Overview

Dataset statistics

Number of variables22
Number of observations78
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.9 KiB
Average record size in memory182.7 B

Variable types

Numeric4
Categorical10
Text5
Boolean2
DateTime1

Alerts

데이터기준 has constant value ""Constant
자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:56:52.476311
Analysis finished2024-03-14 01:56:52.856220
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.5
Minimum1
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2024-03-14T10:56:52.916881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.85
Q120.25
median39.5
Q358.75
95-th percentile74.15
Maximum78
Range77
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation22.660538
Coefficient of variation (CV)0.57368452
Kurtosis-1.2
Mean39.5
Median Absolute Deviation (MAD)19.5
Skewness0
Sum3081
Variance513.5
MonotonicityStrictly increasing
2024-03-14T10:56:53.051359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
51 1
 
1.3%
58 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
50 1
 
1.3%
Other values (68) 68
87.2%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
78 1
1.3%
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%

시군명
Categorical

Distinct14
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size756.0 B
익산시
13 
전주시
11 
군산시
8 
정읍시
7 
임실군
6 
Other values (9)
33 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
익산시 13
16.7%
전주시 11
14.1%
군산시 8
10.3%
정읍시 7
9.0%
임실군 6
7.7%
고창군 6
7.7%
김제시 5
 
6.4%
완주군 5
 
6.4%
남원시 4
 
5.1%
무주군 4
 
5.1%
Other values (4) 9
11.5%

Length

2024-03-14T10:56:53.183646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
익산시 13
16.7%
전주시 11
14.1%
군산시 8
10.3%
정읍시 7
9.0%
임실군 6
7.7%
고창군 6
7.7%
김제시 5
 
6.4%
완주군 5
 
6.4%
남원시 4
 
5.1%
무주군 4
 
5.1%
Other values (4) 9
11.5%

시장명
Text

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-03-14T10:56:53.411887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.7564103
Min length3

Characters and Unicode

Total characters371
Distinct characters107
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

Unique76 ?
Unique (%)97.4%

Sample

1st row서부시장
2nd row남부 시장
3rd row중앙 시장
4th row모래내 시장
5th row동부 시장
ValueCountFrequency (%)
시장 4
 
4.7%
공설시장 2
 
2.3%
상점가 2
 
2.3%
장계시장 1
 
1.2%
운봉시장 1
 
1.2%
장수시장 1
 
1.2%
순창시장 1
 
1.2%
강진시장 1
 
1.2%
관촌시장 1
 
1.2%
신평시장 1
 
1.2%
Other values (71) 71
82.6%
2024-03-14T10:56:53.780926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 69
18.6%
시 61
 
16.4%
상 14
 
3.8%
가 13
 
3.5%
점 13
 
3.5%
산 12
 
3.2%
8
 
2.2%
부 7
 
1.9%
동 6
 
1.6%
대 5
 
1.3%
Other values (97) 163
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 363
97.8%
Space Separator 8
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 69
19.0%
시 61
 
16.8%
상 14
 
3.9%
가 13
 
3.6%
점 13
 
3.6%
산 12
 
3.3%
부 7
 
1.9%
동 6
 
1.7%
대 5
 
1.4%
전 5
 
1.4%
Other values (96) 158
43.5%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 363
97.8%
Common 8
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 69
19.0%
시 61
 
16.8%
상 14
 
3.9%
가 13
 
3.6%
점 13
 
3.6%
산 12
 
3.3%
부 7
 
1.9%
동 6
 
1.7%
대 5
 
1.4%
전 5
 
1.4%
Other values (96) 158
43.5%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 363
97.8%
ASCII 8
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 69
19.0%
시 61
 
16.8%
상 14
 
3.9%
가 13
 
3.6%
점 13
 
3.6%
산 12
 
3.3%
부 7
 
1.9%
동 6
 
1.7%
대 5
 
1.4%
전 5
 
1.4%
Other values (96) 158
43.5%
ASCII
ValueCountFrequency (%)
8
100.0%

시장유형
Categorical

Distinct4
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size756.0 B
상설시장
31 
정기시장(5일장)
26 
상점가
13 
상설+정기시장
8 

