Overview

Dataset statistics

Number of variables16
Number of observations51
Missing cells188
Missing cells (%)23.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory133.6 B

Variable types

Text7
Categorical5
Unsupported2
Numeric1
DateTime1

Dataset

Description전라북_전통시장_16년12월
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202537

Alerts

데이터기준일자 has constant value ""Constant
주차장보유여부 is highly overall correlated with 점포수 and 4 other fieldsHigh correlation
공중화장실보유여부 is highly overall correlated with 점포수 and 4 other fieldsHigh correlation
사용가능상품권 is highly overall correlated with 공중화장실보유여부 and 1 other fieldsHigh correlation
시장개설주기 is highly overall correlated with 시장유형 and 2 other fieldsHigh correlation
시장유형 is highly overall correlated with 시장개설주기 and 2 other fieldsHigh correlation
점포수 is highly overall correlated with 공중화장실보유여부 and 1 other fieldsHigh correlation
공중화장실보유여부 is highly imbalanced (86.1%)Imbalance
주차장보유여부 is highly imbalanced (86.1%)Imbalance
위도 has 51 (100.0%) missing valuesMissing
경도 has 51 (100.0%) missing valuesMissing
취급품목 has 28 (54.9%) missing valuesMissing
홈페이지주소 has 36 (70.6%) missing valuesMissing
개설년도 has 7 (13.7%) missing valuesMissing
전화번호 has 14 (27.5%) missing valuesMissing
데이터기준일자 has 1 (2.0%) missing valuesMissing
위도 is an unsupported type, check if it needs cleaning or further analysisUnsupported
경도 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:49:06.624468
Analysis finished2024-03-14 00:49:07.766746
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시장명
Text

Distinct50
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-03-14T09:49:07.947783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.0588235
Min length3

Characters and Unicode

Total characters258
Distinct characters82
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

Unique49 ?
Unique (%)96.1%

Sample

1st row서부시장
2nd row남부 시장
3rd row중앙 시장
4th row모래내 시장
5th row동부 시장
ValueCountFrequency (%)
시장 4
 
6.8%
공설시장 2
 
3.4%
상점가 2
 
3.4%
동문상점가 1
 
1.7%
부안시장 1
 
1.7%
줄포시장 1
 
1.7%
대야시장 1
 
1.7%
북부시장 1
 
1.7%
금마시장 1
 
1.7%
함열시장 1
 
1.7%
Other values (44) 44
74.6%
2024-03-14T09:49:08.270648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 39
 
15.1%
시 38
 
14.7%
가 13
 
5.0%
상 13
 
5.0%
점 13
 
5.0%
8
 
3.1%
부 7
 
2.7%
산 7
 
2.7%
전 5
 
1.9%
중 4
 
1.6%
Other values (72) 111
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 250
96.9%
Space Separator 8
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 39
 
15.6%
시 38
 
15.2%
가 13
 
5.2%
상 13
 
5.2%
점 13
 
5.2%
부 7
 
2.8%
산 7
 
2.8%
전 5
 
2.0%
중 4
 
1.6%
앙 4
 
1.6%
Other values (71) 107
42.8%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 250
96.9%
Common 8
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 39
 
15.6%
시 38
 
15.2%
가 13
 
5.2%
상 13
 
5.2%
점 13
 
5.2%
부 7
 
2.8%
산 7
 
2.8%
전 5
 
2.0%
중 4
 
1.6%
앙 4
 
1.6%
Other values (71) 107
42.8%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 250
96.9%
ASCII 8
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 39
 
15.6%
시 38
 
15.2%
가 13
 
5.2%
상 13
 
5.2%
점 13
 
5.2%
부 7
 
2.8%
산 7
 
2.8%
전 5
 
2.0%
중 4
 
1.6%
앙 4
 
1.6%
Other values (71) 107
42.8%
ASCII
ValueCountFrequency (%)
8
100.0%

시장유형
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
상설시장
30 
상점가
13 
상설+정기
8 

