Overview

Dataset statistics

Number of variables15
Number of observations126
Missing cells12
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.5 KiB
Average record size in memory126.0 B

Variable types

Text4
Categorical7
Numeric3
DateTime1

Dataset

Description남구 관 내에 등록되어있는 자동차 정비소 정보. 종합정비업, 소형정비업, 전문정비업, 원동기 정비업에 대한 정보로써, 업체명, 주소, 전화번호(유선번호), 위치, 등록일, 면적 등에 대한 정보를 제공합니다.
Author부산광역시 남구
URLhttps://www.data.go.kr/data/15084358/fileData.do

Alerts

영업상태 has constant value ""Constant
운영시작시각 has constant value ""Constant
운영종료시각 has constant value ""Constant
관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
면적 is highly overall correlated with 자동차정비업체종류High correlation
자동차정비업체종류 is highly overall correlated with 면적High correlation
소재지도로명주소 has 2 (1.6%) missing valuesMissing
전화번호 has 10 (7.9%) missing valuesMissing
자동차정비업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:42:06.772896
Analysis finished2023-12-12 19:42:08.990415
Duration2.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자동차정비업체명
Text

UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T04:42:09.309213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length6.9365079
Min length4

Characters and Unicode

Total characters874
Distinct characters173
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)100.0%

Sample

1st row동국자동차정비공업(주)
2nd row(주)호성정비
3rd row시민여객자동차(주) 정비공장
4th row삼보정비(주)
5th row(주)국제자동차정비
ValueCountFrequency (%)
문현점 3
 
2.1%
오토오아시스 3
 
2.1%
대연점 2
 
1.4%
현대자동차 2
 
1.4%
모터스 2
 
1.4%
애니카랜드 2
 
1.4%
선진카센타 1
 
0.7%
동국카정비 1
 
0.7%
감만점 1
 
0.7%
동항카자동차종합병원 1
 
0.7%
Other values (126) 126
87.5%
2023-12-13T04:42:09.910825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 56
 
6.4%
비 48
 
5.5%
카 37
 
4.2%
정 34
 
3.9%
터 34
 
3.9%
모 34
 
3.9%
동 27
 
3.1%
자 21
 
2.4%
차 20
 
2.3%
부 18
 
2.1%
Other values (163) 545
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 812
92.9%
Space Separator 18
 
2.1%
Open Punctuation 11
 
1.3%
Close Punctuation 11
 
1.3%
Other Symbol 10
 
1.1%
Uppercase Letter 10
 
1.1%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 56
 
6.9%
비 48
 
5.9%
카 37
 
4.6%
정 34
 
4.2%
터 34
 
4.2%
모 34
 
4.2%
동 27
 
3.3%
자 21
 
2.6%
차 20
 
2.5%
부 18
 
2.2%
Other values (152) 483
59.5%
Uppercase Letter
ValueCountFrequency (%)
K 4
40.0%
J 2
20.0%
S 2
20.0%
H 1
 
10.0%
O 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 822
94.1%
Common 42
 
4.8%
Latin 10
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 56
 
6.8%
비 48
 
5.8%
카 37
 
4.5%
정 34
 
4.1%
터 34
 
4.1%
모 34
 
4.1%
동 27
 
3.3%
자 21
 
2.6%
차 20
 
2.4%
부 18
 
2.2%
Other values (153) 493
60.0%
Common
ValueCountFrequency (%)
18
42.9%
( 11
26.2%
) 11
26.2%
2 1
 
2.4%
3 1
 
2.4%
Latin
ValueCountFrequency (%)
K 4
40.0%
J 2
20.0%
S 2
20.0%
H 1
 
10.0%
O 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 812
92.9%
ASCII 52
 
5.9%
None 10
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 56
 
6.9%
비 48
 
5.9%
카 37
 
4.6%
정 34
 
4.2%
터 34
 
4.2%
모 34
 
4.2%
동 27
 
3.3%
자 21
 
2.6%
차 20
 
2.5%
부 18
 
2.2%
Other values (152) 483
59.5%
ASCII
ValueCountFrequency (%)
18
34.6%
( 11
21.2%
) 11
21.2%
K 4
 
7.7%
J 2
 
3.8%
S 2
 
3.8%
H 1
 
1.9%
2 1
 
1.9%
O 1
 
1.9%
3 1
 
1.9%
None
ValueCountFrequency (%)
㈜ 10
100.0%

자동차정비업체종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3
98 
1
17 
2
10 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
3 98
77.8%
1 17
 
