Overview

Dataset statistics

Number of variables11
Number of observations472
Missing cells22
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.1 KiB
Average record size in memory91.3 B

Variable types

Text4
Categorical3
DateTime1
Numeric3

Dataset

Description논산시 지역업체 현황에 대한 데이터로 업체명, 업종코드, 업종코드명, 사업자구분, 설립일자, 행정구역, 소재지 도로명주소, 소재지 지번주소, 주요생산품 등의 정보를 제공하고 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=414&beforeMenuCd=DOM_000000201001001000&publicdatapk=15054240

Alerts

부지면적 is highly overall correlated with 건축면적 and 1 other fieldsHigh correlation
건축면적 is highly overall correlated with 부지면적 and 1 other fieldsHigh correlation
종업원수 is highly overall correlated with 부지면적 and 1 other fieldsHigh correlation
부지면적 has 22 (4.7%) missing valuesMissing
부지면적 is highly skewed (γ1 = 21.08639498)Skewed

Reproduction

Analysis started2024-01-09 20:27:01.141311
Analysis finished2024-01-09 20:27:02.762466
Duration1.62 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct459
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-01-10T05:27:02.939826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length5.1059322
Min length2

Characters and Unicode

Total characters2410
Distinct characters352
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

Unique446 ?
Unique (%)94.5%

Sample

1st rowKY식품
2nd row가야곡면떡방아간
3rd row가야촌
4th row강산식품
5th row건강마을
ValueCountFrequency (%)
명성케미칼 2
 
0.4%
세움스틸 2
 
0.4%
유피씨 2
 
0.4%
태호화학 2
 
0.4%
우림산업 2
 
0.4%
대호산업 2
 
0.4%
파트너가구 2
 
0.4%
서광그린엠 2
 
0.4%
시벨코코리아 2
 
0.4%
코캄 2
 
0.4%
Other values (449) 452
95.8%
2024-01-10T05:27:03.316081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 82
 
3.4%
업 77
 
3.2%
이 63
 
2.6%
스 60
 
2.5%
대 44
 
1.8%
리 43
 
1.8%
인 41
 
1.7%
성 37
 
1.5%
에 36
 
1.5%
농 35
 
1.5%
Other values (342) 1892
78.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2378
98.7%
Uppercase Letter 28
 
1.2%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 82
 
3.4%
업 77
 
3.2%
이 63
 
2.6%
스 60
 
2.5%
대 44
 
1.9%
리 43
 
1.8%
인 41
 
1.7%
성 37
 
1.6%
에 36
 
1.5%
농 35
 
1.5%
Other values (325) 1860
78.2%
Uppercase Letter
ValueCountFrequency (%)
C 4
14.3%
S 3
10.7%
N 3
10.7%
P 3
10.7%
K 2
 
7.1%
M 2
 
7.1%
D 2
 
7.1%
F 2
 
7.1%
E 1
 
3.6%
Y 1
 
3.6%
Other values (5) 5
17.9%
Other Punctuation
ValueCountFrequency (%)
& 3
75.0%
. 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2378
98.7%
Latin 28
 
1.2%
Common 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 82
 
3.4%
업 77
 
3.2%
이 63
 
2.6%
스 60
 
2.5%
대 44
 
1.9%
리 43
 
1.8%
인 41
 
1.7%
성 37
 
1.6%
에 36
 
1.5%
농 35
 
1.5%
Other values (325) 1860
78.2%
Latin
ValueCountFrequency (%)
C 4
14.3%
S 3
10.7%
N 3
10.7%
P 3
10.7%
K 2
 
7.1%
M 2
 
7.1%
D 2
 
7.1%
F 2
 
7.1%
E 1
 
3.6%
Y 1
 
3.6%
Other values (5) 5
17.9%
Common
ValueCountFrequency (%)
& 3
75.0%
. 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2378
98.7%
ASCII 32
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 82
 
3.4%
업 77
 
3.2%
이 63
 
2.6%
스 60
 
2.5%
대 44
 
1.9%
리 43
 
1.8%
인 41
 
1.7%
성 37
 
1.6%
에 36
 
1.5%
농 35
 
1.5%
Other values (325) 1860
78.2%
ASCII
ValueCountFrequency (%)
C 4
12.5%
S 3
9.4%
& 3
9.4%
N 3
9.4%
P 3
9.4%
K 2
 