Length

Max length9
Median length7
Mean length5.8076923
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상설시장 31
39.7%
정기시장(5일장) 26
33.3%
상점가 13
16.7%
상설+정기시장 8
 
10.3%

Length

2024-03-14T10:56:53.909513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:54.013825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상설시장 31
39.7%
정기시장(5일장 26
33.3%
상점가 13
16.7%
상설+정기시장 8
 
10.3%

도로명주소
Text

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-03-14T10:56:54.261357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21.5
Mean length17.884615
Min length1

Characters and Unicode

Total characters1395
Distinct characters131
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)97.4%

Sample

1st row전주시 완산구 효동2길 18
2nd row전주시 완산구 풍남문1길 17 (전동)
3rd row전주시 완산구 태평3길 70 (태평동)
4th row전주시 덕진구 모래내4길 8-8 (인후동2가)
5th row전주시 완산구 충경로 109 (경원동3가)
ValueCountFrequency (%)
익산시 13
 
4.1%
전주시 11
 
3.5%
완산구 8
 
2.5%
정읍시 7
 
2.2%
군산시 7
 
2.2%
임실군 6
 
1.9%
고창군 6
 
1.9%
완주군 5
 
1.6%
김제시 5
 
1.6%
무주군 4
 
1.3%
Other values (204) 245
77.3%
2024-03-14T10:56:54.615291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
239
 
17.1%
) 69
 
4.9%
( 69
 
4.9%
1 65
 
4.7%
시 54
 
3.9%
동 52
 
3.7%
로 49
 
3.5%
산 42
 
3.0%
2 38
 
2.7%
군 37
 
2.7%
Other values (121) 681
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 754
54.1%
Decimal Number 240
 
17.2%
Space Separator 239
 
17.1%
Close Punctuation 69
 
4.9%
Open Punctuation 69
 
4.9%
Dash Punctuation 23
 
1.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 54
 
7.2%
동 52
 
6.9%
로 49
 
6.5%
산 42
 
5.6%
군 37
 
4.9%
길 36
 
4.8%
면 27
 
3.6%
주 23
 
3.1%
읍 19
 
2.5%
창 14
 
1.9%
Other values (106) 401
53.2%
Decimal Number
ValueCountFrequency (%)
1 65
27.1%
2 38
15.8%
3 34
14.2%
5 22
 
9.2%
8 17
 
7.1%
6 15
 
6.2%
9 14
 
5.8%
4 13
 
5.4%
0 11
 
4.6%
7 11
 
4.6%
Space Separator
ValueCountFrequency (%)
239
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 754
54.1%
Common 641
45.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 54
 
7.2%
동 52
 
6.9%
로 49
 
6.5%
산 42
 
5.6%
군 37
 
4.9%
길 36
 
4.8%
면 27
 
3.6%
주 23
 
3.1%
읍 19
 
2.5%
창 14
 
1.9%
Other values (106) 401
53.2%
Common
ValueCountFrequency (%)
239
37.3%
) 69
 
10.8%
( 69
 
10.8%
1 65
 
10.1%
2 38
 
5.9%
3 34
 
5.3%
- 23
 
3.6%
5 22
 
3.4%
8 17
 
2.7%
6 15
 
2.3%
Other values (5) 50
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 754
54.1%
ASCII 641
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
37.3%
) 69
 
10.8%
( 69
 
10.8%
1 65
 
10.1%
2 38
 
5.9%
3 34
 
5.3%
- 23
 
3.6%
5 22
 
3.4%
8 17
 
2.7%
6 15
 
2.3%
Other values (5) 50
 
7.8%
Hangul
ValueCountFrequency (%)
시 54
 
7.2%
동 52
 
6.9%
로 49
 
6.5%
산 42
 
5.6%
군 37
 
4.9%
길 36
 
4.8%
면 27
 
3.6%
주 23
 
3.1%
읍 19
 
2.5%
창 14
 
1.9%
Other values (106) 401
53.2%

개설주기
Categorical

Distinct7
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
상설시장
32 
상점가
13 
1일, 6일
8 
2일, 7일
7 
3일, 8일
7 
Other values (2)
11 

