Overview

Dataset statistics

Number of variables12
Number of observations259
Missing cells429
Missing cells (%)13.8%
Duplicate rows23
Duplicate rows (%)8.9%
Total size in memory24.9 KiB
Average record size in memory98.5 B

Variable types

Text4
Numeric2
Categorical6

Dataset

Description파일 다운로드
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-21848/F/1/datasetView.do

Alerts

관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 23 (8.9%) duplicate rowsDuplicates
설치장소유형 is highly overall correlated with 수거쓰레기종류High correlation
수거쓰레기종류 is highly overall correlated with 설치장소유형 and 1 other fieldsHigh correlation
쓰레기통형태 is highly overall correlated with 수거쓰레기종류High correlation
쓰레기통형태 is highly imbalanced (69.2%)Imbalance
소재지도로명주소 has 29 (11.2%) missing valuesMissing
소재지지번주소 has 63 (24.3%) missing valuesMissing
상세위치 has 189 (73.0%) missing valuesMissing
위도 has 74 (28.6%) missing valuesMissing
경도 has 74 (28.6%) missing valuesMissing

Reproduction

Analysis started2023-12-11 05:29:19.710297
Analysis finished2023-12-11 05:29:20.997059
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소재지도로명
Text

Distinct54
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-11T14:29:21.191073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.1583012
Min length3

Characters and Unicode

Total characters1077
Distinct characters59
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)7.3%

Sample

1st row구로동로
2nd row구로동로
3rd row구로동로
4th row남부순환로
5th row남부순환로105길
ValueCountFrequency (%)
경인로 34
 
13.1%
구로동로 29
 
11.2%
가마산로 21
 
8.1%
고척로 13
 
5.0%
구로중앙로 13
 
5.0%
우마길 12
 
4.6%
신도림로 12
 
4.6%
새말로 9
 
3.5%
개봉로 8
 
3.1%
부일로 7
 
2.7%
Other values (43) 101
39.0%
2023-12-11T14:29:21.668973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 291
27.0%
길 61
 
5.7%
구 49
 
4.5%
경 41
 
3.8%
인 41
 
3.8%
마 35
 
3.2%
동 32
 
3.0%
가 26
 
2.4%
산 23
 
2.1%
부 21
 
1.9%
Other values (49) 457
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 982
91.2%
Decimal Number 94
 
8.7%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 291
29.6%
길 61
 
6.2%
구 49
 
5.0%
경 41
 
4.2%
인 41
 
4.2%
마 35
 
3.6%
동 32
 
3.3%
가 26
 
2.6%
산 23
 
2.3%
부 21
 
2.1%
Other values (38) 362
36.9%
Decimal Number
ValueCountFrequency (%)
2 20
21.3%
3 18
19.1%
1 15
16.0%
0 10
10.6%
5 10
10.6%
7 8
 
8.5%
9 5
 
5.3%
6 3
 
3.2%
8 3
 
3.2%
4 2
 
2.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 982
91.2%
Common 95
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 291
29.6%
길 61
 
6.2%
구 49
 
5.0%
경 41
 
4.2%
인 41
 
4.2%
마 35
 
3.6%
동 32
 
3.3%
가 26
 
2.6%
산 23
 
2.3%
부 21
 
2.1%
Other values (38) 362
36.9%
Common
ValueCountFrequency (%)
2 20
21.1%
3 18
18.9%
1 15
15.8%
0 10
10.5%
5 10
10.5%
7 8
 
8.4%
9 5
 
5.3%
6 3
 
3.2%
8 3
 
3.2%
4 2
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 982
91.2%
ASCII 95
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 291
29.6%
길 61
 
6.2%
구 49
 
5.0%
경 41
 
4.2%
인 41
 
4.2%
마 35
 
3.6%
동 32
 
3.3%
가 26
 
2.6%
산 23
 
2.3%
부 21
 
2.1%
Other values (38) 362
36.9%
ASCII
ValueCountFrequency (%)
2 20
21.1%
3 18
18.9%
1 15
15.8%
0 10
10.5%
5 10
10.5%
7 8
 
