Overview

Dataset statistics

Number of variables7
Number of observations641
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.8 KiB
Average record size in memory57.2 B

Variable types

Numeric1
Text5
Categorical1

Alerts

연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:34:24.966145
Analysis finished2024-03-14 00:34:25.798373
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct641
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean321
Minimum1
Maximum641
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-03-14T09:34:25.859587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile33
Q1161
median321
Q3481
95-th percentile609
Maximum641
Range640
Interquartile range (IQR)320

Descriptive statistics

Standard deviation185.18504
Coefficient of variation (CV)0.57690044
Kurtosis-1.2
Mean321
Median Absolute Deviation (MAD)160
Skewness0
Sum205761
Variance34293.5
MonotonicityStrictly increasing
2024-03-14T09:34:25.976208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
482 1
 
0.2%
424 1
 
0.2%
425 1
 
0.2%
426 1
 
0.2%
427 1
 
0.2%
428 1
 
0.2%
429 1
 
0.2%
430 1
 
0.2%
431 1
 
0.2%
Other values (631) 631
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
641 1
0.2%
640 1
0.2%
639 1
0.2%
638 1
0.2%
637 1
0.2%
636 1
0.2%
635 1
0.2%
634 1
0.2%
633 1
0.2%
632 1
0.2%

업체명
Text

Distinct631
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-03-14T09:34:26.182303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length7.2714509
Min length1

Characters and Unicode

Total characters4661
Distinct characters396
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

Unique621 ?
Unique (%)96.9%

Sample

1st row(유)유송건설
2nd row(유)지에스엔지니어링
3rd row(유)한양기공
4th row대원전력주식회사
5th row유한회사 계림건설
ValueCountFrequency (%)
주식회사 34
 
4.7%
유한회사 26
 
3.6%
유 6
 
0.8%
주 5
 
0.7%
그린숲 2
 
0.3%
주)휴먼제이앤씨 2
 
0.3%
에코하이테크 2
 
0.3%
유)범창산업 2
 
0.3%
유)흥진산업 2
 
0.3%
대원전력주식회사 2
 
0.3%
Other values (642) 648
88.6%
2024-03-14T09:34:26.546919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 364
 
7.8%
( 357
 
7.7%
유 269
 
5.8%
주 219
 
4.7%
사 136
 
2.9%
건 111
 
2.4%
이 99
 
2.1%
회 98
 
2.1%
94
 
2.0%
설 93
 
2.0%
Other values (386) 2821
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3772
80.9%
Close Punctuation 364
 
7.8%
Open Punctuation 357
 
7.7%
Space Separator 94
 
2.0%
Uppercase Letter 25
 
0.5%
Lowercase Letter 20
 
0.4%
Decimal Number 17
 
0.4%
Other Punctuation 8
 
0.2%
Other Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 269
 
7.1%
주 219
 
5.8%
사 136
 
3.6%
건 111
 
2.9%
이 99
 
2.6%
회 98
 
2.6%
설 93
 
2.5%
한 74
 
2.0%
식 72
 
1.9%
산 66
 
1.7%
Other values (344) 2535
67.2%
Uppercase Letter
ValueCountFrequency (%)
S 4
16.0%
J 3
12.0%
L 2
 
8.0%
E 2
 
8.0%
M 2
 
8.0%
P 2
 
8.0%
C 1
 
4.0%
H 1
 
4.0%
G 1
 
4.0%
N 1
 
4.0%
Other values (6) 6
24.0%
Lowercase Letter
ValueCountFrequency (%)
s 4
20.0%
a 3
15.0%
e 3
15.0%
n 2
10.0%
g 2
10.0%
t 2
10.0%
l 1
 
5.0%
f 1
 
5.0%
i 1
 
5.0%
r 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
1 4
23.5%
2 3
17.6%
6 3
17.6%
7 2
11.8%
3 1
 
5.9%
5 1
 
5.9%
4 1
 
5.9%
0 1
 
5.9%
9 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
& 3
37.5%
' 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 364
100.0%
Open Punctuation
ValueCountFrequency (%)
( 357
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3776
81.0%
Common 840
 
18.0%
Latin 45
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 269
 
7.1%
주 219
 
5.8%
사 136
 
3.6%
건 111
 
2.9%
이 99
 
2.6%
회 98
 
2.6%
설 93
 
2.5%
한 74
 
2.0%
식 72
 
1.9%
산 66
 
1.7%
Other values (345) 2539
67.2%
Latin
ValueCountFrequency (%)
S 4
 
8.9%
s 4
 
8.9%
a 3
 
6.7%
e 3
 
6.7%
J 3
 
6.7%
L 2
 
4.4%
n 2
 
4.4%
g 2
 
4.4%
t 2
 
4.4%
E 2
 
4.4%
Other values (16) 18
40.0%
Common
ValueCountFrequency (%)
) 364
43.3%
( 357
42.5%
94
 
