Overview

Dataset statistics

Number of variables20
Number of observations10000
Missing cells39006
Missing cells (%)19.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory173.0 B

Variable types

Text7
Categorical4
Numeric3
DateTime5
Unsupported1

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다.(기관에서 등록한 데이터를 취합한 것으로 개별 파일별 갱신시점이 다름) 전국데이터의 경우 API 서비스를 이용해주시기 바랍니다.
Author지방자치단체
URLhttps://www.data.go.kr/data/15028204/standard.do

Alerts

휴업종료일자 has constant value ""Constant
운영시작시각 is highly overall correlated with 운영종료시각High correlation
운영종료시각 is highly overall correlated with 운영시작시각High correlation
자동차정비업체종류 is highly imbalanced (60.3%)Imbalance
영업상태 is highly imbalanced (82.9%)Imbalance
운영시작시각 is highly imbalanced (55.4%)Imbalance
운영종료시각 is highly imbalanced (64.8%)Imbalance
소재지도로명주소 has 241 (2.4%) missing valuesMissing
소재지지번주소 has 6454 (64.5%) missing valuesMissing
폐업일자 has 9759 (97.6%) missing valuesMissing
휴업시작일자 has 9980 (99.8%) missing valuesMissing
휴업종료일자 has 9999 (> 99.9%) missing valuesMissing
전화번호 has 2573 (25.7%) missing valuesMissing
면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 10:07:16.049821
Analysis finished2024-05-11 10:07:27.779423
Duration11.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자동차정비업체명
Text

Distinct8523
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:07:28.275799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length7.7879
Min length2

Characters and Unicode

Total characters77879
Distinct characters710
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7508 ?
Unique (%)75.1%

Sample

1st row정직 카센타
2nd row호남마스타카
3rd row아민모터스
4th row동도카마스타
5th row경복카써비스
ValueCountFrequency (%)
주식회사 145
 
1.2%
현대자동차 120
 
1.0%
애니카랜드 92
 
0.8%
스피드메이트 87
 
0.7%
오토오아시스 82
 
0.7%
모터스 77
 
0.6%
기아오토큐 72
 
0.6%
한국타이어 53
 
0.4%
티스테이션 47
 
0.4%
카 45
 
0.4%
Other values (8749) 11323
93.2%
2024-05-11T10:07:29.583121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 3247
 
4.2%
카 3138
 
4.0%
스 2946
 
3.8%
비 2886
 
3.7%
자 2882
 
3.7%
차 2820
 
3.6%
사 2539
 
3.3%
공 2268
 
2.9%
업 2203
 
2.8%
2152
 
2.8%
Other values (700) 50798
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71540
91.9%
Space Separator 2152
 
2.8%
Uppercase Letter 1378
 
1.8%
Close Punctuation 788
 
1.0%
Open Punctuation 785
 
1.0%
Decimal Number 485
 
0.6%
Lowercase Letter 423
 
0.5%
Other Symbol 227
 
0.3%
Other Punctuation 63
 
0.1%
Dash Punctuation 35
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3247
 
4.5%
카 3138
 
4.4%
스 2946
 
4.1%
비 2886
 
4.0%
자 2882
 
4.0%
차 2820
 
3.9%
사 2539
 
3.5%
공 2268
 
3.2%
업 2203
 
3.1%
정 2103
 
2.9%
Other values (625) 44508
62.2%
Uppercase Letter
ValueCountFrequency (%)
S 141
 
10.2%
O 134
 
9.7%
M 127
 
9.2%
T 123
 
8.9%
K 98
 
7.1%
R 91
 
6.6%
A 86
 
6.2%
C 81
 
5.9%
J 55
 
4.0%
I 53
 
3.8%
Other values (16) 389
28.2%
Lowercase Letter
ValueCountFrequency (%)
o 65
15.4%
t 58
13.7%
r 41
9.7%
s 41
9.7%
a 38
9.0%
e 34
8.0%
i 26
 
6.1%
n 22
 
5.2%
m 17
 
4.0%
h 14
 
3.3%
Other values (14) 67
15.8%
Decimal Number
ValueCountFrequency (%)
1 236
48.7%
3 64
 
13.2%
2 62
 
12.8%
5 23
 
4.7%
7 21
 
4.3%
4 20
 
4.1%
9 18
 
3.7%
0 18
 
3.7%
6 15
 
3.1%
8 7
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 34
54.0%
& 18
28.6%
, 6
 
9.5%
/ 2
 
3.2%
? 2
 
3.2%
' 1
 
1.6%
Space Separator
ValueCountFrequency (%)
2152
100.0%
Close Punctuation
ValueCountFrequency (%)
) 788
100.0%
Open Punctuation
ValueCountFrequency (%)
( 785
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71766
92.2%
Common 4311
 
