Overview

Dataset statistics

Number of variables5
Number of observations107
Missing cells5
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory42.2 B

Variable types

Numeric1
Text4

Dataset

Description대구광역시_동구_모범음식점현황_20180901
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15052654&dataSetDetailId=1505265419814a5f7d01d_201809211856&provdMethod=FILE

Reproduction

Analysis started2024-04-21 11:46:18.718189
Analysis finished2024-04-21 11:46:19.931360
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

Distinct106
Distinct (%)100.0%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean53.5
Minimum1
Maximum106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-21T20:46:20.105091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.25
Q127.25
median53.5
Q379.75
95-th percentile100.75
Maximum106
Range105
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation30.743563
Coefficient of variation (CV)0.57464604
Kurtosis-1.2
Mean53.5
Median Absolute Deviation (MAD)26.5
Skewness0
Sum5671
Variance945.16667
MonotonicityStrictly increasing
2024-04-21T20:46:20.370296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
81 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
72 1
 
0.9%
Other values (96) 96
89.7%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%
98 1
0.9%
97 1
0.9%

업소명
Text

Distinct105
Distinct (%)99.1%
Missing1
Missing (%)0.9%
Memory size984.0 B
2024-04-21T20:46:21.139218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12.5
Mean length6.3773585
Min length2

Characters and Unicode

Total characters676
Distinct characters229
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)98.1%

Sample

1st row가장맛있는족발(동대구역점)
2nd row강원도인제황태식당
3rd row거송복어식당
4th row고려가든
5th row고려산장식당
ValueCountFrequency (%)
행복한갈비 2
 
1.6%
신기한면 1
 
0.8%
재바우참숯불 1
 
0.8%
일흥정 1
 
0.8%
일출회집 1
 
0.8%
일출회수산시장 1
 
0.8%
일송정 1
 
0.8%
이프(if 1
 
0.8%
이수사 1
 
0.8%
혁신도시점 1
 
0.8%
Other values (111) 111
91.0%
2024-04-21T20:46:22.163732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 28
 
4.1%
당 27
 
4.0%
16
 
2.4%
점 13
 
1.9%
수 13
 
1.9%
구 13
 
1.9%
정 13
 
1.9%
대 13
 
1.9%
산 12
 
1.8%
한 11
 
1.6%
Other values (219) 517
76.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 645
95.4%
Space Separator 16
 
2.4%
Open Punctuation 4
 
0.6%
Close Punctuation 4
 
0.6%
Decimal Number 2
 
0.3%
Uppercase Letter 2
 
0.3%
Lowercase Letter 2
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 28
 
4.3%
당 27
 
4.2%
점 13
 
2.0%
수 13
 
2.0%
구 13
 
2.0%
정 13
 
2.0%
대 13
 
2.0%
산 12
 
1.9%
한 11
 
1.7%
가 11
 
1.7%
Other values (209) 491
76.1%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
8 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
I 1
50.0%
C 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
f 1
50.0%
i 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 642
95.0%
Common 27
 
4.0%
Latin 4
 
0.6%
Han 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 28
 
4.4%
당 27
 
4.2%
점 13
 
2.0%
수 13
 
2.0%
구 13
 
2.0%
정 13
 
2.0%
대 13
 
2.0%
산 12
 
1.9%
한 11
 
1.7%
가 11
 
1.7%
Other values (207) 488
76.0%
Common
ValueCountFrequency (%)
16
59.3%
( 4
 
14.8%
) 4
 
14.8%
3 1
 
3.7%
8 1
 
3.7%
, 1
 
3.7%
Latin
ValueCountFrequency (%)
I 1
25.0%
C 1
25.0%
f 1
25.0%
i 1
25.0%
Han
ValueCountFrequency (%)
愛 2
66.7%
家 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 642
95.0%
ASCII 31
 
