Overview

Dataset statistics

Number of variables4
Number of observations62
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory35.1 B

Variable types

DateTime1
Categorical1
Text1
Numeric1

Dataset

Description2018년~2022년의 서울특별시 성북구 불법주정차 과태료 부과 동별 데이터로서 단속동 및 단속건수 등의 정보를 포함합니다.
URLhttps://www.data.go.kr/data/15113658/fileData.do

Alerts

데이터기준일 has constant value ""Constant
과태료명 has constant value ""Constant
단속동 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:34:30.961798
Analysis finished2023-12-12 07:34:31.392089
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size628.0 B
Minimum2023-05-04 00:00:00
Maximum2023-05-04 00:00:00
2023-12-12T16:34:31.448881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:31.554611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

과태료명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size628.0 B
주정차위반과태료
62 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주정차위반과태료 62
100.0%

Length

2023-12-12T16:34:31.686374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:34:31.810186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주정차위반과태료 62
100.0%

단속동
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-12T16:34:32.023218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length14.435484
Min length13

Characters and Unicode

Total characters895
Distinct characters39
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

Unique62 ?
Unique (%)100.0%

Sample

1st row서울특별시 성북구 길음1동
2nd row서울특별시 성북구 길음2동
3rd row서울특별시 성북구 길음동
4th row서울특별시 성북구 돈암1동
5th row서울특별시 성북구 돈암2동
ValueCountFrequency (%)
서울특별시 62
33.3%
성북구 62
33.3%
삼선동2가 1
 
0.5%
하월곡4동 1
 
0.5%
삼선동3가 1
 
0.5%
삼선동4가 1
 
0.5%
삼선동5가 1
 
0.5%
상월곡동 1
 
0.5%
석관1동 1
 
0.5%
석관동 1
 
0.5%
Other values (54) 54
29.0%
2023-12-12T16:34:32.465266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
124
13.9%
동 77
 
8.6%
성 64
 
7.2%
북 64
 
7.2%
서 62
 
6.9%
특 62
 
6.9%
별 62
 
6.9%
시 62
 
6.9%
구 62
 
6.9%
울 62
 
6.9%
Other values (29) 194
21.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 724
80.9%
Space Separator 124
 
13.9%
Decimal Number 47
 
5.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 77
10.6%
성 64
8.8%
북 64
8.8%
서 62
8.6%
특 62
8.6%
별 62
8.6%
시 62
8.6%
구 62
8.6%
울 62
8.6%
가 30
 
4.1%
Other values (21) 117
16.2%
Decimal Number
ValueCountFrequency (%)
1 14
29.8%
2 10
21.3%
3 7
14.9%
4 7
14.9%
5 5
 
10.6%
7 2
 
4.3%
6 2
 
4.3%
Space Separator
ValueCountFrequency (%)
124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 724
80.9%
Common 171
 
19.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 77
10.6%
성 64
8.8%
북 64
8.8%
서 62
8.6%
특 62
8.6%
별 62
8.6%
시 62
8.6%
구 62
8.6%
울 62
8.6%
가 30
 
4.1%
Other values (21) 117
16.2%
Common
ValueCountFrequency (%)
124
72.5%
1 14
 
8.2%
2 10
 
5.8%
3 7
 
4.1%
4 7
 
4.1%
5 5
 
2.9%
7 2
 
1.2%
6 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 724
80.9%
ASCII 171
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
124
72.5%
1 14
 
8.2%
2 10
 
5.8%
3 7
 
4.1%
4 7
 
4.1%
5 5
 
2.9%
7 2
 
1.2%
6 2
 
1.2%
Hangul
ValueCountFrequency (%)
동 77
10.6%
성 64
8.8%
북 64
8.8%
서 62
8.6%
특 62
8.6%
별 62
8.6%
시 62
8.6%
구 62
8.6%
울 62
8.6%
가 30
 
4.1%
Other values (21) 117
16.2%

단속건수
Real number (ℝ)

Distinct59
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3903.6774
Minimum1
Maximum36101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2023-12-12T16:34:32.655773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.05
Q1623.75
median1192
Q33018.75
95-th percentile20461.95
Maximum36101
Range36100
Interquartile range (IQR)2395

Descriptive statistics

Standard deviation6968.882
Coefficient of variation (CV)1.7852095
Kurtosis8.4446007
Mean3903.6774
Median Absolute Deviation (MAD)817
Skewness2.8331994
Sum242028
Variance48565316
MonotonicityNot monotonic
2023-12-12T16:34:32.839144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 4
 
6.5%
1940 1
 
1.6%
622 1
 
1.6%
1122 1
 
1.6%
3514 1
 
1.6%
3475 1
 
1.6%
18409 1
 
1.6%
11163 1
 
1.6%
2527 1
 
1.6%
1980 1
 
1.6%
Other values (49) 49
79.0%
ValueCountFrequency (%)
1 4
6.5%
2 1
 
1.6%
9 1
 
1.6%
14 1
 
1.6%
50 1
 
1.6%
235 1
 
1.6%
288 1
 
1.6%
346 1
 
1.6%
433 1
 
1.6%
493 1
 
1.6%
ValueCountFrequency (%)
36101 1
1.6%
25159 1
1.6%
21177 1
1.6%
20570 1
1.6%
18409 1
1.6%
13775 1
1.6%
11494 1
1.6%
11178 1
1.6%
11163 1
1.6%
5444 1
1.6%

Interactions

2023-12-12T16:34:31.084181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:34:32.947111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속동단속건수
단속동1.0001.000
단속건수1.0001.000

Missing values

2023-12-12T16:34:31.243753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:34:31.357184image/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

데이터기준일과태료명단속동단속건수
02023-05-04주정차위반과태료서울특별시 성북구 길음1동1940
12023-05-04주정차위반과태료서울특별시 성북구 길음2동9
22023-05-04주정차위반과태료서울특별시 성북구 길음동13775
32023-05-04주정차위반과태료서울특별시 성북구 돈암1동346
42023-05-04주정차위반과태료서울특별시 성북구 돈암2동493
52023-05-04주정차위반과태료서울특별시 성북구 돈암동4784
62023-05-04주정차위반과태료서울특별시 성북구 동선1동1
72023-05-04주정차위반과태료서울특별시 성북구 동선동915
82023-05-04주정차위반과태료서울특별시 성북구 동선동1가11178
92023-05-04주정차위반과태료서울특별시 성북구 동선동2가5444
데이터기준일과태료명단속동단속건수
522023-05-04주정차위반과태료서울특별시 성북구 장위동21177
532023-05-04주정차위반과태료서울특별시 성북구 정릉1동664
542023-05-04주정차위반과태료서울특별시 성북구 정릉2동235
552023-05-04주정차위반과태료서울특별시 성북구 정릉3동50
562023-05-04주정차위반과태료서울특별시 성북구 정릉4동629
572023-05-04주정차위반과태료서울특별시 성북구 정릉동25159
582023-05-04주정차위반과태료서울특별시 성북구 종암동20570
592023-05-04주정차위반과태료서울특별시 성북구 하월곡1동1
602023-05-04주정차위반과태료서울특별시 성북구 하월곡4동2
612023-05-04주정차위반과태료서울특별시 성북구 하월곡동36101