Overview

Dataset statistics

Number of variables6
Number of observations114
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory53.2 B

Variable types

Text1
Numeric3
Categorical1
DateTime1

Dataset

Description강원특별자치도 춘천시 자동차 등록현황에 대한 차종,관용 등록대수, 자가용 등록대수, 영업용 등록대수, 사업용 등록대수 및 기준일자에 대한 자료
Author강원특별자치도 춘천시
URLhttps://www.data.go.kr/data/15040607/fileData.do

Alerts

사업용 has constant value ""Constant
기준일자 has constant value ""Constant
관용 is highly overall correlated with 자가용High correlation
자가용 is highly overall correlated with 관용High correlation
차종 has unique valuesUnique
관용 has 64 (56.1%) zerosZeros
자가용 has 28 (24.6%) zerosZeros
영업용 has 46 (40.4%) zerosZeros

Reproduction

Analysis started2023-12-12 22:24:12.226402
Analysis finished2023-12-12 22:24:13.605240
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

차종
Text

UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T07:24:13.756706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length11.921053
Min length3

Characters and Unicode

Total characters1359
Distinct characters115
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)100.0%

Sample

1st row승용일반형 국산 800CC미만
2nd row승용일반형 국산 1000CC미만
3rd row승용일반형 국산 1500CC미만
4th row승용일반형 국산 2000CC미만
5th row승용일반형 국산 2500CC미만
ValueCountFrequency (%)
승용일반형 26
 
10.2%
외산 13
 
5.1%
국산 13
 
5.1%
이하 10
 
3.9%
미만 9
 
3.5%
화물 9
 
3.5%
승용겸 8
 
3.1%
승용다목적형 8
 
3.1%
승용기타형 8
 
3.1%
화물카고형 7
 
2.8%
Other values (75) 143
56.3%
2023-12-13T07:24:14.119008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
 
10.3%
0 104
 
7.7%
C 81
 
6.0%
형 75
 
5.5%
용 63
 
4.6%
승 57
 
4.2%
미 44
 
3.2%
만 44
 
3.2%
5 35
 
2.6%
반 32
 
2.4%
Other values (105) 684
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 883
65.0%
Decimal Number 197
 
14.5%
Space Separator 140
 
10.3%
Uppercase Letter 81
 
6.0%
Close Punctuation 26
 
1.9%
Open Punctuation 26
 
1.9%
Other Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
형 75
 
8.5%
용 63
 
7.1%
승 57
 
6.5%
미 44
 
5.0%
만 44
 
5.0%
반 32
 
3.6%
물 31
 
3.5%
화 31
 
3.5%
일 31
 
3.5%
산 26
 
2.9%
Other values (93) 449
50.8%
Decimal Number
ValueCountFrequency (%)
0 104
52.8%
5 35
 
17.8%
1 21
 
10.7%
2 15
 
7.6%
3 15
 
7.6%
4 4
 
2.0%
8 3
 
1.5%
Space Separator
ValueCountFrequency (%)
140
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 883
65.0%
Common 395
29.1%
Latin 81
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
형 75
 
8.5%
용 63
 
7.1%
승 57
 
6.5%
미 44
 
5.0%
만 44
 
5.0%
반 32
 
3.6%
물 31
 
3.5%
화 31
 
3.5%
일 31
 
3.5%
산 26
 
2.9%
Other values (93) 449
50.8%
Common
ValueCountFrequency (%)
140
35.4%
0 104
26.3%
5 35
 
8.9%
) 26
 
6.6%
( 26
 
6.6%
1 21
 
5.3%
2 15
 
3.8%
3 15
 
3.8%
, 6
 
1.5%
4 4
 
1.0%
Latin
ValueCountFrequency (%)
C 81
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 883
65.0%
ASCII 476
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
29.4%
0 104
21.8%
C 81
17.0%
5 35
 
7.4%
) 26
 
5.5%
( 26
 
5.5%
1 21
 
4.4%
2 15
 
3.2%
3 15
 
3.2%
, 6
 
1.3%
Other values (2) 7
 
1.5%
Hangul
ValueCountFrequency (%)
형 75
 
8.5%
용 63
 
7.1%
승 57
 
6.5%
미 44
 
5.0%
만 44
 
5.0%
반 32
 
3.6%
물 31
 
3.5%
화 31
 
3.5%
일 31
 
3.5%
산 26
 
2.9%
Other values (93) 449
50.8%

관용
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.7192982
Minimum0
Maximum135
Zeros64
Zeros (%)56.1%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T07:24:14.275074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile35.75
Maximum135
Range135
Interquartile range (IQR)5

Descriptive statistics

Standard deviation19.60608
Coefficient of variation (CV)2.5398786
Kurtosis21.4396
Mean7.7192982
Median Absolute Deviation (MAD)0
Skewness4.2897636
Sum880
Variance384.39839
MonotonicityNot monotonic
2023-12-13T07:24:14.427743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 64
56.1%
1 9
 
