Overview

Dataset statistics

Number of variables9
Number of observations137
Missing cells5
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.0 KiB
Average record size in memory74.9 B

Variable types

Numeric2
Categorical4
DateTime2
Text1

Dataset

Description광주광역시 빛고을국민안전체험관에서 운영하는 이동체험차(안전체험교실) 현황 데이터를 제공합니다.-체험명 : 광주광역시 소방안전 이동교육-차량정보 : 성진소방이동안전체험차량, 성진하이텍소방이동안전체험차량-체험내용 : 지진안전, 화재대피방법 체험 등
Author광주광역시
URLhttps://www.data.go.kr/data/15094122/fileData.do

Alerts

구분 is highly overall correlated with 시간 and 1 other fieldsHigh correlation
주관 is highly overall correlated with 인원 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 유형High correlation
인원 is highly overall correlated with 주관High correlation
유형 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
시간 is highly overall correlated with 유형 and 2 other fieldsHigh correlation
주관 is highly imbalanced (92.1%)Imbalance

Reproduction

Analysis started2024-03-14 20:49:13.998572
Analysis finished2024-03-14 20:49:16.961288
Duration2.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct136
Distinct (%)100.0%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean68.5
Minimum1
Maximum136
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-15T05:49:17.192700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.75
Q134.75
median68.5
Q3102.25
95-th percentile129.25
Maximum136
Range135
Interquartile range (IQR)67.5

Descriptive statistics

Standard deviation39.403892
Coefficient of variation (CV)0.57523929
Kurtosis-1.2
Mean68.5
Median Absolute Deviation (MAD)34
Skewness0
Sum9316
Variance1552.6667
MonotonicityStrictly increasing
2024-03-15T05:49:17.535911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
95 1
 
0.7%
89 1
 
0.7%
90 1
 
0.7%
91 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
96 1
 
0.7%
70 1
 
0.7%
Other values (126) 126
92.0%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%
130 1
0.7%
129 1
0.7%
128 1
0.7%
127 1
0.7%

유형
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
내방교육
89 
방문교육
47 
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
내방교육 89
65.0%
방문교육 47
34.3%
<NA> 1
 
0.7%

Length

2024-03-15T05:49:17.799879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:49:18.094896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
내방교육 89
65.0%
방문교육 47
34.3%
na 1
 
0.7%

일자
Date

Distinct127
Distinct (%)93.4%
Missing1
Missing (%)0.7%
Memory size1.2 KiB
Minimum2022-01-13 00:00:00
Maximum2023-11-22 00:00:00
2024-03-15T05:49:18.402935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:49:18.660802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시간
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
10:00-12:30
35 
09:30-12:30
33 
09:00-13:00
8 
11:00-12:00
6 
11:20-12:20
 
4
Other values (32)
51 

Length

Max length11
Median length11
Mean length10.919708
Min length4

Unique

Unique19 ?
Unique (%)13.9%

Sample

1st row09:00-11:00
2nd row09:00-11:00
3rd row09:00-11:00
4th row14:00-15:00
5th row11:00-14:30

Common Values

ValueCountFrequency (%)
10:00-12:30 35
25.5%
09:30-12:30 33
24.1%
09:00-13:00 8
 
5.8%
11:00-12:00 6
 
4.4%
11:20-12:20 4
 
2.9%
10:00-12:00 4
 
2.9%
09:00-11:00 3
 
2.2%
09:00-12:00 3
 
2.2%
10:0~12:00 3
 
2.2%
10:00-11:30 3
 
2.2%
Other values (27) 35
25.5%

Length

2024-03-15T05:49:18.939016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10:00-12:30 35
25.5%
09:30-12:30 33
24.1%
09:00-13:00 8
 
5.8%
11:00-12:00 6
 
4.4%
11:20-12:20 4
 
2.9%
10:00-12:00 4
 
2.9%
09:00-11:00 3
 
2.2%
09:00-12:00 3
 
2.2%
10:0~12:00 3
 
2.2%
10:00-11:30 3
 
2.2%
Other values (27) 35
25.5%

대상
Text

Distinct114
Distinct (%)83.8%
Missing1
Missing (%)0.7%
Memory size1.2 KiB
2024-03-15T05:49:19.853084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length27
Mean length9.5955882
Min length2

Characters and Unicode

Total characters1305
Distinct characters207
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)75.0%

