.214751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:47.542785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:48.252043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:49.059766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:49.871548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:50.595610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:51.329441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:47.676796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:48.357325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:49.182804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:50.007554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:50.718461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:51.447835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:47.808357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:48.505627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:49.302136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:50.134944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:50.818249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:51.567170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:47.916934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:48.656755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:49.429206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:50.247321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:50.905458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:45:57.242752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번용지면적제조시설부대시설남여
순번1.0000.2980.4470.1560.3250.134
용지면적0.2981.0000.8980.9750.6600.571
제조시설0.4470.8981.0000.8200.6310.268
부대시설0.1560.9750.8201.0000.6230.479
남0.3250.6600.6310.6231.0000.790
여0.1340.5710.2680.4790.7901.000
2023-12-12T20:45:57.355097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번용지면적제조시설부대시설남여
순번1.0000.1300.0970.0940.2450.259
용지면적0.1301.0000.7560.6200.2510.270
제조시설0.0970.7561.0000.5030.2230.202
부대시설0.0940.6200.5031.000-0.113-0.032
남0.2450.2510.223-0.1131.0000.827
여0.2590.2700.202-0.0320.8271.000

Missing values

2023-12-12T20:45:51.732014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:45:51.905845image/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

순번업체명업종주생산품용지면적제조시설부대시설남여
01(재)서울의과학연구소의학 및 약학 연구개발업 (70113)환자 검체 분석 등50.38165.48164.9800
12(주)남산산업구조용 금속 판제품 및 공작물 제조업 (25112)창호0.090.00.021
23(주)네오시스물질 검사, 측정 및 분석기구 제조업 (27213)물질 분석 실험기기11.17536.2250.000
34(주)누리텍기타 정보기술 및 컴퓨터운영 관련 서비스업 (62090)컴퓨터 장애복구 서비스25.1982.7482.4900
45(주)누림소프트응용 소프트웨어 개발 및 공급업 (58222)통계DB관리 시스템92.72304.09303.6700
56(주)다옴메디그 외 기타 의료용 기기 제조업 (27199)의료용 시멘트 혼합기13.644.10.010
67(주)대덕공조플랜트(2공장)그 외 기타 분류 안된 금속 가공 제품 제조업 (25999)알루미늄 프로파일 프레임21.470.2970.0720
78(주)더뷰나인반도체 제조용 기계 제조업 (29271)반도체용 검사장비 및 자동화 장비25.2982.7482.4900
89(주)데베트론코리아전자기 측정, 시험 및 분석기구 제조업 (27212)전원품질 분석기23.0175.675.3700
910(주)디엔에프신소재염료, 조제 무기안료, 유연제 및 기타 착색제 제조업 (20132)고기능성 코팅액1251.8961.65290.15153
순번업체명업종주생산품용지면적제조시설부대시설남여
287288(주)서지텍전자기 측정, 시험 및 분석기구 제조업 (27212)피뢰기 시험기0.020.020.032
288289(주)솔잎기술그 외 기타 분류 안된 화학제품 제조업 (20499)하드코팅용 코팅 수징0.0171.14287.7452
289290(주)와이파워원기타 전기 변환장치 제조업 외 1종 (28119, 28909)기타 전기변환장치, 무선전력전송기기0.052.530.0190
290291(주)트위니산업용 로봇 제조업 (29280)물류로봇0.074.8242.6310648
291292(주)플로우컴스반도체 제조용 기계 제조업 (29271)가스배관라인 및 케미칼 충진설비 외42.92224.089.1611
292293주식회사 더블유에스앤씨그 외 기타 전기장비 제조업 (28909)행거, 실외기 받침대3283.01498.241014.9511
293294주식회사 제이제이엔에스그 외 자동차용 신품 부품 제조업 외 1종 (30399, 72122)자동차용 신품 부품 제조업0.0365.1950.000
294295주식회사 지최일만응용 소프트웨어 개발 및 공급업 (58222)플랫폼 소프트웨어0.00.016.57533
295296페인트팜(주)일반용 도료 및 관련제품 제조업 외 3종 (20411, 26329, 27302, 75992)스크린페인트, 영사스크린, 멀티미디어학습장치, 전시대행0.080.00.044
296297한소 주식회사기체 여과기 제조업 외 2종 (29174, 28909, 70111)UV 공기살균청정기3727.076.632554.32369