Length

Max length7
Median length6
Mean length4.7564103
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상설시장 32
41.0%
상점가 13
16.7%
1일, 6일 8
 
10.3%
2일, 7일 7
 
9.0%
3일, 8일 7
 
9.0%
5일, 10일 6
 
7.7%
4일, 9일 5
 
6.4%

Length

2024-03-14T10:56:55.003820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:55.103782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상설시장 32
28.8%
상점가 13
11.7%
1일 8
 
7.2%
6일 8
 
7.2%
2일 7
 
6.3%
7일 7
 
6.3%
3일 7
 
6.3%
8일 7
 
6.3%
5일 6
 
5.4%
10일 6
 
5.4%
Other values (2) 10
 
9.0%

지번주소
Text

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-03-14T10:56:55.438787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length15.474359
Min length11

Characters and Unicode

Total characters1207
Distinct characters106
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

Unique76 ?
Unique (%)97.4%

Sample

1st row전주시 완산구 효자동1가 201-2
2nd row전주시 완산구 전동 296-9
3rd row전주시 완산구 태평동 36-1
4th row전주시 덕진구 인후동2가 203-10
5th row전주시 완산구 경원동3가 90-13
ValueCountFrequency (%)
익산시 13
 
4.6%
전주시 11
 
3.9%
군산시 8
 
2.8%
완산구 8
 
2.8%
정읍시 7
 
2.5%
고창군 6
 
2.1%
임실군 6
 
2.1%
김제시 5
 
1.8%
완주군 5
 
1.8%
무주군 4
 
1.4%
Other values (178) 211
74.3%
2024-03-14T10:56:55.855674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
206
 
17.1%
1 72
 
6.0%
- 65
 
5.4%
시 49
 
4.1%
동 42
 
3.5%
산 41
 
3.4%
리 40
 
3.3%
2 40
 
3.3%
군 39
 
3.2%
4 34
 
2.8%
Other values (96) 579
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 623
51.6%
Decimal Number 313
25.9%
Space Separator 206
 
17.1%
Dash Punctuation 65
 
5.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 49
 
7.9%
동 42
 
6.7%
산 41
 
6.6%
리 40
 
6.4%
군 39
 
6.3%
면 27
 
4.3%
읍 23
 
3.7%
주 22
 
3.5%
창 14
 
2.2%
장 13
 
2.1%
Other values (84) 313
50.2%
Decimal Number
ValueCountFrequency (%)
1 72
23.0%
2 40
12.8%
4 34
10.9%
3 31
9.9%
5 29
9.3%
8 25
 
8.0%
0 23
 
7.3%
6 23
 
7.3%
9 20
 
6.4%
7 16
 
5.1%
Space Separator
ValueCountFrequency (%)
206
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 623
51.6%
Common 584
48.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 49
 
7.9%
동 42
 
6.7%
산 41
 
6.6%
리 40
 
6.4%
군 39
 
6.3%
면 27
 
4.3%
읍 23
 
3.7%
주 22
 
3.5%
창 14
 
2.2%
장 13
 
2.1%
Other values (84) 313
50.2%
Common
ValueCountFrequency (%)
206
35.3%
1 72
 
12.3%
- 65
 
11.1%
2 40
 
6.8%
4 34
 
5.8%
3 31
 
5.3%
5 29
 
5.0%
8 25
 
4.3%
0 23
 
3.9%
6 23
 
3.9%
Other values (2) 36
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 623
51.6%
ASCII 584
48.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
206
35.3%
1 72
 
12.3%
- 65
 
11.1%
2 40
 
6.8%
4 34
 
5.8%
3 31
 
5.3%
5 29
 
5.0%
8 25
 
4.3%
0 23
 
3.9%
6 23
 
3.9%
Other values (2) 36
 
6.2%
Hangul
ValueCountFrequency (%)
시 49
 
7.9%
동 42
 
6.7%
산 41
 
6.6%
리 40
 
6.4%
군 39
 
6.3%
면 27
 
4.3%
읍 23
 
3.7%
주 22
 
3.5%
창 14
 
2.2%
장 13
 
2.1%
Other values (84) 313
50.2%

경도
Real number (ℝ)