5.5%
Latin 1801
 
2.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3247
 
4.5%
카 3138
 
4.4%
스 2946
 
4.1%
비 2886
 
4.0%
자 2882
 
4.0%
차 2820
 
3.9%
사 2539
 
3.5%
공 2268
 
3.2%
업 2203
 
3.1%
정 2103
 
2.9%
Other values (625) 44734
62.3%
Latin
ValueCountFrequency (%)
S 141
 
7.8%
O 134
 
7.4%
M 127
 
7.1%
T 123
 
6.8%
K 98
 
5.4%
R 91
 
5.1%
A 86
 
4.8%
C 81
 
4.5%
o 65
 
3.6%
t 58
 
3.2%
Other values (40) 797
44.3%
Common
ValueCountFrequency (%)
2152
49.9%
) 788
 
18.3%
( 785
 
18.2%
1 236
 
5.5%
3 64
 
1.5%
2 62
 
1.4%
- 35
 
0.8%
. 34
 
0.8%
5 23
 
0.5%
7 21
 
0.5%
Other values (14) 111
 
2.6%
Han
ValueCountFrequency (%)
時 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71539
91.9%
ASCII 6110
 
7.8%
None 228
 
0.3%
Punctuation 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 3247
 
4.5%
카 3138
 
4.4%
스 2946
 
4.1%
비 2886
 
4.0%
자 2882
 
4.0%
차 2820
 
3.9%
사 2539
 
3.5%
공 2268
 
3.2%
업 2203
 
3.1%
정 2103
 
2.9%
Other values (624) 44507
62.2%
ASCII
ValueCountFrequency (%)
2152
35.2%
) 788
 
12.9%
( 785
 
12.8%
1 236
 
3.9%
S 141
 
2.3%
O 134
 
2.2%
M 127
 
2.1%
T 123
 
2.0%
K 98
 
1.6%
R 91
 
1.5%
Other values (62) 1435
23.5%
None
ValueCountFrequency (%)
㈜ 227
99.6%
２ 1
 
0.4%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%
CJK
ValueCountFrequency (%)
時 1
100.0%

자동차정비업체종류
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
8098 
1
1259 
2
 
555
4
 
65
99
 
23

Length

Max length2
Median length1
Mean length1.0023
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row2
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 8098
81.0%
1 1259
 
12.6%
2 555
 
5.5%
4 65
 
0.7%
99 23
 
0.2%

Length

2024-05-11T10:07:30.099582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:07:30.550184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8098
81.0%
1 1259
 
12.6%
2 555
 
5.5%
4 65
 
0.7%
99 23
 
0.2%

소재지도로명주소
Text

MISSING 

Distinct9374
Distinct (%)96.1%
Missing241
Missing (%)2.4%
Memory size156.2 KiB
2024-05-11T10:07:31.266966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length22.467466
Min length12

Characters and Unicode

Total characters219260
Distinct characters553
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8998 ?
Unique (%)92.2%

Sample

1st row전라북도 고창군 고창읍 녹두로 1290
2nd row전북특별자치도 정읍시 수성3로 39-4(수성동)
3rd row인천광역시 부평구 가좌로96번길 62-1(십정동)
4th row대구광역시 동구 안심로 32(용계동)
5th row경기도 남양주시 진접읍 경복대로 404
ValueCountFrequency (%)
경기도 1933
 
4.4%
서울특별시 1073
 
2.4%
경상남도 599
 
1.4%
경상북도 589
 
1.3%
충청남도 553
 
1.3%
강원도 520
 
1.2%
인천광역시 513
 
1.2%
전라북도 504
 
1.1%
전라남도 499
 
1.1%
부산광역시 495
 
1.1%
Other values (13150) 36722
83.5%
2024-05-11T10:07:33.072498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34241
 
15.6%
시 8973
 
4.1%
로 8676
 
4.0%
동 7640
 
3.5%
1 7160
 
3.3%
도 6709
 
3.1%
구 5788
 
2.6%
) 5665
 
2.6%
( 5665
 
2.6%
2 4555
 
2.1%
Other values (543) 124188
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138113
63.0%
Space Separator 34241
 
15.6%
Decimal Number 33123
 
15.1%
Close Punctuation 5666
 
2.6%
Open Punctuation 5666
 
2.6%
Dash Punctuation 1685
 
0.8%
Other Punctuation 714
 
0.3%
Uppercase Letter 46
 
< 0.1%
Math Symbol 4
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 8973
 
6.5%
로 8676
 
6.3%
동 7640
 
5.5%
도 6709
 
4.9%
구 5788
 
4.2%
경 3555
 
2.6%
길 3252
 
2.4%
광 3248
 
2.4%
산 3181
 
2.3%
남 3110
 
2.3%
Other values (508) 83981
60.8%
Uppercase Letter
ValueCountFrequency (%)
B 14
30.4%
A 11
23.9%
C 8
17.4%
E 2
 
4.3%
K 2
 
4.3%
D 2
 
4.3%
F 1
 
2.2%
H 1
 
2.2%
M 1
 
2.2%
T 1
 
2.2%
Other values (3) 3
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 7160
21.6%
2 4555
13.8%
3 3702
11.2%
4 3156
9.5%
5 2894
8.7%
6 2641
 
8.0%
7 2364
 
7.1%
8 2318
 
7.0%
0 2256
 
6.8%
9 2077
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 705
98.7%
. 8
 
1.1%
· 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 5665
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5665
> 99.9%
[ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
c 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
34241
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1685
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138113
63.0%
Common 81099
37.0%
Latin 48
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 8973
 
6.5%
로 8676
 
6.3%
동 7640
 
5.5%
도 6709
 
4.9%
구 5788
 
4.2%
경 3555
 
2.6%
길 3252
 
2.4%
광 3248
 
2.4%
산 3181
 
2.3%
남 3110
 
2.3%
Other values (508) 83981
60.8%
Common
ValueCountFrequency (%)
34241
42.2%
1 7160
 
