Overview

Dataset statistics

Number of variables10
Number of observations1726
Missing cells205
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory136.7 KiB
Average record size in memory81.1 B

Variable types

Numeric1
Categorical3
Text6

Dataset

Description충청남도 자동차관리사업체(전문정비업) 현황정보로써 (영업상태, 등록일, 관리번호, 상호, 주소 등) 에 대한 데이터 입니다.
URLhttps://www.data.go.kr/data/15048535/fileData.do

Alerts

상태정보 has constant value ""Constant
관리사업유형 has constant value ""Constant
정비형태 has constant value ""Constant
대지면적 has 103 (6.0%) missing valuesMissing
건물면적 has 102 (5.9%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:10:43.303515
Analysis finished2023-12-12 03:10:44.647648
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct1726
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean863.5
Minimum1
Maximum1726
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.3 KiB
2023-12-12T12:10:45.077497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile87.25
Q1432.25
median863.5
Q31294.75
95-th percentile1639.75
Maximum1726
Range1725
Interquartile range (IQR)862.5

Descriptive statistics

Standard deviation498.3976
Coefficient of variation (CV)0.57718309
Kurtosis-1.2
Mean863.5
Median Absolute Deviation (MAD)431.5
Skewness0
Sum1490401
Variance248400.17
MonotonicityStrictly increasing
2023-12-12T12:10:45.299137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1161 1
 
0.1%
1159 1
 
0.1%
1158 1
 
0.1%
1157 1
 
0.1%
1156 1
 
0.1%
1155 1
 
0.1%
1154 1
 
0.1%
1153 1
 
0.1%
1152 1
 
0.1%
Other values (1716) 1716
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1726 1
0.1%
1725 1
0.1%
1724 1
0.1%
1723 1
0.1%
1722 1
0.1%
1721 1
0.1%
1720 1
0.1%
1719 1
0.1%
1718 1
0.1%
1717 1
0.1%

상태정보
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
영업
1726 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 1726
100.0%

Length

2023-12-12T12:10:45.473230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:10:45.613284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 1726
100.0%

등록년월일
Text

Distinct1342
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T12:10:45.918713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.986095
Min length7

Characters and Unicode

Total characters17236
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1103 ?
Unique (%)63.9%

Sample

1st row1996-01-08
2nd row1996-07-23
3rd row1997-02-01
4th row1997-04-30
5th row1997-05-30
ValueCountFrequency (%)
2004-06-30 36
 
2.1%
1998-11-05 14
 
0.8%
2009-07-02 9
 
0.5%
value 8
 
0.5%
1998-10-29 8
 
0.5%
2009-05-15 7
 
0.4%
1998-08-25 6
 
0.3%
1998-11-06 5
 
0.3%
2009-10-01 5
 
0.3%
1998-06-13 4
 
0.2%
Other values (1332) 1624
94.1%
2023-12-12T12:10:46.458334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4320
25.1%
- 3436
19.9%
2 2619
15.2%
1 2572
14.9%
9 1282
 
7.4%
8 610
 
3.5%
3 550
 
3.2%
6 479
 
2.8%
4 443
 
2.6%
7 442
 
2.6%
Other values (8) 483
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13744
79.7%
Dash Punctuation 3436
 
19.9%
Uppercase Letter 40
 
0.2%
Other Punctuation 16
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4320
31.4%
2 2619
19.1%
1 2572
18.7%
9 1282
 
9.3%
8 610
 
4.4%
3 550
 
4.0%
6 479
 
3.5%
4 443
 
3.2%
7 442
 
3.2%
5 427
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
V 8
20.0%
A 8
20.0%
L 8
20.0%
U 8
20.0%
E 8
20.0%
Other Punctuation
ValueCountFrequency (%)
# 8
50.0%
! 8
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 3436
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17196
99.8%
Latin 40
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4320
25.1%
- 3436
20.0%
2 2619
15.2%
1 2572
15.0%
9 1282
 
