Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory712.9 KiB
Average record size in memory73.0 B

Variable types

Numeric1
DateTime1
Categorical5
Text1

Dataset

Description한국소비자원에 접수된 소비자 피해구제 데이터 현황으로 접수일자, 성별, 연령대, 지역, 물품명 등의 항목을 포함합니다.
Author한국소비자원
URLhttps://www.data.go.kr/data/3040720/fileData.do

Alerts

사건번호 is highly skewed (γ1 = 32.13969161)Skewed
사건번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 15:56:03.859343
Analysis finished2024-03-14 15:56:06.299232
Duration2.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사건번호
Real number (ℝ)

SKEWED  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0230581 × 109
Minimum2.0230498 × 109
Maximum2.0240001 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T00:56:06.447065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0230498 × 109
5-th percentile2.0230506 × 109
Q12.0230535 × 109
median2.0230572 × 109
Q32.023061 × 109
95-th percentile2.0230643 × 109
Maximum2.0240001 × 109
Range950266
Interquartile range (IQR)7503.75

Descriptive statistics

Standard deviation28607.017
Coefficient of variation (CV)1.4140482 × 10-5
Kurtosis1055.7831
Mean2.0230581 × 109
Median Absolute Deviation (MAD)3754
Skewness32.139692
Sum2.0230581 × 1013
Variance8.1836142 × 108
MonotonicityNot monotonic
2024-03-15T00:56:06.723065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2023051651 1
 
< 0.1%
2023053481 1
 
< 0.1%
2023053242 1
 
< 0.1%
2023051419 1
 
< 0.1%
2023057937 1
 
< 0.1%
2023051698 1
 
< 0.1%
2023052387 1
 
< 0.1%
2023057925 1
 
< 0.1%
2023063401 1
 
< 0.1%
2023053387 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2023049832 1
< 0.1%
2023049833 1
< 0.1%
2023049834 1
< 0.1%
2023049835 1
< 0.1%
2023049836 1
< 0.1%
2023049837 1
< 0.1%
2023049838 1
< 0.1%
2023049839 1
< 0.1%
2023049840 1
< 0.1%
2023049842 1
< 0.1%
ValueCountFrequency (%)
2024000098 1
< 0.1%
2024000097 1
< 0.1%
2024000096 1
< 0.1%
2024000095 1
< 0.1%
2024000094 1
< 0.1%
2024000093 1
< 0.1%
2024000092 1
< 0.1%
2024000091 1
< 0.1%
2024000001 1
< 0.1%
2023065053 1
< 0.1%

접수일(년월일)
Date

Distinct92
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-10-01 00:00:00
Maximum2023-12-31 00:00:00
2024-03-15T00:56:06.973000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:56:07.329939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여자
5559 
남자
4441 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여자
2nd row남자
3rd row남자
4th row여자
5th row여자

Common Values

ValueCountFrequency (%)
여자 5559
55.6%
남자 4441
44.4%

Length

2024-03-15T00:56:07.773436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:56:08.083263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여자 5559
55.6%
남자 4441
44.4%

연령대
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
30 - 39세
3205 
40 - 49세
2401 
20 - 29세
1740 
50 - 59세
1414 
60 - 64세
459 
Other values (7)
781 

Length

Max length8
Median length8
Mean length7.8773
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row65 - 69세
2nd row20 - 29세
3rd row20 - 29세
4th row65 - 69세
5th row30 - 39세

Common Values

ValueCountFrequency (%)
30 - 39세 3205
32.0%
40 - 49세 2401
24.0%
20 - 29세 1740
17.4%
50 - 59세 1414
14.1%
60 - 64세 459
 
4.6%
65 - 69세 277
 
2.8%
70 - 79세 197
 
2.0%
불명 163
 
1.6%
10 - 19세 60
 
0.6%
80세이상 46
 
0.5%
Other values (2) 38
 
0.4%

Length

2024-03-15T00:56:08.438160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9753
33.1%
30 3205
 
10.9%
39세 3205
 
10.9%
40 2401
 
8.1%
49세 2401
 
8.1%
20 1740
 
5.9%
29세 1740
 
5.9%
50 1414
 
4.8%
59세 1414
 
4.8%
60 459
 
1.6%
Other values (12) 1777
 
6.0%

지역
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
3053 
서울특별시
2686 
인천광역시
715 
부산광역시
602 
대구광역시
401 
Other values (13)
2543 

Length

Max length7
Median length5
Mean length4.2785
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청남도
2nd row경상북도
3rd row경기도
4th row서울특별시
5th row제주도

