Overview

Dataset statistics

Number of variables18
Number of observations95
Missing cells285
Missing cells (%)16.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.2 KiB
Average record size in memory153.4 B

Variable types

Text4
Categorical4
Numeric3
DateTime4
Unsupported3

Dataset

Description자동차정비업을 하려는 자는 자동차관리법 제53조 규정에 따라 시장/군수/구청장에게 등록하여야 하며, 시장/군수/구청장은 등록기준에 적합한 경우 사업을 등록해 주어야 함.
Author서울특별시 마포구
URLhttps://www.data.go.kr/data/15108241/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
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
면적 is highly overall correlated with 자동차정비업체종류High correlation
자동차정비업체종류 is highly overall correlated with 면적High correlation
자동차정비업체종류 is highly imbalanced (61.2%)Imbalance
폐업일자 has 95 (100.0%) missing valuesMissing
휴업시작일자 has 95 (100.0%) missing valuesMissing
휴업종료일자 has 95 (100.0%) missing valuesMissing
자동차정비업체명 has unique valuesUnique
전화번호 has unique valuesUnique
폐업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 13:49:23.721413
Analysis finished2023-12-12 13:49:26.335286
Duration2.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자동차정비업체명
Text

UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-12-12T22:49:26.530026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length8.1789474
Min length3

Characters and Unicode

Total characters777
Distinct characters156
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)100.0%

Sample

1st row상암현대서비스(주)
2nd row한성자동차주식회사
3rd row코오롱글로벌(주) 성산지점
4th row마포동화써비스㈜
5th row태평양카독크
ValueCountFrequency (%)
애니카랜드 4
 
3.6%
주식회사 2
 
1.8%
르노코리아자동차서비스코너 2
 
1.8%
스피드메이트 2
 
1.8%
마포점 2
 
1.8%
용강점 2
 
1.8%
기아오토큐 2
 
1.8%
상암현대서비스(주 1
 
0.9%
카사랑 1
 
0.9%
한라자동차공업사 1
 
0.9%
Other values (92) 92
82.9%
2023-12-12T22:49:26.999000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 50
 
6.4%
사 48
 
6.2%
자 47
 
6.0%
차 46
 
5.9%
공 41
 
5.3%
업 39
 
5.0%
점 21
 
2.7%
카 21
 
2.7%
스 21
 
2.7%
16
 
2.1%
Other values (146) 427
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 752
96.8%
Space Separator 16
 
2.1%
Close Punctuation 4
 
0.5%
Open Punctuation 4
 
0.5%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 50
 
6.6%
사 48
 
6.4%
자 47
 
6.2%
차 46
 
6.1%
공 41
 
5.5%
업 39
 
5.2%
점 21
 
2.8%
카 21
 
2.8%
스 21
 
2.8%
대 16
 
2.1%
Other values (142) 402
53.5%
Space Separator
ValueCountFrequency (%)
16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 753
96.9%
Common 24
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 50
 
6.6%
사 48
 
6.4%
자 47
 
6.2%
차 46
 
6.1%
공 41
 
5.4%
업 39
 
5.2%
점 21
 
2.8%
카 21
 
2.8%
스 21
 
2.8%
대 16
 
2.1%
Other values (143) 403
53.5%
Common
ValueCountFrequency (%)
16
66.7%
) 4
 
16.7%
( 4
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 752
96.8%
ASCII 24
 
3.1%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 50
 
6.6%
사 48
 
6.4%
자 47
 
6.2%
차 46
 
6.1%
공 41
 
5.5%
업 39
 
5.2%
점 21
 
2.8%
카 21
 
2.8%
스 21
 
2.8%
대 16
 
2.1%
Other values (142) 402
53.5%
ASCII
ValueCountFrequency (%)
16
66.7%
) 4
 
16.7%
( 4
 
16.7%
None
ValueCountFrequency (%)
㈜ 1
100.0%

자동차정비업체종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size892.0 B
3
84 
2
 
8
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
3 84
88.4%
2 8
 
8.4%
1 3
 
3.2%

Length

2023-12-12T22:49:27.149541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:49:27.261030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 84
88.4%
2 8
 
8.4%
1 3
 
3.2%

소재지도로명주소
Text

Distinct94
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-12-12T22:49:27.568499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length17.631579
Min length16

Characters and Unicode

Total characters1675
Distinct characters66
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

