Overview

Dataset statistics

Number of variables6
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory53.4 B

Variable types

DateTime1
Categorical1
Text3
Numeric1

Dataset

Description샘플 데이터
Author경기콘텐츠진흥원
URLhttps://www.bigdata-region.kr/#/dataset/ff886860-3b8b-42dc-ae95-decd79108c61

Alerts

기준년월 has constant value ""Constant
시도명 has constant value ""Constant
시군구명 has unique valuesUnique
사용금액 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:45:35.616464
Analysis finished2023-12-10 13:45:36.592846
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2015-01-01 00:00:00
Maximum2015-01-01 00:00:00
2023-12-10T22:45:36.659942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:45:36.773701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 30
100.0%

Length

2023-12-10T22:45:36.958502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:45:37.116374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:45:37.387003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.0333333
Min length3

Characters and Unicode

Total characters151
Distinct characters47
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

Unique30 ?
Unique (%)100.0%

Sample

1st row고양시 일산서구
2nd row오산시
3rd row광명시
4th row성남시 중원구
5th row성남시 분당구
ValueCountFrequency (%)
고양시 3
 
6.8%
성남시 3
 
6.8%
용인시 3
 
6.8%
수원시 2
 
4.5%
안양시 2
 
4.5%
중원구 1
 
2.3%
동두천시 1
 
2.3%
영통구 1
 
2.3%
부천시 1
 
2.3%
수정구 1
 
2.3%
Other values (26) 26
59.1%
2023-12-10T22:45:37.977261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
19.2%
구 15
 
9.9%
14
 
9.3%
양 8
 
5.3%
안 6
 
4.0%
남 5
 
3.3%
산 4
 
2.6%
수 4
 
2.6%
인 4
 
2.6%
원 4
 
2.6%
Other values (37) 58
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
90.7%
Space Separator 14
 
9.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
21.2%
구 15
 
10.9%
양 8
 
5.8%
안 6
 
4.4%
남 5
 
3.6%
산 4
 
2.9%
수 4
 
2.9%
인 4
 
2.9%
원 4
 
2.9%
고 3
 
2.2%
Other values (36) 55
40.1%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
90.7%
Common 14
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
21.2%
구 15
 
10.9%
양 8
 
5.8%
안 6
 
4.4%
남 5
 
3.6%
산 4
 
2.9%
수 4
 
2.9%
인 4
 
2.9%
원 4
 
2.9%
고 3
 
2.2%
Other values (36) 55
40.1%
Common
ValueCountFrequency (%)
14
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
90.7%
ASCII 14
 
9.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
21.2%
구 15
 
10.9%
양 8
 
5.8%
안 6
 
4.4%
남 5
 
3.6%
산 4
 
2.9%
수 4
 
2.9%
인 4
 
2.9%
원 4
 
2.9%
고 3
 
2.2%
Other values (36) 55
40.1%
ASCII
ValueCountFrequency (%)
14
100.0%

국적명
Text

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:45:38.297351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length3.1
Min length2

Characters and Unicode

Total characters93
Distinct characters50
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

Unique15 ?
Unique (%)50.0%

Sample

1st row홍콩
2nd row영국
3rd row몽고
4th row아제르바이잔
5th row캐나다
ValueCountFrequency (%)
미국 5
16.7%
중국 2
 
6.7%
러시아 2
 
6.7%
오스트레일리아 2
 
6.7%
홍콩 2
 
6.7%
태국 2
 
6.7%
인도네시아 1
 
3.3%
아르헨티나 1
 
3.3%
독일 1
 
3.3%
우즈베키스탄 1
 
3.3%
Other values (11) 11
36.7%
2023-12-10T22:45:38.756351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 10
 
10.8%
아 8
 
8.6%
스 6
 
6.5%
미 5
 
5.4%
일 4
 
4.3%
시 3
 
3.2%
리 3
 
3.2%
나 2
 
2.2%
르 2
 
2.2%
핀 2
 
2.2%
Other values (40) 48
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 10
 
10.8%
아 8
 
8.6%
스 6
 
6.5%
미 5
 
5.4%
일 4
 
4.3%
시 3
 
3.2%
리 3
 
3.2%
나 2
 
2.2%
르 2
 
2.2%
핀 2
 
2.2%
Other values (40) 48
51.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 10
 
10.8%
아 8
 
8.6%
스 6
 
6.5%
미 5
 
5.4%
일 4
 
4.3%
시 3
 
3.2%
리 3
 
3.2%
나 2
 
2.2%
르 2
 
2.2%
핀 2
 
2.2%
Other values (40) 48
51.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 10
 
10.8%
아 8
 
8.6%
스 6
 
6.5%
미 5
 
5.4%
일 4
 
4.3%
시 3
 
3.2%
리 3
 
3.2%
나 2
 
2.2%
르 2
 
2.2%
핀 2
 
2.2%
Other values (40) 48
51.6%

업종분류명
Text

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:45:39.071744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length10.3
Min length6

Characters and Unicode

Total characters309
Distinct characters79
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

Unique12 ?
Unique (%)40.0%

Sample

1st row유통.편의점
2nd row요식/유흥.커피전문점
3rd row유통.생활잡화
4th row의류/잡화.남.여기성복
5th row요식/유흥.한식
ValueCountFrequency (%)
요식/유흥.커피전문점 4
 
