Overview

Dataset statistics

Number of variables7
Number of observations193
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.9 KiB
Average record size in memory57.7 B

Variable types

Numeric1
Categorical3
Text2
DateTime1

Dataset

Description서울특별시 동작구 음식물류폐기문 다량배출사업장에는 관리기관명(동작구청), 상호, 사업장 도로명주소, 수거형태 등의 데이터가 포함되어 있습니다.
Author서울특별시 동작구
URLhttps://www.data.go.kr/data/15100504/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
수거형태 is highly imbalanced (91.7%)Imbalance
연번 has unique valuesUnique
상호 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:07:21.904633
Analysis finished2024-04-21 02:07:23.800684
Duration1.9 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct193
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97
Minimum1
Maximum193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T11:07:23.899960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.6
Q149
median97
Q3145
95-th percentile183.4
Maximum193
Range192
Interquartile range (IQR)96

Descriptive statistics

Standard deviation55.858452
Coefficient of variation (CV)0.57586033
Kurtosis-1.2
Mean97
Median Absolute Deviation (MAD)48
Skewness0
Sum18721
Variance3120.1667
MonotonicityStrictly increasing
2024-04-21T11:07:24.028447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
146 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
Other values (183) 183
94.8%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
동작구청
193 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동작구청 193
100.0%

Length

2024-04-21T11:07:24.159932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:07:24.262955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동작구청 193
100.0%

사업장구분
Categorical

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
일반음식점
94 
집단급식소
84 
휴게음식점
14 
농수산물시장
 
1

Length

Max length6
Median length5
Mean length5.0051813
Min length5

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row집단급식소
2nd row일반음식점
3rd row일반음식점
4th row일반음식점
5th row일반음식점

Common Values

ValueCountFrequency (%)
일반음식점 94
48.7%
집단급식소 84
43.5%
휴게음식점 14
 
7.3%
농수산물시장 1
 
0.5%

Length

2024-04-21T11:07:24.352245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:07:24.449265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 94
48.7%
집단급식소 84
43.5%
휴게음식점 14
 
7.3%
농수산물시장 1
 
0.5%

상호
Text

UNIQUE 

Distinct193
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-21T11:07:24.639026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length7.9740933
Min length2

Characters and Unicode

Total characters1539
Distinct characters293
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

Unique193 ?
Unique (%)100.0%

Sample

1st row흑석어린이집
2nd row한우천국
3rd row성민촌 상도점
4th row(주)커피빈코리아
5th row주식회사 마이맘이
ValueCountFrequency (%)
스타벅스 5
 
1.9%
상도점 3
 
1.1%
주식회사 3
 
1.1%
주)스타벅스커피코리아 3
 
1.1%
하이미트 3
 
1.1%
중앙대학교 3
 
1.1%
노량진 2
 
0.7%
구내식당 2
 
0.7%
만남의집 2
 
0.7%
버거킹 2
 
0.7%
Other values (229) 240
89.6%
2024-04-21T11:07:24.976904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
4.9%
학 52
 
3.4%
교 48
 
3.1%
점 40
 
2.6%
이 36
 
2.3%
스 34
 
2.2%
등 30
 
1.9%
대 30
 
1.9%
서 26
 
1.7%
) 26
 
1.7%
Other values (283) 1142
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1380
89.7%
Space Separator 75
 
4.9%
Close Punctuation 26
 
1.7%
Open Punctuation 26
 
1.7%
Decimal Number 13
 
0.8%
Uppercase Letter 11
 
0.7%
Lowercase Letter 8
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 52
 
3.8%
교 48
 
3.5%
점 40
 
2.9%
이 36
 
2.6%
스 34
 
2.5%
등 30
 
2.2%
대 30
 
2.2%
서 26
 
1.9%
주 25
 
1.8%
원 23
 
1.7%
Other values (259) 1036
75.1%
Decimal Number
ValueCountFrequency (%)
0 4
30.8%
9 2
15.4%
1 2
15.4%
6 1
 
7.7%
7 1
 
7.7%
5 1
 
7.7%
2 1
 
7.7%
3 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
27.3%
I 2
18.2%
K 2
18.2%
R 1
 
