Overview

Dataset statistics

Number of variables4
Number of observations125
Missing cells1
Missing cells (%)0.2%
Duplicate rows18
Duplicate rows (%)14.4%
Total size in memory4.2 KiB
Average record size in memory34.1 B

Variable types

Unsupported1
Numeric1
Categorical1
Text1

Dataset

Description광진구시설관리공단 거주자우선주차 현황은 지역별로 시트 내에서 확인이 가능합니다.또한, 형태, 주소, 면수 등을 확인하실 수 있습니다.자세한 내용은 주차사업팀 2049-4540 으로 문의하여 주시기 바랍니다.
Author광진구시설관리공단
URLhttps://www.data.go.kr/data/15112976/fileData.do

Alerts

Dataset has 18 (14.4%) duplicate rowsDuplicates
면수 is highly overall correlated with 형태High correlation
형태 is highly overall correlated with 면수High correlation
형태 is highly imbalanced (87.0%)Imbalance
구획번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-30 07:46:29.171129
Analysis finished2024-03-30 07:46:30.908731
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구획번호
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.1 KiB

면수
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.32
Minimum1
Maximum145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T07:46:31.156711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum145
Range144
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12.925718
Coefficient of variation (CV)5.5714303
Kurtosis122.60067
Mean2.32
Median Absolute Deviation (MAD)0
Skewness11.028409
Sum290
Variance167.07419
MonotonicityNot monotonic
2024-03-30T07:46:31.522935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 120
96.0%
3 1
 
0.8%
6 1
 
0.8%
14 1
 
0.8%
2 1
 
0.8%
145 1
 
0.8%
ValueCountFrequency (%)
1 120
96.0%
2 1
 
0.8%
3 1
 
0.8%
6 1
 
0.8%
14 1
 
0.8%
145 1
 
0.8%
ValueCountFrequency (%)
145 1
 
0.8%
14 1
 
0.8%
6 1
 
0.8%
3 1
 
0.8%
2 1
 
0.8%
1 120
96.0%

형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
노상
120 
경도빌딩
 
1
제이앤빌
 
1
리마크빌
 
1
광남캐스빌
 
1

Length

Max length5
Median length2
Mean length2.088
Min length2

Unique

Unique5 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
노상 120
96.0%
경도빌딩 1
 
0.8%
제이앤빌 1
 
0.8%
리마크빌 1
 
0.8%
광남캐스빌 1
 
0.8%
<NA> 1
 
0.8%

Length

2024-03-30T07:46:32.047872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T07:46:32.683403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노상 120
96.0%
경도빌딩 1
 
0.8%
제이앤빌 1
 
0.8%
리마크빌 1
 
0.8%
광남캐스빌 1
 
0.8%
na 1
 
0.8%

주소
Text

Distinct84
Distinct (%)67.7%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2024-03-30T07:46:33.408910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.3629032
Min length5

Characters and Unicode

Total characters789
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)53.2%

Sample

1st row 639-1
2nd row 639-12
3rd row 642-4
4th row 641-5
5th row 640-6
ValueCountFrequency (%)
643-4 13
 
10.5%
643-1 10
 
8.1%
245-6 4
 
3.2%
612-3 4
 
3.2%
242-20 2
 
1.6%
246-60 2
 
1.6%
646-23 2
 
1.6%
253-4 2
 
1.6%
248-18 2
 
1.6%
242-5 2
 
1.6%
Other values (73) 81
65.3%
2024-03-30T07:46:35.295107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 124
15.7%
2 116
14.7%
4 112
14.2%
  107
13.6%
3 85
10.8%
6 84
10.6%
1 55
7.0%
5 37
 
4.7%
8 20
 
2.5%
7 19
 
2.4%
Other values (3) 30
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 555
70.3%
Dash Punctuation 124
 
15.7%
Space Separator 110
 
13.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 116
20.9%
4 112
20.2%
3 85
15.3%
6 84
15.1%
1 55
9.9%
5 37
 
6.7%
8 20
 
3.6%
7 19
 
3.4%
9 18
 
3.2%
0 9
 
1.6%
Space Separator
ValueCountFrequency (%)
  107
97.3%
3
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 789
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 124
15.7%
2 116
14.7%
4 112
14.2%
  107
13.6%
3 85
10.8%
6 84
10.6%
1 55
7.0%
5 37
 
4.7%
8 20
 
2.5%
7 19
 
2.4%
Other values (3) 30
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 682
86.4%
None 107
 
13.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 124
18.2%
2 116
17.0%
4 112
16.4%
3 85
12.5%
6 84
12.3%
1 55
8.1%
5 37
 
5.4%
8 20
 
2.9%
7 19
 
2.8%
9 18
 
2.6%
Other values (2) 12
 
1.8%
None
ValueCountFrequency (%)
  107
100.0%

Interactions

2024-03-30T07:46:29.381303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T07:46:35.778726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면수형태주소
면수1.000NaNNaN
형태NaN1.0001.000
주소NaN1.0001.000
2024-03-30T07:46:36.042614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면수형태
면수1.0001.000
형태1.0001.000

Missing values

2024-03-30T07:46:30.140915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T07:46:30.729116image/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

구획번호면수형태주소
00011노상639-1
10041노상639-12
20091노상642-4
30101노상641-5
410-21노상640-6
50181노상643-1
60191노상643-1
70211노상643-1
80221노상643-1
90241노상643-1
구획번호면수형태주소
1153711노상235-27
1163741노상232-53
1173781노상233-7
1183791노상233-7
1193801노상635-7
120경도빌딩3경도빌딩626-18
121제이앤빌6제이앤빌233-37
122리마크빌14리마크빌637-5
123광남캐스빌2광남캐스빌646-10
124합 계145<NA><NA>

Duplicate rows

Most frequently occurring

면수형태주소# duplicates
151노상643-413
141노상643-110
81노상245-64
01노상612-33
11노상612-22
21노상636-12
31노상233-72
41노상235-272
51노상242-202
61노상242-52