6.2%
M 2
 
6.2%
D 2
 
6.2%
F 2
 
6.2%
E 1
 
3.1%
Other values (7) 7
21.9%

업종코드명
Categorical

Distinct22
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
식료품 제조업
119 
비금속 광물제품 제조업
59 
금속 가공제품 제조업
46 
섬유제품 제조업
40 
고무 및 플라스틱제품 제조업
38 
Other values (17)
170 

Length

Max length29
Median length17
Mean length10.989407
Min length6

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row식료품 제조업
2nd row식료품 제조업
3rd row식료품 제조업
4th row식료품 제조업
5th row식료품 제조업

Common Values

ValueCountFrequency (%)
식료품 제조업 119
25.2%
비금속 광물제품 제조업 59
12.5%
금속 가공제품 제조업 46
 
9.7%
섬유제품 제조업 40
 
8.5%
고무 및 플라스틱제품 제조업 38
 
8.1%
기타 기계 및 장비 제조업 36
 
7.6%
화학 물질 및 화학제품 제조업 20
 
4.2%
전기장비 제조업 15
 
3.2%
1차 금속 제조업 15
 
3.2%
가구 제조업 12
 
2.5%
Other values (12) 72
15.3%

Length

2024-01-10T05:27:03.460282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제조업 471
31.6%
및 146
 
9.8%
식료품 119
 
8.0%
금속 61
 
4.1%
비금속 59
 
4.0%
광물제품 59
 
4.0%
가공제품 46
 
3.1%
기타 44
 
3.0%
섬유제품 40
 
2.7%
고무 38
 
2.6%
Other values (41) 406
27.3%

사업자구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
법인
336 
개인
136 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row법인
2nd row개인
3rd row법인
4th row개인
5th row법인

Common Values

ValueCountFrequency (%)
법인 336
71.2%
개인 136
28.8%

Length

2024-01-10T05:27:03.565602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:27:03.641632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 336
71.2%
개인 136
28.8%

설립일자
Date

Distinct439
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1952-12-09 00:00:00
Maximum2017-08-30 00:00:00
2024-01-10T05:27:03.733818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:27:03.856260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

행정구역
Categorical

Distinct15
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
연무읍
85 
부적면
73 
연산면
68 
은진면
47 
가야곡면
43 
Other values (10)
156 

Length

Max length4
Median length3
Mean length3.0911017
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row부적면
2nd row가야곡면
3rd row노성면
4th row가야곡면
5th row연무읍

Common Values

ValueCountFrequency (%)
연무읍 85
18.0%
부적면 73
15.5%
연산면 68
14.4%
은진면 47
10.0%
가야곡면 43
9.1%
성동면 43
9.1%
광석면 24
 
5.1%
상월면 22
 
4.7%
노성면 16
 
3.4%
벌곡면 16
 
3.4%
Other values (5) 35
7.4%

Length

2024-01-10T05:27:03.975733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연무읍 85
18.0%
부적면 73
15.5%
연산면 68
14.4%
은진면 47
10.0%
가야곡면 43
9.1%
성동면 43
9.1%
광석면 24
 
5.1%
상월면 22
 
4.7%
노성면 16
 
3.4%
벌곡면 16
 
3.4%
Other values (5) 35
7.4%

소재지도로명주소
Text

Distinct421
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-01-10T05:27:04.173908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length22.358051
Min length15

Characters and Unicode

Total characters10553
Distinct characters127
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

Unique383 ?
Unique (%)81.1%

Sample

1st row충청남도 논산시 부적면 덕평길 72-9
2nd row충청남도 논산시 가야곡면 원앙로 629
3rd row충청남도 논산시 노성면 노성로 630-9
4th row충청남도 논산시 가야곡면 가야로22번길 9
5th row충청남도 논산시 연무읍 원안길 19
ValueCountFrequency (%)
충청남도 472
20.1%
논산시 472
20.1%
연무읍 85
 
3.6%
부적면 73
 
3.1%
연산면 68
 
2.9%
성동면 43
 
1.8%
가야곡면 43
 
1.8%
은진면 40
 
1.7%
계백로 29
 
1.2%
매죽헌로 26
 
1.1%
Other values (513) 993
42.4%
2024-01-10T05:27:04.513938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1872
17.7%
산 630
 
6.0%
논 486
 
4.6%
충 481
 
4.6%
남 475
 
4.5%
청 473
 
4.5%
도 472
 
4.5%
시 472
 
4.5%
1 389
 
3.7%
면 366
 
3.5%
Other values (117) 4437
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6585
62.4%
Decimal Number 1880
 
