Overview

Dataset statistics

Number of variables7
Number of observations883
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.0 KiB
Average record size in memory59.1 B

Variable types

Numeric3
DateTime1
Categorical2
Text1

Dataset

Description대전광역시 서구 무단방치차량 단속현황에 대한 정보(무단방치차량 단속일자, 무단방치차량 위반장소, 무단방치차량 위도, 무단방치차량 경도) 등을 제공합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15075605/fileData.do

Alerts

연번 is highly overall correlated with 차량분류High correlation
위도 is highly overall correlated with 위반동명High correlation
경도 is highly overall correlated with 위반동명High correlation
차량분류 is highly overall correlated with 연번High correlation
위반동명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-14 13:44:59.434385
Analysis finished2024-01-14 13:45:01.517280
Duration2.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct883
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean442
Minimum1
Maximum883
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-01-14T22:45:01.639385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45.1
Q1221.5
median442
Q3662.5
95-th percentile838.9
Maximum883
Range882
Interquartile range (IQR)441

Descriptive statistics

Standard deviation255.04444
Coefficient of variation (CV)0.57702362
Kurtosis-1.2
Mean442
Median Absolute Deviation (MAD)221
Skewness0
Sum390286
Variance65047.667
MonotonicityStrictly increasing
2024-01-14T22:45:01.834358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
595 1
 
0.1%
584 1
 
0.1%
585 1
 
0.1%
586 1
 
0.1%
587 1
 
0.1%
588 1
 
0.1%
589 1
 
0.1%
590 1
 
0.1%
591 1
 
0.1%
Other values (873) 873
98.9%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
883 1
0.1%
882 1
0.1%
881 1
0.1%
880 1
0.1%
879 1
0.1%
878 1
0.1%
877 1
0.1%
876 1
0.1%
875 1
0.1%
874 1
0.1%

단속일자
Date

Distinct150
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
Minimum2023-01-03 00:00:00
Maximum2023-12-26 00:00:00
2024-01-14T22:45:02.023707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:45:02.260015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

차량분류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
자동차
490 
이륜차
393 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차 490
55.5%
이륜차 393
44.5%

Length

2024-01-14T22:45:02.474833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T22:45:02.592879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차 490
55.5%
이륜차 393
44.5%

위반장소
Text

Distinct634
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-01-14T22:45:03.000504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length18.477916
Min length9

Characters and Unicode

Total characters16316
Distinct characters108
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique510 ?
Unique (%)57.8%

Sample

1st row대전광역시 서구 가장동 40-4
2nd row대전광역시 서구 변동 81-25
3rd row대전광역시 서구 가장동 34-7
4th row대전광역시 서구 둔산동 1809
5th row대전광역시 서구 내동 161-6
ValueCountFrequency (%)
서구 885
25.1%
대전광역시 880
25.0%
관저동 36
 
1.0%
월평동 34
 
1.0%
도마동 31
 
0.9%
정림동 29
 
0.8%
703 23
 
0.7%
도산로 20
 
0.6%
도안동 19
 
0.5%
대덕대로 19
 
0.5%
Other values (668) 1550
44.0%
2024-01-14T22:45:03.733310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3029
18.6%
대 996
 
6.1%
서 919
 
5.6%
구 892
 
5.5%
역 886
 
5.4%
전 886
 
5.4%
광 881
 
5.4%
시 880
 
5.4%
1 692
 
4.2%
로 557
 
3.4%
Other values (98) 5698
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9724
59.6%
Decimal Number 3311
 
20.3%
Space Separator 3029
 
18.6%
Dash Punctuation 251
 
1.5%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 996
10.2%
서 919
9.5%
구 892
9.2%
역 886
9.1%
전 886
9.1%
광 881
9.1%
시 880
9.0%
로 557
 
5.7%
길 342
 
3.5%
동 331
 
3.4%
Other values (85) 2154
22.2%
Decimal Number
ValueCountFrequency (%)
1 692
20.9%
2 418
12.6%
3 361
10.9%
5 293
8.8%
7 280
8.5%
0 257
 
7.8%
9 255
 
7.7%
4 253
 
7.6%
6 251
 
7.6%
8 251
 
7.6%
Space Separator
ValueCountFrequency (%)
3029
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 251
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9724
59.6%
Common 6592
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 996
10.2%
서 919
9.5%
구 892
9.2%
역 886
9.1%
전 886
9.1%
광 881
9.1%
시 880
9.0%
로 557
 