Length

Max length5
Median length4
Mean length3.9019608
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상설시장 30
58.8%
상점가 13
25.5%
상설+정기 8
 
15.7%

Length

2024-03-14T09:49:08.393175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:49:08.476688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상설시장 30
58.8%
상점가 13
25.5%
상설+정기 8
 
15.7%

소재지도로명주소
Text

Distinct50
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-03-14T09:49:08.683994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length21.333333
Min length15

Characters and Unicode

Total characters1088
Distinct characters104
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

Unique49 ?
Unique (%)96.1%

Sample

1st row전라북도 전주시 완산구 효동2길 18
2nd row전라북도 전주시 완산구 풍남문1길 19-1 (전동3가)
3rd row전라북도 전주시 완산구 태평3길 70 (태평동)
4th row전라북도 전주시 덕진구 모래내4길 8-8(인후동2가)
5th row전라북도 전주시 완산구 충경로 109 (경원동3가)
ValueCountFrequency (%)
전라북도 51
22.2%
익산시 12
 
5.2%
전주시 11
 
4.8%
완산구 8
 
3.5%
군산시 7
 
3.0%
정읍시 6
 
2.6%
김제시 4
 
1.7%
중앙로3길 3
 
1.3%
덕진구 3
 
1.3%
완주군 3
 
1.3%
Other values (109) 122
53.0%
2024-03-14T09:49:09.030820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
 
16.5%
전 63
 
5.8%
북 54
 
5.0%
도 51
 
4.7%
라 51
 
4.7%
시 47
 
4.3%
1 44
 
4.0%
동 38
 
3.5%
길 34
 
3.1%
산 32
 
2.9%
Other values (94) 495
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 687
63.1%
Space Separator 179
 
16.5%
Decimal Number 159
 
14.6%
Close Punctuation 27
 
2.5%
Open Punctuation 27
 
2.5%
Dash Punctuation 9
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 63
 
9.2%
북 54
 
7.9%
도 51
 
7.4%
라 51
 
7.4%
시 47
 
6.8%
동 38
 
5.5%
길 34
 
4.9%
산 32
 
4.7%
로 25
 
3.6%
군 16
 
2.3%
Other values (80) 276
40.2%
Decimal Number
ValueCountFrequency (%)
1 44
27.7%
3 29
18.2%
2 20
12.6%
8 13
 
8.2%
5 12
 
7.5%
9 11
 
6.9%
4 9
 
5.7%
0 8
 
5.0%
7 8
 
5.0%
6 5
 
3.1%
Space Separator
ValueCountFrequency (%)
179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 687
63.1%
Common 401
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 63
 
9.2%
북 54
 
7.9%
도 51
 
7.4%
라 51
 
7.4%
시 47
 
6.8%
동 38
 
5.5%
길 34
 
4.9%
산 32
 
4.7%
로 25
 
3.6%
군 16
 
2.3%
Other values (80) 276
40.2%
Common
ValueCountFrequency (%)
179
44.6%
1 44
 
11.0%
3 29
 
7.2%
) 27
 
6.7%
( 27
 
6.7%
2 20
 
5.0%
8 13
 
3.2%
5 12
 
3.0%
9 11
 
2.7%
- 9
 
2.2%
Other values (4) 30
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 687
63.1%
ASCII 401
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
44.6%
1 44
 
11.0%
3 29
 
7.2%
) 27
 
6.7%
( 27
 
6.7%
2 20
 
5.0%
8 13
 
3.2%
5 12
 
3.0%
9 11
 
2.7%
- 9
 
2.2%
Other values (4) 30
 
7.5%
Hangul
ValueCountFrequency (%)
전 63
 
9.2%
북 54
 
7.9%
도 51
 
7.4%
라 51
 
7.4%
시 47
 
6.8%
동 38
 
5.5%
길 34
 
4.9%
산 32
 
4.7%
로 25
 
3.6%
군 16
 
2.3%
Other values (80) 276
40.2%

소재지지번주소
Text

Distinct50
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-03-14T09:49:09.275974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length19.509804
Min length16

