Overview

Dataset statistics

Number of variables4
Number of observations3445
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory117.9 KiB
Average record size in memory35.0 B

Variable types

Numeric2
Categorical1
Text1

Dataset

Description서울특별시 강북구 장애인전용주차구역 불법주차 적발건수 및 과태료 부과액 이력입니다. 연도별 위반장소별 벌금 부과금액 자료입니다.
Author서울특별시 강북구
URLhttps://www.data.go.kr/data/15106902/fileData.do

Alerts

연번 is highly overall correlated with 연도High correlation
연도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:34:58.305321
Analysis finished2023-12-12 13:34:59.235079
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3445
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1723
Minimum1
Maximum3445
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T22:34:59.314689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile173.2
Q1862
median1723
Q32584
95-th percentile3272.8
Maximum3445
Range3444
Interquartile range (IQR)1722

Descriptive statistics

Standard deviation994.63017
Coefficient of variation (CV)0.57726649
Kurtosis-1.2
Mean1723
Median Absolute Deviation (MAD)861
Skewness0
Sum5935735
Variance989289.17
MonotonicityStrictly increasing
2023-12-12T22:34:59.456179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2290 1
 
< 0.1%
2292 1
 
< 0.1%
2293 1
 
< 0.1%
2294 1
 
< 0.1%
2295 1
 
< 0.1%
2296 1
 
< 0.1%
2297 1
 
< 0.1%
2298 1
 
< 0.1%
2299 1
 
< 0.1%
Other values (3435) 3435
99.7%
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 (%)
3445 1
< 0.1%
3444 1
< 0.1%
3443 1
< 0.1%
3442 1
< 0.1%
3441 1
< 0.1%
3440 1
< 0.1%
3439 1
< 0.1%
3438 1
< 0.1%
3437 1
< 0.1%
3436 1
< 0.1%

연도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
2021
937 
2018
873 
2019
683 
2022
556 
2020
396 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2021 937
27.2%
2018 873
25.3%
2019 683
19.8%
2022 556
16.1%
2020 396
11.5%

Length

2023-12-12T22:34:59.595606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:34:59.720245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 937
27.2%
2018 873
25.3%
2019 683
19.8%
2022 556
16.1%
2020 396
11.5%

부과금액
Real number (ℝ)

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114978.23
Minimum10000
Maximum2000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T22:34:59.842788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile100000
Q1100000
median100000
Q3100000
95-th percentile100000
Maximum2000000
Range1990000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation168446.93
Coefficient of variation (CV)1.4650333
Kurtosis120.38738
Mean114978.23
Median Absolute Deviation (MAD)0
Skewness11.037442
Sum3.961 × 108
Variance2.8374368 × 1010
MonotonicityNot monotonic
2023-12-12T22:34:59.963188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
100000 3397
98.6%
2000000 27
 
0.8%
50000 17
 
0.5%
40000 1
 
< 0.1%
10000 1
 
< 0.1%
500000 1
 
< 0.1%
1000000 1
 
< 0.1%
ValueCountFrequency (%)
10000 1
 
< 0.1%
40000 1
 
< 0.1%
50000 17
 
0.5%
100000 3397
98.6%
500000 1
 
< 0.1%
1000000 1
 
< 0.1%
2000000 27
 
0.8%
ValueCountFrequency (%)
2000000 27
 
0.8%
1000000 1
 
< 0.1%
500000 1
 
< 0.1%
100000 3397
98.6%
50000 17
 
0.5%
40000 1
 
< 0.1%
10000 1
 
< 0.1%

위반장소
Text

Distinct1380
Distinct (%)40.1%
Missing2
Missing (%)0.1%
Memory size27.0 KiB
2023-12-12T22:35:00.297857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length35
Mean length12.41185
Min length4

Characters and Unicode

Total characters42734
Distinct characters298
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique908 ?
Unique (%)26.4%

Sample

1st row서울 강북구 솔샘로 174 SK 아파트
2nd row서울 강북구 삼각산로 58 국립재활원
3rd row삼양로77길 27
4th row강북구 수유동 289-13 부근
5th row강북구 솔매로7다길 23
ValueCountFrequency (%)
미아동 671
 
8.3%
강북구 428
 
5.3%
서울특별시 384
 
4.7%
번동 340
 
4.2%
수유동 320
 
3.9%
도봉로 189
 
2.3%
1353 118
 
1.5%
앞 109
 
1.3%
1354 100
 
1.2%
278 76
 
0.9%
Other values (1400) 5385
66.3%
2023-12-12T22:35:00.787603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4677
 
10.9%
1 2824
 
6.6%
동 2677
 
6.3%
3 2011
 
4.7%
2 1681
 
3.9%
- 1439
 
3.4%
아 1293
 
3.0%
4 1291
 
3.0%
5 1290
 
3.0%
로 1192
 
2.8%
Other values (288) 22359
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22647
53.0%
Decimal Number 13705
32.1%
Space Separator 4677
 