8.8%
) 5665
 
7.0%
( 5665
 
7.0%
2 4555
 
5.6%
3 3702
 
4.6%
4 3156
 
3.9%
5 2894
 
3.6%
6 2641
 
3.3%
7 2364
 
2.9%
Other values (10) 9056
 
11.2%
Latin
ValueCountFrequency (%)
B 14
29.2%
A 11
22.9%
C 8
16.7%
E 2
 
4.2%
K 2
 
4.2%
D 2
 
4.2%
F 1
 
2.1%
H 1
 
2.1%
c 1
 
2.1%
e 1
 
2.1%
Other values (5) 5
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138113
63.0%
ASCII 81146
37.0%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34241
42.2%
1 7160
 
8.8%
) 5665
 
7.0%
( 5665
 
7.0%
2 4555
 
5.6%
3 3702
 
4.6%
4 3156
 
3.9%
5 2894
 
3.6%
6 2641
 
3.3%
7 2364
 
2.9%
Other values (24) 9103
 
11.2%
Hangul
ValueCountFrequency (%)
시 8973
 
6.5%
로 8676
 
6.3%
동 7640
 
5.5%
도 6709
 
4.9%
구 5788
 
4.2%
경 3555
 
2.6%
길 3252
 
2.4%
광 3248
 
2.4%
산 3181
 
2.3%
남 3110
 
2.3%
Other values (508) 83981
60.8%
None
ValueCountFrequency (%)
· 1
100.0%

소재지지번주소
Text

MISSING 

Distinct3503
Distinct (%)98.8%
Missing6454
Missing (%)64.5%
Memory size156.2 KiB
2024-05-11T10:07:33.998534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length38
Mean length20.345742
Min length14

Characters and Unicode

Total characters72146
Distinct characters333
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3461 ?
Unique (%)97.6%

Sample

1st row전라북도 고창군 고창읍 읍내리 1037-1
2nd row대구광역시 동구 용계동 763-20
3rd row전라북도 군산시 소룡동 1553-3
4th row인천광역시 서구 가좌동 585-76
5th row전북특별자치도 군산시 대야면 지경리 699-243
ValueCountFrequency (%)
경기도 750
 
4.8%
강원도 288
 
1.8%
경상북도 259
 
1.6%
서울특별시 246
 
1.6%
충청북도 221
 
1.4%
인천광역시 204
 
1.3%
전주시 191
 
1.2%
전북특별자치도 189
 
1.2%
전라북도 189
 
1.2%
서구 178
 
1.1%
Other values (5032) 13017
82.7%
2024-05-11T10:07:35.130737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12186
 
16.9%
시 3147
 
4.4%
- 3070
 
4.3%
동 3067
 
4.3%
1 3045
 
4.2%
도 2592
 
3.6%
2 2034
 
2.8%
구 1913
 
2.7%
3 1651
 
2.3%
4 1496
 
2.1%
Other values (323) 37945
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41514
57.5%
Decimal Number 15285
 
21.2%
Space Separator 12186
 
16.9%
Dash Punctuation 3071
 
4.3%
Other Punctuation 60
 
0.1%
Close Punctuation 11
 
< 0.1%
Open Punctuation 10
 
< 0.1%
Uppercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3147
 
7.6%
동 3067
 
7.4%
도 2592
 
6.2%
구 1913
 
4.6%
경 1297
 
3.1%
광 1063
 
2.6%
북 1027
 
2.5%
리 985
 
2.4%
전 961
 
2.3%
산 954
 
2.3%
Other values (298) 24508
59.0%
Decimal Number
ValueCountFrequency (%)
1 3045
19.9%
2 2034
13.3%
3 1651
10.8%
4 1496
9.8%
5 1391
9.1%
6 1270
8.3%
7 1203
 
7.9%
8 1106
 
7.2%
9 1067
 
7.0%
0 1022
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
22.2%
D 2
22.2%
E 1
11.1%
M 1
11.1%
A 1
11.1%
R 1
11.1%
T 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 57
95.0%
. 2
 
3.3%
· 1
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 3070
> 99.9%
― 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41512
57.5%
Common 30623
42.4%
Latin 9
 
< 0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3147
 
7.6%
동 3067
 
7.4%
도 2592
 
6.2%
구 1913
 
4.6%
경 1297
 
3.1%
광 1063
 
2.6%
북 1027
 
2.5%
리 985
 
2.4%
전 961
 
2.3%
산 954
 
2.3%
Other values (296) 24506
59.0%
Common
ValueCountFrequency (%)
12186
39.8%
- 3070
 
10.0%
1 3045
 
9.9%
2 2034
 
6.6%
3 1651
 
5.4%
4 1496
 
4.9%
5 1391
 
4.5%
6 1270
 
4.1%
7 1203
 
3.9%
8 1106
 
3.6%
Other values (8) 2171
 
7.1%
Latin
ValueCountFrequency (%)
B 2
22.2%
D 2
22.2%
E 1
11.1%
M 1
11.1%
A 1
11.1%
R 1
11.1%
T 1
11.1%
Han
ValueCountFrequency (%)
華 1
50.0%
山 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41512
57.5%
ASCII 30630
42.5%
CJK 2
 
< 0.1%
None 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12186
39.8%
- 3070
 