Characters and Unicode

Total characters995
Distinct characters84
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

Unique49 ?
Unique (%)96.1%

Sample

1st row전라북도 전주시 효자동 1가 201-2
2nd row전라북도 전주시 완산구 전동 295-2
3rd row전라북도 전주시 완산구 태평동 36-1
4th row전라북도 전주시 덕진구 인후동2가 203-10
5th row전라북도 전주시 완산구 경원동3가 90-13
ValueCountFrequency (%)
전라북도 51
22.8%
익산시 12
 
5.4%
전주시 10
 
4.5%
군산시 7
 
3.1%
완산구 7
 
3.1%
정읍시 6
 
2.7%
김제시 4
 
1.8%
덕진구 3
 
1.3%
읍내리 3
 
1.3%
신동 3
 
1.3%
Other values (98) 118
52.7%
2024-03-14T09:49:09.616104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
173
17.4%
전 63
 
6.3%
북 52
 
5.2%
도 51
 
5.1%
라 51
 
5.1%
1 45
 
4.5%
- 44
 
4.4%
시 42
 
4.2%
동 38
 
3.8%
산 31
 
3.1%
Other values (74) 405
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 575
57.8%
Decimal Number 203
 
20.4%
Space Separator 173
 
17.4%
Dash Punctuation 44
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 63
 
11.0%
북 52
 
9.0%
도 51
 
8.9%
라 51
 
8.9%
시 42
 
7.3%
동 38
 
6.6%
산 31
 
5.4%
군 16
 
2.8%
읍 14
 
2.4%
리 13
 
2.3%
Other values (62) 204
35.5%
Decimal Number
ValueCountFrequency (%)
1 45
22.2%
3 25
12.3%
4 24
11.8%
2 22
10.8%
8 19
9.4%
5 18
 
8.9%
6 16
 
7.9%
0 12
 
5.9%
7 12
 
5.9%
9 10
 
4.9%
Space Separator
ValueCountFrequency (%)
173
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 575
57.8%
Common 420
42.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 63
 
11.0%
북 52
 
9.0%
도 51
 
8.9%
라 51
 
8.9%
시 42
 
7.3%
동 38
 
6.6%
산 31
 
5.4%
군 16
 
2.8%
읍 14
 
2.4%
리 13
 
2.3%
Other values (62) 204
35.5%
Common
ValueCountFrequency (%)
173
41.2%
1 45
 
10.7%
- 44
 
10.5%
3 25
 
6.0%
4 24
 
5.7%
2 22
 
5.2%
8 19
 
4.5%
5 18
 
4.3%
6 16
 
3.8%
0 12
 
2.9%
Other values (2) 22
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 575
57.8%
ASCII 420
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
173
41.2%
1 45
 
10.7%
- 44
 
10.5%
3 25
 
6.0%
4 24
 
5.7%
2 22
 
5.2%
8 19
 
4.5%
5 18
 
4.3%
6 16
 
3.8%
0 12
 
2.9%
Other values (2) 22
 
5.2%
Hangul
ValueCountFrequency (%)
전 63
 
11.0%
북 52
 
9.0%
도 51
 
8.9%
라 51
 
8.9%
시 42
 
7.3%
동 38
 
6.6%
산 31
 
5.4%
군 16
 
2.8%
읍 14
 
2.4%
리 13
 
2.3%
Other values (62) 204
35.5%

시장개설주기
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size540.0 B
상설시장
31 
상점가
13 
2일, 7일
 
2
4일, 9일
 
2
1일, 6일
 
1
Other values (2)
 
2

Length

Max length7
Median length4
Mean length4.0392157
Min length3

Unique

Unique3 ?
Unique (%)5.9%

Sample

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

Common Values

ValueCountFrequency (%)
상설시장 31
60.8%
상점가 13
25.5%
2일, 7일 2
 
3.9%
4일, 9일 2
 
3.9%
1일, 6일 1
 
2.0%
5일, 10일 1
 
2.0%
3일, 8일 1
 
2.0%

Length

2024-03-14T09:49:09.731225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:49:09.828202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상설시장 31
53.4%
상점가 13
22.4%
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%