7.5%
8 610
 
3.5%
3 550
 
3.2%
6 479
 
2.8%
4 443
 
2.6%
7 442
 
2.6%
Other values (3) 443
 
2.6%
Latin
ValueCountFrequency (%)
V 8
20.0%
A 8
20.0%
L 8
20.0%
U 8
20.0%
E 8
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17236
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4320
25.1%
- 3436
19.9%
2 2619
15.2%
1 2572
14.9%
9 1282
 
7.4%
8 610
 
3.5%
3 550
 
3.2%
6 479
 
2.8%
4 443
 
2.6%
7 442
 
2.6%
Other values (8) 483
 
2.8%

관리사업등록번호
Text

Distinct1717
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T12:10:46.828391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters24164
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1708 ?
Unique (%)99.0%

Sample

1st rowMG014416000007
2nd rowMG014416000019
3rd rowMG014426000043
4th rowMG014411000026
5th rowMG014413001297
ValueCountFrequency (%)
mg014411000233 2
 
0.1%
mg014418000063 2
 
0.1%
mg014427000047 2
 
0.1%
mg014420000101 2
 
0.1%
mg014410000213 2
 
0.1%
mg014411000105 2
 
0.1%
mg014418000060 2
 
0.1%
mg014411000213 2
 
0.1%
mg014411000119 2
 
0.1%
mg014413001623 1
 
0.1%
Other values (1707) 1707
98.9%
2023-12-12T12:10:47.379980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7554
31.3%
1 4364
18.1%
4 4019
16.6%
M 1726
 
7.1%
G 1726
 
7.1%
2 1198
 
5.0%
3 1104
 
4.6%
7 546
 
2.3%
5 546
 
2.3%
6 477
 
2.0%
Other values (2) 904
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20712
85.7%
Uppercase Letter 3452
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7554
36.5%
1 4364
21.1%
4 4019
19.4%
2 1198
 
5.8%
3 1104
 
5.3%
7 546
 
2.6%
5 546
 
2.6%
6 477
 
2.3%
9 454
 
2.2%
8 450
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
M 1726
50.0%
G 1726
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20712
85.7%
Latin 3452
 
14.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7554
36.5%
1 4364
21.1%
4 4019
19.4%
2 1198
 
5.8%
3 1104
 
5.3%
7 546
 
2.6%
5 546
 
2.6%
6 477
 
2.3%
9 454
 
2.2%
8 450
 
2.2%
Latin
ValueCountFrequency (%)
M 1726
50.0%
G 1726
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7554
31.3%
1 4364
18.1%
4 4019
16.6%
M 1726
 
7.1%
G 1726
 
7.1%
2 1198
 
5.0%
3 1104
 
4.6%
7 546
 
2.3%
5 546
 
2.3%
6 477
 
2.0%
Other values (2) 904
 
3.7%

사업자상호(명칭)
Text

Distinct1628
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T12:10:47.800704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length7.1123986
Min length2

Characters and Unicode

Total characters12276
Distinct characters485
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1548 ?
Unique (%)89.7%

Sample

1st row삼화밧데리
2nd row삼양카인테리어
3rd row태안점 기아오토큐
4th row협신자동차써비스
5th row풍세자동차병원종합정비
ValueCountFrequency (%)
스피드메이트 21
 
1.0%
현대자동차 19
 
0.9%
모터스 16
 
0.8%
오토오아시스 15
 
0.7%
애니카랜드 14
 
0.7%
기아오토큐 13
 
0.6%
주식회사 12
 
0.6%
한국타이어 12
 
0.6%
센타 10
 
0.5%
케이지모빌리티 10
 
0.5%
Other values (1687) 1910
93.1%
2023-12-12T12:10:48.417130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
카 817
 