Unique93 ?
Unique (%)97.9%

Sample

1st row서울특별시 마포구 모래내로3길 19
2nd row서울특별시 마포구 모래내로 17
3rd row서울특별시 마포구 월드컵로36길 22
4th row서울특별시 마포구 모래내로 5
5th row서울특별시 마포구 월드컵로34길 17
ValueCountFrequency (%)
서울특별시 95
25.0%
마포구 95
25.0%
동교로 8
 
2.1%
토정로 6
 
1.6%
대흥로 5
 
1.3%
희우정로 5
 
1.3%
망원로 4
 
1.1%
연남로 4
 
1.1%
모래내로3길 4
 
1.1%
월드컵북로 4
 
1.1%
Other values (114) 150
39.5%
2023-12-12T22:49:28.108221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
285
17.0%
포 103
 
6.1%
마 101
 
6.0%
서 99
 
5.9%
구 95
 
5.7%
울 95
 
5.7%
시 95
 
5.7%
특 95
 
5.7%
별 95
 
5.7%
로 94
 
5.6%
Other values (56) 518
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1126
67.2%
Space Separator 285
 
17.0%
Decimal Number 255
 
15.2%
Dash Punctuation 9
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 103
9.1%
마 101
9.0%
서 99
8.8%
구 95
8.4%
울 95
8.4%
시 95
8.4%
특 95
8.4%
별 95
8.4%
로 94
8.3%
길 28
 
2.5%
Other values (44) 226
20.1%
Decimal Number
ValueCountFrequency (%)
1 55
21.6%
3 34
13.3%
2 32
12.5%
4 28
11.0%
7 24
9.4%
5 23
9.0%
9 18
 
7.1%
6 16
 
6.3%
0 14
 
5.5%
8 11
 
4.3%
Space Separator
ValueCountFrequency (%)
285
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1126
67.2%
Common 549
32.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 103
9.1%
마 101
9.0%
서 99
8.8%
구 95
8.4%
울 95
8.4%
시 95
8.4%
특 95
8.4%
별 95
8.4%
로 94
8.3%
길 28
 
2.5%
Other values (44) 226
20.1%
Common
ValueCountFrequency (%)
285
51.9%
1 55
 
10.0%
3 34
 
6.2%
2 32
 
5.8%
4 28
 
5.1%
7 24
 
4.4%
5 23
 
4.2%
9 18
 
3.3%
6 16
 
2.9%
0 14
 
2.6%
Other values (2) 20
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1126
67.2%
ASCII 549
32.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
285
51.9%
1 55
 
10.0%
3 34
 
6.2%
2 32
 
5.8%
4 28
 
5.1%
7 24
 
4.4%
5 23
 
4.2%
9 18
 
3.3%
6 16
 
2.9%
0 14
 
2.6%
Other values (2) 20
 
3.6%
Hangul
ValueCountFrequency (%)
포 103
9.1%
마 101
9.0%
서 99
8.8%
구 95
8.4%
울 95
8.4%
시 95
8.4%
특 95
8.4%
별 95
8.4%
로 94
8.3%
길 28
 
2.5%
Other values (44) 226
20.1%

소재지지번주소
Text

Distinct94
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-12-12T22:49:28.453095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length19.252632
Min length16

Characters and Unicode

Total characters1829
Distinct characters50
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

Unique93 ?
Unique (%)97.9%

Sample

1st row서울특별시 마포구 성산동 590-3
2nd row서울특별시 마포구 성산동 593-8
3rd row서울특별시 마포구 성산동 589
4th row서울특별시 마포구 성산동 592-7
5th row서울특별시 마포구 성산동 590-6
ValueCountFrequency (%)
서울특별시 95
24.9%
마포구 95
24.9%
성산동 28
 
7.3%
망원동 13
 
3.4%
창전동 8
 
2.1%
대흥동 8
 
2.1%
연남동 7
 
1.8%
합정동 5
 
1.3%
신수동 4
 
1.0%
공덕동 4
 
1.0%
Other values (105) 114
29.9%
2023-12-12T22:49:28.901128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
286
15.6%
서 99
 
5.4%
마 95
 
5.2%
울 95
 
5.2%
구 95
 
5.2%
포 95
 
5.2%
동 95
 
5.2%
시 95
 
5.2%
별 95
 
5.2%
특 95
 
5.2%
Other values (40) 684
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1046
57.2%
Decimal Number 408
 