9.1%
X 1
 
9.1%
T 1
 
9.1%
D 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
h 2
25.0%
k 1
12.5%
c 1
12.5%
f 1
12.5%
t 1
12.5%
Space Separator
ValueCountFrequency (%)
75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1380
89.7%
Common 140
 
9.1%
Latin 19
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 52
 
3.8%
교 48
 
3.5%
점 40
 
2.9%
이 36
 
2.6%
스 34
 
2.5%
등 30
 
2.2%
대 30
 
2.2%
서 26
 
1.9%
주 25
 
1.8%
원 23
 
1.7%
Other values (259) 1036
75.1%
Latin
ValueCountFrequency (%)
S 3
15.8%
I 2
10.5%
K 2
10.5%
e 2
10.5%
h 2
10.5%
R 1
 
5.3%
X 1
 
5.3%
T 1
 
5.3%
k 1
 
5.3%
c 1
 
5.3%
Other values (3) 3
15.8%
Common
ValueCountFrequency (%)
75
53.6%
) 26
 
18.6%
( 26
 
18.6%
0 4
 
2.9%
9 2
 
1.4%
1 2
 
1.4%
6 1
 
0.7%
7 1
 
0.7%
5 1
 
0.7%
2 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1380
89.7%
ASCII 159
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
47.2%
) 26
 
16.4%
( 26
 
16.4%
0 4
 
2.5%
S 3
 
1.9%
I 2
 
1.3%
K 2
 
1.3%
e 2
 
1.3%
h 2
 
1.3%
9 2
 
1.3%
Other values (14) 15
 
9.4%
Hangul
ValueCountFrequency (%)
학 52
 
3.8%
교 48
 
3.5%
점 40
 
2.9%
이 36
 
2.6%
스 34
 
2.5%
등 30
 
2.2%
대 30
 
2.2%
서 26
 
1.9%
주 25
 
1.8%
원 23
 
1.7%
Other values (259) 1036
75.1%

사업장도로명주소
Text

Distinct178
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-21T11:07:25.187663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length31.621762
Min length18

Characters and Unicode

Total characters6103
Distinct characters234
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)85.0%

Sample

1st row서울특별시 동작구 서달로4길 46 (흑석동_ 흑석어린이집)
2nd row서울특별시 영등포구 여의대방로 115 (신길동)
3rd row서울특별시 동작구 매봉로 13 (상도1동_ 상도타운)
4th row서울특별시 동작구 보라매로5길 35 (신대방동_ 한국컴퓨터빌딩_보라매현대APT)
5th row서울특별시 동작구 신대방1가길 38_ 지하1층 (신대방동_ 동작상떼빌아파트)
ValueCountFrequency (%)
서울특별시 193
 
16.9%
동작구 192
 
16.8%
사당동 49
 
4.3%
신대방동 31
 
2.7%
상도동 28
 
2.4%
대방동 28
 
2.4%
노량진동 24
 
2.1%
노량진로 15
 
1.3%
흑석동 14
 
1.2%
보라매로5길 11
 
1.0%
Other values (322) 558
48.8%
2024-04-21T11:07:25.662985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
957
 
15.7%
동 436
 
7.1%
작 233
 
3.8%
서 214
 
3.5%
울 206
 
3.4%
시 205
 
3.4%
특 197
 
3.2%
별 197
 
3.2%
구 197
 
3.2%
( 192
 
3.1%
Other values (224) 3069
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3898
63.9%
Space Separator 957
 
15.7%
Decimal Number 649
 
10.6%
Open Punctuation 192
 
3.1%
Close Punctuation 192
 
3.1%
Connector Punctuation 167
 
2.7%
Uppercase Letter 27
 
0.4%
Dash Punctuation 11
 
0.2%
Lowercase Letter 8
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 436
 
11.2%
작 233
 
6.0%
서 214
 
5.5%
울 206
 
5.3%
시 205
 
5.3%
특 197
 
5.1%
별 197
 
5.1%
구 197
 
5.1%
로 181
 
4.6%
대 144
 
3.7%
Other values (190) 1688
43.3%
Decimal Number
ValueCountFrequency (%)
1 161
24.8%
2 96
14.8%
3 76
11.7%
4 69
10.6%
5 65
10.0%
6 50
 
