Overview

Dataset statistics

Number of variables5
Number of observations98
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory44.3 B

Variable types

Categorical3
Numeric2

Dataset

Description경기도 시흥시 지역화폐 업종별 결제현황입니다.(시흥시 지역화폐 업종별 결제현황에는 기준년, 업종명, 결제건수, 결제금액이 있습니다)
Author경기도 시흥시
URLhttps://www.data.go.kr/data/15090670/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
결제건수 is highly overall correlated with 결제금액High correlation
결제금액 is highly overall correlated with 결제건수High correlation
결제금액 has unique valuesUnique

Reproduction

Analysis started2023-12-16 15:42:14.618040
Analysis finished2023-12-16 15:42:18.490770
Duration3.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년
Categorical

Distinct5
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size916.0 B
2021
20 
2022
20 
2023
20 
2019
19 
2020
19 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2021 20
20.4%
2022 20
20.4%
2023 20
20.4%
2019 19
19.4%
2020 19
19.4%

Length

2023-12-16T15:42:18.944554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:42:19.693145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 20
20.4%
2022 20
20.4%
2023 20
20.4%
2019 19
19.4%
2020 19
19.4%

업종명
Categorical

Distinct20
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Memory size916.0 B
가전/통신
 
5
기타
 
5
도서/문화/공연/오락
 
5
미용/뷰티/위생
 
5
부동산
 
5
Other values (15)
73 

Length

Max length11
Median length9
Mean length5.8571429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가전/통신
2nd row기타
3rd row도서/문화/공연/오락
4th row미용/뷰티/위생
5th row부동산

Common Values

ValueCountFrequency (%)
가전/통신 5
 
5.1%
기타 5
 
5.1%
도서/문화/공연/오락 5
 
5.1%
미용/뷰티/위생 5
 
5.1%
부동산 5
 
5.1%
산모/육아 5
 
5.1%
숙박업 5
 
5.1%
스포츠/헬스 5
 
5.1%
시장/거리 5
 
5.1%
여성청소년생필품 5
 
5.1%
Other values (10) 48
49.0%

Length

2023-12-16T15:42:20.443021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가전/통신 5
 
5.1%
기타 5
 
5.1%
학원/교육 5
 
5.1%
편의점/슈퍼/마트 5
 
5.1%
카페/베이커리 5
 
5.1%
주방/가정/인테리어 5
 
5.1%
제조업 5
 
5.1%
자동차/자전거 5
 
5.1%
의류/잡화/안경 5
 
5.1%
의료/보건 5
 
5.1%
Other values (10) 48
49.0%

결제건수
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean288493.62
Minimum2
Maximum2993848
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-16T15:42:21.045666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile14
Q15083.5
median34674.5
Q3255644.5
95-th percentile1374839.9
Maximum2993848
Range2993846
Interquartile range (IQR)250561

Descriptive statistics

Standard deviation563110.96
Coefficient of variation (CV)1.9519009
Kurtosis9.458005
Mean288493.62
Median Absolute Deviation (MAD)34292
Skewness2.9091273
Sum28272375
Variance3.1709395 × 1011
MonotonicityNot monotonic
2023-12-16T15:42:21.817549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5991 2
 
2.0%
14 2
 
2.0%
13 2
 
2.0%
41971 1
 
1.0%
1430471 1
 
1.0%
48754 1
 
1.0%
70317 1
 
1.0%
8015 1
 
1.0%
295099 1
 
1.0%
901695 1
 
1.0%
Other values (85) 85
86.7%
ValueCountFrequency (%)
2 1
1.0%
9 1
1.0%
13 2
2.0%
14 2
2.0%
17 1
1.0%
24 1
1.0%
27 1
1.0%
367 1
1.0%
398 1
1.0%
526 1
1.0%
ValueCountFrequency (%)
2993848 1
1.0%
2789398 1
1.0%
2244260 1
1.0%
1430471 1
1.0%
1390661 1
1.0%
1372048 1
1.0%
1296297 1
1.0%
1220026 1
1.0%
1063396 1
1.0%
939398 1
1.0%

