Overview

Dataset statistics

Number of variables4
Number of observations367
Missing cells72
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.0 KiB
Average record size in memory33.4 B

Variable types

Numeric1
Text3

Dataset

Description서울특별시 강서구의 음식물 쓰레기 다량배출사업장 현황 정보를 제공합니다. 연번,업체명,연락처,주소의 항목이 포함되어 있습니다.
Author서울특별시 강서구
URLhttps://www.data.go.kr/data/15094443/fileData.do

Alerts

연락처 has 72 (19.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:53:52.314582
Analysis finished2023-12-12 14:53:52.920530
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct367
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184
Minimum1
Maximum367
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T23:53:53.027367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.3
Q192.5
median184
Q3275.5
95-th percentile348.7
Maximum367
Range366
Interquartile range (IQR)183

Descriptive statistics

Standard deviation106.08801
Coefficient of variation (CV)0.57656529
Kurtosis-1.2
Mean184
Median Absolute Deviation (MAD)92
Skewness0
Sum67528
Variance11254.667
MonotonicityStrictly increasing
2023-12-12T23:53:53.206313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
243 1
 
0.3%
252 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
247 1
 
0.3%
246 1
 
0.3%
245 1
 
0.3%
Other values (357) 357
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
367 1
0.3%
366 1
0.3%
365 1
0.3%
364 1
0.3%
363 1
0.3%
362 1
0.3%
361 1
0.3%
360 1
0.3%
359 1
0.3%
358 1
0.3%

업체명
Text

Distinct364
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T23:53:53.562187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length20
Mean length8
Min length2

Characters and Unicode

Total characters2936
Distinct characters437
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique361 ?
Unique (%)98.4%

Sample

1st row롯데리아 신김포공항점
2nd row한국맥도날드송정역점
3rd row스타벅스커피 까치산역점
4th row엔제리너스 김포공항1층점
5th row한국맥도날드염창DT점
ValueCountFrequency (%)
발산점 7
 
1.4%
김포공항점 6
 
1.2%
마곡점 6
 
1.2%
등촌점 5
 
1.0%
주식회사 4
 
0.8%
강서점 3
 
0.6%
김포공항 3
 
0.6%
까치산역점 3
 
0.6%
아시아나항공(주 2
 
0.4%
마곡역점 2
 
0.4%
Other values (444) 453
91.7%
2023-12-12T23:53:54.063917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
129
 
4.4%
서 84
 
2.9%
점 81
 
2.8%
교 71
 
2.4%
등 71
 
2.4%
스 69
 
2.4%
학 68
 
2.3%
) 57
 
1.9%
( 56
 
1.9%
주 49
 
1.7%
Other values (427) 2201
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2556
87.1%
Space Separator 129
 
4.4%
Uppercase Letter 74
 
2.5%
Close Punctuation 57
 
1.9%
Open Punctuation 56
 
1.9%
Lowercase Letter 27
 
0.9%
Decimal Number 18
 
0.6%
Other Punctuation 14
 
0.5%
Other Symbol 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 84
 
3.3%
점 81
 
3.2%
교 71
 
2.8%
등 71
 
2.8%
스 69
 
2.7%
학 68
 
2.7%
주 49
 
1.9%
울 47
 
1.8%
이 47
 
1.8%
공 39
 
1.5%
Other values (375) 1930
75.5%
Uppercase Letter
ValueCountFrequency (%)
G 8
10.8%
N 8
10.8%
C 7
 
9.5%
T 7
 
9.5%
E 6
 
8.1%
S 4
 
5.4%
A 4
 
5.4%
I 4
 
5.4%
D 4
 
5.4%
F 4
 
5.4%
Other values (12) 18
24.3%
Lowercase Letter
ValueCountFrequency (%)
e 4
14.8%
o 4
14.8%
s 3
11.1%
u 2
 
