Overview

Dataset statistics

Number of variables8
Number of observations294
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.9 KiB
Average record size in memory69.4 B

Variable types

Categorical4
Numeric3
DateTime1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15980/S/1/datasetView.do

Alerts

기관 명 has constant value ""Constant
모델명 has constant value ""Constant
시리얼 is highly overall correlated with 주차면수 and 2 other fieldsHigh correlation
총주차면수 is highly overall correlated with 주차면수 and 2 other fieldsHigh correlation
주차면수 is highly overall correlated with 시리얼 and 1 other fieldsHigh correlation
빈주차면수 is highly overall correlated with 시리얼 and 1 other fieldsHigh correlation

Reproduction

Analysis started2024-05-18 03:15:05.129432
Analysis finished2024-05-18 03:15:08.577293
Duration3.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
마포구
294 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
마포구 294
100.0%

Length

2024-05-18T12:15:08.794716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:15:09.131175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마포구 294
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
PARKING-SENSOR
294 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPARKING-SENSOR
2nd rowPARKING-SENSOR
3rd rowPARKING-SENSOR
4th rowPARKING-SENSOR
5th rowPARKING-SENSOR

Common Values

ValueCountFrequency (%)
PARKING-SENSOR 294
100.0%

Length

2024-05-18T12:15:09.423350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:15:09.718407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
parking-sensor 294
100.0%

시리얼
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
111467200001
98 
111467200000
98 
111467200002
98 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row111467200001
2nd row111467200000
3rd row111467200002
4th row111467200001
5th row111467200002

Common Values

ValueCountFrequency (%)
111467200001 98
33.3%
111467200000 98
33.3%
111467200002 98
33.3%

Length

2024-05-18T12:15:10.100996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:15:10.411240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
111467200001 98
33.3%
111467200000 98
33.3%
111467200002 98
33.3%

데이터요청일시
Real number (ℝ)

Distinct98
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0240172 × 109
Minimum2.0240129 × 109
Maximum2.0240204 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-18T12:15:10.949380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0240129 × 109
5-th percentile2.0240129 × 109
Q12.024013 × 109
median2.0240201 × 109
Q32.0240203 × 109
95-th percentile2.0240204 × 109
Maximum2.0240204 × 109
Range7513
Interquartile range (IQR)7293

Descriptive statistics

Standard deviation3595.3349
Coefficient of variation (CV)1.7763362 × 10-6
Kurtosis-1.9263423
Mean2.0240172 × 109
Median Absolute Deviation (MAD)300
Skewness-0.28914386
Sum5.9506104 × 1011
Variance12926433
MonotonicityIncreasing
2024-05-18T12:15:11.211157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2024012909 3
 
1.0%
2024020313 3
 
1.0%
2024020311 3
 
1.0%
2024020310 3
 
1.0%
2024020309 3
 
1.0%
2024020222 3
 
1.0%
2024020221 3
 
1.0%
2024020220 3
 
1.0%
2024020219 3
 
1.0%
2024020218 3
 
1.0%
Other values (88) 264
89.8%
ValueCountFrequency (%)
2024012909 3
1.0%
2024012910 3
1.0%
2024012911 3
1.0%
2024012912 3
1.0%
2024012913 3
1.0%
2024012914 3
1.0%
2024012915 3
1.0%
2024012916 3
1.0%
2024012917 3
1.0%
2024012918 3
1.0%
ValueCountFrequency (%)
2024020422 3
1.0%
2024020421 3
1.0%
2024020420 3
1.0%
2024020419 3
1.0%
2024020418 3
1.0%
2024020417 3
1.0%
2024020416 3
1.0%
2024020415 3
1.0%
2024020414 3
1.0%
2024020413 3
1.0%

총주차면수
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
102
98 
38
98 
52
98 

Length

Max length3
Median length2
Mean length2.3333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row102
2nd row38
3rd row52
4th row102
5th row52

Common Values

ValueCountFrequency (%)
102 98
33.3%
38 98
33.3%
52 98
33.3%

Length

2024-05-18T12:15:11.622483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:15:11.929761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
102 98
33.3%
38 98
33.3%
52 98
33.3%

주차면수
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.204082
Minimum8
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-18T12:15:12.269975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q114
median23
Q339.75
95-th percentile67
Maximum94
Range86
Interquartile range (IQR)25.75

Descriptive statistics

Standard deviation18.74162
Coefficient of variation (CV)0.64174659
Kurtosis1.9185703
Mean29.204082
Median Absolute Deviation (MAD)9
Skewness1.432778
Sum8586
Variance351.24831
MonotonicityNot monotonic
2024-05-18T12:15:12.661814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 100
34.0%
44 10
 
