Overview

Dataset statistics

Number of variables7
Number of observations124
Missing cells91
Missing cells (%)10.5%
Duplicate rows1
Duplicate rows (%)0.8%
Total size in memory7.0 KiB
Average record size in memory58.1 B

Variable types

Numeric1
Categorical1
Text5

Dataset

Description충청남도 보령시 산업단지입주기업체현황(산업단지명, 기업명, 사업자등록번호, 전화번호)에 관한 데이터를 제공하고 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=422&beforeMenuCd=DOM_000000201001001000&publicdatapk=15030526

Alerts

Dataset has 1 (0.8%) duplicate rowsDuplicates
연번 is highly overall correlated with 단지명High correlation
단지명 is highly overall correlated with 연번High correlation
연번 has 11 (8.9%) missing valuesMissing
업체명 has 11 (8.9%) missing valuesMissing
사업자등록번호 has 13 (10.5%) missing valuesMissing
주소 has 13 (10.5%) missing valuesMissing
주생산품 has 11 (8.9%) missing valuesMissing
연락처 has 32 (25.8%) missing valuesMissing

Reproduction

Analysis started2024-01-09 21:43:14.697720
Analysis finished2024-01-09 21:43:15.670263
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct113
Distinct (%)100.0%
Missing11
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean57
Minimum1
Maximum113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-10T06:43:15.725761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.6
Q129
median57
Q385
95-th percentile107.4
Maximum113
Range112
Interquartile range (IQR)56

Descriptive statistics

Standard deviation32.76431
Coefficient of variation (CV)0.57481245
Kurtosis-1.2
Mean57
Median Absolute Deviation (MAD)28
Skewness0
Sum6441
Variance1073.5
MonotonicityStrictly increasing
2024-01-10T06:43:15.833174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
82 1
 
0.8%
81 1
 
0.8%
80 1
 
0.8%
79 1
 
0.8%
78 1
 
0.8%
77 1
 
0.8%
76 1
 
0.8%
Other values (103) 103
83.1%
(Missing) 11
 
8.9%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
113 1
0.8%
112 1
0.8%
111 1
0.8%
110 1
0.8%
109 1
0.8%
108 1
0.8%
107 1
0.8%
106 1
0.8%
105 1
0.8%
104 1
0.8%

단지명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
웅천석재농공단지
23 
웅천농공단지
23 
청소농공단지
17 
관창일반산업단지
16 
주포농공단지
15 
Other values (12)
30 

Length

Max length8
Median length6
Mean length6.5080645
Min length1

Unique

Unique10 ?
Unique (%)8.1%

Sample

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

Common Values

ValueCountFrequency (%)
웅천석재농공단지 23
18.5%
웅천농공단지 23
18.5%
청소농공단지 17
13.7%
관창일반산업단지 16
12.9%
주포농공단지 15
12.1%
<NA> 10
8.1%
요암농공단지 10
8.1%
주포5농공단지 1
 
0.8%
주포2농공단지 1
 
0.8%
주포3농공단지 1
 
0.8%
Other values (7) 7
 
5.6%

Length

2024-01-10T06:43:15.941600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
웅천석재농공단지 23
18.7%
웅천농공단지 23
18.7%
청소농공단지 17
13.8%
관창일반산업단지 16
13.0%
주포농공단지 15
12.2%
na 10
8.1%
요암농공단지 10
8.1%
주포5농공단지 1
 
0.8%
주포2농공단지 1
 
0.8%
주포3농공단지 1
 
0.8%
Other values (6) 6
 
4.9%

업체명
Text

MISSING 

Distinct113
Distinct (%)100.0%
Missing11
Missing (%)8.9%
Memory size1.1 KiB
2024-01-10T06:43:16.121211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length7.699115
Min length2

Characters and Unicode

Total characters870
Distinct characters182
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)100.0%

Sample

1st row(주)에스비정공보령공장
2nd row(주)이다
3rd row(주)케이디에프
4th row(주)해피디아
5th rowCS하우징
ValueCountFrequency (%)
주식회사 17
 
11.7%
2공장 4
 
2.8%
제2공장 2
 
1.4%
예성석재 2
 
1.4%
돌 2
 
1.4%
한일기계 2
 
1.4%
큰양지 1
 
0.7%
스톤 1
 
0.7%
앤 1
 
0.7%
백보석재 1
 
0.7%
Other values (112) 112
77.2%
2024-01-10T06:43:16.442345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 73
 