7.4%
t 2
 
7.4%
m 2
 
7.4%
l 2
 
7.4%
n 1
 
3.7%
a 1
 
3.7%
k 1
 
3.7%
Other values (5) 5
18.5%
Decimal Number
ValueCountFrequency (%)
9 5
27.8%
1 4
22.2%
3 3
16.7%
6 2
 
11.1%
4 1
 
5.6%
0 1
 
5.6%
7 1
 
5.6%
5 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 6
42.9%
. 5
35.7%
& 3
21.4%
Space Separator
ValueCountFrequency (%)
129
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2552
86.9%
Common 274
 
9.3%
Latin 101
 
3.4%
Han 9
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 84
 
3.3%
점 81
 
3.2%
교 71
 
2.8%
등 71
 
2.8%
스 69
 
2.7%
학 68
 
2.7%
주 49
 
1.9%
울 47
 
1.8%
이 47
 
1.8%
공 39
 
1.5%
Other values (367) 1926
75.5%
Latin
ValueCountFrequency (%)
G 8
 
7.9%
N 8
 
7.9%
C 7
 
6.9%
T 7
 
6.9%
E 6
 
5.9%
S 4
 
4.0%
e 4
 
4.0%
A 4
 
4.0%
o 4
 
4.0%
I 4
 
4.0%
Other values (27) 45
44.6%
Common
ValueCountFrequency (%)
129
47.1%
) 57
20.8%
( 56
20.4%
, 6
 
2.2%
. 5
 
1.8%
9 5
 
1.8%
1 4
 
1.5%
& 3
 
1.1%
3 3
 
1.1%
6 2
 
0.7%
Other values (4) 4
 
1.5%
Han
ValueCountFrequency (%)
園 1
11.1%
李 1
11.1%
蓬 1
11.1%
萊 1
11.1%
軒 1
11.1%
源 1
11.1%
樂 1
11.1%
明 1
11.1%
家 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2547
86.8%
ASCII 375
 
12.8%
CJK 7
 
0.2%
None 5
 
0.2%
CJK Compat Ideographs 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
129
34.4%
) 57
15.2%
( 56
14.9%
G 8
 
2.1%
N 8
 
2.1%
C 7
 
1.9%
T 7
 
1.9%
E 6
 
1.6%
, 6
 
1.6%
. 5
 
1.3%
Other values (41) 86
22.9%
Hangul
ValueCountFrequency (%)
서 84
 
3.3%
점 81
 
3.2%
교 71
 
2.8%
등 71
 
2.8%
스 69
 
2.7%
학 68
 
2.7%
주 49
 
1.9%
울 47
 
1.8%
이 47
 
1.8%
공 39
 
1.5%
Other values (366) 1921
75.4%
None
ValueCountFrequency (%)
㈜ 5
100.0%
CJK
ValueCountFrequency (%)
園 1
14.3%
蓬 1
14.3%
萊 1
14.3%
軒 1
14.3%
源 1
14.3%
明 1
14.3%
家 1
14.3%
CJK Compat Ideographs
ValueCountFrequency (%)
李 1
50.0%
樂 1
50.0%

연락처
Text

MISSING 

Distinct286
Distinct (%)96.9%
Missing72
Missing (%)19.6%
Memory size3.0 KiB
2023-12-12T23:53:54.335173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.074576
Min length9

Characters and Unicode

Total characters3562
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique277 ?
Unique (%)93.9%

Sample

1st row02-2666-6814
2nd row070-7017-9276
3rd row02-758-8538
4th row02-2667-0108
5th row070-7209-0594
ValueCountFrequency (%)
02-2064-8080 2
 
0.7%
02-2667-9853 2
 
0.7%
02-2064-0765 2
 
0.7%
02-2101-1054 2
 
0.7%
02-2669-5022 2
 
0.7%
02-6395-8703 2
 
0.7%
02-2661-9115 2
 
0.7%
02-3663-3500 2
 
0.7%
02-6116-1567 2
 
0.7%
02-3661-0055 1
 
0.3%
Other values (276) 276
93.6%
2023-12-12T23:53:54.827533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 604
17.0%
- 587
16.5%
2 580
16.3%
6 499
14.0%
3 226
 
