Overview

Dataset statistics

Number of variables14
Number of observations43
Missing cells95
Missing cells (%)15.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory116.1 B

Variable types

Numeric1
Categorical6
Text7

Dataset

Description충청북도 충주시 착한가격업소에 대한 데이터 제공(업종, 업소명, 주소, 연락처, 품목1~3, 가격1~3, 지정일, 시도명, 시군구명, 읍면동)
Author충청북도 충주시
URLhttps://www.data.go.kr/data/3074344/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
연번 is highly overall correlated with 읍면동High correlation
업종 is highly overall correlated with 가격1 and 1 other fieldsHigh correlation
읍면동 is highly overall correlated with 연번High correlation
가격1 is highly overall correlated with 업종High correlation
가격2 is highly overall correlated with 업종High correlation
연락처 has 2 (4.7%) missing valuesMissing
품목2 has 21 (48.8%) missing valuesMissing
품목3 has 36 (83.7%) missing valuesMissing
가격3 has 36 (83.7%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:48:18.704365
Analysis finished2023-12-12 23:48:19.853721
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-13T08:48:19.924508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.1
Q111.5
median22
Q332.5
95-th percentile40.9
Maximum43
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.57075176
Kurtosis-1.2
Mean22
Median Absolute Deviation (MAD)11
Skewness0
Sum946
Variance157.66667
MonotonicityStrictly increasing
2023-12-13T08:48:20.039277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1
 
2.3%
2 1
 
2.3%
25 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%
34 1
2.3%

업종
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
한식
32 
이용업
 
3
미용업
 
2
기타비요식업
 
2
숙박업
 
1
Other values (3)
 
3

Length

Max length6
Median length2
Mean length2.4186047
Min length2

Unique

Unique4 ?
Unique (%)9.3%

Sample

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

Common Values

ValueCountFrequency (%)
한식 32
74.4%
이용업 3
 
7.0%
미용업 2
 
4.7%
기타비요식업 2
 
4.7%
숙박업 1
 
2.3%
중식 1
 
2.3%
세탁업 1
 
2.3%
기타요식업 1
 
2.3%

Length

2023-12-13T08:48:20.155119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:48:20.268459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 32
74.4%
이용업 3
 
7.0%
미용업 2
 
4.7%
기타비요식업 2
 
4.7%
숙박업 1
 
2.3%
중식 1
 
2.3%
세탁업 1
 
2.3%
기타요식업 1
 
2.3%

업소명
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-13T08:48:20.512944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.1395349
Min length2

Characters and Unicode

Total characters221
Distinct characters134
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row헤어센스미용실
2nd row청향가든
3rd row메밀마당
4th row버드나무집
5th row마사밥상슈퍼
ValueCountFrequency (%)
헤어센스미용실 1
 
2.3%
양지찐빵 1
 
2.3%
청춘밥상(시니어클럽 1
 
2.3%
금강감자탕 1
 
2.3%
청정야채버섯칼국수 1
 
2.3%
은영갈비 1
 
2.3%
연수꽃화원 1
 
2.3%
하나미용실 1
 
2.3%
오륙도식육식당 1
 
2.3%
박가네식당 1
 
2.3%
Other values (33) 33
76.7%
2023-12-13T08:48:20.869581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 10
 
4.5%
당 7
 
3.2%
식 7
 
3.2%
국 6
 
2.7%
이 5
 
2.3%
밥 5
 
2.3%
용 4
 
1.8%
칼 4
 
1.8%
상 4
 
1.8%
가 4
 
1.8%
Other values (124) 165
74.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 219
99.1%
Close Punctuation 1
 
0.5%
Open Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 10
 
4.6%
당 7
 
3.2%
식 7
 
3.2%
국 6
 
2.7%
이 5
 
2.3%
밥 5
 
2.3%
용 4
 
1.8%
칼 4
 
1.8%
상 4
 
1.8%
가 4
 
1.8%
Other values (122) 163
74.4%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 219
99.1%
Common 2
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 10
 
4.6%
당 7
 
3.2%
식 7
 
3.2%
국 6
 
2.7%
이 5
 
2.3%
밥 5
 
2.3%
용 4
 
1.8%
칼 4
 
1.8%
상 4
 
1.8%
가 4
 
1.8%
Other values (122) 163
74.4%
Common
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 219
99.1%
ASCII 2
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 10
 
