Overview

Dataset statistics

Number of variables13
Number of observations34
Missing cells46
Missing cells (%)10.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory109.9 B

Variable types

Numeric2
Text5
Categorical3
Boolean2
DateTime1

Alerts

공중화장실 보유여부 has constant value ""Constant
주차장 보유여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 시장유형High correlation
시장유형 is highly overall correlated with 순번High correlation
취급품목 has 1 (2.9%) missing valuesMissing
홈페이지주소 has 31 (91.2%) missing valuesMissing
공중화장실 보유여부 has 4 (11.8%) missing valuesMissing
주차장 보유여부 has 4 (11.8%) missing valuesMissing
개설년도 has 6 (17.6%) missing valuesMissing
순번 has unique valuesUnique
시장명 has unique valuesUnique
주 소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:08:10.721795
Analysis finished2024-03-14 02:08:11.781798
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.5
Minimum1
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-03-14T11:08:11.858395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.65
Q19.25
median17.5
Q325.75
95-th percentile32.35
Maximum34
Range33
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation9.9582462
Coefficient of variation (CV)0.56904264
Kurtosis-1.2
Mean17.5
Median Absolute Deviation (MAD)8.5
Skewness0
Sum595
Variance99.166667
MonotonicityStrictly increasing
2024-03-14T11:08:12.067214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 1
 
2.9%
27 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
26 1
 
2.9%
28 1
 
2.9%
19 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
26 1
2.9%
25 1
2.9%

시장명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T11:08:12.270900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1470588
Min length4

Characters and Unicode

Total characters141
Distinct characters54
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

Unique34 ?
Unique (%)100.0%

Sample

1st row대야시장
2nd row북부시장
3rd row금마시장
4th row함열시장
5th row황등시장
ValueCountFrequency (%)
대야시장 1
 
2.9%
북부시장 1
 
2.9%
무장시장 1
 
2.9%
대산시장 1
 
2.9%
해리시장 1
 
2.9%
흥덕시장 1
 
2.9%
복흥시장 1
 
2.9%
동계시장 1
 
2.9%
순창시장 1
 
2.9%
신태인시장 1
 
2.9%
Other values (24) 24
70.6%
2024-03-14T11:08:12.551025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 37
26.2%
시 30
21.3%
산 5
 
3.5%
터 4
 
2.8%
대 3
 
2.1%
봉 3
 
2.1%
덕 3
 
2.1%
흥 2
 
1.4%
계 2
 
1.4%
창 2
 
1.4%
Other values (44) 50
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 141
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 37
26.2%
시 30
21.3%
산 5
 
3.5%
터 4
 
2.8%
대 3
 
2.1%
봉 3
 
2.1%
덕 3
 
2.1%
흥 2
 
1.4%
계 2
 
1.4%
창 2
 
1.4%
Other values (44) 50
35.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 141
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 37
26.2%
시 30
21.3%
산 5
 
3.5%
터 4
 
2.8%
대 3
 
2.1%
봉 3
 
2.1%
덕 3
 
2.1%
흥 2
 
1.4%
계 2
 
1.4%
창 2
 
1.4%
Other values (44) 50
35.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 141
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 37
26.2%
시 30
21.3%
산 5
 
3.5%
터 4
 
2.8%
대 3
 
2.1%
봉 3
 
2.1%
덕 3
 
2.1%
흥 2
 
1.4%
계 2
 
1.4%
창 2
 
1.4%
Other values (44) 50
35.5%

시장유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
정기시장(5일장)
26 
상설+정기시장
8 

Length

Max length9
Median length9
Mean length8.5294118
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상설+정기시장
2nd row상설+정기시장
3rd row상설+정기시장
4th row상설+정기시장
5th row상설+정기시장

Common Values

ValueCountFrequency (%)
정기시장(5일장) 26
76.5%
상설+정기시장 8
 
23.5%

Length

2024-03-14T11:08:12.661207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:08:12.744432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기시장(5일장 26
76.5%
상설+정기시장 8
 