11.2%
1 4
 
0.5%
. 4
 
0.5%
& 3
 
0.4%
2 3
 
0.4%
6 3
 
0.4%
7 2
 
0.2%
3 1
 
0.1%
Other values (5) 5
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3772
80.9%
ASCII 885
 
19.0%
None 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 364
41.1%
( 357
40.3%
94
 
10.6%
S 4
 
0.5%
1 4
 
0.5%
s 4
 
0.5%
. 4
 
0.5%
& 3
 
0.3%
a 3
 
0.3%
e 3
 
0.3%
Other values (31) 45
 
5.1%
Hangul
ValueCountFrequency (%)
유 269
 
7.1%
주 219
 
5.8%
사 136
 
3.6%
건 111
 
2.9%
이 99
 
2.6%
회 98
 
2.6%
설 93
 
2.5%
한 74
 
2.0%
식 72
 
1.9%
산 66
 
1.7%
Other values (344) 2535
67.2%
None
ValueCountFrequency (%)
㈜ 4
100.0%

대표자
Text

Distinct591
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-03-14T09:34:26.832222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0904836
Min length2

Characters and Unicode

Total characters1981
Distinct characters159
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

Unique545 ?
Unique (%)85.0%

Sample

1st row조은주
2nd row서봉순
3rd row강순덕
4th row박태숙
5th row강점이
ValueCountFrequency (%)
최정희 3
 
0.5%
김영희 3
 
0.5%
김정숙 3
 
0.5%
김영미 3
 
0.5%
김선자 2
 
0.3%
장미숙 2
 
0.3%
오은숙 2
 
0.3%
안기령 2
 
0.3%
김은영 2
 
0.3%
신경숙 2
 
0.3%
Other values (595) 635
96.4%
2024-03-14T09:34:27.215160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 127
 
6.4%
정 118
 
6.0%
숙 94
 
4.7%
이 85
 
4.3%
희 78
 
3.9%
미 78
 
3.9%
영 69
 
3.5%
순 69
 
3.5%
경 66
 
3.3%
은 61
 
3.1%
Other values (149) 1136
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1949
98.4%
Space Separator 21
 
1.1%
Other Punctuation 9
 
0.5%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 127
 
6.5%
정 118
 
6.1%
숙 94
 
4.8%
이 85
 
4.4%
희 78
 
4.0%
미 78
 
4.0%
영 69
 
3.5%
순 69
 
3.5%
경 66
 
3.4%
은 61
 
3.1%
Other values (146) 1104
56.6%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1949
98.4%
Common 32
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 127
 
6.5%
정 118
 
6.1%
숙 94
 
4.8%
이 85
 
4.4%
희 78
 
4.0%
미 78
 
4.0%
영 69
 
3.5%
순 69
 
3.5%
경 66
 
3.4%
은 61
 
3.1%
Other values (146) 1104
56.6%
Common
ValueCountFrequency (%)
21
65.6%
, 9
28.1%
1 2
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1949
98.4%
ASCII 32
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 127
 
6.5%
정 118
 
6.1%
숙 94
 
4.8%
이 85
 
4.4%
희 78
 
4.0%
미 78
 
4.0%
영 69
 
3.5%
순 69
 
3.5%
경 66
 
3.4%
은 61
 
3.1%
Other values (146) 1104
56.6%
ASCII
ValueCountFrequency (%)
21
65.6%
, 9
28.1%
1 2
 
6.2%

우편번호
Text

Distinct325
Distinct (%)50.7%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-03-14T09:34:27.565277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.9906396
Min length1

Characters and Unicode

Total characters4481
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

Unique180 ?
Unique (%)28.1%

Sample

1st row590-120
2nd row560-869
3rd row573-140
4th row573-360
5th row570-986
ValueCountFrequency (%)
560-838 10
 
1.6%
560-821 9
 
1.4%
560-822 9
 
1.4%
570-979 9
 
1.4%
561-330 7
 
1.1%
560-870 7
 
1.1%
595-805 7
 
1.1%
561-845 7
 
1.1%
561-370 7
 
1.1%
560-759 7
 
1.1%
Other values (315) 562
87.7%
2024-03-14T09:34:27.983582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 822
18.3%
- 640
14.3%
0 634
14.1%
8 457
10.2%
6 421
9.4%
7 354
7.9%
1 315
 