4.6%
당 7
 
3.2%
식 7
 
3.2%
국 6
 
2.7%
이 5
 
2.3%
밥 5
 
2.3%
용 4
 
1.8%
칼 4
 
1.8%
상 4
 
1.8%
가 4
 
1.8%
Other values (122) 163
74.4%
ASCII
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
충청북도
43 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청북도 43
100.0%

Length

2023-12-13T08:48:21.000282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:48:21.098773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청북도 43
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
충주시
43 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충주시 43
100.0%

Length

2023-12-13T08:48:21.201253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:48:21.286122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충주시 43
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Memory size476.0 B
교현안림동
7 
문화동
6 
교현2동
4 
성내충인동
4 
엄정면
3 
Other values (12)
19 

Length

Max length5
Median length3
Mean length3.8139535
Min length3

Unique

Unique5 ?
Unique (%)11.6%

Sample

1st row신니면
2nd row노은면
3rd row중앙탑면
4th row금가면
5th row금가면

Common Values

ValueCountFrequency (%)
교현안림동 7
16.3%
문화동 6
14.0%
교현2동 4
9.3%
성내충인동 4
9.3%
엄정면 3
 
7.0%
금가면 2
 
4.7%
동량면 2
 
4.7%
목행용탄동 2
 
4.7%
지현동 2
 
4.7%
호암직동 2
 
4.7%
Other values (7) 9
20.9%

Length

2023-12-13T08:48:21.415561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교현안림동 7
16.3%
문화동 6
14.0%
교현2동 4
9.3%
성내충인동 4
9.3%
엄정면 3
 
7.0%
용산동 2
 
4.7%
연수동 2
 
4.7%
호암직동 2
 
4.7%
지현동 2
 
4.7%
목행용탄동 2
 
4.7%
Other values (7) 9
20.9%

주소
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-13T08:48:21.652086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length13.093023
Min length9

Characters and Unicode

Total characters563
Distinct characters82
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row충주시 신니면 용원1길3
2nd row충주시 감노로 746 (노은면)
3rd row충주시 중앙탑면 중앙탑길103
4th row충주시 금가면 경촌1길 2
5th row충주시 금가면 금가중앙2길 111
ValueCountFrequency (%)
충주시 43
36.4%
엄정면 3
 
2.5%
예성로 3
 
2.5%
사직산21길 2
 
1.7%
금가면 2
 
1.7%
58 2
 
1.7%
109 1
 
0.8%
사직산21길35(문화동 1
 
0.8%
지곡10길40 1
 
0.8%
38 1
 
0.8%
Other values (59) 59
50.0%
2023-12-13T08:48:21.947765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
13.3%
충 44
 
7.8%
주 43
 
7.6%
시 43
 
7.6%
1 40
 
7.1%
길 29
 
5.2%
3 19
 
3.4%
동 15
 
2.7%
로 14
 
2.5%
2 14
 
2.5%
Other values (72) 227
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 328
58.3%
Decimal Number 134
23.8%
Space Separator 75
 
13.3%
Close Punctuation 9
 
1.6%
Dash Punctuation 9
 
1.6%
Open Punctuation 8
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 44
13.4%
주 43
 
13.1%
시 43
 
13.1%
길 29
 
8.8%
동 15
 
4.6%
로 14
 
4.3%
면 9
 
2.7%
사 8
 
2.4%
직 8
 
2.4%
산 7
 
2.1%
Other values (58) 108
32.9%
Decimal Number
ValueCountFrequency (%)
1 40
29.9%
3 19
14.2%
2 14
 
10.4%
5 13
 
9.7%
0 13
 
9.7%
4 10
 
7.5%
8 7
 
5.2%
7 6
 
4.5%
6 6
 
4.5%
9 6
 
4.5%
Space Separator
ValueCountFrequency (%)
75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 328
58.3%
Common 235
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 44
13.4%
주 43
 
13.1%
시 43
 
13.1%
길 29
 
8.8%
동 15
 
4.6%
로 14
 
4.3%
면 9
 
2.7%
사 8
 
2.4%
직 8
 
2.4%
산 7
 
2.1%
Other values (58) 108
32.9%
Common
ValueCountFrequency (%)
75
31.9%
1 40
17.0%
3 19
 
8.1%
2 14
 
6.0%
5 13
 
5.5%
0 13
 
5.5%
4 10
 
4.3%
) 9
 
3.8%
- 9
 
3.8%
( 8
 
3.4%
Other values (4) 25
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 328
58.3%
ASCII 235
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
31.9%
1 40
17.0%
3 19
 
