Overview

Dataset statistics

Number of variables6
Number of observations1876
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory93.6 KiB
Average record size in memory51.1 B

Variable types

Text1
Numeric2
Categorical3

Dataset

Description전국 시장 지류상품권 가맹점에 대한 데이터로 가맹점수(환전대행+가맹점)와 환전 대행 여부, 지류 여부 등을 항목을 제공합니다.
Author소상공인시장진흥공단
URLhttps://www.data.go.kr/data/15091206/fileData.do

Alerts

지류 여부 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates
환전대행 is highly overall correlated with 가맹점수 (환전대행+가맹점) and 2 other fieldsHigh correlation
환전대행 여부 is highly overall correlated with 환전대행High correlation
가맹점수 (환전대행+가맹점) is highly overall correlated with 가맹점 and 1 other fieldsHigh correlation
가맹점 is highly overall correlated with 가맹점수 (환전대행+가맹점) and 1 other fieldsHigh correlation
가맹점 has 20 (1.1%) zerosZeros

Reproduction

Analysis started2023-12-12 03:42:31.733711
Analysis finished2023-12-12 03:42:33.076912
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시장명
Text

Distinct1848
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size14.8 KiB
2023-12-12T12:42:33.244285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length6.7180171
Min length3

Characters and Unicode

Total characters12603
Distinct characters435
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1824 ?
Unique (%)97.2%

Sample

1st row남대문시장
2nd row삼익패션타운
3rd row서울중부시장
4th row신중부시장
5th row평화시장
ValueCountFrequency (%)
상점가 6
 
0.3%
제일시장 3
 
0.2%
동문시장 3
 
0.2%
덕산시장 3
 
0.2%
고투몰(강남터미널지하도상점가 3
 
0.2%
한솔동 3
 
0.2%
중앙시장 3
 
0.2%
역전시장 3
 
0.2%
대현프리몰 2
 
0.1%
골목형상점가 2
 
0.1%
Other values (1913) 1936
98.4%
2023-12-12T12:42:34.076577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 1611
 
12.8%
시 1549
 
12.3%
상 459
 
3.6%
가 440
 
3.5%
동 277
 
2.2%
산 219
 
1.7%
전 208
 
1.7%
점 182
 
1.4%
중 171
 
1.4%
구 164
 
1.3%
Other values (425) 7323
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12122
96.2%
Close Punctuation 131
 
1.0%
Open Punctuation 131
 
1.0%
Decimal Number 108
 
0.9%
Space Separator 93
 
0.7%
Other Punctuation 7
 
0.1%
Uppercase Letter 5
 
< 0.1%
Math Symbol 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 1611
 
13.3%
시 1549
 
12.8%
상 459
 
3.8%
가 440
 
3.6%
동 277
 
2.3%
산 219
 
1.8%
전 208
 
1.7%
점 182
 
1.5%
중 171
 
1.4%
구 164
 
1.4%
Other values (402) 6842
56.4%
Decimal Number
ValueCountFrequency (%)
5 41
38.0%
1 25
23.1%
2 17
15.7%
3 11
 
10.2%
4 5
 
4.6%
6 4
 
3.7%
7 3
 
2.8%
0 1
 
0.9%
9 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
20.0%
C 1
20.0%
B 1
20.0%
A 1
20.0%
D 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
! 1
 
14.3%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 131
100.0%
Open Punctuation
ValueCountFrequency (%)
( 131
100.0%
Space Separator
ValueCountFrequency (%)
93
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12122
96.2%
Common 474
 
3.8%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 1611
 
13.3%
시 1549
 
12.8%
상 459
 
3.8%
가 440
 
3.6%
동 277
 
2.3%
산 219
 
1.8%
전 208
 
1.7%
점 182
 
1.5%
중 171
 
1.4%
구 164
 
1.4%
Other values (402) 6842
56.4%
Common
ValueCountFrequency (%)
) 131
27.6%
( 131
27.6%
93
19.6%
5 41
 
8.6%
1 25
 
5.3%
2 17
 
3.6%
3 11
 
2.3%
, 6
 
1.3%
4 5
 
1.1%
6 4
 
0.8%
Other values (6) 10
 
2.1%
Latin
ValueCountFrequency (%)
S 1
14.3%
C 1
14.3%
B 1
14.3%
A 1
14.3%
D 1
14.3%
k 1
14.3%
s 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12122
96.2%
ASCII 481
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 1611
 
13.3%
시 1549
 
12.8%
상 459
 
3.8%
가 440
 
3.6%
동 277
 
2.3%
산 219
 
1.8%
전 208
 
1.7%
점 182
 
1.5%
중 171
 
1.4%
구 164
 
1.4%
Other values (402) 6842
56.4%
ASCII
ValueCountFrequency (%)
) 131
27.2%
( 131
27.2%
93
19.3%
5 41
 
8.5%
1 25
 
5.2%
2 17
 
3.5%
3 11
 
2.3%
, 6
 
1.2%
4 5
 
1.0%
6 4
 
0.8%
Other values (13) 17
 
3.5%

가맹점수 (환전대행+가맹점)
Real number (ℝ)

HIGH CORRELATION 

Distinct326
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.003198
Minimum1
Maximum1271
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.6 KiB
2023-12-12T12:42:34.298269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q113
median50
Q3110
95-th percentile270.25
Maximum1271
Range1270
Interquartile range (IQR)97

