Overview

Dataset statistics

Number of variables4
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.2 KiB
Average record size in memory35.3 B

Variable types

Text1
Numeric3

Dataset

Description1372 소비자상담센터에 접수된 소비자 상담 데이터 기반의 품목별 상담 접수 현황 (상위 다발 품목 500개) 관련 데이터 입니다.
Author한국소비자원
URLhttps://www.data.go.kr/data/15120072/fileData.do

Alerts

품목명(소) has unique valuesUnique
증감률_전월 has 24 (4.8%) zerosZeros
증감률_전년동월 has 24 (4.8%) zerosZeros

Reproduction

Analysis started2024-04-06 08:05:51.431208
Analysis finished2024-04-06 08:05:53.856405
Duration2.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목명(소)
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-06T17:05:54.166709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length16
Mean length5.64
Min length1

Characters and Unicode

Total characters2820
Distinct characters390
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st row숙녀화(구두·부츠 등)
2nd row헬스장
3rd row신발·운동화
4th row항공여객운송서비스
5th row이동전화서비스
ValueCountFrequency (%)
등 7
 
1.4%
위성방송 1
 
0.2%
블루투스스피커 1
 
0.2%
피혁세탁 1
 
0.2%
인쇄서비스 1
 
0.2%
이불·침대커버 1
 
0.2%
각종사무용품 1
 
0.2%
벨트 1
 
0.2%
케이크 1
 
0.2%
무스탕 1
 
0.2%
Other values (491) 491
96.8%
2024-04-06T17:05:54.879536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 103
 
3.7%
종 100
 
3.5%
각 98
 
3.5%
스 89
 
3.2%
· 78
 
2.8%
비 70
 
2.5%
용 55
 
2.0%
서 55
 
2.0%
자 46
 
1.6%
품 44
 
1.6%
Other values (380) 2082
73.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2632
93.3%
Other Punctuation 82
 
2.9%
Close Punctuation 35
 
1.2%
Open Punctuation 35
 
1.2%
Uppercase Letter 29
 
1.0%
Space Separator 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 103
 
3.9%
종 100
 
3.8%
각 98
 
3.7%
스 89
 
3.4%
비 70
 
2.7%
용 55
 
2.1%
서 55
 
2.1%
자 46
 
1.7%
품 44
 
1.7%
이 39
 
1.5%
Other values (363) 1933
73.4%
Uppercase Letter
ValueCountFrequency (%)
T 6
20.7%
D 5
17.2%
V 5
17.2%
C 4
13.8%
P 3
10.3%
L 1
 
3.4%
A 1
 
3.4%
W 1
 
3.4%
I 1
 
3.4%
O 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
· 78
95.1%
, 2
 
2.4%
/ 2
 
2.4%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2632
93.3%
Common 159
 
5.6%
Latin 29
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 103
 
3.9%
종 100
 
3.8%
각 98
 
3.7%
스 89
 
3.4%
비 70
 
2.7%
용 55
 
2.1%
서 55
 
2.1%
자 46
 
1.7%
품 44
 
1.7%
이 39
 
1.5%
Other values (363) 1933
73.4%
Latin
ValueCountFrequency (%)
T 6
20.7%
D 5
17.2%
V 5
17.2%
C 4
13.8%
P 3
10.3%
L 1
 
3.4%
A 1
 
3.4%
W 1
 
3.4%
I 1
 
3.4%
O 1
 
3.4%
Common
ValueCountFrequency (%)
· 78
49.1%
) 35
22.0%
( 35
22.0%
7
 
4.4%
, 2
 
1.3%
/ 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2632
93.3%
ASCII 110
 
3.9%
None 78
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 103
 
3.9%
종 100
 
3.8%
각 98
 
3.7%
스 89
 
3.4%
비 70
 
2.7%
용 55
 
2.1%
서 55
 
2.1%
자 46
 
1.7%
품 44
 
1.7%
이 39
 
1.5%
Other values (363) 1933
73.4%
None
ValueCountFrequency (%)
· 78
100.0%
ASCII
ValueCountFrequency (%)
) 35
31.8%
( 35
31.8%
7
 
6.4%
T 6
 
5.5%
D 5
 
4.5%
V 5
 
4.5%
C 4
 
3.6%
P 3
 
2.7%
, 2
 
1.8%
/ 2
 
1.8%
Other values (6) 6
 
5.5%

상담건수
Real number (ℝ)

Distinct150
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.944
Minimum9
Maximum1214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-06T17:05:55.245283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile9
Q114
median27
Q361
95-th percentile279.85
Maximum1214
Range1205
Interquartile range (IQR)47

Descriptive statistics

Standard deviation131.47736
Coefficient of variation (CV)1.8274959
Kurtosis24.334052
Mean71.944
Median Absolute Deviation (MAD)16
Skewness4.3743958
Sum35972
Variance17286.297
MonotonicityDecreasing
2024-04-06T17:05:55.680838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 33
 
6.6%
10 30
 
6.0%
11 25
 
5.0%
18 19
 
3.8%
13 18
 
3.6%
15 18
 
3.6%
12 14
 
2.8%
14 13
 
2.6%
17 13
 
2.6%
26 12
 
2.4%
Other values (140) 305
61.0%
ValueCountFrequency (%)
9 33
6.6%
10 30
6.0%
11 25
5.0%
12 14
2.8%
13 18
3.6%
14 13
 
