Overview

Dataset statistics

Number of variables14
Number of observations52
Missing cells88
Missing cells (%)12.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory116.5 B

Variable types

Numeric2
Text5
Categorical4
Boolean2
DateTime1

Alerts

공중화장실 보유여부 has constant value ""Constant
주차장 보유여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
자료출처 has constant value ""Constant
시장유형 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
시장개설주기 is highly overall correlated with 시장유형High correlation
순번 is highly overall correlated with 시장유형High correlation
취급품목 has 29 (55.8%) missing valuesMissing
홈페이지주소 has 39 (75.0%) missing valuesMissing
공중화장실 보유여부 has 6 (11.5%) missing valuesMissing
주차장 보유여부 has 6 (11.5%) missing valuesMissing
개설년도 has 8 (15.4%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:12:01.394818
Analysis finished2024-03-14 01:12:02.719824
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.5
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-03-14T10:12:02.776658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q113.75
median26.5
Q339.25
95-th percentile49.45
Maximum52
Range51
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation15.154757
Coefficient of variation (CV)0.57187763
Kurtosis-1.2
Mean26.5
Median Absolute Deviation (MAD)13
Skewness0
Sum1378
Variance229.66667
MonotonicityStrictly increasing
2024-03-14T10:12:02.889971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
28 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%
43 1
1.9%

시장명
Text

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-03-14T10:12:03.073793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.0384615
Min length3

Characters and Unicode

Total characters262
Distinct characters83
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

Unique50 ?
Unique (%)96.2%

Sample

1st row서부시장
2nd row남부 시장
3rd row중앙 시장
4th row모래내 시장
5th row동부 시장
ValueCountFrequency (%)
시장 4
 
6.7%
공설시장 2
 
3.3%
상점가 2
 
3.3%
고산시장 1
 
1.7%
오수시장 1
 
1.7%
부안시장 1
 
1.7%
줄포시장 1
 
1.7%
대야시장 1
 
1.7%
북부시장 1
 
1.7%
금마시장 1
 
1.7%
Other values (45) 45
75.0%
2024-03-14T10:12:03.360914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 40
 
15.3%
시 39
 
14.9%
점 13
 
5.0%
가 13
 
5.0%
상 13
 
5.0%
8
 
3.1%
부 7
 
2.7%
산 7
 
2.7%
전 5
 
1.9%
중 4
 
1.5%
Other values (73) 113
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 254
96.9%
Space Separator 8
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 40
 
15.7%
시 39
 
15.4%
점 13
 
5.1%
가 13
 
5.1%
상 13
 
5.1%
부 7
 
2.8%
산 7
 
2.8%
전 5
 
2.0%
중 4
 
1.6%
앙 4
 
1.6%
Other values (72) 109
42.9%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 254
96.9%
Common 8
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 40
 
15.7%
시 39
 
15.4%
점 13
 
5.1%
가 13
 
5.1%
상 13
 
5.1%
부 7
 
2.8%
산 7
 
2.8%
전 5
 
2.0%
중 4
 
1.6%
앙 4
 
1.6%
Other values (72) 109
42.9%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 254
96.9%
ASCII 8
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 40
 
15.7%
시 39
 
15.4%
점 13
 
5.1%
가 13
 
5.1%
상 13
 
5.1%
부 7
 
2.8%
산 7
 
2.8%
전 5
 
2.0%
중 4
 
1.6%
앙 4
 
1.6%
Other values (72) 109
42.9%
ASCII
ValueCountFrequency (%)
8
100.0%

시장유형
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
상설시장
31 
상점가
13 
상설+정기시장
8 

Length

Max length7
Median length4
Mean length4.2115385
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상설시장 31
59.6%
상점가 13
25.0%
상설+정기시장 8
 
15.4%

Length

2024-03-14T10:12:03.497987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:12:03.615579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상설시장 31
59.6%
상점가 13
25.0%
상설+정기시장 8
 
15.4%

시장개설주기
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
상설시장
32 
상점가
13 
2일, 7일
 