5.7%
길 342
 
3.5%
동 331
 
3.4%
Other values (85) 2154
22.2%
Common
ValueCountFrequency (%)
3029
45.9%
1 692
 
10.5%
2 418
 
6.3%
3 361
 
5.5%
5 293
 
4.4%
7 280
 
4.2%
0 257
 
3.9%
9 255
 
3.9%
4 253
 
3.8%
- 251
 
3.8%
Other values (3) 503
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9724
59.6%
ASCII 6592
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3029
45.9%
1 692
 
10.5%
2 418
 
6.3%
3 361
 
5.5%
5 293
 
4.4%
7 280
 
4.2%
0 257
 
3.9%
9 255
 
3.9%
4 253
 
3.8%
- 251
 
3.8%
Other values (3) 503
 
7.6%
Hangul
ValueCountFrequency (%)
대 996
10.2%
서 919
9.5%
구 892
9.2%
역 886
9.1%
전 886
9.1%
광 881
9.1%
시 880
9.0%
로 557
 
5.7%
길 342
 
3.5%
동 331
 
3.4%
Other values (85) 2154
22.2%

위반동명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
도마동
115 
월평동
104 
갈마동
101 
관저동
80 
탄방동
65 
Other values (15)
418 

Length

Max length4
Median length3
Mean length2.9501699
Min length2

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row가장동
2nd row변동
3rd row가장동
4th row둔산동
5th row내동

Common Values

ValueCountFrequency (%)
도마동 115
13.0%
월평동 104
11.8%
갈마동 101
11.4%
관저동 80
9.1%
탄방동 65
7.4%
둔산동 62
 
7.0%
도안동 55
 
6.2%
변동 54
 
6.1%
괴정동 53
 
6.0%
가수원동 34
 
3.9%
Other values (10) 160
18.1%

Length

2024-01-14T22:45:04.002405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도마동 115
13.0%
월평동 104
11.8%
갈마동 101
11.4%
관저동 80
9.1%
탄방동 65
7.4%
둔산동 62
 
7.0%
도안동 55
 
6.2%
변동 54
 
6.1%
괴정동 53
 
6.0%
가수원동 34
 
3.9%
Other values (10) 160
18.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct597
Distinct (%)67.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.36872
Minimum127.28429
Maximum127.40111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-01-14T22:45:04.214713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.28429
5-th percentile127.33613
Q1127.35502
median127.37186
Q3127.38041
95-th percentile127.3953
Maximum127.40111
Range0.1168168
Interquartile range (IQR)0.02539755

Descriptive statistics

Standard deviation0.017756144
Coefficient of variation (CV)0.00013940741
Kurtosis0.4513158
Mean127.36872
Median Absolute Deviation (MAD)0.0106141
Skewness-0.62736317
Sum112466.58
Variance0.00031528064
MonotonicityNot monotonic
2024-01-14T22:45:04.461199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.3628776 23
 
2.6%
127.3711552 11
 
1.2%
127.3914823 11
 
1.2%
127.3507234 10
 
1.1%
127.3774758 9
 
1.0%
127.3546802 8
 
0.9%
127.336128 7
 
0.8%
127.3686724 6
 
0.7%
127.3998091 6
 
0.7%
127.380349 6
 
0.7%
Other values (587) 786
89.0%
ValueCountFrequency (%)
127.2842913 1
0.1%
127.2872682 1
0.1%
127.3219644 1
0.1%
127.3224118 1
0.1%
127.3224778 1
0.1%
127.323208 1
0.1%
127.3246026 1
0.1%
127.3251799 1
0.1%
127.3262222 1
0.1%
127.3273077 1
0.1%
ValueCountFrequency (%)
127.4011081 1
0.1%
127.4008523 1
0.1%
127.4008231 1
0.1%
127.4006914 1
0.1%
127.4004753 1
0.1%
127.4004449 2
0.2%
127.4003912 1
0.1%
127.4002842 2
0.2%
127.4002709 1
0.1%
127.4000479 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct597
Distinct (%)67.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.329493
Minimum36.235047
Maximum36.370787
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-01-14T22:45:04.671870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.235047
5-th percentile36.294449
Q136.311959
median36.333608
Q336.347171
95-th percentile36.359058
Maximum36.370787
Range0.13574052
Interquartile range (IQR)0.035211425

