Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory108.0 B

Variable types

Numeric4
Categorical5
DateTime2
Text1

Dataset

Description광주광역시 광산구 불법주정차 단속자료(차종, 단속일시, 단속장소, 단속구분, 단속원금, 위반법규, 단속특별지역 등)를 제공합니다.
URLhttps://www.data.go.kr/data/15039753/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위반법규 is highly overall correlated with 단속특별지역High correlation
단속특별지역 is highly overall correlated with 단속원금 and 4 other fieldsHigh correlation
단속원금 is highly overall correlated with 단속특별지역High correlation
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
단속동 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
단속구분 is highly overall correlated with 단속특별지역High correlation
차종 is highly imbalanced (68.8%)Imbalance
위반법규 is highly imbalanced (68.4%)Imbalance
단속특별지역 is highly imbalanced (52.3%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:07:33.524511
Analysis finished2023-12-12 12:07:37.421854
Duration3.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44750.436
Minimum10
Maximum89465
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:07:37.516087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile4773.4
Q122542
median44565.5
Q367126
95-th percentile85453.9
Maximum89465
Range89455
Interquartile range (IQR)44584

Descriptive statistics

Standard deviation25818.655
Coefficient of variation (CV)0.57694756
Kurtosis-1.1948176
Mean44750.436
Median Absolute Deviation (MAD)22268.5
Skewness0.01786782
Sum4.4750436 × 108
Variance6.6660294 × 108
MonotonicityNot monotonic
2023-12-12T21:07:37.709760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54798 1
 
< 0.1%
44854 1
 
< 0.1%
15015 1
 
< 0.1%
8904 1
 
< 0.1%
5444 1
 
< 0.1%
23472 1
 
< 0.1%
8727 1
 
< 0.1%
55783 1
 
< 0.1%
4137 1
 
< 0.1%
81686 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
10 1
< 0.1%
18 1
< 0.1%
21 1
< 0.1%
37 1
< 0.1%
39 1
< 0.1%
52 1
< 0.1%
57 1
< 0.1%
59 1
< 0.1%
65 1
< 0.1%
74 1
< 0.1%
ValueCountFrequency (%)
89465 1
< 0.1%
89461 1
< 0.1%
89458 1
< 0.1%
89457 1
< 0.1%
89449 1
< 0.1%
89445 1
< 0.1%
89442 1
< 0.1%
89419 1
< 0.1%
89407 1
< 0.1%
89405 1
< 0.1%

차종
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
승용
8718 
화물4톤이하
 
847
승합
 
245
화물4톤초과
 
164
건설,중기,특수
 
26

Length

Max length8
Median length2
Mean length2.42
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
승용 8718
87.2%
화물4톤이하 847
 
8.5%
승합 245
 
2.5%
화물4톤초과 164
 
1.6%
건설,중기,특수 26
 
0.3%

Length

2023-12-12T21:07:37.847293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:07:37.968960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
승용 8718
87.2%
화물4톤이하 847
 
8.5%
승합 245
 
2.5%
화물4톤초과 164
 
1.6%
건설,중기,특수 26
 
0.3%

단속일시
Date

Distinct171
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-01-01 00:00:00
Maximum2022-06-20 00:00:00
2023-12-12T21:07:38.143047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:38.305568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

단속동
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
송정동
1241 
우산동
1148 
수완동
1103 
쌍암동
983 
월계동
924 
Other values (29)
4601 

Length

Max length3
Median length3
Mean length2.9986
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row쌍암동
2nd row운남동
3rd row송정동
4th row쌍암동
5th row월계동

Common Values

ValueCountFrequency (%)
송정동 1241
12.4%
우산동 1148
11.5%
수완동 1103
11.0%
쌍암동 983
9.8%
월계동 924
9.2%
장덕동 848
8.5%
운남동 649
6.5%
신창동 587
 
5.9%
신가동 550
 
5.5%
하남동 471
 
4.7%
Other values (24) 1496
15.0%

Length

2023-12-12T21:07:38.452579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송정동 1241
12.4%
우산동 1148
11.5%
수완동 1103
11.0%
쌍암동 983
9.8%
월계동 924
9.2%
장덕동 848
8.5%
운남동 649
6.5%
신창동 587
 
5.9%
신가동 550
 
5.5%
하남동 471
 
4.7%
Other values (24) 1496
15.0%

단속장소
Text

Distinct1146
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T21:07:38.684768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length8.5137
Min length3

