Overview

Dataset statistics

Number of variables4
Number of observations925
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.9 KiB
Average record size in memory33.1 B

Variable types

Numeric1
Categorical2
Text1

Dataset

Description인천광역시 서구 의류수거함에 대한 데이터로 연번, 행정동, 설치장소, 데이터기준일자의 정보가 포함되어 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15127251&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-06 09:45:28.238385
Analysis finished2024-04-06 09:45:28.816268
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct925
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean463
Minimum1
Maximum925
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-04-06T18:45:28.910246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile47.2
Q1232
median463
Q3694
95-th percentile878.8
Maximum925
Range924
Interquartile range (IQR)462

Descriptive statistics

Standard deviation267.1688
Coefficient of variation (CV)0.57703844
Kurtosis-1.2
Mean463
Median Absolute Deviation (MAD)231
Skewness0
Sum428275
Variance71379.167
MonotonicityStrictly increasing
2024-04-06T18:45:29.129499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
609 1
 
0.1%
611 1
 
0.1%
612 1
 
0.1%
613 1
 
0.1%
614 1
 
0.1%
615 1
 
0.1%
616 1
 
0.1%
617 1
 
0.1%
618 1
 
0.1%
Other values (915) 915
98.9%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
925 1
0.1%
924 1
0.1%
923 1
0.1%
922 1
0.1%
921 1
0.1%
920 1
0.1%
919 1
0.1%
918 1
0.1%
917 1
0.1%
916 1
0.1%

행정동
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
마전동
136 
심곡동
83 
청라동
76 
경서동
69 
신현원창동
60 
Other values (16)
501 

Length

Max length5
Median length3
Mean length3.3264865
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
마전동 136
14.7%
심곡동 83
 
9.0%
청라동 76
 
8.2%
경서동 69
 
7.5%
신현원창동 60
 
6.5%
석남2동 51
 
5.5%
당하동 51
 
5.5%
가좌동 43
 
4.6%
가정1동 43
 
4.6%
가좌1동 39
 
4.2%
Other values (11) 274
29.6%

Length

2024-04-06T18:45:29.389458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
마전동 136
14.7%
심곡동 83
 
9.0%
청라동 76
 
8.2%
경서동 69
 
7.5%
신현원창동 60
 
6.5%
석남2동 51
 
5.5%
당하동 51
 
5.5%
가좌동 43
 
4.6%
가정1동 43
 
4.6%
가좌1동 39
 
4.2%
Other values (11) 274
29.6%

설치장소
Text

Distinct908
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2024-04-06T18:45:29.869926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length11.115676
Min length6

Characters and Unicode

Total characters10282
Distinct characters145
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique892 ?
Unique (%)96.4%

Sample

1st row검암로 20번길15
2nd row검암로 20번길16
3rd row검암로 19번길9
4th row검암로 19번길21
5th row검암로 19번길23
ValueCountFrequency (%)
청라동 76
 
3.4%
완정로 55
 
2.5%
가정로 42
 
1.9%
염곡로 39
 
1.7%
경서로 38
 
1.7%
가현로 28
 
1.3%
당하동 26
 
1.2%
검단로 25
 
1.1%
원당동 24
 
1.1%
승학로 24
 
1.1%
Other values (813) 1860
83.1%
2024-04-06T18:45:30.574073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1514
14.7%
1 971
 
9.4%
로 743
 
7.2%
길 607
 
5.9%
번 592
 
5.8%
2 507
 
4.9%
3 450
 
4.4%
- 431
 
4.2%
4 407
 
4.0%
5 310
 
3.0%
Other values (135) 3750
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4319
42.0%
Decimal Number 4009
39.0%
Space Separator 1514
 
14.7%
Dash Punctuation 431
 
4.2%
Uppercase Letter 5
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 743
17.2%
길 607
 
14.1%
번 592
 
13.7%
동 194
 
4.5%
가 118
 
2.7%
서 113
 
2.6%
정 104
 
2.4%
청 101
 
2.3%
검 93
 
2.2%
라 91
 
2.1%
Other values (118) 1563
36.2%
Decimal Number
ValueCountFrequency (%)
1 971
24.2%
2 507
12.6%
3 450
11.2%
4 407
10.2%
5 310
 
7.7%
6 294
 
7.3%
7 288
 
7.2%
0 282
 
7.0%
8 273
 
6.8%
9 227
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
B 3
60.0%
C 1
 
20.0%
A 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1514
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 431
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5958
57.9%
Hangul 4319
42.0%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 743
17.2%
길 607
 
14.1%
번 592
 
13.7%
동 194
 
4.5%
가 118
 
2.7%
서 113
 
2.6%
정 104
 
2.4%
청 101
 
2.3%
검 93
 
2.2%
라 91
 
2.1%
Other values (118) 1563
36.2%
Common
ValueCountFrequency (%)
1514
25.4%
1 971
16.3%
2 507
 
8.5%
3 450
 
7.6%
- 431
 
7.2%
4 407
 
6.8%
5 310
 
5.2%
6 294
 
4.9%
7 288
 
4.8%
0 282
 
4.7%
Other values (4) 504
 
8.5%
Latin
ValueCountFrequency (%)
B 3
60.0%
C 1
 
20.0%
A 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5963
58.0%
Hangul 4319
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1514
25.4%
1 971
16.3%
2 507
 
8.5%
3 450
 
7.5%
- 431
 
7.2%
4 407
 
6.8%
5 310
 
5.2%
6 294
 
4.9%
7 288
 
4.8%
0 282
 
4.7%
Other values (7) 509
 
8.5%
Hangul
ValueCountFrequency (%)
로 743
17.2%
길 607
 
14.1%
번 592
 
13.7%
동 194
 
4.5%
가 118
 
2.7%
서 113
 
2.6%
정 104
 
2.4%
청 101
 
2.3%
검 93
 
2.2%
라 91
 
2.1%
Other values (118) 1563
36.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2024-03-18
925 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-18
2nd row2024-03-18
3rd row2024-03-18
4th row2024-03-18
5th row2024-03-18

Common Values

ValueCountFrequency (%)
2024-03-18 925
100.0%

Length

2024-04-06T18:45:30.797553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:45:30.949059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-18 925
100.0%

Interactions

2024-04-06T18:45:28.436736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T18:45:31.036328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동
연번1.0000.960
행정동0.9601.000
2024-04-06T18:45:31.163108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동
연번1.0000.789
행정동0.7891.000

Missing values

2024-04-06T18:45:28.620123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:45:28.765882image/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

연번행정동설치장소데이터기준일자
01검암동검암로 20번길152024-03-18
12검암동검암로 20번길162024-03-18
23검암동검암로 19번길92024-03-18
34검암동검암로 19번길212024-03-18
45검암동검암로 19번길232024-03-18
56검암동허암길 5-132024-03-18
67검암동허암길 13-32024-03-18
78검암동검암로 9번길 20-32024-03-18
89검암동검암로 9번길 20-172024-03-18
910검암동검암로 9번길 20-232024-03-18
연번행정동설치장소데이터기준일자
915916석남1동옻우물로 92024-03-18
916917석남1동옻우물로 122024-03-18
917918석남1동옻우물로 14번길 42024-03-18
918919석남1동옻우물로 22-1 (1)2024-03-18
919920석남1동옻우물로 22-1 (2)2024-03-18
920921석남1동옻우물로 26번길 92024-03-18
921922석남1동옻우물로 34번길 42024-03-18
922923석남1동옻우물로 31-12024-03-18
923924석남1동가정로 262번길 232024-03-18
924925석남1동옻우물로 14번길 202024-03-18