7.9%
4 5
 
4.4%
2 4
 
3.5%
12 3
 
2.6%
21 3
 
2.6%
11 3
 
2.6%
6 2
 
1.8%
19 2
 
1.8%
5 2
 
1.8%
Other values (16) 17
 
14.9%
ValueCountFrequency (%)
0 64
56.1%
1 9
 
7.9%
2 4
 
3.5%
3 2
 
1.8%
4 5
 
4.4%
5 2
 
1.8%
6 2
 
1.8%
7 1
 
0.9%
11 3
 
2.6%
12 3
 
2.6%
ValueCountFrequency (%)
135 1
 
0.9%
106 1
 
0.9%
68 1
 
0.9%
65 1
 
0.9%
58 1
 
0.9%
39 1
 
0.9%
34 1
 
0.9%
29 1
 
0.9%
25 1
 
0.9%
21 3
2.6%

자가용
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1250.0088
Minimum0
Maximum32349
Zeros28
Zeros (%)24.6%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T07:24:14.568403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median47
Q3442.25
95-th percentile5291.8
Maximum32349
Range32349
Interquartile range (IQR)441.25

Descriptive statistics

Standard deviation4123.8834
Coefficient of variation (CV)3.2990836
Kurtosis34.856521
Mean1250.0088
Median Absolute Deviation (MAD)47
Skewness5.5564073
Sum142501
Variance17006414
MonotonicityNot monotonic
2023-12-13T07:24:14.724072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28
24.6%
6 4
 
3.5%
1 3
 
2.6%
4 3
 
2.6%
3 3
 
2.6%
25 3
 
2.6%
24 2
 
1.8%
11 2
 
1.8%
68 2
 
1.8%
33 1
 
0.9%
Other values (63) 63
55.3%
ValueCountFrequency (%)
0 28
24.6%
1 3
 
2.6%
3 3
 
2.6%
4 3
 
2.6%
6 4
 
3.5%
7 1
 
0.9%
8 1
 
0.9%
10 1
 
0.9%
11 2
 
1.8%
14 1
 
0.9%
ValueCountFrequency (%)
32349 1
0.9%
21597 1
0.9%
17065 1
0.9%
9266 1
0.9%
7095 1
0.9%
6246 1
0.9%
4778 1
0.9%
4244 1
0.9%
3900 1
0.9%
3307 1
0.9%

영업용
Real number (ℝ)

ZEROS 

Distinct44
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.27193
Minimum0
Maximum1288
Zeros46
Zeros (%)40.4%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T07:24:14.867171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q327.75
95-th percentile257.25
Maximum1288
Range1288
Interquartile range (IQR)27.75

Descriptive statistics

Standard deviation159.56253
Coefficient of variation (CV)2.8868637
Kurtosis34.842825
Mean55.27193
Median Absolute Deviation (MAD)2
Skewness5.3503834
Sum6301
Variance25460.2
MonotonicityNot monotonic
2023-12-13T07:24:15.026617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 46
40.4%
1 9
 
7.9%
2 8
 
7.0%
6 4
 
3.5%
10 3
 
2.6%
27 2
 
1.8%
12 2
 
1.8%
11 2
 
1.8%
4 2
 
1.8%
46 2
 
1.8%
Other values (34) 34
29.8%
ValueCountFrequency (%)
0 46
40.4%
1 9
 
7.9%
2 8
 
7.0%
3 1
 
0.9%
4 2
 
1.8%
5 1
 
0.9%
6 4
 
3.5%
7 1
 
0.9%
8 1
 
0.9%
10 3
 
2.6%
ValueCountFrequency (%)
1288 1
0.9%
762 1
0.9%
525 1
0.9%
386 1
0.9%
363 1
0.9%
280 1
0.9%
245 1
0.9%
193 1
0.9%
179 1
0.9%
178 1
0.9%

사업용
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
114 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 114
100.0%

Length

2023-12-13T07:24:15.176832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:24:15.286724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 114
100.0%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2023-10-31 00:00:00
Maximum2023-10-31 00:00:00
2023-12-13T07:24:15.353318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:24:15.465212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T07:24:13.038289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:24:12.378244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:24:12.668489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:24:13.202104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:24:12.479741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:24:12.775991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:24:13.347726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:24:12.568626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:24:12.899940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:24:15.548432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관용자가용영업용
관용1.0000.7660.733
자가용0.7661.0000.831
영업용0.7330.8311.000
2023-12-13T07:24:15.629447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관용자가용영업용
관용1.0000.6420.466
자가용0.6421.0000.444
영업용0.4660.4441.000

Missing values

2023-12-13T07:24:13.473968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:24:13.568487image/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

차종관용자가용영업용사업용기준일자
0승용일반형 국산 800CC미만1535002023-10-31
1승용일반형 국산 1000CC미만29170652702023-10-31
2승용일반형 국산 1500CC미만33307802023-10-31
3승용일반형 국산 2000CC미만10632349128802023-10-31
4승용일반형 국산 2500CC미만470952202023-10-31
5승용일반형 국산 3000CC미만4390019302023-10-31
6승용일반형 국산 3500CC미만623298702023-10-31
7승용일반형 국산 4000CC미만4765502023-10-31
8승용일반형 국산 4500CC미만06002023-10-31
9승용일반형 국산 5000CC미만025002023-10-31
차종관용자가용영업용사업용기준일자
104구난차 10톤 미만00102023-10-31
105구난차 10톤 이상00202023-10-31
106견인차 5톤 이하01202023-10-31
107견인차 10톤 미만00102023-10-31
108견인차 10톤 이상0415402023-10-31
109특수용도형(고소작업차)516212902023-10-31
110특수용도형(고가사다리소방차)21202023-10-31
111특수용도형(오가크레인)00002023-10-31
112특수용도형(피견인형)085002023-10-31
113특수용도형(기타)122217402023-10-31