Common Values

ValueCountFrequency (%)
경기도 3053
30.5%
서울특별시 2686
26.9%
인천광역시 715
 
7.1%
부산광역시 602
 
6.0%
대구광역시 401
 
4.0%
경상남도 400
 
4.0%
대전광역시 273
 
2.7%
경상북도 266
 
2.7%
충청남도 264
 
2.6%
충청북도 225
 
2.2%
Other values (8) 1115
 
11.2%

Length

2024-03-15T00:56:08.870895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 3053
30.4%
서울특별시 2686
26.8%
인천광역시 715
 
7.1%
부산광역시 602
 
6.0%
대구광역시 401
 
4.0%
경상남도 400
 
4.0%
대전광역시 273
 
2.7%
경상북도 266
 
2.7%
충청남도 264
 
2.6%
충청북도 225
 
2.2%
Other values (10) 1143
 
11.4%

판매유형
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반판매
3749 
국내온라인거래
3169 
기타
752 
방문판매
603 
모바일거래
464 
Other values (7)
1263 

Length

Max length9
Median length7
Mean length5.198
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반판매
2nd row기타
3rd row국제온라인거래
4th row일반판매
5th row일반판매

Common Values

ValueCountFrequency (%)
일반판매 3749
37.5%
국내온라인거래 3169
31.7%
기타 752
 
7.5%
방문판매 603
 
6.0%
모바일거래 464
 
4.6%
기타통신판매 356
 
3.6%
소셜커머스(쇼핑) 324
 
3.2%
전화권유판매 277
 
2.8%
국제온라인거래 167
 
1.7%
TV홈쇼핑 122
 
1.2%
Other values (2) 17
 
0.2%

Length

2024-03-15T00:56:09.306343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반판매 3749
37.5%
국내온라인거래 3169
31.7%
기타 752
 
7.5%
방문판매 603
 
6.0%
모바일거래 464
 
4.6%
기타통신판매 356
 
3.6%
소셜커머스(쇼핑 324
 
3.2%
전화권유판매 277
 
2.8%
국제온라인거래 167
 
1.7%
tv홈쇼핑 122
 
1.2%
Other values (2) 17
 
0.2%

물품소분류
Text

Distinct710
Distinct (%)7.1%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-15T00:56:10.326200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length16
Mean length5.9212843
Min length1

Characters and Unicode

Total characters59201
Distinct characters453
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique189 ?
Unique (%)1.9%

Sample

1st row실손보험
2nd row인터넷게임서비스
3rd row가습기
4th row모바일게임서비스
5th row옷장
ValueCountFrequency (%)
헬스장 573
 
5.6%
항공여객운송서비스 353
 
3.4%
인터넷교육서비스 224
 
2.2%
점퍼·재킷류 191
 
1.9%
필라테스 188
 
1.8%
국외여행 169
 
1.6%
이동전화서비스 158
 
1.5%
양복(서양식 152
 
1.5%
의복)세탁 152
 
1.5%
호텔 143
 
1.4%
Other values (702) 7959
77.6%
2024-03-15T00:56:11.654402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 3469
 
5.9%
기 2763
 
4.7%
비 2307
 
3.9%
서 2235
 
3.8%
타 1739
 
2.9%
· 1397
 
2.4%
장 1006
 
1.7%
이 921
 
1.6%
용 890
 
1.5%
여 879
 
1.5%
Other values (443) 41595
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55471
93.7%
Other Punctuation 1439
 
2.4%
Open Punctuation 805
 
1.4%
Close Punctuation 805
 
1.4%
Uppercase Letter 416
 
0.7%
Space Separator 264
 
0.4%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 3469
 
6.3%
기 2763
 
5.0%
비 2307
 
4.2%
서 2235
 
4.0%
타 1739
 
3.1%
장 1006
 
1.8%
이 921
 
1.7%
용 890
 
1.6%
여 879
 
1.6%
동 726
 
1.3%
Other values (424) 38536
69.5%
Uppercase Letter
ValueCountFrequency (%)
T 129
31.0%
V 96
23.1%
D 53
12.7%
C 44
 
10.6%
P 36
 
8.7%
O 23
 
5.5%
L 14
 
3.4%
I 11
 
2.6%
W 4
 
1.0%
S 4
 
1.0%
Other values (2) 2
 
0.5%
Other Punctuation
ValueCountFrequency (%)
· 1397
97.1%
, 38
 
2.6%
/ 4
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 805
100.0%
Close Punctuation
ValueCountFrequency (%)
) 805
100.0%
Space Separator
ValueCountFrequency (%)
264
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55471
93.7%
Common 3314
 
5.6%
Latin 416
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 3469
 
6.3%
기 2763
 
5.0%
비 2307
 
4.2%
서 2235
 
4.0%
타 1739
 
3.1%
장 1006
 
1.8%
이 921
 
1.7%
용 890
 
1.6%
여 879
 
1.6%
동 726
 
1.3%
Other values (424) 38536
69.5%
Latin
ValueCountFrequency (%)
T 129
31.0%
V 96
23.1%
D 53
12.7%
C 44
 