Characters and Unicode

Total characters85137
Distinct characters212
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique564 ?
Unique (%)5.6%

Sample

1st row694-74 부근
2nd row금구초교
3rd row송정역앞삼거리
4th row쌍암동 첨단강변로99번길
5th row첨단내촌로부근
ValueCountFrequency (%)
부근 3064
 
17.7%
주변 533
 
3.1%
우산동 410
 
2.4%
사거리 385
 
2.2%
송정역 338
 
2.0%
쌍암동 278
 
1.6%
수완1호점주변 231
 
1.3%
김밥천국 231
 
1.3%
새빛콜 200
 
1.2%
승차장 200
 
1.2%
Other values (1066) 11448
66.1%
2023-12-12T21:07:39.101230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7318
 
8.6%
부 3834
 
4.5%
근 3725
 
4.4%
1 3210
 
3.8%
로 3182
 
3.7%
동 2096
 
2.5%
길 1906
 
2.2%
번 1901
 
2.2%
2 1594
 
1.9%
0 1574
 
1.8%
Other values (202) 54797
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62461
73.4%
Decimal Number 14063
 
16.5%
Space Separator 7318
 
8.6%
Dash Punctuation 729
 
0.9%
Uppercase Letter 366
 
0.4%
Open Punctuation 100
 
0.1%
Close Punctuation 100
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 3834
 
6.1%
근 3725
 
6.0%
로 3182
 
5.1%
동 2096
 
3.4%
길 1906
 
3.1%
번 1901
 
3.0%
신 1300
 
2.1%
주 1170
 
1.9%
변 1130
 
1.8%
수 1085
 
1.7%
Other values (182) 41132
65.9%
Decimal Number
ValueCountFrequency (%)
1 3210
22.8%
2 1594
11.3%
0 1574
11.2%
7 1275
 
9.1%
9 1251
 
8.9%
6 1168
 
8.3%
5 1111
 
7.9%
8 1083
 
7.7%
3 1055
 
7.5%
4 742
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
W 148
40.4%
T 50
 
13.7%
K 50
 
13.7%
L 43
 
11.7%
C 43
 
11.7%
S 32
 
8.7%
Space Separator
ValueCountFrequency (%)
7318
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 729
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62461
73.4%
Common 22310
 
26.2%
Latin 366
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 3834
 
6.1%
근 3725
 
6.0%
로 3182
 
5.1%
동 2096
 
3.4%
길 1906
 
3.1%
번 1901
 
3.0%
신 1300
 
2.1%
주 1170
 
1.9%
변 1130
 
1.8%
수 1085
 
1.7%
Other values (182) 41132
65.9%
Common
ValueCountFrequency (%)
7318
32.8%
1 3210
14.4%
2 1594
 
7.1%
0 1574
 
7.1%
7 1275
 
5.7%
9 1251
 
5.6%
6 1168
 
5.2%
5 1111
 
5.0%
8 1083
 
4.9%
3 1055
 
4.7%
Other values (4) 1671
 
7.5%
Latin
ValueCountFrequency (%)
W 148
40.4%
T 50
 
13.7%
K 50
 
13.7%
L 43
 
11.7%
C 43
 
11.7%
S 32
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62461
73.4%
ASCII 22676
 
26.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7318
32.3%
1 3210
14.2%
2 1594
 
7.0%
0 1574
 
6.9%
7 1275
 
5.6%
9 1251
 
5.5%
6 1168
 
5.2%
5 1111
 
4.9%
8 1083
 
4.8%
3 1055
 
4.7%
Other values (10) 2037
 
9.0%
Hangul
ValueCountFrequency (%)
부 3834
 
6.1%
근 3725
 
6.0%
로 3182
 
5.1%
동 2096
 
3.4%
길 1906
 
3.1%
번 1901
 
3.0%
신 1300
 
2.1%
주 1170
 
1.9%
변 1130
 
1.8%
수 1085
 
1.7%
Other values (182) 41132
65.9%

단속구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
고정형CCTV
4923 
주행형CCTV
2799 
시민신고웹
1920 
버스장착형CCTV
 
351
PDA
 
7

Length

Max length9
Median length7
Mean length6.6834
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시민신고웹
2nd row고정형CCTV
3rd row고정형CCTV
4th row주행형CCTV
5th row버스장착형CCTV