23.5%

시장개설주기
Categorical

Distinct6
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size404.0 B
1일, 6일
8 
2일, 7일
7 
3일, 8일
7 
5일, 10일
6 
4일, 9일
5 

Length

Max length7
Median length6
Mean length6.1176471
Min length4

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row1일, 6일
2nd row상설시장
3rd row2일, 7일
4th row2일, 7일
5th row5일, 10일

Common Values

ValueCountFrequency (%)
1일, 6일 8
23.5%
2일, 7일 7
20.6%
3일, 8일 7
20.6%
5일, 10일 6
17.6%
4일, 9일 5
14.7%
상설시장 1
 
2.9%

Length

2024-03-14T11:08:12.829258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:08:12.930041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1일 8
11.9%
6일 8
11.9%
2일 7
10.4%
7일 7
10.4%
3일 7
10.4%
8일 7
10.4%
5일 6
9.0%
10일 6
9.0%
4일 5
7.5%
9일 5
7.5%

주 소
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T11:08:13.149061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.176471
Min length12

Characters and Unicode

Total characters686
Distinct characters93
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

Unique34 ?
Unique (%)100.0%

Sample

1st row전라북도 군산시 대야면 대야시장로 19
2nd row전라북도 익산시 인북로 259
3rd row전라북도 김제시 동서7길 23
4th row전라북도 익산시 함열읍 와리544-34
5th row전라북도 익산시 황등면 황등7길 25
ValueCountFrequency (%)
전라북도 34
 
21.1%
고창군 6
 
3.7%
임실군 4
 
2.5%
익산시 4
 
2.5%
무주군 4
 
2.5%
순창군 3
 
1.9%
남원시 3
 
1.9%
장수군 3
 
1.9%
완주군 2
 
1.2%
16 2
 
1.2%
Other values (93) 96
59.6%
2024-03-14T11:08:13.512518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
18.5%
북 35
 
5.1%
도 35
 
5.1%
전 34
 
5.0%
라 34
 
5.0%
군 24
 
3.5%
1 22
 
3.2%
면 21
 
3.1%
5 17
 
2.5%
로 17
 
2.5%
Other values (83) 320
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 444
64.7%
Space Separator 127
 
18.5%
Decimal Number 104
 
15.2%
Dash Punctuation 11
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 35
 
7.9%
도 35
 
7.9%
전 34
 
7.7%
라 34
 
7.7%
군 24
 
5.4%
면 21
 
4.7%
로 17
 
3.8%
시 15
 
3.4%
산 14
 
3.2%
장 12
 
2.7%
Other values (71) 203
45.7%
Decimal Number
ValueCountFrequency (%)
1 22
21.2%
5 17
16.3%
2 15
14.4%
3 11
10.6%
4 11
10.6%
6 8
 
7.7%
7 6
 
5.8%
8 6
 
5.8%
0 4
 
3.8%
9 4
 
3.8%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 444
64.7%
Common 242
35.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 35
 
7.9%
도 35
 
7.9%
전 34
 
7.7%
라 34
 
7.7%
군 24
 
5.4%
면 21
 
4.7%
로 17
 
3.8%
시 15
 
3.4%
산 14
 
3.2%
장 12
 
2.7%
Other values (71) 203
45.7%
Common
ValueCountFrequency (%)
127
52.5%
1 22
 
9.1%
5 17
 
7.0%
2 15
 
6.2%
3 11
 
4.5%
4 11
 
4.5%
- 11
 
4.5%
6 8
 
3.3%
7 6
 
2.5%
8 6
 
2.5%
Other values (2) 8
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 444
64.7%
ASCII 242
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
52.5%
1 22
 