10.0%
1 3045
 
9.9%
2 2034
 
6.6%
3 1651
 
5.4%
4 1496
 
4.9%
5 1391
 
4.5%
6 1270
 
4.1%
7 1203
 
3.9%
8 1106
 
3.6%
Other values (13) 2178
 
7.1%
Hangul
ValueCountFrequency (%)
시 3147
 
7.6%
동 3067
 
7.4%
도 2592
 
6.2%
구 1913
 
4.6%
경 1297
 
3.1%
광 1063
 
2.6%
북 1027
 
2.5%
리 985
 
2.4%
전 961
 
2.3%
산 954
 
2.3%
Other values (296) 24506
59.0%
None
ValueCountFrequency (%)
· 1
100.0%
Punctuation
ValueCountFrequency (%)
― 1
100.0%
CJK
ValueCountFrequency (%)
華 1
50.0%
山 1
50.0%

위도
Real number (ℝ)

Distinct9573
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.506314
Minimum33.219634
Maximum38.451516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:07:35.570553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.219634
5-th percentile34.891288
Q135.5732
median36.775988
Q337.486334
95-th percentile37.766368
Maximum38.451516
Range5.2318817
Interquartile range (IQR)1.9131343

Descriptive statistics

Standard deviation1.0638628
Coefficient of variation (CV)0.029141884
Kurtosis-0.73921053
Mean36.506314
Median Absolute Deviation (MAD)0.82430868
Skewness-0.48567142
Sum365063.14
Variance1.131804
MonotonicityNot monotonic
2024-05-11T10:07:35.959772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.594188 17
 
0.2%
35.229698 10
 
0.1%
37.461834 4
 
< 0.1%
35.59812171 4
 
< 0.1%
38.109648 3
 
< 0.1%
34.39677079 3
 
< 0.1%
37.32230628 3
 
< 0.1%
34.59652038 3
 
< 0.1%
37.76219462 3
 
< 0.1%
37.55358054 3
 
< 0.1%
Other values (9563) 9947
99.5%
ValueCountFrequency (%)
33.2196345 1
< 0.1%
33.22324681 1
< 0.1%
33.22587135 2
< 0.1%
33.2275831 1
< 0.1%
33.24833803 2
< 0.1%
33.24834527 1
< 0.1%
33.24853417 1
< 0.1%
33.25021318 1
< 0.1%
33.25043125 1
< 0.1%
33.25073462 1
< 0.1%
ValueCountFrequency (%)
38.4515162 1
< 0.1%
38.38903591 1
< 0.1%
38.389008 1
< 0.1%
38.388145 1
< 0.1%
38.3820022 1
< 0.1%
38.38075469 1
< 0.1%
38.38035937 1
< 0.1%
38.3802139 1
< 0.1%
38.266363 1
< 0.1%
38.2459431 1
< 0.1%

경도
Real number (ℝ)

Distinct9566
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.54032
Minimum125.70026
Maximum130.91266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:07:36.285349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum125.70026
5-th percentile126.60932
Q1126.88026
median127.13756
Q3128.34783
95-th percentile129.1577
Maximum130.91266
Range5.2124039
Interquartile range (IQR)1.4675644

Descriptive statistics

Standard deviation0.86651179
Coefficient of variation (CV)0.0067940226
Kurtosis-0.79305899
Mean127.54032
Median Absolute Deviation (MAD)0.38667305
Skewness0.77147173
Sum1275403.2
Variance0.75084268
MonotonicityNot monotonic
2024-05-11T10:07:36.567625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.073986 17
 
0.2%
128.915912 10
 
0.1%
126.6845797 4
 
< 0.1%
127.035374 4
 
< 0.1%
126.6931254 3
 
< 0.1%
127.0932438 3
 
< 0.1%
126.3131668 3
 
< 0.1%
126.8080053 3
 
< 0.1%
126.5047273 3
 
< 0.1%
126.8650142 3
 
< 0.1%
Other values (9556) 9947
99.5%
ValueCountFrequency (%)
125.7002591 1
< 0.1%
125.7008875 1
< 0.1%
125.9299351 1
< 0.1%
126.1142946 1
< 0.1%
126.1261781 2
< 0.1%
126.1468199 1
< 0.1%
126.2528807 1
< 0.1%
126.2569985 2
< 0.1%
126.2574332 1
< 0.1%
126.2604078 1
< 0.1%
ValueCountFrequency (%)
130.912663 1
< 0.1%
130.8875008 1
< 0.1%
129.5482168 1
< 0.1%
129.470124 1
< 0.1%
129.4660299801 1
< 0.1%
129.462703 1
< 0.1%
129.4425432 1
< 0.1%
129.4414972 1
< 0.1%
129.4410455 1
< 0.1%
129.4345113 1
< 0.1%

사업등록일자
Date

Distinct4958
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1967-02-10 00:00:00
Maximum2024-01-17 00:00:00
2024-05-11T10:07:36.893589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:37.492621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

면적
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

영업상태
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9567 
3
 
406
2
 
27

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 9567
95.7%
3 406
 
4.1%
2 27
 
0.3%

Length

2024-05-11T10:07:37.878857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:07:38.087672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9567
95.7%
3 406
 
