Overview

Dataset statistics

Number of variables8
Number of observations84
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory70.6 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 03:14:34.666923
Analysis finished2024-05-18 03:14:37.590636
Duration2.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
마포구
84 

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 84
100.0%

Length

2024-05-18T12:14:37.699425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:14:37.870079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마포구 84
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
PARKING-SENSOR
84 

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 84
100.0%

Length

2024-05-18T12:14:38.085897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:14:38.319898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
parking-sensor 84
100.0%

시리얼
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
111467200002
28 
111467200001
28 
111467200000
28 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
111467200002 28
33.3%
111467200001 28
33.3%
111467200000 28
33.3%

Length

2024-05-18T12:14:38.499372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:14:38.683180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
111467200002 28
33.3%
111467200001 28
33.3%
111467200000 28
33.3%

데이터요청일시
Real number (ℝ)

Distinct28
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0231226 × 109
Minimum2.0231225 × 109
Maximum2.0231226 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-05-18T12:14:38.889451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0231225 × 109
5-th percentile2.0231225 × 109
Q12.0231225 × 109
median2.0231226 × 109
Q32.0231226 × 109
95-th percentile2.0231226 × 109
Maximum2.0231226 × 109
Range113
Interquartile range (IQR)99.5

Descriptive statistics

Standard deviation50.463514
Coefficient of variation (CV)2.494338 × 10-8
Kurtosis-2.0220867
Mean2.0231226 × 109
Median Absolute Deviation (MAD)50
Skewness0
Sum1.699423 × 1011
Variance2546.5663
MonotonicityIncreasing
2024-05-18T12:14:39.216815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2023122509 3
 
3.6%
2023122610 3
 
3.6%
2023122622 3
 
3.6%
2023122621 3
 
3.6%
2023122620 3
 
3.6%
2023122619 3
 
3.6%
2023122618 3
 
3.6%
2023122617 3
 
3.6%
2023122616 3
 
3.6%
2023122615 3
 
3.6%
Other values (18) 54
64.3%
ValueCountFrequency (%)
2023122509 3
3.6%
2023122510 3
3.6%
2023122511 3
3.6%
2023122512 3
3.6%
2023122513 3
3.6%
2023122514 3
3.6%
2023122515 3
3.6%
2023122516 3
3.6%
2023122517 3
3.6%
2023122518 3
3.6%
ValueCountFrequency (%)
2023122622 3
3.6%
2023122621 3
3.6%
2023122620 3
3.6%
2023122619 3
3.6%
2023122618 3
3.6%
2023122617 3
3.6%
2023122616 3
3.6%
2023122615 3
3.6%
2023122614 3
3.6%
2023122613 3
3.6%

총주차면수
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
52
28 
102
28 
38
28 

Length

Max length3
Median length2
Mean length2.3333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
52 28
33.3%
102 28
33.3%
38 28
33.3%

Length

2024-05-18T12:14:39.622053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:14:39.854824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
52 28
33.3%
102 28
33.3%
38 28
33.3%

주차면수
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.535714
Minimum7
Maximum74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-05-18T12:14:40.075922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile10
Q114
median15
Q333
95-th percentile52.85
Maximum74
Range67
Interquartile range (IQR)19

Descriptive statistics

Standard deviation15.007184
Coefficient of variation (CV)0.63763453
Kurtosis1.9945978
Mean23.535714
Median Absolute Deviation (MAD)3.5
Skewness1.5606293
Sum1977
Variance225.21558
MonotonicityNot monotonic
2024-05-18T12:14:40.476826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
14 32
38.1%
34 6
 
7.1%
18 3
 
3.6%
15 3
 
3.6%
26 2
 
2.4%
21 2
 
2.4%
10 2
 
2.4%
33 2
 
2.4%
9 2
 
2.4%
49 2
 
2.4%
Other values (26) 28
33.3%
ValueCountFrequency (%)
7 1
 
1.2%
8 1
 
1.2%
9 2
 
2.4%
10 2
 
2.4%
11 1
 
1.2%
13 1
 
1.2%
14 32
38.1%
15 3
 
3.6%
16 1
 
1.2%
17 2
 
2.4%
ValueCountFrequency (%)
74 1
1.2%
72 1
1.2%
65 1
1.2%
58 1
1.2%
53 1
1.2%
52 1
1.2%
49 2
2.4%
45 1
1.2%
43 1
1.2%
42 1
1.2%

빈주차면수
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.464286
Minimum7
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-05-18T12:14:40.861936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile18
Q124
median35.5
Q353
95-th percentile81.85
Maximum84
Range77
Interquartile range (IQR)29