10.9%
Dash Punctuation 1439
 
3.4%
Uppercase Letter 116
 
0.3%
Lowercase Letter 66
 
0.2%
Other Punctuation 26
 
0.1%
Close Punctuation 21
 
< 0.1%
Open Punctuation 21
 
< 0.1%
Other Symbol 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2677
 
11.8%
아 1293
 
5.7%
로 1192
 
5.3%
미 1064
 
4.7%
수 790
 
3.5%
유 766
 
3.4%
번 708
 
3.1%
북 604
 
2.7%
구 512
 
2.3%
강 511
 
2.3%
Other values (253) 12530
55.3%
Decimal Number
ValueCountFrequency (%)
1 2824
20.6%
3 2011
14.7%
2 1681
12.3%
4 1291
9.4%
5 1290
9.4%
7 1101
 
8.0%
0 1033
 
7.5%
9 838
 
6.1%
8 818
 
6.0%
6 818
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
s 27
40.9%
k 26
39.4%
b 2
 
3.0%
t 2
 
3.0%
h 2
 
3.0%
v 2
 
3.0%
g 2
 
3.0%
c 2
 
3.0%
d 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
S 46
39.7%
K 45
38.8%
B 13
 
11.2%
T 6
 
5.2%
A 4
 
3.4%
D 2
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 13
50.0%
@ 6
23.1%
. 5
 
19.2%
？ 2
 
7.7%
Space Separator
ValueCountFrequency (%)
4677
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1439
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22662
53.0%
Common 19890
46.5%
Latin 182
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2677
 
11.8%
아 1293
 
5.7%
로 1192
 
5.3%
미 1064
 
4.7%
수 790
 
3.5%
유 766
 
3.4%
번 708
 
3.1%
북 604
 
2.7%
구 512
 
2.3%
강 511
 
2.3%
Other values (254) 12545
55.4%
Common
ValueCountFrequency (%)
4677
23.5%
1 2824
14.2%
3 2011
10.1%
2 1681
 
8.5%
- 1439
 
7.2%
4 1291
 
6.5%
5 1290
 
6.5%
7 1101
 
5.5%
0 1033
 
5.2%
9 838
 
4.2%
Other values (9) 1705
 
8.6%
Latin
ValueCountFrequency (%)
S 46
25.3%
K 45
24.7%
s 27
14.8%
k 26
14.3%
B 13
 
7.1%
T 6
 
3.3%
A 4
 
2.2%
b 2
 
1.1%
t 2
 
1.1%
h 2
 
1.1%
Other values (5) 9
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22647
53.0%
ASCII 20070
47.0%
None 17
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4677
23.3%
1 2824
14.1%
3 2011
10.0%
2 1681
 
8.4%
- 1439
 
7.2%
4 1291
 
6.4%
5 1290
 
6.4%
7 1101
 
5.5%
0 1033
 
5.1%
9 838
 
4.2%
Other values (23) 1885
9.4%
Hangul
ValueCountFrequency (%)
동 2677
 
11.8%
아 1293
 
5.7%
로 1192
 
5.3%
미 1064
 
4.7%
수 790
 
3.5%
유 766
 
3.4%
번 708
 
3.1%
북 604
 
2.7%
구 512
 
2.3%
강 511
 
2.3%
Other values (253) 12530
55.3%
None
ValueCountFrequency (%)
㈜ 15
88.2%
？ 2
 
11.8%

Interactions

2023-12-12T22:34:58.817510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:58.601045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:58.925143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:58.707748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:35:00.899765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연도부과금액
연번1.0000.9900.116
연도0.9901.0000.037
부과금액0.1160.0371.000
2023-12-12T22:35:00.994668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번부과금액연도
연번1.0000.0050.854
부과금액0.0051.0000.030
연도0.8540.0301.000

Missing values

2023-12-12T22:34:59.103353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:34:59.199631image/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

연번연도부과금액위반장소
012018100000서울 강북구 솔샘로 174 SK 아파트
122018100000서울 강북구 삼각산로 58 국립재활원
232018100000삼양로77길 27
342018100000강북구 수유동 289-13 부근
452018100000강북구 솔매로7다길 23
562018100000도봉로399 수유메가박스 지하1층
672018100000미아동 1389-0
782018100000삼양로299 수유1동주민센터.수유문화정보도서관
892018100000미아동 87-54
9102018100000미아동 127-9
연번연도부과금액위반장소
343534362022100000서울특별시 강북구 삼양로19길 25
343634372022100000서울특별시 강북구 번동 411-61
343734382022100000서울특별시 강북구 미아동 195-1
343834392022100000서울특별시 강북구 삼양로689
343934402022100000서울특별시 강북구 오현로 117
344034412022100000서울특별시 강북구 미아동 1357
344134422022100000서울특별시 강북구 번동 242
344234432022100000서울특별시 강북구 미아동 1354
344334442022100000서울특별시 강북구 미아동 670-29
344434452022100000서울특별시 강북구 미아동 160-26