8.1%
2 14
 
6.0%
5 13
 
5.5%
0 13
 
5.5%
4 10
 
4.3%
) 9
 
3.8%
- 9
 
3.8%
( 8
 
3.4%
Other values (4) 25
 
10.6%
Hangul
ValueCountFrequency (%)
충 44
13.4%
주 43
 
13.1%
시 43
 
13.1%
길 29
 
8.8%
동 15
 
4.6%
로 14
 
4.3%
면 9
 
2.7%
사 8
 
2.4%
직 8
 
2.4%
산 7
 
2.1%
Other values (58) 108
32.9%

연락처
Text

MISSING 

Distinct41
Distinct (%)100.0%
Missing2
Missing (%)4.7%
Memory size476.0 B
2023-12-13T08:48:22.133677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.02439
Min length12

Characters and Unicode

Total characters493
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

Unique41 ?
Unique (%)100.0%

Sample

1st row043-852-1141
2nd row043-847-8977
3rd row043-855-0283
4th row043-855-9611
5th row043-855-4420
ValueCountFrequency (%)
043-855-8798 1
 
2.4%
043-842-0357 1
 
2.4%
043-852-3442 1
 
2.4%
043-847-7401 1
 
2.4%
043-847-1736 1
 
2.4%
043-852-6966 1
 
2.4%
043-842-5172 1
 
2.4%
043-843-0991 1
 
2.4%
043-847-6943 1
 
2.4%
043-857-2943 1
 
2.4%
Other values (31) 31
75.6%
2023-12-13T08:48:22.407756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 82
16.6%
4 77
15.6%
0 61
12.4%
8 56
11.4%
3 53
10.8%
5 46
9.3%
7 31
 
6.3%
2 27
 
5.5%
1 24
 
4.9%
9 21
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 411
83.4%
Dash Punctuation 82
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 77
18.7%
0 61
14.8%
8 56
13.6%
3 53
12.9%
5 46
11.2%
7 31
7.5%
2 27
 
6.6%
1 24
 
5.8%
9 21
 
5.1%
6 15
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 493
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 82
16.6%
4 77
15.6%
0 61
12.4%
8 56
11.4%
3 53
10.8%
5 46
9.3%
7 31
 
6.3%
2 27
 
5.5%
1 24
 
4.9%
9 21
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 493
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 82
16.6%
4 77
15.6%
0 61
12.4%
8 56
11.4%
3 53
10.8%
5 46
9.3%
7 31
 
6.3%
2 27
 
5.5%
1 24
 
4.9%
9 21
 
4.3%

품목1
Text

Distinct33
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-13T08:48:22.571697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length4.0465116
Min length2

Characters and Unicode

Total characters174
Distinct characters89
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

Unique26 ?
Unique (%)60.5%

Sample

1st row커트
2nd row우렁된장찌개
3rd row메밀막국수
4th row황태구이
5th row마사밥상
ValueCountFrequency (%)
커트 4
 
9.3%
청국장 3
 
7.0%
손칼국수 2
 
4.7%
메밀칼국수 2
 
4.7%
김치찌개 2
 
4.7%
칼국수 2
 
4.7%
백반 2
 
4.7%
찐빵(4개 1
 
2.3%
국밥 1
 
2.3%
컷트 1
 
2.3%
Other values (23) 23
53.5%
2023-12-13T08:48:22.827338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 14
 
8.0%
수 9
 
5.2%
칼 7
 
4.0%
밥 7
 
4.0%
장 6
 
3.4%
트 5
 
2.9%
커 4
 
2.3%
개 4
 
2.3%
지 4
 
2.3%
메 4
 
2.3%
Other values (79) 110
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167
96.0%
Open Punctuation 3
 
1.7%
Close Punctuation 3
 
1.7%
Decimal Number 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 14
 
8.4%
수 9
 
5.4%
칼 7
 
4.2%
밥 7
 
4.2%
장 6
 
3.6%
트 5
 
3.0%
커 4
 
2.4%
개 4
 
2.4%
지 4
 
2.4%
메 4
 
2.4%
Other values (76) 103
61.7%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 167
96.0%
Common 7
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 14
 