7.0%
9 265
 
5.9%
3 248
 
5.5%
2 209
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3841
85.7%
Dash Punctuation 640
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 822
21.4%
0 634
16.5%
8 457
11.9%
6 421
11.0%
7 354
9.2%
1 315
 
8.2%
9 265
 
6.9%
3 248
 
6.5%
2 209
 
5.4%
4 116
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 640
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4481
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 822
18.3%
- 640
14.3%
0 634
14.1%
8 457
10.2%
6 421
9.4%
7 354
7.9%
1 315
 
7.0%
9 265
 
5.9%
3 248
 
5.5%
2 209
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4481
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 822
18.3%
- 640
14.3%
0 634
14.1%
8 457
10.2%
6 421
9.4%
7 354
7.9%
1 315
 
7.0%
9 265
 
5.9%
3 248
 
5.5%
2 209
 
4.7%

주소
Text

Distinct620
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-03-14T09:34:28.310187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length26.975039
Min length14

Characters and Unicode

Total characters17291
Distinct characters349
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

Unique600 ?
Unique (%)93.6%

Sample

1st row전북 남원시 왕정동 194
2nd row전북 전주시 완산구 효자동3가 1450-2
3rd row전북 군산시 문화동 904-1
4th row전북 군산시 미룡동 408-4번지
5th row전북 익산시 인화동2가 100-2
ValueCountFrequency (%)
전라북도 581
 
15.8%
전주시 274
 
7.5%
완산구 150
 
4.1%
덕진구 124
 
3.4%
익산시 123
 
3.3%
전북 67
 
1.8%
군산시 61
 
1.7%
김제시 38
 
1.0%
남원시 34
 
0.9%
정읍시 28
 
0.8%
Other values (1258) 2192
59.7%
2024-03-14T09:34:28.764577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3231
 
18.7%
전 975
 
5.6%
북 698
 
4.0%
도 615
 
3.6%
라 594
 
3.4%
시 579
 
3.3%
1 563
 
3.3%
동 470
 
2.7%
산 440
 
2.5%
2 430
 
2.5%
Other values (339) 8696
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10325
59.7%
Space Separator 3231
 
18.7%
Decimal Number 2691
 
15.6%
Close Punctuation 367
 
2.1%
Open Punctuation 367
 
2.1%
Dash Punctuation 269
 
1.6%
Other Punctuation 28
 
0.2%
Uppercase Letter 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 975
 
9.4%
북 698
 
6.8%
도 615
 
6.0%
라 594
 
5.8%
시 579
 
5.6%
동 470
 
4.6%
산 440
 
4.3%
로 368
 
3.6%
주 344
 
3.3%
구 294
 
2.8%
Other values (310) 4948
47.9%
Decimal Number
ValueCountFrequency (%)
1 563
20.9%
2 430
16.0%
3 354
13.2%
4 236
8.8%
5 231
8.6%
0 220
 
8.2%
6 196
 
7.3%
7 191
 
7.1%
8 142
 
5.3%
9 128
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
J 2
15.4%
S 2
15.4%
F 2
15.4%
B 1
7.7%
G 1
7.7%
I 1
7.7%
T 1
7.7%
K 1
7.7%
M 1
7.7%
A 1
7.7%
Other Punctuation
ValueCountFrequency (%)
, 14
50.0%
， 10
35.7%
. 4
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 366
99.7%
] 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 366
99.7%
[ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
3231
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 269
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10325
59.7%
Common 6953
40.2%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 975
 
9.4%
북 698
 
6.8%
도 615
 
6.0%
라 594
 
5.8%
시 579
 
5.6%
동 470
 
4.6%
산 440
 
4.3%
로 368
 
3.6%
주 344
 
3.3%
구 294
 
2.8%
Other values (310) 4948
47.9%
Common
ValueCountFrequency (%)
3231
46.5%
1 563
 
8.1%
2 430
 
6.2%
) 366
 
5.3%
( 366
 
5.3%
3 354
 
5.1%
- 269
 
3.9%
4 236
 
3.4%
5 231
 
3.3%
0 220
 
3.2%
Other values (9) 687
 
9.9%
Latin
ValueCountFrequency (%)
J 2
15.4%
S 2
15.4%
F 2
15.4%
B 1
7.7%
G 1
7.7%
I 1
7.7%
T 1
7.7%
K 1
7.7%
M 1
7.7%
A 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10325
59.7%
ASCII 6956
40.2%
None 10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3231
46.4%
1 563
 
