Overview

Dataset statistics

Number of variables4
Number of observations894
Missing cells7
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.9 KiB
Average record size in memory33.1 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description인천광역시 미추홀구의 동별 의류수거함 위치 현황에 대한 데이터로 연번, 관할동, 도로명주소, 지번주소 등의 항목을 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15086045/fileData.do

Alerts

연번 is highly overall correlated with 관할동High correlation
관할동 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:18:06.561990
Analysis finished2023-12-12 00:18:07.436555
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct894
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean447.5
Minimum1
Maximum894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-12T09:18:07.509183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45.65
Q1224.25
median447.5
Q3670.75
95-th percentile849.35
Maximum894
Range893
Interquartile range (IQR)446.5

Descriptive statistics

Standard deviation258.21987
Coefficient of variation (CV)0.57702764
Kurtosis-1.2
Mean447.5
Median Absolute Deviation (MAD)223.5
Skewness0
Sum400065
Variance66677.5
MonotonicityStrictly increasing
2023-12-12T09:18:07.639389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
602 1
 
0.1%
591 1
 
0.1%
592 1
 
0.1%
593 1
 
0.1%
594 1
 
0.1%
595 1
 
0.1%
596 1
 
0.1%
597 1
 
0.1%
598 1
 
0.1%
Other values (884) 884
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 (%)
894 1
0.1%
893 1
0.1%
892 1
0.1%
891 1
0.1%
890 1
0.1%
889 1
0.1%
888 1
0.1%
887 1
0.1%
886 1
0.1%
885 1
0.1%

관할동
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
도화1동
107 
용현1_4동
100 
주안2동
74 
문학동
62 
숭의2동
52 
Other values (16)
499 

Length

Max length6
Median length4
Mean length4.2651007
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숭의1_3동
2nd row숭의1_3동
3rd row숭의1_3동
4th row숭의1_3동
5th row숭의1_3동

Common Values

ValueCountFrequency (%)
도화1동 107
 
12.0%
용현1_4동 100
 
11.2%
주안2동 74
 
8.3%
문학동 62
 
6.9%
숭의2동 52
 
5.8%
숭의4동 44
 
4.9%
주안4동 43
 
4.8%
용현5동 43
 
4.8%
주안1동 43
 
4.8%
도화2_3동 35
 
3.9%
Other values (11) 291
32.6%

Length

2023-12-12T09:18:07.763840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도화1동 107
 
12.0%
용현1_4동 100
 
11.2%
주안2동 74
 
8.3%
문학동 62
 
6.9%
숭의2동 52
 
5.8%
숭의4동 44
 
4.9%
주안4동 43
 
4.8%
용현5동 43
 
4.8%
주안1동 43
 
4.8%
도화2_3동 35
 
3.9%
Other values (11) 291
32.6%

도로명주소
Text

Distinct884
Distinct (%)99.2%
Missing3
Missing (%)0.3%
Memory size7.1 KiB
2023-12-12T09:18:08.086018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length32
Mean length21.940516
Min length16

Characters and Unicode

Total characters19549
Distinct characters127
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

Unique877 ?
Unique (%)98.4%

Sample

1st row인천광역시 미추홀구 제물량로24번길 51
2nd row인천광역시 미추홀구 제물량로24번길 33
3rd row인천광역시 미추홀구 석정로50번길 12
4th row인천광역시 미추홀구 경인로7번길 45
5th row인천광역시 미추홀구 석정로64번길 30
ValueCountFrequency (%)
인천광역시 891
24.2%
미추홀구 891
24.2%
재넘이길 32
 
0.9%
한나루로 23
 
0.6%
17 22
 
0.6%
경인남길 21
 
0.6%
경인로 21
 
0.6%
인하로 21
 
0.6%
8 18
 
0.5%
경인북길 18
 
0.5%
Other values (825) 1731
46.9%
2023-12-12T09:18:08.494960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2808
 
14.4%
인 1119
 
5.7%
홀 961
 
4.9%
미 944
 
4.8%
추 944
 
4.8%
천 910
 
4.7%
구 895
 
4.6%
시 892
 
4.6%
광 891
 
4.6%
역 891
 
4.6%
Other values (117) 8294
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12629
64.6%
Decimal Number 3863
 
19.8%
Space Separator 2808
 
14.4%
Dash Punctuation 223
 
1.1%
Open Punctuation 9
 
< 0.1%
Close Punctuation 9
 
< 0.1%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 1119
 
8.9%
홀 961
 
7.6%
미 944
 
7.5%
추 944
 
7.5%
천 910
 
7.2%
구 895
 
7.1%
시 892
 
7.1%
광 891
 
7.1%
역 891
 
7.1%
길 850
 
6.7%
Other values (100) 3332
26.4%
Decimal Number
ValueCountFrequency (%)
1 715
18.5%
2 522
13.5%
3 486
12.6%
4 413
10.7%
5 377
9.8%
6 325
8.4%
7 304
7.9%
8 279
 