8.4%
9 5
 
5.3%
6 3
 
3.2%
8 3
 
3.2%
4 2
 
2.1%

소재지도로명주소
Text

MISSING 

Distinct168
Distinct (%)73.0%
Missing29
Missing (%)11.2%
Memory size2.2 KiB
2023-12-11T14:29:22.103435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length17.943478
Min length13

Characters and Unicode

Total characters4127
Distinct characters61
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)53.0%

Sample

1st row서울특별시 구로구 구로동로 13
2nd row서울특별시 구로구 구로동로 25
3rd row서울특별시 구로구 구로동로 31
4th row서울특별시 구로구 남부순환로 1295
5th row서울특별시 구로구 남부순환로105길 76
ValueCountFrequency (%)
서울특별시 230
25.3%
구로구 230
25.3%
구로동로 28
 
3.1%
경인로 21
 
2.3%
가마산로 21
 
2.3%
고척로 13
 
1.4%
신도림로 11
 
1.2%
구로중앙로 10
 
1.1%
개봉로 8
 
0.9%
우마길 6
 
0.7%
Other values (191) 332
36.5%
2023-12-11T14:29:22.700557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
680
16.5%
구 512
12.4%
로 486
11.8%
시 234
 
5.7%
서 231
 
5.6%
특 230
 
5.6%
별 230
 
5.6%
울 230
 
5.6%
1 131
 
3.2%
2 112
 
2.7%
Other values (51) 1051
25.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2726
66.1%
Decimal Number 693
 
16.8%
Space Separator 680
 
16.5%
Dash Punctuation 28
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 512
18.8%
로 486
17.8%
시 234
8.6%
서 231
8.5%
특 230
8.4%
별 230
8.4%
울 230
8.4%
길 64
 
2.3%
동 38
 
1.4%
마 35
 
1.3%
Other values (39) 436
16.0%
Decimal Number
ValueCountFrequency (%)
1 131
18.9%
2 112
16.2%
3 79
11.4%
5 72
10.4%
6 64
9.2%
4 58
8.4%
7 57
8.2%
0 50
 
7.2%
9 36
 
5.2%
8 34
 
4.9%
Space Separator
ValueCountFrequency (%)
680
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2726
66.1%
Common 1401
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 512
18.8%
로 486
17.8%
시 234
8.6%
서 231
8.5%
특 230
8.4%
별 230
8.4%
울 230
8.4%
길 64
 
2.3%
동 38
 
1.4%
마 35
 
1.3%
Other values (39) 436
16.0%
Common
ValueCountFrequency (%)
680
48.5%
1 131
 
9.4%
2 112
 
8.0%
3 79
 
5.6%
5 72
 
5.1%
6 64
 
4.6%
4 58
 
4.1%
7 57
 
4.1%
0 50
 
3.6%
9 36
 
2.6%
Other values (2) 62
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2726
66.1%
ASCII 1401
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
680
48.5%
1 131
 
9.4%
2 112
 
8.0%
3 79
 
5.6%
5 72
 
5.1%
6 64
 
4.6%
4 58
 
4.1%
7 57
 
4.1%
0 50
 
3.6%
9 36
 
2.6%
Other values (2) 62
 
4.4%
Hangul
ValueCountFrequency (%)
구 512
18.8%
로 486
17.8%
시 234
8.6%
서 231
8.5%
특 230
8.4%
별 230
8.4%
울 230
8.4%
길 64
 
2.3%
동 38
 
1.4%
마 35
 
1.3%
Other values (39) 436
16.0%

소재지지번주소
Text

MISSING 

Distinct145
Distinct (%)74.0%
Missing63
Missing (%)24.3%
Memory size2.2 KiB
2023-12-11T14:29:23.150398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length19.117347
Min length16

Characters and Unicode

Total characters3747
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)54.1%

Sample

1st row서울특별시 구로구 가리봉동 121-30
2nd row서울특별시 구로구 가리봉동 88-18
3rd row서울특별시 구로구 가리봉동 25-51
4th row서울특별시 구로구 가리봉동 137-4
5th row서울특별시 구로구 가리봉동 125-16
ValueCountFrequency (%)
서울특별시 196
25.0%
구로구 196
25.0%
구로동 103
13.1%
개봉동 26
 
