Overview

Dataset statistics

Number of variables6
Number of observations80
Missing cells3
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory50.6 B

Variable types

Numeric1
Categorical1
Text3
DateTime1

Dataset

Description대구광역시 중구 소재의 음식물류폐기물다량배출사업장 현황(업소명, 도로명주소, 전화번호 등) 정보를 제공합니다.
Author대구광역시 중구
URLhttps://www.data.go.kr/data/15034435/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 사업장구분High correlation
사업장구분 is highly overall correlated with 연번High correlation
사업장 전화번호 has 3 (3.8%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:57:42.440504
Analysis finished2023-12-12 03:57:43.627122
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.5
Minimum1
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-12T12:57:43.720964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.95
Q120.75
median40.5
Q360.25
95-th percentile76.05
Maximum80
Range79
Interquartile range (IQR)39.5

Descriptive statistics

Standard deviation23.2379
Coefficient of variation (CV)0.57377531
Kurtosis-1.2
Mean40.5
Median Absolute Deviation (MAD)20
Skewness0
Sum3240
Variance540
MonotonicityStrictly increasing
2023-12-12T12:57:43.937233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
42 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
53 1
 
1.2%
Other values (70) 70
87.5%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%
72 1
1.2%
71 1
1.2%

사업장구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
일반음식점
55 
집단급식소
25 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 55
68.8%
집단급식소 25
31.2%

Length

2023-12-12T12:57:44.137446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:57:44.267950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 55
68.8%
집단급식소 25
31.2%

상호
Text

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-12T12:57:44.603890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length7.925
Min length2

Characters and Unicode

Total characters634
Distinct characters241
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)100.0%

Sample

1st row감포생아구
2nd row대보일번지
3rd row국일생갈비
4th row교동면옥 동인점
5th row부산안면옥
ValueCountFrequency (%)
주식회사 3
 
2.7%
동성로점 3
 
2.7%
삼성웰스토리 2
 
1.8%
대구점 2
 
1.8%
고기굽는남자 2
 
1.8%
낙영찜갈비 2
 
1.8%
구내식당 2
 
1.8%
종로초등학교 1
 
0.9%
큐투코 1
 
0.9%
수창초등학교 1
 
0.9%
Other values (94) 94
83.2%
2023-12-12T12:57:45.236502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
 
5.7%
점 19
 
3.0%
대 16
 
2.5%
스 15
 
2.4%
구 13
 
2.1%
식 12
 
1.9%
비 12
 
1.9%
원 12
 
1.9%
학 11
 
1.7%
( 11
 
1.7%
Other values (231) 477
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 529
83.4%
Space Separator 36
 
5.7%
Lowercase Letter 19
 
3.0%
Decimal Number 13
 
2.1%
Open Punctuation 11
 
1.7%
Close Punctuation 11
 
1.7%
Uppercase Letter 7
 
1.1%
Other Symbol 6
 
0.9%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 19
 
3.6%
대 16
 
3.0%
스 15
 
2.8%
구 13
 
2.5%
식 12
 
2.3%
비 12
 
2.3%
원 12
 
2.3%
학 11
 
2.1%
동 11
 
2.1%
교 11
 
2.1%
Other values (200) 397
75.0%
Lowercase Letter
ValueCountFrequency (%)
g 3
15.8%
u 3
15.8%
b 2
10.5%
e 2
10.5%
a 2
10.5%
n 2
10.5%
r 1
 
5.3%
f 1
 
5.3%
l 1
 
5.3%
p 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
9 4
30.8%
7 2
15.4%
6 2
15.4%
0 1
 
7.7%
2 1
 
7.7%
1 1
 
7.7%
4 1
 
7.7%
3 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
K 1
14.3%
O 1
14.3%
F 1
14.3%
D 1
14.3%
T 1
14.3%
G 1
14.3%
C 1
14.3%
Space Separator
ValueCountFrequency (%)
36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 535
84.4%
Common 73
 
