Overview

Dataset statistics

Number of variables8
Number of observations40
Missing cells9
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory68.2 B

Variable types

Numeric1
DateTime1
Categorical2
Text4

Dataset

Description대구서구 관내에 위치한 착한가격, 청결하고 좋은 서비스를 제공하는 착한가격업소 공개에 대한 데이터로 가격, 위치등을 제공합니다.
Author대구광역시 서구
URLhttps://www.data.go.kr/data/3071988/fileData.do

Alerts

전화번호 has 9 (22.5%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:57:55.048275
Analysis finished2024-03-14 12:57:56.533834
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size488.0 B
2024-03-14T21:57:56.736358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2024-03-14T21:57:57.180324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

지정일자
Date

Distinct22
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
Minimum2011-11-01 00:00:00
Maximum2023-10-14 00:00:00
2024-03-14T21:57:57.556020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:57:57.940368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

업종
Categorical

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
한식
26 
이미용업
9 
중식
3 
미용업
 
1
기타
 
1

Length

Max length4
Median length2
Mean length2.475
Min length2

Unique

Unique2 ?
Unique (%)5.0%

Sample

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

Common Values

ValueCountFrequency (%)
한식 26
65.0%
이미용업 9
 
22.5%
중식 3
 
7.5%
미용업 1
 
2.5%
기타 1
 
2.5%

Length

2024-03-14T21:57:58.298544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:57:58.513243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 26
65.0%
이미용업 9
 
22.5%
중식 3
 
7.5%
미용업 1
 
2.5%
기타 1
 
2.5%

업소명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
2024-03-14T21:57:59.346338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length4.8
Min length3

Characters and Unicode

Total characters192
Distinct characters101
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row금성숯불식당
2nd row혜인미용실
3rd row덕성반점
4th row쌍둥이정갈비
5th row아란미용실
ValueCountFrequency (%)
금성숯불식당 1
 
2.5%
혜인미용실 1
 
2.5%
돈장군숯불갈비 1
 
2.5%
엄마떡볶이 1
 
2.5%
시골통닭 1
 
2.5%
원대시장횟집 1
 
2.5%
풍미식당 1
 
2.5%
내당칼국수 1
 
2.5%
대청마루 1
 
2.5%
동경식당 1
 
2.5%
Other values (30) 30
75.0%
2024-03-14T21:58:00.425790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
미 9
 
4.7%
용 8
 
4.2%
당 7
 
3.6%
실 7
 
3.6%
식 6
 
3.1%
국 6
 
3.1%
성 5
 
2.6%
칼 4
 
2.1%
이 4
 
2.1%
밥 4
 
2.1%
Other values (91) 132
68.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 192
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 9
 
4.7%
용 8
 
4.2%
당 7
 
3.6%
실 7
 
3.6%
식 6
 
3.1%
국 6
 
3.1%
성 5
 
2.6%
칼 4
 
2.1%
이 4
 
2.1%
밥 4
 
2.1%
Other values (91) 132
68.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 192
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 9
 
4.7%
용 8
 
4.2%
당 7
 
3.6%
실 7
 
3.6%
식 6
 
3.1%
국 6
 
3.1%
성 5
 
2.6%
칼 4
 
2.1%
이 4
 
2.1%
밥 4
 
2.1%
Other values (91) 132
68.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 192
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
미 9
 
4.7%
용 8
 
4.2%
당 7
 
3.6%
실 7
 
3.6%
식 6
 
3.1%
국 6
 
3.1%
성 5
 
2.6%
칼 4
 
2.1%
이 4
 
2.1%
밥 4
 
2.1%
Other values (91) 132
68.8%

주소
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
2024-03-14T21:58:01.276966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length20.725
Min length15

Characters and Unicode

Total characters829
Distinct characters49
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

Unique38 ?
Unique (%)95.0%

Sample

1st row대구광역시 서구 팔달로 186-1
2nd row대구광역시 서구 고성로 17
3rd row대구광역시 서구 문화로49길 5-1
4th row대구광역시 서구 국채보상로 197
5th row대구광역시 서구 통학로13길 15
ValueCountFrequency (%)
대구광역시 40
24.4%
서구 40
24.4%
달서로54길 4
 