3.3%
신도림동 14
 
1.8%
오류동 13
 
1.7%
가리봉동 12
 
1.5%
궁동 8
 
1.0%
항동 8
 
1.0%
83-4 5
 
0.6%
Other values (147) 203
25.9%
2023-12-11T14:29:23.818499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
588
15.7%
구 495
13.2%
로 299
 
8.0%
서 196
 
5.2%
특 196
 
5.2%
별 196
 
5.2%
시 196
 
5.2%
동 196
 
5.2%
울 196
 
5.2%
1 168
 
4.5%
Other values (27) 1021
27.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2166
57.8%
Decimal Number 828
 
22.1%
Space Separator 588
 
15.7%
Dash Punctuation 165
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 495
22.9%
로 299
13.8%
서 196
 
9.0%
특 196
 
9.0%
별 196
 
9.0%
시 196
 
9.0%
동 196
 
9.0%
울 196
 
9.0%
봉 38
 
1.8%
개 26
 
1.2%
Other values (15) 132
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 168
20.3%
4 100
12.1%
3 94
11.4%
2 85
10.3%
0 82
9.9%
8 69
8.3%
6 64
 
7.7%
5 57
 
6.9%
9 55
 
6.6%
7 54
 
6.5%
Space Separator
ValueCountFrequency (%)
588
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 165
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2166
57.8%
Common 1581
42.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 495
22.9%
로 299
13.8%
서 196
 
9.0%
특 196
 
9.0%
별 196
 
9.0%
시 196
 
9.0%
동 196
 
9.0%
울 196
 
9.0%
봉 38
 
1.8%
개 26
 
1.2%
Other values (15) 132
 
6.1%
Common
ValueCountFrequency (%)
588
37.2%
1 168
 
10.6%
- 165
 
10.4%
4 100
 
6.3%
3 94
 
5.9%
2 85
 
5.4%
0 82
 
5.2%
8 69
 
4.4%
6 64
 
4.0%
5 57
 
3.6%
Other values (2) 109
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2166
57.8%
ASCII 1581
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
588
37.2%
1 168
 
10.6%
- 165
 
10.4%
4 100
 
6.3%
3 94
 
5.9%
2 85
 
5.4%
0 82
 
5.2%
8 69
 
4.4%
6 64
 
4.0%
5 57
 
3.6%
Other values (2) 109
 
6.9%
Hangul
ValueCountFrequency (%)
구 495
22.9%
로 299
13.8%
서 196
 
9.0%
특 196
 
9.0%
별 196
 
9.0%
시 196
 
9.0%
동 196
 
9.0%
울 196
 
9.0%
봉 38
 
1.8%
개 26
 
1.2%
Other values (15) 132
 
6.1%

상세위치
Text

MISSING 

Distinct52
Distinct (%)74.3%
Missing189
Missing (%)73.0%
Memory size2.2 KiB
2023-12-11T14:29:24.096989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.9714286
Min length1

Characters and Unicode

Total characters558
Distinct characters148
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

Unique39 ?
Unique (%)55.7%

Sample

1st row개봉1동사거리 버스정류장
2nd row개봉푸르지오 정문
3rd row삼호아파트 102동 앞
4th row임괄아파트 2동 앞
5th row현대연예인아파트 입구
ValueCountFrequency (%)
앞 19
 
18.1%
버스 6
 
5.7%
횡단보도 3
 
2.9%
맞은편 3
 
2.9%
입구 2
 
1.9%
버스전용차로-17005 2
 
1.9%
버스전용차로-17006 2
 
1.9%
파리바게트 2
 
1.9%
503동 2
 
1.9%
대림12차아파트 2
 
1.9%
Other values (53) 62
59.0%
2023-12-11T14:29:24.522683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
6.3%
0 30
 
5.4%
1 21
 
3.8%
버 20
 
3.6%
스 20
 
3.6%
앞 20
 
3.6%
차 18
 
3.2%
아 15
 
2.7%
로 15
 
2.7%
파 15
 
2.7%
Other values (138) 349
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 409
73.3%
Decimal Number 91
 