22.3%
Space Separator 286
 
15.6%
Dash Punctuation 89
 
4.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 99
9.5%
마 95
9.1%
울 95
9.1%
구 95
9.1%
포 95
9.1%
동 95
9.1%
시 95
9.1%
별 95
9.1%
특 95
9.1%
산 29
 
2.8%
Other values (28) 158
15.1%
Decimal Number
ValueCountFrequency (%)
1 66
16.2%
3 63
15.4%
4 50
12.3%
2 48
11.8%
5 43
10.5%
6 37
9.1%
9 33
8.1%
7 27
6.6%
0 24
 
5.9%
8 17
 
4.2%
Space Separator
ValueCountFrequency (%)
286
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1046
57.2%
Common 783
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 99
9.5%
마 95
9.1%
울 95
9.1%
구 95
9.1%
포 95
9.1%
동 95
9.1%
시 95
9.1%
별 95
9.1%
특 95
9.1%
산 29
 
2.8%
Other values (28) 158
15.1%
Common
ValueCountFrequency (%)
286
36.5%
- 89
 
11.4%
1 66
 
8.4%
3 63
 
8.0%
4 50
 
6.4%
2 48
 
6.1%
5 43
 
5.5%
6 37
 
4.7%
9 33
 
4.2%
7 27
 
3.4%
Other values (2) 41
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1046
57.2%
ASCII 783
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
286
36.5%
- 89
 
11.4%
1 66
 
8.4%
3 63
 
8.0%
4 50
 
6.4%
2 48
 
6.1%
5 43
 
5.5%
6 37
 
4.7%
9 33
 
4.2%
7 27
 
3.4%
Other values (2) 41
 
5.2%
Hangul
ValueCountFrequency (%)
서 99
9.5%
마 95
9.1%
울 95
9.1%
구 95
9.1%
포 95
9.1%
동 95
9.1%
시 95
9.1%
별 95
9.1%
특 95
9.1%
산 29
 
2.8%
Other values (28) 158
15.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.555767
Minimum37.537473
Maximum37.581192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size987.0 B
2023-12-12T22:49:29.039533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.537473
5-th percentile37.543324
Q137.548305
median37.554397
Q337.564427
95-th percentile37.566921
Maximum37.581192
Range0.043718488
Interquartile range (IQR)0.016121494

Descriptive statistics

Standard deviation0.0086008987
Coefficient of variation (CV)0.00022901672
Kurtosis-0.58265108
Mean37.555767
Median Absolute Deviation (MAD)0.0078493725
Skewness0.20894424
Sum3567.7979
Variance7.3975458 × 10-5
MonotonicityNot monotonic
2023-12-12T22:49:29.176921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5645513698 2
 
2.1%
37.5659799565 1
 
1.1%
37.5656380538 1
 
1.1%
37.5374731685 1
 
1.1%
37.55729493 1
 
1.1%
37.5432283824 1
 
1.1%
37.5465477321 1
 
1.1%
37.5511882516 1
 
1.1%
37.56504926 1
 
1.1%
37.542397255 1
 
1.1%
Other values (84) 84
88.4%
ValueCountFrequency (%)
37.5374731685 1
1.1%
37.5421183825 1
1.1%
37.542397255 1
1.1%
37.5429118547 1
1.1%
37.5432283824 1
1.1%
37.5433654064 1
1.1%
37.5446125129 1
1.1%
37.5446251364 1
1.1%
37.5447148155 1
1.1%
37.5451151551 1
1.1%
ValueCountFrequency (%)
37.5811916566 1
1.1%
37.5738142557 1
1.1%
37.5686229867 1
1.1%
37.5673617953 1
1.1%
37.5672450952 1
1.1%
37.5667818964 1
1.1%
37.5666192947 1
1.1%
37.5661110906 1
1.1%
37.5659799565 1
1.1%
37.5659367262 1
1.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.92055
Minimum126.87717
Maximum126.96243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size987.0 B
2023-12-12T22:49:29.305235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.87717
5-th percentile126.90172
Q1126.90421
median126.91507
Q3126.93755
95-th percentile126.95298
Maximum126.96243
Range0.085263262
Interquartile range (IQR)0.03334823

Descriptive statistics

Standard deviation0.018081903
Coefficient of variation (CV)0.00014246632
Kurtosis-0.77946647
Mean126.92055
Median Absolute Deviation (MAD)0.011894865
Skewness0.43182228
Sum12057.452
Variance0.00032695522
MonotonicityNot monotonic
2023-12-12T22:49:29.436426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9038879525 2
 
