Overview

Dataset statistics

Number of variables7
Number of observations195
Missing cells114
Missing cells (%)8.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.2 KiB
Average record size in memory58.7 B

Variable types

Numeric2
Text5

Dataset

Description서구관내공장등록현황(업체명,사업장주소,업종명,전화번호, 종업원수,생산품에 대한 정보제공)에 대하여 정보공개합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15028066/fileData.do

Alerts

전화번호 has 14 (7.2%) missing valuesMissing
생산품 has 99 (50.8%) missing valuesMissing
순번 has unique valuesUnique
종업원수 has 7 (3.6%) zerosZeros

Reproduction

Analysis started2024-03-14 09:34:20.590901
Analysis finished2024-03-14 09:34:23.400775
Duration2.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98
Minimum1
Maximum195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-14T18:34:23.632424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.7
Q149.5
median98
Q3146.5
95-th percentile185.3
Maximum195
Range194
Interquartile range (IQR)97

Descriptive statistics

Standard deviation56.435804
Coefficient of variation (CV)0.57587555
Kurtosis-1.2
Mean98
Median Absolute Deviation (MAD)49
Skewness0
Sum19110
Variance3185
MonotonicityStrictly increasing
2024-03-14T18:34:24.093318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
124 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%

회사명
Text

Distinct193
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T18:34:25.004227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length7.6307692
Min length3

Characters and Unicode

Total characters1488
Distinct characters249
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

Unique191 ?
Unique (%)97.9%

Sample

1st row(주) 드론디비젼
2nd row(주)거성산업
3rd row(주)건승
4th row(주)광전자통신
5th row(주)구이
ValueCountFrequency (%)
주식회사 35
 
14.0%
한스산업(주 2
 
0.8%
와이제이테크 2
 
0.8%
농업회사법인 2
 
0.8%
윤기획 1
 
0.4%
이엠트리 1
 
0.4%
오성레이저테크(주 1
 
0.4%
오케이디자인 1
 
0.4%
우명동 1
 
0.4%
참기름마을 1
 
0.4%
Other values (203) 203
81.2%
2024-03-14T18:34:26.352038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 136
 
9.1%
( 99
 
6.7%
) 99
 
6.7%
이 56
 
3.8%
55
 
3.7%
사 53
 
3.6%
회 42
 
2.8%
식 39
 
2.6%
스 38
 
2.6%
업 27
 
1.8%
Other values (239) 844
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1228
82.5%
Open Punctuation 99
 
6.7%
Close Punctuation 99
 
6.7%
Space Separator 55
 
3.7%
Uppercase Letter 4
 
0.3%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 136
 
11.1%
이 56
 
4.6%
사 53
 
4.3%
회 42
 
3.4%
식 39
 
3.2%
스 38
 
3.1%
업 27
 
2.2%
지 22
 
1.8%
에 21
 
1.7%
인 21
 
1.7%
Other values (231) 773
62.9%
Uppercase Letter
ValueCountFrequency (%)
Q 1
25.0%
B 1
25.0%
F 1
25.0%
C 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 99
100.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1228
82.5%
Common 256
 
17.2%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 136
 
11.1%
이 56
 
4.6%
사 53
 
4.3%
회 42
 
3.4%
식 39
 
3.2%
스 38
 
3.1%
업 27
 
2.2%
지 22
 
1.8%
에 21
 
1.7%
인 21
 
1.7%
Other values (231) 773
62.9%
Common
ValueCountFrequency (%)
( 99
38.7%
) 99
38.7%
55
21.5%
& 3
 
1.2%
Latin
ValueCountFrequency (%)
Q 1
25.0%
B 1
25.0%
F 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1228
82.5%
ASCII 260
 