8.4%
( 53
 
6.1%
) 53
 
6.1%
34
 
3.9%
에 25
 
2.9%
이 23
 
2.6%
사 23
 
2.6%
스 23
 
2.6%
식 21
 
2.4%
회 20
 
2.3%
Other values (172) 522
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 708
81.4%
Open Punctuation 53
 
6.1%
Close Punctuation 53
 
6.1%
Space Separator 34
 
3.9%
Decimal Number 7
 
0.8%
Other Symbol 7
 
0.8%
Uppercase Letter 7
 
0.8%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 73
 
10.3%
에 25
 
3.5%
이 23
 
3.2%
사 23
 
3.2%
스 23
 
3.2%
식 21
 
3.0%
회 20
 
2.8%
공 14
 
2.0%
대 13
 
1.8%
장 13
 
1.8%
Other values (159) 460
65.0%
Uppercase Letter
ValueCountFrequency (%)
O 1
14.3%
Z 1
14.3%
L 1
14.3%
C 1
14.3%
H 1
14.3%
A 1
14.3%
S 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Decimal Number
ValueCountFrequency (%)
2 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 7
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 715
82.2%
Common 148
 
17.0%
Latin 7
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 73
 
10.2%
에 25
 
3.5%
이 23
 
3.2%
사 23
 
3.2%
스 23
 
3.2%
식 21
 
2.9%
회 20
 
2.8%
공 14
 
2.0%
대 13
 
1.8%
장 13
 
1.8%
Other values (160) 467
65.3%
Latin
ValueCountFrequency (%)
O 1
14.3%
Z 1
14.3%
L 1
14.3%
C 1
14.3%
H 1
14.3%
A 1
14.3%
S 1
14.3%
Common
ValueCountFrequency (%)
( 53
35.8%
) 53
35.8%
34
23.0%
2 7
 
4.7%
& 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 708
81.4%
ASCII 155
 
17.8%
None 7
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 73
 
10.3%
에 25
 
3.5%
이 23
 
3.2%
사 23
 
3.2%
스 23
 
3.2%
식 21
 
3.0%
회 20
 
2.8%
공 14
 
2.0%
대 13
 
1.8%
장 13
 
1.8%
Other values (159) 460
65.0%
ASCII
ValueCountFrequency (%)
( 53
34.2%
) 53
34.2%
34
21.9%
2 7
 
4.5%
& 1
 
0.6%
O 1
 
0.6%
Z 1
 
0.6%
L 1
 
0.6%
C 1
 
0.6%
H 1
 
0.6%
Other values (2) 2
 
1.3%
None
ValueCountFrequency (%)
㈜ 7
100.0%

사업자등록번호
Text

MISSING 

Distinct106
Distinct (%)95.5%
Missing13
Missing (%)10.5%
Memory size1.1 KiB
2024-01-10T06:43:16.659862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1332
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

Unique101 ?
Unique (%)91.0%

Sample

1st row606-81-75079
2nd row141-81-23467
3rd row312-86-12761
4th row873-86-01847
5th row402-36-91502
ValueCountFrequency (%)
606-86-26554 2
 
1.8%
313-81-08339 2
 
1.8%
165-05-00563 2
 
1.8%
313-81-24149 2
 
1.8%
313-03-87281 2
 
1.8%
313-03-41188 1
 
0.9%
314-86-66259 1
 
0.9%
313-04-68898 1
 
0.9%
363-55-00503 1
 
0.9%
602-81-68090 1
 
0.9%
Other values (96) 96
86.5%
2024-01-10T06:43:16.967000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 222
16.7%
1 208
15.6%
3 194
14.6%
8 149
11.2%
0 126
9.5%
2 101
7.6%
6 97
7.3%
5 75
 
5.6%
4 62
 
4.7%
7 56
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1110
83.3%
Dash Punctuation 222
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 208
18.7%
3 194
17.5%
8 149
13.4%
0 126
11.4%
2 101
9.1%
6 97
8.7%
5 75
 
6.8%
4 62
 
5.6%
7 56
 
5.0%
9 42
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 222
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1332
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 222
16.7%
1 208
15.6%
3 194
14.6%
8 149
11.2%
0 126
9.5%
2 101
7.6%
6 97
7.3%
5 75
 
5.6%
4 62
 
4.7%
7 56
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 222
16.7%
1 208
15.6%
3 194
14.6%
8 149
11.2%
0 126
9.5%
2 101
7.6%
6 97
7.3%
5 75
 