Descriptive statistics

Standard deviation21.73468
Coefficient of variation (CV)0.53713242
Kurtosis-0.68934052
Mean40.464286
Median Absolute Deviation (MAD)11.5
Skewness0.75866374
Sum3399
Variance472.3963
MonotonicityNot monotonic
2024-05-18T12:14:41.177775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
24 28
33.3%
38 4
 
4.8%
37 4
 
4.8%
18 3
 
3.6%
68 3
 
3.6%
44 2
 
2.4%
30 2
 
2.4%
53 2
 
2.4%
42 2
 
2.4%
84 2
 
2.4%
Other values (27) 32
38.1%
ValueCountFrequency (%)
7 1
 
1.2%
9 1
 
1.2%
10 1
 
1.2%
13 1
 
1.2%
18 3
 
3.6%
19 1
 
1.2%
24 28
33.3%
28 1
 
1.2%
30 2
 
2.4%
34 1
 
1.2%
ValueCountFrequency (%)
84 2
2.4%
83 2
2.4%
82 1
1.2%
81 2
2.4%
79 1
1.2%
76 2
2.4%
75 1
1.2%
74 1
1.2%
72 1
1.2%
71 1
1.2%

등록일자
Date

Distinct37
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
Minimum2023-12-25 09:00:01
Maximum2023-12-26 22:00:06
2024-05-18T12:14:41.638747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:14:41.983071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

Interactions

2024-05-18T12:14:36.640757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:14:35.121417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:14:36.068716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:14:36.797509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:14:35.549650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:14:36.219291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:14:36.995178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:14:35.787063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:14:36.383394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T12:14:42.191224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시리얼데이터요청일시총주차면수주차면수빈주차면수등록일자
시리얼1.0000.0001.0000.7380.9940.000
데이터요청일시0.0001.0000.0000.0000.3931.000
총주차면수1.0000.0001.0000.7380.9940.000
주차면수0.7380.0000.7381.0000.8750.000
빈주차면수0.9940.3930.9940.8751.0000.000
등록일자0.0001.0000.0000.0000.0001.000
2024-05-18T12:14:42.458673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시리얼총주차면수
시리얼1.0001.000
총주차면수1.0001.000
2024-05-18T12:14:42.693272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터요청일시주차면수빈주차면수시리얼총주차면수
데이터요청일시1.0000.249-0.2040.0000.000
주차면수0.2491.0000.2080.5780.578
빈주차면수-0.2040.2081.0000.8710.871
시리얼0.0000.5780.8711.0001.000
총주차면수0.0000.5780.8711.0001.000

Missing values

2024-05-18T12:14:37.275408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T12:14:37.505039image/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-SENSOR1114672000022023122509528442023-12-25 09:00:01
1마포구PARKING-SENSOR111467200001202312250910219832023-12-25 09:00:01
2마포구PARKING-SENSOR11146720000020231225093814242023-12-25 09:00:01
3마포구PARKING-SENSOR111467200001202312251010221812023-12-25 09:59:53
4마포구PARKING-SENSOR11146720000020231225103814242023-12-25 09:59:54
5마포구PARKING-SENSOR1114672000022023122510527452023-12-25 09:59:54
6마포구PARKING-SENSOR111467200001202312251110223792023-12-25 10:59:53
7마포구PARKING-SENSOR11146720000020231225113814242023-12-25 10:59:54
8마포구PARKING-SENSOR1114672000022023122511529432023-12-25 10:59:54
9마포구PARKING-SENSOR11146720000020231225123814242023-12-25 11:59:53
기관 명모델명시리얼데이터요청일시총주차면수주차면수빈주차면수등록일자
74마포구PARKING-SENSOR11146720000220231226195222302023-12-26 19:00:06
75마포구PARKING-SENSOR11146720000020231226203814242023-12-26 19:59:59
76마포구PARKING-SENSOR111467200001202312262010226762023-12-26 19:59:59
77마포구PARKING-SENSOR11146720000220231226205215372023-12-26 19:59:59
78마포구PARKING-SENSOR11146720000020231226213814242023-12-26 20:59:59
79마포구PARKING-SENSOR111467200001202312262110221812023-12-26 20:59:59
80마포구PARKING-SENSOR11146720000220231226215214382023-12-26 20:59:59
81마포구PARKING-SENSOR11146720000020231226223814242023-12-26 22:00:06
82마포구PARKING-SENSOR111467200001202312262210219832023-12-26 22:00:06
83마포구PARKING-SENSOR11146720000220231226225210422023-12-26 22:00:06