Sample

1st row체험관 방문 체험객
2nd row체험관 방문 체험객
3rd row체험관 방문 체험객
4th row체험관 방문 체험객
5th row체험관 방문 체험객
ValueCountFrequency (%)
리더스유치원 9
 
4.5%
체험관 8
 
4.0%
방문 8
 
4.0%
체험객 7
 
3.5%
신미라유치원 6
 
3.0%
병설유치원 5
 
2.5%
등 5
 
2.5%
동운어린이집 3
 
1.5%
선창초등학교 3
 
1.5%
별아이유치원 3
 
1.5%
Other values (126) 142
71.4%
2024-03-15T05:49:21.186350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 80
 
6.1%
유 77
 
5.9%
치 75
 
5.7%
65
 
5.0%
이 55
 
4.2%
어 46
 
3.5%
학 45
 
3.4%
린 44
 
3.4%
집 42
 
3.2%
등 41
 
3.1%
Other values (197) 735
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1179
90.3%
Space Separator 65
 
5.0%
Other Punctuation 38
 
2.9%
Decimal Number 14
 
1.1%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 80
 
6.8%
유 77
 
6.5%
치 75
 
6.4%
이 55
 
4.7%
어 46
 
3.9%
학 45
 
3.8%
린 44
 
3.7%
집 42
 
3.6%
등 41
 
3.5%
초 39
 
3.3%
Other values (185) 635
53.9%
Decimal Number
ValueCountFrequency (%)
1 8
57.1%
9 2
 
14.3%
3 1
 
7.1%
5 1
 
7.1%
2 1
 
7.1%
4 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
W 1
33.3%
Space Separator
ValueCountFrequency (%)
65
100.0%
Other Punctuation
ValueCountFrequency (%)
, 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1179
90.3%
Common 123
 
9.4%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 80
 
6.8%
유 77
 
6.5%
치 75
 
6.4%
이 55
 
4.7%
어 46
 
3.9%
학 45
 
3.8%
린 44
 
3.7%
집 42
 
3.6%
등 41
 
3.5%
초 39
 
3.3%
Other values (185) 635
53.9%
Common
ValueCountFrequency (%)
65
52.8%
, 38
30.9%
1 8
 
6.5%
( 3
 
2.4%
) 3
 
2.4%
9 2
 
1.6%
3 1
 
0.8%
5 1
 
0.8%
2 1
 
0.8%
4 1
 
0.8%
Latin
ValueCountFrequency (%)
B 2
66.7%
W 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1179
90.3%
ASCII 126
 
9.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 80
 
6.8%
유 77
 
6.5%
치 75
 
6.4%
이 55
 
4.7%
어 46
 
3.9%
학 45
 
3.8%
린 44
 
3.7%
집 42
 
3.6%
등 41
 
3.5%
초 39
 
3.3%
Other values (185) 635
53.9%
ASCII
ValueCountFrequency (%)
65
51.6%
, 38
30.2%
1 8
 
6.3%
( 3
 
2.4%
) 3
 
2.4%
9 2
 
1.6%
B 2
 
1.6%
3 1
 
0.8%
5 1
 
0.8%
2 1
 
0.8%
Other values (2) 2
 
1.6%

인원
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)69.1%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean139.80882
Minimum9
Maximum820
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-15T05:49:21.623023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile22.5
Q170.75
median116
Q3170
95-th percentile310.25
Maximum820
Range811
Interquartile range (IQR)99.25

Descriptive statistics

Standard deviation118.12903
Coefficient of variation (CV)0.84493255
Kurtosis12.634205
Mean139.80882
Median Absolute Deviation (MAD)48
Skewness2.9246085
Sum19014
Variance13954.467
MonotonicityNot monotonic
2024-03-15T05:49:21.919112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 5
 
3.6%
140 4
 
2.9%
80 4
 
2.9%
68 4
 
2.9%
32 3
 
2.2%
170 3
 
2.2%
61 2
 
1.5%
180 2
 
1.5%
212 2
 
1.5%
70 2
 
1.5%
Other values (84) 105
76.6%
ValueCountFrequency (%)
9 1
0.7%
12 1
0.7%
17 2
1.5%
18 1
0.7%
19 1
0.7%
21 1
0.7%
23 2
1.5%
25 2
1.5%
29 1
0.7%
30 1
0.7%
ValueCountFrequency (%)
820 1
0.7%
750 1
0.7%
500 1
0.7%
435 1
0.7%
400 1
0.7%
390 1
0.7%
350 1
0.7%
297 1
0.7%
295 1
0.7%
283 1
0.7%

