Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory78.4 B

Variable types

Numeric2
Categorical4
Text2
DateTime1

Dataset

Description전통시장에 대한 화재안전 등급 분류 현황(시장명, 주소, 점포수, 점검일자 등)
Author대전광역시
URLhttps://www.data.go.kr/data/15077544/fileData.do

Alerts

시도명 has constant value ""Constant
연번 is highly overall correlated with 소방서명High correlation
소방서명 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
등록여부 is highly overall correlated with 소방서명High correlation
등록여부 is highly imbalanced (78.9%)Imbalance
연번 has unique valuesUnique
시장명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:01:44.007285
Analysis finished2023-12-12 11:01:45.491259
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T20:01:45.609436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2023-12-12T20:01:45.880096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
대전
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전 30
100.0%

Length

2023-12-12T20:01:46.088819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:01:46.275355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전 30
100.0%

소방서명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
동부
17 
서부
5 
대덕
4 
둔산
2 
유성
2 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동부 17
56.7%
서부 5
 
16.7%
대덕 4
 
13.3%
둔산 2
 
6.7%
유성 2
 
6.7%

Length

2023-12-12T20:01:46.946358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:01:47.098188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동부 17
56.7%
서부 5
 
16.7%
대덕 4
 
13.3%
둔산 2
 
6.7%
유성 2
 
6.7%

시장명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-12T20:01:47.384529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.8
Min length4

Characters and Unicode

Total characters144
Distinct characters48
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row대전도매시장
2nd row자유도매시장
3rd row중앙도매시장
4th row가양시장
5th row문창시장
ValueCountFrequency (%)
대전도매시장 1
 
3.3%
자유도매시장 1
 
3.3%
도마시장 1
 
3.3%
오류시장 1
 
3.3%
산성시장 1
 
3.3%
유천시장 1
 
3.3%
용두시장 1
 
3.3%
송강시장 1
 
3.3%
신탄전통시장 1
 
3.3%
송촌시장 1
 
3.3%
Other values (20) 20
66.7%
2023-12-12T20:01:47.963799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 28
19.4%
장 28
19.4%
중 7
 
4.9%
도 6
 
4.2%
앙 6
 
4.2%
전 6
 
4.2%
가 5
 
3.5%
매 4
 
2.8%
통 3
 
2.1%
유 3
 
2.1%
Other values (38) 48
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 144
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 28
19.4%
장 28
19.4%
중 7
 
4.9%
도 6
 
4.2%
앙 6
 
4.2%
전 6
 
4.2%
가 5
 
3.5%
매 4
 
2.8%
통 3
 
2.1%
유 3
 
2.1%
Other values (38) 48
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 144
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 28
19.4%
장 28
19.4%
중 7
 
4.9%
도 6
 
4.2%
앙 6
 
4.2%
전 6
 
4.2%
가 5
 
3.5%
매 4
 
2.8%
통 3
 
2.1%
유 3
 
2.1%
Other values (38) 48
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 144
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 28
19.4%
장 28
19.4%
중 7
 
4.9%
도 6
 
4.2%
앙 6
 
4.2%
전 6
 
4.2%
가 5
 
3.5%
매 4
 
2.8%
통 3
 
2.1%
유 3
 
2.1%
Other values (38) 48
33.3%

주소
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-12T20:01:48.389314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32.5
Mean length29.866667
Min length20

Characters and Unicode

Total characters896
Distinct characters75
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)93.3%

Sample

1st row대전광역시 동구 대전로785번길 10 (중동 76-12)
2nd row대전광역시 동구 중앙로200번길 40 (원동 64-1)
3rd row대전광역시 동구 중앙로200번길 73 (원동 38-1)
4th row대전광역시 동구 매봉로 18 (가양동 434)
5th row대전광역시 중구 보문로20번길 22 (문창동 116-8)
ValueCountFrequency (%)
대전광역시 30
 
16.9%
동구 15
 
8.4%
중구 7
 
3.9%
원동 6
 
3.4%
중앙로200번길 4
 
2.2%
대덕구 4
 
2.2%
중동 3
 
1.7%
65-7 2
 
1.1%
중교로 2
 
1.1%
유성구 2
 
1.1%
Other values (97) 103
57.9%
2023-12-12T20:01:49.009694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
 
16.5%
동 46
 
5.1%
1 45
 
5.0%
대 42
 
4.7%
전 34
 
3.8%
구 31
 
3.5%
- 30
 
3.3%
광 30
 
3.3%
역 30
 
3.3%
시 30
 
3.3%
Other values (65) 430
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 427
47.7%
Decimal Number 233
26.0%
Space Separator 148
 
16.5%
Dash Punctuation 30
 
3.3%
Open Punctuation 29
 
3.2%
Close Punctuation 29
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 46
10.8%
대 42
 
9.8%
전 34
 
8.0%
구 31
 
7.3%
광 30
 
7.0%
역 30
 
7.0%
시 30
 
7.0%
로 29
 
6.8%
길 21
 
4.9%
번 20
 
4.7%
Other values (51) 114
26.7%
Decimal Number
ValueCountFrequency (%)
1 45
19.3%
2 27
11.6%
3 26
11.2%
0 24
10.3%
4 22
9.4%
8 22
9.4%
7 20
8.6%
6 20
8.6%
5 15
 
6.4%
9 12
 
5.2%
Space Separator
ValueCountFrequency (%)
148
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 469
52.3%
Hangul 427
47.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 46
10.8%
대 42
 