8.4%
수 9
 
5.4%
칼 7
 
4.2%
밥 7
 
4.2%
장 6
 
3.6%
트 5
 
3.0%
커 4
 
2.4%
개 4
 
2.4%
지 4
 
2.4%
메 4
 
2.4%
Other values (76) 103
61.7%
Common
ValueCountFrequency (%)
( 3
42.9%
) 3
42.9%
4 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 167
96.0%
ASCII 7
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 14
 
8.4%
수 9
 
5.4%
칼 7
 
4.2%
밥 7
 
4.2%
장 6
 
3.6%
트 5
 
3.0%
커 4
 
2.4%
개 4
 
2.4%
지 4
 
2.4%
메 4
 
2.4%
Other values (76) 103
61.7%
ASCII
ValueCountFrequency (%)
( 3
42.9%
) 3
42.9%
4 1
 
14.3%

가격1
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Memory size476.0 B
5000원
9 
7000원
8 
8000원
7 
6000원
3 
2000원
2 
Other values (12)
14 

Length

Max length7
Median length5
Mean length5.2325581
Min length5

Unique

Unique10 ?
Unique (%)23.3%

Sample

1st row 8000원
2nd row7000원
3rd row7500원
4th row9000원
5th row7000원

Common Values

ValueCountFrequency (%)
5000원 9
20.9%
7000원 8
18.6%
8000원 7
16.3%
6000원 3
 
7.0%
2000원 2
 
4.7%
10000원 2
 
4.7%
9000원 2
 
4.7%
40000원 1
 
2.3%
4000원 1
 
2.3%
15000원 1
 
2.3%
Other values (7) 7
16.3%

Length

2023-12-13T08:48:22.940834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5000원 9
20.9%
7000원 8
18.6%
8000원 8
18.6%
6000원 3
 
7.0%
2000원 2
 
4.7%
10000원 2
 
4.7%
9000원 2
 
4.7%
40000원 1
 
2.3%
4000원 1
 
2.3%
15000원 1
 
2.3%
Other values (6) 6
14.0%

품목2
Text

MISSING 

Distinct18
Distinct (%)81.8%
Missing21
Missing (%)48.8%
Memory size476.0 B
2023-12-13T08:48:23.077577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.6363636
Min length2

Characters and Unicode

Total characters80
Distinct characters47
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

Unique14 ?
Unique (%)63.6%

Sample

1st row청국장
2nd row삼겹살
3rd row청국장
4th row짬뽕
5th row아이스티
ValueCountFrequency (%)
두부찌개 2
 
9.1%
염색 2
 
9.1%
비지장 2
 
9.1%
청국장 2
 
9.1%
갈비짜글이 1
 
4.5%
도토리냉묵밥 1
 
4.5%
메밀만둣국 1
 
4.5%
아이스티 1
 
4.5%
산초두부 1
 
4.5%
쟁반막국수 1
 
4.5%
Other values (8) 8
36.4%
2023-12-13T08:48:23.320753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 5
 
6.2%
장 5
 
6.2%
개 4
 
5.0%
부 4
 
5.0%
비 4
 
5.0%
두 3
 
3.8%
밥 3
 
3.8%
찌 3
 
3.8%
수 3
 
3.8%
메 2
 
2.5%
Other values (37) 44
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 5
 
6.2%
장 5
 
6.2%
개 4
 
5.0%
부 4
 
5.0%
비 4
 
5.0%
두 3
 
3.8%
밥 3
 
3.8%
찌 3
 
3.8%
수 3
 
3.8%
메 2
 
2.5%
Other values (37) 44
55.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 5
 
6.2%
장 5
 
6.2%
개 4
 
5.0%
부 4
 
5.0%
비 4
 
5.0%
두 3
 
3.8%
밥 3
 
3.8%
찌 3
 
3.8%
수 3
 
3.8%
메 2
 
2.5%
Other values (37) 44
55.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 5
 
6.2%
장 5
 
6.2%
개 4
 
5.0%
부 4
 
5.0%
비 4
 
5.0%
두 3
 
3.8%
밥 3
 
3.8%
찌 3
 
3.8%
수 3
 
3.8%
메 2
 
2.5%
Other values (37) 44
55.0%

가격2
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
<NA>
21 
7000원
6 
5000원
4 
8000원
4 
12000원
 
