Overview

Dataset statistics

Number of variables10
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory85.8 B

Variable types

Categorical4
Text4
Numeric2

Dataset

Description대구광역시 동구_착한가격업소_20220822
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15059765&dataSetDetailId=1505976518dd28024b855&provdMethod=FILE

Alerts

데이터기준일 has constant value ""Constant
위도 is highly overall correlated with 법정동명High correlation
경도 is highly overall correlated with 행정동명 and 1 other fieldsHigh correlation
업종 is highly overall correlated with 법정동명High correlation
행정동명 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
법정동명 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
업종 is highly imbalanced (59.8%)Imbalance
업소명 has unique valuesUnique
소재지 has unique valuesUnique
전화번호 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:00:01.398277
Analysis finished2024-04-21 02:00:03.104892
Duration1.71 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size400.0 B
한식
28 
중식
 
1
일식
 
1
미용업
 
1
세탁업
 
1
Other values (2)
 
2

Length

Max length9
Median length2
Mean length2.2647059
Min length2

Unique

Unique6 ?
Unique (%)17.6%

Sample

1st row한식
2nd row한식
3rd row중식
4th row한식
5th row한식

Common Values

ValueCountFrequency (%)
한식 28
82.4%
중식 1
 
2.9%
일식 1
 
2.9%
미용업 1
 
2.9%
세탁업 1
 
2.9%
기타양식(제과점) 1
 
2.9%
양식 1
 
2.9%

Length

2024-04-21T11:00:03.230752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:00:03.438157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 28
82.4%
중식 1
 
2.9%
일식 1
 
2.9%
미용업 1
 
2.9%
세탁업 1
 
2.9%
기타양식(제과점 1
 
2.9%
양식 1
 
2.9%

업소명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-04-21T11:00:04.121359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length7
Mean length5.1470588
Min length2

Characters and Unicode

Total characters175
Distinct characters100
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st row대구삼계탕
2nd row두곡동숯불갈비
3rd row영남루반점
4th row유정갈비
5th row태종대
ValueCountFrequency (%)
대구삼계탕 1
 
2.8%
이가숯불갈비 1
 
2.8%
가원식당 1
 
2.8%
만보 1
 
2.8%
신산홍 1
 
2.8%
파스타누오바 1
 
2.8%
미소띤하루 1
 
2.8%
태왕세탁소 1
 
2.8%
두곡동숯불갈비 1
 
2.8%
부산복해물칼국수 1
 
2.8%
Other values (26) 26
72.2%
2024-04-21T11:00:05.251788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 7
 
4.0%
수 6
 
3.4%
갈 6
 
3.4%
비 6
 
3.4%
국 5
 
2.9%
불 5
 
2.9%
당 5
 
2.9%
칼 4
 
2.3%
어 4
 
2.3%
숯 4
 
2.3%
Other values (90) 123
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 173
98.9%
Space Separator 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 7
 
4.0%
수 6
 
3.5%
갈 6
 
3.5%
비 6
 
3.5%
국 5
 
2.9%
불 5
 
2.9%
당 5
 
2.9%
칼 4
 
2.3%
어 4
 
2.3%
숯 4
 
2.3%
Other values (89) 121
69.9%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 173
98.9%
Common 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 7
 
4.0%
수 6
 
3.5%
갈 6
 
3.5%
비 6
 
3.5%
국 5
 
2.9%
불 5
 
2.9%
당 5
 
2.9%
칼 4
 
2.3%
어 4
 
2.3%
숯 4
 
2.3%
Other values (89) 121
69.9%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
98.9%
ASCII 2
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 7
 
4.0%
수 6
 
3.5%
갈 6
 
3.5%
비 6
 
3.5%
국 5
 
2.9%
불 5
 
2.9%
당 5
 
2.9%
칼 4
 
2.3%
어 4
 
2.3%
숯 4
 
2.3%
Other values (89) 121
69.9%
ASCII
ValueCountFrequency (%)
2
100.0%

소재지
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-04-21T11:00:06.052395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length30.5
Mean length21.323529
Min length16

Characters and Unicode

Total characters725
Distinct characters79
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st row대구 동구 대현로 118-7(신암동)
2nd row대구 동구 아양로49길 6(신암동)
3rd row대구 동구 해동로 18(지저동)
4th row대구 동구 아양로 6(신암동)
5th row대구 동구 팔공로24길 19-10(불로동)
ValueCountFrequency (%)
대구 34
22.8%
동구 34
22.8%
아양로 4
 
