Overview

Dataset statistics

Number of variables3
Number of observations1551
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.0 KiB
Average record size in memory25.1 B

Variable types

Numeric1
Text1
Categorical1

Dataset

Description소비자들의 민원에 대한 상담 데이터에 대하여 품목코드를 대, 중, 소 로 구분하여 관리하고 이를 보여주는 데이터 입니다. 이 데이터는 품목코드, 품목명을 포함하고 있습니다.
Author공정거래위원회
URLhttps://www.data.go.kr/data/15098317/fileData.do

Alerts

등록일자(REG_YMD) has constant value ""Constant
품목코드(ITEM_CODE) has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:27:49.075127
Analysis finished2023-12-12 23:27:49.635571
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목코드(ITEM_CODE)
Real number (ℝ)

UNIQUE 

Distinct1551
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean228068.59
Minimum110000
Maximum510399
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.8 KiB
2023-12-13T08:27:49.706391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110000
5-th percentile110404.5
Q1140552
median190304
Q3250500.5
95-th percentile499992.5
Maximum510399
Range400399
Interquartile range (IQR)109948.5

Descriptive statistics

Standard deviation116022.81
Coefficient of variation (CV)0.50871892
Kurtosis0.13305741
Mean228068.59
Median Absolute Deviation (MAD)50700
Skewness1.1077207
Sum3.5373439 × 108
Variance1.3461292 × 1010
MonotonicityNot monotonic
2023-12-13T08:27:49.862876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
350401 1
 
0.1%
400207 1
 
0.1%
170806 1
 
0.1%
170800 1
 
0.1%
170599 1
 
0.1%
160299 1
 
0.1%
160000 1
 
0.1%
159909 1
 
0.1%
159902 1
 
0.1%
150627 1
 
0.1%
Other values (1541) 1541
99.4%
ValueCountFrequency (%)
110000 1
0.1%
110100 1
0.1%
110101 1
0.1%
110102 1
0.1%
110103 1
0.1%
110104 1
0.1%
110105 1
0.1%
110106 1
0.1%
110107 1
0.1%
110108 1
0.1%
ValueCountFrequency (%)
510399 1
0.1%
510303 1
0.1%
510302 1
0.1%
510301 1
0.1%
510300 1
0.1%
510299 1
0.1%
510204 1
0.1%
510203 1
0.1%
510202 1
0.1%
510201 1
0.1%

품목명(ITEM_NAME)
Text

Distinct1537
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
2023-12-13T08:27:50.069849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length16
Mean length5.0625403
Min length1

Characters and Unicode

Total characters7852
Distinct characters587
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1523 ?
Unique (%)98.2%

Sample

1st row공동주택관리서비스
2nd row건물관리서비스
3rd row기타관리서비스
4th row정보통신서비스
5th row전보·전신환
ValueCountFrequency (%)
등 7
 
0.4%
기타의류·섬유 2
 
0.1%
기타승용물 2
 
0.1%
기타보건·위생용품 2
 
0.1%
세탁서비스 2
 
0.1%
아동복 2
 
0.1%
기타문화용품 2
 
0.1%
기타가사용품 2
 
0.1%
기타의료서비스 2
 
0.1%
비료 2
 
0.1%
Other values (1532) 1537
98.4%
2023-12-13T08:27:50.389582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 442
 
5.6%
스 238
 
3.0%
· 208
 
2.6%
타 196
 
2.5%
비 193
 
2.5%
용 173
 
2.2%
품 159
 
2.0%
서 141
 
1.8%
이 120
 
1.5%
자 115
 
1.5%
Other values (577) 5867
74.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7398
94.2%
Other Punctuation 209
 
2.7%
Uppercase Letter 79
 
1.0%
Close Punctuation 72
 
0.9%
Open Punctuation 72
 
0.9%
Space Separator 11
 
0.1%
Lowercase Letter 9
 
0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 442
 
6.0%
스 238
 
3.2%
타 196
 
2.6%
비 193
 
2.6%
용 173
 
2.3%
품 159
 
2.1%
서 141
 
1.9%
이 120
 
1.6%
자 115
 
1.6%
전 100
 
1.4%
Other values (544) 5521
74.6%
Uppercase Letter
ValueCountFrequency (%)
D 15
19.0%
V 12
15.2%
T 11
13.9%
P 9
11.4%
C 7
8.9%
L 4
 
