Overview

Dataset statistics

Number of variables6
Number of observations290
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.3 KiB
Average record size in memory50.5 B

Variable types

DateTime1
Categorical1
Numeric2
Text2

Dataset

Description(주)한국가스기술공사의 상품권 구입현황입니다. 구매일자, 종류,구입금액, 배부처, 배부금액의 정보를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15103500/fileData.do

Alerts

종류 has constant value ""Constant
구입금액 is highly overall correlated with 배부금액(원)High correlation
배부금액(원) is highly overall correlated with 구입금액High correlation
구입금액 has 10 (3.4%) zerosZeros

Reproduction

Analysis started2023-12-12 14:55:41.724199
Analysis finished2023-12-12 14:55:42.640912
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구입일자
Date

Distinct97
Distinct (%)33.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2022-01-18 00:00:00
Maximum2022-12-30 00:00:00
2023-12-12T23:55:42.720730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:55:42.881140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

종류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
온누리상품권
290 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
온누리상품권 290
100.0%

Length

2023-12-12T23:55:43.009525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:55:43.115399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온누리상품권 290
100.0%

구입금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct58
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2069689.7
Minimum0
Maximum1.2275 × 108
Zeros10
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-12T23:55:43.223153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30000
Q150000
median60000
Q3257500
95-th percentile9500000
Maximum1.2275 × 108
Range1.2275 × 108
Interquartile range (IQR)207500

Descriptive statistics

Standard deviation9478472.5
Coefficient of variation (CV)4.5796588
Kurtosis94.423262
Mean2069689.7
Median Absolute Deviation (MAD)40000
Skewness8.5050554
Sum6.0021 × 108
Variance8.984144 × 1013
MonotonicityNot monotonic
2023-12-12T23:55:43.372406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 106
36.6%
200000 17
 
5.9%
30000 17
 
5.9%
400000 12
 
4.1%
100000 11
 
3.8%
150000 10
 
3.4%
0 10
 
3.4%
1000000 9
 
3.1%
60000 8
 
2.8%
250000 8
 
2.8%
Other values (48) 82
28.3%
ValueCountFrequency (%)
0 10
 
3.4%
10000 1
 
0.3%
20000 3
 
1.0%
30000 17
 
5.9%
40000 3
 
1.0%
50000 106
36.6%
60000 8
 
2.8%
70000 1
 
0.3%
80000 2
 
0.7%
90000 7
 
2.4%
ValueCountFrequency (%)
122750000 1
0.3%
40250000 1
0.3%
40000000 1
0.3%
38500000 1
0.3%
36000000 1
0.3%
33250000 1
0.3%
31500000 1
0.3%
30000000 1
0.3%
24000000 2
0.7%
23500000 1
0.3%

구입목적
Text

Distinct262
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T23:55:43.663331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length33
Mean length20.589655
Min length6

Characters and Unicode

Total characters5971
Distinct characters226
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique245 ?
Unique (%)84.5%

Sample

1st row21년 4분기 안전활동 우수자 장려금 지급
2nd row설명절 나눔행사 후원
3rd row설명절 음식나눔행사 후원금
4th row설명절 음식나눔행사 후원금
5th row설 명절 맞이 사회공헌 활동_후원
ValueCountFrequency (%)
포상 109
 
7.8%
2022년 74
 
5.3%
이달의 54
 
3.9%
우수 50
 
3.6%
지급 43
 
3.1%
선정 42
 
3.0%
기술인 41
 
2.9%
22년 37
 
2.6%
안전퀴즈 32
 
2.3%
우수자 32
 
2.3%
Other values (204) 888
63.3%
2023-12-12T23:55:44.183420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1124
 
18.8%
2 352
 
5.9%
상 265
 
4.4%
기 240
 
4.0%
포 155
 
2.6%
수 137
 
2.3%
우 135
 
2.3%
사 129
 
2.2%
년 125
 
2.1%
0 97
 
1.6%
Other values (216) 3212
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3930
65.8%
Space Separator 1124
 
18.8%
Decimal Number 577
 
9.7%
Lowercase Letter 114
 
1.9%
Other Punctuation 67
 
1.1%
Uppercase Letter 58
 
1.0%
Close Punctuation 38
 
0.6%
Open Punctuation 37
 
0.6%
Dash Punctuation 10
 
0.2%
Connector Punctuation 9
 
0.2%
Other values (2) 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 265
 
6.7%
기 240
 
6.1%
포 155
 
3.9%
수 137
 
3.5%
우 135
 
3.4%
사 129
 
3.3%
년 125
 
3.2%
자 93
 
2.4%
인 91
 
2.3%
술 88
 
2.2%
Other values (182) 2472
62.9%
Decimal Number
ValueCountFrequency (%)
2 352
61.0%
0 97
 
16.8%
1 57
 
9.9%
3 21
 
3.6%
4 13
 
2.3%
8 12
 
2.1%
7 12
 
2.1%
9 12
 
2.1%
5 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
e 37
32.5%
t 26
22.8%
c 13
 