6.7%
스 484
 
3.9%
타 463
 
3.8%
비 372
 
3.0%
333
 
2.7%
센 331
 
2.7%
자 298
 
2.4%
동 294
 
2.4%
차 274
 
2.2%
점 254
 
2.1%
Other values (475) 8356
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11426
93.1%
Space Separator 333
 
2.7%
Uppercase Letter 220
 
1.8%
Close Punctuation 78
 
0.6%
Open Punctuation 78
 
0.6%
Lowercase Letter 72
 
0.6%
Decimal Number 45
 
0.4%
Other Punctuation 15
 
0.1%
Dash Punctuation 8
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
카 817
 
7.2%
스 484
 
4.2%
타 463
 
4.1%
비 372
 
3.3%
센 331
 
2.9%
자 298
 
2.6%
동 294
 
2.6%
차 274
 
2.4%
점 254
 
2.2%
이 246
 
2.2%
Other values (418) 7593
66.5%
Uppercase Letter
ValueCountFrequency (%)
S 32
14.5%
T 28
12.7%
K 17
 
7.7%
O 16
 
7.3%
M 15
 
6.8%
A 13
 
5.9%
R 13
 
5.9%
C 11
 
5.0%
J 10
 
4.5%
E 10
 
4.5%
Other values (13) 55
25.0%
Lowercase Letter
ValueCountFrequency (%)
r 11
15.3%
o 10
13.9%
t 9
12.5%
n 8
11.1%
e 6
8.3%
a 6
8.3%
i 6
8.3%
s 4
 
5.6%
c 3
 
4.2%
g 2
 
2.8%
Other values (7) 7
9.7%
Decimal Number
ValueCountFrequency (%)
1 13
28.9%
2 13
28.9%
3 5
 
11.1%
5 4
 
8.9%
4 4
 
8.9%
0 2
 
4.4%
8 2
 
4.4%
9 1
 
2.2%
6 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 9
60.0%
& 4
26.7%
, 2
 
13.3%
Space Separator
ValueCountFrequency (%)
333
100.0%
Close Punctuation
ValueCountFrequency (%)
) 78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11426
93.1%
Common 558
 
4.5%
Latin 292
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
카 817
 
7.2%
스 484
 
4.2%
타 463
 
4.1%
비 372
 
3.3%
센 331
 
2.9%
자 298
 
2.6%
동 294
 
2.6%
차 274
 
2.4%
점 254
 
2.2%
이 246
 
2.2%
Other values (418) 7593
66.5%
Latin
ValueCountFrequency (%)
S 32
 
11.0%
T 28
 
9.6%
K 17
 
5.8%
O 16
 
5.5%
M 15
 
5.1%
A 13
 
4.5%
R 13
 
4.5%
C 11
 
3.8%
r 11
 
3.8%
o 10
 
3.4%
Other values (30) 126
43.2%
Common
ValueCountFrequency (%)
333
59.7%
) 78
 
14.0%
( 78
 
14.0%
1 13
 
2.3%
2 13
 
2.3%
. 9
 
1.6%
- 8
 
1.4%
3 5
 
0.9%
5 4
 
0.7%
4 4
 
0.7%
Other values (7) 13
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11426
93.1%
ASCII 850
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
카 817
 
7.2%
스 484
 
4.2%
타 463
 
4.1%
비 372
 
3.3%
센 331
 
2.9%
자 298
 
2.6%
동 294
 
2.6%
차 274
 
2.4%
점 254
 
2.2%
이 246
 
2.2%
Other values (418) 7593
66.5%
ASCII
ValueCountFrequency (%)
333
39.2%
) 78
 
9.2%
( 78
 
9.2%
S 32
 
3.8%
T 28
 
3.3%
K 17
 
2.0%
O 16
 
1.9%
M 15
 
1.8%
A 13
 
1.5%
1 13
 
1.5%
Other values (47) 227
26.7%

사업자주소
Text

Distinct1674
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T12:10:48.932286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length23.072422
Min length10

Characters and Unicode

Total characters39823
Distinct characters299
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