Descriptive statistics

Standard deviation111.04146
Coefficient of variation (CV)1.3377973
Kurtosis18.911431
Mean83.003198
Median Absolute Deviation (MAD)42
Skewness3.4700661
Sum155714
Variance12330.205
MonotonicityNot monotonic
2023-12-12T12:42:34.514878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 133
 
7.1%
2 73
 
3.9%
3 52
 
2.8%
4 42
 
2.2%
8 28
 
1.5%
6 27
 
1.4%
5 24
 
1.3%
20 22
 
1.2%
7 21
 
1.1%
14 20
 
1.1%
Other values (316) 1434
76.4%
ValueCountFrequency (%)
1 133
7.1%
2 73
3.9%
3 52
 
2.8%
4 42
 
2.2%
5 24
 
1.3%
6 27
 
1.4%
7 21
 
1.1%
8 28
 
1.5%
9 13
 
0.7%
10 14
 
0.7%
ValueCountFrequency (%)
1271 1
0.1%
922 1
0.1%
911 1
0.1%
900 1
0.1%
808 1
0.1%
778 1
0.1%
721 1
0.1%
701 1
0.1%
695 1
0.1%
682 1
0.1%

환전대행
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.8 KiB
1
1005 
<NA>
843 
2
 
27
38
 
1

Length

Max length4
Median length1
Mean length2.3486141
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row38
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1005
53.6%
<NA> 843
44.9%
2 27
 
1.4%
38 1
 
0.1%

Length

2023-12-12T12:42:34.705474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:42:34.847310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1005
53.6%
na 843
44.9%
2 27
 
1.4%
38 1
 
0.1%

가맹점
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct328
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.418443
Minimum0
Maximum1233
Zeros20
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size16.6 KiB
2023-12-12T12:42:35.000032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q113
median49
Q3109
95-th percentile269.25
Maximum1233
Range1233
Interquartile range (IQR)96

Descriptive statistics

Standard deviation110.61932
Coefficient of variation (CV)1.3421671
Kurtosis18.333693
Mean82.418443
Median Absolute Deviation (MAD)42
Skewness3.4410431
Sum154617
Variance12236.634
MonotonicityNot monotonic
2023-12-12T12:42:35.151875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 131
 
7.0%
2 66
 
3.5%
3 47
 
2.5%
4 38
 
2.0%
5 31
 
1.7%
13 25
 
1.3%
8 25
 
1.3%
6 25
 
1.3%
20 23
 
1.2%
7 21
 
1.1%
Other values (318) 1444
77.0%
ValueCountFrequency (%)
0 20
 
1.1%
1 131
7.0%
2 66
3.5%
3 47
 
2.5%
4 38
 
2.0%
5 31
 
1.7%
6 25
 
1.3%
7 21
 
1.1%
8 25
 
1.3%
9 12
 
0.6%
ValueCountFrequency (%)
1233 1
0.1%
921 1
0.1%
909 1
0.1%
899 1
0.1%
807 1
0.1%
777 1
0.1%
720 1
0.1%
700 1
0.1%
694 1
0.1%
681 1
0.1%

지류 여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.8 KiB
O
1876 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
O 1876
100.0%

Length

2023-12-12T12:42:35.299043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:42:35.396119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 1876
100.0%

환전대행 여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.8 KiB
O
1033 
X
843 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
O 1033
55.1%
X 843
44.9%

Length

2023-12-12T12:42:35.519719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:42:35.629534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 1033
55.1%
x 843
44.9%

Interactions

2023-12-12T12:42:32.501773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:42:32.191850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:42:32.651731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:42:32.327723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:42:35.701612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점수 (환전대행+가맹점)환전대행가맹점환전대행 여부
가맹점수\n(환전대행+가맹점)1.0000.9460.9990.340
환전대행0.9461.0000.947NaN
가맹점0.9990.9471.0000.343
환전대행 \n여부0.340NaN0.3431.000
2023-12-12T12:42:35.803614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환전대행환전대행 여부
환전대행1.0001.000
환전대행 \n여부1.0001.000
2023-12-12T12:42:35.900282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점수 (환전대행+가맹점)가맹점환전대행환전대행 여부
가맹점수\n(환전대행+가맹점)1.0001.0000.7240.339
가맹점1.0001.0000.7270.342
환전대행0.7240.7271.0001.000
환전대행 \n여부0.3390.3421.0001.000

Missing values

2023-12-12T12:42:32.858030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:42:33.012137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

시장명가맹점수 (환전대행+가맹점)환전대행가맹점지류 여부환전대행 여부
0남대문시장1271381233OO
1삼익패션타운4881487OO
2서울중부시장2251224OO
3신중부시장2031202OO
4평화시장6601659OO
5서울중앙시장1661165OO
6남평화시장92<NA>92OX
7청평화시장211OO
8제일평화시장170<NA>170OX
9벨포스트(구 에리어식스)93<NA>93OX
시장명가맹점수 (환전대행+가맹점)환전대행가맹점지류 여부환전대행 여부
1866영일대북부시장(구 북부시장)64<NA>64OX
1867환호시장1<NA>1OX
1868장량성도시장72<NA>72OX
1869양학시장26<NA>26OX
1870포항서부시장2<NA>2OX
1871청하시장918OO
1872한라종합시장1<NA>1OX
1873죽도중앙시장1<NA>1OX
1874죽변어판장부근1<NA>1OX
1875일신시장2<NA>2OX

Duplicate rows

Most frequently occurring

시장명가맹점수 (환전대행+가맹점)환전대행가맹점지류 여부환전대행 여부# duplicates
0중앙시장2<NA>2OX2