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.05384
Minimum126.49121
Maximum127.84901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2024-03-14T10:56:55.987245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.49121
5-th percentile126.66506
Q1126.85341
median126.97856
Q3127.20844
95-th percentile127.60971
Maximum127.84901
Range1.3577951
Interquartile range (IQR)0.35502632

Descriptive statistics

Standard deviation0.29699344
Coefficient of variation (CV)0.00233754
Kurtosis0.020190168
Mean127.05384
Median Absolute Deviation (MAD)0.17245556
Skewness0.52653869
Sum9910.1998
Variance0.088205104
MonotonicityNot monotonic
2024-03-14T10:56:56.116645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8864162 2
 
2.6%
127.12660509 1
 
1.3%
127.395934 1
 
1.3%
127.14543245 1
 
1.3%
127.16088683 1
 
1.3%
127.26809398 1
 
1.3%
127.22417343 1
 
1.3%
127.28328023 1
 
1.3%
127.58209173 1
 
1.3%
127.51723363 1
 
1.3%
Other values (67) 67
85.9%
ValueCountFrequency (%)
126.49121174 1
1.3%
126.54247897 1
1.3%
126.56051815 1
1.3%
126.59906561 1
1.3%
126.67670797 1
1.3%
126.69543974 1
1.3%
126.69878193 1
1.3%
126.70008281 1
1.3%
126.701885 1
1.3%
126.70504446 1
1.3%
ValueCountFrequency (%)
127.84900688 1
1.3%
127.7880424 1
1.3%
127.65412242 1
1.3%
127.65353916 1
1.3%
127.60197802 1
1.3%
127.58209173 1
1.3%
127.52898374 1
1.3%
127.51723363 1
1.3%
127.4296071 1
1.3%
127.395934 1
1.3%

위도
Real number (ℝ)

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.762321
Minimum35.340088
Maximum36.093868
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2024-03-14T10:56:56.239125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.340088
5-th percentile35.413295
Q135.57594
median35.808872
Q335.951731
95-th percentile36.007021
Maximum36.093868
Range0.75377983
Interquartile range (IQR)0.37579097

Descriptive statistics

Standard deviation0.21001031
Coefficient of variation (CV)0.0058723905
Kurtosis-1.1425788
Mean35.762321
Median Absolute Deviation (MAD)0.16254831
Skewness-0.40028168
Sum2789.461
Variance0.044104331
MonotonicityNot monotonic
2024-03-14T10:56:56.371719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.800136677 2
 
2.6%
35.804942658 1
 
1.3%
35.584631753 1
 
1.3%
35.37122678 1
 
1.3%
35.528935537 1
 
1.3%
35.678498824 1
 
1.3%
35.655666895 1
 
1.3%
35.614488557 1
 
1.3%
35.729456163 1
 
1.3%
35.649181647 1
 
1.3%
Other values (67) 67
85.9%
ValueCountFrequency (%)
35.340088482 1
1.3%
35.37122678 1
1.3%
35.404986257 1
1.3%
35.407154078 1
1.3%
35.414379011 1
1.3%
35.431425825 1
1.3%
35.432682532 1
1.3%
35.43619254 1
1.3%
35.439654552 1
1.3%
35.444265633 1
1.3%
ValueCountFrequency (%)
36.093868313 1
1.3%
36.080828352 1
1.3%
36.058624623 1
1.3%
36.009963641 1
1.3%
36.006501843 1
1.3%
36.004720965 1
1.3%
35.994071354 1
1.3%
35.984850101 1
1.3%
35.983171122 1
1.3%
35.982722426 1
1.3%

점포수
Real number (ℝ)

Distinct60
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.782051
Minimum6
Maximum382
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2024-03-14T10:56:56.490851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile12
Q137.25
median64.5
Q3133.25
95-th percentile292.2
Maximum382
Range376
Interquartile range (IQR)96