3.4%
32 7
 
2.4%
18 7
 
2.4%
21 7
 
2.4%
34 7
 
2.4%
45 6
 
2.0%
23 6
 
2.0%
13 6
 
2.0%
28 5
 
1.7%
Other values (57) 133
45.2%
ValueCountFrequency (%)
8 1
 
0.3%
9 1
 
0.3%
10 1
 
0.3%
11 3
 
1.0%
12 2
 
0.7%
13 6
 
2.0%
14 100
34.0%
15 1
 
0.3%
16 4
 
1.4%
17 5
 
1.7%
ValueCountFrequency (%)
94 1
 
0.3%
93 1
 
0.3%
92 1
 
0.3%
91 1
 
0.3%
89 1
 
0.3%
87 3
1.0%
86 1
 
0.3%
85 1
 
0.3%
81 1
 
0.3%
79 1
 
0.3%

빈주차면수
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.795918
Minimum5
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-18T12:15:13.042676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8
Q124
median24
Q346.75
95-th percentile79.7
Maximum88
Range83
Interquartile range (IQR)22.75

Descriptive statistics

Standard deviation21.486384
Coefficient of variation (CV)0.61749725
Kurtosis-0.17828992
Mean34.795918
Median Absolute Deviation (MAD)9
Skewness0.97518436
Sum10230
Variance461.66469
MonotonicityNot monotonic
2024-05-18T12:15:13.435946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 99
33.7%
8 10
 
3.4%
39 8
 
2.7%
15 6
 
2.0%
20 6
 
2.0%
35 5
 
1.7%
23 5
 
1.7%
12 4
 
1.4%
41 4
 
1.4%
31 4
 
1.4%
Other values (66) 143
48.6%
ValueCountFrequency (%)
5 1
 
0.3%
6 1
 
0.3%
7 4
 
1.4%
8 10
3.4%
9 4
 
1.4%
10 4
 
1.4%
11 2
 
0.7%
12 4
 
1.4%
13 2
 
0.7%
14 2
 
0.7%
ValueCountFrequency (%)
88 1
 
0.3%
86 2
0.7%
85 2
0.7%
84 3
1.0%
83 3
1.0%
82 1
 
0.3%
81 3
1.0%
79 3
1.0%
78 1
 
0.3%
77 3
1.0%

등록일자
Date

Distinct121
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2024-01-29 08:58:48
Maximum2024-02-04 21:58:34
2024-05-18T12:15:13.800002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:15:14.209755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-18T12:15:07.186059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:15:05.493123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:15:06.322591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:15:07.454614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:15:05.810238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:15:06.695116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:15:07.682165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:15:06.066786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:15:06.920891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T12:15:14.476682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시리얼데이터요청일시총주차면수주차면수빈주차면수
시리얼1.0000.0001.0000.7830.875
데이터요청일시0.0001.0000.0000.2670.140
총주차면수1.0000.0001.0000.7830.875
주차면수0.7830.2670.7831.0000.905
빈주차면수0.8750.1400.8750.9051.000
2024-05-18T12:15:14.732873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시리얼총주차면수
시리얼1.0001.000
총주차면수1.0001.000
2024-05-18T12:15:14.968456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터요청일시주차면수빈주차면수시리얼총주차면수
데이터요청일시1.0000.023-0.1360.0000.000
주차면수0.0231.000-0.0700.6580.658
빈주차면수-0.136-0.0701.0000.7990.799
시리얼0.0000.6580.7991.0001.000
총주차면수0.0000.6580.7991.0001.000

Missing values

2024-05-18T12:15:07.998665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T12:15:08.422007image/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

기관 명모델명시리얼데이터요청일시총주차면수주차면수빈주차면수등록일자
0마포구PARKING-SENSOR111467200001202401290910228742024-01-29 08:58:48
1마포구PARKING-SENSOR11146720000020240129093814242024-01-29 08:58:48
2마포구PARKING-SENSOR11146720000220240129095217352024-01-29 08:58:48
3마포구PARKING-SENSOR111467200001202401291010228742024-01-29 09:58:48
4마포구PARKING-SENSOR11146720000220240129105222302024-01-29 09:58:49
5마포구PARKING-SENSOR11146720000020240129103814242024-01-29 09:58:49
6마포구PARKING-SENSOR11146720000220240129115223292024-01-29 10:58:42
7마포구PARKING-SENSOR111467200001202401291110228742024-01-29 10:58:42
8마포구PARKING-SENSOR11146720000020240129113814242024-01-29 10:58:42
9마포구PARKING-SENSOR11146720000220240129125229232024-01-29 11:58:48
기관 명모델명시리얼데이터요청일시총주차면수주차면수빈주차면수등록일자
284마포구PARKING-SENSOR111467200001202402041910235672024-02-04 18:58:34
285마포구PARKING-SENSOR11146720000020240204203814242024-02-04 19:58:27
286마포구PARKING-SENSOR111467200001202402042010225772024-02-04 19:58:27
287마포구PARKING-SENSOR11146720000220240204205216362024-02-04 19:58:28
288마포구PARKING-SENSOR111467200001202402042110220822024-02-04 20:58:33
289마포구PARKING-SENSOR11146720000220240204215213392024-02-04 20:58:34
290마포구PARKING-SENSOR11146720000020240204213814242024-02-04 20:58:34
291마포구PARKING-SENSOR111467200001202402042210218842024-02-04 21:58:33
292마포구PARKING-SENSOR11146720000020240204223814242024-02-04 21:58:34
293마포구PARKING-SENSOR11146720000220240204225213392024-02-04 21:58:34