2
4일, 9일
 
2
1일, 6일
 
1
Other values (2)
 
2

Length

Max length7
Median length4
Mean length4.0384615
Min length3

Unique

Unique3 ?
Unique (%)5.8%

Sample

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

Common Values

ValueCountFrequency (%)
상설시장 32
61.5%
상점가 13
25.0%
2일, 7일 2
 
3.8%
4일, 9일 2
 
3.8%
1일, 6일 1
 
1.9%
5일, 10일 1
 
1.9%
3일, 8일 1
 
1.9%

Length

2024-03-14T10:12:03.730573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:12:03.825786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상설시장 32
54.2%
상점가 13
22.0%
2일 2
 
3.4%
7일 2
 
3.4%
4일 2
 
3.4%
9일 2
 
3.4%
1일 1
 
1.7%
6일 1
 
1.7%
5일 1
 
1.7%
10일 1
 
1.7%
Other values (2) 2
 
3.4%

주소
Text

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-03-14T10:12:04.044956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length18.769231
Min length15

Characters and Unicode

Total characters976
Distinct characters103
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

Unique50 ?
Unique (%)96.2%

Sample

1st row전라북도 전주시 효자동 1가 201-2
2nd row전라북도 전주시 완산구 풍남문1길 19-1
3rd row전라북도 전주시 완산구 태평3길 70
4th row전라북도 전주시 덕진구 모래내4길 8-8
5th row전라북도 전주시 완산구 충경로 109
ValueCountFrequency (%)
전라북도 52
22.7%
익산시 12
 
5.2%
전주시 11
 
4.8%
군산시 8
 
3.5%
완산구 7
 
3.1%
정읍시 6
 
2.6%
김제시 4
 
1.7%
20 3
 
1.3%
완주군 3
 
1.3%
덕진구 3
 
1.3%
Other values (105) 120
52.4%
2024-03-14T10:12:04.462750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
177
18.1%
전 63
 
6.5%
북 54
 
5.5%
도 52
 
5.3%
라 52
 
5.3%
시 46
 
4.7%
1 45
 
4.6%
산 32
 
3.3%
길 30
 
3.1%
3 26
 
2.7%
Other values (93) 399
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 616
63.1%
Space Separator 177
 
18.1%
Decimal Number 167
 
17.1%
Dash Punctuation 14
 
1.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 63
 
10.2%
북 54
 
8.8%
도 52
 
8.4%
라 52
 
8.4%
시 46
 
7.5%
산 32
 
5.2%
길 30
 
4.9%
로 23
 
3.7%
군 17
 
2.8%
동 15
 
2.4%
Other values (79) 232
37.7%
Decimal Number
ValueCountFrequency (%)
1 45
26.9%
3 26
15.6%
2 20
12.0%
5 14
 
8.4%
4 13
 
7.8%
0 12
 
7.2%
9 11
 
6.6%
8 10
 
6.0%
7 9
 
5.4%
6 7
 
4.2%
Space Separator
ValueCountFrequency (%)
177
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 616
63.1%
Common 360
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 63
 
10.2%
북 54
 
8.8%
도 52
 
8.4%
라 52
 
8.4%
시 46
 
7.5%
산 32
 
5.2%
길 30
 
4.9%
로 23
 
3.7%
군 17
 
2.8%
동 15
 
2.4%
Other values (79) 232
37.7%
Common
ValueCountFrequency (%)
177
49.2%
1 45
 
12.5%
3 26
 
7.2%
2 20
 
5.6%
5 14
 
3.9%
- 14
 
3.9%
4 13
 
3.6%
0 12
 
3.3%
9 11
 
3.1%
8 10
 
2.8%
Other values (4) 18
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 616
63.1%
ASCII 360
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
177
49.2%
1 45
 