2.1%
126.9036272533 1
 
1.1%
126.9046570321 1
 
1.1%
126.9466529317 1
 
1.1%
126.9040095441 1
 
1.1%
126.9383032068 1
 
1.1%
126.9440485408 1
 
1.1%
126.9374387277 1
 
1.1%
126.9070031 1
 
1.1%
126.9396096844 1
 
1.1%
Other values (84) 84
88.4%
ValueCountFrequency (%)
126.877167038 1
1.1%
126.9001698446 1
1.1%
126.9006322355 1
1.1%
126.9006702735 1
1.1%
126.9012284444 1
1.1%
126.9019327537 1
1.1%
126.9020573658 1
1.1%
126.9024719831 1
1.1%
126.9025576477 1
1.1%
126.9030363236 1
1.1%
ValueCountFrequency (%)
126.9624303 1
1.1%
126.9577137287 1
1.1%
126.9570808353 1
1.1%
126.9561809193 1
1.1%
126.9559735085 1
1.1%
126.95169564 1
1.1%
126.9485220812 1
1.1%
126.947237927 1
1.1%
126.9466529317 1
1.1%
126.946187966 1
1.1%

사업등록일자
Date

Distinct89
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size892.0 B
Minimum1994-01-20 00:00:00
Maximum2022-03-07 00:00:00
2023-12-12T22:49:29.577447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:29.701478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean273.89389
Minimum35
Maximum5243.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size987.0 B
2023-12-12T22:49:29.844097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile46.528
Q160.505
median75.39
Q3134.48
95-th percentile706.348
Maximum5243.29
Range5208.29
Interquartile range (IQR)73.975

Descriptive statistics

Standard deviation791.67217
Coefficient of variation (CV)2.8904338
Kurtosis28.986884
Mean273.89389
Median Absolute Deviation (MAD)22.69
Skewness5.339107
Sum26019.92
Variance626744.82
MonotonicityNot monotonic
2023-12-12T22:49:29.981890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64.6 2
 
2.1%
1188.09 1
 
1.1%
57.9 1
 
1.1%
49.9 1
 
1.1%
62.44 1
 
1.1%
317.78 1
 
1.1%
59.34 1
 
1.1%
48.58 1
 
1.1%
68.64 1
 
1.1%
143.06 1
 
1.1%
Other values (84) 84
88.4%
ValueCountFrequency (%)
35.0 1
1.1%
35.4 1
1.1%
39.75 1
1.1%
41.91 1
1.1%
43.98 1
1.1%
47.62 1
1.1%
48.58 1
1.1%
49.9 1
1.1%
50.38 1
1.1%
51.04 1
1.1%
ValueCountFrequency (%)
5243.29 1
1.1%
4766.98 1
1.1%
3380.4 1
1.1%
1188.09 1
1.1%
806.0 1
1.1%
663.64 1
1.1%
414.32 1
1.1%
407.49 1
1.1%
403.13 1
1.1%
400.37 1
1.1%

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size892.0 B
1
95 

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 95
100.0%

Length

2023-12-12T22:49:30.141012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:49:30.220633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 95
100.0%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing95
Missing (%)100.0%
Memory size987.0 B

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing95
Missing (%)100.0%
Memory size987.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing95
Missing (%)100.0%
Memory size987.0 B

운영시작시각
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size892.0 B
Minimum2023-12-12 09:00:00
Maximum2023-12-12 09:00:00
2023-12-12T22:49:30.310875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:30.395509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

운영종료시각
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size892.0 B
Minimum2023-12-12 18:00:00
Maximum2023-12-12 18:00:00
2023-12-12T22:49:30.495125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:30.598635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

전화번호
Text

UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size892.0 B
2023-12-12T22:49:30.930903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.042105
Min length11

Characters and Unicode

Total characters1049
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

Unique95 ?
Unique (%)100.0%

Sample

1st row02-374-6437
2nd row02-309-3421
3rd row02-375-7301
4th row02-308-3100
5th row02-375-7127
ValueCountFrequency (%)
02-374-6437 1
 