9.1%
5 17
 
7.0%
2 15
 
6.2%
3 11
 
4.5%
4 11
 
4.5%
- 11
 
4.5%
6 8
 
3.3%
7 6
 
2.5%
8 6
 
2.5%
Other values (2) 8
 
3.3%
Hangul
ValueCountFrequency (%)
북 35
 
7.9%
도 35
 
7.9%
전 34
 
7.7%
라 34
 
7.7%
군 24
 
5.4%
면 21
 
4.7%
로 17
 
3.8%
시 15
 
3.4%
산 14
 
3.2%
장 12
 
2.7%
Other values (71) 203
45.7%

점포수
Real number (ℝ)

Distinct26
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.705882
Minimum6
Maximum199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-03-14T11:08:13.619807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile8.95
Q129
median37.5
Q350
95-th percentile177.1
Maximum199
Range193
Interquartile range (IQR)21

Descriptive statistics

Standard deviation49.971222
Coefficient of variation (CV)0.96645139
Kurtosis3.6711425
Mean51.705882
Median Absolute Deviation (MAD)12.5
Skewness2.1063632
Sum1758
Variance2497.123
MonotonicityNot monotonic
2024-03-14T11:08:13.733759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
50 3
 
8.8%
33 2
 
5.9%
29 2
 
5.9%
34 2
 
5.9%
47 2
 
5.9%
12 2
 
5.9%
32 2
 
5.9%
13 1
 
2.9%
51 1
 
2.9%
66 1
 
2.9%
Other values (16) 16
47.1%
ValueCountFrequency (%)
6 1
2.9%
7 1
2.9%
10 1
2.9%
12 2
5.9%
13 1
2.9%
20 1
2.9%
25 1
2.9%
29 2
5.9%
32 2
5.9%
33 2
5.9%
ValueCountFrequency (%)
199 1
 
2.9%
194 1
 
2.9%
168 1
 
2.9%
154 1
 
2.9%
67 1
 
2.9%
66 1
 
2.9%
51 1
 
2.9%
50 3
8.8%
49 1
 
2.9%
47 2
5.9%

취급품목
Text

MISSING 

Distinct33
Distinct (%)100.0%
Missing1
Missing (%)2.9%
Memory size404.0 B
2024-03-14T11:08:13.884190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length8.4545455
Min length1

Characters and Unicode

Total characters279
Distinct characters77
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

Unique33 ?
Unique (%)100.0%

Sample

1st row배추, 무 등
2nd row생선, 농산물, 의류 등
3rd row파, 대추 등
4th row고구마
5th row대추, 사과, 복숭아, 포도 등
ValueCountFrequency (%)
등 21
22.1%
고추 7
 
7.4%
대추 4
 
4.2%
배추 3
 
3.2%
마늘 3
 
3.2%
사과 3
 
3.2%
채소 3
 
3.2%
양파 2
 
2.1%
과일 2
 
2.1%
무 2
 
2.1%
Other values (39) 45
47.4%
2024-03-14T11:08:14.199209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62
22.2%
, 38
 
13.6%
등 21
 
7.5%
추 15
 
5.4%
고 10
 
3.6%
소 6
 
2.2%
채 5
 
1.8%
대 5
 
1.8%
과 5
 
1.8%
마 5
 
1.8%
Other values (67) 107
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 179
64.2%
Space Separator 62
 
22.2%
Other Punctuation 38
 
13.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 21
 
11.7%
추 15
 
8.4%
고 10
 
5.6%
소 6
 
3.4%
채 5
 
2.8%
대 5
 
2.8%
과 5
 
2.8%
마 5
 
2.8%
복 4
 
2.2%
류 3
 
1.7%
Other values (65) 100
55.9%
Space Separator
ValueCountFrequency (%)
62
100.0%
Other Punctuation
ValueCountFrequency (%)
, 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 179
64.2%
Common 100
35.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 21
 