Descriptive statistics

Standard deviation90.298732
Coefficient of variation (CV)0.93301114
Kurtosis2.3207821
Mean96.782051
Median Absolute Deviation (MAD)32
Skewness1.6798069
Sum7549
Variance8153.861
MonotonicityNot monotonic
2024-03-14T10:56:56.612841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 3
 
3.8%
33 3
 
3.8%
25 2
 
2.6%
76 2
 
2.6%
106 2
 
2.6%
47 2
 
2.6%
32 2
 
2.6%
12 2
 
2.6%
34 2
 
2.6%
38 2
 
2.6%
Other values (50) 56
71.8%
ValueCountFrequency (%)
6 1
1.3%
7 1
1.3%
10 1
1.3%
12 2
2.6%
13 1
1.3%
20 1
1.3%
25 2
2.6%
29 2
2.6%
30 1
1.3%
32 2
2.6%
ValueCountFrequency (%)
382 1
1.3%
370 1
1.3%
360 1
1.3%
350 1
1.3%
282 2
2.6%
260 1
1.3%
229 1
1.3%
220 1
1.3%
199 1
1.3%
194 1
1.3%

취급품목
Text

Distinct49
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-03-14T10:56:56.817778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length6.025641
Min length1

Characters and Unicode

Total characters470
Distinct characters120
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

Unique48 ?
Unique (%)61.5%

Sample

1st row김부각,육류,과일,건강식품,배추 등
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
등 36
21.2%
30
17.6%
고추 7
 
4.1%
야채 4
 
2.4%
대추 4
 
2.4%
마늘 3
 
1.8%
생선 3
 
1.8%
사과 3
 
1.8%
배추 3
 
1.8%
과일 3
 
1.8%
Other values (62) 74
43.5%
2024-03-14T10:56:57.111319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
19.6%
, 57
 
12.1%
등 36
 
7.7%
- 30
 
6.4%
추 16
 
3.4%
고 10
 
2.1%
과 8
 
1.7%
채 7
 
1.5%
대 7
 
1.5%
소 6
 
1.3%
Other values (110) 201
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 291
61.9%
Space Separator 92
 
19.6%
Other Punctuation 57
 
12.1%
Dash Punctuation 30
 
6.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 36
 
12.4%
추 16
 
5.5%
고 10
 
3.4%
과 8
 
2.7%
채 7
 
2.4%
대 7
 
2.4%
소 6
 
2.1%
물 6
 
2.1%
류 5
 
1.7%
일 5
 
1.7%
Other values (107) 185
63.6%
Space Separator
ValueCountFrequency (%)
92
100.0%
Other Punctuation
ValueCountFrequency (%)
, 57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 291
61.9%
Common 179
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 36
 
12.4%
추 16
 
5.5%
고 10
 
3.4%
과 8
 
2.7%
채 7
 
2.4%
대 7
 
2.4%
소 6
 
2.1%
물 6
 
2.1%
류 5
 
1.7%
일 5
 
1.7%
Other values (107) 185
63.6%
Common
ValueCountFrequency (%)
92
51.4%
, 57
31.8%
- 30
 
16.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 291
61.9%
ASCII 179
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
51.4%
, 57
31.8%
- 30
 
16.8%
Hangul
ValueCountFrequency (%)
등 36
 
12.4%
추 16
 
5.5%
고 10
 
3.4%
과 8
 
2.7%
채 7
 
2.4%
대 7
 
2.4%
소 6
 
2.1%
물 6
 
2.1%
류 5
 
1.7%
일 5
 
1.7%
Other values (107) 185
63.6%

사용상품권
Categorical

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
온누리상품권, 전자상품권
40 
-
26 
온누리상품권
12 

Length

Max length13
Median length13
Mean length7.9230769
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
온누리상품권, 전자상품권 40
51.3%
- 26
33.3%
온누리상품권 12
 
15.4%

Length

2024-03-14T10:56:57.223155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:57.305495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온누리상품권 52
44.1%
전자상품권 40
33.9%
26
22.0%

홈페이지
Categorical

Distinct27
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size756.0 B
-
43 
http://jbsj.kr/?m_code=isja
5 
http://jbsj.kr/?m_code=nwyn
 