6.3%
1 198
 
5.6%
5 188
 
5.3%
7 183
 
5.1%
9 181
 
5.1%
8 170
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2975
83.5%
Dash Punctuation 587
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 604
20.3%
2 580
19.5%
6 499
16.8%
3 226
 
7.6%
1 198
 
6.7%
5 188
 
6.3%
7 183
 
6.2%
9 181
 
6.1%
8 170
 
5.7%
4 146
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 587
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3562
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 604
17.0%
- 587
16.5%
2 580
16.3%
6 499
14.0%
3 226
 
6.3%
1 198
 
5.6%
5 188
 
5.3%
7 183
 
5.1%
9 181
 
5.1%
8 170
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3562
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 604
17.0%
- 587
16.5%
2 580
16.3%
6 499
14.0%
3 226
 
6.3%
1 198
 
5.6%
5 188
 
5.3%
7 183
 
5.1%
9 181
 
5.1%
8 170
 
4.8%

주소
Text

Distinct322
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T23:53:55.112827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length51
Mean length22.079019
Min length14

Characters and Unicode

Total characters8103
Distinct characters179
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique290 ?
Unique (%)79.0%

Sample

1st row서울특별시 강서구 하늘길 38 (방화동)
2nd row서울특별시 강서구 공항대로 21, 1~3층 (공항동)
3rd row서욱특별시 강서구 강서로1길 3
4th row서울특별시 강서구 하늘길 112 (공항동_ 김포공항)
5th row서울특별시 강서구 공항대로71길 3 (염창동)
ValueCountFrequency (%)
강서구 366
21.9%
서울특별시 347
20.7%
공항대로 49
 
2.9%
양천로 35
 
2.1%
강서로 29
 
1.7%
화곡로 23
 
1.4%
하늘길 23
 
1.4%
등촌동 20
 
1.2%
서울 18
 
1.1%
38 14
 
0.8%
Other values (418) 749
44.8%
2023-12-12T23:53:55.919818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1324
16.3%
서 806
 
9.9%
강 429
 
5.3%
울 369
 
4.6%
구 367
 
4.5%
시 350
 
4.3%
별 348
 
4.3%
특 348
 
4.3%
로 340
 
4.2%
1 269
 
3.3%
Other values (169) 3153
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4996
61.7%
Decimal Number 1404
 
17.3%
Space Separator 1324
 
16.3%
Open Punctuation 104
 
1.3%
Close Punctuation 104
 
1.3%
Connector Punctuation 51
 
0.6%
Other Punctuation 43
 
0.5%
Dash Punctuation 31
 
0.4%
Lowercase Letter 21
 
0.3%
Math Symbol 17
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 806
16.1%
강 429
 
8.6%
울 369
 
7.4%
구 367
 
7.3%
시 350
 
7.0%
별 348
 
7.0%
특 348
 
7.0%
로 340
 
6.8%
동 134
 
2.7%
길 131
 
2.6%
Other values (140) 1374
27.5%
Decimal Number
ValueCountFrequency (%)
1 269
19.2%
3 177
12.6%
2 177
12.6%
4 154
11.0%
6 141
10.0%
5 126
9.0%
0 107
 
7.6%
7 94
 
6.7%
8 88
 
6.3%
9 71
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
k 6
28.6%
s 3
14.3%
y 3
14.3%
a 3
14.3%
r 3
14.3%
p 3
14.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
25.0%
S 2
25.0%
Y 1
12.5%
N 1
12.5%
E 1
12.5%
B 1
12.5%
Space Separator
ValueCountFrequency (%)
1324
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 51
100.0%
Other Punctuation
ValueCountFrequency (%)
, 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4996
61.7%
Common 3078
38.0%
Latin 29
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 806
16.1%
강 429
 