Unique1625 ?
Unique (%)94.1%

Sample

1st row충청남도 금산군 금산읍 비호로 124
2nd row충청남도 금산군 금산읍 비호로 41
3rd row충청남도 태안군 태안읍 동백로 236
4th row충청남도 보령시 주교면 울계큰길 399
5th row충청남도 천안시 동남구 풍세면 풍세로 279
ValueCountFrequency (%)
충청남도 1717
 
19.9%
천안시 541
 
6.3%
서북구 281
 
3.3%
동남구 256
 
3.0%
아산시 193
 
2.2%
당진시 152
 
1.8%
서산시 142
 
1.6%
논산시 119
 
1.4%
보령시 104
 
1.2%
홍성군 86
 
1.0%
Other values (2485) 5018
58.3%
2023-12-12T12:10:49.713591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6892
 
17.3%
남 2046
 
5.1%
청 1818
 
4.6%
충 1814
 
4.6%
도 1734
 
4.4%
시 1370
 
3.4%
1 1270
 
3.2%
동 1201
 
3.0%
로 1183
 
3.0%
천 849
 
2.1%
Other values (289) 19646
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25089
63.0%
Space Separator 6892
 
17.3%
Decimal Number 5979
 
15.0%
Open Punctuation 722
 
1.8%
Close Punctuation 722
 
1.8%
Dash Punctuation 333
 
0.8%
Other Punctuation 82
 
0.2%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 2046
 
8.2%
청 1818
 
7.2%
충 1814
 
7.2%
도 1734
 
6.9%
시 1370
 
5.5%
동 1201
 
4.8%
로 1183
 
4.7%
천 849
 
3.4%
산 846
 
3.4%
안 725
 
2.9%
Other values (270) 11503
45.8%
Decimal Number
ValueCountFrequency (%)
1 1270
21.2%
2 796
13.3%
3 687
11.5%
4 582
9.7%
6 488
 
8.2%
0 483
 
8.1%
7 456
 
7.6%
5 456
 
7.6%
8 423
 
7.1%
9 338
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
A 1
25.0%
E 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 80
97.6%
. 2
 
2.4%
Space Separator
ValueCountFrequency (%)
6892
100.0%
Open Punctuation
ValueCountFrequency (%)
( 722
100.0%
Close Punctuation
ValueCountFrequency (%)
) 722
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 333
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25089
63.0%
Common 14730
37.0%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 2046
 
8.2%
청 1818
 
7.2%
충 1814
 
7.2%
도 1734
 
6.9%
시 1370
 
5.5%
동 1201
 
4.8%
로 1183
 
4.7%
천 849
 
3.4%
산 846
 
3.4%
안 725
 
2.9%
Other values (270) 11503
45.8%
Common
ValueCountFrequency (%)
6892
46.8%
1 1270
 
8.6%
2 796
 
5.4%
( 722
 
4.9%
) 722
 
4.9%
3 687
 
4.7%
4 582
 
4.0%
6 488
 
3.3%
0 483
 
3.3%
7 456
 
3.1%
Other values (6) 1632
 
11.1%
Latin
ValueCountFrequency (%)
B 2
50.0%
A 1
25.0%
E 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25089
63.0%
ASCII 14734
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6892
46.8%
1 1270
 
8.6%
2 796
 
5.4%
( 722
 
4.9%
) 722
 
4.9%
3 687
 
4.7%
4 582
 
4.0%
6 488
 
3.3%
0 483
 
3.3%
7 456
 
3.1%
Other values (9) 1636
 
11.1%
Hangul
ValueCountFrequency (%)
남 2046
 
8.2%
청 1818
 
7.2%
충 1814
 
7.2%
도 1734
 
6.9%
시 1370
 
5.5%
동 1201
 
4.8%
로 1183
 
4.7%
천 849
 
3.4%
산 846
 
3.4%
안 725
 
2.9%
Other values (270) 11503
45.8%

관리사업유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
자동차정비업
1726 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차정비업 1726
100.0%