12.5%
3 26
 
7.2%
2 20
 
5.6%
5 14
 
3.9%
- 14
 
3.9%
4 13
 
3.6%
0 12
 
3.3%
9 11
 
3.1%
8 10
 
2.8%
Other values (4) 18
 
5.0%
Hangul
ValueCountFrequency (%)
전 63
 
10.2%
북 54
 
8.8%
도 52
 
8.4%
라 52
 
8.4%
시 46
 
7.5%
산 32
 
5.2%
길 30
 
4.9%
로 23
 
3.7%
군 17
 
2.8%
동 15
 
2.4%
Other values (79) 232
37.7%

점포수
Real number (ℝ)

Distinct45
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean125.15385
Minimum25
Maximum382
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-03-14T10:12:04.577673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile31.65
Q154.75
median87.5
Q3161.25
95-th percentile354.5
Maximum382
Range357
Interquartile range (IQR)106.5

Descriptive statistics

Standard deviation96.013558
Coefficient of variation (CV)0.76716426
Kurtosis1.0159919
Mean125.15385
Median Absolute Deviation (MAD)46
Skewness1.3431054
Sum6508
Variance9218.6033
MonotonicityNot monotonic
2024-03-14T10:12:04.681098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
38 2
 
3.8%
46 2
 
3.8%
106 2
 
3.8%
282 2
 
3.8%
85 2
 
3.8%
72 2
 
3.8%
76 2
 
3.8%
143 1
 
1.9%
30 1
 
1.9%
168 1
 
1.9%
Other values (35) 35
67.3%
ValueCountFrequency (%)
25 1
1.9%
29 1
1.9%
30 1
1.9%
33 1
1.9%
34 1
1.9%
38 2
3.8%
45 1
1.9%
46 2
3.8%
48 1
1.9%
49 1
1.9%
ValueCountFrequency (%)
382 1
1.9%
370 1
1.9%
360 1
1.9%
350 1
1.9%
282 2
3.8%
260 1
1.9%
229 1
1.9%
220 1
1.9%
199 1
1.9%
174 1
1.9%

취급품목
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing29
Missing (%)55.8%
Memory size548.0 B
2024-03-14T10:12:04.840036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length10.521739
Min length3

Characters and Unicode

Total characters242
Distinct characters92
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

Unique23 ?
Unique (%)100.0%

Sample

1st row김부각,육류,과일,건강식품,배추 등
2nd row박대, 김치 등
3rd row치킨집, 건어물 등
4th row방앗간, 음식점 등
5th row야채, 과일, 생선 등
ValueCountFrequency (%)
등 22
31.0%
농산물 2
 
2.8%
음식점 2
 
2.8%
순대국밥 2
 
2.8%
생선 2
 
2.8%
야채 2
 
2.8%
대추 2
 
2.8%
영상기기 1
 
1.4%
커피숍 1
 
1.4%
귀금속 1
 
1.4%
Other values (34) 34
47.9%
2024-03-14T10:12:05.088883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
19.8%
, 30
 
12.4%
등 22
 
9.1%
대 5
 
2.1%
물 5
 
2.1%
추 5
 
2.1%
산 4
 
1.7%
과 4
 
1.7%
식 3
 
1.2%
밥 3
 
1.2%
Other values (82) 113
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164
67.8%
Space Separator 48
 
19.8%
Other Punctuation 30
 
12.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 22
 
13.4%
대 5
 
3.0%
물 5
 
3.0%
추 5
 
3.0%
산 4
 
2.4%
과 4
 
2.4%
식 3
 
1.8%
밥 3
 
1.8%
국 3
 
1.8%
농 3
 
1.8%
Other values (80) 107
65.2%
Space Separator
ValueCountFrequency (%)
48
100.0%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164
67.8%
Common 78
32.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 22
 
13.4%
대 5
 
3.0%
물 5
 
3.0%
추 5
 
3.0%
산 4
 
2.4%
과 4
 
2.4%
식 3
 
1.8%
밥 3
 
1.8%
국 3
 
1.8%
농 3
 
1.8%
Other values (80) 107
65.2%
Common
ValueCountFrequency (%)
48
61.5%
, 30
38.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164
67.8%
ASCII 78
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
61.5%
, 30
38.5%
Hangul
ValueCountFrequency (%)
등 22
 