2.7%
동촌로 3
 
2.0%
해동로 3
 
2.0%
103호(각산동 2
 
1.3%
6(신암동 2
 
1.3%
장등로 2
 
1.3%
동부로 2
 
1.3%
128(신천동 1
 
0.7%
Other values (62) 62
41.6%
2024-04-21T11:00:07.081919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
115
15.9%
동 80
 
11.0%
구 69
 
9.5%
로 37
 
5.1%
대 36
 
5.0%
( 34
 
4.7%
) 34
 
4.7%
1 34
 
4.7%
길 16
 
2.2%
0 16
 
2.2%
Other values (69) 254
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 387
53.4%
Decimal Number 135
 
18.6%
Space Separator 115
 
15.9%
Open Punctuation 34
 
4.7%
Close Punctuation 34
 
4.7%
Dash Punctuation 12
 
1.7%
Other Punctuation 8
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 80
20.7%
구 69
17.8%
로 37
 
9.6%
대 36
 
9.3%
길 16
 
4.1%
신 14
 
3.6%
암 10
 
2.6%
양 8
 
2.1%
아 8
 
2.1%
효 7
 
1.8%
Other values (54) 102
26.4%
Decimal Number
ValueCountFrequency (%)
1 34
25.2%
0 16
11.9%
2 16
11.9%
3 15
11.1%
8 11
 
8.1%
6 11
 
8.1%
5 9
 
6.7%
4 9
 
6.7%
7 7
 
5.2%
9 7
 
5.2%
Space Separator
ValueCountFrequency (%)
115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 387
53.4%
Common 338
46.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 80
20.7%
구 69
17.8%
로 37
 
9.6%
대 36
 
9.3%
길 16
 
4.1%
신 14
 
3.6%
암 10
 
2.6%
양 8
 
2.1%
아 8
 
2.1%
효 7
 
1.8%
Other values (54) 102
26.4%
Common
ValueCountFrequency (%)
115
34.0%
( 34
 
10.1%
) 34
 
10.1%
1 34
 
10.1%
0 16
 
4.7%
2 16
 
4.7%
3 15
 
4.4%
- 12
 
3.6%
8 11
 
3.3%
6 11
 
3.3%
Other values (5) 40
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 387
53.4%
ASCII 338
46.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
115
34.0%
( 34
 
10.1%
) 34
 
10.1%
1 34
 
10.1%
0 16
 
4.7%
2 16
 
4.7%
3 15
 
4.4%
- 12
 
3.6%
8 11
 
3.3%
6 11
 
3.3%
Other values (5) 40
 
11.8%
Hangul
ValueCountFrequency (%)
동 80
20.7%
구 69
17.8%
로 37
 
9.6%
대 36
 
9.3%
길 16
 
4.1%
신 14
 
3.6%
암 10
 
2.6%
양 8
 
2.1%
아 8
 
2.1%
효 7
 
1.8%
Other values (54) 102
26.4%

취급품목(원산지)
Text

Distinct29
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-04-21T11:00:07.753478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length5.2058824
Min length2

Characters and Unicode

Total characters177
Distinct characters76
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

Unique24 ?
Unique (%)70.6%

Sample

1st row삼계탕
2nd row돼지왕갈비(국내산)
3rd row자장면
4th row왕갈비(국내산)
5th row삼겹살(국내산)
ValueCountFrequency (%)
삼계탕 2
 
5.9%
칼국수 2
 
5.9%
복어탕 2
 
5.9%
삼겹살(국내산 2
 
5.9%
잔치국수 2
 
5.9%
한우a++갈비살 1
 
2.9%
돼지찌개 1
 
2.9%
능이닭백숙 1
 
2.9%
닭목살 1
 
2.9%
목살김치필라프 1
 
2.9%
Other values (19) 19
55.9%
2024-04-21T11:00:08.713918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 13
 
7.3%
) 8
 
4.5%
산 8
 
4.5%
( 8
 
4.5%
탕 7
 
4.0%
비 7
 
4.0%
삼 6
 
3.4%
살 6
 
3.4%
갈 6
 
3.4%
내 6
 
3.4%
Other values (66) 102
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 155
87.6%
Close Punctuation 8
 
4.5%
Open Punctuation 8
 
4.5%
Other Punctuation 2
 
1.1%
Math Symbol 2
 
1.1%
Uppercase Letter 1
 
0.6%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 13
 
8.4%
산 8
 
5.2%
탕 7
 
4.5%
비 7
 
4.5%
삼 6
 
3.9%
살 6
 
3.9%
갈 6
 
3.9%
내 6
 
3.9%
수 6
 
3.9%
어 4
 
2.6%
Other values (60) 86
55.5%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 155
87.6%
Common 21
 
