Overview

Dataset statistics

Number of variables7
Number of observations109
Missing cells409
Missing cells (%)53.6%
Duplicate rows2
Duplicate rows (%)1.8%
Total size in memory6.1 KiB
Average record size in memory57.2 B

Variable types

Text1
Unsupported6

Dataset

Description소비자상담및피해구제접수현황2017년도
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201709

Alerts

Dataset has 2 (1.8%) duplicate rowsDuplicates
2017년도 소비자상담 및 피해구제 접수 현황 (전라북도 내 소비자상담기관 상담 통계) has 32 (29.4%) missing valuesMissing
Unnamed: 1 has 24 (22.0%) missing valuesMissing
Unnamed: 2 has 23 (21.1%) missing valuesMissing
Unnamed: 3 has 55 (50.5%) missing valuesMissing
Unnamed: 4 has 83 (76.1%) missing valuesMissing
Unnamed: 5 has 85 (78.0%) missing valuesMissing
Unnamed: 6 has 107 (98.2%) missing valuesMissing
Unnamed: 1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:52:33.121237
Analysis finished2024-03-14 02:52:33.507315
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2017년도 소비자상담 및 피해구제 접수 현황 (전라북도 내 소비자상담기관 상담 통계)
Text

MISSING 

Distinct75
Distinct (%)97.4%
Missing32
Missing (%)29.4%
Memory size1004.0 B
2024-03-14T11:52:33.665519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.1818182
Min length2

Characters and Unicode

Total characters476
Distinct characters140
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

Unique74 ?
Unique (%)96.1%

Sample

1st row1. 연도별 접수 현황
2nd row(단위: 건)
3rd row구분
4th row상담건수
5th row2. 접수방법별 현황
ValueCountFrequency (%)
현황 7
 
6.6%
총 3
 
2.8%
계 3
 
2.8%
소비자상담 3
 
2.8%
통계 3
 
2.8%
건 2
 
1.9%
처리결과별 2
 
1.9%
접수방법별 2
 
1.9%
품목별 2
 
1.9%
피해구제 1
 
0.9%
Other values (78) 78
73.6%
2024-03-14T11:52:34.001476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
 
6.5%
. 13
 
2.7%
상 11
 
2.3%
계 11
 
2.3%
품 11
 
2.3%
별 11
 
2.3%
· 9
 
1.9%
수 9
 
1.9%
비 9
 
1.9%
황 8
 
1.7%
Other values (130) 353
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 373
78.4%
Space Separator 31
 
6.5%
Decimal Number 27
 
5.7%
Other Punctuation 26
 
5.5%
Open Punctuation 5
 
1.1%
Dash Punctuation 5
 
1.1%
Close Punctuation 5
 
1.1%
Uppercase Letter 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 11
 
2.9%
계 11
 
2.9%
품 11
 
2.9%
별 11
 
2.9%
수 9
 
2.4%
비 9
 
2.4%
황 8
 
2.1%
기 8
 
2.1%
현 8
 
2.1%
매 8
 
2.1%
Other values (109) 279
74.8%
Decimal Number
ValueCountFrequency (%)
0 5
18.5%
9 5
18.5%
2 3
11.1%
4 3
11.1%
3 3
11.1%
5 3
11.1%
1 3
11.1%
7 1
 
3.7%
6 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 13
50.0%
· 9
34.6%
/ 3
 
11.5%
: 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
V 1
25.0%
T 1
25.0%
A 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 373
78.4%
Common 99
 
20.8%
Latin 4
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 11
 
2.9%
계 11
 
2.9%
품 11
 
2.9%
별 11
 
2.9%
수 9
 
2.4%
비 9
 
2.4%
황 8
 
2.1%
기 8
 
2.1%
현 8
 
2.1%
매 8
 
2.1%
Other values (109) 279
74.8%
Common
ValueCountFrequency (%)
31
31.3%
. 13
13.1%
· 9
 
9.1%
( 5
 
5.1%
0 5
 
5.1%
- 5
 
5.1%
9 5
 
5.1%
) 5
 
5.1%
2 3
 
3.0%
4 3
 
3.0%
Other values (7) 15
15.2%
Latin
ValueCountFrequency (%)
V 1
25.0%
T 1
25.0%
A 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 373
78.4%
ASCII 94
 
19.7%
None 9
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31
33.0%
. 13
13.8%
( 5
 
5.3%
0 5
 
5.3%
- 5
 
5.3%
9 5
 
5.3%
) 5
 
5.3%
2 3
 
3.2%
4 3
 
3.2%
/ 3
 
3.2%
Other values (10) 16
17.0%
Hangul
ValueCountFrequency (%)
상 11
 
2.9%
계 11
 
2.9%
품 11
 
2.9%
별 11
 
2.9%
수 9
 
2.4%
비 9
 
2.4%
황 8
 
2.1%
기 8
 
2.1%
현 8
 
2.1%
매 8
 
2.1%
Other values (109) 279
74.8%
None
ValueCountFrequency (%)
· 9
100.0%

Unnamed: 1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)22.0%
Memory size1004.0 B

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)21.1%
Memory size1004.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing55
Missing (%)50.5%
Memory size1004.0 B

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing83
Missing (%)76.1%
Memory size1004.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)78.0%
Memory size1004.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing107
Missing (%)98.2%
Memory size1004.0 B

Missing values

2024-03-14T11:52:33.247549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:52:33.345843image/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.
2024-03-14T11:52:33.440673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

2017년도 소비자상담 및 피해구제 접수 현황 (전라북도 내 소비자상담기관 상담 통계)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
0<NA>NaNNaNNaNNaNNaNNaN
1<NA>NaNNaNNaNNaNNaNNaN
2<NA>NaNNaNNaNNaNNaNNaN
31. 연도별 접수 현황NaNNaNNaNNaNNaNNaN
4(단위: 건)NaNNaNNaNNaNNaNNaN
5구분2014년도2015년도2016년도2017년도NaNNaN
6상담건수34830290433113134705NaNNaN
7<NA>NaNNaNNaNNaNNaNNaN
82. 접수방법별 현황NaNNaNNaNNaNNaNNaN
9접수방법별 현황NaNNaNNaNNaNNaNNaN
2017년도 소비자상담 및 피해구제 접수 현황 (전라북도 내 소비자상담기관 상담 통계)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
99<NA>NaNNaNNaNNaNNaNNaN
1007. 연령별 현황NaNNaNNaNNaNNaNNaN
101연령대NaNNaNNaNNaNNaNNaN
102연령건 수비율연령건 수비율NaN
10310-19세1250.3660 - 64세24697.11NaN
10420-29세32109.2565 - 69세7482.16NaN
10530-39세849624.4870-79세4761.37NaN
10640-49세1041830.0280세 이상770.22NaN
10750-59세855224.64불명1340.39NaN
108총 계NaNNaNNaN34705100NaN

Duplicate rows

Most frequently occurring

2017년도 소비자상담 및 피해구제 접수 현황 (전라북도 내 소비자상담기관 상담 통계)# duplicates
1<NA>32
0총 계3