11.7%
추 15
 
8.4%
고 10
 
5.6%
소 6
 
3.4%
채 5
 
2.8%
대 5
 
2.8%
과 5
 
2.8%
마 5
 
2.8%
복 4
 
2.2%
류 3
 
1.7%
Other values (65) 100
55.9%
Common
ValueCountFrequency (%)
62
62.0%
, 38
38.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 179
64.2%
ASCII 100
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62
62.0%
, 38
38.0%
Hangul
ValueCountFrequency (%)
등 21
 
11.7%
추 15
 
8.4%
고 10
 
5.6%
소 6
 
3.4%
채 5
 
2.8%
대 5
 
2.8%
과 5
 
2.8%
마 5
 
2.8%
복 4
 
2.2%
류 3
 
1.7%
Other values (65) 100
55.9%

사용가능상품권
Categorical

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
온누리상품권, 전자상품권
14 
<NA>
11 
온누리상품권
9 

Length

Max length13
Median length7
Mean length8.5
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row 온누리상품권
2nd row온누리상품권, 전자상품권
3rd row<NA>
4th row<NA>
5th row온누리상품권, 전자상품권

Common Values

ValueCountFrequency (%)
온누리상품권, 전자상품권 14
41.2%
<NA> 11
32.4%
온누리상품권 9
26.5%

Length

2024-03-14T11:08:14.389204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:08:14.476926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온누리상품권 23
47.9%
전자상품권 14
29.2%
na 11
22.9%

홈페이지주소
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing31
Missing (%)91.2%
Memory size404.0 B
2024-03-14T11:08:14.593179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length13.666667
Min length11

Characters and Unicode

Total characters41
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowwww.isbb.kr
2nd rowhttp://www.nwgs.kr
3rd rowwww.mnwiw.kr
ValueCountFrequency (%)
www.isbb.kr 1
33.3%
http://www.nwgs.kr 1
33.3%
www.mnwiw.kr 1
33.3%
2024-03-14T11:08:14.820193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 12
29.3%
. 6
14.6%
k 3
 
7.3%
r 3
 
7.3%
i 2
 
4.9%
s 2
 
4.9%
b 2
 
4.9%
t 2
 
4.9%
/ 2
 
4.9%
n 2
 
4.9%
Other values (5) 5
12.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32
78.0%
Other Punctuation 9
 
22.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 12
37.5%
k 3
 
9.4%
r 3
 
9.4%
i 2
 
6.2%
s 2
 
6.2%
b 2
 
6.2%
t 2
 
6.2%
n 2
 
6.2%
h 1
 
3.1%
p 1
 
3.1%
Other values (2) 2
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
/ 2
 
22.2%
: 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 32
78.0%
Common 9
 
22.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 12
37.5%
k 3
 
9.4%
r 3
 
9.4%
i 2
 
6.2%
s 2
 
6.2%
b 2
 
6.2%
t 2
 
6.2%
n 2
 
6.2%
h 1
 
3.1%
p 1
 
3.1%
Other values (2) 2
 
6.2%
Common
ValueCountFrequency (%)
. 6
66.7%
/ 2
 
22.2%
: 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 12
29.3%
. 6
14.6%
k 3
 
7.3%
r 3
 
7.3%
i 2
 
4.9%
s 2
 
4.9%
b 2
 
4.9%
t 2
 
4.9%
/ 2
 
4.9%
n 2
 
4.9%
Other values (5) 5
12.2%

공중화장실 보유여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)3.3%
Missing4
Missing (%)11.8%
Memory size200.0 B
True
30 
(Missing)
4 
ValueCountFrequency (%)
True 30
88.2%
(Missing) 4
 
11.8%
2024-03-14T11:08:14.905077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

주차장 보유여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)3.3%
Missing4
Missing (%)11.8%
Memory size200.0 B
True
30 
(Missing)
4 
ValueCountFrequency (%)
True 30
88.2%
(Missing) 4
 
11.8%
2024-03-14T11:08:14.961281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

개설년도
Text

MISSING 

Distinct22
Distinct (%)78.6%
Missing6
Missing (%)17.6%
Memory size404.0 B
2024-03-14T11:08:15.074881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0357143
Min length5