7.2%
0 226
 
5.9%
9 216
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
A 4
50.0%
B 3
37.5%
J 1
 
12.5%
Space Separator
ValueCountFrequency (%)
2808
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 223
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12629
64.6%
Common 6912
35.4%
Latin 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 1119
 
8.9%
홀 961
 
7.6%
미 944
 
7.5%
추 944
 
7.5%
천 910
 
7.2%
구 895
 
7.1%
시 892
 
7.1%
광 891
 
7.1%
역 891
 
7.1%
길 850
 
6.7%
Other values (100) 3332
26.4%
Common
ValueCountFrequency (%)
2808
40.6%
1 715
 
10.3%
2 522
 
7.6%
3 486
 
7.0%
4 413
 
6.0%
5 377
 
5.5%
6 325
 
4.7%
7 304
 
4.4%
8 279
 
4.0%
0 226
 
3.3%
Other values (4) 457
 
6.6%
Latin
ValueCountFrequency (%)
A 4
50.0%
B 3
37.5%
J 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12629
64.6%
ASCII 6920
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2808
40.6%
1 715
 
10.3%
2 522
 
7.5%
3 486
 
7.0%
4 413
 
6.0%
5 377
 
5.4%
6 325
 
4.7%
7 304
 
4.4%
8 279
 
4.0%
0 226
 
3.3%
Other values (7) 465
 
6.7%
Hangul
ValueCountFrequency (%)
인 1119
 
8.9%
홀 961
 
7.6%
미 944
 
7.5%
추 944
 
7.5%
천 910
 
7.2%
구 895
 
7.1%
시 892
 
7.1%
광 891
 
7.1%
역 891
 
7.1%
길 850
 
6.7%
Other values (100) 3332
26.4%

지번주소
Text

Distinct877
Distinct (%)98.5%
Missing4
Missing (%)0.4%
Memory size7.1 KiB
2023-12-12T09:18:08.868706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length24.7
Min length17

Characters and Unicode

Total characters21983
Distinct characters307
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique865 ?
Unique (%)97.2%

Sample

1st row인천광역시 미추홀구 숭의동 359-1 솔루나
2nd row인천광역시 미추홀구 숭의동 388-6 새빛타운
3rd row인천광역시 미추홀구 숭의동 162-4 삼성캐슬
4th row인천광역시 미추홀구 숭의동 161-36
5th row인천광역시 미추홀구 숭의동 160-73
ValueCountFrequency (%)
미추홀구 935
22.7%
인천광역시 934
22.7%
주안동 291
 
7.1%
용현동 198
 
4.8%
도화동 144
 
3.5%
숭의동 75
 
1.8%
문학동 63
 
1.5%
학익동 57
 
1.4%
관교동 19
 
0.5%
0 7
 
0.2%
Other values (1309) 1387
33.7%
2023-12-12T09:18:09.367575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3810
 
17.3%
인 967
 
4.4%
미 949
 
4.3%
천 946
 
4.3%
광 945
 
4.3%
시 941
 
4.3%
구 937
 
4.3%
추 936
 
4.3%
홀 936
 
4.3%
역 934
 
4.2%
Other values (297) 9682
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13230
60.2%
Decimal Number 4064
 
18.5%
Space Separator 3810
 
17.3%
Dash Punctuation 839
 
3.8%
Uppercase Letter 19
 
0.1%
Lowercase Letter 9
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Letter Number 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 967
 
7.3%
미 949
 
7.2%
천 946
 
7.2%
광 945
 
7.1%
시 941
 
7.1%
구 937
 
7.1%
추 936
 
7.1%
홀 936
 
7.1%
역 934
 
7.1%
동 871
 
6.6%
Other values (262) 3868
29.2%
Uppercase Letter
ValueCountFrequency (%)
L 4
21.1%
I 3
15.8%
G 2
10.5%
O 2
10.5%
T 2
10.5%
S 1
 
5.3%
Y 1
 
5.3%
C 1
 
5.3%
N 1
 
5.3%
U 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 738
18.2%
2 488
12.0%
3 465
11.4%
4 424
10.4%
5 415
10.2%
6 399
9.8%
8 296
7.3%
9 291
 
7.2%
7 278
 
6.8%
0 270
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
u 1
11.1%
l 1
11.1%
m 1
11.1%
y 1
11.1%
o 1
11.1%
z 1
11.1%
c 1
11.1%
Space Separator
ValueCountFrequency (%)
3810
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 839
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
# 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13230
60.2%
Common 8724
39.7%
Latin 29
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 967
 