5.6%
4 62
 
4.7%
7 56
 
4.2%

주소
Text

MISSING 

Distinct102
Distinct (%)91.9%
Missing13
Missing (%)10.5%
Memory size1.1 KiB
2024-01-10T06:43:17.249767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length25.891892
Min length17

Characters and Unicode

Total characters2874
Distinct characters115
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)84.7%

Sample

1st row충청남도 보령시 주교면 관창공단길 225
2nd row충청남도 보령시 주교면 관창공단길 10
3rd row충청남도 보령시 주교면 관창공단길 129
4th row충청남도 보령시 주교면 관창리 1227-11번지
5th row충청남도 보령시 주교면 관창리 1227-18번지
ValueCountFrequency (%)
충청남도 111
17.7%
보령시 111
17.7%
웅천읍 45
 
7.2%
주포면 24
 
3.8%
산업단지길 23
 
3.7%
석재단지길 22
 
3.5%
주교면 18
 
2.9%
청소면 17
 
2.7%
외 14
 
2.2%
충서로 14
 
2.2%
Other values (131) 228
36.4%
2024-01-10T06:43:17.612163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
516
 
18.0%
청 128
 
4.5%
충 125
 
4.3%
보 114
 
4.0%
령 113
 
3.9%
남 111
 
3.9%
도 111
 
3.9%
시 111
 
3.9%
1 89
 
3.1%
지 79
 
2.7%
Other values (105) 1377
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1793
62.4%
Space Separator 516
 
18.0%
Decimal Number 415
 
14.4%
Dash Punctuation 52
 
1.8%
Open Punctuation 38
 
1.3%
Close Punctuation 38
 
1.3%
Other Punctuation 11
 
0.4%
Uppercase Letter 10
 
0.3%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 128
 
7.1%
충 125
 
7.0%
보 114
 
6.4%
령 113
 
6.3%
남 111
 
6.2%
도 111
 
6.2%
시 111
 
6.2%
지 79
 
4.4%
길 75
 
4.2%
단 68
 
3.8%
Other values (80) 758
42.3%
Decimal Number
ValueCountFrequency (%)
1 89
21.4%
2 62
14.9%
6 51
12.3%
7 45
10.8%
4 44
10.6%
3 37
8.9%
5 34
 
8.2%
8 21
 
5.1%
9 18
 
4.3%
0 14
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
O 2
20.0%
F 1
10.0%
I 1
10.0%
G 1
10.0%
M 1
10.0%
D 1
10.0%
A 1
10.0%
E 1
10.0%
W 1
10.0%
Space Separator
ValueCountFrequency (%)
516
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1794
62.4%
Common 1070
37.2%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 128
 
7.1%
충 125
 
7.0%
보 114
 
6.4%
령 113
 
6.3%
남 111
 
6.2%
도 111
 
6.2%
시 111
 
6.2%
지 79
 
4.4%
길 75
 
4.2%
단 68
 
3.8%
Other values (81) 759
42.3%
Common
ValueCountFrequency (%)
516
48.2%
1 89
 
8.3%
2 62
 
5.8%
- 52
 
4.9%
6 51
 
4.8%
7 45
 
4.2%
4 44
 
4.1%
( 38
 
3.6%
) 38
 
3.6%
3 37
 
3.5%
Other values (5) 98
 
9.2%
Latin
ValueCountFrequency (%)
O 2
20.0%
F 1
10.0%
I 1
10.0%
G 1
10.0%
M 1
10.0%
D 1
10.0%
A 1
10.0%
E 1
10.0%
W 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1793
62.4%
ASCII 1080
37.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
516
47.8%
1 89
 
8.2%
2 62
 
5.7%
- 52
 
4.8%
6 51
 
4.7%
7 45
 
4.2%
4 44
 
4.1%
( 38
 
3.5%
) 38
 
3.5%
3 37
 
3.4%
Other values (14) 108
 
10.0%
Hangul
ValueCountFrequency (%)
청 128
 
7.1%
충 125
 
7.0%
보 114
 
6.4%
령 113
 
6.3%
남 111
 
6.2%
도 111
 
6.2%
시 111
 
6.2%
지 79
 
4.4%
길 75
 
4.2%
단 68
 
3.8%
Other values (80) 758
42.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

주생산품
Text

MISSING 

Distinct99
Distinct (%)87.6%
Missing11
Missing (%)8.9%
Memory size1.1 KiB
2024-01-10T06:43:17.788916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length29
Mean length10.752212
Min length2

