Overview

Dataset statistics

Number of variables3
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory29.2 B

Variable types

Categorical1
Numeric1
Text1

Dataset

Description120바로콜센터의 상담사가 상담시 상담 참고자료로 활용하기 위한 보조업무시스템인 지능형상담정보시스템을 사용하여 검색한 키워드 정보입니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15078206/fileData.do

Reproduction

Analysis started2024-03-14 15:37:46.681944
Analysis finished2024-03-14 15:37:47.483568
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조사년도
Categorical

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
2020
10 
2021
10 
2022
10 
2023
10 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 10
25.0%
2021 10
25.0%
2022 10
25.0%
2023 10
25.0%

Length

2024-03-15T00:37:47.694693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:37:48.087420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 10
25.0%
2021 10
25.0%
2022 10
25.0%
2023 10
25.0%

순위
Real number (ℝ)

Distinct10
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size488.0 B
2024-03-15T00:37:48.478261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5.5
Q38
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.9088724
Coefficient of variation (CV)0.52888589
Kurtosis-1.2258632
Mean5.5
Median Absolute Deviation (MAD)2.5
Skewness0
Sum220
Variance8.4615385
MonotonicityNot monotonic
2024-03-15T00:37:48.817842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 4
10.0%
2 4
10.0%
3 4
10.0%
4 4
10.0%
5 4
10.0%
6 4
10.0%
7 4
10.0%
8 4
10.0%
9 4
10.0%
10 4
10.0%
ValueCountFrequency (%)
1 4
10.0%
2 4
10.0%
3 4
10.0%
4 4
10.0%
5 4
10.0%
6 4
10.0%
7 4
10.0%
8 4
10.0%
9 4
10.0%
10 4
10.0%
ValueCountFrequency (%)
10 4
10.0%
9 4
10.0%
8 4
10.0%
7 4
10.0%
6 4
10.0%
5 4
10.0%
4 4
10.0%
3 4
10.0%
2 4
10.0%
1 4
10.0%

키워드
Text

Distinct29
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
2024-03-15T00:37:49.570865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.575
Min length2

Characters and Unicode

Total characters143
Distinct characters79
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)50.0%

Sample

1st row차량이전
2nd row자동차세
3rd row번호판
4th row회진
5th row상속
ValueCountFrequency (%)
번호판 3
 
7.3%
여권 3
 
7.3%
저감장치 2
 
4.9%
이전 2
 
4.9%
개인 2
 
4.9%
자동차세 2
 
4.9%
공동명의 2
 
4.9%
조기폐차 2
 
4.9%
머물자리론 2
 
4.9%
공동 1
 
2.4%
Other values (20) 20
48.8%
2024-03-15T00:37:50.626735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
차 7
 
4.9%
자 5
 
3.5%
동 5
 
3.5%
번 4
 
2.8%
판 4
 
2.8%
여 4
 
2.8%
권 4
 
2.8%
량 4
 
2.8%
호 4
 
2.8%
전 4
 
2.8%
Other values (69) 98
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142
99.3%
Space Separator 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 7
 
4.9%
자 5
 
3.5%
동 5
 
3.5%
번 4
 
2.8%
판 4
 
2.8%
여 4
 
2.8%
권 4
 
2.8%
량 4
 
2.8%
호 4
 
2.8%
전 4
 
2.8%
Other values (68) 97
68.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142
99.3%
Common 1
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 7
 
4.9%
자 5
 
3.5%
동 5
 
3.5%
번 4
 
2.8%
판 4
 
2.8%
여 4
 
2.8%
권 4
 
2.8%
량 4
 
2.8%
호 4
 
2.8%
전 4
 
2.8%
Other values (68) 97
68.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142
99.3%
ASCII 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
차 7
 
4.9%
자 5
 
3.5%
동 5
 
3.5%
번 4
 
2.8%
판 4
 
2.8%
여 4
 
2.8%
권 4
 
2.8%
량 4
 
2.8%
호 4
 
2.8%
전 4
 
2.8%
Other values (68) 97
68.3%
ASCII
ValueCountFrequency (%)
1
100.0%

Interactions

2024-03-15T00:37:46.839047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:37:50.887118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조사년도순위키워드
조사년도1.0000.0000.000
순위0.0001.0000.740
키워드0.0000.7401.000
2024-03-15T00:37:51.125370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위조사년도
순위1.0000.000
조사년도0.0001.000

Missing values

2024-03-15T00:37:47.145608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:37:47.387567image/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

조사년도순위키워드
020201차량이전
120202자동차세
220203번호판
320204회진
420205상속
520206건축분쟁
620207여권
720208마스크 미착용
820209농산물꾸러미
9202010부산
조사년도순위키워드
3020231노후경유차량
3120232저감장치
3220233긴급여권
3320234머물자리론
3420235전기차보조금
3520236운수사업법
3620237불량번호판
3720238주택융자
3820239자동차세
39202310긴급난방비