13.5%
2 10
 
7.9%
4 1
 
0.8%

Length

2023-12-13T04:42:10.076689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:42:10.188348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 98
77.8%
1 17
 
13.5%
2 10
 
7.9%
4 1
 
0.8%

소재지도로명주소
Text

MISSING 

Distinct118
Distinct (%)95.2%
Missing2
Missing (%)1.6%
Memory size1.1 KiB
2023-12-13T04:42:10.565784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length16.943548
Min length14

Characters and Unicode

Total characters2101
Distinct characters67
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

Unique113 ?
Unique (%)91.1%

Sample

1st row부산광역시 남구 신선대산복로 32
2nd row부산광역시 남구 신선로 189
3rd row부산광역시 남구 백운포로 40
4th row부산광역시 남구 우암로 307
5th row부산광역시 남구 무민사로 26
ValueCountFrequency (%)
부산광역시 124
24.9%
남구 124
24.9%
신선로 25
 
5.0%
우암로 13
 
2.6%
유엔로 12
 
2.4%
무민사로 10
 
2.0%
용호로 7
 
1.4%
문현로 7
 
1.4%
동명로 4
 
0.8%
114 4
 
0.8%
Other values (131) 167
33.6%
2023-12-13T04:42:11.096392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
373
17.8%
산 128
 
6.1%
남 127
 
6.0%
부 125
 
5.9%
구 124
 
5.9%
로 124
 
5.9%
시 124
 
5.9%
역 124
 
5.9%
광 124
 
5.9%
1 84
 
4.0%
Other values (57) 644
30.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1340
63.8%
Space Separator 373
 
17.8%
Decimal Number 372
 
17.7%
Dash Punctuation 16
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 128
9.6%
남 127
9.5%
부 125
9.3%
구 124
9.3%
로 124
9.3%
시 124
9.3%
역 124
9.3%
광 124
9.3%
신 29
 
2.2%
선 29
 
2.2%
Other values (45) 282
21.0%
Decimal Number
ValueCountFrequency (%)
1 84
22.6%
2 61
16.4%
3 41
11.0%
4 36
9.7%
7 35
9.4%
6 27
 
7.3%
9 26
 
7.0%
5 23
 
6.2%
0 21
 
5.6%
8 18
 
4.8%
Space Separator
ValueCountFrequency (%)
373
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1340
63.8%
Common 761
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 128
9.6%
남 127
9.5%
부 125
9.3%
구 124
9.3%
로 124
9.3%
시 124
9.3%
역 124
9.3%
광 124
9.3%
신 29
 
2.2%
선 29
 
2.2%
Other values (45) 282
21.0%
Common
ValueCountFrequency (%)
373
49.0%
1 84
 
11.0%
2 61
 
8.0%
3 41
 
5.4%
4 36
 
4.7%
7 35
 
4.6%
6 27
 
3.5%
9 26
 
3.4%
5 23
 
3.0%
0 21
 
2.8%
Other values (2) 34
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1340
63.8%
ASCII 761
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
373
49.0%
1 84
 
11.0%
2 61
 
8.0%
3 41
 
5.4%
4 36
 
4.7%
7 35
 
4.6%
6 27
 
3.5%
9 26
 
3.4%
5 23
 
3.0%
0 21
 
2.8%
Other values (2) 34
 
4.5%
Hangul
ValueCountFrequency (%)
산 128
9.6%
남 127
9.5%
부 125
9.3%
구 124
9.3%
로 124
9.3%
시 124
9.3%
역 124
9.3%
광 124
9.3%
신 29
 
2.2%
선 29
 
2.2%
Other values (45) 282
21.0%

소재지지번주소
Text

Distinct120
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T04:42:11.437771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length18.15873
Min length14

Characters and Unicode

Total characters2288
Distinct characters31
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

Unique115 ?
Unique (%)91.3%

Sample

1st row부산광역시 남구 용당동 100-9
2nd row부산광역시 남구 감만동 254-48
3rd row부산광역시 남구 용호동 895
4th row부산광역시 남구 문현동 1201-2
5th row부산광역시 남구 감만동 271
ValueCountFrequency (%)
부산광역시 126
25.0%
남구 126
25.0%
감만동 35
 