Characters and Unicode

Total characters1215
Distinct characters249
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

Unique90 ?
Unique (%)79.6%

Sample

1st row미션부품(GF6 COVER)
2nd row알루미늄 프로파일, PVC프로파일, 도장제품
3rd rowPVC바닥재
4th row생활용품, 유아용품
5th row철 구조물 제작
ValueCountFrequency (%)
자동차부품 6
 
2.6%
석재품 5
 
2.2%
석제품 5
 
2.2%
및 5
 
2.2%
등 4
 
1.7%
알루미늄 4
 
1.7%
조미김 3
 
1.3%
영상감시장치 3
 
1.3%
외 2
 
0.9%
가로등주 2
 
0.9%
Other values (175) 193
83.2%
2024-01-10T06:43:18.059690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
 
9.9%
, 90
 
7.4%
품 35
 
2.9%
기 27
 
2.2%
재 21
 
1.7%
석 20
 
1.6%
장 20
 
1.6%
동 19
 
1.6%
용 19
 
1.6%
제 19
 
1.6%
Other values (239) 825
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 930
76.5%
Space Separator 120
 
9.9%
Other Punctuation 95
 
7.8%
Uppercase Letter 46
 
3.8%
Lowercase Letter 10
 
0.8%
Open Punctuation 5
 
0.4%
Close Punctuation 5
 
0.4%
Decimal Number 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 35
 
3.8%
기 27
 
2.9%
재 21
 
2.3%
석 20
 
2.2%
장 20
 
2.2%
동 19
 
2.0%
용 19
 
2.0%
제 19
 
2.0%
조 19
 
2.0%
자 18
 
1.9%
Other values (213) 713
76.7%
Uppercase Letter
ValueCountFrequency (%)
C 11
23.9%
V 7
15.2%
D 5
10.9%
E 5
10.9%
T 4
 
8.7%
L 3
 
6.5%
P 3
 
6.5%
R 2
 
4.3%
F 2
 
4.3%
O 2
 
4.3%
Other values (2) 2
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
20.0%
l 2
20.0%
y 1
10.0%
u 1
10.0%
r 1
10.0%
p 1
10.0%
m 1
10.0%
a 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 90
94.7%
. 5
 
5.3%
Space Separator
ValueCountFrequency (%)
120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Decimal Number
ValueCountFrequency (%)
6 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 930
76.5%
Common 229
 
18.8%
Latin 56
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 35
 
3.8%
기 27
 
2.9%
재 21
 
2.3%
석 20
 
2.2%
장 20
 
2.2%
동 19
 
2.0%
용 19
 
2.0%
제 19
 
2.0%
조 19
 
2.0%
자 18
 
1.9%
Other values (213) 713
76.7%
Latin
ValueCountFrequency (%)
C 11
19.6%
V 7
12.5%
D 5
8.9%
E 5
8.9%
T 4
 
7.1%
L 3
 
5.4%
P 3
 
5.4%
R 2
 
3.6%
e 2
 
3.6%
F 2
 
3.6%
Other values (10) 12
21.4%
Common
ValueCountFrequency (%)
120
52.4%
, 90
39.3%
( 5
 
2.2%
. 5
 
2.2%
) 5
 
2.2%
6 4
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 930
76.5%
ASCII 285
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
42.1%
, 90
31.6%
C 11
 
3.9%
V 7
 
2.5%
D 5
 
1.8%
E 5
 
1.8%
( 5
 
1.8%
. 5
 
1.8%
) 5
 
1.8%
T 4
 
1.4%
Other values (16) 28
 
9.8%
Hangul
ValueCountFrequency (%)
품 35
 
3.8%
기 27
 
2.9%
재 21
 
2.3%
석 20
 
2.2%
장 20
 
2.2%
동 19
 
2.0%
용 19
 
2.0%
제 19
 
2.0%
조 19
 
2.0%
자 18
 
1.9%
Other values (213) 713
76.7%

연락처
Text

MISSING 

Distinct89
Distinct (%)96.7%
Missing32
Missing (%)25.8%
Memory size1.1 KiB
2024-01-10T06:43:18.257890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.032609
Min length12

Characters and Unicode

Total characters1107
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

Unique86 ?
Unique (%)93.5%

Sample

1st row041-934-5520
2nd row031-957-0107
3rd row041-549-0311
4th row041-939-7700
5th row041-402-7800
ValueCountFrequency (%)
041-932-3678 2
 
