Overview

Dataset statistics

Number of variables5
Number of observations50
Missing cells12
Missing cells (%)4.8%
Duplicate rows2
Duplicate rows (%)4.0%
Total size in memory2.2 KiB
Average record size in memory45.6 B

Variable types

Categorical2
Text1
DateTime1
Numeric1

Dataset

Description한국교통안전공단 통합홈페이지시스템에서 관리하고 있는 일일접속자 및 만족도 평가관리 정보입니다
Author한국교통안전공단
URLhttps://www.data.go.kr/data/15066124/fileData.do

Alerts

Dataset has 2 (4.0%) duplicate rowsDuplicates
개선의견 has 6 (12.0%) missing valuesMissing
직업구분 has 6 (12.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 07:42:25.818218
Analysis finished2023-12-12 07:42:26.610890
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

만족도점수
Categorical

Distinct6
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
5
18 
4
10 
1
8 
<NA>
6 
3
6 

Length

Max length4
Median length1
Mean length1.36
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
5 18
36.0%
4 10
20.0%
1 8
16.0%
<NA> 6
 
12.0%
3 6
 
12.0%
2 2
 
4.0%

Length

2023-12-12T16:42:26.694031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:42:26.827064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 18
36.0%
4 10
20.0%
1 8
16.0%
na 6
 
12.0%
3 6
 
12.0%
2 2
 
4.0%

개선의견
Text

MISSING 

Distinct30
Distinct (%)68.2%
Missing6
Missing (%)12.0%
Memory size532.0 B
2023-12-12T16:42:27.079631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length53
Mean length12.727273
Min length1

Characters and Unicode

Total characters560
Distinct characters189
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)54.5%

Sample

1st rowe
2nd rowe
3rd rowe
4th rowe
5th row만족합니다
ValueCountFrequency (%)
8
 
6.6%
없음 5
 
4.1%
좋아요 5
 
4.1%
e 4
 
3.3%
곳 2
 
1.6%
다른 2
 
1.6%
정밀검사 2
 
1.6%
볼수있게 2
 
1.6%
있나요 2
 
1.6%
운전적성 2
 
1.6%
Other values (86) 88
72.1%
2023-12-12T16:42:27.440286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
78
 
13.9%
. 18
 
3.2%
요 16
 
2.9%
이 12
 
2.1%
자 10
 
1.8%
없 8
 
1.4%
전 8
 
1.4%
1 8
 
1.4%
사 8
 
1.4%
아 7
 
1.2%
Other values (179) 387
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 396
70.7%
Space Separator 78
 
13.9%
Other Punctuation 30
 
5.4%
Decimal Number 24
 
4.3%
Lowercase Letter 17
 
3.0%
Dash Punctuation 4
 
0.7%
Close Punctuation 4
 
0.7%
Open Punctuation 3
 
0.5%
Math Symbol 3
 
0.5%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
요 16
 
4.0%
이 12
 
3.0%
자 10
 
2.5%
없 8
 
2.0%
전 8
 
2.0%
사 8
 
2.0%
아 7
 
1.8%
시 7
 
1.8%
다 7
 
1.8%
서 6
 
1.5%
Other values (150) 307
77.5%
Decimal Number
ValueCountFrequency (%)
1 8
33.3%
0 5
20.8%
9 3
 
12.5%
6 3
 
12.5%
2 2
 
8.3%
3 1
 
4.2%
8 1
 
4.2%
5 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 18
60.0%
, 3
 
10.0%
? 3
 
10.0%
; 2
 
6.7%
! 2
 
6.7%
@ 1
 
3.3%
: 1
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
q 5
29.4%
e 4
23.5%
d 4
23.5%
a 1
 
5.9%
m 1
 
5.9%
t 1
 
5.9%
j 1
 
5.9%
Math Symbol
ValueCountFrequency (%)
> 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 396
70.7%
Common 146
 
26.1%
Latin 18
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
요 16
 
4.0%
이 12
 
3.0%
자 10
 
2.5%
없 8
 
2.0%
전 8
 
2.0%
사 8
 
2.0%
아 7
 
1.8%
시 7
 
1.8%
다 7
 
1.8%
서 6
 
1.5%
Other values (150) 307
77.5%
Common
ValueCountFrequency (%)
78
53.4%
. 18
 
12.3%
1 8
 
5.5%
0 5
 
3.4%
- 4
 
2.7%
) 4
 
2.7%
( 3
 
2.1%
, 3
 
2.1%
9 3
 
2.1%
? 3
 
2.1%
Other values (11) 17
 
11.6%
Latin
ValueCountFrequency (%)
q 5
27.8%
e 4
22.2%
d 4
22.2%
a 1
 
5.6%
m 1
 
5.6%
t 1
 
5.6%
j 1
 
5.6%
N 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 394
70.4%
ASCII 164
29.3%
Compat Jamo 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
47.6%
. 18
 