위도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size591.0 B

경도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size591.0 B

점포수
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.01961
Minimum11
Maximum440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-03-14T09:49:09.971466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile29.5
Q147
median87
Q3157.5
95-th percentile335
Maximum440
Range429
Interquartile range (IQR)110.5

Descriptive statistics

Standard deviation100.20249
Coefficient of variation (CV)0.82119993
Kurtosis1.6802112
Mean122.01961
Median Absolute Deviation (MAD)47
Skewness1.4628
Sum6223
Variance10040.54
MonotonicityNot monotonic
2024-03-14T09:49:10.107933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
40 3
 
5.9%
30 2
 
3.9%
46 2
 
3.9%
106 2
 
3.9%
76 2
 
3.9%
48 1
 
2.0%
182 1
 
2.0%
38 1
 
2.0%
138 1
 
2.0%
29 1
 
2.0%
Other values (35) 35
68.6%
ValueCountFrequency (%)
11 1
 
2.0%
23 1
 
2.0%
29 1
 
2.0%
30 2
3.9%
34 1
 
2.0%
38 1
 
2.0%
40 3
5.9%
43 1
 
2.0%
46 2
3.9%
48 1
 
2.0%
ValueCountFrequency (%)
440 1
2.0%
382 1
2.0%
350 1
2.0%
320 1
2.0%
298 1
2.0%
257 1
2.0%
245 1
2.0%
223 1
2.0%
221 1
2.0%
199 1
2.0%

취급품목
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing28
Missing (%)54.9%
Memory size540.0 B
2024-03-14T09:49:10.284460image/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%
2024-03-14T09:49:10.549785image/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

HIGH CORRELATION 

Distinct3
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
온누리상품권, 전자상품권
30 
<NA>
17 
온누리상품권
4 

Length

Max length13
Median length13
Mean length9.5294118
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 30
58.8%
<NA> 17
33.3%
온누리상품권 4
 
7.8%

Length

2024-03-14T09:49:10.662352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:49:10.753958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온누리상품권 34
42.0%
전자상품권 30
37.0%
na 17
21.0%

홈페이지주소
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing36
Missing (%)70.6%
Memory size540.0 B
2024-03-14T09:49:10.885356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length24
Mean length15.866667
Min length8

Characters and Unicode

Total characters238
Distinct characters31
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

Unique15 ?
Unique (%)100.0%

Sample

1st rowhttps://dawayu.modoo.at/
2nd rowwww.jjnm.kr
3rd rowwww.jjja.kr
4th rowjjmrn.kr
5th rowhttp://shinjoongang.allofthat.kr/
ValueCountFrequency (%)
https://dawayu.modoo.at 1
 
6.7%
www.jjnm.kr 1
 
6.7%
www.jjja.kr 1
 
6.7%
jjmrn.kr 1
 
6.7%
http://shinjoongang.allofthat.kr 1
 
6.7%
www.gssysj.kr 1
 
6.7%
www.gsmssj.kr 1
 
6.7%
www.isnb.kr 1
 
6.7%
http://www.nwyn.kr 1
 
6.7%
gosanmiso.co.kr 1
 
6.7%
Other values (5) 5
33.3%
2024-03-14T09:49:11.408648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 30
 
12.6%
. 29
 
12.2%
r 15
 
6.3%
n 13
 
5.5%
o 13
 
5.5%
s 13
 
5.5%
k 13
 
5.5%
t 13
 
5.5%
/ 12
 
5.0%
a 12
 
5.0%
Other values (21) 75
31.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 186
78.2%
Other Punctuation 45
 
18.9%
Uppercase Letter 7
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 30
16.1%
r 15
 
8.1%
n 13
 
7.0%
o 13
 
7.0%
s 13
 
7.0%
k 13
 
7.0%
t 13
 
7.0%
a 12
 
6.5%
j 10
 
5.4%
m 9
 
4.8%
Other values (13) 45
24.2%
Uppercase Letter
ValueCountFrequency (%)
R 2
28.6%
I 2
28.6%
G 1
14.3%
N 1
14.3%
O 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 29
64.4%
/ 12
26.7%
: 4
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 193
81.1%
Common 45
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 30
15.5%
r 15
 