17.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 136
 
11.1%
이 56
 
4.6%
사 53
 
4.3%
회 42
 
3.4%
식 39
 
3.2%
스 38
 
3.1%
업 27
 
2.2%
지 22
 
1.8%
에 21
 
1.7%
인 21
 
1.7%
Other values (231) 773
62.9%
ASCII
ValueCountFrequency (%)
( 99
38.1%
) 99
38.1%
55
21.2%
& 3
 
1.2%
Q 1
 
0.4%
B 1
 
0.4%
F 1
 
0.4%
C 1
 
0.4%

공장대표주소(도로명)
Text

Distinct191
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T18:34:27.243677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length52
Mean length30.369231
Min length19

Characters and Unicode

Total characters5922
Distinct characters171
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

Unique187 ?
Unique (%)95.9%

Sample

1st row대전광역시 서구 도안북로 88, 창업진흥센터 O-1관 104,105,106,110호(도안동, 목원대학교)
2nd row대전광역시 서구 계룡로232번길 157 (월평동)
3rd row대전광역시 서구 배재로46번길 19 (도마동)
4th row대전광역시 서구 갈마로197번길 19 (괴정동)
5th row대전광역시 서구 한밭대로612번길 6 (월평동)
ValueCountFrequency (%)
대전광역시 195
 
16.7%
서구 195
 
16.7%
1층 25
 
2.1%
월평동 19
 
1.6%
갈마동 18
 
1.5%
탄방동 15
 
1.3%
도마동 14
 
1.2%
평촌동 13
 
1.1%
2층 13
 
1.1%
정림동 9
 
0.8%
Other values (376) 655
55.9%
2024-03-14T18:34:28.624942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
976
 
16.5%
대 238
 
4.0%
1 236
 
4.0%
동 219
 
3.7%
역 204
 
3.4%
서 204
 
3.4%
전 203
 
3.4%
( 199
 
3.4%
) 199
 
3.4%
광 197
 
3.3%
Other values (161) 3047
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3215
54.3%
Decimal Number 1097
 
18.5%
Space Separator 976
 
16.5%
Open Punctuation 199
 
3.4%
Close Punctuation 199
 
3.4%
Other Punctuation 174
 
2.9%
Dash Punctuation 50
 
0.8%
Uppercase Letter 8
 
0.1%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 238
 
7.4%
동 219
 
6.8%
역 204
 
6.3%
서 204
 
6.3%
전 203
 
6.3%
광 197
 
6.1%
시 196
 
6.1%
구 195
 
6.1%
로 158
 
4.9%
길 96
 
3.0%
Other values (141) 1305
40.6%
Decimal Number
ValueCountFrequency (%)
1 236
21.5%
2 139
12.7%
5 121
11.0%
0 119
10.8%
4 116
10.6%
3 103
9.4%
6 94
 
8.6%
8 76
 
6.9%
7 60
 
5.5%
9 33
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
O 6
75.0%
B 1
 
12.5%
E 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 172
98.9%
. 2
 
1.1%
Space Separator
ValueCountFrequency (%)
976
100.0%
Open Punctuation
ValueCountFrequency (%)
( 199
100.0%
Close Punctuation
ValueCountFrequency (%)
) 199
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3215
54.3%
Common 2699
45.6%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 238
 
7.4%
동 219
 
6.8%
역 204
 
6.3%
서 204
 
6.3%
전 203
 
6.3%
광 197
 
6.1%
시 196
 
6.1%
구 195
 
6.1%
로 158
 
4.9%
길 96
 
3.0%
Other values (141) 1305
40.6%
Common
ValueCountFrequency (%)
976
36.2%
1 236
 
8.7%
( 199
 
7.4%
) 199
 
7.4%
, 172
 
6.4%
2 139
 
5.2%
5 121
 
4.5%
0 119
 
4.4%
4 116
 
4.3%
3 103
 
3.8%
Other values (7) 319
 
11.8%
Latin
ValueCountFrequency (%)
O 6
75.0%
B 1
 
12.5%
E 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3215
54.3%
ASCII 2707
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
976
36.1%
1 236
 
