Overview

Dataset statistics

Number of variables5
Number of observations109
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory42.2 B

Variable types

Categorical4
Numeric1

Dataset

Description동대문구 거주자 우선주차 이용안내, 수납 및 환불방법, 방문주차, 동별 구획현황 등 정보제공
Author동대문구시설관리공단
URLhttps://www.data.go.kr/data/15012753/fileData.do

Alerts

구분 is highly overall correlated with 운영형태High correlation
동명 is highly overall correlated with 지구명 and 1 other fieldsHigh correlation
지구명 is highly overall correlated with 동명 and 1 other fieldsHigh correlation
운영형태 is highly overall correlated with 구획수 and 3 other fieldsHigh correlation
구획수 is highly overall correlated with 운영형태High correlation
운영형태 is highly imbalanced (92.5%)Imbalance
구획수 has 38 (34.9%) zerosZeros

Reproduction

Analysis started2023-12-12 01:46:20.305235
Analysis finished2023-12-12 01:46:20.932217
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size1004.0 B
용신동
12 
전농1동
12 
답십리1동
12 
장안2동
12 
제기동
8 
Other values (10)
53 

Length

Max length5
Median length4
Mean length3.9633028
Min length3

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
용신동 12
11.0%
전농1동 12
11.0%
답십리1동 12
11.0%
장안2동 12
11.0%
제기동 8
7.3%
답십리2동 8
7.3%
장안1동 8
7.3%
청량리동 8
7.3%
이문1동 8
7.3%
전농2동 4
 
3.7%
Other values (5) 17
15.6%

Length

2023-12-12T10:46:21.042833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용신동 12
11.0%
전농1동 12
11.0%
답십리1동 12
11.0%
장안2동 12
11.0%
제기동 8
7.3%
답십리2동 8
7.3%
장안1동 8
7.3%
청량리동 8
7.3%
이문1동 8
7.3%
전농2동 4
 
3.7%
Other values (5) 17
15.6%

지구명
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Memory size1004.0 B
신설동
 
4
용두1동
 
4
용두2동
 
4
제기1동
 
4
제기2동
 
4
Other values (23)
89 

Length

Max length5
Median length4
Mean length4.2568807
Min length3

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row신설동
2nd row신설동
3rd row신설동
4th row신설동
5th row용두1동

Common Values

ValueCountFrequency (%)
신설동 4
 
3.7%
용두1동 4
 
3.7%
용두2동 4
 
3.7%
제기1동 4
 
3.7%
제기2동 4
 
3.7%
전농1동 4
 
3.7%
전농2동 4
 
3.7%
전농4동 4
 
3.7%
전농3동 4
 
3.7%
답십리1동 4
 
3.7%
Other values (18) 69
63.3%

Length

2023-12-12T10:46:21.228245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신설동 4
 
3.7%
용두1동 4
 
3.7%
이문3동 4
 
3.7%
이문2동 4
 
3.7%
이문1동 4
 
3.7%
휘경2동 4
 
3.7%
휘경1동 4
 
3.7%
회기동 4
 
3.7%
청량리2동 4
 
3.7%
청량리1동 4
 
3.7%
Other values (18) 69
63.3%

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size1004.0 B
노상일반
27 
노상지정
27 
노외지평
27 
노외건물
27 
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row노상일반
2nd row노상지정
3rd row노외지평
4th row노외건물
5th row노상일반

Common Values

ValueCountFrequency (%)
노상일반 27
24.8%
노상지정 27
24.8%
노외지평 27
24.8%
노외건물 27
24.8%
<NA> 1
 
0.9%

Length

2023-12-12T10:46:21.376545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:46:21.501884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노상일반 27
24.8%
노상지정 27
24.8%
노외지평 27
24.8%
노외건물 27
24.8%
na 1
 