4.6%
CJK 3
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 28
 
4.4%
당 27
 
4.2%
점 13
 
2.0%
수 13
 
2.0%
구 13
 
2.0%
정 13
 
2.0%
대 13
 
2.0%
산 12
 
1.9%
한 11
 
1.7%
가 11
 
1.7%
Other values (207) 488
76.0%
ASCII
ValueCountFrequency (%)
16
51.6%
( 4
 
12.9%
) 4
 
12.9%
3 1
 
3.2%
8 1
 
3.2%
I 1
 
3.2%
C 1
 
3.2%
f 1
 
3.2%
i 1
 
3.2%
, 1
 
3.2%
CJK
ValueCountFrequency (%)
愛 2
66.7%
家 1
33.3%

주소
Text

Distinct102
Distinct (%)96.2%
Missing1
Missing (%)0.9%
Memory size984.0 B
2024-04-21T20:46:23.103780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length41
Mean length25.075472
Min length20

Characters and Unicode

Total characters2658
Distinct characters125
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)92.5%

Sample

1st row대구광역시 동구 동부로22길 43 (신천동)
2nd row대구광역시 동구 동북로 435 (효목동)
3rd row대구광역시 동구 동촌로 263 (방촌동)
4th row대구광역시 동구 팔공산로185길 60 (용수동)
5th row대구광역시 동구 팔공산로185길 62 (용수동)
ValueCountFrequency (%)
대구광역시 106
20.2%
동구 106
20.2%
신천동 14
 
2.7%
동촌로 11
 
2.1%
효목동 10
 
1.9%
신암동 10
 
1.9%
율하동 8
 
1.5%
방촌동 6
 
1.1%
용수동 6
 
1.1%
중대동 5
 
1.0%
Other values (174) 244
46.4%
2024-04-21T20:46:24.074490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
420
15.8%
동 259
 
9.7%
구 215
 
8.1%
대 115
 
4.3%
시 107
 
4.0%
( 107
 
4.0%
) 107
 
4.0%
광 106
 
4.0%
역 106
 
4.0%
로 105
 
4.0%
Other values (115) 1011
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1528
57.5%
Decimal Number 436
 
16.4%
Space Separator 420
 
15.8%
Open Punctuation 107
 
4.0%
Close Punctuation 107
 
4.0%
Other Punctuation 31
 
1.2%
Dash Punctuation 23
 
0.9%
Uppercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 259
17.0%
구 215
14.1%
대 115
 
7.5%
시 107
 
7.0%
광 106
 
6.9%
역 106
 
6.9%
로 105
 
6.9%
신 48
 
3.1%
길 47
 
3.1%
촌 24
 
1.6%
Other values (95) 396
25.9%
Decimal Number
ValueCountFrequency (%)
1 88
20.2%
2 78
17.9%
3 52
11.9%
0 49
11.2%
5 37
8.5%
6 37
8.5%
7 29
 
6.7%
4 28
 
6.4%
8 21
 
4.8%
9 17
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
33.3%
B 1
16.7%
D 1
16.7%
C 1
16.7%
J 1
16.7%
Space Separator
ValueCountFrequency (%)
420
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Other Punctuation
ValueCountFrequency (%)
, 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1528
57.5%
Common 1124
42.3%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 259
17.0%
구 215
14.1%
대 115
 
7.5%
시 107
 
7.0%
광 106
 
6.9%
역 106
 
6.9%
로 105
 
6.9%
신 48
 
3.1%
길 47
 
3.1%
촌 24
 
1.6%
Other values (95) 396
25.9%
Common
ValueCountFrequency (%)
420
37.4%
( 107
 
9.5%
) 107
 
9.5%
1 88
 
7.8%
2 78
 
6.9%
3 52
 
4.6%
0 49
 
4.4%
5 37
 
3.3%
6 37
 
3.3%
, 31
 
2.8%
Other values (5) 118
 
10.5%
Latin
ValueCountFrequency (%)
A 2
33.3%
B 1
16.7%
D 1
16.7%
C 1
16.7%
J 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1528
57.5%
ASCII 1130
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
420
37.2%
( 107
 