13.3%
요식/유흥.일반대중음식 2
 
6.7%
문화/레져.종합레저타운/놀이동산 2
 
6.7%
건강/미용.대중목욕탕 2
 
6.7%
유통.할인점/슈퍼마켓 2
 
6.7%
자동차.주유소 2
 
6.7%
의류/잡화.남.여기성복 2
 
6.7%
요식/유흥.한식 2
 
6.7%
요식/유흥.제과점 1
 
3.3%
유통.편의점 1
 
3.3%
Other values (10) 10
33.3%
2023-12-10T22:45:39.597070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 32
 
10.4%
/ 25
 
8.1%
유 20
 
6.5%
식 19
 
6.1%
흥 13
 
4.2%
요 12
 
3.9%
점 10
 
3.2%
화 8
 
2.6%
문 7
 
2.3%
통 6
 
1.9%
Other values (69) 157
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
81.6%
Other Punctuation 57
 
18.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 20
 
7.9%
식 19
 
7.5%
흥 13
 
5.2%
요 12
 
4.8%
점 10
 
4.0%
화 8
 
3.2%
문 7
 
2.8%
통 6
 
2.4%
산 5
 
2.0%
중 5
 
2.0%
Other values (67) 147
58.3%
Other Punctuation
ValueCountFrequency (%)
. 32
56.1%
/ 25
43.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
81.6%
Common 57
 
18.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 20
 
7.9%
식 19
 
7.5%
흥 13
 
5.2%
요 12
 
4.8%
점 10
 
4.0%
화 8
 
3.2%
문 7
 
2.8%
통 6
 
2.4%
산 5
 
2.0%
중 5
 
2.0%
Other values (67) 147
58.3%
Common
ValueCountFrequency (%)
. 32
56.1%
/ 25
43.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
81.6%
ASCII 57
 
18.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 32
56.1%
/ 25
43.9%
Hangul
ValueCountFrequency (%)
유 20
 
7.9%
식 19
 
7.5%
흥 13
 
5.2%
요 12
 
4.8%
점 10
 
4.0%
화 8
 
3.2%
문 7
 
2.8%
통 6
 
2.4%
산 5
 
2.0%
중 5
 
2.0%
Other values (67) 147
58.3%

사용금액
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1145759.8
Minimum7900
Maximum7459800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:45:39.881127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7900
5-th percentile10925
Q134537.5
median153950
Q31362600
95-th percentile5849982.7
Maximum7459800
Range7451900
Interquartile range (IQR)1328062.5

Descriptive statistics

Standard deviation1985050.8
Coefficient of variation (CV)1.7325191
Kurtosis3.8650096
Mean1145759.8
Median Absolute Deviation (MAD)142700
Skewness2.1264895
Sum34372795
Variance3.9404267 × 1012
MonotonicityNot monotonic
2023-12-10T22:45:40.201196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
40950 1
 
3.3%
238706 1
 
3.3%
31000 1
 
3.3%
2300000 1
 
3.3%
188900 1
 
3.3%
27700 1
 
3.3%
6270105 1
 
3.3%
1853400 1
 
3.3%
119000 1
 
3.3%
7900 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
7900 1
3.3%
8000 1
3.3%
14500 1
3.3%
15000 1
3.3%
22800 1
3.3%
27700 1
3.3%
31000 1
3.3%
32400 1
3.3%
40950 1
3.3%
44000 1
3.3%
ValueCountFrequency (%)
7459800 1
3.3%
6270105 1
3.3%
5336500 1
3.3%
3128000 1
3.3%
2740000 1
3.3%
2300000 1
3.3%
1853400 1
3.3%
1429800 1
3.3%
1161000 1
3.3%
532090 1
3.3%

Interactions

2023-12-10T22:45:36.133172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:45:40.358222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명국적명업종분류명사용금액
시군구명1.0001.0001.0001.000
국적명1.0001.0000.4200.000
업종분류명1.0000.4201.0000.306
사용금액1.0000.0000.3061.000

Missing values

2023-12-10T22:45:36.357639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:45:36.529946image/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

기준년월시도명시군구명국적명업종분류명사용금액
02015-01경기도고양시 일산서구홍콩유통.편의점40950
12015-01경기도오산시영국요식/유흥.커피전문점14500
22015-01경기도광명시몽고유통.생활잡화2740000
32015-01경기도성남시 중원구아제르바이잔의류/잡화.남.여기성복1429800
42015-01경기도성남시 분당구캐나다요식/유흥.한식5336500
52015-01경기도안산시 단원구루마니아요식/유흥.일반대중음식15000
62015-01경기도용인시 처인구러시아문화/레져.종합레저타운/놀이동산7459800
72015-01경기도과천시핀란드문화/레져.종합레저타운/놀이동산51600
82015-01경기도용인시 수지구필리핀요식/유흥.일식70000
92015-01경기도파주시오스트레일리아요식/유흥.중식90000
기준년월시도명시군구명국적명업종분류명사용금액
202015-01경기도고양시 일산동구우즈베키스탄요식/유흥.한식8000
212015-01경기도의정부시러시아건강/미용.대중목욕탕44000
222015-01경기도평택시독일요식/유흥.커피전문점7900
232015-01경기도하남시오스트레일리아건강/미용.화장품119000
242015-01경기도남양주시미국요식/유흥.일반대중음식1853400
252015-01경기도안양시 동안구중국문화/레져.수련원체험장6270105
262015-01경기도성남시 수정구미국요식/유흥.커피전문점27700
272015-01경기도부천시아르헨티나유통.할인점/슈퍼마켓188900
282015-01경기도수원시 영통구대만요식/유흥.유흥주점2300000
292015-01경기도시흥시미국건강/미용.대중목욕탕31000