Length

2023-12-12T12:10:49.955225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:10:50.122397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차정비업 1726
100.0%

정비형태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
자동차전문정비업
1726 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차전문정비업 1726
100.0%

Length

2023-12-12T12:10:50.302320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:10:50.470141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차전문정비업 1726
100.0%

대지면적
Text

MISSING 

Distinct945
Distinct (%)58.2%
Missing103
Missing (%)6.0%
Memory size13.6 KiB
2023-12-12T12:10:50.980025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.6019717
Min length1

Characters and Unicode

Total characters5846
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique728 ?
Unique (%)44.9%

Sample

1st row988
2nd row573
3rd row133
4th row198
5th row204
ValueCountFrequency (%)
100 27
 
1.7%
150 20
 
1.2%
120 18
 
1.1%
108 18
 
1.1%
104 17
 
1.0%
200 16
 
1.0%
105 16
 
1.0%
110 14
 
0.9%
102 13
 
0.8%
180 13
 
0.8%
Other values (934) 1448
89.4%
2023-12-12T12:10:51.785928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1222
20.9%
0 647
11.1%
2 581
9.9%
5 484
 
8.3%
4 476
 
8.1%
3 467
 
8.0%
6 441
 
7.5%
. 422
 
7.2%
9 385
 
6.6%
8 365
 
6.2%
Other values (2) 356
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5421
92.7%
Other Punctuation 422
 
7.2%
Space Separator 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1222
22.5%
0 647
11.9%
2 581
10.7%
5 484
 
8.9%
4 476
 
8.8%
3 467
 
8.6%
6 441
 
8.1%
9 385
 
7.1%
8 365
 
6.7%
7 353
 
6.5%
Other Punctuation
ValueCountFrequency (%)
. 422
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5846
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1222
20.9%
0 647
11.1%
2 581
9.9%
5 484
 
8.3%
4 476
 
8.1%
3 467
 
8.0%
6 441
 
7.5%
. 422
 
7.2%
9 385
 
6.6%
8 365
 
6.2%
Other values (2) 356
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5846
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1222
20.9%
0 647
11.1%
2 581
9.9%
5 484
 
8.3%
4 476
 
8.1%
3 467
 
8.0%
6 441
 
7.5%
. 422
 
7.2%
9 385
 
6.6%
8 365
 
6.2%
Other values (2) 356
 
6.1%

건물면적
Text

MISSING 

Distinct888
Distinct (%)54.7%
Missing102
Missing (%)5.9%
Memory size13.6 KiB
2023-12-12T12:10:52.285962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.5412562
Min length1

Characters and Unicode

Total characters5751
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique695 ?
Unique (%)42.8%

Sample

1st row121
2nd row230
3rd row64
4th row198
5th row49.06
ValueCountFrequency (%)
0 155
 
9.6%
99 23
 
1.4%
96 19
 
1.2%
100 17
 
1.1%
198 16
 
1.0%
120 16
 
1.0%
84 12
 
0.7%
98 12
 
0.7%
49 12
 
0.7%
66 11
 
0.7%
Other values (877) 1326
81.9%
2023-12-12T12:10:52.944086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 978
17.0%
. 706
12.3%
9 547
9.5%
0 524
9.1%
2 518
9.0%
4 456
7.9%
6 450
7.8%
5 440
7.7%
8 413
7.2%
3 393
6.8%
Other values (2) 326
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5040
87.6%
Other Punctuation 706
 
12.3%
Space Separator 5
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 978
19.4%
9 547
10.9%
0 524
10.4%
2 518
10.3%
4 456
9.0%
6 450
8.9%
5 440
8.7%
8 413
8.2%
3 393
7.8%
7 321
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 706
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5751
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 978
17.0%
. 706
12.3%
9 547
9.5%
0 524
9.1%
2 518
9.0%
4 456
7.9%
6 450
7.8%
5 440
7.7%
8 413
7.2%
3 393
6.8%
Other values (2) 326
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5751
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 978
17.0%
. 706
12.3%
9 547
9.5%
0 524
9.1%
2 518
9.0%
4 456
7.9%
6 450
7.8%
5 440
7.7%
8 413
7.2%
3 393
6.8%
Other values (2) 326
 