7.7%
0 45
 
6.9%
7 37
 
5.7%
9 25
 
3.9%
8 25
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
T 6
22.2%
A 6
22.2%
P 5
18.5%
B 3
11.1%
V 2
 
7.4%
S 2
 
7.4%
K 1
 
3.7%
D 1
 
3.7%
I 1
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
j 1
12.5%
g 1
12.5%
n 1
12.5%
o 1
12.5%
k 1
12.5%
a 1
12.5%
s 1
12.5%
t 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
/ 1
50.0%
Space Separator
ValueCountFrequency (%)
957
100.0%
Open Punctuation
ValueCountFrequency (%)
( 192
100.0%
Close Punctuation
ValueCountFrequency (%)
) 192
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3898
63.9%
Common 2170
35.6%
Latin 35
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 436
 
11.2%
작 233
 
6.0%
서 214
 
5.5%
울 206
 
5.3%
시 205
 
5.3%
특 197
 
5.1%
별 197
 
5.1%
구 197
 
5.1%
로 181
 
4.6%
대 144
 
3.7%
Other values (190) 1688
43.3%
Common
ValueCountFrequency (%)
957
44.1%
( 192
 
8.8%
) 192
 
8.8%
_ 167
 
7.7%
1 161
 
7.4%
2 96
 
4.4%
3 76
 
3.5%
4 69
 
3.2%
5 65
 
3.0%
6 50
 
2.3%
Other values (7) 145
 
6.7%
Latin
ValueCountFrequency (%)
T 6
17.1%
A 6
17.1%
P 5
14.3%
B 3
8.6%
V 2
 
5.7%
S 2
 
5.7%
K 1
 
2.9%
j 1
 
2.9%
g 1
 
2.9%
n 1
 
2.9%
Other values (7) 7
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3898
63.9%
ASCII 2205
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
957
43.4%
( 192
 
8.7%
) 192
 
8.7%
_ 167
 
7.6%
1 161
 
7.3%
2 96
 
4.4%
3 76
 
3.4%
4 69
 
3.1%
5 65
 
2.9%
6 50
 
2.3%
Other values (24) 180
 
8.2%
Hangul
ValueCountFrequency (%)
동 436
 
11.2%
작 233
 
6.0%
서 214
 
5.5%
울 206
 
5.3%
시 205
 
5.3%
특 197
 
5.1%
별 197
 
5.1%
구 197
 
5.1%
로 181
 
4.6%
대 144
 
3.7%
Other values (190) 1688
43.3%

수거형태
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
위탁처리
191 
자가처리
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁처리 191
99.0%
자가처리 2
 
1.0%

Length

2024-04-21T11:07:25.817525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:07:25.917663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁처리 191
99.0%
자가처리 2
 
1.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-04-21T11:07:25.993999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:07:26.073737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T11:07:23.409122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:07:26.143698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업장구분수거형태
연번1.0000.4050.000
사업장구분0.4051.0000.000
수거형태0.0000.0001.000
2024-04-21T11:07:26.239275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장구분수거형태
사업장구분1.0000.000
수거형태0.0001.000
2024-04-21T11:07:26.331791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업장구분수거형태
연번1.0000.2470.000
사업장구분0.2471.0000.000
수거형태0.0000.0001.000

Missing values

2024-04-21T11:07:23.596283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:07:23.735802image/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

연번관리기관명사업장구분상호사업장도로명주소수거형태데이터기준일자
01동작구청집단급식소흑석어린이집서울특별시 동작구 서달로4길 46 (흑석동_ 흑석어린이집)위탁처리2023-12-31
12동작구청일반음식점한우천국서울특별시 영등포구 여의대방로 115 (신길동)위탁처리2023-12-31
23동작구청일반음식점성민촌 상도점서울특별시 동작구 매봉로 13 (상도1동_ 상도타운)위탁처리2023-12-31
34동작구청일반음식점(주)커피빈코리아서울특별시 동작구 보라매로5길 35 (신대방동_ 한국컴퓨터빌딩_보라매현대APT)위탁처리2023-12-31
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