2.2%
041-933-4227 2
 
2.2%
041-934-5520 2
 
2.2%
041-936-1500 1
 
1.1%
041-931-2476 1
 
1.1%
041-931-7012 1
 
1.1%
041-931-3337 1
 
1.1%
041-931-2241 1
 
1.1%
041-934-8945 1
 
1.1%
041-931-2173 1
 
1.1%
Other values (79) 79
85.9%
2024-01-10T06:43:18.565150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 184
16.6%
0 156
14.1%
1 148
13.4%
4 134
12.1%
3 133
12.0%
9 117
10.6%
2 55
 
5.0%
5 54
 
4.9%
6 45
 
4.1%
7 42
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 923
83.4%
Dash Punctuation 184
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 156
16.9%
1 148
16.0%
4 134
14.5%
3 133
14.4%
9 117
12.7%
2 55
 
6.0%
5 54
 
5.9%
6 45
 
4.9%
7 42
 
4.6%
8 39
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1107
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 184
16.6%
0 156
14.1%
1 148
13.4%
4 134
12.1%
3 133
12.0%
9 117
10.6%
2 55
 
5.0%
5 54
 
4.9%
6 45
 
4.1%
7 42
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1107
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 184
16.6%
0 156
14.1%
1 148
13.4%
4 134
12.1%
3 133
12.0%
9 117
10.6%
2 55
 
5.0%
5 54
 
4.9%
6 45
 
4.1%
7 42
 
3.8%

Interactions

2024-01-10T06:43:15.356272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:43:18.643507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단지명주생산품연락처
연번1.0000.9150.9520.813
단지명0.9151.0000.9480.996
주생산품0.9520.9481.0000.960
연락처0.8130.9960.9601.000
2024-01-10T06:43:18.715366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단지명
연번1.0000.632
단지명0.6321.000

Missing values

2024-01-10T06:43:15.435256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:43:15.519444image/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.
2024-01-10T06:43:15.606531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번단지명업체명사업자등록번호주소주생산품연락처
01관창일반산업단지(주)에스비정공보령공장606-81-75079충청남도 보령시 주교면 관창공단길 225미션부품(GF6 COVER)041-934-5520
12관창일반산업단지(주)이다141-81-23467충청남도 보령시 주교면 관창공단길 10알루미늄 프로파일, PVC프로파일, 도장제품031-957-0107
23관창일반산업단지(주)케이디에프312-86-12761충청남도 보령시 주교면 관창공단길 129PVC바닥재041-549-0311
34관창일반산업단지(주)해피디아873-86-01847충청남도 보령시 주교면 관창리 1227-11번지생활용품, 유아용품<NA>
45관창일반산업단지CS하우징402-36-91502충청남도 보령시 주교면 관창리 1227-18번지철 구조물 제작<NA>
56관창일반산업단지두원전선(주)133-81-11387충청남도 보령시 주교면 관창공단길 197 (두원전선㈜)절연전선041-939-7700
67관창일반산업단지수이앤지586-07-01195충청남도 보령시 주교면 관창리 1227-19번지철판절곡가공<NA>
78관창일반산업단지에스앤에스아이앤씨(주) 2공장556-85-01362충청남도 보령시 주교면 관창리 1227-3번지자동차용 신품 부품041-402-7800
89관창일반산업단지에스앤에스아이엔씨313-85-04461충청남도 보령시 주교면 관창공단길 241 (주교면)자동차6단기어 단조품041-931-6320
910관창일반산업단지우리기업313-05-31836충청남도 보령시 주교면 관창리 1227-20번지철 구조물 제작<NA>
연번단지명업체명사업자등록번호주소주생산품연락처
114<NA><NA><NA><NA><NA><NA><NA>
115<NA><NA><NA><NA><NA><NA><NA>
116<NA><NA><NA><NA><NA><NA><NA>
117<NA><NA><NA><NA><NA><NA><NA>
118<NA><NA><NA><NA><NA><NA><NA>
119<NA><NA><NA><NA><NA><NA><NA>
120<NA><NA><NA><NA><NA><NA><NA>
121<NA><NA><NA><NA><NA><NA><NA>
122<NA><NA><NA><NA><NA><NA><NA>
123<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

연번단지명업체명사업자등록번호주소주생산품연락처# duplicates
0<NA><NA><NA><NA><NA><NA><NA>10