9.8%
전 34
 
8.0%
구 31
 
7.3%
광 30
 
7.0%
역 30
 
7.0%
시 30
 
7.0%
로 29
 
6.8%
길 21
 
4.9%
번 20
 
4.7%
Other values (51) 114
26.7%
Common
ValueCountFrequency (%)
148
31.6%
1 45
 
9.6%
- 30
 
6.4%
( 29
 
6.2%
) 29
 
6.2%
2 27
 
5.8%
3 26
 
5.5%
0 24
 
5.1%
4 22
 
4.7%
8 22
 
4.7%
Other values (4) 67
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 469
52.3%
Hangul 427
47.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
31.6%
1 45
 
9.6%
- 30
 
6.4%
( 29
 
6.2%
) 29
 
6.2%
2 27
 
5.8%
3 26
 
5.5%
0 24
 
5.1%
4 22
 
4.7%
8 22
 
4.7%
Other values (4) 67
14.3%
Hangul
ValueCountFrequency (%)
동 46
10.8%
대 42
 
9.8%
전 34
 
8.0%
구 31
 
7.3%
광 30
 
7.0%
역 30
 
7.0%
시 30
 
7.0%
로 29
 
6.8%
길 21
 
4.9%
번 20
 
4.7%
Other values (51) 114
26.7%

점포수(개소)
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.36667
Minimum12
Maximum515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T20:01:49.183142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile27.05
Q155.25
median75
Q3121.75
95-th percentile202.75
Maximum515
Range503
Interquartile range (IQR)66.5

Descriptive statistics

Standard deviation93.127826
Coefficient of variation (CV)0.91872239
Kurtosis13.432239
Mean101.36667
Median Absolute Deviation (MAD)32.5
Skewness3.2417052
Sum3041
Variance8672.792
MonotonicityNot monotonic
2023-12-12T20:01:49.363974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
77 3
 
10.0%
41 1
 
3.3%
189 1
 
3.3%
133 1
 
3.3%
515 1
 
3.3%
46 1
 
3.3%
71 1
 
3.3%
66 1
 
3.3%
54 1
 
3.3%
62 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
12 1
3.3%
23 1
3.3%
32 1
3.3%
41 1
3.3%
42 1
3.3%
43 1
3.3%
46 1
3.3%
54 1
3.3%
59 1
3.3%
60 1
3.3%
ValueCountFrequency (%)
515 1
3.3%
214 1
3.3%
189 1
3.3%
172 1
3.3%
170 1
3.3%
147 1
3.3%
133 1
3.3%
122 1
3.3%
121 1
3.3%
110 1
3.3%

점검일자
Date

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-06-21 00:00:00
Maximum2017-09-25 00:00:00
2023-12-12T20:01:49.521055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:01:49.677686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

분류등급
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
B
14 
C
11 
D
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB
2nd rowC
3rd rowB
4th rowC
5th rowC

Common Values

ValueCountFrequency (%)
B 14
46.7%
C 11
36.7%
D 5
 
16.7%

Length

2023-12-12T20:01:49.842093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:01:49.976418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b 14
46.7%
c 11
36.7%
d 5
 
16.7%

등록여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
등록
29 
미등록
 
1

Length

Max length3
Median length2
Mean length2.0333333
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
등록 29
96.7%
미등록 1
 
3.3%

Length

2023-12-12T20:01:50.125713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:01:50.284730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록 29
96.7%
미등록 1
 
3.3%

Interactions

2023-12-12T20:01:44.853921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:01:44.551126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:01:44.995018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:01:44.694887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:01:50.388043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소방서명시장명주소점포수(개소)점검일자분류등급등록여부
연번1.0000.8981.0000.9270.0000.8050.2120.159
소방서명0.8981.0001.0001.0000.1750.8680.4060.524
시장명1.0001.0001.0001.0001.0001.0001.0001.000
주소0.9271.0001.0001.0000.9080.9740.0001.000
점포수(개소)0.0000.1751.0000.9081.0000.9840.4950.365
점검일자0.8050.8681.0000.9740.9841.0000.7511.000
분류등급0.2120.4061.0000.0000.4950.7511.0000.000
등록여부0.1590.5241.0001.0000.3651.0000.0001.000
2023-12-12T20:01:50.550683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소방서명등록여부분류등급
소방서명1.0000.5980.317
등록여부0.5981.0000.000
분류등급0.3170.0001.000
2023-12-12T20:01:50.682557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번점포수(개소)소방서명분류등급등록여부
연번1.0000.1730.5160.0380.000
점포수(개소)0.1731.0000.0840.2080.231
소방서명0.5160.0841.0000.3170.598
분류등급0.0380.2080.3171.0000.000
등록여부0.0000.2310.5980.0001.000

Missing values

2023-12-12T20:01:45.201472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:01:45.408584image/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

연번시도명소방서명시장명주소점포수(개소)점검일자분류등급등록여부
01대전동부대전도매시장대전광역시 동구 대전로785번길 10 (중동 76-12)412017-06-21B등록
12대전동부자유도매시장대전광역시 동구 중앙로200번길 40 (원동 64-1)722017-06-21C등록
23대전동부중앙도매시장대전광역시 동구 중앙로200번길 73 (원동 38-1)772017-07-07B등록
34대전동부가양시장대전광역시 동구 매봉로 18 (가양동 434)122017-07-07C등록
45대전동부문창시장대전광역시 중구 보문로20번길 22 (문창동 116-8)2142017-07-20C등록
56대전동부역전시장대전광역시 동구 중교로 119 (원동 65-7)832017-07-24D등록
67대전동부용운시장대전광역시 동구 용운로164번길 9 (용운동 349-1)422017-07-25C등록
78대전동부중앙메가프라자대전광역시 동구 중앙로200번길 99 (원동 42-1)1102017-07-31B등록
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