Overview

Dataset statistics

Number of variables7
Number of observations899
Missing cells900
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.0 KiB
Average record size in memory58.1 B

Variable types

Numeric1
Text3
Categorical2
Unsupported1

Dataset

Description충청남도 전통시장 홈페이지의 전통시장 내 점포 정보(시장명, 점포명, 지류 온누리상품권 가맹여부, 카드결제 가능여부 등)
Author충청남도
URLhttps://www.data.go.kr/data/15040771/fileData.do

Alerts

결제옵션(온누리상품권, 카드 등) is highly imbalanced (65.8%)Imbalance
Unnamed: 6 has 899 (100.0%) missing valuesMissing
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 01:41:10.686464
Analysis finished2023-12-12 01:41:11.764772
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

Distinct898
Distinct (%)100.0%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean449.5
Minimum1
Maximum898
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-12T10:41:11.872186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45.85
Q1225.25
median449.5
Q3673.75
95-th percentile853.15
Maximum898
Range897
Interquartile range (IQR)448.5

Descriptive statistics

Standard deviation259.37457
Coefficient of variation (CV)0.57702907
Kurtosis-1.2
Mean449.5
Median Absolute Deviation (MAD)224.5
Skewness0
Sum403651
Variance67275.167
MonotonicityStrictly increasing
2023-12-12T10:41:12.049666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
675 1
 
0.1%
593 1
 
0.1%
594 1
 
0.1%
595 1
 
0.1%
596 1
 
0.1%
597 1
 
0.1%
598 1
 
0.1%
599 1
 
0.1%
600 1
 
0.1%
Other values (888) 888
98.8%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
898 1
0.1%
897 1
0.1%
896 1
0.1%
895 1
0.1%
894 1
0.1%
893 1
0.1%
892 1
0.1%
891 1
0.1%
890 1
0.1%
889 1
0.1%

시장명
Text

Distinct54
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T10:41:12.324542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.1334816
Min length4

Characters and Unicode

Total characters5514
Distinct characters85
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)1.3%

Sample

1st row갈산전통시장
2nd row갈산전통시장
3rd row갈산전통시장
4th row강경대흥시장
5th row강경대흥시장
ValueCountFrequency (%)
공주산성시장 121
13.5%
천안중앙시장 102
 
11.3%
강경대흥시장 70
 
7.8%
온양온천시장 64
 
7.1%
보령한내시장 59
 
6.6%
천안역전시장 44
 
4.9%
논산화지중앙시장 41
 
4.6%
금산수삼센터 37
 
4.1%
서천특화시장 34
 
3.8%
대천항종합수산물시장 30
 
3.3%
Other values (44) 297
33.0%
2023-12-12T10:41:12.837542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 871
 
15.8%
시 860
 
15.6%
산 343
 
6.2%
천 289
 
5.2%
안 181
 
3.3%
성 171
 
3.1%
중 159
 
2.9%
앙 158
 
2.9%
온 128
 
2.3%
공 121
 
2.2%
Other values (75) 2233
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5513
> 99.9%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 871
 
15.8%
시 860
 
15.6%
산 343
 
6.2%
천 289
 
5.2%
안 181
 
3.3%
성 171
 
3.1%
중 159
 
2.9%
앙 158
 
2.9%
온 128
 
2.3%
공 121
 
2.2%
Other values (74) 2232
40.5%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5514
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 871
 
15.8%
시 860
 
15.6%
산 343
 
6.2%
천 289
 
5.2%
안 181
 
3.3%
성 171
 
3.1%
중 159
 
2.9%
앙 158
 
2.9%
온 128
 
2.3%
공 121
 
2.2%
Other values (75) 2233
40.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5513
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 871
 
15.8%
시 860
 
15.6%
산 343
 
6.2%
천 289
 
5.2%
안 181
 
3.3%
성 171
 
3.1%
중 159
 
2.9%
앙 158
 
2.9%
온 128
 
2.3%
공 121
 
2.2%
Other values (74) 2232
40.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

점포명
Text

Distinct875
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T10:41:13.229244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.0678532
Min length2

Characters and Unicode

Total characters4556
Distinct characters488
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique852 ?
Unique (%)94.8%

Sample

1st row행산식당
2nd row갈산식품
3rd row혜성활어유통
4th row천혜종합마트
5th row돈사랑
ValueCountFrequency (%)
금산수삼센터 12
 
1.3%
못난이꽈배기 3
 
0.3%
수삼센터 3
 
0.3%
노점 3
 
0.3%
행복한정육백화점 2
 
0.2%
공주점 2
 
0.2%
원전진호 2
 
0.2%
배드민턴창고 2
 
0.2%
금산수삼센타 2
 
0.2%
21호 2
 
0.2%
Other values (896) 915
96.5%
2023-12-12T10:41:13.750050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 140
 
3.1%
산 133
 
2.9%
회 102
 
2.2%
상 102
 
2.2%
점 73
 
1.6%
호 62
 
1.4%
삼 61
 
1.3%
식 59
 
1.3%
국 56
 
1.2%
이 54
 
1.2%
Other values (478) 3714
81.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4357
95.6%
Decimal Number 105
 