16.3%
Space Separator 35
 
6.3%
Dash Punctuation 12
 
2.2%
Open Punctuation 4
 
0.7%
Close Punctuation 4
 
0.7%
Uppercase Letter 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
버 20
 
4.9%
스 20
 
4.9%
앞 20
 
4.9%
차 18
 
4.4%
아 15
 
3.7%
로 15
 
3.7%
파 15
 
3.7%
트 13
 
3.2%
전 13
 
3.2%
용 12
 
2.9%
Other values (125) 248
60.6%
Decimal Number
ValueCountFrequency (%)
0 30
33.0%
1 21
23.1%
7 12
 
13.2%
2 10
 
11.0%
3 8
 
8.8%
6 4
 
4.4%
5 4
 
4.4%
4 2
 
2.2%
Space Separator
ValueCountFrequency (%)
35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 409
73.3%
Common 146
 
26.2%
Latin 3
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
버 20
 
4.9%
스 20
 
4.9%
앞 20
 
4.9%
차 18
 
4.4%
아 15
 
3.7%
로 15
 
3.7%
파 15
 
3.7%
트 13
 
3.2%
전 13
 
3.2%
용 12
 
2.9%
Other values (125) 248
60.6%
Common
ValueCountFrequency (%)
35
24.0%
0 30
20.5%
1 21
14.4%
- 12
 
8.2%
7 12
 
8.2%
2 10
 
6.8%
3 8
 
5.5%
( 4
 
2.7%
6 4
 
2.7%
5 4
 
2.7%
Other values (2) 6
 
4.1%
Latin
ValueCountFrequency (%)
A 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 409
73.3%
ASCII 149
 
26.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
23.5%
0 30
20.1%
1 21
14.1%
- 12
 
8.1%
7 12
 
8.1%
2 10
 
6.7%
3 8
 
5.4%
( 4
 
2.7%
6 4
 
2.7%
5 4
 
2.7%
Other values (3) 9
 
6.0%
Hangul
ValueCountFrequency (%)
버 20
 
4.9%
스 20
 
4.9%
앞 20
 
4.9%
차 18
 
4.4%
아 15
 
3.7%
로 15
 
3.7%
파 15
 
3.7%
트 13
 
3.2%
전 13
 
3.2%
용 12
 
2.9%
Other values (125) 248
60.6%

위도
Real number (ℝ)

MISSING 

Distinct133
Distinct (%)71.9%
Missing74
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean37.493796
Minimum37.479118
Maximum37.509924
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T14:29:24.706831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.479118
5-th percentile37.482987
Q137.488253
median37.493891
Q337.498134
95-th percentile37.507068
Maximum37.509924
Range0.03080576
Interquartile range (IQR)0.00988116

Descriptive statistics

Standard deviation0.0071327388
Coefficient of variation (CV)0.00019023784
Kurtosis-0.55426314
Mean37.493796
Median Absolute Deviation (MAD)0.00516558
Skewness0.14440435
Sum6936.3522
Variance5.0875963 × 10-5
MonotonicityNot monotonic
2023-12-11T14:29:24.879066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.49481403 5
 
1.9%
37.50116014 4
 
1.5%
37.49586031 4
 
1.5%
37.50777999 3
 
1.2%
37.49246153 3
 
1.2%
37.4851606 3
 
1.2%
37.48484996 3
 
1.2%
37.48662187 3
 
1.2%
37.4938915 2
 
0.8%
37.48353325 2
 
0.8%
Other values (123) 153
59.1%
(Missing) 74
28.6%
ValueCountFrequency (%)
37.47911835 1
0.4%
37.48016123 1
0.4%
37.48035893 1
0.4%
37.48076327 1
0.4%
37.48161059 1
0.4%
37.48196844 1
0.4%
37.48217645 2
0.8%
37.48289633 1
0.4%
37.48298724 2
0.8%
37.48339166 2
0.8%
ValueCountFrequency (%)
37.50992411 1
 
0.4%
37.50938921 1
 
0.4%
37.50907721 1
 
0.4%
37.50839683 1
 
0.4%
37.50777999 3
1.2%
37.5074418 1
 
0.4%
37.50727521 2
0.8%
37.50623763 1
 
0.4%
37.50559462 2
0.8%
37.50547022 2
0.8%

경도
Real number (ℝ)