17.8%
Space Separator 1872
 
17.7%
Dash Punctuation 216
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 630
 
9.6%
논 486
 
7.4%
충 481
 
7.3%
남 475
 
7.2%
청 473
 
7.2%
도 472
 
7.2%
시 472
 
7.2%
면 366
 
5.6%
로 350
 
5.3%
길 235
 
3.6%
Other values (105) 2145
32.6%
Decimal Number
ValueCountFrequency (%)
1 389
20.7%
2 283
15.1%
3 239
12.7%
4 186
9.9%
5 166
8.8%
7 161
8.6%
0 125
 
6.6%
8 111
 
5.9%
6 111
 
5.9%
9 109
 
5.8%
Space Separator
ValueCountFrequency (%)
1872
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 216
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6585
62.4%
Common 3968
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 630
 
9.6%
논 486
 
7.4%
충 481
 
7.3%
남 475
 
7.2%
청 473
 
7.2%
도 472
 
7.2%
시 472
 
7.2%
면 366
 
5.6%
로 350
 
5.3%
길 235
 
3.6%
Other values (105) 2145
32.6%
Common
ValueCountFrequency (%)
1872
47.2%
1 389
 
9.8%
2 283
 
7.1%
3 239
 
6.0%
- 216
 
5.4%
4 186
 
4.7%
5 166
 
4.2%
7 161
 
4.1%
0 125
 
3.2%
8 111
 
2.8%
Other values (2) 220
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6585
62.4%
ASCII 3968
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1872
47.2%
1 389
 
9.8%
2 283
 
7.1%
3 239
 
6.0%
- 216
 
5.4%
4 186
 
4.7%
5 166
 
4.2%
7 161
 
4.1%
0 125
 
3.2%
8 111
 
2.8%
Other values (2) 220
 
5.5%
Hangul
ValueCountFrequency (%)
산 630
 
9.6%
논 486
 
7.4%
충 481
 
7.3%
남 475
 
7.2%
청 473
 
7.2%
도 472
 
7.2%
시 472
 
7.2%
면 366
 
5.6%
로 350
 
5.3%
길 235
 
3.6%
Other values (105) 2145
32.6%

주요생산품
Text

Distinct415
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-01-10T05:27:04.726646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length20
Mean length7.3622881
Min length1

Characters and Unicode

Total characters3475
Distinct characters411
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

Unique380 ?
Unique (%)80.5%

Sample

1st row생강차+천마차
2nd row떡류
3rd row육류 가공
4th row누룽지
5th row음료
ValueCountFrequency (%)
제조업 28
 
3.9%
및 27
 
3.8%
등 19
 
2.7%
플라스틱 13
 
1.8%
기타 13
 
1.8%
쌀 9
 
1.3%
석제품 9
 
1.3%
사료 9
 
1.3%
레미콘 7
 
1.0%
제품 7
 
1.0%
Other values (487) 573
80.3%
2024-01-10T05:27:05.051803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
252
 
7.3%
+ 169
 
4.9%
제 95
 
2.7%
기 77
 
2.2%
품 70
 
2.0%
조 64
 
1.8%
용 58
 
1.7%
가 54
 
1.6%
스 53
 
1.5%
장 48
 
1.4%
Other values (401) 2535
72.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2939
84.6%
Space Separator 252
 
7.3%
Math Symbol 169
 
4.9%
Uppercase Letter 73
 
2.1%
Open Punctuation 16
 
0.5%
Close Punctuation 16
 
0.5%
Decimal Number 5
 
0.1%
Other Punctuation 3
 
0.1%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 95
 
3.2%
기 77
 
2.6%
품 70
 
2.4%
조 64
 
2.2%
용 58
 
2.0%
가 54
 
1.8%
스 53
 
1.8%
장 48
 
1.6%
업 46
 
1.6%
리 44
 
1.5%
Other values (376) 2330
79.3%
Uppercase Letter
ValueCountFrequency (%)
P 14
19.2%
C 10
13.7%
V 8
11.0%
E 8
11.0%
L 6
8.2%
R 4
 
5.5%
D 4
 
5.5%
T 3
 
4.1%
F 3
 
4.1%
I 3
 
4.1%
Other values (6) 10
13.7%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
0 2
40.0%
1 1
20.0%
Space Separator
ValueCountFrequency (%)
252
100.0%
Math Symbol
ValueCountFrequency (%)
+ 169
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2939
84.6%
Common 463
 
