Overview

Dataset statistics

Number of variables4
Number of observations55
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory36.4 B

Variable types

DateTime1
Categorical1
Numeric2

Dataset

Description국립아시아문화전당 예매 관련 가상계좌별 월 거래건수 및 거래금액에 대한 데이터로 월별, 가상계좌 은행, 거래건수, 거래금액 데이터 항목이 있으며 가상계좌 은행별 월 거래건수 및 금액을 확인할 수 있습니다.
Author문화체육관광부
URLhttps://www.data.go.kr/data/15071301/fileData.do

Alerts

거래건수 is highly overall correlated with 거래 금액High correlation
거래 금액 is highly overall correlated with 거래건수High correlation

Reproduction

Analysis started2023-12-12 17:49:22.642714
Analysis finished2023-12-12 17:49:23.343022
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

월별
Date

Distinct12
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
Minimum2020-01-01 00:00:00
Maximum2020-12-01 00:00:00
2023-12-13T02:49:23.384641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:49:23.486582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

가상계좌 은행
Categorical

Distinct8
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
농협
12 
우리
12 
국민
9 
기업
7 
우체국
6 
Other values (3)
9 

Length

Max length5
Median length2
Mean length2.2727273
Min length2

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row국민
2nd row농협
3rd row우리
4th row우체국
5th row국민

Common Values

ValueCountFrequency (%)
농협 12
21.8%
우리 12
21.8%
국민 9
16.4%
기업 7
12.7%
우체국 6
10.9%
신한 5
9.1%
KEB하나 3
 
5.5%
대구 1
 
1.8%

Length

2023-12-13T02:49:23.602898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:49:23.708743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농협 12
21.8%
우리 12
21.8%
국민 9
16.4%
기업 7
12.7%
우체국 6
10.9%
신한 5
9.1%
keb하나 3
 
5.5%
대구 1
 
1.8%

거래건수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.5636364
Minimum1
Maximum81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-13T02:49:23.817914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q38.5
95-th percentile41.8
Maximum81
Range80
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation16.022858
Coefficient of variation (CV)1.6753939
Kurtosis9.7137785
Mean9.5636364
Median Absolute Deviation (MAD)2
Skewness3.040774
Sum526
Variance256.73199
MonotonicityNot monotonic
2023-12-13T02:49:23.921538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3 10
18.2%
1 10
18.2%
2 10
18.2%
4 4
 
7.3%
6 4
 
7.3%
12 2
 
3.6%
40 1
 
1.8%
9 1
 
1.8%
17 1
 
1.8%
15 1
 
1.8%
Other values (11) 11
20.0%
ValueCountFrequency (%)
1 10
18.2%
2 10
18.2%
3 10
18.2%
4 4
 
7.3%
5 1
 
1.8%
6 4
 
7.3%
7 1
 
1.8%
8 1
 
1.8%
9 1
 
1.8%
12 2
 
3.6%
ValueCountFrequency (%)
81 1
1.8%
68 1
1.8%
46 1
1.8%
40 1
1.8%
37 1
1.8%
23 1
1.8%
19 1
1.8%
17 1
1.8%
15 1
1.8%
14 1
1.8%

거래 금액
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean336727.27
Minimum4000
Maximum2776000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-13T02:49:24.043753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4000
5-th percentile5500
Q120000
median100000
Q3327750
95-th percentile1362950
Maximum2776000
Range2772000
Interquartile range (IQR)307750

Descriptive statistics

Standard deviation578410.54
Coefficient of variation (CV)1.7177419
Kurtosis7.9848183
Mean336727.27
Median Absolute Deviation (MAD)92000
Skewness2.7237738
Sum18520000
Variance3.3455875 × 1011
MonotonicityNot monotonic
2023-12-13T02:49:24.160861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
5500 3
 
5.5%
40000 3
 
5.5%
8000 2
 
3.6%
20000 2
 
3.6%
12000 2
 
3.6%
18000 2
 
3.6%
4000 2
 
3.6%
102000 1
 
1.8%
2475000 1
 
1.8%
230000 1
 
1.8%
Other values (36) 36
65.5%
ValueCountFrequency (%)
4000 2
3.6%
5500 3
5.5%
6000 1
 
1.8%
8000 2
3.6%
10000 1
 
1.8%
12000 2
3.6%
18000 2
3.6%
20000 2
3.6%
22000 1
 
1.8%
24000 1
 
1.8%
ValueCountFrequency (%)
2776000 1
1.8%
2475000 1
1.8%
1441000 1
1.8%
1329500 1
1.8%
1232500 1
1.8%
1106500 1
1.8%
1025000 1
1.8%
854000 1
1.8%
695000 1
1.8%
576500 1
1.8%

Interactions

2023-12-13T02:49:23.002058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:49:22.788537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:49:23.111999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:49:22.896729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:49:24.235193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월별가상계좌 은행거래건수거래 금액
월별1.0000.0000.0000.000
가상계좌 은행0.0001.0000.0000.000
거래건수0.0000.0001.0000.912
거래 금액0.0000.0000.9121.000
2023-12-13T02:49:24.316891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거래건수거래 금액가상계좌 은행
거래건수1.0000.7970.000
거래 금액0.7971.0000.000
가상계좌 은행0.0000.0001.000

Missing values

2023-12-13T02:49:23.220637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:49:23.310231image/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

월별가상계좌 은행거래건수거래 금액
02020-01국민4102000
12020-01농협28000
22020-01우리35500
32020-01우체국15500
42020-02국민31025000
52020-02기업225000
62020-02농협12576500
72020-02우리41232500
82020-02우체국2232000
92020-03농협130000
월별가상계좌 은행거래건수거래 금액
452020-10우리17503000
462020-10우체국16000
472020-11국민318000
482020-11농협6160000
492020-11우리4100000
502020-12국민312000
512020-12기업25500
522020-12농협940000
532020-12신한38000
542020-12우리324000