Overview

Dataset statistics

Number of variables3
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory730.0 B
Average record size in memory31.7 B

Variable types

Numeric2
Text1

Dataset

Description강원도 홍천군_강원도 홍천군_강원도_홍천군_지방세ARS간편납부시스템_은행코드
Author강원도 홍천군
URLhttps://www.data.go.kr/data/15072388/fileData.do

Alerts

연번 has unique valuesUnique
은행명 has unique valuesUnique
코드명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:05:47.226983
Analysis finished2023-12-12 00:05:47.855613
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T09:05:47.916671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2023-12-12T09:05:48.092342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

은행명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T09:05:48.366338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.3913043
Min length2

Characters and Unicode

Total characters101
Distinct characters53
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row국민은행
2nd row기업은행
3rd row농협중앙회
4th row단위농협
5th row우리은행
ValueCountFrequency (%)
국민은행 1
 
4.3%
상호저축은행 1
 
4.3%
하나(서울)은행 1
 
4.3%
sc제일은행 1
 
4.3%
전북은행 1
 
4.3%
제주은행 1
 
4.3%
외환은행 1
 
4.3%
신협 1
 
4.3%
씨티(한미)은행 1
 
4.3%
새마을금고 1
 
4.3%
Other values (13) 13
56.5%
2023-12-12T09:05:48.792839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
은 17
 
16.8%
행 17
 
16.8%
협 4
 
4.0%
국 3
 
3.0%
한 3
 
3.0%
산 2
 
2.0%
제 2
 
2.0%
신 2
 
2.0%
) 2
 
2.0%
우 2
 
2.0%
Other values (43) 47
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 95
94.1%
Close Punctuation 2
 
2.0%
Open Punctuation 2
 
2.0%
Uppercase Letter 2
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
은 17
17.9%
행 17
17.9%
협 4
 
4.2%
국 3
 
3.2%
한 3
 
3.2%
산 2
 
2.1%
제 2
 
2.1%
신 2
 
2.1%
우 2
 
2.1%
주 2
 
2.1%
Other values (39) 41
43.2%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
C 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 95
94.1%
Common 4
 
4.0%
Latin 2
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
은 17
17.9%
행 17
17.9%
협 4
 
4.2%
국 3
 
3.2%
한 3
 
3.2%
산 2
 
2.1%
제 2
 
2.1%
신 2
 
2.1%
우 2
 
2.1%
주 2
 
2.1%
Other values (39) 41
43.2%
Common
ValueCountFrequency (%)
) 2
50.0%
( 2
50.0%
Latin
ValueCountFrequency (%)
S 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 95
94.1%
ASCII 6
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
은 17
17.9%
행 17
17.9%
협 4
 
4.2%
국 3
 
3.2%
한 3
 
3.2%
산 2
 
2.1%
제 2
 
2.1%
신 2
 
2.1%
우 2
 
2.1%
주 2
 
2.1%
Other values (39) 41
43.2%
ASCII
ValueCountFrequency (%)
) 2
33.3%
( 2
33.3%
S 1
16.7%
C 1
16.7%

코드명
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.695652
Minimum1
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T09:05:48.977936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q19
median31
Q342
95-th percentile80
Maximum88
Range87
Interquartile range (IQR)33

Descriptive statistics

Standard deviation25.033495
Coefficient of variation (CV)0.8155388
Kurtosis0.14736167
Mean30.695652
Median Absolute Deviation (MAD)19
Skewness0.82802128
Sum706
Variance626.67589
MonotonicityNot monotonic
2023-12-12T09:05:49.124571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
4 1
 
4.3%
3 1
 
4.3%
1 1
 
4.3%
81 1
 
4.3%
23 1
 
4.3%
37 1
 
4.3%
35 1
 
4.3%
5 1
 
4.3%
48 1
 
4.3%
27 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
7 1
4.3%
11 1
4.3%
12 1
4.3%
20 1
4.3%
23 1
4.3%
ValueCountFrequency (%)
88 1
4.3%
81 1
4.3%
71 1
4.3%
50 1
4.3%
48 1
4.3%
45 1
4.3%
39 1
4.3%
37 1
4.3%
35 1
4.3%
34 1
4.3%

Interactions

2023-12-12T09:05:47.519523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:05:47.356168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:05:47.608724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:05:47.441489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:05:49.206581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번은행명코드명
연번1.0001.0000.509
은행명1.0001.0001.000
코드명0.5091.0001.000
2023-12-12T09:05:49.310685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번코드명
연번1.0000.155
코드명0.1551.000

Missing values

2023-12-12T09:05:47.722855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:05:47.818158image/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

연번은행명코드명
01국민은행4
12기업은행3
23농협중앙회11
34단위농협12
45우리은행20
56우체국71
67신한은행88
78경남은행39
89광주은행34
910대구은행31
연번은행명코드명
1314수협7
1415새마을금고45
1516씨티(한미)은행27
1617신협48
1718외환은행5
1819제주은행35
1920전북은행37
2021SC제일은행23
2122하나(서울)은행81
2223한국은행1