6.9%
대연동 31
 
6.1%
문현동 22
 
4.4%
용당동 19
 
3.8%
용호동 14
 
2.8%
우암동 5
 
1.0%
8-12 3
 
0.6%
239-19 2
 
0.4%
Other values (119) 122
24.2%
2023-12-13T04:42:11.934130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
379
16.6%
산 127
 
5.6%
부 126
 
5.5%
광 126
 
5.5%
역 126
 
5.5%
시 126
 
5.5%
남 126
 
5.5%
구 126
 
5.5%
동 126
 
5.5%
- 113
 
4.9%
Other values (21) 787
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1261
55.1%
Decimal Number 535
23.4%
Space Separator 379
 
16.6%
Dash Punctuation 113
 
4.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 127
10.1%
부 126
10.0%
광 126
10.0%
역 126
10.0%
시 126
10.0%
남 126
10.0%
구 126
10.0%
동 126
10.0%
만 35
 
2.8%
감 35
 
2.8%
Other values (9) 182
14.4%
Decimal Number
ValueCountFrequency (%)
1 95
17.8%
2 78
14.6%
5 59
11.0%
8 59
11.0%
3 52
9.7%
4 51
9.5%
9 47
8.8%
7 37
 
6.9%
0 30
 
5.6%
6 27
 
5.0%
Space Separator
ValueCountFrequency (%)
379
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1261
55.1%
Common 1027
44.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 127
10.1%
부 126
10.0%
광 126
10.0%
역 126
10.0%
시 126
10.0%
남 126
10.0%
구 126
10.0%
동 126
10.0%
만 35
 
2.8%
감 35
 
2.8%
Other values (9) 182
14.4%
Common
ValueCountFrequency (%)
379
36.9%
- 113
 
11.0%
1 95
 
9.3%
2 78
 
7.6%
5 59
 
5.7%
8 59
 
5.7%
3 52
 
5.1%
4 51
 
5.0%
9 47
 
4.6%
7 37
 
3.6%
Other values (2) 57
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1261
55.1%
ASCII 1027
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
379
36.9%
- 113
 
11.0%
1 95
 
9.3%
2 78
 
7.6%
5 59
 
5.7%
8 59
 
5.7%
3 52
 
5.1%
4 51
 
5.0%
9 47
 
4.6%
7 37
 
3.6%
Other values (2) 57
 
5.6%
Hangul
ValueCountFrequency (%)
산 127
10.1%
부 126
10.0%
광 126
10.0%
역 126
10.0%
시 126
10.0%
남 126
10.0%
구 126
10.0%
동 126
10.0%
만 35
 
2.8%
감 35
 
2.8%
Other values (9) 182
14.4%

위도
Real number (ℝ)

Distinct120
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.125549
Minimum35.104781
Maximum35.149955
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T04:42:12.127669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.104781
5-th percentile35.110813
Q135.113814
median35.123849
Q335.135407
95-th percentile35.145667
Maximum35.149955
Range0.04517364
Interquartile range (IQR)0.021592207

Descriptive statistics

Standard deviation0.012015862
Coefficient of variation (CV)0.00034208325
Kurtosis-1.0107582
Mean35.125549
Median Absolute Deviation (MAD)0.01048876
Skewness0.38441884
Sum4425.8191
Variance0.00014438094
MonotonicityNot monotonic
2023-12-13T04:42:12.313747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.12104758 3
 
2.4%
35.11822316 2
 
1.6%
35.13542414 2
 
1.6%
35.11091354 2
 
1.6%
35.11128047 2
 
1.6%
35.13320648 1
 
0.8%
35.12154357 1
 
0.8%
35.12771376 1
 
0.8%
35.11327806 1
 
0.8%
35.11700981 1
 
0.8%
Other values (110) 110
87.3%
ValueCountFrequency (%)
35.10478136 1
0.8%
35.11014824 1
0.8%
35.11034284 1
0.8%
35.11034315 1
0.8%
35.11042135 1
0.8%
35.11078259 1
0.8%
35.11080178 1
0.8%
35.11084608 1
0.8%
35.1108837 1
0.8%
35.11089187 1
0.8%
ValueCountFrequency (%)
35.149955 1
0.8%
35.14994551 1
0.8%
35.14993341 1
0.8%
35.1493586 1
0.8%
35.14747129 1
0.8%
35.14703768 1
0.8%
35.14573525 1
0.8%
35.14546418 1
0.8%
35.14480827 1
0.8%
35.14441878 1
0.8%