2.4%
13 4
 
2.4%
달구벌대로361길 3
 
1.8%
문화로 3
 
1.8%
6 3
 
1.8%
문화로49길 2
 
1.2%
5-1 2
 
1.2%
국채보상로 2
 
1.2%
Other values (58) 61
37.2%
2024-03-14T21:58:02.427274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
124
15.0%
구 86
 
10.4%
서 52
 
6.3%
대 46
 
5.5%
1 43
 
5.2%
광 40
 
4.8%
역 40
 
4.8%
시 40
 
4.8%
로 40
 
4.8%
길 30
 
3.6%
Other values (39) 288
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 502
60.6%
Decimal Number 161
 
19.4%
Space Separator 124
 
15.0%
Open Punctuation 14
 
1.7%
Close Punctuation 14
 
1.7%
Dash Punctuation 13
 
1.6%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 86
17.1%
서 52
10.4%
대 46
9.2%
광 40
8.0%
역 40
8.0%
시 40
8.0%
로 40
8.0%
길 30
 
6.0%
달 16
 
3.2%
동 14
 
2.8%
Other values (24) 98
19.5%
Decimal Number
ValueCountFrequency (%)
1 43
26.7%
3 25
15.5%
5 18
11.2%
2 16
 
9.9%
4 15
 
9.3%
6 13
 
8.1%
7 12
 
7.5%
8 7
 
4.3%
9 6
 
3.7%
0 6
 
3.7%
Space Separator
ValueCountFrequency (%)
124
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 502
60.6%
Common 326
39.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 86
17.1%
서 52
10.4%
대 46
9.2%
광 40
8.0%
역 40
8.0%
시 40
8.0%
로 40
8.0%
길 30
 
6.0%
달 16
 
3.2%
동 14
 
2.8%
Other values (24) 98
19.5%
Common
ValueCountFrequency (%)
124
38.0%
1 43
 
13.2%
3 25
 
7.7%
5 18
 
5.5%
2 16
 
4.9%
4 15
 
4.6%
( 14
 
4.3%
) 14
 
4.3%
- 13
 
4.0%
6 13
 
4.0%
Other values (4) 31
 
9.5%
Latin
ValueCountFrequency (%)
a 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 502
60.6%
ASCII 327
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
124
37.9%
1 43
 
13.1%
3 25
 
7.6%
5 18
 
5.5%
2 16
 
4.9%
4 15
 
4.6%
( 14
 
4.3%
) 14
 
4.3%
- 13
 
4.0%
6 13
 
4.0%
Other values (5) 32
 
9.8%
Hangul
ValueCountFrequency (%)
구 86
17.1%
서 52
10.4%
대 46
9.2%
광 40
8.0%
역 40
8.0%
시 40
8.0%
로 40
8.0%
길 30
 
6.0%
달 16
 
3.2%
동 14
 
2.8%
Other values (24) 98
19.5%

전화번호
Text

MISSING 

Distinct31
Distinct (%)100.0%
Missing9
Missing (%)22.5%
Memory size448.0 B
2024-03-14T21:58:03.177860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters372
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

Unique31 ?
Unique (%)100.0%

Sample

1st row053-354-8216
2nd row053-353-5526
3rd row053-555-6623
4th row053-552-9716
5th row053-557-0890
ValueCountFrequency (%)
053-354-8216 1
 
3.2%
053-981-0810 1
 
3.2%
053-552-8402 1
 
3.2%
053-523-2030 1
 
3.2%
053-522-8828 1
 
3.2%
053-523-3840 1
 
3.2%
053-564-0068 1
 
3.2%
053-522-7922 1
 
3.2%
053-565-9588 1
 
3.2%
053-552-6125 1
 
3.2%
Other values (21) 21
67.7%
2024-03-14T21:58:04.125600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 84
22.6%
- 62
16.7%
0 50
13.4%
3 50
13.4%
2 32
 
8.6%
1 19
 
5.1%
8 18
 
4.8%
6 18
 
4.8%
7 16
 
4.3%
4 15
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 310
83.3%
Dash Punctuation 62
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 84
27.1%
0 50
16.1%
3 50
16.1%
2 32
 