11.9%
Latin 1
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 13
 
8.4%
산 8
 
5.2%
탕 7
 
4.5%
비 7
 
4.5%
삼 6
 
3.9%
살 6
 
3.9%
갈 6
 
3.9%
내 6
 
3.9%
수 6
 
3.9%
어 4
 
2.6%
Other values (60) 86
55.5%
Common
ValueCountFrequency (%)
) 8
38.1%
( 8
38.1%
, 2
 
9.5%
+ 2
 
9.5%
1
 
4.8%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 155
87.6%
ASCII 22
 
12.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 13
 
8.4%
산 8
 
5.2%
탕 7
 
4.5%
비 7
 
4.5%
삼 6
 
3.9%
살 6
 
3.9%
갈 6
 
3.9%
내 6
 
3.9%
수 6
 
3.9%
어 4
 
2.6%
Other values (60) 86
55.5%
ASCII
ValueCountFrequency (%)
) 8
36.4%
( 8
36.4%
, 2
 
9.1%
+ 2
 
9.1%
A 1
 
4.5%
1
 
4.5%

전화번호
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-04-21T11:00:09.448891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters408
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

Unique34 ?
Unique (%)100.0%

Sample

1st row053-955-7848
2nd row053-942-8495
3rd row053-981-9881
4th row053-943-6616
5th row053-983-3477
ValueCountFrequency (%)
053-955-7848 1
 
2.9%
053-942-8495 1
 
2.9%
053-814-0640 1
 
2.9%
053-982-7524 1
 
2.9%
053-944-5650 1
 
2.9%
053-965-0658 1
 
2.9%
053-965-9794 1
 
2.9%
053-751-1121 1
 
2.9%
053-959-2830 1
 
2.9%
053-958-7353 1
 
2.9%
Other values (24) 24
70.6%
2024-04-21T11:00:10.349056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 68
16.7%
5 61
15.0%
0 60
14.7%
3 49
12.0%
9 45
11.0%
8 28
6.9%
4 27
 
6.6%
2 21
 
5.1%
1 20
 
4.9%
6 17
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 340
83.3%
Dash Punctuation 68
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 61
17.9%
0 60
17.6%
3 49
14.4%
9 45
13.2%
8 28
8.2%
4 27
7.9%
2 21
 
6.2%
1 20
 
5.9%
6 17
 
5.0%
7 12
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 408
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 68
16.7%
5 61
15.0%
0 60
14.7%
3 49
12.0%
9 45
11.0%
8 28
6.9%
4 27
 
6.6%
2 21
 
5.1%
1 20
 
4.9%
6 17
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 68
16.7%
5 61
15.0%
0 60
14.7%
3 49
12.0%
9 45
11.0%
8 28
6.9%
4 27
 
6.6%
2 21
 
5.1%
1 20
 
4.9%
6 17
 
4.2%

행정동명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)47.1%
Missing0
Missing (%)0.0%
Memory size400.0 B
동촌동
4 
공산동
4 
불로.봉무동
3 
효목1동
3 
신암5동
2 
Other values (11)
18 

Length

Max length6
Median length4
Mean length3.7941176
Min length3

Unique

Unique4 ?
Unique (%)11.8%

Sample

1st row신암2동
2nd row신암5동
3rd row지저동
4th row신암3동
5th row불로.봉무동

Common Values

ValueCountFrequency (%)
동촌동 4
11.8%
공산동 4
11.8%
불로.봉무동 3
 
8.8%
효목1동 3
 
8.8%
신암5동 2
 
5.9%
신암3동 2
 
5.9%
신천3동 2
 
5.9%
신암1동 2
 
5.9%
신암4동 2
 
5.9%
효목2동 2
 
5.9%
Other values (6) 8
23.5%

Length

2024-04-21T11:00:10.588768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
동촌동 4
11.8%
공산동 4
11.8%
불로.봉무동 3
 
8.8%
효목1동 3
 
8.8%
신암5동 2
 
5.9%
신암3동 2
 
5.9%
신천3동 2
 
5.9%
신암1동 2
 
5.9%
신암4동 2
 
5.9%
효목2동 2
 
5.9%
Other values (6) 8
23.5%

법정동명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size400.0 B
신암동
9 
효목동
5 
신천동
4 
불로동
3 
검사동
3 
Other values (7)
10 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)11.8%

