Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells20000
Missing cells (%)18.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory105.0 B

Variable types

DateTime1
Categorical4
Text1
Numeric3
Unsupported2

Dataset

Description서울특별시 강서구의 관심차량 일별통계정보를 제공합니다. 통계일, 관심차량구분명, 촉탁구분명, 시설물분류명, 발생건수, 취소건수, 승인건수 등의 항목을 포함하고 있습니다.
Author서울특별시 강서구
URLhttps://www.data.go.kr/data/15072602/fileData.do

Alerts

승인건수 has constant value ""Constant
완료건수 has constant value ""Constant
발생건수 is highly overall correlated with 취소건수 and 1 other fieldsHigh correlation
취소건수 is highly overall correlated with 발생건수 and 1 other fieldsHigh correlation
푸시건수 is highly overall correlated with 발생건수 and 1 other fieldsHigh correlation
영치건수 has 10000 (100.0%) missing valuesMissing
영치금액 has 10000 (100.0%) missing valuesMissing
영치건수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영치금액 is an unsupported type, check if it needs cleaning or further analysisUnsupported
발생건수 has 8505 (85.0%) zerosZeros
취소건수 has 8697 (87.0%) zerosZeros
푸시건수 has 8697 (87.0%) zerosZeros

Reproduction

Analysis started2023-12-12 15:17:36.477405
Analysis finished2023-12-12 15:17:38.743516
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계일
Date

Distinct204
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-01-01 00:00:00
Maximum2020-07-22 00:00:00
2023-12-13T00:17:38.833644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:39.015806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관심차량구분명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
3361 
5
3059 
30
2982 
20
598 

Length

Max length2
Median length1
Mean length1.358
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row3
3rd row30
4th row30
5th row3

Common Values

ValueCountFrequency (%)
3 3361
33.6%
5 3059
30.6%
30 2982
29.8%
20 598
 
6.0%

Length

2023-12-13T00:17:39.178174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:17:39.304232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3361
33.6%
5 3059
30.6%
30 2982
29.8%
20 598
 
6.0%

촉탁구분명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5647 
1
4353 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 5647
56.5%
1 4353
43.5%

Length

2023-12-13T00:17:39.743680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:17:39.835500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5647
56.5%
1 4353
43.5%

시설물분류명
Text

Distinct132
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T00:17:40.042739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length20.9058
Min length20

Characters and Unicode

Total characters209058
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11500CTVGTV1000012848
2nd row11500CTVGTV1000008741
3rd row11500CTVGTV1000014797
4th row11500CTVGTV1000016267
5th row11500CTVGTV100000706
ValueCountFrequency (%)
11500ctvgtv1000020540 156
 
1.6%
11500ctvgtv1000017975 155
 
1.6%
11500ctvgtv1000012848 153
 
1.5%
11500ctvgtv1000023960 149
 
1.5%
11500ctvgtv100000485 145
 
1.5%
11500ctvgtv1000016266 145
 
1.5%
11500ctvgtv1000011136 144
 
1.4%
11500ctvgtv1000023811 142
 
1.4%
11500ctvgtv1000026775 141
 
1.4%
11500ctvgtv1000022100 135
 
1.4%
Other values (122) 8535
85.4%
2023-12-13T00:17:40.403058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64382
30.8%
1 39445
18.9%
T 20000
 
9.6%
V 20000
 
9.6%
5 13334
 
6.4%
C 10000
 
4.8%
G 10000
 
4.8%
2 7877
 
3.8%
6 4952
 
2.4%
4 4687
 
2.2%
Other values (4) 14381
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 149058
71.3%
Uppercase Letter 60000
28.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64382
43.2%
1 39445
26.5%
5 13334
 
8.9%
2 7877
 
5.3%
6 4952
 
3.3%
4 4687
 
3.1%
7 4669
 
3.1%
8 3330
 
2.2%
3 3304
 
2.2%
9 3078
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
T 20000
33.3%
V 20000
33.3%
C 10000
16.7%
G 10000
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 149058
71.3%
Latin 60000
28.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64382
43.2%
1 39445
26.5%
5 13334
 
