Overview

Dataset statistics

Number of variables5
Number of observations413
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.7 KiB
Average record size in memory41.3 B

Variable types

Numeric1
Categorical2
Text2

Dataset

Description경상북도 시군의 착한가격업소명, 업종, 주소 현황입니다(경상북도 착한가격업소의 시군별 업종, 업소명, 도로명 주소 현황입니다. )
Author경상북도
URLhttps://www.data.go.kr/data/3073794/fileData.do

Alerts

구분 is highly overall correlated with 시군High correlation
시군 is highly overall correlated with 구분High correlation
구분 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:16:39.707001
Analysis finished2023-12-12 07:16:40.400641
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct413
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean207
Minimum1
Maximum413
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-12T16:16:40.481770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.6
Q1104
median207
Q3310
95-th percentile392.4
Maximum413
Range412
Interquartile range (IQR)206

Descriptive statistics

Standard deviation119.36708
Coefficient of variation (CV)0.57665256
Kurtosis-1.2
Mean207
Median Absolute Deviation (MAD)103
Skewness0
Sum85491
Variance14248.5
MonotonicityStrictly increasing
2023-12-12T16:16:40.618765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
273 1
 
0.2%
283 1
 
0.2%
282 1
 
0.2%
281 1
 
0.2%
280 1
 
0.2%
279 1
 
0.2%
278 1
 
0.2%
277 1
 
0.2%
276 1
 
0.2%
Other values (403) 403
97.6%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
413 1
0.2%
412 1
0.2%
411 1
0.2%
410 1
0.2%
409 1
0.2%
408 1
0.2%
407 1
0.2%
406 1
0.2%
405 1
0.2%
404 1
0.2%

시군
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
포항시 남구
41 
영주시
41 
상주시
32 
포항시 북구
29 
문경시
29 
Other values (19)
241 

Length

Max length6
Median length3
Mean length3.5084746
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
포항시 남구 41
 
9.9%
영주시 41
 
9.9%
상주시 32
 
7.7%
포항시 북구 29
 
7.0%
문경시 29
 
7.0%
안동시 27
 
6.5%
의성군 26
 
6.3%
구미시 23
 
5.6%
김천시 22
 
5.3%
경주시 21
 
5.1%
Other values (14) 122
29.5%

Length

2023-12-12T16:16:40.777551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
포항시 70
14.5%
남구 41
 
8.5%
영주시 41
 
8.5%
상주시 32
 
6.6%
북구 29
 
6.0%
문경시 29
 
6.0%
안동시 27
 
5.6%
의성군 26
 
5.4%
구미시 23
 
4.8%
김천시 22
 
4.6%
Other values (15) 143
29.6%

업종
Categorical

Distinct11
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
한식
243 
이미용업
83 
중식
28 
세탁업
 
24
목욕업
 
14
Other values (6)
 
21

Length

Max length6
Median length2
Mean length2.5835351
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
한식 243
58.8%
이미용업 83
 
20.1%
중식 28
 
6.8%
세탁업 24
 
5.8%
목욕업 14
 
3.4%
기타양식 8
 
1.9%
기타서비스업 4
 
1.0%
일식 3
 
0.7%
숙박업 3
 
0.7%
양식 2
 
0.5%

Length

2023-12-12T16:16:40.916037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 243
58.8%
이미용업 83
 
20.1%
중식 28
 
6.8%
세탁업 24
 
5.8%
목욕업 14
 
3.4%
기타양식 8
 
1.9%
기타서비스업 4
 
1.0%
일식 3
 
0.7%
숙박업 3
 
0.7%
양식 2
 
0.5%

업소명
Text

Distinct403
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2023-12-12T16:16:41.211971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.2469734
Min length2

Characters and Unicode

Total characters2167
Distinct characters366
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique396 ?
Unique (%)95.9%

Sample

1st row엘리트 독서실
2nd row대홍화루
3rd row마이따친친
4th row모퉁이식당
5th row산수식당
ValueCountFrequency (%)
미용실 7
 