4.1%
2 27
 
0.3%

폐업일자
Date

MISSING 

Distinct219
Distinct (%)90.9%
Missing9759
Missing (%)97.6%
Memory size156.2 KiB
Minimum2000-03-09 00:00:00
Maximum2023-11-13 00:00:00
2024-05-11T10:07:38.424063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:38.885579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct19
Distinct (%)95.0%
Missing9980
Missing (%)99.8%
Memory size156.2 KiB
Minimum2013-06-25 00:00:00
Maximum2023-11-21 00:00:00
2024-05-11T10:07:39.295104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:39.655950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

휴업종료일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
Minimum2024-09-17 00:00:00
Maximum2024-09-17 00:00:00
2024-05-11T10:07:39.958816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:40.347058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

운영시작시각
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
09:00
5316 
<NA>
4462 
10:00
 
153
08:30
 
51
08:00
 
16

Length

Max length5
Median length5
Mean length4.5538
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09:00
2nd row<NA>
3rd row09:00
4th row<NA>
5th row09:00

Common Values

ValueCountFrequency (%)
09:00 5316
53.2%
<NA> 4462
44.6%
10:00 153
 
1.5%
08:30 51
 
0.5%
08:00 16
 
0.2%
00:00 2
 
< 0.1%

Length

2024-05-11T10:07:40.734017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:07:41.029145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09:00 5316
53.2%
na 4462
44.6%
10:00 153
 
1.5%
08:30 51
 
0.5%
08:00 16
 
0.2%
00:00 2
 
< 0.1%

운영종료시각
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
18:00
5420 
<NA>
4432 
19:30
 
52
19:00
 
45
20:00
 
44
Other values (4)
 
7

Length

Max length5
Median length5
Mean length4.5568
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row18:00
2nd row<NA>
3rd row18:00
4th row<NA>
5th row18:00

Common Values

ValueCountFrequency (%)
18:00 5420
54.2%
<NA> 4432
44.3%
19:30 52
 
0.5%
19:00 45
 
0.4%
20:00 44
 
0.4%
21:00 3
 
< 0.1%
18:30 2
 
< 0.1%
00:00 1
 
< 0.1%
17:00 1
 
< 0.1%

Length

2024-05-11T10:07:41.410968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:07:41.924157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18:00 5420
54.2%
na 4432
44.3%
19:30 52
 
0.5%
19:00 45
 
0.4%
20:00 44
 
0.4%
21:00 3
 
< 0.1%
18:30 2
 
< 0.1%
00:00 1
 
< 0.1%
17:00 1
 
< 0.1%

전화번호
Text

MISSING 

Distinct6802
Distinct (%)91.6%
Missing2573
Missing (%)25.7%
Memory size156.2 KiB
2024-05-11T10:07:42.692528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.905211
Min length9

Characters and Unicode

Total characters88420
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

Unique6379 ?
Unique (%)85.9%

Sample

1st row063-561-6066
2nd row063-538-0244
3rd row032-572-0223
4th row031-572-5597
5th row063-911-5400
ValueCountFrequency (%)
041-540-2746 83
 
1.1%
032-625-3986 62
 
0.8%
041-350-4525 12
 
0.2%
000-000-0000 11
 
0.1%
051-000-0000 10
 
0.1%
000-0000-0000 10
 
0.1%
02-0000-0000 9
 
0.1%
031-0000-0000 6
 
0.1%
061-000-0000 6
 
0.1%
063-211-3150 3
 
< 0.1%
Other values (6792) 7215
97.1%
2024-05-11T10:07:44.232457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 14851
16.8%
0 12488
14.1%
3 9917
11.2%
5 8449
9.6%
2 8410
9.5%
1 6961
7.9%
4 6651
7.5%
6 6443
7.3%
8 5316
 
6.0%
7 5048
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73569
83.2%
Dash Punctuation 14851
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12488
17.0%
3 9917
13.5%
5 8449
11.5%
2 8410
11.4%
1 6961
9.5%
4 6651
9.0%
6 6443
8.8%
8 5316
7.2%
7 5048
6.9%
9 3886
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 14851
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 14851
16.8%
0 12488
14.1%
3 9917
11.2%
5 8449
9.6%
2 8410
9.5%
1 6961
7.9%
4 6651
7.5%
6 6443
7.3%
8 5316
 
6.0%
7 5048
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 14851
16.8%
0 12488
14.1%
3 9917
11.2%
5 8449
9.6%
2 8410
9.5%
1 6961
7.9%
4 6651
7.5%
6 6443
7.3%
8 5316
 
6.0%
7 5048
 
5.7%

관리기관명
Text

Distinct424
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:07:45.024276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length9.5878
Min length3

Characters and Unicode

Total characters95878
Distinct characters161
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.1%

Sample

1st row전라북도 고창군
2nd row전북특별자치도 정읍시청
3rd row인천광역시 부평구
4th row대구광역시 동구청
5th row경기도 남양주시
ValueCountFrequency (%)
경기도 1843
 
8.6%
서울특별시 1060
 
5.0%
경상남도 617
 
2.9%
충청남도 599
 
2.8%
경상북도 567
 
2.7%
인천광역시 517
 
2.4%
강원도 517
 
2.4%
부산광역시 510
 
2.4%
전라남도 508
 
2.4%
전라북도 507
 
2.4%
Other values (377) 14119
66.1%
2024-05-11T10:07:46.298266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11364
 