11.0%
1 8
 
4.9%
q 5
 
3.0%
0 5
 
3.0%
e 4
 
2.4%
d 4
 
2.4%
- 4
 
2.4%
) 4
 
2.4%
( 3
 
1.8%
Other values (19) 31
 
18.9%
Hangul
ValueCountFrequency (%)
요 16
 
4.1%
이 12
 
3.0%
자 10
 
2.5%
없 8
 
2.0%
전 8
 
2.0%
사 8
 
2.0%
아 7
 
1.8%
시 7
 
1.8%
다 7
 
1.8%
서 6
 
1.5%
Other values (148) 305
77.4%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
50.0%
ㅎ 1
50.0%

최초등록일시
Date

Distinct9
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
Minimum2019-03-06 00:00:00
Maximum2020-03-25 00:00:00
2023-12-12T16:42:27.536649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:42:27.624841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

직업구분
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)18.2%
Missing6
Missing (%)12.0%
Infinite0
Infinite (%)0.0%
Mean5.5909091
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-12T16:42:27.706989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median6.5
Q37
95-th percentile7
Maximum19
Range18
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.8228155
Coefficient of variation (CV)0.50489383
Kurtosis11.067388
Mean5.5909091
Median Absolute Deviation (MAD)0.5
Skewness2.239429
Sum246
Variance7.9682875
MonotonicityNot monotonic
2023-12-12T16:42:27.789229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
7 21
42.0%
4 13
26.0%
2 3
 
6.0%
6 2
 
4.0%
1 2
 
4.0%
5 1
 
2.0%
19 1
 
2.0%
3 1
 
2.0%
(Missing) 6
 
12.0%
ValueCountFrequency (%)
1 2
 
4.0%
2 3
 
6.0%
3 1
 
2.0%
4 13
26.0%
5 1
 
2.0%
6 2
 
4.0%
7 21
42.0%
19 1
 
2.0%
ValueCountFrequency (%)
19 1
 
2.0%
7 21
42.0%
6 2
 
4.0%
5 1
 
2.0%
4 13
26.0%
3 1
 
2.0%
2 3
 
6.0%
1 2
 
4.0%

연령대
Categorical

Distinct6
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
5
21 
4
10 
<NA>
6 
6
6 
2
4 

Length

Max length4
Median length1
Mean length1.36
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row6

Common Values

ValueCountFrequency (%)
5 21
42.0%
4 10
20.0%
<NA> 6
 
12.0%
6 6
 
12.0%
2 4
 
8.0%
3 3
 
6.0%

Length

2023-12-12T16:42:27.907163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:42:28.010514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 21
42.0%
4 10
20.0%
na 6
 
12.0%
6 6
 
12.0%
2 4
 
8.0%
3 3
 
6.0%

Interactions

2023-12-12T16:42:26.127579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:42:28.077841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
만족도점수개선의견최초등록일시직업구분연령대
만족도점수1.0000.9660.5530.0000.464
개선의견0.9661.0000.8860.8110.812
최초등록일시0.5530.8861.0000.0910.574
직업구분0.0000.8110.0911.0000.675
연령대0.4640.8120.5740.6751.000
2023-12-12T16:42:28.154957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
만족도점수연령대
만족도점수1.0000.182
연령대0.1821.000
2023-12-12T16:42:28.217807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
직업구분만족도점수연령대
직업구분1.0000.0000.307
만족도점수0.0001.0000.182
연령대0.3070.1821.000

Missing values

2023-12-12T16:42:26.280054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:42:26.397416image/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.
2023-12-12T16:42:26.542596image/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

만족도점수개선의견최초등록일시직업구분연령대
0<NA><NA>2020-03-25<NA><NA>
1<NA><NA>2020-02-24<NA><NA>
2<NA><NA>2020-01-23<NA><NA>
3<NA><NA>2019-12-07<NA><NA>
41e2019-11-3076
51e2019-11-3076
61e2019-11-3076
71e2019-11-3076
8<NA><NA>2019-11-07<NA><NA>
9<NA><NA>2019-11-06<NA><NA>
만족도점수개선의견최초등록일시직업구분연령대
404좋아요2019-03-0775
415좋아요.2019-03-0745
424dd2019-03-0773
43502019-03-0645
443모바일버전에서는 알림서비스신청 불가2019-03-0645
453기타2019-03-0675
464자격증에 격을살리자2019-03-0625
474좋아요2019-03-0662
484..2019-03-0644
494없음2019-03-0646

Duplicate rows

Most frequently occurring

만족도점수개선의견최초등록일시직업구분연령대# duplicates
01e2019-11-30764
14좋아요2019-03-07752