2.3%
Space Separator 52
 
1.1%
Close Punctuation 16
 
0.4%
Open Punctuation 15
 
0.3%
Other Symbol 6
 
0.1%
Other Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 140
 
3.2%
산 133
 
3.1%
회 102
 
2.3%
상 102
 
2.3%
점 73
 
1.7%
호 62
 
1.4%
삼 61
 
1.4%
식 59
 
1.4%
국 56
 
1.3%
이 54
 
1.2%
Other values (462) 3515
80.7%
Decimal Number
ValueCountFrequency (%)
2 19
18.1%
3 16
15.2%
1 12
11.4%
4 12
11.4%
9 12
11.4%
7 11
10.5%
0 6
 
5.7%
8 6
 
5.7%
5 6
 
5.7%
6 5
 
4.8%
Other Punctuation
ValueCountFrequency (%)
& 3
60.0%
. 2
40.0%
Space Separator
ValueCountFrequency (%)
52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4363
95.8%
Common 193
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 140
 
3.2%
산 133
 
3.0%
회 102
 
2.3%
상 102
 
2.3%
점 73
 
1.7%
호 62
 
1.4%
삼 61
 
1.4%
식 59
 
1.4%
국 56
 
1.3%
이 54
 
1.2%
Other values (463) 3521
80.7%
Common
ValueCountFrequency (%)
52
26.9%
2 19
 
9.8%
) 16
 
8.3%
3 16
 
8.3%
( 15
 
7.8%
1 12
 
6.2%
4 12
 
6.2%
9 12
 
6.2%
7 11
 
5.7%
0 6
 
3.1%
Other values (5) 22
11.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4357
95.6%
ASCII 193
 
4.2%
None 6
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 140
 
3.2%
산 133
 
3.1%
회 102
 
2.3%
상 102
 
2.3%
점 73
 
1.7%
호 62
 
1.4%
삼 61
 
1.4%
식 59
 
1.4%
국 56
 
1.3%
이 54
 
1.2%
Other values (462) 3515
80.7%
ASCII
ValueCountFrequency (%)
52
26.9%
2 19
 
9.8%
) 16
 
8.3%
3 16
 
8.3%
( 15
 
7.8%
1 12
 
6.2%
4 12
 
6.2%
9 12
 
6.2%
7 11
 
5.7%
0 6
 
3.1%
Other values (5) 22
11.4%
None
ValueCountFrequency (%)
㈜ 6
100.0%

업종
Categorical

Distinct14
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
음식점업
228 
기타
166 
농산물
117 
수산물
115 
의류/신발/양말
111 
Other values (9)
162 

Length

Max length21
Median length10
Mean length4.3459399
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row음식점업
2nd row슈퍼
3rd row수산물
4th row슈퍼
5th row음식점업

Common Values

ValueCountFrequency (%)
음식점업 228
25.4%
기타 166
18.5%
농산물 117
13.0%
수산물 115
12.8%
의류/신발/양말 111
12.3%
축산물 45
 
5.0%
식품업 35
 
3.9%
근린생활서비스(미용,목욕탕,세탁소 등) 27
 
3.0%
슈퍼 17
 
1.9%
가공식품 16
 
1.8%
Other values (4) 22
 
2.4%

Length

2023-12-12T10:41:13.970475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
음식점업 228
24.6%
기타 166
17.9%
농산물 117
12.6%
수산물 115
12.4%
의류/신발/양말 111
12.0%
축산물 45
 
4.9%
식품업 35
 
3.8%
근린생활서비스(미용,목욕탕,세탁소 27
 
2.9%
등 27
 
2.9%
슈퍼 17
 
1.8%
Other values (5) 38
 
4.1%

주요품목
Text

Distinct307
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T10:41:14.428229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length2
Mean length2.9354839
Min length1

Characters and Unicode

Total characters2639
Distinct characters254
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique205 ?
Unique (%)22.8%

Sample

1st row한식
2nd row야채
3rd row수산물
4th row마트
5th row한식
ValueCountFrequency (%)
의류 70
 
7.4%
한식 63
 
6.6%
수산물 52
 
5.5%
젓갈 34
 
3.6%
음식 33
 
3.5%
수삼 22
 
2.3%
생선 20
 
2.1%
채소 19
 
2.0%
농산물 16
 
1.7%
야채 16
 
1.7%
Other values (289) 606
63.7%
2023-12-12T10:41:15.109208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 179
 
6.8%
물 120
 
4.5%
수 109
 
4.1%
류 105
 
4.0%
의 90
 
3.4%
산 85
 
3.2%
한 72
 
2.7%
, 67
 
2.5%
삼 56
 
2.1%
53
 
2.0%
Other values (244) 1703
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2472
93.7%
Other Punctuation 68
 
2.6%
Space Separator 53
 
2.0%
Close Punctuation 22
 
0.8%
Open Punctuation 22
 
0.8%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 179
 
7.2%
물 120
 
4.9%
수 109
 
4.4%
류 105
 
4.2%
의 90
 
3.6%
산 85
 
3.4%
한 72
 
2.9%
삼 56
 
2.3%
음 52
 
2.1%
품 49
 
2.0%
Other values (237) 1555
62.9%
Other Punctuation
ValueCountFrequency (%)
, 67
98.5%
/ 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
R 1
50.0%
Space Separator
ValueCountFrequency (%)
53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2472
93.7%
Common 165
 