10.3%
1 19
 
6.1%
8 18
 
5.8%
6 18
 
5.8%
7 16
 
5.2%
4 15
 
4.8%
9 8
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 372
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 84
22.6%
- 62
16.7%
0 50
13.4%
3 50
13.4%
2 32
 
8.6%
1 19
 
5.1%
8 18
 
4.8%
6 18
 
4.8%
7 16
 
4.3%
4 15
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 84
22.6%
- 62
16.7%
0 50
13.4%
3 50
13.4%
2 32
 
8.6%
1 19
 
5.1%
8 18
 
4.8%
6 18
 
4.8%
7 16
 
4.3%
4 15
 
4.0%

대표메뉴
Text

Distinct30
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
2024-03-14T21:58:04.785345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length3.925
Min length2

Characters and Unicode

Total characters157
Distinct characters74
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)65.0%

Sample

1st row불고기
2nd row퍼머
3rd row자장면
4th row돼지갈비(160g)
5th row퍼머
ValueCountFrequency (%)
커트 5
 
12.2%
퍼머 4
 
9.8%
자장면 3
 
7.3%
정식 2
 
4.9%
아메리카노 1
 
2.4%
들깨칼국수 1
 
2.4%
자연김밥 1
 
2.4%
물회 1
 
2.4%
추어탕 1
 
2.4%
정식(2인분 1
 
2.4%
Other values (21) 21
51.2%
2024-03-14T21:58:05.745148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 7
 
4.5%
커 6
 
3.8%
트 6
 
3.8%
장 6
 
3.8%
수 6
 
3.8%
식 5
 
3.2%
) 5
 
3.2%
( 5
 
3.2%
칼 5
 
3.2%
정 5
 
3.2%
Other values (64) 101
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
87.3%
Decimal Number 7
 
4.5%
Close Punctuation 5
 
3.2%
Open Punctuation 5
 
3.2%
Lowercase Letter 2
 
1.3%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 7
 
5.1%
커 6
 
4.4%
트 6
 
4.4%
장 6
 
4.4%
수 6
 
4.4%
식 5
 
3.6%
칼 5
 
3.6%
정 5
 
3.6%
지 4
 
2.9%
퍼 4
 
2.9%
Other values (56) 83
60.6%
Decimal Number
ValueCountFrequency (%)
2 2
28.6%
0 2
28.6%
1 2
28.6%
6 1
14.3%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136
86.6%
Common 18
 
11.5%
Latin 2
 
1.3%
Han 1
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 7
 
5.1%
커 6
 
4.4%
트 6
 
4.4%
장 6
 
4.4%
수 6
 
4.4%
식 5
 
3.7%
칼 5
 
3.7%
정 5
 
3.7%
지 4
 
2.9%
퍼 4
 
2.9%
Other values (55) 82
60.3%
Common
ValueCountFrequency (%)
) 5
27.8%
( 5
27.8%
2 2
 
11.1%
0 2
 
11.1%
1 2
 
11.1%
1
 
5.6%
6 1
 
5.6%
Latin
ValueCountFrequency (%)
g 2
100.0%
Han
ValueCountFrequency (%)
大 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136
86.6%
ASCII 20
 
12.7%
CJK 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 7
 
5.1%
커 6
 
4.4%
트 6
 
4.4%
장 6
 
4.4%
수 6
 
4.4%
식 5
 
3.7%
칼 5
 
3.7%
정 5
 
3.7%
지 4
 
2.9%
퍼 4
 
2.9%
Other values (55) 82
60.3%
ASCII
ValueCountFrequency (%)
) 5
25.0%
( 5
25.0%
2 2
 
10.0%
g 2
 
10.0%
0 2
 
10.0%
1 2
 
10.0%
1
 
5.0%
6 1
 
5.0%
CJK
ValueCountFrequency (%)
大 1
100.0%

대표매뉴가격
Categorical

Distinct18
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
8000
7 
10000
5 
7000
4 
3000
3 
6000
3 
Other values (13)
18 