2
http://jbsj.kr/?m_code=jjpnm
 
2
http://jbsj.kr/?m_code=gssy
 
2
Other values (22)
24 

Length

Max length29
Median length1
Mean length12.782051
Min length1

Unique

Unique20 ?
Unique (%)25.6%

Sample

1st rowhttp://jbsj.kr/?m_code=jjsu
2nd rowhttp://jbsj.kr/?m_code=jjnm
3rd rowhttp://jbsj.kr/?m_code=jjpnm
4th rowhttp://jbsj.kr/?m_code=jjmrn
5th row-

Common Values

ValueCountFrequency (%)
- 43
55.1%
http://jbsj.kr/?m_code=isja 5
 
6.4%
http://jbsj.kr/?m_code=nwyn 2
 
2.6%
http://jbsj.kr/?m_code=jjpnm 2
 
2.6%
http://jbsj.kr/?m_code=gssy 2
 
2.6%
http://jbsj.kr/?m_code=gsmssj 2
 
2.6%
http://jbsj.kr/?m_code=dhrs 2
 
2.6%
blog.naver.com/buanmarket 1
 
1.3%
http://jbsj.kr/?m_code=jjmrn 1
 
1.3%
http://jbsj.kr/?m_code=jjbdnm 1
 
1.3%
Other values (17) 17
 
21.8%

Length

2024-03-14T10:56:57.453158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
43
55.1%
http://jbsj.kr/?m_code=isja 5
 
6.4%
http://jbsj.kr/?m_code=nwyn 2
 
2.6%
http://jbsj.kr/?m_code=jjpnm 2
 
2.6%
http://jbsj.kr/?m_code=gssy 2
 
2.6%
http://jbsj.kr/?m_code=gsmssj 2
 
2.6%
http://jbsj.kr/?m_code=dhrs 2
 
2.6%
http://jbsj.kr/?m_code=jjsu 1
 
1.3%
http://jbsj.kr/?m_code=ishd 1
 
1.3%
http://jbsj.kr/?m_code=jjkrr 1
 
1.3%
Other values (17) 17
 
21.8%

공중화장실
Boolean

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size210.0 B
True
68 
False
10 
ValueCountFrequency (%)
True 68
87.2%
False 10
 
12.8%
2024-03-14T10:56:57.567007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

주차장
Boolean

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size210.0 B
True
68 
False
10 
ValueCountFrequency (%)
True 68
87.2%
False 10
 
12.8%
2024-03-14T10:56:57.643665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

개설년도
Categorical

Distinct37
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Memory size756.0 B
-
13 
2005년
5 
1990년
 
4
2008년
 
4
2000년
 
4
Other values (32)
48 

Length

Max length5
Median length5
Mean length4.3205128
Min length1

Unique

Unique22 ?
Unique (%)28.2%

Sample

1st row-
2nd row1938년
3rd row1990년
4th row1970년
5th row2008년

Common Values

ValueCountFrequency (%)
- 13
16.7%
2005년 5
 
6.4%
1990년 4
 
5.1%
2008년 4
 
5.1%
2000년 4
 
5.1%
2006년 4
 
5.1%
2009년 4
 
5.1%
1992년 3
 
3.8%
1980년 3
 
3.8%
2007년 2
 
2.6%
Other values (27) 32
41.0%

Length

2024-03-14T10:56:57.752155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
13
16.7%
2005년 5
 
6.4%
1990년 4
 
5.1%
2008년 4
 
5.1%
2000년 4
 
5.1%
2006년 4
 
5.1%
2009년 4
 
5.1%
1992년 3
 
3.8%
1980년 3
 
3.8%
1994년 2
 
2.6%
Other values (27) 32
41.0%

전화번호
Text

Distinct57
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-03-14T10:56:57.957684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.0897436
Min length1

Characters and Unicode

Total characters709
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

Unique55 ?
Unique (%)70.5%

Sample

1st row070-8946-2243
2nd row063-284-1344
3rd row063-253-6535
4th row063-278-5802
5th row063-288-4487
ValueCountFrequency (%)
21
26.9%
063-547-3070 2
 