경도
Real number (ℝ)

Distinct120
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.08866
Minimum129.06424
Maximum129.1145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T04:42:12.495685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.06424
5-th percentile129.06815
Q1129.08044
median129.08797
Q3129.09815
95-th percentile129.11126
Maximum129.1145
Range0.0502632
Interquartile range (IQR)0.01771625

Descriptive statistics

Standard deviation0.012553135
Coefficient of variation (CV)9.7244288 × 10-5
Kurtosis-0.65383865
Mean129.08866
Median Absolute Deviation (MAD)0.0082565
Skewness0.18843813
Sum16265.171
Variance0.00015758119
MonotonicityNot monotonic
2023-12-13T04:42:12.683197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0824657 3
 
2.4%
129.079564 2
 
1.6%
129.0665653 2
 
1.6%
129.0884458 2
 
1.6%
129.0799333 2
 
1.6%
129.0922682 1
 
0.8%
129.0822143 1
 
0.8%
129.0905278 1
 
0.8%
129.0813411 1
 
0.8%
129.0992929 1
 
0.8%
Other values (110) 110
87.3%
ValueCountFrequency (%)
129.0642386 1
0.8%
129.066299 1
0.8%
129.0663652 1
0.8%
129.0665653 2
1.6%
129.0668032 1
0.8%
129.0680209 1
0.8%
129.0685485 1
0.8%
129.0708885 1
0.8%
129.0712612 1
0.8%
129.0714756 1
0.8%
ValueCountFrequency (%)
129.1145018 1
0.8%
129.1143991 1
0.8%
129.1130277 1
0.8%
129.1122761 1
0.8%
129.1118509 1
0.8%
129.1114663 1
0.8%
129.1113767 1
0.8%
129.110927 1
0.8%
129.1109029 1
0.8%
129.1108026 1
0.8%

사업등록일자
Date

Distinct121
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1968-12-19 00:00:00
Maximum2021-10-15 00:00:00
2023-12-13T04:42:12.859666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:42:13.025079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct119
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean609.5104
Minimum70.2
Maximum9872
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T04:42:13.219155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70.2
5-th percentile78.345
Q1109.5125
median185.25
Q3340.5
95-th percentile2749.0025
Maximum9872
Range9801.8
Interquartile range (IQR)230.9875

Descriptive statistics

Standard deviation1326.031
Coefficient of variation (CV)2.1755675
Kurtosis28.517275
Mean609.5104
Median Absolute Deviation (MAD)87.75
Skewness4.9022781
Sum76798.31
Variance1758358.3
MonotonicityNot monotonic
2023-12-13T04:42:13.396442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
139.0 3
 
2.4%
108.0 2
 
1.6%
180.2 2
 
1.6%
90.95 2
 
1.6%
190.0 2
 
1.6%
185.6 2
 
1.6%
1915.68 1
 
0.8%
119.2 1
 
0.8%
150.1 1
 
0.8%
90.0 1
 
0.8%
Other values (109) 109
86.5%
ValueCountFrequency (%)
70.2 1
0.8%
71.7 1
0.8%
72.8 1
0.8%
76.0 1
0.8%
76.86 1
0.8%
77.35 1
0.8%
78.3 1
0.8%
78.48 1
0.8%
82.6 1
0.8%
82.82 1
0.8%
ValueCountFrequency (%)
9872.0 1
0.8%
8539.0 1
0.8%
3738.08 1
0.8%
3674.45 1
0.8%
3323.0 1
0.8%
2862.0 1
0.8%
2853.0 1
0.8%
2437.01 1
0.8%
2213.0 1
0.8%
2078.55 1
0.8%

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
1
126 

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 (%)
1 126
100.0%

Length

2023-12-13T04:42:13.538410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:42:13.945494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 126
100.0%

운영시작시각
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
10:00
126 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10:00
2nd row10:00
3rd row10:00
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
10:00 126
100.0%

Length

2023-12-13T04:42:14.081596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:42:14.184666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10:00 126
100.0%

운영종료시각
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
18:00
126 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row18:00
2nd row18:00
3rd row18:00
4th row18:00
5th row18:00

Common Values

ValueCountFrequency (%)
18:00 126
100.0%

Length

2023-12-13T04:42:14.300144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:42:14.412522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18:00 126
100.0%