13.3%
Latin 73
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 95
 
3.2%
기 77
 
2.6%
품 70
 
2.4%
조 64
 
2.2%
용 58
 
2.0%
가 54
 
1.8%
스 53
 
1.8%
장 48
 
1.6%
업 46
 
1.6%
리 44
 
1.5%
Other values (376) 2330
79.3%
Latin
ValueCountFrequency (%)
P 14
19.2%
C 10
13.7%
V 8
11.0%
E 8
11.0%
L 6
8.2%
R 4
 
5.5%
D 4
 
5.5%
T 3
 
4.1%
F 3
 
4.1%
I 3
 
4.1%
Other values (6) 10
13.7%
Common
ValueCountFrequency (%)
252
54.4%
+ 169
36.5%
( 16
 
3.5%
) 16
 
3.5%
, 3
 
0.6%
2 2
 
0.4%
- 2
 
0.4%
0 2
 
0.4%
1 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2939
84.6%
ASCII 536
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
252
47.0%
+ 169
31.5%
( 16
 
3.0%
) 16
 
3.0%
P 14
 
2.6%
C 10
 
1.9%
V 8
 
1.5%
E 8
 
1.5%
L 6
 
1.1%
R 4
 
0.7%
Other values (15) 33
 
6.2%
Hangul
ValueCountFrequency (%)
제 95
 
3.2%
기 77
 
2.6%
품 70
 
2.4%
조 64
 
2.2%
용 58
 
2.0%
가 54
 
1.8%
스 53
 
1.8%
장 48
 
1.6%
업 46
 
1.6%
리 44
 
1.5%
Other values (376) 2330
79.3%

부지면적
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct423
Distinct (%)94.0%
Missing22
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean17741.876
Minimum128
Maximum4472000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-01-10T05:27:05.188141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128
5-th percentile635.25
Q11944.25
median4029
Q38862.5
95-th percentile27612.05
Maximum4472000
Range4471872
Interquartile range (IQR)6918.25

Descriptive statistics

Standard deviation210868.17
Coefficient of variation (CV)11.885337
Kurtosis446.3615
Mean17741.876
Median Absolute Deviation (MAD)2690.5
Skewness21.086395
Sum7983844
Variance4.4465386 × 1010
MonotonicityNot monotonic
2024-01-10T05:27:05.590778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2314 3
 
0.6%
999 3
 
0.6%
5540 2
 
0.4%
990 2
 
0.4%
1977 2
 
0.4%
1271 2
 
0.4%
5778 2
 
0.4%
5202 2
 
0.4%
825 2
 
0.4%
4351 2
 
0.4%
Other values (413) 428
90.7%
(Missing) 22
 
4.7%
ValueCountFrequency (%)
128 1
0.2%
143 1
0.2%
165 2
0.4%
198 1
0.2%
222 1
0.2%
247 1
0.2%
255 1
0.2%
280 1
0.2%
281 1
0.2%
300 1
0.2%
ValueCountFrequency (%)
4472000 1
0.2%
165825 1
0.2%
123642 1
0.2%
108328 1
0.2%
58016 1
0.2%
46671 1
0.2%
45332 1
0.2%
43572 1
0.2%
43533 1
0.2%
40019 1
0.2%

건축면적
Real number (ℝ)

HIGH CORRELATION 

Distinct419
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2796.1814
Minimum33
Maximum232590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-01-10T05:27:05.720622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile133.65
Q1389.75
median963
Q32367
95-th percentile9306.15
Maximum232590
Range232557
Interquartile range (IQR)1977.25

Descriptive statistics

Standard deviation11779.729
Coefficient of variation (CV)4.2127915
Kurtosis312.97266
Mean2796.1814
Median Absolute Deviation (MAD)690.5
Skewness16.585157
Sum1319797.6
Variance1.3876202 × 108
MonotonicityNot monotonic
2024-01-10T05:27:05.837442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330.0 6
 