9.5%
) 107
 
9.5%
1 88
 
7.8%
2 78
 
6.9%
3 52
 
4.6%
0 49
 
4.3%
5 37
 
3.3%
6 37
 
3.3%
, 31
 
2.7%
Other values (10) 124
 
11.0%
Hangul
ValueCountFrequency (%)
동 259
17.0%
구 215
14.1%
대 115
 
7.5%
시 107
 
7.0%
광 106
 
6.9%
역 106
 
6.9%
로 105
 
6.9%
신 48
 
3.1%
길 47
 
3.1%
촌 24
 
1.6%
Other values (95) 396
25.9%

전화번호
Text

Distinct105
Distinct (%)99.1%
Missing1
Missing (%)0.9%
Memory size984.0 B
2024-04-21T20:46:24.836986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1272
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

Unique104 ?
Unique (%)98.1%

Sample

1st row053-744-5849
2nd row053-951-7838
3rd row053-984-6755
4th row053-982-0103
5th row053-982-0126
ValueCountFrequency (%)
053-961-7200 2
 
1.9%
053-961-5295 1
 
0.9%
053-754-1900 1
 
0.9%
053-984-2002 1
 
0.9%
053-422-4800 1
 
0.9%
053-752-4456 1
 
0.9%
053-953-5326 1
 
0.9%
053-965-5326 1
 
0.9%
053-983-7711 1
 
0.9%
053-952-1011 1
 
0.9%
Other values (95) 95
89.6%
2024-04-21T20:46:25.816368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 212
16.7%
0 191
15.0%
5 184
14.5%
3 156
12.3%
9 129
10.1%
8 92
7.2%
2 70
 
5.5%
6 66
 
5.2%
4 60
 
4.7%
1 57
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1060
83.3%
Dash Punctuation 212
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 191
18.0%
5 184
17.4%
3 156
14.7%
9 129
12.2%
8 92
8.7%
2 70
 
6.6%
6 66
 
6.2%
4 60
 
5.7%
1 57
 
5.4%
7 55
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 212
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1272
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 212
16.7%
0 191
15.0%
5 184
14.5%
3 156
12.3%
9 129
10.1%
8 92
7.2%
2 70
 
5.5%
6 66
 
5.2%
4 60
 
4.7%
1 57
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 212
16.7%
0 191
15.0%
5 184
14.5%
3 156
12.3%
9 129
10.1%
8 92
7.2%
2 70
 
5.5%
6 66
 
5.2%
4 60
 
4.7%
1 57
 
4.5%

주메뉴
Text

Distinct88
Distinct (%)83.0%
Missing1
Missing (%)0.9%
Memory size984.0 B
2024-04-21T20:46:26.462470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.509434
Min length3

Characters and Unicode

Total characters796
Distinct characters150
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)74.5%

Sample

1st row족발,보쌈
2nd row황태찜,황태전골,황태구이
3rd row복어요리
4th row자연산송이전골,송이돌솥밥
5th row송이버섯샤브,송이버섯정식
ValueCountFrequency (%)
생선회 7
 
6.4%
복어요리 5
 
4.5%
한우구이,한우불고기 3
 
2.7%
한우구이 3
 
2.7%
콩나물국밥 2
 
1.8%
흑태찜 2
 
1.8%
한정식 2
 
1.8%
냉면,갈비탕,갈비찜 2
 
1.8%
중식요리 2
 
1.8%
돼지갈비,버섯불고기 1
 
0.9%
Other values (81) 81
73.6%
2024-04-21T20:46:27.632487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 75
 
9.4%
이 27
 
3.4%
한 22
 
2.8%
비 21
 
2.6%
생 20
 
2.5%
갈 20
 
2.5%
리 20
 
2.5%
구 19
 
2.4%
회 15
 
1.9%
수 15
 
1.9%
Other values (140) 542
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 714
89.7%
Other Punctuation 76
 