전화번호
Text

MISSING 

Distinct116
Distinct (%)100.0%
Missing10
Missing (%)7.9%
Memory size1.1 KiB
2023-12-13T04:42:14.718770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1392
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

Unique116 ?
Unique (%)100.0%

Sample

1st row051-621-6691
2nd row051-637-7322
3rd row051-622-7455
4th row051-643-0111
5th row051-633-6400
ValueCountFrequency (%)
051-636-5587 1
 
0.9%
051-623-2716 1
 
0.9%
051-637-3001 1
 
0.9%
051-638-7783 1
 
0.9%
051-635-1507 1
 
0.9%
051-628-8384 1
 
0.9%
051-633-8871 1
 
0.9%
051-628-9752 1
 
0.9%
051-622-0119 1
 
0.9%
051-621-1194 1
 
0.9%
Other values (106) 106
91.4%
2023-12-13T04:42:15.148567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 232
16.7%
1 199
14.3%
5 197
14.2%
0 195
14.0%
6 156
11.2%
2 100
7.2%
3 78
 
5.6%
7 74
 
5.3%
4 62
 
4.5%
8 50
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1160
83.3%
Dash Punctuation 232
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 199
17.2%
5 197
17.0%
0 195
16.8%
6 156
13.4%
2 100
8.6%
3 78
 
6.7%
7 74
 
6.4%
4 62
 
5.3%
8 50
 
4.3%
9 49
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 232
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1392
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 232
16.7%
1 199
14.3%
5 197
14.2%
0 195
14.0%
6 156
11.2%
2 100
7.2%
3 78
 
5.6%
7 74
 
5.3%
4 62
 
4.5%
8 50
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1392
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 232
16.7%
1 199
14.3%
5 197
14.2%
0 195
14.0%
6 156
11.2%
2 100
7.2%
3 78
 
5.6%
7 74
 
5.3%
4 62
 
4.5%
8 50
 
3.6%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
부산광역시 남구
126 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 남구
2nd row부산광역시 남구
3rd row부산광역시 남구
4th row부산광역시 남구
5th row부산광역시 남구

Common Values

ValueCountFrequency (%)
부산광역시 남구 126
100.0%

Length

2023-12-13T04:42:15.311299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:42:15.410127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 126
50.0%
남구 126
50.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
051-607-4498
126 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row051-607-4498
2nd row051-607-4498
3rd row051-607-4498
4th row051-607-4498
5th row051-607-4498

Common Values

ValueCountFrequency (%)
051-607-4498 126
100.0%

Length

2023-12-13T04:42:15.520987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:42:15.621991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-607-4498 126
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2022-01-14
126 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-01-14
2nd row2022-01-14
3rd row2022-01-14
4th row2022-01-14
5th row2022-01-14

Common Values

ValueCountFrequency (%)
2022-01-14 126
100.0%

Length

2023-12-13T04:42:15.732414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:42:15.837930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-01-14 126
100.0%

Interactions

2023-12-13T04:42:08.034178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:42:07.267671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:42:07.658111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:42:08.152128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:42:07.404746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:42:07.782391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:42:08.257230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:42:07.527768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:42:07.909913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:42:15.913279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자동차정비업체종류위도경도면적
자동차정비업체종류1.0000.2010.0000.679
위도0.2011.0000.8050.251
경도0.0000.8051.0000.195
면적0.6790.2510.1951.000
2023-12-13T04:42:16.029499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도면적자동차정비업체종류
위도1.000-0.196-0.3470.116
경도-0.1961.0000.2650.000
면적-0.3470.2651.0000.505
자동차정비업체종류0.1160.0000.5051.000

Missing values

2023-12-13T04:42:08.434307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:42:08.751897image/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.
2023-12-13T04:42:08.916905image/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