Characters and Unicode

Total characters141
Distinct characters12
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

Unique17 ?
Unique (%)60.7%

Sample

1st row1975년
2nd row1974년
3rd row2009년
4th row2004년
5th row2014년
ValueCountFrequency (%)
2006년 3
 
10.7%
2000년 2
 
7.1%
2009년 2
 
7.1%
1987년 2
 
7.1%
1990년 2
 
7.1%
1965년 1
 
3.6%
1993년 1
 
3.6%
1980년 1
 
3.6%
1967년 1
 
3.6%
2008년 1
 
3.6%
Other values (12) 12
42.9%
2024-03-14T11:08:15.339326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28
19.9%
년 28
19.9%
9 25
17.7%
1 18
12.8%
2 14
9.9%
7 7
 
5.0%
6 6
 
4.3%
8 4
 
2.8%
4 4
 
2.8%
3 3
 
2.1%
Other values (2) 4
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 112
79.4%
Other Letter 28
 
19.9%
Space Separator 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28
25.0%
9 25
22.3%
1 18
16.1%
2 14
12.5%
7 7
 
6.2%
6 6
 
5.4%
8 4
 
3.6%
4 4
 
3.6%
3 3
 
2.7%
5 3
 
2.7%
Other Letter
ValueCountFrequency (%)
년 28
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 113
80.1%
Hangul 28
 
19.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28
24.8%
9 25
22.1%
1 18
15.9%
2 14
12.4%
7 7
 
6.2%
6 6
 
5.3%
8 4
 
3.5%
4 4
 
3.5%
3 3
 
2.7%
5 3
 
2.7%
Hangul
ValueCountFrequency (%)
년 28
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 113
80.1%
Hangul 28
 
19.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28
24.8%
9 25
22.1%
1 18
15.9%
2 14
12.4%
7 7
 
6.2%
6 6
 
5.3%
8 4
 
3.5%
4 4
 
3.5%
3 3
 
2.7%
5 3
 
2.7%
Hangul
ValueCountFrequency (%)
년 28
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
Minimum2015-09-25 00:00:00
Maximum2015-09-25 00:00:00
2024-03-14T11:08:15.437700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:08:15.514938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T11:08:11.265572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:08:11.129067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:08:11.337519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:08:11.196688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:08:15.574932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시장명시장유형시장개설주기주 소점포수취급품목사용가능상품권홈페이지주소개설년도
순번1.0001.0000.9920.0001.0000.4151.0000.7531.0000.000
시장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시장유형0.9921.0001.0000.0941.0000.3721.0000.0001.0000.869
시장개설주기0.0001.0000.0941.0001.0000.6111.0000.0001.0000.690
주 소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
점포수0.4151.0000.3720.6111.0001.0001.0000.0001.0000.000
취급품목1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사용가능상품권0.7531.0000.0000.0001.0000.0001.0001.000NaN0.935
홈페이지주소1.0001.0001.0001.0001.0001.0001.000NaN1.0001.000
개설년도0.0001.0000.8690.6901.0000.0001.0000.9351.0001.000
2024-03-14T11:08:15.903833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시장유형사용가능상품권시장개설주기
시장유형1.0000.0000.000
사용가능상품권0.0001.0000.000
시장개설주기0.0000.0001.000
2024-03-14T11:08:15.978135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번점포수시장유형시장개설주기사용가능상품권
순번1.0000.0420.7990.0000.452
점포수0.0421.0000.3600.4080.000
시장유형0.7990.3601.0000.0000.000
시장개설주기0.0000.4080.0001.0000.000
사용가능상품권0.4520.0000.0000.0001.000

Missing values

2024-03-14T11:08:11.438550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:08:11.610020image/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.
2024-03-14T11:08:11.714190image/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