8.1%
2 430
 
6.2%
) 366
 
5.3%
( 366
 
5.3%
3 354
 
5.1%
- 269
 
3.9%
4 236
 
3.4%
5 231
 
3.3%
0 220
 
3.2%
Other values (18) 690
 
9.9%
Hangul
ValueCountFrequency (%)
전 975
 
9.4%
북 698
 
6.8%
도 615
 
6.0%
라 594
 
5.8%
시 579
 
5.6%
동 470
 
4.6%
산 440
 
4.3%
로 368
 
3.6%
주 344
 
3.3%
구 294
 
2.8%
Other values (310) 4948
47.9%
None
ValueCountFrequency (%)
， 10
100.0%

주업종
Categorical

Distinct15
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
제조업
227 
건설업
223 
도매 및 소매업
71 
사업시설관리 및 사업지원서비스업
42 
출판, 영상, 방송통신 및 정보서비스
 
16
Other values (10)
62 

Length

Max length21
Median length3
Mean length5.8892356
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row건설업
2nd row건설업
3rd row건설업
4th row전기, 가스, 증기 및 수도사업
5th row건설업

Common Values

ValueCountFrequency (%)
제조업 227
35.4%
건설업 223
34.8%
도매 및 소매업 71
 
11.1%
사업시설관리 및 사업지원서비스업 42
 
6.6%
출판, 영상, 방송통신 및 정보서비스 16
 
2.5%
수리 및 기타서비스업 16
 
2.5%
전기, 가스, 증기 및 수도사업 13
 
2.0%
전문, 과학 및 기술 서비스업 12
 
1.9%
부동산업 및 임대업 4
 
0.6%
운수업 4
 
0.6%
Other values (5) 13
 
2.0%

Length

2024-03-14T09:34:28.887201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제조업 227
20.4%
건설업 223
20.0%
및 184
16.5%
도매 71
 
6.4%
소매업 71
 
6.4%
사업시설관리 42
 
3.8%
사업지원서비스업 42
 
3.8%
출판 16
 
1.4%
영상 16
 
1.4%
정보서비스 16
 
1.4%
Other values (30) 207
18.6%

주생산품
Text

Distinct310
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-03-14T09:34:29.050179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length4.9469579
Min length1

Characters and Unicode

Total characters3171
Distinct characters344
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique275 ?
Unique (%)42.9%

Sample

1st row시설물유지관리
2nd row기계설비공사
3rd row없음
4th row전기공사용역
5th row건축공사
ValueCountFrequency (%)
233
31.5%
건물청소용역 14
 
1.9%
전기공사 13
 
1.8%
의약품 10
 
1.4%
건설업 8
 
1.1%
전기공사용역 7
 
0.9%
시설물유지관리업 7
 
0.9%
및 7
 
0.9%
실내건축공사 7
 
0.9%
철근콘크리트공사 6
 
0.8%
Other values (360) 427
57.8%
2024-03-14T09:34:29.521575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 234
 
7.4%
공 127
 
4.0%
사 125
 
3.9%
102
 
3.2%
, 85
 
2.7%
기 77
 
2.4%
건 74
 
2.3%
용 70
 
2.2%
설 68
 
2.1%
물 67
 
2.1%
Other values (334) 2142
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2679
84.5%
Dash Punctuation 234
 
7.4%
Other Punctuation 109
 
3.4%
Space Separator 102
 
3.2%
Decimal Number 13
 
0.4%
Uppercase Letter 12
 
0.4%
Close Punctuation 11
 
0.3%
Open Punctuation 11
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 127
 
4.7%
사 125
 
4.7%
기 77
 
2.9%
건 74
 
2.8%
용 70
 
2.6%
설 68
 
2.5%
물 67
 
2.5%
업 64
 
2.4%
리 54
 
2.0%
전 48
 
1.8%
Other values (313) 1905
71.1%
Uppercase Letter
ValueCountFrequency (%)
C 2
16.7%
D 2
16.7%
I 1
8.3%
F 1
8.3%
R 1
8.3%
M 1
8.3%
Y 1
8.3%
N 1
8.3%
K 1
8.3%
T 1
8.3%
Decimal Number
ValueCountFrequency (%)
9 9
69.2%
0 2
 
15.4%
3 1
 
7.7%
2 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 85
78.0%
. 18
 
16.5%
/ 6
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 234
100.0%
Space Separator
ValueCountFrequency (%)
102
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2678
84.5%
Common 480
 