11.9%
시 9005
 
9.4%
청 6360
 
6.6%
도 6343
 
6.6%
구 4374
 
4.6%
경 3216
 
3.4%
광 3128
 
3.3%
역 2466
 
2.6%
남 2386
 
2.5%
북 2205
 
2.3%
Other values (151) 45031
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84491
88.1%
Space Separator 11364
 
11.9%
Decimal Number 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9005
 
10.7%
청 6360
 
7.5%
도 6343
 
7.5%
구 4374
 
5.2%
경 3216
 
3.8%
광 3128
 
3.7%
역 2466
 
2.9%
남 2386
 
2.8%
북 2205
 
2.6%
주 2074
 
2.5%
Other values (147) 42934
50.8%
Decimal Number
ValueCountFrequency (%)
1 10
43.5%
2 7
30.4%
3 6
26.1%
Space Separator
ValueCountFrequency (%)
11364
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84491
88.1%
Common 11387
 
11.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9005
 
10.7%
청 6360
 
7.5%
도 6343
 
7.5%
구 4374
 
5.2%
경 3216
 
3.8%
광 3128
 
3.7%
역 2466
 
2.9%
남 2386
 
2.8%
북 2205
 
2.6%
주 2074
 
2.5%
Other values (147) 42934
50.8%
Common
ValueCountFrequency (%)
11364
99.8%
1 10
 
0.1%
2 7
 
0.1%
3 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84491
88.1%
ASCII 11387
 
11.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11364
99.8%
1 10
 
0.1%
2 7
 
0.1%
3 6
 
0.1%
Hangul
ValueCountFrequency (%)
시 9005
 
10.7%
청 6360
 
7.5%
도 6343
 
7.5%
구 4374
 
5.2%
경 3216
 
3.8%
광 3128
 
3.7%
역 2466
 
2.9%
남 2386
 
2.8%
북 2205
 
2.6%
주 2074
 
2.5%
Other values (147) 42934
50.8%

관리기관전화번호
Text

Distinct507
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:07:46.986451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.0114
Min length11

Characters and Unicode

Total characters120114
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

Unique91 ?
Unique (%)0.9%

Sample

1st row063-560-2418
2nd row063-539-5933
3rd row032-509-6760
4th row053-662-3047
5th row031-590-2133
ValueCountFrequency (%)
041-521-5856 150
 
1.5%
031-324-4557 141
 
1.4%
063-859-5564 131
 
1.3%
033-737-3522 128
 
1.3%
063-270-6382 127
 
1.3%
031-228-4316 115
 
1.1%
055-330-3543 109
 
1.1%
042-608-5276 105
 
1.1%
063-454-5772 103
 
1.0%
033-640-5383 87
 
0.9%
Other values (497) 8804
88.0%
2024-05-11T10:07:48.305269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 20000
16.7%
0 18042
15.0%
3 14302
11.9%
5 12062
10.0%
2 11443
9.5%
6 9845
8.2%
4 9465
7.9%
1 8442
7.0%
7 6035
 
5.0%
8 5545
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100114
83.3%
Dash Punctuation 20000
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18042
18.0%
3 14302
14.3%
5 12062
12.0%
2 11443
11.4%
6 9845
9.8%
4 9465
9.5%
1 8442
8.4%
7 6035
 
6.0%
8 5545
 
5.5%
9 4933
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120114
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 20000
16.7%
0 18042
15.0%
3 14302
11.9%
5 12062
10.0%
2 11443
9.5%
6 9845
8.2%
4 9465
7.9%
1 8442
7.0%
7 6035
 
5.0%
8 5545
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 20000
16.7%
0 18042
15.0%
3 14302
11.9%
5 12062
10.0%
2 11443
9.5%
6 9845
8.2%
4 9465
7.9%
1 8442
7.0%
7 6035
 
5.0%
8 5545
 
4.6%

데이터기준일자
Date

Distinct166
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-10 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T10:07:48.926597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:49.625834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

Distinct244
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3315550.9
Minimum1613000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:07:50.129020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1613000
5-th percentile1613000
Q11613000
median3600000
Q34490000
95-th percentile5450000
Maximum6520000
Range4907000
Interquartile range (IQR)2877000

Descriptive statistics

Standard deviation1411586.4
Coefficient of variation (CV)0.42574717
Kurtosis-1.2954566
Mean3315550.9
Median Absolute Deviation (MAD)1220000
Skewness0.0088201876
Sum3.3155508 × 1010
Variance1.9925761 × 1012
MonotonicityNot monotonic
2024-05-11T10:07:50.578514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1613000 3568
35.7%
4490000 150
 
1.5%
4050000 141
 
1.4%
5710000 135
 
1.4%
3940000 133
 
1.3%
3740000 115
 
1.1%
5350000 109
 
1.1%
4641000 102
 
1.0%
3680000 101
 
1.0%
4640000 89
 
0.9%
Other values (234) 5357
53.6%
ValueCountFrequency (%)
1613000 3568
35.7%
3000000 4
 
< 0.1%
3010000 4
 
< 0.1%
3020000 12
 
0.1%
3030000 60
 
0.6%
3040000 18
 
0.2%
3050000 21
 
0.2%
3060000 55
 
0.5%
3070000 19
 
0.2%
3080000 17
 
0.2%
ValueCountFrequency (%)
6520000 16
 
0.2%
6510000 59
0.6%
6500000 19
 
0.2%
5710000 135
1.4%
5700000 30
 
0.3%
5690000 31
 
0.3%
5680000 54
 
0.5%
5600000 61
0.6%
5590000 53
 
0.5%
5570000 10
 
0.1%

제공기관명
Text

Distinct244
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:07:51.421955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.1229
Min length5