Sample

1st row신암동
2nd row신암동
3rd row지저동
4th row신암동
5th row불로동

Common Values

ValueCountFrequency (%)
신암동 9
26.5%
효목동 5
14.7%
신천동 4
11.8%
불로동 3
 
8.8%
검사동 3
 
8.8%
방촌동 2
 
5.9%
지묘동 2
 
5.9%
각산동 2
 
5.9%
지저동 1
 
2.9%
입석동 1
 
2.9%
Other values (2) 2
 
5.9%

Length

2024-04-21T11:00:10.803592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신암동 9
26.5%
효목동 5
14.7%
신천동 4
11.8%
불로동 3
 
8.8%
검사동 3
 
8.8%
방촌동 2
 
5.9%
지묘동 2
 
5.9%
각산동 2
 
5.9%
지저동 1
 
2.9%
입석동 1
 
2.9%
Other values (2) 2
 
5.9%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.893363
Minimum35.870624
Maximum35.990634
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T11:00:11.008394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.870624
5-th percentile35.87325
Q135.880403
median35.884067
Q335.889945
95-th percentile35.945617
Maximum35.990634
Range0.12001001
Interquartile range (IQR)0.0095410675

Descriptive statistics

Standard deviation0.026172155
Coefficient of variation (CV)0.0007291642
Kurtosis5.5249074
Mean35.893363
Median Absolute Deviation (MAD)0.004217625
Skewness2.323549
Sum1220.3743
Variance0.0006849817
MonotonicityNot monotonic
2024-04-21T11:00:11.234754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
35.88113773 1
 
2.9%
35.91045056 1
 
2.9%
35.8856554 1
 
2.9%
35.88617963 1
 
2.9%
35.87162715 1
 
2.9%
35.87491435 1
 
2.9%
35.88727613 1
 
2.9%
35.87725819 1
 
2.9%
35.87938708 1
 
2.9%
35.91135273 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
35.87062366 1
2.9%
35.87162715 1
2.9%
35.87412326 1
2.9%
35.87491435 1
2.9%
35.87725819 1
2.9%
35.87844487 1
2.9%
35.87888572 1
2.9%
35.87938708 1
2.9%
35.88031131 1
2.9%
35.88067989 1
2.9%
ValueCountFrequency (%)
35.99063367 1
2.9%
35.95393177 1
2.9%
35.94113913 1
2.9%
35.93869953 1
2.9%
35.91135273 1
2.9%
35.91045056 1
2.9%
35.90986622 1
2.9%
35.89662303 1
2.9%
35.89076166 1
2.9%
35.88749311 1
2.9%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.64437
Minimum128.61189
Maximum128.71784
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T11:00:11.461903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.61189
5-th percentile128.61498
Q1128.62971
median128.63906
Q3128.64743
95-th percentile128.70341
Maximum128.71784
Range0.1059574
Interquartile range (IQR)0.017718425

Descriptive statistics

Standard deviation0.026452503
Coefficient of variation (CV)0.00020562504
Kurtosis2.1408156
Mean128.64437
Median Absolute Deviation (MAD)0.00924285
Skewness1.5437518
Sum4373.9086
Variance0.00069973494
MonotonicityNot monotonic
2024-04-21T11:00:11.698165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
128.6118851 1
 
2.9%
128.6425017 1
 
2.9%
128.6357329 1
 
2.9%
128.6337545 1
 
2.9%
128.6296075 1
 
2.9%
128.6232105 1
 
2.9%
128.6411178 1
 
2.9%
128.6300287 1
 
2.9%
128.6399023 1
 
2.9%
128.6423428 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
128.6118851 1
2.9%
128.6148524 1
2.9%
128.6150491 1
2.9%
128.6176867 1
2.9%
128.6185413 1
2.9%
128.6232105 1
2.9%
128.6232875 1
2.9%
128.6267806 1
2.9%
128.6296075 1
2.9%
128.6300287 1
2.9%
ValueCountFrequency (%)
128.7178425 1
2.9%
128.7156793 1
2.9%
128.696797 1
2.9%
128.6938467 1
2.9%
128.668727 1
2.9%
128.660874 1
2.9%
128.654847 1
2.9%
128.6507629 1
2.9%
128.6476987 1
2.9%
128.6466288 1
2.9%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
2022-08-22
34 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-22
2nd row2022-08-22
3rd row2022-08-22
4th row2022-08-22
5th row2022-08-22

Common Values

ValueCountFrequency (%)
2022-08-22 34
100.0%

Length

2024-04-21T11:00:11.930007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:00:12.093726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-22 34
100.0%