0.9%

구획수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct56
Distinct (%)51.9%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean48.185185
Minimum0
Maximum302
Zeros38
Zeros (%)34.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T10:46:21.655962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14.5
Q367
95-th percentile199.3
Maximum302
Range302
Interquartile range (IQR)67

Descriptive statistics

Standard deviation68.620744
Coefficient of variation (CV)1.4241046
Kurtosis2.3126662
Mean48.185185
Median Absolute Deviation (MAD)14.5
Skewness1.6953816
Sum5204
Variance4708.8065
MonotonicityNot monotonic
2023-12-12T10:46:21.809254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38
34.9%
14 3
 
2.8%
11 3
 
2.8%
67 3
 
2.8%
3 2
 
1.8%
48 2
 
1.8%
4 2
 
1.8%
141 2
 
1.8%
21 2
 
1.8%
2 2
 
1.8%
Other values (46) 49
45.0%
ValueCountFrequency (%)
0 38
34.9%
2 2
 
1.8%
3 2
 
1.8%
4 2
 
1.8%
5 1
 
0.9%
6 1
 
0.9%
9 1
 
0.9%
10 1
 
0.9%
11 3
 
2.8%
14 3
 
2.8%
ValueCountFrequency (%)
302 1
0.9%
277 1
0.9%
225 1
0.9%
223 1
0.9%
209 1
0.9%
200 1
0.9%
198 1
0.9%
173 1
0.9%
166 1
0.9%
165 1
0.9%

운영형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1004.0 B
주간,야간,전일
108 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.9449541
Min length4

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row 주간,야간,전일
2nd row 주간,야간,전일
3rd row 주간,야간,전일
4th row 주간,야간,전일
5th row 주간,야간,전일

Common Values

ValueCountFrequency (%)
주간,야간,전일 108
99.1%
<NA> 1
 
0.9%

Length

2023-12-12T10:46:21.980781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:46:22.089403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주간,야간,전일 108
99.1%
na 1
 
0.9%

Interactions

2023-12-12T10:46:20.583001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:46:22.155524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동명지구명구분구획수
동명1.0001.0000.0000.432
지구명1.0001.0000.0000.000
구분0.0000.0001.0000.490
구획수0.4320.0000.4901.000
2023-12-12T10:46:22.252353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분동명지구명운영형태
구분1.0000.0000.0001.000
동명0.0001.0000.9281.000
지구명0.0000.9281.0001.000
운영형태1.0001.0001.0001.000
2023-12-12T10:46:22.399763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구획수동명지구명구분운영형태
구획수1.0000.1900.0000.3261.000
동명0.1901.0000.9280.0001.000
지구명0.0000.9281.0000.0001.000
구분0.3260.0000.0001.0001.000
운영형태1.0001.0001.0001.0001.000

Missing values

2023-12-12T10:46:20.728731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:46:20.878791image/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

동명지구명구분구획수운영형태
0용신동신설동노상일반160주간,야간,전일
1용신동신설동노상지정33주간,야간,전일
2용신동신설동노외지평0주간,야간,전일
3용신동신설동노외건물0주간,야간,전일
4용신동용두1동노상일반166주간,야간,전일
5용신동용두1동노상지정29주간,야간,전일
6용신동용두1동노외지평18주간,야간,전일
7용신동용두1동노외건물0주간,야간,전일
8용신동용두2동노상일반173주간,야간,전일
9용신동용두2동노상지정28주간,야간,전일
동명지구명구분구획수운영형태
99이문1동이문1동노외건물0주간,야간,전일
100이문1동이문2동노상일반141주간,야간,전일
101이문1동이문2동노상지정10주간,야간,전일
102이문1동이문2동노외지평0주간,야간,전일
103이문1동이문2동노외건물0주간,야간,전일
104이문2동이문3동노상일반302주간,야간,전일
105이문2동이문3동노상지정0주간,야간,전일
106이문2동이문3동노외지평0주간,야간,전일
107이문2동이문3동노외건물0주간,야간,전일
108<NA><NA><NA><NA><NA>