Characters and Unicode

Total characters71229
Distinct characters139
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row전북특별자치도 고창군
2nd row전북특별자치도 정읍시
3rd row국토교통부
4th row대구광역시 동구
5th row국토교통부
ValueCountFrequency (%)
국토교통부 3568
21.8%
경기도 1342
 
8.2%
서울특별시 550
 
3.4%
충청남도 458
 
2.8%
경상북도 393
 
2.4%
경상남도 380
 
2.3%
전북특별자치도 330
 
2.0%
인천광역시 310
 
1.9%
대구광역시 306
 
1.9%
전라북도 305
 
1.9%
Other values (200) 8440
51.5%
2024-05-11T10:07:52.702291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6382
 
9.0%
시 5703
 
8.0%
도 4424
 
6.2%
부 4014
 
5.6%
통 3590
 
5.0%
국 3568
 
5.0%
교 3568
 
5.0%
토 3568
 
5.0%
구 2381
 
3.3%
경 2235
 
3.1%
Other values (129) 31796
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64847
91.0%
Space Separator 6382
 
9.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 5703
 
8.8%
도 4424
 
6.8%
부 4014
 
6.2%
통 3590
 
5.5%
국 3568
 
5.5%
교 3568
 
5.5%
토 3568
 
5.5%
구 2381
 
3.7%
경 2235
 
3.4%
광 1810
 
2.8%
Other values (128) 29986
46.2%
Space Separator
ValueCountFrequency (%)
6382
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64847
91.0%
Common 6382
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 5703
 
8.8%
도 4424
 
6.8%
부 4014
 
6.2%
통 3590
 
5.5%
국 3568
 
5.5%
교 3568
 
5.5%
토 3568
 
5.5%
구 2381
 
3.7%
경 2235
 
3.4%
광 1810
 
2.8%
Other values (128) 29986
46.2%
Common
ValueCountFrequency (%)
6382
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64847
91.0%
ASCII 6382
 
9.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6382
100.0%
Hangul
ValueCountFrequency (%)
시 5703
 
8.8%
도 4424
 
6.8%
부 4014
 
6.2%
통 3590
 
5.5%
국 3568
 
5.5%
교 3568
 
5.5%
토 3568
 
5.5%
구 2381
 
3.7%
경 2235
 
3.4%
광 1810
 
2.8%
Other values (128) 29986
46.2%

Interactions

2024-05-11T10:07:24.919049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:22.415736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:23.740382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:25.189587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:22.912714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:24.134680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:25.467623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:23.325570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:07:24.502506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T10:07:53.267879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자동차정비업체종류위도경도영업상태휴업시작일자운영시작시각운영종료시각제공기관코드
자동차정비업체종류1.0000.1580.1050.0281.0000.0000.0400.141
위도0.1581.0000.5300.1350.8930.4340.1470.776
경도0.1050.5301.0000.2510.9400.3540.1540.613
영업상태0.0280.1350.2511.0001.0000.0730.1080.171
휴업시작일자1.0000.8930.9401.0001.0001.0001.0001.000
운영시작시각0.0000.4340.3540.0731.0001.0000.7210.408
운영종료시각0.0400.1470.1540.1081.0000.7211.0000.282
제공기관코드0.1410.7760.6130.1711.0000.4080.2821.000
2024-05-11T10:07:53.836069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영시작시각영업상태운영종료시각자동차정비업체종류
운영시작시각1.0000.0540.5530.000
영업상태0.0541.0000.0680.021
운영종료시각0.5530.0681.0000.024
자동차정비업체종류0.0000.0210.0241.000
2024-05-11T10:07:54.119012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도제공기관코드자동차정비업체종류영업상태운영시작시각운영종료시각
위도1.000-0.245-0.0950.0660.0810.1940.070
경도-0.2451.0000.0180.0610.1140.2130.075
제공기관코드-0.0950.0181.0000.0800.1530.3050.169
자동차정비업체종류0.0660.0610.0801.0000.0210.0000.024
영업상태0.0810.1140.1530.0211.0000.0540.068
운영시작시각0.1940.2130.3050.0000.0541.0000.553
운영종료시각0.0700.0750.1690.0240.0680.5531.000

Missing values

2024-05-11T10:07:25.899811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:07:26.963584image/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.
2024-05-11T10:07:27.509334image/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