Interactions

2024-04-21T11:00:02.417736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:00:02.130730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:00:02.558111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:00:02.272895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:00:12.204803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종업소명소재지취급품목(원산지)전화번호행정동명법정동명위도경도
업종1.0001.0001.0001.0001.0000.6870.8270.4990.249
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0001.0001.0001.000
취급품목(원산지)1.0001.0001.0001.0001.0000.5690.8790.3910.808
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
행정동명0.6871.0001.0000.5691.0001.0000.9420.8250.927
법정동명0.8271.0001.0000.8791.0000.9421.0000.9710.939
위도0.4991.0001.0000.3911.0000.8250.9711.0000.752
경도0.2491.0001.0000.8081.0000.9270.9390.7521.000
2024-04-21T11:00:12.401270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명업종행정동명
법정동명1.0000.5330.640
업종0.5331.0000.306
행정동명0.6400.3061.000
2024-04-21T11:00:12.549353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도업종행정동명법정동명
위도1.0000.3940.1760.4520.832
경도0.3941.0000.1320.5970.727
업종0.1760.1321.0000.3060.533
행정동명0.4520.5970.3061.0000.640
법정동명0.8320.7270.5330.6401.000

Missing values

2024-04-21T11:00:02.757383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:00:03.008341image/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

업종업소명소재지취급품목(원산지)전화번호행정동명법정동명위도경도데이터기준일
0한식대구삼계탕대구 동구 대현로 118-7(신암동)삼계탕053-955-7848신암2동신암동35.881138128.6118852022-08-22
1한식두곡동숯불갈비대구 동구 아양로49길 6(신암동)돼지왕갈비(국내산)053-942-8495신암5동신암동35.887307128.6387142022-08-22
2중식영남루반점대구 동구 해동로 18(지저동)자장면053-981-9881지저동지저동35.896623128.6376932022-08-22
3한식유정갈비대구 동구 아양로 6(신암동)왕갈비(국내산)053-943-6616신암3동신암동35.881032128.6148522022-08-22
4한식태종대대구 동구 팔공로24길 19-10(불로동)삼겹살(국내산)053-983-3477불로.봉무동불로동35.909866128.642222022-08-22
5한식팔공식당대구 동구 송라로32길 5(신암동)돌솥비빔밥053-941-1289신암3동신암동35.88068128.6150492022-08-22
6한식흥부고을숯불갈비대구 동구 동촌로 80-14(검사동)돼지갈비(독일,칠레산)053-986-0092동촌동검사동35.887026128.6507632022-08-22
7한식고향손칼국수대구 동구 장등로 35(신천동)잔치국수053-752-8894신천3동신천동35.870624128.6232882022-08-22
8한식미진손칼국수대구 동구 아양로50길 119-1(효목동)손칼국수053-941-4664효목1동효목동35.882463128.6428292022-08-22
9한식이가숯불갈비대구 동구 아양로 37-4(신암동)돼지갈비(국내산,미국산)053-958-7353신암1동신암동35.882555128.6185412022-08-22
업종업소명소재지취급품목(원산지)전화번호행정동명법정동명위도경도데이터기준일
24한식면사랑칼국수대구 동구 효동로 126, 2층(효목동)칼국수053-954-2001효목1동효목동35.887276128.6411182022-08-22
25미용업헐리우드 헤어대구 동구 동부로 162(신천동)헤어컷(남성)053-000-0000신천4동신천동35.877258128.6300292022-08-22
26한식부산복해물칼국수대구 동구 팔공로28길 8-10(불로동)복어탕053-959-2830불로.봉무동불로동35.910451128.6425022022-08-22
27세탁업태왕세탁소대구 동구 동북로 500, 603-115(효목동, 태왕메트로시티)드라이053-751-1121효목2동효목동35.879387128.6399022022-08-22
28기타양식(제과점)미소띤하루대구 동구 이노밸리로 168, 103호(각산동, 안심빌딩)소보로빵053-965-9794혁신동각산동35.878445128.7156792022-08-22
29양식파스타누오바대구 동구 과학로 13길 8, 1층 103호(각산동)목살김치필라프053-965-0658혁신동각산동35.884966128.7178422022-08-22
30한식신산홍대구 동구 아양로7길 12, 가상가동 지하1층 108호(신암동, 신암뜨란채)닭목살053-944-5650신암1동신암동35.882334128.6176872022-08-22
31한식만보대구 동구 팔공로209길 15(백안동)칼국수053-982-7524공산동백안동35.953932128.6938472022-08-22
32한식가원식당대구 동구 팔공산로199길 6-3(용수동)능이닭백숙053-814-0640공산동용수동35.990634128.6967972022-08-22
33한식공산숯불갈비대구 동구 파계로22길 40(지묘동)왕갈비053-983-9233공산동지묘동35.941139128.6393372022-08-22