8.7%
( 199
 
7.4%
) 199
 
7.4%
, 172
 
6.4%
2 139
 
5.1%
5 121
 
4.5%
0 119
 
4.4%
4 116
 
4.3%
3 103
 
3.8%
Other values (10) 327
 
12.1%
Hangul
ValueCountFrequency (%)
대 238
 
7.4%
동 219
 
6.8%
역 204
 
6.3%
서 204
 
6.3%
전 203
 
6.3%
광 197
 
6.1%
시 196
 
6.1%
구 195
 
6.1%
로 158
 
4.9%
길 96
 
3.0%
Other values (141) 1305
40.6%

업종명
Text

Distinct151
Distinct (%)77.8%
Missing1
Missing (%)0.5%
Memory size1.6 KiB
2024-03-14T18:34:29.643547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length23
Mean length17.649485
Min length5

Characters and Unicode

Total characters3424
Distinct characters220
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)65.5%

Sample

1st row무인 항공기 및 무인 비행장치 제조업
2nd row금속 문, 창, 셔터 및 관련제품 제조업
3rd row구조용 금속 판제품 및 공작물 제조업 외 7 종
4th row비디오 및 기타 영상기기 제조업 외 3 종
5th row방송장비 제조업 외 1 종
ValueCountFrequency (%)
제조업 172
 
15.3%
외 134
 
11.9%
종 117
 
10.4%
및 78
 
6.9%
1 55
 
4.9%
기타 53
 
4.7%
그 17
 
1.5%
금속 16
 
1.4%
3 15
 
1.3%
전기 12
 
1.1%
Other values (208) 458
40.6%
2024-03-14T18:34:31.122403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
933
27.2%
제 228
 
6.7%
업 208
 
6.1%
조 200
 
5.8%
외 139
 
4.1%
기 137
 
4.0%
종 119
 
3.5%
및 80
 
2.3%
1 67
 
2.0%
타 58
 
1.7%
Other values (210) 1255
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2332
68.1%
Space Separator 933
27.2%
Decimal Number 131
 
3.8%
Other Punctuation 22
 
0.6%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 228
 
9.8%
업 208
 
8.9%
조 200
 
8.6%
외 139
 
6.0%
기 137
 
5.9%
종 119
 
5.1%
및 80
 
3.4%
타 58
 
2.5%
장 44
 
1.9%
용 42
 
1.8%
Other values (195) 1077
46.2%
Decimal Number
ValueCountFrequency (%)
1 67
51.1%
3 18
 
13.7%
2 16
 
12.2%
4 14
 
10.7%
5 5
 
3.8%
7 5
 
3.8%
0 3
 
2.3%
9 2
 
1.5%
6 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 19
86.4%
. 2
 
9.1%
· 1
 
4.5%
Space Separator
ValueCountFrequency (%)
933
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2332
68.1%
Common 1092
31.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 228
 
9.8%
업 208
 
8.9%
조 200
 
8.6%
외 139
 
6.0%
기 137
 
5.9%
종 119
 
5.1%
및 80
 
3.4%
타 58
 
2.5%
장 44
 
1.9%
용 42
 
1.8%
Other values (195) 1077
46.2%
Common
ValueCountFrequency (%)
933
85.4%
1 67
 
6.1%
, 19
 
1.7%
3 18
 
1.6%
2 16
 
1.5%
4 14
 
1.3%
5 5
 
0.5%
7 5
 
0.5%
0 3
 
0.3%
) 3
 
0.3%
Other values (5) 9
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2330
68.0%
ASCII 1091
31.9%
Compat Jamo 2
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
933
85.5%
1 67
 