8.9%
2 7877
 
5.3%
6 4952
 
3.3%
4 4687
 
3.1%
7 4669
 
3.1%
8 3330
 
2.2%
3 3304
 
2.2%
9 3078
 
2.1%
Latin
ValueCountFrequency (%)
T 20000
33.3%
V 20000
33.3%
C 10000
16.7%
G 10000
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 209058
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64382
30.8%
1 39445
18.9%
T 20000
 
9.6%
V 20000
 
9.6%
5 13334
 
6.4%
C 10000
 
4.8%
G 10000
 
4.8%
2 7877
 
3.8%
6 4952
 
2.4%
4 4687
 
2.2%
Other values (4) 14381
 
6.9%

발생건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.439
Minimum0
Maximum20
Zeros8505
Zeros (%)85.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:17:40.557774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5093399
Coefficient of variation (CV)3.4381318
Kurtosis40.235732
Mean0.439
Median Absolute Deviation (MAD)0
Skewness5.5328434
Sum4390
Variance2.2781068
MonotonicityNot monotonic
2023-12-13T00:17:40.726110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 8505
85.0%
1 623
 
6.2%
2 274
 
2.7%
3 204
 
2.0%
4 122
 
1.2%
5 73
 
0.7%
6 61
 
0.6%
8 32
 
0.3%
9 27
 
0.3%
7 20
 
0.2%
Other values (10) 59
 
0.6%
ValueCountFrequency (%)
0 8505
85.0%
1 623
 
6.2%
2 274
 
2.7%
3 204
 
2.0%
4 122
 
1.2%
5 73
 
0.7%
6 61
 
0.6%
7 20
 
0.2%
8 32
 
0.3%
9 27
 
0.3%
ValueCountFrequency (%)
20 3
 
< 0.1%
19 1
 
< 0.1%
18 3
 
< 0.1%
16 1
 
< 0.1%
15 3
 
< 0.1%
14 6
 
0.1%
13 6
 
0.1%
12 8
0.1%
11 17
0.2%
10 11
0.1%

취소건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2502
Minimum0
Maximum12
Zeros8697
Zeros (%)87.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:17:40.863748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8374187
Coefficient of variation (CV)3.3469972
Kurtosis36.085134
Mean0.2502
Median Absolute Deviation (MAD)0
Skewness5.1649078
Sum2502
Variance0.70127009
MonotonicityNot monotonic
2023-12-13T00:17:40.997984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 8697
87.0%
1 724
 
7.2%
2 296
 
3.0%
3 140
 
1.4%
4 56
 
0.6%
6 34
 
0.3%
5 31
 
0.3%
7 9
 
0.1%
8 6
 
0.1%
11 3
 
< 0.1%
Other values (2) 4
 
< 0.1%
ValueCountFrequency (%)
0 8697
87.0%
1 724
 
7.2%
2 296
 
3.0%
3 140
 
1.4%
4 56
 
0.6%
5 31
 
0.3%
6 34
 
0.3%
7 9
 
0.1%
8 6
 
0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
11 3
 
< 0.1%
9 3
 
< 0.1%
8 6
 
0.1%
7 9
 
0.1%
6 34
 
0.3%
5 31
 
0.3%
4 56
 
0.6%
3 140
1.4%
2 296
3.0%

승인건수
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-13T00:17:41.136097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:17:41.240119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

완료건수
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-13T00:17:41.344985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:17:41.446815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

영치건수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

영치금액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

푸시건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1118
Minimum0
Maximum144
Zeros8697
Zeros (%)87.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:17:41.564232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12
Maximum144
Range144
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.3693551
Coefficient of variation (CV)3.9631381
Kurtosis60.5077
Mean2.1118
Median Absolute Deviation (MAD)0
Skewness6.6390812
Sum21118
Variance70.046105
MonotonicityNot monotonic
2023-12-13T00:17:41.704250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 8697
87.0%
12 418
 
