Overview

Dataset statistics

Number of variables7
Number of observations241
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory14.0 KiB
Average record size in memory59.5 B

Variable types

Categorical4
Text1
Numeric2

Dataset

Description충청남도 부여군 주정차단속 현황에 대한 정보입니다.(단속년도, 단속구분, 단속지역, 단속위치정보, 문자발송건수, 단속건수 등)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=411&beforeMenuCd=DOM_000000201001001000&publicdatapk=15040579

Alerts

단속년도 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 1 (0.4%) duplicate rowsDuplicates
문자발송건수 is highly overall correlated with 단속건수High correlation
단속건수 is highly overall correlated with 문자발송건수High correlation
단속지역 is highly imbalanced (72.9%)Imbalance
문자발송건수 has 142 (58.9%) zerosZeros

Reproduction

Analysis started2024-01-09 21:38:44.850969
Analysis finished2024-01-09 21:38:45.695460
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단속년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2019
241 

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 241
100.0%

Length

2024-01-10T06:38:45.744530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:45.810706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 241
100.0%

단속구분
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
민원신고
142 
이동형CCTV단속
77 
고정형CCTV단속
22 

Length

Max length9
Median length4
Mean length6.0539419
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
민원신고 142
58.9%
이동형CCTV단속 77
32.0%
고정형CCTV단속 22
 
9.1%

Length

2024-01-10T06:38:45.885935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:45.981413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민원신고 142
58.9%
이동형cctv단속 77
32.0%
고정형cctv단속 22
 
9.1%

단속지역
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
충청남도 부여군 부여읍
218 
충청남도 부여군 규암면
 
18
충청남도 부여군 홍산면
 
4
충청남도 부여군 임천면
 
1

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row충청남도 부여군 부여읍
2nd row충청남도 부여군 부여읍
3rd row충청남도 부여군 부여읍
4th row충청남도 부여군 부여읍
5th row충청남도 부여군 부여읍

Common Values

ValueCountFrequency (%)
충청남도 부여군 부여읍 218
90.5%
충청남도 부여군 규암면 18
 
7.5%
충청남도 부여군 홍산면 4
 
1.7%
충청남도 부여군 임천면 1
 
0.4%

Length

2024-01-10T06:38:46.063631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:46.137533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 241
33.3%
부여군 241
33.3%
부여읍 218
30.2%
규암면 18
 
2.5%
홍산면 4
 
0.6%
임천면 1
 
0.1%

단속위치정보
Text

Distinct236
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-01-10T06:38:46.294447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length14.419087
Min length5

Characters and Unicode

Total characters3475
Distinct characters211
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique231 ?
Unique (%)95.9%

Sample

1st row관광주차장
2nd row관광주차장1
3rd row관광주차장2
4th row동산약국 앞
5th row동산약국 앞 1
ValueCountFrequency (%)
부여읍 118
19.2%
부근 73
 
11.9%
동남리 48
 
7.8%
쌍북리 27
 
4.4%
구아리 24
 
3.9%
규암면 18
 
2.9%
외리 7
 
1.1%
구교리 7
 
1.1%
모퉁이 6
 
1.0%
합정리 5
 
0.8%
Other values (246) 280
45.7%
2024-01-10T06:38:46.572312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
373
 
10.7%
부 207
 
6.0%
리 155
 
4.5%
) 143
 
4.1%
( 142
 
4.1%
여 127
 
3.7%
읍 119
 
3.4%
1 109
 
3.1%
- 106
 
3.1%
2 91
 
2.6%
Other values (201) 1903
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2146
61.8%
Decimal Number 549
 
15.8%
Space Separator 373
 
10.7%
Close Punctuation 143
 
4.1%
Open Punctuation 142
 
4.1%
Dash Punctuation 106
 
3.1%
Other Punctuation 14
 
0.4%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 207
 
9.6%
리 155
 
7.2%
여 127
 
5.9%
읍 119
 
5.5%
도 77
 
3.6%
근 75
 
3.5%
동 61
 
2.8%
보 60
 
2.8%
남 58
 
2.7%
구 54
 
2.5%
Other values (184) 1153
53.7%
Decimal Number
ValueCountFrequency (%)
1 109
19.9%
2 91
16.6%
3 69
12.6%
4 60
10.9%
7 59
10.7%
5 47
8.6%
6 40
 