7.8%
n 13
 
6.7%
o 13
 
6.7%
s 13
 
6.7%
k 13
 
6.7%
t 13
 
6.7%
a 12
 
6.2%
j 10
 
5.2%
m 9
 
4.7%
Other values (18) 52
26.9%
Common
ValueCountFrequency (%)
. 29
64.4%
/ 12
26.7%
: 4
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 30
 
12.6%
. 29
 
12.2%
r 15
 
6.3%
n 13
 
5.5%
o 13
 
5.5%
s 13
 
5.5%
k 13
 
5.5%
t 13
 
5.5%
/ 12
 
5.0%
a 12
 
5.0%
Other values (21) 75
31.5%

공중화장실보유여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
유
50 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0588235
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
유 50
98.0%
<NA> 1
 
2.0%

Length

2024-03-14T09:49:11.528313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:49:11.612975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유 50
98.0%
na 1
 
2.0%

주차장보유여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
유
50 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0588235
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
유 50
98.0%
<NA> 1
 
2.0%

Length

2024-03-14T09:49:11.699080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:49:11.795115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유 50
98.0%
na 1
 
2.0%

개설년도
Text

MISSING 

Distinct28
Distinct (%)63.6%
Missing7
Missing (%)13.7%
Memory size540.0 B
2024-03-14T09:49:11.944267image/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%
2024-03-14T09:49:12.183447image/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%

전화번호
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing14
Missing (%)27.5%
Memory size540.0 B
2024-03-14T09:49:12.441698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.891892
Min length8

Characters and Unicode

Total characters440
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

Unique37 ?
Unique (%)100.0%

Sample

1st row063-223-3321
2nd row063-284-1344
3rd row063-253-6535
4th row063-278-5802
5th row063-288-4487
ValueCountFrequency (%)
063-443-4192 1
 
2.7%
063-547-3894 1
 
2.7%
063-836-6731 1
 
2.7%
063-262-0119 1
 
2.7%
063-291-9429 1
 
2.7%
063-644-2007 1
 
2.7%
063-584-3070 1
 
2.7%
063-580-4612 1
 
2.7%
063-855-6891 1
 
2.7%
063-862-2900 1
 
2.7%
Other values (27) 27
73.0%
2024-03-14T09:49:12.762130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 73
16.6%
6 62
14.1%
3 61
13.9%
0 55
12.5%
2 39
8.9%
4 38
8.6%
8 35
8.0%
5 28
 
6.4%
1 20
 
4.5%
9 16
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 367
83.4%
Dash Punctuation 73
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 62
16.9%
3 61
16.6%
0 55
15.0%
2 39
10.6%
4 38
10.4%
8 35
9.5%
5 28
7.6%
1 20
 
5.4%
9 16
 
4.4%
7 13
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 440
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 73
16.6%
6 62
14.1%
3 61
13.9%
0 55
12.5%
2 39
8.9%
4 38
8.6%
8 35
8.0%
5 28
 
6.4%
1 20
 
4.5%
9 16
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 73
16.6%
6 62
14.1%
3 61
13.9%
0 55
12.5%
2 39
8.9%
4 38
8.6%
8 35
8.0%
5 28
 