1.1%
02-333-5935 1
 
1.1%
02-324-8118 1
 
1.1%
02-703-9118 1
 
1.1%
02-704-2533 1
 
1.1%
02-704-5999 1
 
1.1%
02-323-1413 1
 
1.1%
02-712-0622 1
 
1.1%
02-337-3003 1
 
1.1%
02-332-7062 1
 
1.1%
Other values (85) 85
89.5%
2023-12-12T22:49:31.438752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 190
18.1%
2 166
15.8%
0 157
15.0%
3 142
13.5%
7 81
7.7%
1 76
 
7.2%
5 62
 
5.9%
6 50
 
4.8%
4 49
 
4.7%
8 49
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 859
81.9%
Dash Punctuation 190
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 166
19.3%
0 157
18.3%
3 142
16.5%
7 81
9.4%
1 76
8.8%
5 62
 
7.2%
6 50
 
5.8%
4 49
 
5.7%
8 49
 
5.7%
9 27
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1049
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 190
18.1%
2 166
15.8%
0 157
15.0%
3 142
13.5%
7 81
7.7%
1 76
 
7.2%
5 62
 
5.9%
6 50
 
4.8%
4 49
 
4.7%
8 49
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1049
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 190
18.1%
2 166
15.8%
0 157
15.0%
3 142
13.5%
7 81
7.7%
1 76
 
7.2%
5 62
 
5.9%
6 50
 
4.8%
4 49
 
4.7%
8 49
 
4.7%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size892.0 B
마포구청 교통행정과
95 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row마포구청 교통행정과
2nd row마포구청 교통행정과
3rd row마포구청 교통행정과
4th row마포구청 교통행정과
5th row마포구청 교통행정과

Common Values

ValueCountFrequency (%)
마포구청 교통행정과 95
100.0%

Length

2023-12-12T22:49:31.608592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:49:31.723927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마포구청 95
50.0%
교통행정과 95
50.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size892.0 B
02-3153-9633
95 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row02-3153-9633
2nd row02-3153-9633
3rd row02-3153-9633
4th row02-3153-9633
5th row02-3153-9633

Common Values

ValueCountFrequency (%)
02-3153-9633 95
100.0%

Length

2023-12-12T22:49:31.842073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:49:31.954872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02-3153-9633 95
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size892.0 B
Minimum2022-11-21 00:00:00
Maximum2022-11-21 00:00:00
2023-12-12T22:49:32.038331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:32.153560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T22:49:25.634534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:24.762037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:25.012880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:25.723780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:24.850840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:25.115571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:25.817769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:24.931046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:25.229126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:49:32.261350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자동차정비업체명자동차정비업체종류소재지도로명주소소재지지번주소위도경도사업등록일자면적전화번호
자동차정비업체명1.0001.0001.0001.0001.0001.0001.0001.0001.000
자동차정비업체종류1.0001.0000.0000.0000.5020.3530.0000.7961.000
소재지도로명주소1.0000.0001.0001.0001.0001.0000.9960.0001.000
소재지지번주소1.0000.0001.0001.0001.0001.0000.9960.0001.000
위도1.0000.5021.0001.0001.0000.7690.9300.0001.000
경도1.0000.3531.0001.0000.7691.0000.0000.0001.000
사업등록일자1.0000.0000.9960.9960.9300.0001.0000.6621.000
면적1.0000.7960.0000.0000.0000.0000.6621.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-12T22:49:32.410863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도면적자동차정비업체종류
위도1.000-0.7260.2330.334
경도-0.7261.000-0.2050.158
면적0.233-0.2051.0000.805
자동차정비업체종류0.3340.1580.8051.000

Missing values

2023-12-12T22:49:25.943719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:49:26.236743image/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

