Overview

Dataset statistics

Number of variables7
Number of observations350
Missing cells5
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.0 KiB
Average record size in memory58.4 B

Variable types

Numeric2
Text3
DateTime1
Categorical1

Alerts

순번 is highly overall correlated with 단지명High correlation
단지명 is highly overall correlated with 순번High correlation
전화번호 has 5 (1.4%) missing valuesMissing
순번 has unique valuesUnique
종업원수 has 18 (5.1%) zerosZeros

Reproduction

Analysis started2024-01-09 21:10:36.544322
Analysis finished2024-01-09 21:10:37.384601
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct350
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean175.5
Minimum1
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-10T06:10:37.776705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.45
Q188.25
median175.5
Q3262.75
95-th percentile332.55
Maximum350
Range349
Interquartile range (IQR)174.5

Descriptive statistics

Standard deviation101.18053
Coefficient of variation (CV)0.57652725
Kurtosis-1.2
Mean175.5
Median Absolute Deviation (MAD)87.5
Skewness0
Sum61425
Variance10237.5
MonotonicityStrictly increasing
2024-01-10T06:10:37.914065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
232 1
 
0.3%
240 1
 
0.3%
239 1
 
0.3%
238 1
 
0.3%
237 1
 
0.3%
236 1
 
0.3%
235 1
 
0.3%
234 1
 
0.3%
233 1
 
0.3%
Other values (340) 340
97.1%
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 (%)
350 1
0.3%
349 1
0.3%
348 1
0.3%
347 1
0.3%
346 1
0.3%
345 1
0.3%
344 1
0.3%
343 1
0.3%
342 1
0.3%
341 1
0.3%

회사명
Text

Distinct328
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-01-10T06:10:38.167121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length8.5314286
Min length2

Characters and Unicode

Total characters2986
Distinct characters284
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

Unique308 ?
Unique (%)88.0%

Sample

1st row(주)가람이엔알
2nd row(주)광진기계
3rd row(주)금성인슈텍
4th row(주)다원알로이
5th row(주)대성스틸
ValueCountFrequency (%)
주식회사 62
 
13.9%
아산공장 7
 
1.6%
태평양에어콘트롤공업(주 5
 
1.1%
이든테크(주 3
 
0.7%
아산지점 3
 
0.7%
주)코윈테크 3
 
0.7%
에스와이(주 3
 
0.7%
주)톱텍 2
 
0.4%
에프엔에스테크(주 2
 
0.4%
지점 2
 
0.4%
Other values (336) 355
79.4%
2024-01-10T06:10:38.569738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 323
 
10.8%
( 252
 
8.4%
) 252
 
8.4%
이 133
 
4.5%
에 105
 
3.5%
스 105
 
3.5%
97
 
3.2%
사 77
 
2.6%
회 74
 
2.5%
식 73
 
2.4%
Other values (274) 1495
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2331
78.1%
Open Punctuation 252
 
8.4%
Close Punctuation 252
 
8.4%
Space Separator 97
 
3.2%
Uppercase Letter 29
 
1.0%
Decimal Number 10
 
0.3%
Other Punctuation 8
 
0.3%
Other Symbol 4
 
0.1%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 323
 
13.9%
이 133
 
5.7%
에 105
 
4.5%
스 105
 
4.5%
사 77
 
3.3%
회 74
 
3.2%
식 73
 
3.1%
아 49
 
2.1%
지 40
 
1.7%
크 39
 
1.7%
Other values (241) 1313
56.3%
Uppercase Letter
ValueCountFrequency (%)
A 4
13.8%
X 3
 
10.3%
M 3
 
10.3%
T 2
 
6.9%
L 2
 
6.9%
S 2
 
6.9%
H 2
 
6.9%
E 1
 
3.4%
G 1
 
3.4%
I 1
 
3.4%
Other values (8) 8
27.6%
Decimal Number
ValueCountFrequency (%)
4 3
30.0%
1 2
20.0%
2 2
20.0%
3 2
20.0%
5 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 5
62.5%
& 2
 
25.0%
, 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
d 1
33.3%
t 1
33.3%
o 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 252
100.0%
Close Punctuation
ValueCountFrequency (%)
) 252
100.0%
Space Separator
ValueCountFrequency (%)
97
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2335
78.2%
Common 619
 