자동차정비업체명자동차정비업체종류소재지도로명주소소재지지번주소위도경도사업등록일자면적영업상태폐업일자휴업시작일자휴업종료일자운영시작시각운영종료시각전화번호관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
9674정직 카센타3전라북도 고창군 고창읍 녹두로 1290전라북도 고창군 고창읍 읍내리 1037-135.433386126.6872882016-11-144181<NA><NA><NA>09:0018:00063-561-6066전라북도 고창군063-560-24182023-07-204781000전북특별자치도 고창군
15710호남마스타카3전북특별자치도 정읍시 수성3로 39-4(수성동)<NA>35.583144126.8579942012-04-24356.11<NA><NA><NA><NA><NA>063-538-0244전북특별자치도 정읍시청063-539-59332024-01-244691000전북특별자치도 정읍시
46503아민모터스2인천광역시 부평구 가좌로96번길 62-1(십정동)<NA>37.47705126.6901052009-06-23976.441<NA><NA><NA>09:0018:00032-572-0223인천광역시 부평구032-509-67602021-10-221613000국토교통부
3764동도카마스타3대구광역시 동구 안심로 32(용계동)대구광역시 동구 용계동 763-2035.871619128.6895512007-05-171921<NA><NA><NA><NA><NA><NA>대구광역시 동구청053-662-30472023-11-133420000대구광역시 동구
3473경복카써비스3경기도 남양주시 진접읍 경복대로 404<NA>37.732614127.2102552009-10-09163.81<NA><NA><NA>09:0018:00031-572-5597경기도 남양주시031-590-21332021-10-221613000국토교통부
30696애니카랜드 호매실점3경기도 수원시 권선구 금곡로 5-5(금곡동)<NA>37.268218126.9385072018-08-303411<NA><NA><NA><NA><NA><NA>경기도 수원시청031-228-43162023-10-233740000경기도 수원시
21951이레카샵3전라북도 군산시 칠성4길 197전라북도 군산시 소룡동 1553-335.972792126.6778862012-03-13140.521<NA><NA><NA>10:0018:00063-911-5400전라북도 군산시청063-454-57722023-10-314670000전라북도 군산시
46710존스오토3서울특별시 서초구 바우뫼로 210(양재동)<NA>37.480432127.0419492006-06-20502.821<NA><NA><NA>09:0018:0002-575-5702서울특별시 서초구02-2155-72072021-10-221613000국토교통부
2279평창카센타3강원도 평창군 평창읍 노성로 273<NA>37.368966128.4053631999-05-18387.351<NA><NA><NA>09:0018:00033-333-1662강원도 평창군033-330-22452021-10-221613000국토교통부
6551두원자동차공업사1경기도 안성시 죽산면 장원남산길 140<NA>37.071075127.4374252016-01-051208.751<NA><NA><NA>09:0018:00031-677-9967경기도 안성시031-678-28312021-10-221613000국토교통부
자동차정비업체명자동차정비업체종류소재지도로명주소소재지지번주소위도경도사업등록일자면적영업상태폐업일자휴업시작일자휴업종료일자운영시작시각운영종료시각전화번호관리기관명관리기관전화번호데이터기준일자제공기관코드제공기관명
43701영진자동차공업사3경기도 안양시 만안구 양화로28번길 15(안양동)경기도 안양시 만안구 안양동 784-5337.396852126.9148111999-10-2880.991<NA><NA><NA><NA><NA>031-442-4114경기도 안양시청031-8045-56502023-12-013830000경기도 안양시
34388OK카크리닉3경상북도 구미시 인동32길 44-29(진평동)경상북도 구미시 진평동 1049-336.092007128.4274422003-07-04101.01<NA><NA><NA><NA><NA><NA>경상북도 구미시청054-480-29222023-11-295080000경상북도 구미시
10911타원모터스3경기도 안산시 단원구 만해로 205, C103호 (성곡동)<NA>37.323776126.7611332020-03-25131.041<NA><NA><NA><NA><NA><NA>경기도 안산시청031-481-29512023-12-193930000경기도 안산시
33881주문진점 현대자동차3강원도 강릉시 주문진읍 연주로 285<NA>37.877935128.8271991999-12-30427.561<NA><NA><NA>09:0018:00033-661-8272강원도 강릉시033-640-52562021-10-221613000국토교통부
1399피트인모터스3인천광역시 미추홀구 인하로411번길 5인천광역시 미추홀구 관교동 320-637.446898126.6936272013-09-11127.961<NA><NA><NA><NA><NA><NA>인천광역시 미추홀구청032-880-45312023-12-153510500인천광역시 미추홀구
32067기흥점 기아오토큐3경기도 용인시 기흥구 흥덕2로 1경기도 용인시 기흥구 영덕동 545-2번지37.268104127.0732492001-02-1494.21<NA><NA><NA>09:0018:00031-217-1141용인시 차량등록사업소031-324-45572023-11-294050000경기도 용인시
17611거금카센타3전라남도 고흥군 금산면 거금중앙길 194<NA>34.46662127.133052003-11-285351<NA><NA><NA>09:0018:00061-844-7010전라남도 고흥군061-830-52452021-10-221613000국토교통부
37249타이어프로 중흥점3광주광역시 북구 서암대로 247(중흥동)<NA>35.167184126.9110141998-12-21386.81<NA><NA><NA><NA><NA><NA>광주광역시 북구청 교통행정과062-410-89192023-12-283620000광주광역시 북구
9399K모터스3전라남도 목포시 장미로 112(옥암동)<NA>34.805436126.4324972009-07-13264.451<NA><NA><NA>09:0018:00061-981-0028전라남도 목포시061-270-32462021-10-221613000국토교통부
11145드림자동차병원3대전광역시 유성구 진잠로 137(교촌동)대전광역시 유성구 교촌동 634-1536.30338127.3165892019-06-051441<NA><NA><NA><NA><NA>070-8292-1196대전광역시 유성구청042-611-25872023-11-223670000대전광역시 유성구