7.3%
9 25
 
4.6%
8 25
 
4.6%
0 24
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
373
100.0%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Open Punctuation
ValueCountFrequency (%)
( 142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2146
61.8%
Common 1327
38.2%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 207
 
9.6%
리 155
 
7.2%
여 127
 
5.9%
읍 119
 
5.5%
도 77
 
3.6%
근 75
 
3.5%
동 61
 
2.8%
보 60
 
2.8%
남 58
 
2.7%
구 54
 
2.5%
Other values (184) 1153
53.7%
Common
ValueCountFrequency (%)
373
28.1%
) 143
 
10.8%
( 142
 
10.7%
1 109
 
8.2%
- 106
 
8.0%
2 91
 
6.9%
3 69
 
5.2%
4 60
 
4.5%
7 59
 
4.4%
5 47
 
3.5%
Other values (5) 128
 
9.6%
Latin
ValueCountFrequency (%)
S 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2146
61.8%
ASCII 1329
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
373
28.1%
) 143
 
10.8%
( 142
 
10.7%
1 109
 
8.2%
- 106
 
8.0%
2 91
 
6.8%
3 69
 
5.2%
4 60
 
4.5%
7 59
 
4.4%
5 47
 
3.5%
Other values (7) 130
 
9.8%
Hangul
ValueCountFrequency (%)
부 207
 
9.6%
리 155
 
7.2%
여 127
 
5.9%
읍 119
 
5.5%
도 77
 
3.6%
근 75
 
3.5%
동 61
 
2.8%
보 60
 
2.8%
남 58
 
2.7%
구 54
 
2.5%
Other values (184) 1153
53.7%

문자발송건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.107884
Minimum0
Maximum560
Zeros142
Zeros (%)58.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T06:38:46.675704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile107
Maximum560
Range560
Interquartile range (IQR)2

Descriptive statistics

Standard deviation70.8654
Coefficient of variation (CV)3.7086996
Kurtosis35.218268
Mean19.107884
Median Absolute Deviation (MAD)0
Skewness5.6558815
Sum4605
Variance5021.905
MonotonicityNot monotonic
2024-01-10T06:38:46.768986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 142
58.9%
1 33
 
13.7%
2 14
 
5.8%
7 3
 
1.2%
6 3
 
1.2%
3 3
 
1.2%
110 3
 
1.2%
4 3
 
1.2%
31 2
 
0.8%
8 2
 
0.8%
Other values (31) 33
 
13.7%
ValueCountFrequency (%)
0 142
58.9%
1 33
 
13.7%
2 14
 
5.8%
3 3
 
1.2%
4 3
 
1.2%
6 3
 
1.2%
7 3
 
1.2%
8 2
 
0.8%
12 2
 
0.8%
14 1
 
0.4%
ValueCountFrequency (%)
560 1
 
0.4%
528 1
 
0.4%
485 1
 
0.4%
362 1
 
0.4%
334 1
 
0.4%
194 1
 
0.4%
174 1
 
0.4%
162 1
 
0.4%
111 1
 
0.4%
110 3
1.2%

단속건수
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.589212
Minimum1
Maximum560
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T06:38:46.862388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile107
Maximum560
Range559
Interquartile range (IQR)3

Descriptive statistics

Standard deviation70.654451
Coefficient of variation (CV)3.4316249
Kurtosis35.192687
Mean20.589212
Median Absolute Deviation (MAD)0
Skewness5.6470278
Sum4962
Variance4992.0514
MonotonicityNot monotonic
2024-01-10T06:38:46.957852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 137
56.8%
2 35
 