13.4%
대 5
 
3.0%
물 5
 
3.0%
추 5
 
3.0%
산 4
 
2.4%
과 4
 
2.4%
식 3
 
1.8%
밥 3
 
1.8%
국 3
 
1.8%
농 3
 
1.8%
Other values (80) 107
65.2%

사용가능상품권
Categorical

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
온누리상품권, 전자상품권
31 
<NA>
17 
온누리상품권
4 

Length

Max length13
Median length13
Mean length9.5961538
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
온누리상품권, 전자상품권 31
59.6%
<NA> 17
32.7%
온누리상품권 4
 
7.7%

Length

2024-03-14T10:12:05.189252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:12:05.266980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온누리상품권 35
42.2%
전자상품권 31
37.3%
na 17
20.5%

홈페이지주소
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing39
Missing (%)75.0%
Memory size548.0 B
2024-03-14T10:12:05.407390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length18
Mean length13.923077
Min length8

Characters and Unicode

Total characters181
Distinct characters29
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)100.0%

Sample

1st rowwww.jjnm.kr
2nd rowwww.jjja.kr
3rd rowjjmrn.kr
4th rowwww.gssysj.kr
5th rowwww.gsmssj.kr
ValueCountFrequency (%)
www.jjnm.kr 1
 
7.7%
www.jjja.kr 1
 
7.7%
jjmrn.kr 1
 
7.7%
www.gssysj.kr 1
 
7.7%
www.gsmssj.kr 1
 
7.7%
www.isnb.kr 1
 
7.7%
http://www.nwyn.kr 1
 
7.7%
gosanmiso.co.kr 1
 
7.7%
blog.naver.com/buanmarket 1
 
7.7%
www.isbb.kr 1
 
7.7%
Other values (3) 3
23.1%
2024-03-14T10:12:05.670512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 29
16.0%
. 25
13.8%
r 14
 
7.7%
k 12
 
6.6%
s 11
 
6.1%
n 10
 
5.5%
j 9
 
5.0%
m 8
 
4.4%
o 7
 
3.9%
/ 6
 
3.3%
Other values (19) 50
27.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 141
77.9%
Other Punctuation 33
 
18.2%
Uppercase Letter 7
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 29
20.6%
r 14
9.9%
k 12
8.5%
s 11
 
7.8%
n 10
 
7.1%
j 9
 
6.4%
m 8
 
5.7%
o 7
 
5.0%
t 6
 
4.3%
a 6
 
4.3%
Other values (11) 29
20.6%
Uppercase Letter
ValueCountFrequency (%)
I 2
28.6%
R 2
28.6%
N 1
14.3%
G 1
14.3%
O 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 25
75.8%
/ 6
 
18.2%
: 2
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 148
81.8%
Common 33
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 29
19.6%
r 14
 
9.5%
k 12
 
8.1%
s 11
 
7.4%
n 10
 
6.8%
j 9
 
6.1%
m 8
 
5.4%
o 7
 
4.7%
t 6
 
4.1%
a 6
 
4.1%
Other values (16) 36
24.3%
Common
ValueCountFrequency (%)
. 25
75.8%
/ 6
 
18.2%
: 2
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 181
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 29
16.0%
. 25
13.8%
r 14
 
7.7%
k 12
 
6.6%
s 11
 
6.1%
n 10
 
5.5%
j 9
 
5.0%
m 8
 
4.4%
o 7
 
3.9%
/ 6
 
3.3%
Other values (19) 50
27.6%

공중화장실 보유여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.2%
Missing6
Missing (%)11.5%
Memory size236.0 B
True
46 
(Missing)
6 
ValueCountFrequency (%)
True 46
88.5%
(Missing) 6
 
11.5%
2024-03-14T10:12:05.763295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

주차장 보유여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.2%
Missing6
Missing (%)11.5%
Memory size236.0 B
True
46 
(Missing)
6 
ValueCountFrequency (%)
True 46
88.5%
(Missing) 6
 
11.5%
2024-03-14T10:12:05.824803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

