Overview

Dataset statistics

Number of variables5
Number of observations73
Missing cells152
Missing cells (%)41.6%
Duplicate rows1
Duplicate rows (%)1.4%
Total size in memory3.2 KiB
Average record size in memory44.8 B

Variable types

Numeric1
Unsupported2
Categorical1
Text1

Dataset

Description이 파일에는 청양군에 있는 위치한 의류 수거함의 연번, 관리번호, 관리단체, 행정동과 의류 수거함의 도로명 주소가 있습니다.
Author충청남도 청양군
URLhttps://www.data.go.kr/data/15127312/fileData.do

Alerts

Dataset has 1 (1.4%) duplicate rowsDuplicates
연번 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 연번High correlation
행정동 is highly imbalanced (75.3%)Imbalance
연번 has 3 (4.1%) missing valuesMissing
관리번호 has 73 (100.0%) missing valuesMissing
관리단체 has 73 (100.0%) missing valuesMissing
설치장소(도로명) has 3 (4.1%) missing valuesMissing
관리번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
관리단체 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 08:56:00.758472
Analysis finished2024-04-06 08:56:02.181846
Duration1.42 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct70
Distinct (%)100.0%
Missing3
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean35.5
Minimum1
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-04-06T17:56:02.363168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.45
Q118.25
median35.5
Q352.75
95-th percentile66.55
Maximum70
Range69
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation20.351085
Coefficient of variation (CV)0.57327
Kurtosis-1.2
Mean35.5
Median Absolute Deviation (MAD)17.5
Skewness0
Sum2485
Variance414.16667
MonotonicityStrictly increasing
2024-04-06T17:56:02.645793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
45 1
 
1.4%
54 1
 
1.4%
44 1
 
1.4%
Other values (60) 60
82.2%
(Missing) 3
 
4.1%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%
61 1
1.4%

관리번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing73
Missing (%)100.0%
Memory size789.0 B

관리단체
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing73
Missing (%)100.0%
Memory size789.0 B

행정동
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
청양읍
70 
<NA>
 
3

Length

Max length4
Median length3
Mean length3.0410959
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청양읍 70
95.9%
<NA> 3
 
4.1%

Length

2024-04-06T17:56:02.945914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:56:03.141382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청양읍 70
95.9%
na 3
 
4.1%

설치장소(도로명)
Text

MISSING 

Distinct70
Distinct (%)100.0%
Missing3
Missing (%)4.1%
Memory size716.0 B
2024-04-06T17:56:03.745174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length16.914286
Min length10

Characters and Unicode

Total characters1184
Distinct characters135
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)100.0%

Sample

1st row청양읍 중앙로 35 (필로스캐슬)
2nd row청양읍 읍내리 383-4(예미지전시관)
3rd row청양읍 중앙로 70-4(샤인빌)
4th row청양읍 중앙로 70-8(동아노블타운)
5th row청양읍 중앙로 70-10(해마루타운)
ValueCountFrequency (%)
청양읍 70
27.9%
중앙로 23
 
9.2%
칠갑산로 14
 
5.6%
평촌1길 5
 
2.0%
고리섬들길 5
 
2.0%
앞 5
 
2.0%
12길 3
 
1.2%
3길 3
 
1.2%
14길 3
 
1.2%
열길 3
 
1.2%
Other values (105) 117
46.6%
2024-04-06T17:56:04.744590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
181
 
15.3%
청 80
 
6.8%
양 76
 
6.4%
읍 73
 
6.2%
1 69
 
5.8%
길 50
 
4.2%
로 50
 
4.2%
2 36
 
3.0%
) 32
 
2.7%
( 32
 
2.7%
Other values (125) 505
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 686
57.9%
Decimal Number 223
 
18.8%
Space Separator 181
 
15.3%
Close Punctuation 32
 
2.7%
Open Punctuation 32
 
2.7%
Dash Punctuation 26
 
2.2%
Lowercase Letter 2
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 80
 
11.7%
양 76
 
11.1%
읍 73
 
10.6%
길 50
 
7.3%
로 50
 
7.3%
산 25
 
3.6%
중 24
 
3.5%
앙 24
 
3.5%
칠 20
 
2.9%
갑 20
 
2.9%
Other values (107) 244
35.6%
Decimal Number
ValueCountFrequency (%)
1 69
30.9%
2 36
16.1%
3 23
 