6.1%
, 19
 
1.7%
3 18
 
1.6%
2 16
 
1.5%
4 14
 
1.3%
5 5
 
0.5%
7 5
 
0.5%
0 3
 
0.3%
) 3
 
0.3%
Other values (4) 8
 
0.7%
Hangul
ValueCountFrequency (%)
제 228
 
9.8%
업 208
 
8.9%
조 200
 
8.6%
외 139
 
6.0%
기 137
 
5.9%
종 119
 
5.1%
및 80
 
3.4%
타 58
 
2.5%
장 44
 
1.9%
용 42
 
1.8%
Other values (194) 1075
46.1%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

전화번호
Text

MISSING 

Distinct178
Distinct (%)98.3%
Missing14
Missing (%)7.2%
Memory size1.6 KiB
2024-03-14T18:34:32.023368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.016575
Min length7

Characters and Unicode

Total characters2175
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

Unique176 ?
Unique (%)97.2%

Sample

1st row042-627-0929
2nd row042-524-0083
3rd row042-534-0996
4th row042-531-6643
5th row042-483-8844
ValueCountFrequency (%)
042-585-8870 3
 
1.7%
042-535-0708 2
 
1.1%
042-610-6680 1
 
0.6%
042-531-3001 1
 
0.6%
042-627-0929 1
 
0.6%
042-487-0934 1
 
0.6%
042-582-3245 1
 
0.6%
042-825-5071 1
 
0.6%
042-537-0472 1
 
0.6%
042-581-1837 1
 
0.6%
Other values (168) 168
92.8%
2024-03-14T18:34:33.344286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 360
16.6%
2 323
14.9%
0 306
14.1%
4 302
13.9%
5 199
9.1%
8 148
6.8%
3 131
 
6.0%
7 121
 
5.6%
1 119
 
5.5%
6 93
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1815
83.4%
Dash Punctuation 360
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 323
17.8%
0 306
16.9%
4 302
16.6%
5 199
11.0%
8 148
8.2%
3 131
7.2%
7 121
 
6.7%
1 119
 
6.6%
6 93
 
5.1%
9 73
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 360
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 360
16.6%
2 323
14.9%
0 306
14.1%
4 302
13.9%
5 199
9.1%
8 148
6.8%
3 131
 
6.0%
7 121
 
5.6%
1 119
 
5.5%
6 93
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 360
16.6%
2 323
14.9%
0 306
14.1%
4 302
13.9%
5 199
9.1%
8 148
6.8%
3 131
 
6.0%
7 121
 
5.6%
1 119
 
5.5%
6 93
 
4.3%

종업원수
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.6307692
Minimum0
Maximum169
Zeros7
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-14T18:34:33.934334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median5
Q310
95-th percentile27.9
Maximum169
Range169
Interquartile range (IQR)7

Descriptive statistics

Standard deviation17.976705
Coefficient of variation (CV)1.8665908
Kurtosis42.696613
Mean9.6307692
Median Absolute Deviation (MAD)3
Skewness5.9218652
Sum1878
Variance323.16193
MonotonicityNot monotonic
2024-03-14T18:34:34.340613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
3 27
13.8%
2 22
11.3%
4 19
 
9.7%
5 18
 
9.2%
1 13
 
6.7%
6 12
 
6.2%
7 11
 
5.6%
8 10
 
5.1%
10 8
 
4.1%
0 7
 
3.6%
Other values (24) 48
24.6%
ValueCountFrequency (%)
0 7
 
3.6%
1 13
6.7%
2 22
11.3%
3 27
13.8%
4 19
9.7%
5 18
9.2%
6 12
6.2%
7 11
5.6%
8 10
 
5.1%
9 4
 
2.1%
ValueCountFrequency (%)
169 1
0.5%
127 1
0.5%
90 1
0.5%
71 1
0.5%
50 1
0.5%
45 1
0.5%
43 1
0.5%
42 1
0.5%
36 1
0.5%
30 1
0.5%

생산품
Text

MISSING 

Distinct93
Distinct (%)96.9%
Missing99
Missing (%)50.8%
Memory size1.6 KiB
2024-03-14T18:34:35.358016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length25
Mean length10.791667
Min length2