1.3%
59.0 5
 
1.1%
1953.0 4
 
0.8%
450.0 3
 
0.6%
492.0 3
 
0.6%
900.0 3
 
0.6%
810.0 3
 
0.6%
2811.0 2
 
0.4%
196.0 2
 
0.4%
333.0 2
 
0.4%
Other values (409) 439
93.0%
ValueCountFrequency (%)
33.0 1
 
0.2%
53.0 1
 
0.2%
59.0 5
1.1%
65.0 1
 
0.2%
66.0 2
 
0.4%
72.0 1
 
0.2%
93.0 1
 
0.2%
110.0 1
 
0.2%
113.0 1
 
0.2%
116.0 2
 
0.4%
ValueCountFrequency (%)
232590.0 1
0.2%
81668.0 1
0.2%
38358.0 1
0.2%
26038.0 1
0.2%
21148.0 1
0.2%
20251.0 1
0.2%
17860.0 1
0.2%
16915.0 1
0.2%
16382.0 1
0.2%
15942.0 1
0.2%

종업원수
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.84322
Minimum1
Maximum297
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-01-10T05:27:05.953095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median9
Q320
95-th percentile81.7
Maximum297
Range296
Interquartile range (IQR)16

Descriptive statistics

Standard deviation33.651215
Coefficient of variation (CV)1.6958545
Kurtosis22.668238
Mean19.84322
Median Absolute Deviation (MAD)6
Skewness4.2351608
Sum9366
Variance1132.4042
MonotonicityNot monotonic
2024-01-10T05:27:06.079867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 41
 
8.7%
2 37
 
7.8%
5 33
 
7.0%
4 33
 
7.0%
7 24
 
5.1%
1 22
 
4.7%
6 21
 
4.4%
9 20
 
4.2%
10 19
 
4.0%
8 19
 
4.0%
Other values (70) 203
43.0%
ValueCountFrequency (%)
1 22
4.7%
2 37
7.8%
3 41
8.7%
4 33
7.0%
5 33
7.0%
6 21
4.4%
7 24
5.1%
8 19
4.0%
9 20
4.2%
10 19
4.0%
ValueCountFrequency (%)
297 1
0.2%
256 1
0.2%
233 1
0.2%
200 1
0.2%
180 1
0.2%
167 1
0.2%
151 1
0.2%
150 2
0.4%
145 1
0.2%
130 2
0.4%

전화번호
Text

Distinct440
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-01-10T05:27:06.302681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.993644
Min length9

Characters and Unicode

Total characters5661
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

Unique425 ?
Unique (%)90.0%

Sample

1st row041-734-8858
2nd row000-000-0000
3rd row041-732-5401
4th row041-741-8986
5th row041-741-4131
ValueCountFrequency (%)
000-000-0000 19
 
4.0%
041-740-3600 2
 
0.4%
041-742-3311 2
 
0.4%
041-733-8996 2
 
0.4%
041-736-9230 2
 
0.4%
041-742-6082 2
 
0.4%
041-733-7261 2
 
0.4%
041-732-7890 2
 
0.4%
041-741-7251 2
 
0.4%
041-741-9533 2
 
0.4%
Other values (430) 435
92.2%
2024-01-10T05:27:06.651279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 941
16.6%
0 940
16.6%
4 830
14.7%
1 716
12.6%
7 613
10.8%
3 527
9.3%
2 304
 
5.4%
5 230
 
4.1%
8 194
 
3.4%
9 186
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4720
83.4%
Dash Punctuation 941
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 940
19.9%
4 830
17.6%
1 716
15.2%
7 613
13.0%
3 527
11.2%
2 304
 
6.4%
5 230
 
4.9%
8 194
 
4.1%
9 186
 
3.9%
6 180
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 941
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5661
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 941
16.6%
0 940
16.6%
4 830
14.7%
1 716
12.6%
7 613
10.8%
3 527
9.3%
2 304
 
5.4%
5 230
 
4.1%
8 194
 
3.4%
9 186
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5661
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 941
16.6%
0 940
16.6%
4 830
14.7%
1 716
12.6%
7 613
10.8%
3 527
9.3%
2 304
 