9.5%
Space Separator 4
 
0.5%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 27
 
3.8%
한 22
 
3.1%
비 21
 
2.9%
생 20
 
2.8%
갈 20
 
2.8%
리 20
 
2.8%
구 19
 
2.7%
회 15
 
2.1%
수 15
 
2.1%
밥 15
 
2.1%
Other values (135) 520
72.8%
Other Punctuation
ValueCountFrequency (%)
, 75
98.7%
. 1
 
1.3%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 714
89.7%
Common 82
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 27
 
3.8%
한 22
 
3.1%
비 21
 
2.9%
생 20
 
2.8%
갈 20
 
2.8%
리 20
 
2.8%
구 19
 
2.7%
회 15
 
2.1%
수 15
 
2.1%
밥 15
 
2.1%
Other values (135) 520
72.8%
Common
ValueCountFrequency (%)
, 75
91.5%
4
 
4.9%
( 1
 
1.2%
) 1
 
1.2%
. 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 714
89.7%
ASCII 82
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 75
91.5%
4
 
4.9%
( 1
 
1.2%
) 1
 
1.2%
. 1
 
1.2%
Hangul
ValueCountFrequency (%)
이 27
 
3.8%
한 22
 
3.1%
비 21
 
2.9%
생 20
 
2.8%
갈 20
 
2.8%
리 20
 
2.8%
구 19
 
2.7%
회 15
 
2.1%
수 15
 
2.1%
밥 15
 
2.1%
Other values (135) 520
72.8%

Interactions

2024-04-21T20:46:19.272324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T20:46:27.883306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주메뉴
연번1.0000.454
주메뉴0.4541.000

Missing values

2024-04-21T20:46:19.455789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T20:46:19.638896image/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.
2024-04-21T20:46:19.811863image/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

연번업소명주소전화번호주메뉴
01가장맛있는족발(동대구역점)대구광역시 동구 동부로22길 43 (신천동)053-744-5849족발,보쌈
12강원도인제황태식당대구광역시 동구 동북로 435 (효목동)053-951-7838황태찜,황태전골,황태구이
23거송복어식당대구광역시 동구 동촌로 263 (방촌동)053-984-6755복어요리
34고려가든대구광역시 동구 팔공산로185길 60 (용수동)053-982-0103자연산송이전골,송이돌솥밥
45고려산장식당대구광역시 동구 팔공산로185길 62 (용수동)053-982-0126송이버섯샤브,송이버섯정식
56고산정삼계탕대구광역시 동구 안심로 375 (신서동)053-962-6699삼계탕,순살찜닭
67고향식당대구광역시 동구 팔공산로185길 63 (용수동)053-982-1755가마솥밥정식,송이전골
78고향집칼국수,재바우대구광역시 동구 송라로 93 (신천동)053-751-6850칼국수,수육,암뽕
89고향차밭골식당대구광역시 동구 파계로138길 12 (중대동)053-981-5883차밭골한정식
910공산한우식육식당대구광역시 동구 신암남로 162-1 (신암동)053-955-7272한우구이, 육회
연번업소명주소전화번호주메뉴
9798한통정육식당대구광역시 동구 동촌로 370 (용계동)053-959-5003소고기구이,생삼겹살
9899해금강대구광역시 동구 신암남로 133 (신암동)053-954-2323복어요리
99100해송식당대구광역시 동구 장등로 57 (신천동)053-751-9561생선회
100101행복한갈비대구광역시 동구 신암남로 166(신암동)053-958-8592돼지갈비,돼지주물럭
101102행복한갈비대구광역시 동구 신서로 36(신서동)053-964-9259돼지갈비,한우갈비살
102103현풍닭칼국수 신서점대구광역시 동구 신서로22길4-2(신서동)053-963-2242닭칼국수
103104호박영양밥대구광역시 동구 팔공산로 291 (덕곡동)053-983-2050호박밥,호박오리
104105화우정식당대구광역시 동구 서촌로23길 13-1 (덕곡동)053-986-5900영양오리백숙,생오리구이
105106황장군용계점대구광역시 동구 동촌로 402(용계동)053-986-3000냉면,갈비탕,갈비찜
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