1.6%
고향식당 3
 
0.7%
밀양돼지국밥 3
 
0.7%
시장식당 3
 
0.7%
엄마손칼국수 2
 
0.5%
현 2
 
0.5%
헤어샵 2
 
0.5%
중앙식육식당 2
 
0.5%
미성식당 2
 
0.5%
자갈마당 2
 
0.5%
Other values (407) 407
93.6%
2023-12-12T16:16:41.632344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 139
 
6.4%
당 104
 
4.8%
미 71
 
3.3%
용 45
 
2.1%
실 42
 
1.9%
리 41
 
1.9%
이 31
 
1.4%
소 30
 
1.4%
한 28
 
1.3%
우 27
 
1.2%
Other values (356) 1609
74.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2138
98.7%
Space Separator 22
 
1.0%
Decimal Number 6
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 139
 
6.5%
당 104
 
4.9%
미 71
 
3.3%
용 45
 
2.1%
실 42
 
2.0%
리 41
 
1.9%
이 31
 
1.4%
소 30
 
1.4%
한 28
 
1.3%
우 27
 
1.3%
Other values (351) 1580
73.9%
Decimal Number
ValueCountFrequency (%)
0 4
66.7%
1 1
 
16.7%
2 1
 
16.7%
Space Separator
ValueCountFrequency (%)
22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2138
98.7%
Common 29
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 139
 
6.5%
당 104
 
4.9%
미 71
 
3.3%
용 45
 
2.1%
실 42
 
2.0%
리 41
 
1.9%
이 31
 
1.4%
소 30
 
1.4%
한 28
 
1.3%
우 27
 
1.3%
Other values (351) 1580
73.9%
Common
ValueCountFrequency (%)
22
75.9%
0 4
 
13.8%
1 1
 
3.4%
, 1
 
3.4%
2 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2138
98.7%
ASCII 29
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 139
 
6.5%
당 104
 
4.9%
미 71
 
3.3%
용 45
 
2.1%
실 42
 
2.0%
리 41
 
1.9%
이 31
 
1.4%
소 30
 
1.4%
한 28
 
1.3%
우 27
 
1.3%
Other values (351) 1580
73.9%
ASCII
ValueCountFrequency (%)
22
75.9%
0 4
 
13.8%
1 1
 
3.4%
, 1
 
3.4%
2 1
 
3.4%

주소
Text

Distinct409
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2023-12-12T16:16:41.909935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length31
Mean length18.699758
Min length10

Characters and Unicode

Total characters7723
Distinct characters218
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

Unique406 ?
Unique (%)98.3%

Sample

1st row경상북도경산시원효로 144
2nd row경상북도경산시삼풍로 6길 2
3rd row경상북도경산시삼풍로 6길
4th row경상북도경산시자인면 일연로 43
5th row경상북도경산시와촌면 금송로 423
ValueCountFrequency (%)
경상북도포항시 70
 
6.0%
경상북도의성군의성읍 12
 
1.0%
15 10
 
0.9%
남구오천읍 10
 
0.9%
경상북도성주군성주읍 9
 
0.8%
경상북도군위군군위읍 8
 
0.7%
19 8
 
0.7%
경상북도영양군영양읍 8
 
0.7%
11 7
 
0.6%
경상북도안동시경동로 7
 
0.6%
Other values (728) 1017
87.2%
2023-12-12T16:16:42.393443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
753
 
9.8%
경 512
 
6.6%
상 476
 
6.2%
북 460
 
6.0%
도 452
 
5.9%
시 359
 
4.6%
1 356
 
4.6%
길 247
 
3.2%
로 245
 
3.2%
2 196
 
2.5%
Other values (208) 3667
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5430
70.3%
Decimal Number 1356
 
17.6%
Space Separator 753
 
9.8%
Dash Punctuation 121
 
1.6%
Open Punctuation 25
 
0.3%
Close Punctuation 25
 
0.3%
Other Punctuation 12
 
0.2%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 512
 
9.4%
상 476
 
8.8%
북 460
 
8.5%
도 452
 
8.3%
시 359
 
6.6%
길 247
 
4.5%
로 245
 
4.5%
군 161
 
3.0%
주 141
 
2.6%
읍 112
 
2.1%
Other values (192) 2265
41.7%
Decimal Number
ValueCountFrequency (%)
1 356
26.3%
2 196
14.5%
3 145
10.7%
5 138
 