10.3%
8 19
 
8.5%
7 15
 
6.7%
6 15
 
6.7%
4 14
 
6.3%
5 14
 
6.3%
0 13
 
5.8%
9 5
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
t 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
H 1
50.0%
Space Separator
ValueCountFrequency (%)
181
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 686
57.9%
Common 494
41.7%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 80
 
11.7%
양 76
 
11.1%
읍 73
 
10.6%
길 50
 
7.3%
로 50
 
7.3%
산 25
 
3.6%
중 24
 
3.5%
앙 24
 
3.5%
칠 20
 
2.9%
갑 20
 
2.9%
Other values (107) 244
35.6%
Common
ValueCountFrequency (%)
181
36.6%
1 69
 
14.0%
2 36
 
7.3%
) 32
 
6.5%
( 32
 
6.5%
- 26
 
5.3%
3 23
 
4.7%
8 19
 
3.8%
7 15
 
3.0%
6 15
 
3.0%
Other values (4) 46
 
9.3%
Latin
ValueCountFrequency (%)
k 1
25.0%
L 1
25.0%
H 1
25.0%
t 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 686
57.9%
ASCII 498
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
181
36.3%
1 69
 
13.9%
2 36
 
7.2%
) 32
 
6.4%
( 32
 
6.4%
- 26
 
5.2%
3 23
 
4.6%
8 19
 
3.8%
7 15
 
3.0%
6 15
 
3.0%
Other values (8) 50
 
10.0%
Hangul
ValueCountFrequency (%)
청 80
 
11.7%
양 76
 
11.1%
읍 73
 
10.6%
길 50
 
7.3%
로 50
 
7.3%
산 25
 
3.6%
중 24
 
3.5%
앙 24
 
3.5%
칠 20
 
2.9%
갑 20
 
2.9%
Other values (107) 244
35.6%

Interactions

2024-04-06T17:56:01.051331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:56:05.052613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치장소(도로명)
연번1.0001.000
설치장소(도로명)1.0001.000
2024-04-06T17:56:05.275580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동
연번1.0001.000
행정동1.0001.000

Missing values

2024-04-06T17:56:01.316508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:56:01.484592image/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.
2024-04-06T17:56:02.064433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번관리번호관리단체행정동설치장소(도로명)
01<NA><NA>청양읍청양읍 중앙로 35 (필로스캐슬)
12<NA><NA>청양읍청양읍 읍내리 383-4(예미지전시관)
23<NA><NA>청양읍청양읍 중앙로 70-4(샤인빌)
34<NA><NA>청양읍청양읍 중앙로 70-8(동아노블타운)
45<NA><NA>청양읍청양읍 중앙로 70-10(해마루타운)
56<NA><NA>청양읍청양읍 청산로 29(천강아파트)
67<NA><NA>청양읍청양읍 고리섬들길 108-16
78<NA><NA>청양읍청양읍 고리섬들길 105
89<NA><NA>청양읍청양읍 고리섬들길 97-1
910<NA><NA>청양읍청양읍 고리섬들길 92(디엠에이스빌아파트)
연번관리번호관리단체행정동설치장소(도로명)
6364<NA><NA>청양읍청양읍 중앙로 17길 8
6465<NA><NA>청양읍청양읍 중앙로 17길 18-1
6566<NA><NA>청양읍청양읍 문화예술로 창성빌라 옆
6667<NA><NA>청양읍청양읍 문화예술로 182(드림아파트)
6768<NA><NA>청양읍청양읍 문화예술1길 8(드림팰리스)
6869<NA><NA>청양읍청양읍 중앙로 13길 8(청양읍 kt)
6970<NA><NA>청양읍청양읍 칠갑산3길 15-13
70<NA><NA><NA><NA><NA>
71<NA><NA><NA><NA><NA>
72<NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

연번행정동설치장소(도로명)# duplicates
0<NA><NA><NA>3