2.6%
15 18
3.6%
16 4
 
0.8%
17 13
 
2.6%
18 19
3.8%
ValueCountFrequency (%)
1214 1
0.2%
1000 1
0.2%
820 1
0.2%
819 1
0.2%
781 1
0.2%
733 1
0.2%
631 1
0.2%
627 1
0.2%
569 1
0.2%
557 1
0.2%

증감률_전월
Real number (ℝ)

ZEROS 

Distinct312
Distinct (%)62.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.4748
Minimum-70
Maximum500
Zeros24
Zeros (%)4.8%
Negative340
Negative (%)68.0%
Memory size4.5 KiB
2024-04-06T17:05:56.070768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-70
5-th percentile-48.575
Q1-29.775
median-13.4
Q35.075
95-th percentile100
Maximum500
Range570
Interquartile range (IQR)34.85

Descriptive statistics

Standard deviation50.416838
Coefficient of variation (CV)-20.372086
Kurtosis23.338705
Mean-2.4748
Median Absolute Deviation (MAD)16.85
Skewness3.6476973
Sum-1237.4
Variance2541.8576
MonotonicityNot monotonic
2024-04-06T17:05:56.309165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 24
 
4.8%
-25.0 7
 
1.4%
100.0 6
 
1.2%
-50.0 6
 
1.2%
-10.0 5
 
1.0%
150.0 5
 
1.0%
-28.6 5
 
1.0%
-30.8 5
 
1.0%
-9.1 5
 
1.0%
11.1 5
 
1.0%
Other values (302) 427
85.4%
ValueCountFrequency (%)
-70.0 1
0.2%
-64.3 1
0.2%
-62.1 1
0.2%
-59.5 1
0.2%
-59.4 1
0.2%
-56.5 1
0.2%
-55.0 1
0.2%
-54.5 2
0.4%
-54.2 1
0.2%
-53.8 1
0.2%
ValueCountFrequency (%)
500.0 1
 
0.2%
233.3 1
 
0.2%
225.0 1
 
0.2%
200.0 2
 
0.4%
198.7 1
 
0.2%
192.9 1
 
0.2%
175.0 1
 
0.2%
160.0 1
 
0.2%
157.1 1
 
0.2%
150.0 5
1.0%

증감률_전년동월
Real number (ℝ)

ZEROS 

Distinct323
Distinct (%)64.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.969
Minimum-70.6
Maximum3383.3
Zeros24
Zeros (%)4.8%
Negative248
Negative (%)49.6%
Memory size4.5 KiB
2024-04-06T17:05:56.575496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-70.6
5-th percentile-44.92
Q1-23.1
median0
Q325.925
95-th percentile188.125
Maximum3383.3
Range3453.9
Interquartile range (IQR)49.025

Descriptive statistics

Standard deviation220.5949
Coefficient of variation (CV)5.8098685
Kurtosis122.54179
Mean37.969
Median Absolute Deviation (MAD)23.5
Skewness9.7665912
Sum18984.5
Variance48662.109
MonotonicityNot monotonic
2024-04-06T17:05:56.830054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 24
 
4.8%
20.0 7
 
1.4%
-25.0 6
 
1.2%
12.5 6
 
1.2%
-18.2 6
 
1.2%
22.2 6
 
1.2%
150.0 6
 
1.2%
11.1 5
 
1.0%
-20.0 5
 
1.0%
200.0 5
 
1.0%
Other values (313) 424
84.8%
ValueCountFrequency (%)
-70.6 1
0.2%
-69.4 1
0.2%
-67.7 1
0.2%
-60.0 1
0.2%
-59.1 1
0.2%
-57.6 1
0.2%
-55.0 1
0.2%
-53.2 1
0.2%
-51.5 1
0.2%
-51.4 1
0.2%
ValueCountFrequency (%)
3383.3 1
0.2%
1800.0 1
0.2%
1700.0 1
0.2%
1050.0 1
0.2%
1045.3 1
0.2%
900.0 2
0.4%
811.8 1
0.2%
800.0 1
0.2%
656.7 1
0.2%
361.1 1
0.2%

Interactions

2024-04-06T17:05:52.891686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:05:51.826489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:05:52.362235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:05:53.076510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:05:52.023010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:05:52.526220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:05:53.260150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:05:52.192515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:05:52.702869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:05:57.012989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상담건수증감률_전월증감률_전년동월
상담건수1.0000.0000.710
증감률_전월0.0001.0000.521
증감률_전년동월0.7100.5211.000
2024-04-06T17:05:57.221609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상담건수증감률_전월증감률_전년동월
상담건수1.000-0.074-0.072
증감률_전월-0.0741.0000.464
증감률_전년동월-0.0720.4641.000

Missing values

2024-04-06T17:05:53.588443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:05:53.793179image/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

품목명(소)상담건수증감률_전월증감률_전년동월
0숙녀화(구두·부츠 등)121432.11045.3
1헬스장1000-9.6-27.3
2신발·운동화8205.57.8
3항공여객운송서비스819-3.89.1
4이동전화서비스781-19.8-28.8
5각종건강식품733-17.526.6
6의류·섬유631-32.0-23.0
7비타민제62713.03383.3
8휴대폰/스마트폰5692.0-18.2
9점퍼·재킷류557-45.2-6.4
품목명(소)상담건수증감률_전월증감률_전년동월
490탁자950.0200.0
491소아청소년과90.012.5
492태양열온수기9-52.6-40.0
493각종냉장·냉동기기928.6-10.0
494레인지후드980.012.5
495벽지·바닥재9-47.1200.0
496각종사무용기기980.0350.0
497바나나9125.0350.0
498신사복세트9-52.6-50.0
499각종관람·감상9125.0-25.0