Overview

Dataset statistics

Number of variables4
Number of observations1254
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.0 KiB
Average record size in memory35.1 B

Variable types

Categorical3
Numeric1

Dataset

Description운전면허시험장 관련 공지사항 수신정보 관련 내용으로 운전면허시험장 지역별 발급(코드) 번호 안내가 되어 있음
Author도로교통공단
URLhttps://www.data.go.kr/data/15049937/fileData.do

Alerts

작성연도 has constant value ""Constant
수신구분 is highly imbalanced (78.1%)Imbalance

Reproduction

Analysis started2023-12-12 04:39:11.817271
Analysis finished2023-12-12 04:39:12.188559
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

작성연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2019
1254 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 1254
100.0%

Length

2023-12-12T13:39:12.253219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:39:12.352278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 1254
100.0%

게시번호
Real number (ℝ)

Distinct76
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.551834
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2023-12-12T13:39:12.461951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q118
median34.5
Q355
95-th percentile76
Maximum84
Range83
Interquartile range (IQR)37

Descriptive statistics

Standard deviation22.772726
Coefficient of variation (CV)0.62302555
Kurtosis-1.0181343
Mean36.551834
Median Absolute Deviation (MAD)18.5
Skewness0.23993425
Sum45836
Variance518.59707
MonotonicityIncreasing
2023-12-12T13:39:12.635596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84 30
 
2.4%
76 30
 
2.4%
68 30
 
2.4%
73 30
 
2.4%
1 29
 
2.3%
43 29
 
2.3%
64 29
 
2.3%
33 29
 
2.3%
35 29
 
2.3%
36 29
 
2.3%
Other values (66) 960
76.6%
ValueCountFrequency (%)
1 29
2.3%
2 29
2.3%
3 29
2.3%
5 1
 
0.1%
6 29
2.3%
7 12
1.0%
8 1
 
0.1%
9 28
2.2%
10 29
2.3%
11 29
2.3%
ValueCountFrequency (%)
84 30
2.4%
83 1
 
0.1%
82 1
 
0.1%
81 1
 
0.1%
80 1
 
0.1%
79 1
 
0.1%
78 1
 
0.1%
77 1
 
0.1%
76 30
2.4%
75 1
 
0.1%

수신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2
1210 
1
 
44

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1210
96.5%
1 44
 
3.5%

Length

2023-12-12T13:39:12.765714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:39:12.867971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1210
96.5%
1 44
 
3.5%

수신지명
Categorical

Distinct43
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
광 양
 
41
예 산
 
41
충 주
 
41
태 백
 
41
강 남
 
41
Other values (38)
1049 

Length

Max length6
Median length6
Mean length5.708134
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row본 부
2nd row서 부
3rd row도 봉
4th row강 남
5th row강 서

Common Values

ValueCountFrequency (%)
광 양 41
 
3.3%
예 산 41
 
3.3%
충 주 41
 
3.3%
태 백 41
 
3.3%
강 남 41
 
3.3%
강 서 41
 
3.3%
부산북부 41
 
3.3%
인 천 41
 
3.3%
춘 천 41
 
3.3%
청 주 41
 
3.3%
Other values (33) 844
67.3%

Length

2023-12-12T13:39:12.982793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주 203
 
8.5%
산 163
 
6.8%
전 123
 
5.1%
강 123
 
5.1%
부 117
 
4.9%
천 86
 
3.6%
서 82
 
3.4%
인 82
 
3.4%
대 82
 
3.4%
남 82
 
3.4%
Other values (41) 1252
52.3%

Interactions

2023-12-12T13:39:11.960498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:39:13.088119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
게시번호수신구분수신지명
게시번호1.0000.4770.000
수신구분0.4771.0000.424
수신지명0.0000.4241.000
2023-12-12T13:39:13.206750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수신구분수신지명
수신구분1.0000.349
수신지명0.3491.000
2023-12-12T13:39:13.325115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
게시번호수신구분수신지명
게시번호1.0000.3650.000
수신구분0.3651.0000.349
수신지명0.0000.3491.000

Missing values

2023-12-12T13:39:12.077245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:39:12.155938image/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

작성연도게시번호수신구분수신지명
0201912본 부
1201912서 부
2201912도 봉
3201912강 남
4201912강 서
5201912부산북부
6201912인 천
7201912춘 천
8201912청 주
9201912대 전
작성연도게시번호수신구분수신지명
12442019842부산남부
12452019842포 항
12462019842충 주
12472019842예 산
12482019842울 산
12492019842원 주
12502019842태 백
12512019842광 양
12522019842광 주
12532019842천 안