Common Values

ValueCountFrequency (%)
고정형CCTV 4923
49.2%
주행형CCTV 2799
28.0%
시민신고웹 1920
 
19.2%
버스장착형CCTV 351
 
3.5%
PDA 7
 
0.1%

Length

2023-12-12T21:07:39.233786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:07:39.344871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정형cctv 4923
49.2%
주행형cctv 2799
28.0%
시민신고웹 1920
 
19.2%
버스장착형cctv 351
 
3.5%
pda 7
 
0.1%

단속원금
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52893.5
Minimum10000
Maximum130000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:07:39.478578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile40000
Q140000
median40000
Q340000
95-th percentile120000
Maximum130000
Range120000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation28318.022
Coefficient of variation (CV)0.5353781
Kurtosis1.685091
Mean52893.5
Median Absolute Deviation (MAD)0
Skewness1.8785651
Sum5.28935 × 108
Variance8.0191035 × 108
MonotonicityNot monotonic
2023-12-12T21:07:39.611069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
40000 7831
78.3%
120000 1371
 
13.7%
50000 457
 
4.6%
80000 239
 
2.4%
130000 54
 
0.5%
20000 18
 
0.2%
60000 15
 
0.1%
90000 9
 
0.1%
10000 5
 
0.1%
65000 1
 
< 0.1%
ValueCountFrequency (%)
10000 5
 
0.1%
20000 18
 
0.2%
40000 7831
78.3%
50000 457
 
4.6%
60000 15
 
0.1%
65000 1
 
< 0.1%
80000 239
 
2.4%
90000 9
 
0.1%
120000 1371
 
13.7%
130000 54
 
0.5%
ValueCountFrequency (%)
130000 54
 
0.5%
120000 1371
 
13.7%
90000 9
 
0.1%
80000 239
 
2.4%
65000 1
 
< 0.1%
60000 15
 
0.1%
50000 457
 
4.6%
40000 7831
78.3%
20000 18
 
0.2%
10000 5
 
0.1%

위반법규
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
32조위반
8382 
보도,횡단보도
1046 
소방시설주변 절대금지
 
249
교차로 모퉁이
 
227
버스승강장
 
61
Other values (2)
 
35

Length

Max length11
Median length5
Mean length5.4058
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보도,횡단보도
2nd row32조위반
3rd row32조위반
4th row32조위반
5th row32조위반

Common Values

ValueCountFrequency (%)
32조위반 8382
83.8%
보도,횡단보도 1046
 
10.5%
소방시설주변 절대금지 249
 
2.5%
교차로 모퉁이 227
 
2.3%
버스승강장 61
 
0.6%
34조위반 26
 
0.3%
어린이보호구역 9
 
0.1%

Length

2023-12-12T21:07:39.773819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:07:39.883289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
32조위반 8382
80.0%
보도,횡단보도 1046
 
10.0%
소방시설주변 249
 
2.4%
절대금지 249
 
2.4%
교차로 227
 
2.2%
모퉁이 227
 
2.2%
버스승강장 61
 
0.6%
34조위반 26
 
0.2%
어린이보호구역 9
 
0.1%

단속특별지역
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8318 
어린이보호구역
1433 
소방시설주변 절대금지
 
249

Length

Max length11
Median length4
Mean length4.6042
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row어린이보호구역
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 8318
83.2%
어린이보호구역 1433
 
14.3%
소방시설주변 절대금지 249
 
2.5%

Length

2023-12-12T21:07:40.032485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:07:40.167222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8318
81.2%
어린이보호구역 1433
 
14.0%
소방시설주변 249
 
2.4%
절대금지 249
 
2.4%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct3689
Distinct (%)36.9%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean35.180706
Minimum35.098571
Maximum35.22473
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:07:40.331089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.098571
5-th percentile35.136343
Q135.162794
median35.183622
Q335.19773
95-th percentile35.220509
Maximum35.22473
Range0.1261588
Interquartile range (IQR)0.03493563

Descriptive statistics

Standard deviation0.026232118
Coefficient of variation (CV)0.00074563931
Kurtosis-0.77356249
Mean35.180706
Median Absolute Deviation (MAD)0.01982921
Skewness-0.24514646
Sum351771.88
Variance0.000688124
MonotonicityNot monotonic
2023-12-12T21:07:40.526029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.19125687 231
 