2
Other values (5)
6 

Length

Max length6
Median length5
Mean length4.5813953
Min length4

Unique

Unique4 ?
Unique (%)9.3%

Sample

1st row<NA>
2nd row7000원
3rd row<NA>
4th row12000원
5th row7000원

Common Values

ValueCountFrequency (%)
<NA> 21
48.8%
7000원 6
 
14.0%
5000원 4
 
9.3%
8000원 4
 
9.3%
12000원 2
 
4.7%
6000원 2
 
4.7%
7,000 1
 
2.3%
2500원 1
 
2.3%
10000원 1
 
2.3%
6500원 1
 
2.3%

Length

2023-12-13T08:48:23.426500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:48:23.529675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
48.8%
7000원 6
 
14.0%
5000원 4
 
9.3%
8000원 4
 
9.3%
12000원 2
 
4.7%
6000원 2
 
4.7%
7,000 1
 
2.3%
2500원 1
 
2.3%
10000원 1
 
2.3%
6500원 1
 
2.3%

품목3
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing36
Missing (%)83.7%
Memory size476.0 B
2023-12-13T08:48:23.665251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4
Min length3

Characters and Unicode

Total characters28
Distinct characters26
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

Unique7 ?
Unique (%)100.0%

Sample

1st row유자차
2nd row순두부
3rd row아메리카노
4th row쟁반막국수
5th row된장찌개
ValueCountFrequency (%)
유자차 1
14.3%
순두부 1
14.3%
아메리카노 1
14.3%
쟁반막국수 1
14.3%
된장찌개 1
14.3%
떡만두국 1
14.3%
학생커트 1
14.3%
2023-12-13T08:48:23.933773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 2
 
7.1%
두 2
 
7.1%
유 1
 
3.6%
커 1
 
3.6%
생 1
 
3.6%
학 1
 
3.6%
만 1
 
3.6%
떡 1
 
3.6%
개 1
 
3.6%
찌 1
 
3.6%
Other values (16) 16
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 2
 
7.1%
두 2
 
7.1%
유 1
 
3.6%
커 1
 
3.6%
생 1
 
3.6%
학 1
 
3.6%
만 1
 
3.6%
떡 1
 
3.6%
개 1
 
3.6%
찌 1
 
3.6%
Other values (16) 16
57.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 2
 
7.1%
두 2
 
7.1%
유 1
 
3.6%
커 1
 
3.6%
생 1
 
3.6%
학 1
 
3.6%
만 1
 
3.6%
떡 1
 
3.6%
개 1
 
3.6%
찌 1
 
3.6%
Other values (16) 16
57.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 2
 
7.1%
두 2
 
7.1%
유 1
 
3.6%
커 1
 
3.6%
생 1
 
3.6%
학 1
 
3.6%
만 1
 
3.6%
떡 1
 
3.6%
개 1
 
3.6%
찌 1
 
3.6%
Other values (16) 16
57.1%

가격3
Text

MISSING 

Distinct5
Distinct (%)71.4%
Missing36
Missing (%)83.7%
Memory size476.0 B
2023-12-13T08:48:24.069816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters35
Distinct characters7
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

Unique4 ?
Unique (%)57.1%

Sample

1st row3000원
2nd row5000원
3rd row2000원
4th row6000원
5th row6000원
ValueCountFrequency (%)
6000원 3
42.9%
3000원 1
 
14.3%
5000원 1
 
14.3%
2000원 1
 
14.3%
8000원 1
 
14.3%
2023-12-13T08:48:24.341616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21
60.0%
원 7
 
20.0%
6 3
 
8.6%
3 1
 
2.9%
5 1
 
2.9%
2 1
 
2.9%
8 1
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28
80.0%
Other Letter 7
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21
75.0%
6 3
 
10.7%
3 1
 
3.6%
5 1
 
3.6%
2 1
 
3.6%
8 1
 
3.6%
Other Letter
ValueCountFrequency (%)
원 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28
80.0%
Hangul 7
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21
75.0%
6 3
 
10.7%
3 1
 
3.6%
5 1
 
3.6%
2 1
 
3.6%
8 1
 
3.6%
Hangul
ValueCountFrequency (%)
원 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
80.0%
Hangul 7
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21
75.0%
6 3
 