20.7%
Latin 32
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 323
 
13.8%
이 133
 
5.7%
에 105
 
4.5%
스 105
 
4.5%
사 77
 
3.3%
회 74
 
3.2%
식 73
 
3.1%
아 49
 
2.1%
지 40
 
1.7%
크 39
 
1.7%
Other values (242) 1317
56.4%
Latin
ValueCountFrequency (%)
A 4
 
12.5%
X 3
 
9.4%
M 3
 
9.4%
T 2
 
6.2%
L 2
 
6.2%
S 2
 
6.2%
H 2
 
6.2%
E 1
 
3.1%
G 1
 
3.1%
I 1
 
3.1%
Other values (11) 11
34.4%
Common
ValueCountFrequency (%)
( 252
40.7%
) 252
40.7%
97
 
15.7%
. 5
 
0.8%
4 3
 
0.5%
1 2
 
0.3%
& 2
 
0.3%
2 2
 
0.3%
3 2
 
0.3%
5 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2331
78.1%
ASCII 651
 
21.8%
None 4
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 323
 
13.9%
이 133
 
5.7%
에 105
 
4.5%
스 105
 
4.5%
사 77
 
3.3%
회 74
 
3.2%
식 73
 
3.1%
아 49
 
2.1%
지 40
 
1.7%
크 39
 
1.7%
Other values (241) 1313
56.3%
ASCII
ValueCountFrequency (%)
( 252
38.7%
) 252
38.7%
97
 
14.9%
. 5
 
0.8%
A 4
 
0.6%
X 3
 
0.5%
M 3
 
0.5%
4 3
 
0.5%
1 2
 
0.3%
T 2
 
0.3%
Other values (22) 28
 
4.3%
None
ValueCountFrequency (%)
㈜ 4
100.0%

지번주소
Text

Distinct279
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-01-10T06:10:38.900977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length21
Mean length21.591429
Min length18

Characters and Unicode

Total characters7557
Distinct characters107
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

Unique227 ?
Unique (%)64.9%

Sample

1st row충청남도 아산시 인주면 걸매리 1044
2nd row충청남도 아산시 인주면 걸매리 1047
3rd row충청남도 아산시 인주면 걸매리 1056
4th row충청남도 아산시 인주면 걸매리 1008 (주)다원알로이
5th row충청남도 아산시 인주면 걸매리 1010
ValueCountFrequency (%)
충청남도 350
19.8%
아산시 350
19.8%
둔포면 195
11.0%
석곡리 181
 
10.2%
인주면 49
 
2.8%
걸매리 47
 
2.7%
음봉면 38
 
2.1%
득산동 36
 
2.0%
신휴리 28
 
1.6%
외 12
 
0.7%
Other values (319) 485
27.4%
2024-01-10T06:10:39.347680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1429
18.9%
산 400
 
5.3%
도 356
 
4.7%
아 354
 
4.7%
남 353
 
4.7%
충 350
 
4.6%
청 350
 
4.6%
시 350
 
4.6%
1 339
 
4.5%
리 310
 
4.1%
Other values (97) 2966
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4588
60.7%
Space Separator 1429
 
18.9%
Decimal Number 1428
 
18.9%
Dash Punctuation 80
 
1.1%
Uppercase Letter 10
 
0.1%
Open Punctuation 9
 
0.1%
Close Punctuation 8
 
0.1%
Other Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 400
 
8.7%
도 356
 
7.8%
아 354
 
7.7%
남 353
 
7.7%
충 350
 
7.6%
청 350
 
7.6%
시 350
 
7.6%
리 310
 
6.8%
면 309
 
6.7%
포 196
 
4.3%
Other values (76) 1260
27.5%
Decimal Number
ValueCountFrequency (%)
1 339
23.7%
3 194
13.6%
2 178
12.5%
5 158
11.1%
0 142
9.9%
4 103
 
7.2%
9 95
 
6.7%
7 83
 
5.8%
6 79
 
5.5%
8 57
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
50.0%
C 1
 
10.0%
N 1
 
10.0%
G 1
 
10.0%
L 1
 
10.0%
S 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1429
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4588
60.7%
Common 2959
39.2%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 400
 
8.7%
도 356
 
7.8%
아 354
 
7.7%
남 353
 
7.7%
충 350
 
7.6%
청 350
 
7.6%
시 350
 
7.6%
리 310
 
6.8%
면 309
 
6.7%
포 196
 
4.3%
Other values (76) 1260
27.5%
Common
ValueCountFrequency (%)
1429
48.3%
1 339
 
11.5%
3 194
 
6.6%
2 178
 
6.0%
5 158
 
5.3%
0 142
 
4.8%
4 103
 
3.5%
9 95
 
3.2%
7 83
 
2.8%
- 80
 
2.7%
Other values (5) 158
 
5.3%
Latin
ValueCountFrequency (%)
B 5
50.0%
C 1
 
10.0%
N 1
 
10.0%
G 1
 
10.0%
L 1
 
10.0%
S 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4588
60.7%
ASCII 2969
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1429
48.1%
1 339
 