Characters and Unicode

Total characters1036
Distinct characters251
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)93.8%

Sample

1st row드론
2nd row창틀, 철문
3rd row음수대,차양,금속가구
4th rowcctv,방송장비 등
5th rowCCTV
ValueCountFrequency (%)
등 5
 
2.4%
및 4
 
2.0%
cctv 3
 
1.5%
간판 3
 
1.5%
환 3
 
1.5%
와송 3
 
1.5%
컴퓨터 3
 
1.5%
꾸지뽕 3
 
1.5%
외 3
 
1.5%
작업복 3
 
1.5%
Other values (163) 172
83.9%
2024-03-14T18:34:36.812985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111
 
10.7%
, 94
 
9.1%
기 40
 
3.9%
제 16
 
1.5%
장 15
 
1.4%
지 15
 
1.4%
C 14
 
1.4%
스 14
 
1.4%
복 14
 
1.4%
등 13
 
1.3%
Other values (241) 690
66.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 762
73.6%
Space Separator 111
 
10.7%
Other Punctuation 95
 
9.2%
Uppercase Letter 41
 
4.0%
Lowercase Letter 19
 
1.8%
Close Punctuation 4
 
0.4%
Open Punctuation 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 40
 
5.2%
제 16
 
2.1%
장 15
 
2.0%
지 15
 
2.0%
스 14
 
1.8%
복 14
 
1.8%
등 13
 
1.7%
판 12
 
1.6%
라 11
 
1.4%
카 10
 
1.3%
Other values (219) 602
79.0%
Lowercase Letter
ValueCountFrequency (%)
c 6
31.6%
t 3
15.8%
v 3
15.8%
m 1
 
5.3%
n 1
 
5.3%
s 1
 
5.3%
e 1
 
5.3%
r 1
 
5.3%
l 1
 
5.3%
p 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
C 14
34.1%
T 7
17.1%
V 7
17.1%
D 4
 
9.8%
L 4
 
9.8%
E 4
 
9.8%
I 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 94
98.9%
. 1
 
1.1%
Space Separator
ValueCountFrequency (%)
111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 762
73.6%
Common 214
 
20.7%
Latin 60
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 40
 
5.2%
제 16
 
2.1%
장 15
 
2.0%
지 15
 
2.0%
스 14
 
1.8%
복 14
 
1.8%
등 13
 
1.7%
판 12
 
1.6%
라 11
 
1.4%
카 10
 
1.3%
Other values (219) 602
79.0%
Latin
ValueCountFrequency (%)
C 14
23.3%
T 7
11.7%
V 7
11.7%
c 6
10.0%
D 4
 
6.7%
L 4
 
6.7%
E 4
 
6.7%
t 3
 
5.0%
v 3
 
5.0%
m 1
 
1.7%
Other values (7) 7
11.7%
Common
ValueCountFrequency (%)
111
51.9%
, 94
43.9%
) 4
 
1.9%
( 4
 
1.9%
. 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 761
73.5%
ASCII 274
 
26.4%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
40.5%
, 94
34.3%
C 14
 
5.1%
T 7
 
2.6%
V 7
 
2.6%
c 6
 
2.2%
D 4
 
1.5%
L 4
 
1.5%
E 4
 
1.5%
) 4
 
1.5%
Other values (12) 19
 
6.9%
Hangul
ValueCountFrequency (%)
기 40
 
5.3%
제 16
 
2.1%
장 15
 
2.0%
지 15
 
2.0%
스 14
 
1.8%
복 14
 
1.8%
등 13
 
1.7%
판 12
 
1.6%
라 11
 
1.4%
카 10
 
1.3%
Other values (218) 601
79.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

Interactions

2024-03-14T18:34:21.941198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:34:21.410372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:34:22.204820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:34:21.677806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:34:37.069407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종업원수생산품
순번1.0000.0000.517
종업원수0.0001.0000.000
생산품0.5170.0001.000
2024-03-14T18:34:37.309583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종업원수
순번1.000-0.203
종업원수-0.2031.000