자동차정비업체명자동차정비업체종류소재지도로명주소소재지지번주소위도경도사업등록일자면적영업상태운영시작시각운영종료시각전화번호관리기관명관리기관전화번호데이터기준일자
0동국자동차정비공업(주)1부산광역시 남구 신선대산복로 32부산광역시 남구 용당동 100-935.11701129.0992932000-05-151915.68110:0018:00051-621-6691부산광역시 남구051-607-44982022-01-14
1(주)호성정비1부산광역시 남구 신선로 189부산광역시 남구 감만동 254-4835.111544129.0848552001-02-011222.0110:0018:00051-637-7322부산광역시 남구051-607-44982022-01-14
2시민여객자동차(주) 정비공장1부산광역시 남구 백운포로 40부산광역시 남구 용호동 89535.104781129.1113772001-06-051306.64110:0018:00051-622-7455부산광역시 남구051-607-44982022-01-14
3삼보정비(주)1부산광역시 남구 우암로 307부산광역시 남구 문현동 1201-235.129202129.0668031968-12-193674.45110:0018:00051-643-0111부산광역시 남구051-607-44982022-01-14
4(주)국제자동차정비1부산광역시 남구 무민사로 26부산광역시 남구 감만동 27135.11205129.0816931992-02-211528.23110:0018:00051-633-6400부산광역시 남구051-607-44982022-01-14
5(주)백운자동차정비1부산광역시 남구 신선로 321부산광역시 남구 용당동 144-335.114441129.0947121997-12-162437.01110:0018:00051-626-5612부산광역시 남구051-607-44982022-01-14
6우성자동차정비(주)1부산광역시 남구 신선대산복로 38부산광역시 남구 용당동 100-835.11642129.0992451994-12-243323.0110:0018:00051-625-7005부산광역시 남구051-607-44982022-01-14
7(주)현대기아남구정비서비스1부산광역시 남구 신선로 340부산광역시 남구 용당동 128-935.117051129.095971982-11-109872.0110:0018:00051-624-2121부산광역시 남구051-607-44982022-01-14
8부경트럭모터스1부산광역시 남구 우암로 114부산광역시 남구 감만동 8-1235.121048129.0824661994-05-208539.0110:0018:00051-719-5155부산광역시 남구051-607-44982022-01-14
9㈜남부자동차정비1부산광역시 남구 용호로 128부산광역시 남구 용호동 370-235.120866129.1118511997-10-151358.0110:0018:00051-625-3200부산광역시 남구051-607-44982022-01-14
자동차정비업체명자동차정비업체종류소재지도로명주소소재지지번주소위도경도사업등록일자면적영업상태운영시작시각운영종료시각전화번호관리기관명관리기관전화번호데이터기준일자
116영진카클리닉3부산광역시 남구 유엔평화로143번길 10-1부산광역시 남구 용당동 568-735.12402129.09752018-11-29375.0110:0018:00051-809-0962부산광역시 남구051-607-44982022-01-14
117JJ 모터스3부산광역시 남구 동명로 12부산광역시 남구 용당동 9935.120444129.0994182019-04-24278.03110:0018:00<NA>부산광역시 남구051-607-44982022-01-14
118마이다스 모터스3부산광역시 남구 황령대로353번길 19-1부산광역시 남구 대연동 231-335.147471129.0959832019-04-24108.0110:0018:00051-557-7533부산광역시 남구051-607-44982022-01-14
119비전모터스3부산광역시 남구 신선로 468부산광역시 남구 대연동 702-435.12632129.1021222019-11-26111.04110:0018:00<NA>부산광역시 남구051-607-44982022-01-14
120보스서비스3부산광역시 남구 무민사로 40부산광역시 남구 감만동 292-1235.113577129.0816452020-03-09113.0110:0018:00051-923-2938부산광역시 남구051-607-44982022-01-14
121몽키2모터스3부산광역시 남구 신선로 400부산광역시 남구 용당동 99-1435.120811129.098832020-07-24236.69110:0018:00<NA>부산광역시 남구051-607-44982022-01-14
122㈜유엔모터스3<NA>부산광역시 남구 대연동 734-2135.125009129.0961282020-12-21458.02110:0018:00051-626-0756부산광역시 남구051-607-44982022-01-14
123HK모터스3부산광역시 남구 우암로 114부산광역시 남구 감만동 8-1235.121048129.0824662021-04-30231.8110:0018:00<NA>부산광역시 남구051-607-44982022-01-14
124에스티모터스3부산광역시 남구 신선로 172부산광역시 남구 감만동 254-3635.110343129.0828832021-06-22575.12110:0018:00<NA>부산광역시 남구051-607-44982022-01-14
125열린모터스3부산광역시 남구 동명로 132번길 79부산광역시 남구 용호동 486-7235.116279129.1104642021-10-15323.0110:0018:00<NA>부산광역시 남구051-607-44982022-01-14