자동차정비업체명자동차정비업체종류소재지도로명주소소재지지번주소위도경도사업등록일자면적영업상태폐업일자휴업시작일자휴업종료일자운영시작시각운영종료시각전화번호관리기관명관리기관전화번호데이터기준일자
0상암현대서비스(주)1서울특별시 마포구 모래내로3길 19서울특별시 마포구 성산동 590-337.56598126.9036271999-08-311188.091<NA><NA><NA>9:0018:0002-374-6437마포구청 교통행정과02-3153-96332022-11-21
1한성자동차주식회사1서울특별시 마포구 모래내로 17서울특별시 마포구 성산동 593-837.564519126.9048061999-11-164766.981<NA><NA><NA>9:0018:0002-309-3421마포구청 교통행정과02-3153-96332022-11-21
2코오롱글로벌(주) 성산지점1서울특별시 마포구 월드컵로36길 22서울특별시 마포구 성산동 58937.566619126.9039491999-12-295243.291<NA><NA><NA>9:0018:0002-375-7301마포구청 교통행정과02-3153-96332022-11-21
3마포동화써비스㈜2서울특별시 마포구 모래내로 5서울특별시 마포구 성산동 592-737.564255126.9036881998-03-02400.341<NA><NA><NA>9:0018:0002-308-3100마포구청 교통행정과02-3153-96332022-11-21
4태평양카독크2서울특별시 마포구 월드컵로34길 17서울특별시 마포구 성산동 590-637.565587126.9038611994-01-20663.641<NA><NA><NA>9:0018:0002-375-7127마포구청 교통행정과02-3153-96332022-11-21
5성산자동차공업사2서울특별시 마포구 모래내로1길 3서울특별시 마포구 성산동 592-437.564551126.9038881998-04-24806.01<NA><NA><NA>9:0018:0002-376-2301마포구청 교통행정과02-3153-96332022-11-21
6아주네트웍스주식회사2서울특별시 마포구 모래내로1길 23서울특별시 마포구 성산동 591-737.56552126.9025582014-06-103380.41<NA><NA><NA>9:0018:0002-2038-4700마포구청 교통행정과02-3153-96332022-11-21
7중앙자동차써비스2서울특별시 마포구 모래내로1길 20서울특별시 마포구 성산동 590-437.565695126.9032841999-12-03407.491<NA><NA><NA>9:0018:0002-372-1787마포구청 교통행정과02-3153-96332022-11-21
8대보모터스2서울특별시 마포구 월드컵로34길 13서울특별시 마포구 성산동 590-537.565446126.9035482015-04-23400.371<NA><NA><NA>9:0018:0002-376-0615마포구청 교통행정과02-3153-96332022-11-21
9동양카독크2서울특별시 마포구 모래내로3길 11서울특별시 마포구 성산동 593-537.564984126.9045661999-04-02414.321<NA><NA><NA>9:0018:0002-375-5561마포구청 교통행정과02-3153-96332022-11-21
자동차정비업체명자동차정비업체종류소재지도로명주소소재지지번주소위도경도사업등록일자면적영업상태폐업일자휴업시작일자휴업종료일자운영시작시각운영종료시각전화번호관리기관명관리기관전화번호데이터기준일자
85다모아자동차(주)3서울특별시 마포구 가양대로 117서울특별시 마포구 상암동 166737.581192126.8771672013-07-08279.01<NA><NA><NA>9:0018:0002-376-2300마포구청 교통행정과02-3153-96332022-11-21
86알파모터스3서울특별시 마포구 백범로 35서울특별시 마포구 신수동 산 1-137.551469126.9430252015-04-13158.971<NA><NA><NA>9:0018:0002-6015-7905마포구청 교통행정과02-3153-96332022-11-21
87대원특장3서울특별시 마포구 토정로 185서울특별시 마포구 창전동 150-3937.545773126.9314992015-05-01103.61<NA><NA><NA>9:0018:0002-701-5088마포구청 교통행정과02-3153-96332022-11-21
88원스톱코너3서울특별시 마포구 월드컵로 220서울특별시 마포구 성산동 44037.567362126.900672015-07-2979.81<NA><NA><NA>9:0018:0002-305-0158마포구청 교통행정과02-3153-96332022-11-21
89조흥카세차장3서울특별시 마포구 동교로27길 96서울특별시 마포구 연남동 504-2637.561735126.9198152017-11-2343.981<NA><NA><NA>9:0018:0002-322-0137마포구청 교통행정과02-3153-96332022-11-21
90타이어타운성산점3서울특별시 마포구 월드컵로34길 8서울특별시 마포구 성산동 592-337.564793126.9033372017-12-08101.091<NA><NA><NA>9:0018:0002-376-0613마포구청 교통행정과02-3153-96332022-11-21
91현대카정비공업사3서울특별시 마포구 희우정로 100서울특별시 마포구 망원동 406-1737.554271126.9020572018-04-27101.481<NA><NA><NA>9:0018:0002-338-1889마포구청 교통행정과02-3153-96332022-11-21
92주식회사헌터코리아엔지니어링3서울특별시 마포구 토정로 137서울특별시 마포구 상수동 25037.545688126.926132020-04-22135.141<NA><NA><NA>9:0018:0002-323-3011마포구청 교통행정과02-3153-96332022-11-21
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