5.1%
M 3
 
3.8%
E 3
 
3.8%
A 3
 
3.8%
S 2
 
2.5%
Other values (8) 10
12.7%
Lowercase Letter
ValueCountFrequency (%)
t 2
22.2%
a 1
11.1%
i 1
11.1%
u 1
11.1%
g 1
11.1%
r 1
11.1%
p 1
11.1%
o 1
11.1%
Other Punctuation
ValueCountFrequency (%)
· 208
99.5%
/ 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
3 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 72
100.0%
Open Punctuation
ValueCountFrequency (%)
( 72
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7398
94.2%
Common 366
 
4.7%
Latin 88
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 442
 
6.0%
스 238
 
3.2%
타 196
 
2.6%
비 193
 
2.6%
용 173
 
2.3%
품 159
 
2.1%
서 141
 
1.9%
이 120
 
1.6%
자 115
 
1.6%
전 100
 
1.4%
Other values (544) 5521
74.6%
Latin
ValueCountFrequency (%)
D 15
17.0%
V 12
13.6%
T 11
12.5%
P 9
10.2%
C 7
 
8.0%
L 4
 
4.5%
M 3
 
3.4%
E 3
 
3.4%
A 3
 
3.4%
S 2
 
2.3%
Other values (16) 19
21.6%
Common
ValueCountFrequency (%)
· 208
56.8%
) 72
 
19.7%
( 72
 
19.7%
11
 
3.0%
2 1
 
0.3%
3 1
 
0.3%
/ 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7398
94.2%
ASCII 246
 
3.1%
None 208
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 442
 
6.0%
스 238
 
3.2%
타 196
 
2.6%
비 193
 
2.6%
용 173
 
2.3%
품 159
 
2.1%
서 141
 
1.9%
이 120
 
1.6%
자 115
 
1.6%
전 100
 
1.4%
Other values (544) 5521
74.6%
None
ValueCountFrequency (%)
· 208
100.0%
ASCII
ValueCountFrequency (%)
) 72
29.3%
( 72
29.3%
D 15
 
6.1%
V 12
 
4.9%
T 11
 
4.5%
11
 
4.5%
P 9
 
3.7%
C 7
 
2.8%
L 4
 
1.6%
M 3
 
1.2%
Other values (22) 30
12.2%

등록일자(REG_YMD)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
2021-12-27
1551 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-12-27
2nd row2021-12-27
3rd row2021-12-27
4th row2021-12-27
5th row2021-12-27

Common Values

ValueCountFrequency (%)
2021-12-27 1551
100.0%

Length

2023-12-13T08:27:50.517704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:27:50.633366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-12-27 1551
100.0%

Interactions

2023-12-13T08:27:49.365439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T08:27:49.521326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:27:49.603642image/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

품목코드(ITEM_CODE)품목명(ITEM_NAME)등록일자(REG_YMD)
0350401공동주택관리서비스2021-12-27
1350402건물관리서비스2021-12-27
2350499기타관리서비스2021-12-27
3360000정보통신서비스2021-12-27
4360101전보·전신환2021-12-27
5360102우편2021-12-27
6360199기타정보통신2021-12-27
7360201국내전화2021-12-27
8360202국제전화2021-12-27
9360301무선호출서비스2021-12-27
품목코드(ITEM_CODE)품목명(ITEM_NAME)등록일자(REG_YMD)
1541500207기타투자자문컨설팅·상품2021-12-27
1542370409필라테스2021-12-27
1543370410요가2021-12-27
1544139915음식물처리기2021-12-27
1545170308티셔츠2021-12-27
1546170309니트(스웨터)2021-12-27
1547139916음식물처리기대여(렌트)2021-12-27
1548180618안마의자대여(렌트)2021-12-27
1549150326공기청정기대여(렌트)2021-12-27
1550140408침대·매트리스대여(렌트)2021-12-27