4.2%
2 275
 
2.8%
24 142
 
1.4%
4 101
 
1.0%
36 86
 
0.9%
6 66
 
0.7%
14 54
 
0.5%
48 26
 
0.3%
72 22
 
0.2%
Other values (21) 113
 
1.1%
ValueCountFrequency (%)
0 8697
87.0%
2 275
 
2.8%
4 101
 
1.0%
6 66
 
0.7%
8 11
 
0.1%
10 11
 
0.1%
12 418
 
4.2%
14 54
 
0.5%
16 10
 
0.1%
18 2
 
< 0.1%
ValueCountFrequency (%)
144 1
 
< 0.1%
132 3
 
< 0.1%
108 1
 
< 0.1%
96 4
 
< 0.1%
86 1
 
< 0.1%
84 4
 
< 0.1%
74 4
 
< 0.1%
72 22
0.2%
68 2
 
< 0.1%
64 1
 
< 0.1%

Interactions

2023-12-13T00:17:37.930821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:37.018275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:37.454951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:38.117535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:37.163823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:37.610102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:38.284130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:37.304271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:37.785811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:17:41.801590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관심차량구분명촉탁구분명발생건수취소건수푸시건수
관심차량구분명1.0000.6440.3990.3050.241
촉탁구분명0.6441.0000.3830.2130.171
발생건수0.3990.3831.0000.7660.697
취소건수0.3050.2130.7661.0000.980
푸시건수0.2410.1710.6970.9801.000
2023-12-13T00:17:41.912066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관심차량구분명촉탁구분명
관심차량구분명1.0000.450
촉탁구분명0.4501.000
2023-12-13T00:17:42.013573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발생건수취소건수푸시건수관심차량구분명촉탁구분명
발생건수1.0000.9280.9260.2020.272
취소건수0.9281.0000.9980.1990.212
푸시건수0.9260.9981.0000.1560.171
관심차량구분명0.2020.1990.1561.0000.450
촉탁구분명0.2720.2120.1710.4501.000

Missing values

2023-12-13T00:17:38.478712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:17:38.668154image/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

통계일관심차량구분명촉탁구분명시설물분류명발생건수취소건수승인건수완료건수영치건수영치금액푸시건수
246992020-02-2120111500CTVGTV10000128480000<NA><NA>0
777502020-06-083011500CTVGTV10000087410000<NA><NA>0
836002020-06-1930011500CTVGTV10000147970000<NA><NA>0
946922020-07-1130011500CTVGTV10000162670000<NA><NA>0
817172020-06-163011500CTVGTV1000007060000<NA><NA>0
282592020-02-2830111500CTVGTV10000128480000<NA><NA>0
933352020-07-093011500CTVGTV10000264741100<NA><NA>2
753832020-06-033111500CTVGTV10000161552000<NA><NA>0
446892020-04-025011500CTVGTV10000120350000<NA><NA>0
912352020-07-0430111500CTVGTV10000267750000<NA><NA>0
통계일관심차량구분명촉탁구분명시설물분류명발생건수취소건수승인건수완료건수영치건수영치금액푸시건수
162172020-02-043011500CTVGTV10000145580000<NA><NA>0
794732020-06-115111500CTVGTV10000108340000<NA><NA>0
336982020-03-113011500CTVGTV10000266640000<NA><NA>0
714592020-05-265011500CTVGTV1000004840000<NA><NA>0
869042020-06-265011500CTVGTV10000221001100<NA><NA>6
207002020-02-135011500CTVGTV10000203920000<NA><NA>0
171262020-02-0530111500CTVGTV10000175980000<NA><NA>0
666772020-05-1620111500CTVGTV10000239600000<NA><NA>0
280022020-02-285011500CTVGTV10000238120000<NA><NA>0
387842020-03-215011500CTVGTV10000238570000<NA><NA>0