2.6%
063-288-5288 1
 
1.3%
063-324-9996 1
 
1.3%
063-833-5887 1
 
1.3%
063-351-5381 1
 
1.3%
070-8946-2243 1
 
1.3%
063-351-1141 1
 
1.3%
063-564-3097 1
 
1.3%
063-571-7040 1
 
1.3%
Other values (47) 47
60.3%
2024-03-14T10:56:58.252835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 135
19.0%
3 103
14.5%
6 93
13.1%
0 89
12.6%
5 56
7.9%
4 52
 
7.3%
8 50
 
7.1%
2 45
 
6.3%
7 33
 
4.7%
1 29
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 574
81.0%
Dash Punctuation 135
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 103
17.9%
6 93
16.2%
0 89
15.5%
5 56
9.8%
4 52
9.1%
8 50
8.7%
2 45
7.8%
7 33
 
5.7%
1 29
 
5.1%
9 24
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 135
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 709
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 135
19.0%
3 103
14.5%
6 93
13.1%
0 89
12.6%
5 56
7.9%
4 52
 
7.3%
8 50
 
7.1%
2 45
 
6.3%
7 33
 
4.7%
1 29
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 709
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 135
19.0%
3 103
14.5%
6 93
13.1%
0 89
12.6%
5 56
7.9%
4 52
 
7.3%
8 50
 
7.1%
2 45
 
6.3%
7 33
 
4.7%
1 29
 
4.1%

데이터기준
Date

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
Minimum2015-09-25 00:00:00
Maximum2015-09-25 00:00:00
2024-03-14T10:56:58.354377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:56:58.455166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
일자리경제정책관실
78 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일자리경제정책관실 78
100.0%

Length

2024-03-14T10:56:58.544604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:58.620766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일자리경제정책관실 78
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
공개
78 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 78
100.0%

Length

2024-03-14T10:56:58.704653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:58.794565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 78
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
2015.1
78 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 78
100.0%

Length

2024-03-14T10:56:58.888028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:58.981611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 78
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
1년
78 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 78
100.0%

Length

2024-03-14T10:56:59.064700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:59.133224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 78
100.0%