2.3%
35.13614548 200
 
2.0%
35.18980121 175
 
1.8%
35.17925973 168
 
1.7%
35.13761811 167
 
1.7%
35.19772961 158
 
1.6%
35.16379296 153
 
1.5%
35.18976043 148
 
1.5%
35.13827859 138
 
1.4%
35.16400196 136
 
1.4%
Other values (3679) 8325
83.2%
ValueCountFrequency (%)
35.09857137 18
0.2%
35.1105963 1
 
< 0.1%
35.1109799 1
 
< 0.1%
35.1110363 1
 
< 0.1%
35.1110754 1
 
< 0.1%
35.1144035 1
 
< 0.1%
35.1146641 2
 
< 0.1%
35.116824 2
 
< 0.1%
35.1201577 1
 
< 0.1%
35.1212022 3
 
< 0.1%
ValueCountFrequency (%)
35.22473017 1
 
< 0.1%
35.2245329 1
 
< 0.1%
35.22448083 1
 
< 0.1%
35.2240808 1
 
< 0.1%
35.2234771 5
0.1%
35.2234458 3
< 0.1%
35.2233847 1
 
< 0.1%
35.2233702 1
 
< 0.1%
35.2233479 1
 
< 0.1%
35.2233366 1
 
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct3798
Distinct (%)38.0%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean126.81787
Minimum126.75083
Maximum126.85607
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:07:40.716755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.75083
5-th percentile126.78964
Q1126.80395
median126.81704
Q3126.83686
95-th percentile126.84907
Maximum126.85607
Range0.1052366
Interquartile range (IQR)0.0329084

Descriptive statistics

Standard deviation0.019754772
Coefficient of variation (CV)0.00015577278
Kurtosis-0.65633425
Mean126.81787
Median Absolute Deviation (MAD)0.014982
Skewness-0.15617139
Sum1268051.9
Variance0.00039025101
MonotonicityNot monotonic
2023-12-12T21:07:40.929264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8262053 231
 