5.4%
5 230
 
4.1%
8 194
 
3.4%
9 186
 
3.3%

Interactions

2024-01-10T05:27:02.313934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:27:01.805742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:27:02.047228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:27:02.385835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:27:01.874267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:27:02.132217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:27:02.457446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:27:01.954391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:27:02.218521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:27:06.744117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종코드명사업자구분행정구역부지면적건축면적종업원수
업종코드명1.0000.0000.3180.0000.0000.000
사업자구분0.0001.0000.1160.0000.0580.222
행정구역0.3180.1161.0000.1020.0000.147
부지면적0.0000.0000.1021.0001.0000.000
건축면적0.0000.0580.0001.0001.0000.706
종업원수0.0000.2220.1470.0000.7061.000
2024-01-10T05:27:06.840924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역사업자구분업종코드명
행정구역1.0000.1040.103
사업자구분0.1041.0000.000
업종코드명0.1030.0001.000
2024-01-10T05:27:06.922151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부지면적건축면적종업원수업종코드명사업자구분행정구역
부지면적1.0000.8200.6110.0000.0000.091
건축면적0.8201.0000.6990.0000.0380.000
종업원수0.6110.6991.0000.0000.1690.054
업종코드명0.0000.0000.0001.0000.0000.103
사업자구분0.0000.0380.1690.0001.0000.104
행정구역0.0910.0000.0540.1030.1041.000

Missing values

2024-01-10T05:27:02.571283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:27:02.708728image/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

업체명업종코드명사업자구분설립일자행정구역소재지도로명주소주요생산품부지면적건축면적종업원수전화번호
0KY식품식료품 제조업법인2016-08-18부적면충청남도 논산시 부적면 덕평길 72-9생강차+천마차2950773.013041-734-8858
1가야곡면떡방아간식료품 제조업개인2010-10-15가야곡면충청남도 논산시 가야곡면 원앙로 629떡류763116.02000-000-0000
2가야촌식료품 제조업법인2009-12-10노성면충청남도 논산시 노성면 노성로 630-9육류 가공2098398.09041-732-5401
3강산식품식료품 제조업개인2003-07-09가야곡면충청남도 논산시 가야곡면 가야로22번길 9누룽지1057180.02041-741-8986
4건강마을식료품 제조업법인2004-04-22연무읍충청남도 논산시 연무읍 원안길 19음료3346450.019041-741-4131
5고려제빙식료품 제조업개인2003-08-13부적면충청남도 논산시 부적면 계백로1546번길 19얼음995750.03041-733-4124
6광석미곡처리장식료품 제조업개인2002-05-27광석면충청남도 논산시 광석면 천동길 18쌀40281049.01041-732-7770
7궁골식품영농조합법인식료품 제조업법인2009-08-01상월면충청남도 논산시 상월면 대촌3길 23-10장류 제조업843122.09041-734-8753
8그린농산식료품 제조업개인2004-02-27부적면충청남도 논산시 부적면 충곡로 110-37기타 식품 첨가물707190.05041-733-3495
9김치누리영농조합법인식료품 제조업법인2010-03-15은진면충청남도 논산시 은진면 방축3길 7-3김치1009182.06041-742-0128
업체명업종코드명사업자구분설립일자행정구역소재지도로명주소주요생산품부지면적건축면적종업원수전화번호
462파트너가구가구 제조업개인1993-07-10연무읍충청남도 논산시 연무읍 동안로 954사무용가구4173825.08041-742-6100
463퍼니텍가구 제조업법인2014-11-05연산면충청남도 논산시 연산면 계백로 2354-27부엌가구+붙박이장42181893.04042-673-0000
464피오코리아가구 제조업개인2000-02-15연무읍충청남도 논산시 연무읍 황화로 119-12목재가구사무용가구3756655.07041-742-8989
465한성넥스가구 제조업법인2009-05-12광석면충청남도 논산시 광석면 사계로 196침대+사무용가구55552360.028041-734-4970
466금정산업기타 제품 제조업개인1993-05-01취암동충청남도 논산시 지산1길 16욕실수납장 거울+유리2988582.05041-733-3566
467스벤손코리아기타 제품 제조업법인2011-03-07은진면충청남도 논산시 은진면 가야공단길 24-11차광막+보온재2285680.02070-7700-5704
468아그로드기타 제품 제조업법인2007-10-24상월면충청남도 논산시 상월면 득안대로 3025수입비료포장판매78311989.018042-933-2292
469에프투비기타 제품 제조업법인2015-03-01가야곡면충청남도 논산시 가야곡면 매죽헌로 897아스팔트보강재+토목용 보강재<NA>685.05041-742-9181
470코리아농업개발기타 제품 제조업법인2011-02-11은진면충청남도 논산시 은진면 가야공단길 24-11온실자재45701359.02041-741-5704
471휴먼테크기타 제품 제조업법인2009-07-14상월면충청남도 논산시 상월면 상월로 82-38칫솔 및 브러시276355435.068041-734-5687