10.7%
3 1
 
3.6%
5 1
 
3.6%
2 1
 
3.6%
8 1
 
3.6%
Hangul
ValueCountFrequency (%)
원 7
100.0%

Interactions

2023-12-13T08:48:19.342359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:48:24.453828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종업소명읍면동주소연락처품목1가격1품목2가격2품목3가격3
연번1.0000.1521.0000.9371.0001.0000.0000.3410.8700.5971.0000.936
업종0.1521.0001.0000.2271.0001.0000.9410.8771.0000.9321.0001.000
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
읍면동0.9370.2271.0001.0001.0001.0000.3350.6610.4820.5291.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
품목10.0000.9411.0000.3351.0001.0001.0000.9550.9040.9141.0000.977
가격10.3410.8771.0000.6611.0001.0000.9551.0000.9650.8101.0000.839
품목20.8701.0001.0000.4821.0001.0000.9040.9651.0000.9071.0000.767
가격20.5970.9321.0000.5291.0001.0000.9140.8100.9071.0001.0000.953
품목31.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
가격30.9361.0001.0001.0001.0001.0000.9770.8390.7670.9531.0001.000
2023-12-13T08:48:24.589005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가격1읍면동가격2업종
가격11.0000.1730.3530.529
읍면동0.1731.0000.1220.000
가격20.3530.1221.0000.748
업종0.5290.0000.7481.000
2023-12-13T08:48:24.693495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종읍면동가격1가격2
연번1.0000.0000.6240.0300.000
업종0.0001.0000.0000.5290.748
읍면동0.6240.0001.0000.1730.122
가격10.0300.5290.1731.0000.353
가격20.0000.7480.1220.3531.000

Missing values

2023-12-13T08:48:19.453038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:48:19.638775image/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.
2023-12-13T08:48:19.780912image/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

연번업종업소명시도명시군구명읍면동주소연락처품목1가격1품목2가격2품목3가격3
01미용업헤어센스미용실충청북도충주시신니면충주시 신니면 용원1길3043-852-1141커트8000원<NA><NA><NA><NA>
12한식청향가든충청북도충주시노은면충주시 감노로 746 (노은면)043-847-8977우렁된장찌개7000원청국장7000원<NA><NA>
23한식메밀마당충청북도충주시중앙탑면충주시 중앙탑면 중앙탑길103043-855-0283메밀막국수7500원<NA><NA><NA><NA>
34한식버드나무집충청북도충주시금가면충주시 금가면 경촌1길 2043-855-9611황태구이9000원삼겹살12000원<NA><NA>
45한식마사밥상슈퍼충청북도충주시금가면충주시 금가면 금가중앙2길 111043-855-4420마사밥상7000원청국장7000원<NA><NA>
56숙박업래미안느충청북도충주시동량면충주시 김생로 58043-857-8855숙박35000원<NA><NA><NA><NA>
67기타비요식업강남종합상사충청북도충주시동량면충주시 동량면 충원대로 1315-4043-851-8225온돌판넬24000원<NA><NA><NA><NA>
78한식밤안개식당충청북도충주시엄정면충주시 엄정면 구룡로393043-852-6065청국장8000원<NA><NA><NA><NA>
89한식엄정우리집충청북도충주시엄정면충주시 엄정면 동막 강현길401043-848-0017백반8000원<NA><NA><NA><NA>
910중식평화루충청북도충주시엄정면충주시 엄정면 미내장터길11043-855-8798짜장면5000원짬뽕7,000<NA><NA>
연번업종업소명시도명시군구명읍면동주소연락처품목1가격1품목2가격2품목3가격3
3334한식백송식당충청북도충주시문화동충주시 사직산23길10(문화동)043-851-1020칼국수4000원보리밥5000원된장찌개6000원
3435한식명진관충청북도충주시문화동충주시 사직산23길2043-843-9897보리밥5000원<NA><NA><NA><NA>
3536이용업마을이발관충청북도충주시호암직동충주시 원호암3길1(호암동)043-855-8444커트8000원<NA><NA><NA><NA>
3637한식야상회충청북도충주시호암직동충주시 상아배이길 100-1043-851-1788삼선짜장7000원<NA><NA><NA><NA>
3738한식수산칼국수충청북도충주시봉방동충주시 봉방4길 5(봉방동)043-855-6513칼국수5000원수제비5000원떡만두국6000원
3839한식돈이랑칼국수충청북도충주시칠금금릉동충주시 금제1길 39-1043-854-5656김치찌개5000원두부찌개5000원<NA><NA>
3940한식주혜옹심이칼국수충청북도충주시연수동충주시 동수9길 6(연수동)043-843-2077메밀칼국수7000원메일부침개6000원<NA><NA>
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