MISSING 

Distinct133
Distinct (%)71.9%
Missing74
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean126.87365
Minimum126.82219
Maximum126.90142
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T14:29:25.056877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.82219
5-th percentile126.83148
Q1126.85671
median126.88287
Q3126.88868
95-th percentile126.8958
Maximum126.90142
Range0.0792381
Interquartile range (IQR)0.0319643

Descriptive statistics

Standard deviation0.021180329
Coefficient of variation (CV)0.00016694033
Kurtosis-0.34027375
Mean126.87365
Median Absolute Deviation (MAD)0.0065305
Skewness-0.97513725
Sum23471.625
Variance0.00044860636
MonotonicityNot monotonic
2023-12-11T14:29:25.231468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8886765 5
 
1.9%
126.882773 4
 
1.5%
126.8888073 4
 
1.5%
126.8805952 3
 
1.2%
126.8409746 3
 
1.2%
126.8867371 3
 
1.2%
126.8865766 3
 
1.2%
126.8567122 3
 
1.2%
126.8314768 2
 
0.8%
126.899752 2
 
0.8%
Other values (123) 153
59.1%
(Missing) 74
28.6%
ValueCountFrequency (%)
126.8221862 1
0.4%
126.822945 1
0.4%
126.823542 2
0.8%
126.823634 1
0.4%
126.8236695 1
0.4%
126.8289553 1
0.4%
126.8292071 1
0.4%
126.8299962 1
0.4%
126.8314768 2
0.8%
126.8327262 1
0.4%
ValueCountFrequency (%)
126.9014243 2
0.8%
126.9011985 1
0.4%
126.9010446 2
0.8%
126.9003821 1
0.4%
126.899752 2
0.8%
126.8983387 1
0.4%
126.8958922 1
0.4%
126.8954329 1
0.4%
126.8948323 1
0.4%
126.8941033 1
0.4%

설치장소유형
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
도로변(횡단보도 포함)
163 
정류소(버스, 택시 등)
74 
상가지역
 
16
광장, 공원 등 다중집합장소
 
4
지하철역 입구
 
2

Length

Max length15
Median length12
Mean length11.799228
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row도로변(횡단보도 포함)
2nd row정류소(버스, 택시 등)
3rd row지하철역 입구
4th row정류소(버스, 택시 등)
5th row정류소(버스, 택시 등)

Common Values

ValueCountFrequency (%)
도로변(횡단보도 포함) 163
62.9%
정류소(버스, 택시 등) 74
28.6%
상가지역 16
 
6.2%
광장, 공원 등 다중집합장소 4
 
1.5%
지하철역 입구 2
 
0.8%

Length

2023-12-11T14:29:25.393348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:29:25.496022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도로변(횡단보도 163
27.9%
포함 163
27.9%
등 78
13.4%
정류소(버스 74
12.7%
택시 74
12.7%
상가지역 16
 
2.7%
광장 4
 
0.7%
공원 4
 
0.7%
다중집합장소 4
 
0.7%
지하철역 2
 
0.3%

수거쓰레기종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
일반쓰레기
125 
재활용
120 
담배꽁초
14 

Length

Max length5
Median length4
Mean length4.019305
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반쓰레기
2nd row일반쓰레기
3rd row일반쓰레기
4th row일반쓰레기
5th row재활용

Common Values

ValueCountFrequency (%)
일반쓰레기 125
48.3%
재활용 120
46.3%
담배꽁초 14
 
5.4%

Length

2023-12-11T14:29:25.650913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:29:25.766775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반쓰레기 125
48.3%
재활용 120
46.3%
담배꽁초 14
 
5.4%

쓰레기통형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
일반 사각 쓰레기통
228 
담배꽁초 수거함
 
14
항아리형 쓰레기통
 
13
IoT태양광 압축 쓰레기통
 
2
원통형 쓰레기통
 
2

Length

Max length14
Median length10
Mean length9.8571429
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반 사각 쓰레기통
2nd row일반 사각 쓰레기통
3rd row일반 사각 쓰레기통
4th row일반 사각 쓰레기통
5th row일반 사각 쓰레기통

Common Values

ValueCountFrequency (%)
일반 사각 쓰레기통 228
88.0%
담배꽁초 수거함 14
 
5.4%
항아리형 쓰레기통 13
 
5.0%
IoT태양광 압축 쓰레기통 2
 
0.8%
원통형 쓰레기통 2
 
0.8%

Length

2023-12-11T14:29:25.863174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:29:26.321028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
쓰레기통 245
32.8%
일반 228
30.5%
사각 228
30.5%
담배꽁초 14
 