8.6%
울 369
 
7.4%
구 367
 
7.3%
시 350
 
7.0%
별 348
 
7.0%
특 348
 
7.0%
로 340
 
6.8%
동 134
 
2.7%
길 131
 
2.6%
Other values (140) 1374
27.5%
Common
ValueCountFrequency (%)
1324
43.0%
1 269
 
8.7%
3 177
 
5.8%
2 177
 
5.8%
4 154
 
5.0%
6 141
 
4.6%
5 126
 
4.1%
0 107
 
3.5%
( 104
 
3.4%
) 104
 
3.4%
Other values (7) 395
 
12.8%
Latin
ValueCountFrequency (%)
k 6
20.7%
s 3
10.3%
y 3
10.3%
a 3
10.3%
r 3
10.3%
p 3
10.3%
C 2
 
6.9%
S 2
 
6.9%
Y 1
 
3.4%
N 1
 
3.4%
Other values (2) 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4996
61.7%
ASCII 3107
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1324
42.6%
1 269
 
8.7%
3 177
 
5.7%
2 177
 
5.7%
4 154
 
5.0%
6 141
 
4.5%
5 126
 
4.1%
0 107
 
3.4%
( 104
 
3.3%
) 104
 
3.3%
Other values (19) 424
 
13.6%
Hangul
ValueCountFrequency (%)
서 806
16.1%
강 429
 
8.6%
울 369
 
7.4%
구 367
 
7.3%
시 350
 
7.0%
별 348
 
7.0%
특 348
 
7.0%
로 340
 
6.8%
동 134
 
2.7%
길 131
 
2.6%
Other values (140) 1374
27.5%

Interactions

2023-12-12T23:53:52.649862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T23:53:52.780944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:53:52.878454image/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

연번업체명연락처주소
01롯데리아 신김포공항점02-2666-6814서울특별시 강서구 하늘길 38 (방화동)
12한국맥도날드송정역점070-7017-9276서울특별시 강서구 공항대로 21, 1~3층 (공항동)
23스타벅스커피 까치산역점02-758-8538서욱특별시 강서구 강서로1길 3
34엔제리너스 김포공항1층점02-2667-0108서울특별시 강서구 하늘길 112 (공항동_ 김포공항)
45한국맥도날드염창DT점070-7209-0594서울특별시 강서구 공항대로71길 3 (염창동)
56투썸플레이스 발산역점02-3662-3388서울특별시 강서구 마곡중앙6로 93_ 1~2층 (마곡동_ 열린프라자)
67스타벅스 화곡DT점2648-3257서울특별시 강서구 등촌로 57(등촌동)
78㈜케이에프씨코리아 kfc 목동사거리점2061-3176서울특별시 강서구 등촌로 19 (화곡동)
89(재)서울호서직업전문학교02-3663-2122서울특별시 강서구 강서로 418 (등촌동_ 동우빌딩)
910(주)국민은행전산정보그룹<NA>서울특별시 강서구 양천로 643 (염창동_국민은행전산센터)
연번업체명연락처주소
357358제주금한돈<NA>서울특별시 강서구 하늘길 233 C동
358359남문설렁탕02-6448-9293서울특별시 강서구 강서로 385 208~209호
359360마미된장 김포공항점0507-1456-1421서울특별시 강서구 하늘길 112 김포공항 국내선청사 4층
360361쏘킹인삼한우02-1899-8008서울특별시 강서구 공항대로71길 49
361362상무초밥 등촌점02-3663-3660서울특별시 강서구 공항대로 525
362363금고깃집 하늘직영점<NA>서울특별시 강서구 마곡중앙4로 10
363364방화 화덕 생선구이<NA>서울특별시 강서구 금낭화로 128
364365여행맛02-6116-3177서울특별시 강서구 하늘길 38
365366오제<NA>서울특별시 강서구 마곡동로 62 마곡사이언스타워 2층 201~203호
366367엄마손 식당<NA>서울특별시 강서구 마곡중앙6로 16 203~205호