7.3%
미 949
 
7.2%
천 946
 
7.2%
광 945
 
7.1%
시 941
 
7.1%
구 937
 
7.1%
추 936
 
7.1%
홀 936
 
7.1%
역 934
 
7.1%
동 871
 
6.6%
Other values (262) 3868
29.2%
Latin
ValueCountFrequency (%)
L 4
 
13.8%
I 3
 
10.3%
G 2
 
6.9%
O 2
 
6.9%
e 2
 
6.9%
T 2
 
6.9%
u 1
 
3.4%
S 1
 
3.4%
l 1
 
3.4%
m 1
 
3.4%
Other values (10) 10
34.5%
Common
ValueCountFrequency (%)
3810
43.7%
- 839
 
9.6%
1 738
 
8.5%
2 488
 
5.6%
3 465
 
5.3%
4 424
 
4.9%
5 415
 
4.8%
6 399
 
4.6%
8 296
 
3.4%
9 291
 
3.3%
Other values (5) 559
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13230
60.2%
ASCII 8752
39.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3810
43.5%
- 839
 
9.6%
1 738
 
8.4%
2 488
 
5.6%
3 465
 
5.3%
4 424
 
4.8%
5 415
 
4.7%
6 399
 
4.6%
8 296
 
3.4%
9 291
 
3.3%
Other values (24) 587
 
6.7%
Hangul
ValueCountFrequency (%)
인 967
 
7.3%
미 949
 
7.2%
천 946
 
7.2%
광 945
 
7.1%
시 941
 
7.1%
구 937
 
7.1%
추 936
 
7.1%
홀 936
 
7.1%
역 934
 
7.1%
동 871
 
6.6%
Other values (262) 3868
29.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

Interactions

2023-12-12T09:18:06.816719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:18:09.461519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관할동
연번1.0000.976
관할동0.9761.000
2023-12-12T09:18:09.549325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관할동
연번1.0000.858
관할동0.8581.000

Missing values

2023-12-12T09:18:07.229551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:18:07.311630image/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.
2023-12-12T09:18:07.386944image/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

연번관할동도로명주소지번주소
01숭의1_3동인천광역시 미추홀구 제물량로24번길 51인천광역시 미추홀구 숭의동 359-1 솔루나
12숭의1_3동인천광역시 미추홀구 제물량로24번길 33인천광역시 미추홀구 숭의동 388-6 새빛타운
23숭의1_3동인천광역시 미추홀구 석정로50번길 12인천광역시 미추홀구 숭의동 162-4 삼성캐슬
34숭의1_3동인천광역시 미추홀구 경인로7번길 45인천광역시 미추홀구 숭의동 161-36
45숭의1_3동인천광역시 미추홀구 석정로64번길 30인천광역시 미추홀구 숭의동 160-73
56숭의1_3동인천광역시 미추홀구 미추로46번길 31-10인천광역시 미추홀구 숭의동 147-54 신한맨션
67숭의1_3동인천광역시 미추홀구 미추로58번길 21인천광역시 미추홀구 숭의동 146-15 나라아트빌
78숭의1_3동인천광역시 미추홀구 미추로64번길 21인천광역시 미추홀구 숭의동 129-13
89숭의1_3동인천광역시 미추홀구 미추로 62-1인천광역시 미추홀구 숭의동 128-16 다인캐슬
910숭의1_3동인천광역시 미추홀구 경인로41번길 3인천광역시 미추홀구 숭의동 148-20 해피드림
연번관할동도로명주소지번주소
884885문학동인천광역시 미추홀구 매소홀로553번길 10인천광역시 미추홀구 문학동 346-11
885886문학동인천광역시 미추홀구 매소홀로541번길 3인천광역시 미추홀구 문학동 342-6
886887문학동인천광역시 미추홀구 매소홀로541번길 33인천광역시 미추홀구 문학동 339-16 가천탑스빌
887888문학동인천광역시 미추홀구 매소홀로535번길 38-22인천광역시 미추홀구 문학동 336-5 우일파크맨션
888889문학동인천광역시 미추홀구 매소홀로535번길 19-1인천광역시 미추홀구 문학동 337-19
889890문학동인천광역시 미추홀구 매소홀로535번길 36인천광역시 미추홀구 문학동 336-1
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891892문학동인천광역시 미추홀구 승학길 22인천광역시 미추홀구 문학동 335-1 호화빌라
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893894문학동인천광역시 미추홀구 승학길 4인천광역시 미추홀구 문학동 337-2 삼마빌딩