개설년도
Text

MISSING 

Distinct28
Distinct (%)63.6%
Missing8
Missing (%)15.4%
Memory size548.0 B
2024-03-14T10:12:05.962122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters220
Distinct characters11
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

Unique18 ?
Unique (%)40.9%

Sample

1st row1938년
2nd row1990년
3rd row1970년
4th row2008년
5th row2007년
ValueCountFrequency (%)
2005년 5
 
11.4%
2009년 4
 
9.1%
2008년 3
 
6.8%
1970년 2
 
4.5%
2000년 2
 
4.5%
2006년 2
 
4.5%
1992년 2
 
4.5%
2007년 2
 
4.5%
1990년 2
 
4.5%
1980년 2
 
4.5%
Other values (18) 18
40.9%
2024-03-14T10:12:06.198489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 54
24.5%
년 44
20.0%
9 34
15.5%
2 28
12.7%
1 25
11.4%
7 8
 
3.6%
5 7
 
3.2%
8 7
 
3.2%
3 5
 
2.3%
6 4
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 176
80.0%
Other Letter 44
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 54
30.7%
9 34
19.3%
2 28
15.9%
1 25
14.2%
7 8
 
4.5%
5 7
 
4.0%
8 7
 
4.0%
3 5
 
2.8%
6 4
 
2.3%
4 4
 
2.3%
Other Letter
ValueCountFrequency (%)
년 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 176
80.0%
Hangul 44
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 54
30.7%
9 34
19.3%
2 28
15.9%
1 25
14.2%
7 8
 
4.5%
5 7
 
4.0%
8 7
 
4.0%
3 5
 
2.8%
6 4
 
2.3%
4 4
 
2.3%
Hangul
ValueCountFrequency (%)
년 44
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 176
80.0%
Hangul 44
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 54
30.7%
9 34
19.3%
2 28
15.9%
1 25
14.2%
7 8
 
4.5%
5 7
 
4.0%
8 7
 
4.0%
3 5
 
2.8%
6 4
 
2.3%
4 4
 
2.3%
Hangul
ValueCountFrequency (%)
년 44
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
Minimum2015-09-25 00:00:00
Maximum2015-09-25 00:00:00
2024-03-14T10:12:06.309752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:12:06.408818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
일자리경제정책관
52 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일자리경제정책관 52
100.0%

Length

2024-03-14T10:12:06.761043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:12:06.844064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일자리경제정책관 52
100.0%

Interactions

2024-03-14T10:12:02.234787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:12:02.041825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:12:02.303185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:12:02.147191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:12:06.897251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시장명시장유형시장개설주기주소점포수취급품목사용가능상품권홈페이지주소개설년도
순번1.0000.9290.9400.7440.9290.4531.0000.0001.0000.000
시장명0.9291.0000.0000.0000.9970.0001.0001.0001.0000.988
시장유형0.9400.0001.0000.9370.0000.6221.0000.0001.0000.327
시장개설주기0.7440.0000.9371.0000.0000.0001.0000.5701.0000.734
주소0.9290.9970.0000.0001.0000.9571.0001.0001.0001.000
점포수0.4530.0000.6220.0000.9571.0001.0000.0001.0000.000
취급품목1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사용가능상품권0.0001.0000.0000.5701.0000.0001.0001.0001.0001.000
홈페이지주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개설년도0.0000.9880.3270.7341.0000.0001.0001.0001.0001.000
2024-03-14T10:12:06.993801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시장유형사용가능상품권시장개설주기
시장유형1.0000.0000.916
사용가능상품권0.0001.0000.383
시장개설주기0.9160.3831.000
2024-03-14T10:12:07.094989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번점포수시장유형시장개설주기사용가능상품권
순번1.000-0.0070.8550.4810.000
점포수-0.0071.0000.3160.0000.000
시장유형0.8550.3161.0000.9160.000
시장개설주기0.4810.0000.9161.0000.383
사용가능상품권0.0000.0000.0000.3831.000

Missing values

2024-03-14T10:12:02.407413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:12:02.550009image/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.
2024-03-14T10:12:02.656890image/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