11.4%
3 194
 
6.5%
2 178
 
6.0%
5 158
 
5.3%
0 142
 
4.8%
4 103
 
3.5%
9 95
 
3.2%
7 83
 
2.8%
- 80
 
2.7%
Other values (11) 168
 
5.7%
Hangul
ValueCountFrequency (%)
산 400
 
8.7%
도 356
 
7.8%
아 354
 
7.7%
남 353
 
7.7%
충 350
 
7.6%
청 350
 
7.6%
시 350
 
7.6%
리 310
 
6.8%
면 309
 
6.7%
포 196
 
4.3%
Other values (76) 1260
27.5%

최초등록일
Date

Distinct325
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum1988-11-25 00:00:00
Maximum2023-03-27 00:00:00
2024-01-10T06:10:39.487012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:10:39.637645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct312
Distinct (%)90.4%
Missing5
Missing (%)1.4%
Memory size2.9 KiB
2024-01-10T06:10:39.853382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.043478
Min length11

Characters and Unicode

Total characters4155
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

Unique286 ?
Unique (%)82.9%

Sample

1st row041-534-5307
2nd row041-421-4019
3rd row041-547-8806
4th row041-531-9611
5th row031-682-9102
ValueCountFrequency (%)
041-543-2320 4
 
1.2%
041-629-3500 4
 
1.2%
041-547-2131 3
 
0.9%
041-547-3710 3
 
0.9%
041-582-6301 3
 
0.9%
041-531-9915 2
 
0.6%
041-533-7965 2
 
0.6%
041-532-3914 2
 
0.6%
051-780-7800 2
 
0.6%
031-997-0041 2
 
0.6%
Other values (302) 318
92.2%
2024-01-10T06:10:40.213872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 690
16.6%
0 676
16.3%
1 575
13.8%
4 561
13.5%
5 373
9.0%
3 335
8.1%
2 244
 
5.9%
7 198
 
4.8%
8 179
 
4.3%
6 171
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3465
83.4%
Dash Punctuation 690
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 676
19.5%
1 575
16.6%
4 561
16.2%
5 373
10.8%
3 335
9.7%
2 244
 
7.0%
7 198
 
5.7%
8 179
 
5.2%
6 171
 
4.9%
9 153
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 690
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4155
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 690
16.6%
0 676
16.3%
1 575
13.8%
4 561
13.5%
5 373
9.0%
3 335
8.1%
2 244
 
5.9%
7 198
 
4.8%
8 179
 
4.3%
6 171
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4155
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 690
16.6%
0 676
16.3%
1 575
13.8%
4 561
13.5%
5 373
9.0%
3 335
8.1%
2 244
 
5.9%
7 198
 
4.8%
8 179
 
4.3%
6 171
 
4.1%

종업원수
Real number (ℝ)

ZEROS 

Distinct121
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.9
Minimum0
Maximum2832
Zeros18
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-10T06:10:40.339181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.45
Q110
median27
Q358
95-th percentile239.6
Maximum2832
Range2832
Interquartile range (IQR)48

Descriptive statistics

Standard deviation233.16257
Coefficient of variation (CV)3.0719706
Kurtosis92.080901
Mean75.9
Median Absolute Deviation (MAD)19
Skewness8.8935326
Sum26565
Variance54364.784
MonotonicityNot monotonic
2024-01-10T06:10:40.458850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18
 
5.1%
10 14
 
4.0%
20 13
 
3.7%
6 13
 
3.7%
30 12
 
3.4%
7 11
 
3.1%
9 9
 
2.6%
5 8
 
2.3%
11 8
 
2.3%
15 7
 
2.0%
Other values (111) 237
67.7%
ValueCountFrequency (%)
0 18
5.1%
1 1
 
0.3%
2 6
 
1.7%
3 6
 
1.7%
4 4
 
1.1%
5 8
2.3%
6 13
3.7%
7 11
3.1%
8 6
 
1.7%
9 9
2.6%
ValueCountFrequency (%)
2832 1
0.3%
2500 1
0.3%
1282 1
0.3%
1222 1
0.3%
679 1
0.3%
653 1
0.3%
531 1
0.3%
490 1
0.3%
400 1
0.3%
390 1
0.3%

단지명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
아산테크노밸리일반산업단지
122 
아산제2테크노밸리일반산업단지
86 
아산인주일반산업단지
49 
아산득산농공단지
37 
아산운용일반산업단지
 