Length

Max length6
Median length4
Mean length4.4
Min length4

Unique

Unique8 ?
Unique (%)20.0%

Sample

1st row10000
2nd row20000
3rd row3000
4th row6000
5th row25000

Common Values

ValueCountFrequency (%)
8000 7
17.5%
10000 5
12.5%
7000 4
10.0%
3000 3
 
7.5%
6000 3
 
7.5%
4000 2
 
5.0%
5,000 2
 
5.0%
8,000 2
 
5.0%
5500 2
 
5.0%
25000 2
 
5.0%
Other values (8) 8
20.0%

Length

2024-03-14T21:58:05.984952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
8000 7
17.5%
10000 5
12.5%
7000 4
10.0%
3000 3
 
7.5%
6000 3
 
7.5%
8,000 2
 
5.0%
5500 2
 
5.0%
25000 2
 
5.0%
5,000 2
 
5.0%
4000 2
 
5.0%
Other values (8) 8
20.0%

Interactions

2024-03-14T21:57:55.601807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:58:06.227327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지정일자업종업소명주소전화번호대표메뉴대표매뉴가격
연번1.0000.8890.1751.0000.9321.0000.6790.473
지정일자0.8891.0000.6141.0001.0001.0000.8410.000
업종0.1750.6141.0001.0001.0001.0001.0000.730
업소명1.0001.0001.0001.0001.0001.0001.0001.000
주소0.9321.0001.0001.0001.0001.0000.9560.981
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
대표메뉴0.6790.8411.0001.0000.9561.0001.0000.896
대표매뉴가격0.4730.0000.7301.0000.9811.0000.8961.000
2024-03-14T21:58:06.420478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대표매뉴가격업종
대표매뉴가격1.0000.370
업종0.3701.000
2024-03-14T21:58:06.559099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종대표매뉴가격
연번1.0000.0000.128
업종0.0001.0000.370
대표매뉴가격0.1280.3701.000

Missing values

2024-03-14T21:57:55.966252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:57:56.375162image/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

연번지정일자업종업소명주소전화번호대표메뉴대표매뉴가격
012011-11-01한식금성숯불식당대구광역시 서구 팔달로 186-1053-354-8216불고기10000
122011-11-01이미용업혜인미용실대구광역시 서구 고성로 17053-353-5526퍼머20000
232011-11-01중식덕성반점대구광역시 서구 문화로49길 5-1053-555-6623자장면3000
342011-11-01한식쌍둥이정갈비대구광역시 서구 국채보상로 197053-552-9716돼지갈비(160g)6000
452011-11-01이미용업아란미용실대구광역시 서구 통학로13길 15053-557-0890퍼머25000
562011-11-01이미용업성화미용실대구광역시 서구 달서로17길 17 105호053-561-0174퍼머25000
672012-06-01중식금성각대구광역시 서구 당산로47길 69 일신a상가 105053-562-8877자장면3000
782012-06-01한식이모김밥대구광역시 서구 달서로 136-1053-555-8807된장찌개5500
892012-06-01한식초원식당대구광역시 서구 문화로47길 6053-521-3780칼국수4000
9102013-06-01한식소백산식당대구광역시 서구 북비산로 160053-553-2421삼겹살(120g)8000
연번지정일자업종업소명주소전화번호대표메뉴대표매뉴가격
30312023-10-05한식추어나루대구광역시 서구 문화로 337(비산동)053-522-7922추어탕8000
31322023-10-06기타커피먼저대구광역시 서구 평리로 413 (평리동)<NA>아메리카노2000
32332023-10-07중식대국성반점대구광역시 서구 국채보상로 300(평리동)053-564-0068자장면5500
33342023-10-08한식자연김밥대구광역시 서구 문화로49길 12-1(평리동)053-523-3840자연김밥2500
34352023-10-09한식청하식당대구광역시 서구 문화로 241-1(평리동)053-522-8828정식6000
35362023-10-10이미용업손길헤어대구광역시 서구 국채보상로52길 33(평리동)<NA>커트10000
36372023-10-11한식들깨칼국수대구광역시 서구 통학로17길 23(평리동)<NA>들깨칼국수7000
37382023-10-12한식미주싱싱바지락칼국수대구광역시 서구 국채보상로46길 54(평리동)053-523-2030바지락칼국수8000
38392023-10-13한식돼지새끼대구광역시 서구 서대구로2길 48(내당동)053-565-0371삽겹살9000
39402023-10-14한식평리통닭대구광역시 서구 통학로13길 18(평리동)<NA>후라이드10000