10.6%
P 36
 
8.7%
O 23
 
5.5%
L 14
 
3.4%
I 11
 
2.6%
W 4
 
1.0%
S 4
 
1.0%
Other values (2) 2
 
0.5%
Common
ValueCountFrequency (%)
· 1397
42.2%
( 805
24.3%
) 805
24.3%
264
 
8.0%
, 38
 
1.1%
/ 4
 
0.1%
2 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55471
93.7%
ASCII 2333
 
3.9%
None 1397
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 3469
 
6.3%
기 2763
 
5.0%
비 2307
 
4.2%
서 2235
 
4.0%
타 1739
 
3.1%
장 1006
 
1.8%
이 921
 
1.7%
용 890
 
1.6%
여 879
 
1.6%
동 726
 
1.3%
Other values (424) 38536
69.5%
None
ValueCountFrequency (%)
· 1397
100.0%
ASCII
ValueCountFrequency (%)
( 805
34.5%
) 805
34.5%
264
 
11.3%
T 129
 
5.5%
V 96
 
4.1%
D 53
 
2.3%
C 44
 
1.9%
, 38
 
1.6%
P 36
 
1.5%
O 23
 
1.0%
Other values (8) 40
 
1.7%

청구이유
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
계약해제.해지/위약금
2839 
품질(물품/용역)
2260 
계약불이행(불완전이행)
1796 
청약철회
1392 
AS불만
544 
Other values (11)
1169 

Length

Max length12
Median length11
Mean length8.6243
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row계약불이행(불완전이행)
2nd row부당행위
3rd row계약불이행(불완전이행)
4th row계약해제.해지/위약금
5th row계약해제.해지/위약금

Common Values

ValueCountFrequency (%)
계약해제.해지/위약금 2839
28.4%
품질(물품/용역) 2260
22.6%
계약불이행(불완전이행) 1796
18.0%
청약철회 1392
13.9%
AS불만 544
 
5.4%
부당행위 427
 
4.3%
표시.광고 210
 
2.1%
약관 173
 
1.7%
가격.요금 135
 
1.4%
안전(제품/시설) 114
 
1.1%
Other values (6) 110
 
1.1%

Length

2024-03-15T00:56:12.091361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계약해제.해지/위약금 2839
28.4%
품질(물품/용역 2260
22.6%
계약불이행(불완전이행 1796
18.0%
청약철회 1392
13.9%
as불만 544
 
5.4%
부당행위 427
 
4.3%
표시.광고 210
 
2.1%
약관 173
 
1.7%
가격.요금 135
 
1.4%
안전(제품/시설 114
 
1.1%
Other values (6) 110
 
1.1%

Interactions

2024-03-15T00:56:05.166019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:56:12.334184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사건번호접수일(년월일)성별연령대지역판매유형청구이유
사건번호1.0001.0000.0000.0000.0190.0000.000
접수일(년월일)1.0001.0000.0470.0000.1160.0810.090
성별0.0000.0471.0000.1770.0580.0770.158
연령대0.0000.0000.1771.0000.0930.2140.207
지역0.0190.1160.0580.0931.0000.1750.105
판매유형0.0000.0810.0770.2140.1751.0000.374
청구이유0.0000.0900.1580.2070.1050.3741.000
2024-03-15T00:56:12.525664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
청구이유판매유형지역성별연령대
청구이유1.0000.1420.0340.1240.075
판매유형0.1421.0000.0590.0600.062
지역0.0340.0591.0000.0450.031
성별0.1240.0600.0451.0000.137
연령대0.0750.0620.0310.1371.000
2024-03-15T00:56:12.728348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사건번호성별연령대지역판매유형청구이유
사건번호1.0000.0000.0000.0150.0000.000
성별0.0001.0000.1370.0450.0600.124
연령대0.0000.1371.0000.0310.0620.075
지역0.0150.0450.0311.0000.0590.034
판매유형0.0000.0600.0620.0591.0000.142
청구이유0.0000.1240.0750.0340.1421.000

Missing values

2024-03-15T00:56:05.741454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:56:06.111125image/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

사건번호접수일(년월일)성별연령대지역판매유형물품소분류청구이유
145920230516512023-10-16여자65 - 69세충청남도일반판매실손보험계약불이행(불완전이행)
835520230603342023-12-04남자20 - 29세경상북도기타인터넷게임서비스부당행위
436620230553112023-11-06남자20 - 29세경기도국제온라인거래가습기계약불이행(불완전이행)
673220230582172023-11-22여자65 - 69세서울특별시일반판매모바일게임서비스계약해제.해지/위약금
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