6.3%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 179
 
7.2%
물 120
 
4.9%
수 109
 
4.4%
류 105
 
4.2%
의 90
 
3.6%
산 85
 
3.4%
한 72
 
2.9%
삼 56
 
2.3%
음 52
 
2.1%
품 49
 
2.0%
Other values (237) 1555
62.9%
Common
ValueCountFrequency (%)
, 67
40.6%
53
32.1%
) 22
 
13.3%
( 22
 
13.3%
/ 1
 
0.6%
Latin
ValueCountFrequency (%)
C 1
50.0%
R 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2472
93.7%
ASCII 167
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 179
 
7.2%
물 120
 
4.9%
수 109
 
4.4%
류 105
 
4.2%
의 90
 
3.6%
산 85
 
3.4%
한 72
 
2.9%
삼 56
 
2.3%
음 52
 
2.1%
품 49
 
2.0%
Other values (237) 1555
62.9%
ASCII
ValueCountFrequency (%)
, 67
40.1%
53
31.7%
) 22
 
13.2%
( 22
 
13.2%
C 1
 
0.6%
/ 1
 
0.6%
R 1
 
0.6%

결제옵션(온누리상품권, 카드 등)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
온누리상품권 카드결제
794 
온누리상품권
102 
온누리상품권
 
3

Length

Max length11
Median length11
Mean length10.419355
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row온누리상품권
2nd row온누리상품권
3rd row온누리상품권
4th row온누리상품권 카드결제
5th row온누리상품권 카드결제

Common Values

ValueCountFrequency (%)
온누리상품권 카드결제 794
88.3%
온누리상품권 102
 
11.3%
온누리상품권 3
 
0.3%

Length

2023-12-12T10:41:15.283812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:41:15.425308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온누리상품권 899
53.1%
카드결제 794
46.9%

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing899
Missing (%)100.0%
Memory size8.0 KiB

Interactions

2023-12-12T10:41:11.357745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:41:15.513327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시장명업종결제옵션(온누리상품권, 카드 등)
연번1.0000.9880.4020.646
시장명0.9881.0000.6120.975
업종0.4020.6121.0000.181
결제옵션(온누리상품권, 카드 등)0.6460.9750.1811.000
2023-12-12T10:41:15.649255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결제옵션(온누리상품권, 카드 등)업종
결제옵션(온누리상품권, 카드 등)1.0000.100
업종0.1001.000
2023-12-12T10:41:15.767320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종결제옵션(온누리상품권, 카드 등)
연번1.0000.1740.492
업종0.1741.0000.100
결제옵션(온누리상품권, 카드 등)0.4920.1001.000

Missing values

2023-12-12T10:41:11.538952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:41:11.698350image/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

연번시장명점포명업종주요품목결제옵션(온누리상품권, 카드 등)Unnamed: 6
0<NA>갈산전통시장행산식당음식점업한식온누리상품권<NA>
11갈산전통시장갈산식품슈퍼야채온누리상품권<NA>
22갈산전통시장혜성활어유통수산물수산물온누리상품권<NA>
33강경대흥시장천혜종합마트슈퍼마트온누리상품권 카드결제<NA>
44강경대흥시장돈사랑음식점업한식온누리상품권 카드결제<NA>
55강경대흥시장은하젓갈가공식품젓갈온누리상품권 카드결제<NA>
66강경대흥시장지혜네분식음식점업팥죽, 국수온누리상품권 카드결제<NA>
77강경대흥시장여왕벌미장원근린생활서비스(미용,목욕탕,세탁소 등)미용실온누리상품권 카드결제<NA>
88강경대흥시장소잇소축산물식육온누리상품권 카드결제<NA>
99강경대흥시장성현닭집축산물생닭온누리상품권<NA>
연번시장명점포명업종주요품목결제옵션(온누리상품권, 카드 등)Unnamed: 6
889889해미시장만나산야초국수음식점업음식온누리상품권 카드결제<NA>
890890해미시장오르보아음식점업커피온누리상품권 카드결제<NA>
891891해미종합시장읍성건강원기타건강원온누리상품권 카드결제<NA>
892892현대시장대성상회기타잡화온누리상품권 카드결제<NA>
893893홍성상설시장예담 궁 테라피근린생활서비스(미용,목욕탕,세탁소 등)피부미용업온누리상품권 카드결제<NA>
894894홍성상설시장시골집음식점업음식점온누리상품권 카드결제<NA>
895895홍성상설시장웰빙시대 건강백화점가공식품가공식품온누리상품권 카드결제<NA>
896896홍성상설시장꽃비의류/신발/양말의류온누리상품권 카드결제<NA>
897897홍성전통시장자연상회수산물수산물온누리상품권 카드결제<NA>
898898홍성전통시장죽림건강원기타건강원온누리상품권 카드결제<NA>