Missing values

2024-03-14T18:34:22.558986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:34:22.950378image/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.
2024-03-14T18:34:23.255593image/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

순번회사명공장대표주소(도로명)업종명전화번호종업원수생산품
01(주) 드론디비젼대전광역시 서구 도안북로 88, 창업진흥센터 O-1관 104,105,106,110호(도안동, 목원대학교)무인 항공기 및 무인 비행장치 제조업042-627-09294드론
12(주)거성산업대전광역시 서구 계룡로232번길 157 (월평동)금속 문, 창, 셔터 및 관련제품 제조업042-524-008319창틀, 철문
23(주)건승대전광역시 서구 배재로46번길 19 (도마동)구조용 금속 판제품 및 공작물 제조업 외 7 종042-534-099621음수대,차양,금속가구
34(주)광전자통신대전광역시 서구 갈마로197번길 19 (괴정동)비디오 및 기타 영상기기 제조업 외 3 종042-531-66433cctv,방송장비 등
45(주)구이대전광역시 서구 한밭대로612번길 6 (월평동)방송장비 제조업 외 1 종042-483-88446CCTV
56(주)그대로대전광역시 서구 대덕대로168번길 50, 2층 203호 (갈마동, 위너스빌)기타 가정용 전기기기 제조업070-4015-45141음식물처리기
67(주)대경이앤씨대전광역시 서구 월드컵대로484번길 147-42 (월평동)방송장비 제조업 외 4 종042-525-35684전광판, 교통신호제어기
78(주)대성전기조명 서부지점대전광역시 서구 도솔로 327, 102호 (괴정동)육상 금속 골조 구조재 제조업 외 9 종042-525-68382백열등,형광등
89(주)더존페이퍼대전광역시 서구 장전길 55 (오동)위생용 종이제품 제조업042-585-208314화장지, 키친타올
910(주)동산기획대전광역시 서구 월드컵대로484번길 187-50, (주)동산기획 (월평동) 외 1필지기타 직물제품 제조업 외 1 종042-523-198216태극기, 직물제품제조, 플라스틱 깃대
순번회사명공장대표주소(도로명)업종명전화번호종업원수생산품
185186플랜비대전광역시 서구 배재로 155-40, 창업보육센터 B102호 (도마동, 배재대학교)침구 및 관련제품 제조업 외 3 종<NA>2<NA>
186187플러스대전광역시 서구 계백로 1301-14 (정림동)무인 항공기 및 무인 비행장치 제조업042-581-58243<NA>
187188한스산업(주)대전광역시 서구 혜천로 40 (정림동, 한스빌딩)근무복, 작업복 및 유사의복 제조업 외 4 종042-523-827816<NA>
188189한스산업(주)대전광역시 서구 혜천로 42, 2층 (정림동)구두류 제조업 외 1 종042-581-367730<NA>
189190합자회사 유승기업대전광역시 서구 용문동 518-2번지<NA>042-523-003371<NA>
190191해드림에너지(주 )대전광역시 서구 당고개길 103 (평촌동)전동기 및 발전기 제조업042-343-55773<NA>
191192해솔정보통신(주)대전광역시 서구 벌곡로1328번안길 143 (가수원동)비디오 및 기타 영상기기 제조업 외 5 종042-349-35625<NA>
192193화성전기(주)대전광역시 서구 변동로 104 (변동)방송장비 제조업042-544-27823<NA>
193194화신엔지니어링대전광역시 서구 계룡로354번길 99, 1층, 지하1층 (갈마동)기타 전기 변환장치 제조업 외 5 종042-533-52427<NA>
194195흥진섬유(주)대전광역시 서구 갈마역로 155, 2층(월평동, 둔산테크노) 2층셔츠 및 블라우스 제조업 외 13 종042-489-274250<NA>