1.9%
수거함 14
 
1.9%
항아리형 13
 
1.7%
iot태양광 2
 
0.3%
압축 2
 
0.3%
원통형 2
 
0.3%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
구로구청 청소행정과
259 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row구로구청 청소행정과
2nd row구로구청 청소행정과
3rd row구로구청 청소행정과
4th row구로구청 청소행정과
5th row구로구청 청소행정과

Common Values

ValueCountFrequency (%)
구로구청 청소행정과 259
100.0%

Length

2023-12-11T14:29:26.450635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:29:26.554603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구로구청 259
50.0%
청소행정과 259
50.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
02-860-2918
259 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row02-860-2918
2nd row02-860-2918
3rd row02-860-2918
4th row02-860-2918
5th row02-860-2918

Common Values

ValueCountFrequency (%)
02-860-2918 259
100.0%

Length

2023-12-11T14:29:26.669523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:29:26.762962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02-860-2918 259
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-03-31
259 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-31
2nd row2023-03-31
3rd row2023-03-31
4th row2023-03-31
5th row2023-03-31

Common Values

ValueCountFrequency (%)
2023-03-31 259
100.0%

Length

2023-12-11T14:29:26.882797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:29:26.987033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-31 259
100.0%

Interactions

2023-12-11T14:29:20.320236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:29:20.153842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:29:20.416104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:29:20.229587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T14:29:27.071911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지도로명상세위치위도경도설치장소유형수거쓰레기종류쓰레기통형태
소재지도로명1.0000.9720.9030.9680.8560.9220.651
상세위치0.9721.0000.9400.9720.9880.8450.716
위도0.9030.9401.0000.5810.3110.2100.330
경도0.9680.9720.5811.0000.3050.1630.106
설치장소유형0.8560.9880.3110.3051.0000.6830.833
수거쓰레기종류0.9220.8450.2100.1630.6831.0000.728
쓰레기통형태0.6510.7160.3300.1060.8330.7281.000
2023-12-11T14:29:27.213983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
쓰레기통형태수거쓰레기종류설치장소유형
쓰레기통형태1.0000.7180.463
수거쓰레기종류0.7181.0000.657
설치장소유형0.4630.6571.000
2023-12-11T14:29:27.322277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설치장소유형수거쓰레기종류쓰레기통형태
위도1.000-0.2720.1310.1570.205
경도-0.2721.0000.1790.1590.043
설치장소유형0.1310.1791.0000.6570.463
수거쓰레기종류0.1570.1590.6571.0000.718
쓰레기통형태0.2050.0430.4630.7181.000

Missing values

2023-12-11T14:29:20.565937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T14:29:20.783543image/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.
2023-12-11T14:29:20.916077image/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