10.2%
4 124
 
9.1%
6 95
 
7.0%
0 84
 
6.2%
7 80
 
5.9%
9 73
 
5.4%
8 65
 
4.8%
Space Separator
ValueCountFrequency (%)
753
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5430
70.3%
Common 2292
29.7%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 512
 
9.4%
상 476
 
8.8%
북 460
 
8.5%
도 452
 
8.3%
시 359
 
6.6%
길 247
 
4.5%
로 245
 
4.5%
군 161
 
3.0%
주 141
 
2.6%
읍 112
 
2.1%
Other values (192) 2265
41.7%
Common
ValueCountFrequency (%)
753
32.9%
1 356
15.5%
2 196
 
8.6%
3 145
 
6.3%
5 138
 
6.0%
4 124
 
5.4%
- 121
 
5.3%
6 95
 
4.1%
0 84
 
3.7%
7 80
 
3.5%
Other values (5) 200
 
8.7%
Latin
ValueCountFrequency (%)
D 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5430
70.3%
ASCII 2293
29.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
753
32.8%
1 356
15.5%
2 196
 
8.5%
3 145
 
6.3%
5 138
 
6.0%
4 124
 
5.4%
- 121
 
5.3%
6 95
 
4.1%
0 84
 
3.7%
7 80
 
3.5%
Other values (6) 201
 
8.8%
Hangul
ValueCountFrequency (%)
경 512
 
9.4%
상 476
 
8.8%
북 460
 
8.5%
도 452
 
8.3%
시 359
 
6.6%
길 247
 
4.5%
로 245
 
4.5%
군 161
 
3.0%
주 141
 
2.6%
읍 112
 
2.1%
Other values (192) 2265
41.7%

Interactions

2023-12-12T16:16:40.076530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:16:42.529490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시군업종
구분1.0000.9770.498
시군0.9771.0000.662
업종0.4980.6621.000
2023-12-12T16:16:42.606798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종시군
업종1.0000.305
시군0.3051.000
2023-12-12T16:16:42.693233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시군업종
구분1.0000.8500.173
시군0.8501.0000.305
업종0.1730.3051.000

Missing values

2023-12-12T16:16:40.213193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:16:40.361991image/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

구분시군업종업소명주소
01경산시기타서비스업엘리트 독서실경상북도경산시원효로 144
12경산시중식대홍화루경상북도경산시삼풍로 6길 2
23경산시중식마이따친친경상북도경산시삼풍로 6길
34경산시한식모퉁이식당경상북도경산시자인면 일연로 43
45경산시한식산수식당경상북도경산시와촌면 금송로 423
56경산시한식토속정경상북도경산시진량읍 낙산길 29
67경산시중식신동아반점경상북도경산시중앙로 17길 37
78경산시중식연경 짬뽕 전문점경상북도경산시삼풍로 6길 8
89경산시이미용업황실미용실경상북도경산시경안로 41길 11
910경산시이미용업미스,미스터 미용실경상북도경산시중앙로 15
구분시군업종업소명주소
403404포항시 북구한식미성식당경상북도포항시 북구삼호로 253번길 3
404405포항시 북구이미용업미스터임 미용실경상북도포항시 북구새천년대로 1123 217호
405406포항시 북구이미용업송영철남성헤어커트경상북도포항시 북구새마을로 3
406407포항시 북구이미용업미헤어 코디경상북도포항시 북구중흥로 171번길19
407408포항시 북구이미용업선린 미용실경상북도포항시 북구대신로 35번길 7
408409포항시 북구이미용업웰스남성헤어경상북도포항시 북구학전로 24-2
409410포항시 북구목욕업파라다이스경상북도포항시 북구흥해읍 초곡길 81
410411포항시 북구이미용업동백미용실경상북도포항시 북구흥해읍 흥해로 69
411412포항시 북구이미용업김은숙헤어세상경상북도포항시 북구흥해읍 중성로32번길 14(1층)
412413포항시 북구이미용업박윤미헤어모드경상북도포항시 북구흥해읍 흥해로85번길 5