2.3%
126.7904995 200
 
2.0%
126.8170426 175
 
1.8%
126.824874 168
 
1.7%
126.7914306 167
 
1.7%
126.8373217 159
 
1.6%
126.8062607 153
 
1.5%
126.8235734 148
 
1.5%
126.7918283 138
 
1.4%
126.8039508 136
 
1.4%
Other values (3788) 8324
83.2%
ValueCountFrequency (%)
126.7508336 1
 
< 0.1%
126.7509365 1
 
< 0.1%
126.7512234 1
 
< 0.1%
126.7513621 1
 
< 0.1%
126.7519297 1
 
< 0.1%
126.7557354 1
 
< 0.1%
126.7567256 7
0.1%
126.7568787 1
 
< 0.1%
126.7608161 2
 
< 0.1%
126.7622326 1
 
< 0.1%
ValueCountFrequency (%)
126.8560702 1
 
< 0.1%
126.8528788 1
 
< 0.1%
126.8528197 1
 
< 0.1%
126.8528078 1
 
< 0.1%
126.8528017 1
 
< 0.1%
126.8527923 1
 
< 0.1%
126.8527643 1
 
< 0.1%
126.8527617 1
 
< 0.1%
126.8527567 1
 
< 0.1%
126.8526844 21
0.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-12T21:07:41.059967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:41.158047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T21:07:36.058590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:34.868743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:35.260105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:35.672689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:36.171373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:34.978166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:35.354818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:35.757265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:36.335036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:35.069010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:35.446879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:35.853224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:36.456990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:35.166777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:35.564458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:07:35.952100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:07:41.257012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번차종단속동단속구분단속원금위반법규단속특별지역위도경도
연번1.0000.0000.2120.2340.1470.0550.2340.1690.178
차종0.0001.0000.2610.2020.5900.0560.0000.2000.168
단속동0.2120.2611.0000.5270.5170.3920.7280.9710.957
단속구분0.2340.2020.5271.0000.3450.6020.6220.4560.419
단속원금0.1470.5900.5170.3451.0000.7900.9370.2430.252
위반법규0.0550.0560.3920.6020.7901.0000.7200.2020.157
단속특별지역0.2340.0000.7280.6220.9370.7201.0000.4330.541
위도0.1690.2000.9710.4560.2430.2020.4331.0000.887
경도0.1780.1680.9570.4190.2520.1570.5410.8871.000
2023-12-12T21:07:41.412287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속동위반법규차종단속특별지역단속구분
단속동1.0000.1710.1250.6510.278
위반법규0.1711.0000.0360.9590.443
차종0.1250.0361.0000.0000.076
단속특별지역0.6510.9590.0001.0000.889
단속구분0.2780.4430.0760.8891.000
2023-12-12T21:07:41.530528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단속원금위도경도차종단속동단속구분위반법규단속특별지역
연번1.0000.106-0.050-0.0540.0000.0760.0990.0280.179
단속원금0.1061.0000.0760.0620.4310.2390.2290.3870.998
위도-0.0500.0761.0000.8850.0840.8190.2060.1030.332
경도-0.0540.0620.8851.0000.0710.7590.1860.0800.542
차종0.0000.4310.0840.0711.0000.1250.0760.0360.000
단속동0.0760.2390.8190.7590.1251.0000.2780.1710.651
단속구분0.0990.2290.2060.1860.0760.2781.0000.4430.889
위반법규0.0280.3870.1030.0800.0360.1710.4431.0000.959
단속특별지역0.1790.9980.3320.5420.0000.6510.8890.9591.000

Missing values

2023-12-12T21:07:36.985459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:07:37.192397image/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.
2023-12-12T21:07:37.354709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번차종단속일시단속동단속장소단속구분단속원금위반법규단속특별지역위도경도데이터기준일자
5479754798승용2022-05-02쌍암동694-74 부근시민신고웹40000보도,횡단보도<NA>35.215178126.8509452022-12-31
7592875929승용2022-05-31운남동금구초교고정형CCTV12000032조위반어린이보호구역35.176011126.8147992022-12-31
6402264023승용2022-05-14송정동송정역앞삼거리고정형CCTV4000032조위반<NA>35.137618126.7914312022-12-31
1512815129승용2022-02-08쌍암동쌍암동 첨단강변로99번길주행형CCTV4000032조위반<NA>35.215707126.8505672022-12-31
6183861839승용2022-05-11월계동첨단내촌로부근버스장착형CCTV4000032조위반<NA>35.211021126.8372262022-12-31
3458034581승용2022-03-23신촌동신촌동 광산로주행형CCTV4000032조위반<NA>35.143562126.803382022-12-31
6629066291승용2022-05-17장덕동1092 부근시민신고웹40000보도,횡단보도<NA>35.195279126.8138912022-12-31
3338933390승용2022-03-21쌍암동첨단중앙로 부근주행형CCTV4000032조위반<NA>35.220113126.841862022-12-31
6761467615승용2022-05-19우산동우산동 어등마을고정형CCTV4000032조위반<NA>35.163793126.8062612022-12-31
59835984승용2022-01-13월계동첨단LC타워고정형CCTV4000032조위반<NA>35.214423126.8430352022-12-31
연번차종단속일시단속동단속장소단속구분단속원금위반법규단속특별지역위도경도데이터기준일자
6371463715승용2022-05-14우산동어등초교 주변고정형CCTV12000032조위반어린이보호구역35.1662126.8073792022-12-31
8651086511승용2022-06-16우산동송우초교 주변고정형CCTV12000032조위반어린이보호구역35.158242126.8095892022-12-31
2416324164승용2022-02-28송정동송정1동 행정복지센터고정형CCTV4000032조위반<NA>35.140752126.7985292022-12-31
7093570936승용2022-05-23월계동901 부근시민신고웹40000보도,횡단보도<NA>35.214646126.8452522022-12-31
8839188392승용2022-06-18송정동송정역 승강장고정형CCTV4000032조위반<NA>35.138279126.7918282022-12-31
4721247213승용2022-04-20우산동우산동 무진대로주행형CCTV4000032조위반<NA>35.159998126.8101172022-12-31
2481924820승용2022-02-28운남동운남우체국고정형CCTV4000032조위반<NA>35.178307126.8245552022-12-31
4335543356승용2022-04-13월계동산월초교고정형CCTV12000032조위반어린이보호구역35.211379126.8396492022-12-31
7425274253승용2022-05-29산정동산정초교 주변고정형CCTV12000032조위반어린이보호구역35.172768126.8001492022-12-31
33603361승용2022-01-07수완동김밥천국 수완1호점주변고정형CCTV4000032조위반<NA>35.191257126.8262052022-12-31