11.4%
s 13
 
11.4%
r 13
 
11.4%
f 11
 
9.6%
o 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P 14
24.1%
B 13
22.4%
K 10
17.2%
T 10
17.2%
G 10
17.2%
C 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
' 35
52.2%
& 14
 
20.9%
, 13
 
19.4%
/ 5
 
7.5%
Close Punctuation
ValueCountFrequency (%)
) 37
97.4%
」 1
 
2.6%
Space Separator
ValueCountFrequency (%)
1124
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 6
100.0%
Other Symbol
ValueCountFrequency (%)
㎏ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3930
65.8%
Common 1869
31.3%
Latin 172
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 265
 
6.7%
기 240
 
6.1%
포 155
 
3.9%
수 137
 
3.5%
우 135
 
3.4%
사 129
 
3.3%
년 125
 
3.2%
자 93
 
2.4%
인 91
 
2.3%
술 88
 
2.2%
Other values (182) 2472
62.9%
Common
ValueCountFrequency (%)
1124
60.1%
2 352
 
18.8%
0 97
 
5.2%
1 57
 
3.0%
) 37
 
2.0%
( 37
 
2.0%
' 35
 
1.9%
3 21
 
1.1%
& 14
 
0.7%
4 13
 
0.7%
Other values (11) 82
 
4.4%
Latin
ValueCountFrequency (%)
e 37
21.5%
t 26
15.1%
P 14
 
8.1%
c 13
 
7.6%
B 13
 
7.6%
s 13
 
7.6%
r 13
 
7.6%
f 11
 
6.4%
K 10
 
5.8%
T 10
 
5.8%
Other values (3) 12
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3930
65.8%
ASCII 2039
34.1%
None 1
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1124
55.1%
2 352
 
17.3%
0 97
 
4.8%
1 57
 
2.8%
) 37
 
1.8%
e 37
 
1.8%
( 37
 
1.8%
' 35
 
1.7%
t 26
 
1.3%
3 21
 
1.0%
Other values (22) 216
 
10.6%
Hangul
ValueCountFrequency (%)
상 265
 
6.7%
기 240
 
6.1%
포 155
 
3.9%
수 137
 
3.5%
우 135
 
3.4%
사 129
 
3.3%
년 125
 
3.2%
자 93
 
2.4%
인 91
 
2.3%
술 88
 
2.2%
Other values (182) 2472
62.9%
None
ValueCountFrequency (%)
」 1
100.0%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%

배부처
Text

Distinct63
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T23:55:44.407275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length5
Mean length5.5793103
Min length2

Characters and Unicode

Total characters1618
Distinct characters116
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)15.9%

Sample

1st row직원 3명
2nd row서구장애인 종합복지관
3rd row통영시장애인종합복지권
4th row통영시종합사회복지관
5th row성육보육원
ValueCountFrequency (%)
직원 255
47.5%
1명 140
26.1%
2명 24
 
4.5%
3명 21
 
3.9%
4명 15
 
2.8%
6명 5
 
0.9%
10명 3
 
0.6%
7명 3
 
0.6%
5명 3
 
0.6%
9명 3
 
0.6%
Other values (57) 65
 
12.1%
2023-12-12T23:55:45.064987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 263
16.3%
직 258
15.9%
248
15.3%
명 236
14.6%
1 155
9.6%
2 32
 
2.0%
지 27
 
1.7%
3 25
 
1.5%
복 20
 
1.2%
4 20
 
1.2%
Other values (106) 334
20.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1088
67.2%
Decimal Number 260
 
16.1%
Space Separator 248
 
15.3%
Open Punctuation 8
 
0.5%
Close Punctuation 8
 
0.5%
Other Punctuation 3
 
0.2%
Dash Punctuation 2
 
0.1%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 263
24.2%
직 258
23.7%
명 236
21.7%
지 27
 
2.5%
복 20
 
1.8%
인 14
 
1.3%
관 14
 
1.3%
합 13
 
1.2%
사 13
 
1.2%
회 11
 
1.0%
Other values (90) 219
20.1%
Decimal Number
ValueCountFrequency (%)
1 155
59.6%
2 32
 
12.3%
3 25
 
9.6%
4 20
 
7.7%
6 9
 
3.5%
9 5
 
1.9%
0 5
 
1.9%
5 4
 
1.5%
7 3
 
1.2%
8 2
 
0.8%
Space Separator
ValueCountFrequency (%)
248
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1088
67.2%
Common 530
32.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 263
24.2%
직 258
23.7%
명 236
21.7%
지 27
 
2.5%
복 20
 
1.8%
인 14
 
1.3%
관 14
 
1.3%
합 13
 
1.2%
사 13
 
1.2%
회 11
 
1.0%
Other values (90) 219
20.1%
Common
ValueCountFrequency (%)
248
46.8%
1 155
29.2%
2 32
 