6.4%
1 20
 
4.5%
9 16
 
3.6%

데이터기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)2.0%
Missing1
Missing (%)2.0%
Memory size540.0 B
Minimum2016-12-31 00:00:00
Maximum2016-12-31 00:00:00
2024-03-14T09:49:12.849330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:49:12.921614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T09:49:07.261771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:49:12.995009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시장명시장유형소재지도로명주소소재지지번주소시장개설주기점포수취급품목사용가능상품권홈페이지주소개설년도전화번호
시장명1.0000.0000.9970.9970.0000.8721.0001.0001.0000.9691.000
시장유형0.0001.0000.0000.0000.9370.0001.0000.0001.0000.4821.000
소재지도로명주소0.9970.0001.0001.0000.0000.9951.0001.0001.0000.9691.000
소재지지번주소0.9970.0001.0001.0000.0000.9951.0001.0001.0000.9691.000
시장개설주기0.0000.9370.0000.0001.0000.0001.0000.5611.0000.7871.000
점포수0.8720.0000.9950.9950.0001.0001.0000.3391.0000.0001.000
취급품목1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사용가능상품권1.0000.0001.0001.0000.5610.3391.0001.0001.0000.7571.000
홈페이지주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개설년도0.9690.4820.9690.9690.7870.0001.0000.7571.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-03-14T09:49:13.144904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차장보유여부공중화장실보유여부사용가능상품권시장개설주기시장유형
주차장보유여부1.0001.0001.0001.0001.000
공중화장실보유여부1.0001.0001.0001.0001.000
사용가능상품권1.0001.0001.0000.3750.000
시장개설주기1.0001.0000.3751.0000.915
시장유형1.0001.0000.0000.9151.000
2024-03-14T09:49:13.245280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
점포수시장유형시장개설주기사용가능상품권공중화장실보유여부주차장보유여부
점포수1.0000.0000.0000.2891.0001.000
시장유형0.0001.0000.9150.0001.0001.000
시장개설주기0.0000.9151.0000.3751.0001.000
사용가능상품권0.2890.0000.3751.0001.0001.000
공중화장실보유여부1.0001.0001.0001.0001.0001.000
주차장보유여부1.0001.0001.0001.0001.0001.000

Missing values

2024-03-14T09:49:07.357568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:49:07.532375image/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.
2024-03-14T09:49:07.662924image/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

시장명시장유형소재지도로명주소소재지지번주소시장개설주기위도경도점포수취급품목사용가능상품권홈페이지주소공중화장실보유여부주차장보유여부개설년도전화번호데이터기준일자
0서부시장상설시장전라북도 전주시 완산구 효동2길 18전라북도 전주시 효자동 1가 201-2상설시장<NA><NA>23김부각,육류,과일,건강식품,배추 등온누리상품권, 전자상품권https://dawayu.modoo.at/유유<NA>063-223-33212016. 12. 31
1남부 시장상설시장전라북도 전주시 완산구 풍남문1길 19-1 (전동3가)전라북도 전주시 완산구 전동 295-2상설시장<NA><NA>350<NA>온누리상품권www.jjnm.kr유유1938년063-284-13442016. 12. 31
2중앙 시장상설시장전라북도 전주시 완산구 태평3길 70 (태평동)전라북도 전주시 완산구 태평동 36-1상설시장<NA><NA>440<NA>온누리상품권, 전자상품권www.jjja.kr유유1990년063-253-65352016. 12. 31
3모래내 시장상설시장전라북도 전주시 덕진구 모래내4길 8-8(인후동2가)전라북도 전주시 덕진구 인후동2가 203-10상설시장<NA><NA>223<NA>온누리상품권, 전자상품권jjmrn.kr유유1970년063-278-58022016. 12. 31
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시장명시장유형소재지도로명주소소재지지번주소시장개설주기위도경도점포수취급품목사용가능상품권홈페이지주소공중화장실보유여부주차장보유여부개설년도전화번호데이터기준일자
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47연지상점가상점가전라북도 정읍시 명덕로 47전라북도 정읍시 연지동 329-15상점가<NA><NA>382<NA><NA><NA>유유2000년<NA>2016. 12. 31
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49오수상점가상점가전라북도 임실군 오수면 삼일로 11전라북도 오수면 오수리 366-3상점가<NA><NA>137<NA><NA><NA>유유2005년<NA>2016. 12. 31
50고산 구시장 상점가상점가전라북도 완주군 고사면 고산로 113-1전라북도 완주군 고산면 읍내리 548-2상점가<NA><NA>106<NA><NA><NA><NA><NA><NA><NA><NA>