구분
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
유아, 성인
83 
초등학교, 성인
26 
유아, 초등학교, 성인
13 
유아
 
6
유아, 초등학교
 
3
Other values (4)
 
6

Length

Max length28
Median length6
Mean length6.9489051
Min length2

Unique

Unique3 ?
Unique (%)2.2%

Sample

1st row유아
2nd row유아
3rd row유아
4th row유아, 초등학교
5th row유아, 초등학교

Common Values

ValueCountFrequency (%)
유아, 성인 83
60.6%
초등학교, 성인 26
 
19.0%
유아, 초등학교, 성인 13
 
9.5%
유아 6
 
4.4%
유아, 초등학교 3
 
2.2%
유아 성인 3
 
2.2%
유아, 초등학교, 중학교, 고등학교, 대학교, 성인 1
 
0.7%
유아,초등학교 1
 
0.7%
<NA> 1
 
0.7%

Length

2024-03-15T05:49:22.184052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:49:22.484995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성인 126
44.5%
유아 109
38.5%
초등학교 43
 
15.2%
중학교 1
 
0.4%
고등학교 1
 
0.4%
대학교 1
 
0.4%
유아,초등학교 1
 
0.4%
na 1
 
0.4%

주관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
빛고을국민안전체험관
135 
광주광역시청
 
1
<NA>
 
1

Length

Max length10
Median length10
Mean length9.9270073
Min length4

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
빛고을국민안전체험관 135
98.5%
광주광역시청 1
 
0.7%
<NA> 1
 
0.7%

Length

2024-03-15T05:49:22.840384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:49:23.043560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
빛고을국민안전체험관 135
98.5%
광주광역시청 1
 
0.7%
na 1
 
0.7%

데이터기준일자
Date

Distinct2
Distinct (%)1.5%
Missing1
Missing (%)0.7%
Memory size1.2 KiB
Minimum2022-12-31 00:00:00
Maximum2024-02-14 00:00:00
2024-03-15T05:49:23.186860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:49:23.352238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

Interactions

2024-03-15T05:49:15.184275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:49:14.649820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:49:15.458967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:49:14.916147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:49:23.540897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번유형시간인원구분주관데이터기준일자
연번1.0000.8870.7980.2690.4140.0840.997
유형0.8871.0000.8990.1560.2570.0000.858
시간0.7980.8991.0000.6360.8901.0000.954
인원0.2690.1560.6361.0000.7720.8640.323
구분0.4140.2570.8900.7721.0001.0000.554
주관0.0840.0001.0000.8641.0001.0000.000
데이터기준일자0.9970.8580.9540.3230.5540.0001.000
2024-03-15T05:49:23.825794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분유형시간주관
구분1.0000.1880.5280.977
유형0.1881.0000.6650.000
시간0.5280.6651.0000.864
주관0.9770.0000.8641.000
2024-03-15T05:49:24.107300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번인원유형시간구분주관
연번1.0000.4110.6950.3800.2360.000
인원0.4111.0000.1130.2620.3570.669
유형0.6950.1131.0000.6650.1880.000
시간0.3800.2620.6651.0000.5280.864
구분0.2360.3570.1880.5281.0000.977
주관0.0000.6690.0000.8640.9771.000

Missing values

2024-03-15T05:49:15.946720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:49:16.222393image/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.
2024-03-15T05:49:16.694183image/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

연번유형일자시간대상인원구분주관데이터기준일자
01내방교육2022-01-1309:00-11:00체험관 방문 체험객12유아빛고을국민안전체험관2022-12-31
12내방교육2022-01-1809:00-11:00체험관 방문 체험객17유아빛고을국민안전체험관2022-12-31
23내방교육2022-01-2709:00-11:00체험관 방문 체험객18유아빛고을국민안전체험관2022-12-31
34내방교육2022-02-2214:00-15:00체험관 방문 체험객29유아, 초등학교빛고을국민안전체험관2022-12-31
45내방교육2022-03-0511:00-14:30체험관 방문 체험객52유아, 초등학교빛고을국민안전체험관2022-12-31
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