6.0%
3 25
 
4.7%
4 20
 
3.8%
6 9
 
1.7%
( 8
 
1.5%
) 8
 
1.5%
9 5
 
0.9%
0 5
 
0.9%
Other values (6) 15
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1088
67.2%
ASCII 530
32.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 263
24.2%
직 258
23.7%
명 236
21.7%
지 27
 
2.5%
복 20
 
1.8%
인 14
 
1.3%
관 14
 
1.3%
합 13
 
1.2%
사 13
 
1.2%
회 11
 
1.0%
Other values (90) 219
20.1%
ASCII
ValueCountFrequency (%)
248
46.8%
1 155
29.2%
2 32
 
6.0%
3 25
 
4.7%
4 20
 
3.8%
6 9
 
1.7%
( 8
 
1.5%
) 8
 
1.5%
9 5
 
0.9%
0 5
 
0.9%
Other values (6) 15
 
2.8%

배부금액(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2069689.7
Minimum10000
Maximum1.2275 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-12T23:55:45.207619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile30000
Q150000
median90000
Q3300000
95-th percentile9500000
Maximum1.2275 × 108
Range1.2274 × 108
Interquartile range (IQR)250000

Descriptive statistics

Standard deviation9473660.7
Coefficient of variation (CV)4.5773339
Kurtosis94.597677
Mean2069689.7
Median Absolute Deviation (MAD)50000
Skewness8.5137332
Sum6.0021 × 108
Variance8.9750247 × 1013
MonotonicityNot monotonic
2023-12-12T23:55:45.395024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 106
36.6%
200000 21
 
7.2%
30000 17
 
5.9%
400000 12
 
4.1%
100000 11
 
3.8%
150000 10
 
3.4%
1000000 10
 
3.4%
500000 9
 
3.1%
250000 9
 
3.1%
60000 8
 
2.8%
Other values (45) 77
26.6%
ValueCountFrequency (%)
10000 1
 
0.3%
20000 3
 
1.0%
30000 17
 
5.9%
40000 3
 
1.0%
50000 106
36.6%
60000 8
 
2.8%
70000 1
 
0.3%
80000 2
 
0.7%
90000 7
 
2.4%
100000 11
 
3.8%
ValueCountFrequency (%)
122750000 1
0.3%
40250000 1
0.3%
39750000 1
0.3%
38500000 1
0.3%
36000000 1
0.3%
33250000 1
0.3%
31500000 1
0.3%
30000000 1
0.3%
24000000 2
0.7%
23500000 1
0.3%

Interactions

2023-12-12T23:55:42.239966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:55:42.047278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:55:42.338167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:55:42.133552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:55:45.482194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구입일자구입금액배부처배부금액(원)
구입일자1.0000.0000.0000.000
구입금액0.0001.0000.9241.000
배부처0.0000.9241.0000.923
배부금액(원)0.0001.0000.9231.000
2023-12-12T23:55:45.569343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구입금액배부금액(원)
구입금액1.0000.877
배부금액(원)0.8771.000

Missing values

2023-12-12T23:55:42.465851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:55:42.591378image/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

구입일자종류구입금액구입목적배부처배부금액(원)
02022-01-18온누리상품권15000021년 4분기 안전활동 우수자 장려금 지급직원 3명150000
12022-01-24온누리상품권1000000설명절 나눔행사 후원서구장애인 종합복지관1000000
22022-01-25온누리상품권2000000설명절 음식나눔행사 후원금통영시장애인종합복지권1000000
32022-01-25온누리상품권0설명절 음식나눔행사 후원금통영시종합사회복지관1000000
42022-01-26온누리상품권2500000설 명절 맞이 사회공헌 활동_후원성육보육원2000000
52022-01-26온누리상품권0설 명절 맞이 사회공헌 활동_후원평택서부노인복지관500000
62022-01-26온누리상품권1200000그린누리 봉사활동시각장애인복지관,연수지역아동센터,장애인종합복지관,모니카의집1200000
72022-01-27온누리상품권1000000사회공헌활동(설 연휴)사회복지법인 금성원300000
82022-01-27온누리상품권0사회공헌활동(설 연휴)소화성가정200000
92022-01-27온누리상품권0사회공헌활동(설 연휴)편한집200000
구입일자종류구입금액구입목적배부처배부금액(원)
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2812022-12-29온누리상품권4000002022년도 공로상 포상자 부상직원 4명400000
2822022-12-29온누리상품권5000002022년 공로상(근무유공,본부장상,특별유공) 포상직원 5명500000
2832022-12-29온누리상품권50000이달의 우수 기술인(12월) 포상직원 1명50000
2842022-12-29온누리상품권5000012월 경상사업 '이달의 우수 기술인'직원 1명50000
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2862022-12-29온누리상품권400000근무유공 포상직원 4명400000
2872022-12-29온누리상품권800002022년 근로자 안전신고 포상직원 1명80000
2882022-12-30온누리상품권200000근무유공 포상비직원 2명200000
2892022-12-30온누리상품권400000'22년도 공로상(근무유공,본부장상,특별유공)포상직원400000