순번시장명시장유형시장개설주기주 소점포수취급품목사용가능상품권홈페이지주소공중화장실 보유여부주차장 보유여부개설년도데이터기준일자
01대야시장상설+정기시장1일, 6일전라북도 군산시 대야면 대야시장로 1938배추, 무 등온누리상품권<NA>YY1975년2015-09-25
12북부시장상설+정기시장상설시장전라북도 익산시 인북로 259168생선, 농산물, 의류 등온누리상품권, 전자상품권www.isbb.krYY1974년2015-09-25
23금마시장상설+정기시장2일, 7일전라북도 김제시 동서7길 2329파, 대추 등<NA><NA>YY2009년2015-09-25
34함열시장상설+정기시장2일, 7일전라북도 익산시 함열읍 와리544-3434고구마<NA><NA>YY2004년2015-09-25
45황등시장상설+정기시장5일, 10일전라북도 익산시 황등면 황등7길 2546대추, 사과, 복숭아, 포도 등온누리상품권, 전자상품권<NA>YY2014년2015-09-25
56공설시장상설+정기시장4일, 9일전라북도 남원시 의총로 51154부각, 순대국밥 등온누리상품권, 전자상품권http://www.nwgs.krYY2006년2015-09-25
67진안시장상설+정기시장4일, 9일전라북도 진안군 진안읍 시장1길 1649고추, 인삼, 채소 등온누리상품권, 전자상품권<NA>YY2009년2015-09-25
78고창시장상설+정기시장3일, 8일전라북도 고창군 고창읍 읍내리 368199복분자술, 풍천장어 등온누리상품권, 전자상품권<NA>YY1970년2015-09-25
89여산시장정기시장(5일장)1일, 6일전라북도 익산시 여산면 여산리 412-46야채, 과일, 고기 등<NA><NA><NA><NA>1963년2015-09-25
910신태인시장정기시장(5일장)3일, 8일전라북도 정읍시 신태안읍신태인2길14번지45쌀온누리상품권, 전자상품권<NA>YY2013년2015-09-25
순번시장명시장유형시장개설주기주 소점포수취급품목사용가능상품권홈페이지주소공중화장실 보유여부주차장 보유여부개설년도데이터기준일자
2425관촌시장정기시장(5일장)5일, 10일전라북도 임실군 관촌면 관촌리 580-137고추온누리상품권, 전자상품권<NA>YY2006년2015-09-25
2526강진시장정기시장(5일장)2일, 7일전라북도 임실군 강진면 호국로 32-5532감<NA><NA>YY<NA>2015-09-25
2627순창시장정기시장(5일장)1일, 6일전라북도 순창군 순창읍 남계로 58194밤, 고추 등온누리상품권, 전자상품권<NA>YY1990년2015-09-25
2728동계시장정기시장(5일장)2일, 7일전라북도 순창군 동계면 동계로 3720매실, 밤 등<NA><NA>YY<NA>2015-09-25
2829복흥시장정기시장(5일장)3일, 8일전라북도 순창군 복흥면 정산2길 247배추, 무, 고랭지 채소<NA><NA>YY<NA>2015-09-25
2930흥덕시장정기시장(5일장)4일, 9일전라북도 고창군 흥덕면 흥덕리 240-425사과, 대추 등온누리상품권<NA>YY1987년2015-09-25
3031해리시장정기시장(5일장)4일, 9일전라북도 고창군 해리면 해리중앙로 56-2147천일염, 세하, 바지락온누리상품권<NA>YY2000년2015-09-25
3132대산시장정기시장(5일장)2일, 7일전라북도 고창군 대산면 공음대산로 93566배추, 대추온누리상품권<NA>YY1980년2015-09-25
3233무장시장정기시장(5일장)5일, 10일전라북도 고창군 무장면 왕제산로 72551부추온누리상품권<NA>YY1993년2015-09-25
3334상하시장정기시장(5일장)1일, 6일전라북도 고창군 상하면 상하1길 1650조개류, 젓갈류온누리상품권<NA>YY1997년2015-09-25