소재지도로명소재지도로명주소소재지지번주소상세위치위도경도설치장소유형수거쓰레기종류쓰레기통형태관리기관명관리기관전화번호데이터기준일자
0구로동로서울특별시 구로구 구로동로 13서울특별시 구로구 가리봉동 121-30<NA>37.482896126.886887도로변(횡단보도 포함)일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
1구로동로서울특별시 구로구 구로동로 25서울특별시 구로구 가리봉동 88-18<NA>37.483873126.886325정류소(버스, 택시 등)일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
2구로동로서울특별시 구로구 구로동로 31서울특별시 구로구 가리봉동 25-51<NA>37.48444126.885991지하철역 입구일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
3남부순환로서울특별시 구로구 남부순환로 1295서울특별시 구로구 가리봉동 137-4<NA>37.479118126.894832정류소(버스, 택시 등)일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
4남부순환로105길서울특별시 구로구 남부순환로105길 76서울특별시 구로구 가리봉동 125-16<NA>37.480161126.888695정류소(버스, 택시 등)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
5남부순환로105길서울특별시 구로구 남부순환로105길 134서울특별시 구로구 가리봉동 121-44<NA>37.482176126.886722도로변(횡단보도 포함)일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
6남부순환로105길서울특별시 구로구 남부순환로105길 134서울특별시 구로구 가리봉동 121-44<NA>37.482176126.886722도로변(횡단보도 포함)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
7디지털로서울특별시 구로구 디지털로 226서울특별시 구로구 가리봉동 134-114<NA>37.480359126.891423도로변(횡단보도 포함)일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
8디지털로서울특별시 구로구 디지털로 231서울특별시 구로구 가리봉동 131-11<NA>37.480763126.891283도로변(횡단보도 포함)일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
9디지털로27길서울특별시 구로구 디지털로27길 135서울특별시 구로구 가리봉동 89-99<NA>37.48485126.886577도로변(횡단보도 포함)일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
소재지도로명소재지도로명주소소재지지번주소상세위치위도경도설치장소유형수거쓰레기종류쓰레기통형태관리기관명관리기관전화번호데이터기준일자
249서해안로<NA>서울특별시 구로구 오류동 332-36<NA><NA><NA>광장, 공원 등 다중집합장소일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
250오류로<NA>서울특별시 구로구 오류동 169-3<NA><NA><NA>정류소(버스, 택시 등)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
251서해안로<NA>서울특별시 구로구 항동 115-2<NA><NA><NA>도로변(횡단보도 포함)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
252서해안로<NA>서울특별시 구로구 항동 113-5<NA><NA><NA>도로변(횡단보도 포함)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
253서해안로<NA>서울특별시 구로구 항동 82-7<NA><NA><NA>정류소(버스, 택시 등)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
254서해안로<NA>서울특별시 구로구 항동 88-2<NA><NA><NA>정류소(버스, 택시 등)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
255서해안로<NA>서울특별시 구로구 항동 204-2<NA><NA><NA>정류소(버스, 택시 등)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
256연동로<NA>서울특별시 구로구 항동 169-1<NA><NA><NA>도로변(횡단보도 포함)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
257연동로<NA>서울특별시 구로구 항동 100-14<NA><NA><NA>정류소(버스, 택시 등)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31
258연동로서울특별시 구로구 연동로 240서울특별시 구로구 항동 9-1<NA>37.481968126.823669정류소(버스, 택시 등)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-31

Duplicate rows

Most frequently occurring

소재지도로명소재지도로명주소소재지지번주소상세위치위도경도설치장소유형수거쓰레기종류쓰레기통형태관리기관명관리기관전화번호데이터기준일자# duplicates
1가마산로서울특별시 구로구 가마산로 250서울특별시 구로구 구로동 83-4<NA>37.494814126.888677도로변(횡단보도 포함)일반쓰레기항아리형 쓰레기통구로구청 청소행정과02-860-29182023-03-314
20신도림로서울특별시 구로구 신도림로 40서울특별시 구로구 신도림동 390-68<NA>37.50778126.880595도로변(횡단보도 포함)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-313
0가마산로서울특별시 구로구 가마산로 218서울특별시 구로구 구로동 80-24<NA>37.493216126.885141정류소(버스, 택시 등)일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-312
2가마산로서울특별시 구로구 가마산로 283서울특별시 구로구 구로동 104-9<NA>37.496905126.891385도로변(횡단보도 포함)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-312
3개봉로서울특별시 구로구 개봉로 10서울특별시 구로구 개봉동 403-196<NA>37.486622126.856712도로변(횡단보도 포함)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-312
4경인로서울특별시 구로구 경인로 445<NA><NA><NA><NA>도로변(횡단보도 포함)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-312
5경인로<NA><NA>버스전용차로-17004<NA><NA>정류소(버스, 택시 등)일반쓰레기항아리형 쓰레기통구로구청 청소행정과02-860-29182023-03-312
6경인로67길서울특별시 구로구 신도림동 329-2<NA>아이파크아파트 맞은편<NA><NA>도로변(횡단보도 포함)일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-312
7구로동로서울특별시 구로구 구로동로 124서울특별시 구로구 구로동 732-3<NA>37.489632126.884536도로변(횡단보도 포함)일반쓰레기일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-312
8구로동로서울특별시 구로구 구로동로 203서울특별시 구로구 구로동 481-7<NA>37.496719126.88227도로변(횡단보도 포함)재활용일반 사각 쓰레기통구로구청 청소행정과02-860-29182023-03-312