15.1%
Latin 12
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 127
 
4.7%
사 125
 
4.7%
기 77
 
2.9%
건 74
 
2.8%
용 70
 
2.6%
설 68
 
2.5%
물 67
 
2.5%
업 64
 
2.4%
리 54
 
2.0%
전 48
 
1.8%
Other values (312) 1904
71.1%
Common
ValueCountFrequency (%)
- 234
48.8%
102
21.2%
, 85
 
17.7%
. 18
 
3.8%
) 11
 
2.3%
( 11
 
2.3%
9 9
 
1.9%
/ 6
 
1.2%
0 2
 
0.4%
3 1
 
0.2%
Latin
ValueCountFrequency (%)
C 2
16.7%
D 2
16.7%
I 1
8.3%
F 1
8.3%
R 1
8.3%
M 1
8.3%
Y 1
8.3%
N 1
8.3%
K 1
8.3%
T 1
8.3%
Han
ValueCountFrequency (%)
無 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2678
84.5%
ASCII 492
 
15.5%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 234
47.6%
102
20.7%
, 85
 
17.3%
. 18
 
3.7%
) 11
 
2.2%
( 11
 
2.2%
9 9
 
1.8%
/ 6
 
1.2%
C 2
 
0.4%
0 2
 
0.4%
Other values (11) 12
 
2.4%
Hangul
ValueCountFrequency (%)
공 127
 
4.7%
사 125
 
4.7%
기 77
 
2.9%
건 74
 
2.8%
용 70
 
2.6%
설 68
 
2.5%
물 67
 
2.5%
업 64
 
2.4%
리 54
 
2.0%
전 48
 
1.8%
Other values (312) 1904
71.1%
CJK
ValueCountFrequency (%)
無 1
100.0%

Interactions

2024-03-14T09:34:25.573832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:34:29.596415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주업종
연번1.0000.228
주업종0.2281.000
2024-03-14T09:34:29.680210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주업종
연번1.0000.084
주업종0.0841.000

Missing values

2024-03-14T09:34:25.669736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:34:25.761044image/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

연번업체명대표자우편번호주소주업종주생산품
01(유)유송건설조은주590-120전북 남원시 왕정동 194건설업시설물유지관리
12(유)지에스엔지니어링서봉순560-869전북 전주시 완산구 효자동3가 1450-2건설업기계설비공사
23(유)한양기공강순덕573-140전북 군산시 문화동 904-1건설업없음
34대원전력주식회사박태숙573-360전북 군산시 미룡동 408-4번지전기, 가스, 증기 및 수도사업전기공사용역
45유한회사 계림건설강점이570-986전북 익산시 인화동2가 100-2건설업건축공사
56오리엔트21양태련570-210전북 익산시 어양동 513-16번지제조업석재타일 및 판석
67(주)빗살이지수570-811전북 익산시 황등면 율촌리 907번지제조업-
78대한엔지니어링김경미560-822전북 전주시 완산구 서신동 991-2전기, 가스, 증기 및 수도사업전기공사용역
89(주)영웅건설임옥희570-988전북 익산시 중앙동3가 8-5건설업건설업
910(유)양손건설손현숙560-839전북 전주시 완산구 중화산동2가 749-5 3층건설업시설물유지관리
연번업체명대표자우편번호주소주업종주생산품
631632(유)우리산업강춘화590-911전라북도 남원시 덕과면 덕오로 474제조업-
632633(유)범건설유현자590-989전라북도 남원시 동림로 47 (향교동)건설업건설업
633634주식회사 포올최귀숙585-821전라북도 고창군 흥덕면 선운대로 3619-79건설업-
634635태양전력(유)이덕례580-060전라북도 정읍시 청수1길 3 전북정읍시시기동204-117 (시기동)전기, 가스, 증기 및 수도사업-
635636(유)하나석재오민행570-801전라북도 익산시 함열읍 미륵사지로 1098제조업경계석
636637대원전력주식회사박태숙573-360전라북도 군산시 미제길 10-18 408-4 (미룡동)전기, 가스, 증기 및 수도사업-
637638성원유통민지은560-870전라북도 전주시 완산구 서곡2길 14-1 (효자동3가)도매 및 소매업사무용품및액세사리
638639(유)신흥공영박순영570-803전라북도 익산시 함열읍 함열10길 15건설업창호공사
639640오에이원정보경560-901전라북도 전주시 완산구 척동9길 5-6 204호 (효자동3가)도매 및 소매업서비스
640641한들인쇄이금순외1명560-838전라북도 전주시 완산구 메너머1길 15 (중화산동2가)제조업-