결제금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.4150876 × 109
Minimum20
Maximum8.3834368 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-16T15:42:22.627411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile4066500
Q12.7212106 × 108
median1.4204627 × 109
Q39.1199143 × 109
95-th percentile5.3963077 × 1010
Maximum8.3834368 × 1010
Range8.3834368 × 1010
Interquartile range (IQR)8.8477933 × 109

Descriptive statistics

Standard deviation1.7276763 × 1010
Coefficient of variation (CV)1.8350082
Kurtosis7.6766131
Mean9.4150876 × 109
Median Absolute Deviation (MAD)1.4166097 × 109
Skewness2.7409729
Sum9.2267858 × 1011
Variance2.9848654 × 1020
MonotonicityNot monotonic
2023-12-16T15:42:23.781998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24539600 1
 
1.0%
4158000 1
 
1.0%
702138687 1
 
1.0%
625622180 1
 
1.0%
7942493132 1
 
1.0%
24544365570 1
 
1.0%
66913828582 1
 
1.0%
711919069 1
 
1.0%
266680088 1
 
1.0%
7370266922 1
 
1.0%
Other values (88) 88
89.8%
ValueCountFrequency (%)
20 1
1.0%
147000 1
1.0%
2047000 1
1.0%
2108000 1
1.0%
3548000 1
1.0%
4158000 1
1.0%
4266180 1
1.0%
4328540 1
1.0%
7779500 1
1.0%
8427300 1
1.0%
ValueCountFrequency (%)
83834368260 1
1.0%
80936066923 1
1.0%
66913828582 1
1.0%
65545207539 1
1.0%
56219155526 1
1.0%
53564944950 1
1.0%
30830185382 1
1.0%
27937510913 1
1.0%
27524566956 1
1.0%
27276160664 1
1.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2023-11-30
98 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-30
2nd row2023-11-30
3rd row2023-11-30
4th row2023-11-30
5th row2023-11-30

Common Values

ValueCountFrequency (%)
2023-11-30 98
100.0%

Length

2023-12-16T15:42:24.569233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:42:25.072764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-30 98
100.0%

Interactions

2023-12-16T15:42:16.382022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:42:15.278849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:42:17.017749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:42:15.840573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T15:42:25.399077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년업종명결제건수결제금액
기준년1.0000.0000.0000.000
업종명0.0001.0000.7440.721
결제건수0.0000.7441.0000.945
결제금액0.0000.7210.9451.000
2023-12-16T15:42:26.169502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명기준년
업종명1.0000.000
기준년0.0001.000
2023-12-16T15:42:26.779185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결제건수결제금액기준년업종명
결제건수1.0000.9510.0000.403
결제금액0.9511.0000.0000.381
기준년0.0000.0001.0000.000
업종명0.4030.3810.0001.000

Missing values

2023-12-16T15:42:17.743606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:42:18.216856image/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

기준년업종명결제건수결제금액데이터기준일자
02019가전/통신530245396002023-11-30
12019기타4212115090620282023-11-30
22019도서/문화/공연/오락74201934065122023-11-30
32019미용/뷰티/위생188399267947822023-11-30
42019부동산2202023-11-30
52019산모/육아739195347712023-11-30
62019숙박업398150110022023-11-30
72019스포츠/헬스47704792559372023-11-30
82019시장/거리141470002023-11-30
92019여성청소년생필품1281174018102023-11-30
기준년업종명결제건수결제금액데이터기준일자
882023음식점2244260535649449502023-11-30
892023의료/보건822174209255749672023-11-30
902023의류/잡화/안경24738161499778312023-11-30
912023자동차/자전거55804190494702023-11-30
922023제조업540845226206162023-11-30
932023주방/가정/인테리어3240731848797112023-11-30
942023주유소921080002023-11-30
952023카페/베이커리81568168746943862023-11-30
962023편의점/슈퍼/마트811771154878481732023-11-30
972023학원/교육409582809360669232023-11-30