Overview

Dataset statistics

Number of variables3
Number of observations37
Missing cells24
Missing cells (%)21.6%
Duplicate rows2
Duplicate rows (%)5.4%
Total size in memory1020.0 B
Average record size in memory27.6 B

Variable types

Text1
Categorical1
Unsupported1

Dataset

Description부산광역시기장군_연도별주정차단속현황_20230609
Author부산광역시 기장군
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15101513

Alerts

Dataset has 2 (5.4%) duplicate rowsDuplicates
월별 위반일자 기준 통계 has 24 (64.9%) missing valuesMissing
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 16:29:55.914375
Analysis finished2023-12-10 16:29:56.242019
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

월별 위반일자 기준 통계
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing24
Missing (%)64.9%
Memory size428.0 B
2023-12-11T01:29:56.389433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.7692308
Min length4

Characters and Unicode

Total characters88
Distinct characters15
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

Unique13 ?
Unique (%)100.0%

Sample

1st row위반년월
2nd row2011-01
3rd row2011-02
4th row2011-03
5th row2011-04
ValueCountFrequency (%)
위반년월 1
 
7.7%
2011-01 1
 
7.7%
2011-02 1
 
7.7%
2011-03 1
 
7.7%
2011-04 1
 
7.7%
2011-05 1
 
7.7%
2011-06 1
 
7.7%
2011-07 1
 
7.7%
2011-08 1
 
7.7%
2011-09 1
 
7.7%
Other values (3) 3
23.1%
2023-12-11T01:29:56.787548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 29
33.0%
0 22
25.0%
2 14
15.9%
- 12
13.6%
위 1
 
1.1%
반 1
 
1.1%
년 1
 
1.1%
월 1
 
1.1%
3 1
 
1.1%
4 1
 
1.1%
Other values (5) 5
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
81.8%
Dash Punctuation 12
 
13.6%
Other Letter 4
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 29
40.3%
0 22
30.6%
2 14
19.4%
3 1
 
1.4%
4 1
 
1.4%
5 1
 
1.4%
6 1
 
1.4%
7 1
 
1.4%
8 1
 
1.4%
9 1
 
1.4%
Other Letter
ValueCountFrequency (%)
위 1
25.0%
반 1
25.0%
년 1
25.0%
월 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84
95.5%
Hangul 4
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 29
34.5%
0 22
26.2%
2 14
16.7%
- 12
14.3%
3 1
 
1.2%
4 1
 
1.2%
5 1
 
1.2%
6 1
 
1.2%
7 1
 
1.2%
8 1
 
1.2%
Hangul
ValueCountFrequency (%)
위 1
25.0%
반 1
25.0%
년 1
25.0%
월 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
95.5%
Hangul 4
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 29
34.5%
0 22
26.2%
2 14
16.7%
- 12
14.3%
3 1
 
1.2%
4 1
 
1.2%
5 1
 
1.2%
6 1
 
1.2%
7 1
 
1.2%
8 1
 
1.2%
Hangul
ValueCountFrequency (%)
위 1
25.0%
반 1
25.0%
년 1
25.0%
월 1
25.0%

Unnamed: 1
Categorical

Distinct4
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size428.0 B
부과
12 
> 수납
12 
> 미수납
12 
구분
 
1

Length

Max length5
Median length4
Mean length3.6216216
Min length2

Unique

Unique1 ?
Unique (%)2.7%

Sample

1st row구분
2nd row부과
3rd row> 수납
4th row> 미수납
5th row부과

Common Values

ValueCountFrequency (%)
부과 12
32.4%
> 수납 12
32.4%
> 미수납 12
32.4%
구분 1
 
2.7%

Length

2023-12-11T01:29:56.948052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:29:57.113629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
24
39.3%
부과 12
19.7%
수납 12
19.7%
미수납 12
19.7%
구분 1
 
1.6%

Unnamed: 2
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size428.0 B

Correlations

2023-12-11T01:29:57.226260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월별 위반일자 기준 통계Unnamed: 1
월별 위반일자 기준 통계1.0001.000
Unnamed: 11.0001.000

Missing values

2023-12-11T01:29:56.071647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:29:56.195436image/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

월별 위반일자 기준 통계Unnamed: 1Unnamed: 2
0위반년월구분건수
12011-01부과861
2<NA>> 수납786
3<NA>> 미수납75
42011-02부과569
5<NA>> 수납509
6<NA>> 미수납60
72011-03부과609
8<NA>> 수납554
9<NA>> 미수납55
월별 위반일자 기준 통계Unnamed: 1Unnamed: 2
27<NA>> 미수납67
282011-10부과848
29<NA>> 수납769
30<NA>> 미수납79
312011-11부과944
32<NA>> 수납861
33<NA>> 미수납83
342011-12부과646
35<NA>> 수납593
36<NA>> 미수납53

Duplicate rows

Most frequently occurring

월별 위반일자 기준 통계Unnamed: 1# duplicates
0<NA>> 미수납12
1<NA>> 수납12