5.7%

Interactions

2023-12-12T12:10:44.079629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T12:10:44.250266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:10:44.437648image/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.
2023-12-12T12:10:44.587766image/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

순번상태정보등록년월일관리사업등록번호사업자상호(명칭)사업자주소관리사업유형정비형태대지면적건물면적
01영업1996-01-08MG014416000007삼화밧데리충청남도 금산군 금산읍 비호로 124자동차정비업자동차전문정비업988121
12영업1996-07-23MG014416000019삼양카인테리어충청남도 금산군 금산읍 비호로 41자동차정비업자동차전문정비업573230
23영업1997-02-01MG014426000043태안점 기아오토큐충청남도 태안군 태안읍 동백로 236자동차정비업자동차전문정비업<NA><NA>
34영업1997-04-30MG014411000026협신자동차써비스충청남도 보령시 주교면 울계큰길 399자동차정비업자동차전문정비업13364
45영업1997-05-30MG014413001297풍세자동차병원종합정비충청남도 천안시 동남구 풍세면 풍세로 279자동차정비업자동차전문정비업198198
56영업1997-06-19MG014418000073홍산정비공업사충청남도 부여군 홍산면 홍산로 63자동차정비업자동차전문정비업20449.06
67영업1997-07-08MG014419000047형제자동차공업사충청남도 논산시 양촌면 황산벌로 434자동차정비업자동차전문정비업873119
78영업1997-07-24MG014413001544기로카쎈타충청남도 천안시 서북구 입장면 입장로 45자동차정비업자동차전문정비업1950
89영업1997-07-24MG014410000076인주카포스충청남도 아산시 인주면 아산만로 1691자동차정비업자동차전문정비업2120
910영업1997-07-24MG014410000077현대제일카충청남도 아산시 인주면 현대로 1088자동차정비업자동차전문정비업114.50
순번상태정보등록년월일관리사업등록번호사업자상호(명칭)사업자주소관리사업유형정비형태대지면적건물면적
17161717영업2023-07-06MG014413001933EXTREME 퍼포먼스충청남도 천안시 동남구 목천읍 신계리 166번지 22호 101동 501호자동차정비업자동차전문정비업274130.87
17171718영업2023-07-17MG014413001934한국타이어 신방점충청남도 천안시 동남구 풍세로 636, 2동(신방동)자동차정비업자동차전문정비업82.7882.78
17181719영업#VALUE!MG014418000109모든카센타충청남도 부여군 규암면 흥수로 809자동차정비업자동차전문정비업459112.68
17191720영업#VALUE!MG014422000028김종민카충청남도 청양군 청양읍 중앙로 66자동차정비업자동차전문정비업10020
17201721영업#VALUE!MG014422000040금정공업사충청남도 청양군 남양면 충절로 768-7자동차정비업자동차전문정비업25030
17211722영업#VALUE!MG014422000046누리카충청남도 청양군 정산면 충의로 1719-1자동차정비업자동차전문정비업5030
17221723영업#VALUE!MG014422000043영원카서비스충청남도 청양군 화성면 산정리 174번지 14호자동차정비업자동차전문정비업23070
17231724영업#VALUE!MG014422000044현대카충청남도 청양군 정산면 서정리 231번지 1호자동차정비업자동차전문정비업8050
17241725영업#VALUE!MG014422000045장평카충청남도 청양군 청양읍 송방리 178번지 2호자동차정비업자동차전문정비업250120
17251726영업#VALUE!MG014422000042남양카충청남도 청양군 청양읍 읍내리 106번지 18호자동차정비업자동차전문정비업536025