순번시장명시장유형시장개설주기주소점포수취급품목사용가능상품권홈페이지주소공중화장실 보유여부주차장 보유여부개설년도데이터기준일자자료출처
01서부시장상설시장상설시장전라북도 전주시 효자동 1가 201-225김부각,육류,과일,건강식품,배추 등온누리상품권, 전자상품권<NA><NA><NA><NA>2015-09-25일자리경제정책관
12남부 시장상설시장상설시장전라북도 전주시 완산구 풍남문1길 19-1350<NA>온누리상품권www.jjnm.krYY1938년2015-09-25일자리경제정책관
23중앙 시장상설시장상설시장전라북도 전주시 완산구 태평3길 70370<NA>온누리상품권, 전자상품권www.jjja.krYY1990년2015-09-25일자리경제정책관
34모래내 시장상설시장상설시장전라북도 전주시 덕진구 모래내4길 8-8220<NA>온누리상품권, 전자상품권jjmrn.krYY1970년2015-09-25일자리경제정책관
45동부 시장상설시장상설시장전라북도 전주시 완산구 충경로 10945<NA>온누리상품권, 전자상품권<NA>YY2008년2015-09-25일자리경제정책관
56신중앙시장상설시장상설시장전라북도 전주시 완산구 태평5길 33229<NA>온누리상품권, 전자상품권<NA>YY2007년2015-09-25일자리경제정책관
67공설시장상설시장상설시장전라북도 군산시 신금길 18282<NA>온누리상품권, 전자상품권<NA>YY1990년2015-09-25일자리경제정책관
78신영시장상설시장상설시장전라북도 군산시 동신영길 36160<NA>온누리상품권, 전자상품권www.gssysj.krYY1993년2015-09-25일자리경제정책관
89역전종합시장상설시장상설시장전라북도 군산시 대명3길 31102<NA>온누리상품권, 전자상품권<NA>YY1992년2015-09-25일자리경제정책관
910명산시장상설시장상설시장전라북도 군산시 금광길 2072박대, 김치 등온누리상품권, 전자상품권www.gsmssj.krYY1950년2015-09-25일자리경제정책관
순번시장명시장유형시장개설주기주소점포수취급품목사용가능상품권홈페이지주소공중화장실 보유여부주차장 보유여부개설년도데이터기준일자자료출처
4243서부시장상점가상점가상점가전라북도 전주시 완산구 효자동 1가205-1294정육, 순대국밥 등<NA><NA>YY2012년2015-09-25일자리경제정책관
4344전북대 대학로 상점가상점가상점가전라북도 전주시 덕진구 권삼득로 285360<NA><NA><NA><NA><NA><NA>2015-09-25일자리경제정책관
4445그린상점가상점가상점가전라북도 익산시 동서로19길 9981커피숍, 음식점 등<NA><NA>YY2005년2015-09-25일자리경제정책관
4546원광온누리상점가상점가상점가전라북도 익산시 동서로19길 8876<NA><NA><NA>YY2010년2015-09-25일자리경제정책관
4647중앙로상점가상점가상점가전라북도 정읍시 중앙동 12585<NA><NA><NA>YY2005년2015-09-25일자리경제정책관
4748새암길상점가상점가상점가전라북도 정읍시 새암길 40-1(수성동)106귀금속, 신발 등<NA><NA>YY2000년2015-09-25일자리경제정책관
4849연지상점가상점가상점가전라북도 정읍시 명덕로 47382<NA><NA><NA><NA><NA><NA>2015-09-25일자리경제정책관
4950정읍산외한우마을상점가상점가상점가전라북도 정읍시 산외면 산외로 43578<NA><NA><NA>YY2005년2015-09-25일자리경제정책관
5051오수상점가상점가상점가전라북도 임실군 오수면 삼일로 11137<NA><NA><NA>YY<NA>2015-09-25일자리경제정책관
5152고산 구시장 상점가상점가상점가전라북도 완주군 고산면 고산로 113-1106<NA><NA><NA><NA><NA><NA>2015-09-25일자리경제정책관