11.5%
Latin 26
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 19
 
3.6%
대 16
 
3.0%
스 15
 
2.8%
구 13
 
2.4%
식 12
 
2.2%
비 12
 
2.2%
원 12
 
2.2%
학 11
 
2.1%
동 11
 
2.1%
교 11
 
2.1%
Other values (201) 403
75.3%
Latin
ValueCountFrequency (%)
g 3
 
11.5%
u 3
 
11.5%
b 2
 
7.7%
e 2
 
7.7%
a 2
 
7.7%
n 2
 
7.7%
K 1
 
3.8%
O 1
 
3.8%
F 1
 
3.8%
D 1
 
3.8%
Other values (8) 8
30.8%
Common
ValueCountFrequency (%)
36
49.3%
( 11
 
15.1%
) 11
 
15.1%
9 4
 
5.5%
7 2
 
2.7%
6 2
 
2.7%
. 2
 
2.7%
0 1
 
1.4%
2 1
 
1.4%
1 1
 
1.4%
Other values (2) 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 529
83.4%
ASCII 99
 
15.6%
None 6
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
36.4%
( 11
 
11.1%
) 11
 
11.1%
9 4
 
4.0%
g 3
 
3.0%
u 3
 
3.0%
b 2
 
2.0%
e 2
 
2.0%
a 2
 
2.0%
n 2
 
2.0%
Other values (20) 23
23.2%
Hangul
ValueCountFrequency (%)
점 19
 
3.6%
대 16
 
3.0%
스 15
 
2.8%
구 13
 
2.5%
식 12
 
2.3%
비 12
 
2.3%
원 12
 
2.3%
학 11
 
2.1%
동 11
 
2.1%
교 11
 
2.1%
Other values (200) 397
75.0%
None
ValueCountFrequency (%)
㈜ 6
100.0%

사업장 주소
Text

Distinct79
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-12T12:57:45.545242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length34
Mean length26.45
Min length15

Characters and Unicode

Total characters2116
Distinct characters95
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)97.5%

Sample

1st row대구광역시 중구 경상감영1길 7 지상 1 2층 (전동)
2nd row대구광역시 중구 경상감영길 117-7 (향촌동)
3rd row대구광역시 중구 국채보상로 492 (동산동)
4th row대구광역시 중구 국채보상로 679-14 1층 (동인동2가)
5th row대구광역시 중구 국채보상로 125길 4-1, 1층 공평동
ValueCountFrequency (%)
대구광역시 80
 
18.3%
중구 80
 
18.3%
국채보상로 12
 
2.7%
삼덕동1가 11
 
2.5%
2층 10
 
2.3%
1층 9
 
2.1%
달구벌대로 6
 
1.4%
동성로5길 5
 
1.1%
지상2층 5
 
1.1%
동덕로 5
 
1.1%
Other values (154) 214
49.0%
2023-12-12T12:57:46.039407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
358
 
16.9%
구 167
 
7.9%
대 100
 
4.7%
1 92
 
4.3%
동 91
 
4.3%
중 86
 
4.1%
로 83
 
3.9%
역 80
 
3.8%
광 80
 
3.8%
시 80
 
3.8%
Other values (85) 899
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1211
57.2%
Decimal Number 389
 
18.4%
Space Separator 358
 
16.9%
Close Punctuation 55
 
2.6%
Open Punctuation 55
 
2.6%
Other Punctuation 24
 
1.1%
Dash Punctuation 20
 
0.9%
Math Symbol 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 167
13.8%
대 100
 
8.3%
동 91
 
7.5%
중 86
 
7.1%
로 83
 
6.9%
역 80
 
6.6%
광 80
 
6.6%
시 80
 
6.6%
층 44
 
3.6%
길 41
 
3.4%
Other values (66) 359
29.6%
Decimal Number
ValueCountFrequency (%)
1 92
23.7%
2 74
19.0%
3 46
11.8%
4 36
 
9.3%
5 28
 
7.2%
7 26
 
6.7%
0 24
 
6.2%
8 22
 
5.7%
6 22
 
5.7%
9 19
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 22
91.7%
. 2
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
358
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1211
57.2%
Common 903
42.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 167
13.8%
대 100
 
8.3%
동 91
 
7.5%
중 86
 
7.1%
로 83
 
6.9%
역 80
 
6.6%
광 80
 
6.6%
시 80
 
6.6%
층 44
 
3.6%
길 41
 
3.4%
Other values (66) 359
29.6%
Common
ValueCountFrequency (%)
358
39.6%
1 92
 
10.2%
2 74
 
8.2%
) 55
 
6.1%
( 55
 
6.1%
3 46
 
5.1%
4 36
 
4.0%
5 28
 
3.1%
7 26
 
2.9%
0 24
 
2.7%
Other values (7) 109
 
12.1%
Latin
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1211
57.2%
ASCII 905
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
358
39.6%
1 92
 