Sample

순번시군명시장명시장유형도로명주소개설주기지번주소경도위도점포수취급품목사용상품권홈페이지공중화장실주차장개설년도전화번호데이터기준자료출처공개여부작성일갱신주기
01전주시서부시장상설시장전주시 완산구 효동2길 18상설시장전주시 완산구 효자동1가 201-2127.12660535.80494325김부각,육류,과일,건강식품,배추 등온누리상품권, 전자상품권http://jbsj.kr/?m_code=jjsuNN-070-8946-22432015-09-25일자리경제정책관실공개2015.11년
12전주시남부 시장상설시장전주시 완산구 풍남문1길 17 (전동)상설시장전주시 완산구 전동 296-9127.14787235.8128350-온누리상품권http://jbsj.kr/?m_code=jjnmYY1938년063-284-13442015-09-25일자리경제정책관실공개2015.11년
23전주시중앙 시장상설시장전주시 완산구 태평3길 70 (태평동)상설시장전주시 완산구 태평동 36-1127.14245835.825226370-온누리상품권, 전자상품권http://jbsj.kr/?m_code=jjpnmYY1990년063-253-65352015-09-25일자리경제정책관실공개2015.11년
34전주시모래내 시장상설시장전주시 덕진구 모래내4길 8-8 (인후동2가)상설시장전주시 덕진구 인후동2가 203-10127.1438735.833564220-온누리상품권, 전자상품권http://jbsj.kr/?m_code=jjmrnYY1970년063-278-58022015-09-25일자리경제정책관실공개2015.11년
45전주시동부 시장상설시장전주시 완산구 충경로 109 (경원동3가)상설시장전주시 완산구 경원동3가 90-13127.15100835.82003145-온누리상품권, 전자상품권-YY2008년063-288-44872015-09-25일자리경제정책관실공개2015.11년
56전주시신중앙시장상설시장전주시 완산구 태평5길 35 (태평동)상설시장전주시 완산구 태평동 40-2127.14347535.824273229-온누리상품권, 전자상품권http://jbsj.kr/?m_code=jjbdnmYY2007년063-274-75352015-09-25일자리경제정책관실공개2015.11년
67군산시공설시장상설시장군산시 신금길 18 (신영동)상설시장군산시 신영동 18-1126.72032535.983171282-온누리상품권, 전자상품권http://jbsj.kr/?m_code=gssyYY1990년063-445-49292015-09-25일자리경제정책관실공개2015.11년
78군산시신영시장상설시장군산시 동신영길 36 (신영동)상설시장군산시 신영동 19-5126.72021735.98485160-온누리상품권, 전자상품권http://jbsj.kr/?m_code=gssyYY1993년070-7788-02972015-09-25일자리경제정책관실공개2015.11년
89군산시역전종합시장상설시장군산시 구암3.1로 7 (대명동)상설시장군산시 대명동 138126.72019935.980334102-온누리상품권, 전자상품권http://jbsj.kr/?m_code=gsyjYY1992년070-7749-28252015-09-25일자리경제정책관실공개2015.11년
910군산시명산시장상설시장군산시 금광길 20 (명산동)상설시장군산시 명산동 19-10126.70911635.98272272박대, 김치 등온누리상품권, 전자상품권http://jbsj.kr/?m_code=gsmssjYY1950년070-4038-53282015-09-25일자리경제정책관실공개2015.11년
순번시군명시장명시장유형도로명주소개설주기지번주소경도위도점포수취급품목사용상품권홈페이지공중화장실주차장개설년도전화번호데이터기준자료출처공개여부작성일갱신주기
6869전주시서부시장상점가상점가전주시 완산구 효동2길 23 (효자동1가)상점가전주시 완산구 효자동1가 205-12127.12677635.80441994정육, 순대국밥 등--YY2012년-2015-09-25일자리경제정책관실공개2015.11년
6970전주시전북대 대학로 상점가상점가전주시 덕진구 권삼득로 285 (금암동)상점가전주시 덕진구 금암동 664-55127.12982435.841936360--http://jbsj.kr/?m_code=dhrsNN--2015-09-25일자리경제정책관실공개2015.11년
7071익산시그린상점가상점가익산시 동서로19길 99 (신동)상점가익산시 신동 789-6126.95819835.9628181커피숍, 음식점 등--YY2005년063-858-82472015-09-25일자리경제정책관실공개2015.11년
7172익산시원광온누리상점가상점가익산시 동서로19길 88 (신동)상점가익산시 신동 786-21126.95837735.96178676---YY2010년063-833-58872015-09-25일자리경제정책관실공개2015.11년
7273정읍시중앙로상점가상점가정읍시 중앙로 125 (수성동)상점가정읍시 수성동 558-50126.85269235.56699185---YY2005년-2015-09-25일자리경제정책관실공개2015.11년
7374정읍시새암길상점가상점가정읍시 새암길 40-1 (수성동)상점가정읍시 수성동 571-6126.85303435.567018106귀금속, 신발 등--YY2000년063-532-30002015-09-25일자리경제정책관실공개2015.11년
7475정읍시연지상점가상점가정읍시 명덕로 47 (연지동)상점가정읍시 연지동 329-15126.84464335.575534382---NN--2015-09-25일자리경제정책관실공개2015.11년
7576정읍시정읍산외한우마을상점가상점가정읍시 산외로 435 (산외면)상점가정읍시 산외면 평사리 461-8127.03921135.62140278---YY2005년-2015-09-25일자리경제정책관실공개2015.11년
7677임실군오수상점가상점가임실군 삼일로 11 (오수면)상점가임실군 오수면 오수리 366-3127.32701935.539627137---YY--2015-09-25일자리경제정책관실공개2015.11년
7778완주군고산 구시장 상점가상점가완주군 고산로 113-1 (고산면)상점가완주군 고산면 읍내리 548-2127.20945335.974677106---NN--2015-09-25일자리경제정책관실공개2015.11년