Descriptive statistics

Standard deviation0.022432826
Coefficient of variation (CV)0.00061748248
Kurtosis-0.23468967
Mean36.329493
Median Absolute Deviation (MAD)0.01515721
Skewness-0.54217398
Sum32078.943
Variance0.00050323167
MonotonicityNot monotonic
2024-01-14T22:45:04.902274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.30309406 23
 
2.6%
36.32198301 11
 
1.2%
36.36338329 11
 
1.2%
36.29444887 10
 
1.1%
36.32124996 9
 
1.0%
36.28578212 8
 
0.9%
36.30758128 7
 
0.8%
36.31910397 6
 
0.7%
36.34555353 6
 
0.7%
36.3269067 6
 
0.7%
Other values (587) 786
89.0%
ValueCountFrequency (%)
36.23504688 1
 
0.1%
36.25394467 1
 
0.1%
36.25516853 1
 
0.1%
36.25900265 1
 
0.1%
36.2625466 1
 
0.1%
36.27100161 1
 
0.1%
36.27501582 2
0.2%
36.27503312 3
0.3%
36.2752868 1
 
0.1%
36.27962868 4
0.5%
ValueCountFrequency (%)
36.3707874 3
0.3%
36.37067734 1
 
0.1%
36.37057001 1
 
0.1%
36.36932675 1
 
0.1%
36.36799721 1
 
0.1%
36.36717312 4
0.5%
36.36692625 1
 
0.1%
36.36642058 2
0.2%
36.36617358 1
 
0.1%
36.3635821 1
 
0.1%

Interactions

2024-01-14T22:45:00.699234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:44:59.841582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:45:00.247666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:45:00.838769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:44:59.994815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:45:00.386234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:45:01.013610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:45:00.123819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:45:00.546497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-14T22:45:05.332034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번차량분류위반동명위도경도
연번1.0000.9970.4630.2550.413
차량분류0.9971.0000.4070.2940.314
위반동명0.4630.4071.0000.9430.984
위도0.2550.2940.9431.0000.718
경도0.4130.3140.9840.7181.000
2024-01-14T22:45:05.437252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차량분류위반동명
차량분류1.0000.318
위반동명0.3181.000
2024-01-14T22:45:05.530490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도차량분류위반동명
연번1.0000.1640.0420.9440.163
위도0.1641.0000.4710.2200.742
경도0.0420.4711.0000.2400.783
차량분류0.9440.2200.2401.0000.318
위반동명0.1630.7420.7830.3181.000

Missing values

2024-01-14T22:45:01.259285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-14T22:45:01.450952image/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

연번단속일자차량분류위반장소위반동명위도경도
012023-01-03자동차대전광역시 서구 가장동 40-4가장동127.38502536.329932
122023-01-03자동차대전광역시 서구 변동 81-25변동127.37098236.328309
232023-01-03자동차대전광역시 서구 가장동 34-7가장동127.38657736.328092
342023-01-03자동차대전광역시 서구 둔산동 1809둔산동127.39814336.355107
452023-01-03자동차대전광역시 서구 내동 161-6내동127.37189336.335524
562023-01-03자동차대전광역시 서구 한밭대로570번길 33월평동127.36237536.356707
672023-01-03자동차대전광역시 서구 갈마로 10갈마동127.36880336.351315
782023-01-03자동차대전광역시 서구 갈마로 10갈마동127.36880336.351315
892023-01-06자동차대전광역시 서구 관저동 건양대학교병원관저동127.33188136.296382
9102023-01-07자동차대전광역시 서구 대덕대로 294둔산동127.37989436.359061
연번단속일자차량분류위반장소위반동명위도경도
8738742023-12-19이륜차대전광역시 서구 관저북로 52관저동127.33864436.304973
8748752023-12-19이륜차대전광역시 서구 도솔로388번길 46괴정동127.39015336.339466
8758762023-12-19이륜차대전광역시 서구 변동중로 62변동127.37612136.329165
8768772023-12-19이륜차대전광역시 서구 월평중로14번길 37월평동127.36614836.355808
8778782023-12-21이륜차대전광역시 서구 가수원동 486-6가수원동127.35375836.30455
8788792023-12-21이륜차대전광역시 서구 관저동 1622관저동127.34514336.300141
8798802023-12-21이륜차대전광역시 서구 괴곡동 731-1괴곡동127.35518636.281152
8808812023-12-21이륜차대전광역시 서구 도마동 161-34도마동127.37143836.313071
8818822023-12-21이륜차대전광역시 서구 둔산서로 63둔산동127.38259936.352325
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