10.2%
2 74
 
8.2%
) 55
 
6.1%
( 55
 
6.1%
3 46
 
5.1%
4 36
 
4.0%
5 28
 
3.1%
7 26
 
2.9%
0 24
 
2.7%
Other values (9) 111
 
12.3%
Hangul
ValueCountFrequency (%)
구 167
13.8%
대 100
 
8.3%
동 91
 
7.5%
중 86
 
7.1%
로 83
 
6.9%
역 80
 
6.6%
광 80
 
6.6%
시 80
 
6.6%
층 44
 
3.6%
길 41
 
3.4%
Other values (66) 359
29.6%

사업장 전화번호
Text

MISSING 

Distinct75
Distinct (%)97.4%
Missing3
Missing (%)3.8%
Memory size772.0 B
2023-12-12T12:57:46.319852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.285714
Min length9

Characters and Unicode

Total characters946
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

Unique73 ?
Unique (%)94.8%

Sample

1st row0507-1365-6636
2nd row053-255-6667
3rd row053-254-5115
4th row053-426-9222
5th row053-424-9389
ValueCountFrequency (%)
053-425-7184 2
 
2.6%
053-803-2747 2
 
2.6%
053-253-5933 1
 
1.3%
053-963-0006 1
 
1.3%
053-252-0306 1
 
1.3%
053-232-0456 1
 
1.3%
053-232-0626 1
 
1.3%
053-232-0841 1
 
1.3%
053-420-4979 1
 
1.3%
053-242-1324 1
 
1.3%
Other values (65) 65
84.4%
2023-12-12T12:57:46.701077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 159
16.8%
- 153
16.2%
3 130
13.7%
5 126
13.3%
2 103
10.9%
4 62
 
6.6%
7 57
 
6.0%
1 50
 
5.3%
6 37
 
3.9%
9 36
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 793
83.8%
Dash Punctuation 153
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 159
20.1%
3 130
16.4%
5 126
15.9%
2 103
13.0%
4 62
 
7.8%
7 57
 
7.2%
1 50
 
6.3%
6 37
 
4.7%
9 36
 
4.5%
8 33
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 153
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 946
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 159
16.8%
- 153
16.2%
3 130
13.7%
5 126
13.3%
2 103
10.9%
4 62
 
6.6%
7 57
 
6.0%
1 50
 
5.3%
6 37
 
3.9%
9 36
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 946
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 159
16.8%
- 153
16.2%
3 130
13.7%
5 126
13.3%
2 103
10.9%
4 62
 
6.6%
7 57
 
6.0%
1 50
 
5.3%
6 37
 
3.9%
9 36
 
3.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
Minimum2022-08-26 00:00:00
Maximum2022-08-26 00:00:00
2023-12-12T12:57:46.854000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:57:46.966486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T12:57:43.262269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:57:47.056111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업장구분상호사업장 주소사업장 전화번호
연번1.0000.9991.0000.9391.000
사업장구분0.9991.0001.0000.0001.000
상호1.0001.0001.0001.0001.000
사업장 주소0.9390.0001.0001.0000.995
사업장 전화번호1.0001.0001.0000.9951.000
2023-12-12T12:57:47.166542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업장구분
연번1.0000.920
사업장구분0.9201.000

Missing values

2023-12-12T12:57:43.427736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:57:43.573717image/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

연번사업장구분상호사업장 주소사업장 전화번호데이터기준일
01일반음식점감포생아구대구광역시 중구 경상감영1길 7 지상 1 2층 (전동)0507-1365-66362022-08-26
12일반음식점대보일번지대구광역시 중구 경상감영길 117-7 (향촌동)053-255-66672022-08-26
23일반음식점국일생갈비대구광역시 중구 국채보상로 492 (동산동)053-254-51152022-08-26
34일반음식점교동면옥 동인점대구광역시 중구 국채보상로 679-14 1층 (동인동2가)053-426-92222022-08-26
45일반음식점부산안면옥대구광역시 중구 국채보상로 125길 4-1, 1층 공평동053-424-93892022-08-26
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