14.5%
3 7
 
2.9%
4 6
 
2.5%
6 4
 
1.7%
5 4
 
1.7%
16 3
 
1.2%
7 3
 
1.2%
31 3
 
1.2%
110 3
 
1.2%
Other values (34) 36
 
14.9%
ValueCountFrequency (%)
1 137
56.8%
2 35
 
14.5%
3 7
 
2.9%
4 6
 
2.5%
5 4
 
1.7%
6 4
 
1.7%
7 3
 
1.2%
8 2
 
0.8%
12 2
 
0.8%
14 1
 
0.4%
ValueCountFrequency (%)
560 1
 
0.4%
528 1
 
0.4%
485 1
 
0.4%
362 1
 
0.4%
334 1
 
0.4%
194 1
 
0.4%
174 1
 
0.4%
162 1
 
0.4%
111 1
 
0.4%
110 3
1.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2021-09-24
241 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-24
2nd row2021-09-24
3rd row2021-09-24
4th row2021-09-24
5th row2021-09-24

Common Values

ValueCountFrequency (%)
2021-09-24 241
100.0%

Length

2024-01-10T06:38:47.055687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:47.129442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-24 241
100.0%

Interactions

2024-01-10T06:38:45.403244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:45.279181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:45.467233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:45.340650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:38:47.171263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속구분단속지역문자발송건수단속건수
단속구분1.0000.1660.5290.519
단속지역0.1661.0000.0000.000
문자발송건수0.5290.0001.0001.000
단속건수0.5190.0001.0001.000
2024-01-10T06:38:47.252219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속지역단속구분
단속지역1.0000.156
단속구분0.1561.000
2024-01-10T06:38:47.336730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문자발송건수단속건수단속구분단속지역
문자발송건수1.0000.6410.3900.000
단속건수0.6411.0000.3810.000
단속구분0.3900.3811.0000.156
단속지역0.0000.0000.1561.000

Missing values

2024-01-10T06:38:45.563748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:38:45.657380image/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

단속년도단속구분단속지역단속위치정보문자발송건수단속건수데이터기준일자
02019고정형CCTV단속충청남도 부여군 부여읍관광주차장91912021-09-24
12019고정형CCTV단속충청남도 부여군 부여읍관광주차장1882021-09-24
22019고정형CCTV단속충청남도 부여군 부여읍관광주차장2662021-09-24
32019고정형CCTV단속충청남도 부여군 부여읍동산약국 앞3623622021-09-24
42019고정형CCTV단속충청남도 부여군 부여읍동산약국 앞 11101102021-09-24
52019고정형CCTV단속충청남도 부여군 부여읍동산약국 앞 253532021-09-24
62019고정형CCTV단속충청남도 부여군 부여읍뚜레쥬르부여점5285282021-09-24
72019고정형CCTV단속충청남도 부여군 부여읍미성삼거리1101102021-09-24
82019고정형CCTV단속충청남도 부여군 부여읍미성삼거리 1662021-09-24
92019고정형CCTV단속충청남도 부여군 부여읍미성삼거리 21101102021-09-24
단속년도단속구분단속지역단속위치정보문자발송건수단속건수데이터기준일자
2312019이동형CCTV단속충청남도 부여군 부여읍충무체육사 부근32322021-09-24
2322019이동형CCTV단속충청남도 부여군 부여읍퓨리나사료112021-09-24
2332019이동형CCTV단속충청남도 부여군 부여읍피자마루 부근112021-09-24
2342019이동형CCTV단속충청남도 부여군 부여읍하겐커피 부근12122021-09-24
2352019이동형CCTV단속충청남도 부여군 부여읍하나로마트 부근14142021-09-24
2362019이동형CCTV단속충청남도 부여군 부여읍하나은행 부근1111112021-09-24
2372019이동형CCTV단속충청남도 부여군 부여읍하나의원 부근112021-09-24
2382019이동형CCTV단속충청남도 부여군 부여읍합동타이루 부근442021-09-24
2392019이동형CCTV단속충청남도 부여군 부여읍향우정 부근112021-09-24
2402019이동형CCTV단속충청남도 부여군 부여읍현대내과 부근112021-09-24

Duplicate rows

Most frequently occurring

단속년도단속구분단속지역단속위치정보문자발송건수단속건수데이터기준일자# duplicates
02019민원신고충청남도 부여군 부여읍부여읍 구아리 324-1(횡단보도)012021-09-242