10
Other values (10)
46 

Length

Max length18
Median length15
Mean length12.074286
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아산테크노밸리일반산업단지 122
34.9%
아산제2테크노밸리일반산업단지 86
24.6%
아산인주일반산업단지 49
14.0%
아산득산농공단지 37
 
10.6%
아산운용일반산업단지 10
 
2.9%
아산디지털일반산업단지 10
 
2.9%
아산탕정디스플레이시티1일반산업단지 6
 
1.7%
아산도고농공단지 6
 
1.7%
아산신창농공단지 6
 
1.7%
아산영인농공단지 4
 
1.1%
Other values (5) 14
 
4.0%

Length

2024-01-10T06:10:40.602497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아산테크노밸리일반산업단지 122
34.9%
아산제2테크노밸리일반산업단지 86
24.6%
아산인주일반산업단지 49
14.0%
아산득산농공단지 37
 
10.6%
아산운용일반산업단지 10
 
2.9%
아산디지털일반산업단지 10
 
2.9%
아산탕정디스플레이시티1일반산업단지 6
 
1.7%
아산도고농공단지 6
 
1.7%
아산신창농공단지 6
 
1.7%
아산영인농공단지 4
 
1.1%
Other values (5) 14
 
4.0%

Interactions

2024-01-10T06:10:36.989807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:10:36.818898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:10:37.094131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:10:36.904886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:10:40.680647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종업원수단지명
순번1.0000.0000.899
종업원수0.0001.0000.426
단지명0.8990.4261.000
2024-01-10T06:10:40.774622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종업원수단지명
순번1.0000.0260.607
종업원수0.0261.0000.211
단지명0.6070.2111.000

Missing values

2024-01-10T06:10:37.222893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:10:37.337348image/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

순번회사명지번주소최초등록일전화번호종업원수단지명
01(주)가람이엔알충청남도 아산시 인주면 걸매리 10442012-03-14041-534-53073아산인주일반산업단지
12(주)광진기계충청남도 아산시 인주면 걸매리 10472007-06-01041-421-4019245아산인주일반산업단지
23(주)금성인슈텍충청남도 아산시 인주면 걸매리 10562017-10-17041-547-880622아산인주일반산업단지
34(주)다원알로이충청남도 아산시 인주면 걸매리 1008 (주)다원알로이2020-03-05041-531-961127아산인주일반산업단지
45(주)대성스틸충청남도 아산시 인주면 걸매리 10102015-06-03031-682-910215아산인주일반산업단지
56(주)대영정밀충청남도 아산시 인주면 걸매리 10422008-01-17041-531-905168아산인주일반산업단지
67(주)디엠티충청남도 아산시 인주면 걸매리 10322011-02-14041-532-1480116아산인주일반산업단지
78(주)디엠티충청남도 아산시 인주면 걸매리 1031-12019-02-19041-532-148031아산인주일반산업단지
89(주)서영충청남도 아산시 인주면 걸매리 10202007-04-09041-538-550033아산인주일반산업단지
910(주)썬테크충청남도 아산시 인주면 걸매리 10402007-09-14041-533-761050아산인주일반산업단지
순번회사명지번주소최초등록일전화번호종업원수단지명
340341정우신약(주)충청남도 아산시 신창면 읍내리 80-131994-08-18041-533-619170아산신창농공단지
341342주식회사 쌤큐충청남도 아산시 신창면 읍내리 80-162020-12-30041-544-29265아산신창농공단지
342343행운산업(주)충청남도 아산시 신창면 읍내리 80-221991-03-18041-541-483739아산신창농공단지
343344(주)대륙제관충청남도 아산시 영인면 신운리 223-12000-04-21041-540-3300290아산영인농공단지
344345대협철강(주)충청남도 아산시 영인면 신운리 150 외 2필지2000-03-30041-543-440030아산영인농공단지
345346매일유업(주) 아산공장충청남도 아산시 영인면 신운리 241-11998-09-07041-538-160049아산영인농공단지
346347빔보큐에스알코리아 주식회사충청남도 아산시 영인면 신운리 241-61998-08-14041-539-395074아산영인농공단지
347348동광산업사충청남도 아산시 탕정면 호산리 45-91997-10-01041-541-762611아산탕정농공단지
348349신일판넬(주)충청남도 아산시 탕정면 동산리 45-231999-01-23041-543-985130아산탕정농공단지
349350이누스 주식회사충청남도 아산시 탕정면 동산리 45-9 외 5필지1988-11-25041-530-3700168아산탕정농공단지